paulo037/starcoder · Datasets at Hugging Face

max_stars_repo_path stringlengths 4 237	max_stars_repo_name stringlengths 6 117	max_stars_count int64 0 95.2k	id stringlengths 1 7	content stringlengths 12 593k	input_ids sequencelengths 7 549k
text/ko_dictionary.py	mozzihozzi/Custom-Speech-Synthesis-Service-using-Multi-speaker-tacotron	3	77205	etc_dictionary = { '2 30대': '이삼십대', '20~30대': '이삼십대', '20, 30대': '이십대 삼십대', '1+1': '원플러스원', '3에서 6개월인': '3개월에서 육개월인', } english_dictionary = { 'Devsisters': '데브시스터즈', 'track': '트랙', # krbook 'LA': '엘에이', 'LG': '엘지', 'KOREA': '코리아', 'JSA': '제이에스에이', 'PGA': '피지에이', 'GA': '지에이', 'idol': '아이돌', 'KTX': '케이티엑스', 'AC': '에이씨', 'DVD': '디비디', 'US': '유에스', 'CNN': '씨엔엔', 'LPGA': '엘피지에이', 'P': '피', 'L': '엘', 'T': '티', 'B': '비', 'C': '씨', 'BIFF': '비아이에프에프', 'GV': '지비', # JTBC 'IT': '아이티', 'IQ': '아이큐', 'JTBC': '제이티비씨', 'trickle down effect': '트리클 다운 이펙트', 'trickle up effect': '트리클 업 이펙트', 'down': '다운', 'up': '업', 'FCK': '에프씨케이', 'AP': '에이피', 'WHERETHEWILDTHINGSARE': '', 'Rashomon Effect': '', 'O': '오', 'OO': '오오', 'B': '비', 'GDP': '지디피', 'CIPA': '씨아이피에이', 'YS': '와이에스', 'Y': '와이', 'S': '에스', 'JTBC': '제이티비씨', 'PC': '피씨', 'bill': '빌', 'Halmuny': '하모니', ##### 'X': '엑스', 'SNS': '에스엔에스', 'ability': '어빌리티', 'shy': '', 'CCTV': '씨씨티비', 'IT': '아이티', 'the tenth man': '더 텐쓰 맨', #### 'L': '엘', 'PC': '피씨', 'YSDJJPMB': '', ######## 'Content Attitude Timing': '컨텐트 애티튜드 타이밍', 'CAT': '캣', 'IS': '아이에스', 'SNS': '에스엔에스', 'K': '케이', 'Y': '와이', 'KDI': '케이디아이', 'DOC': '디오씨', 'CIA': '씨아이에이', 'PBS': '피비에스', 'D': '디', 'PPropertyPositionPowerPrisonP' 'S': '에스', 'francisco': '프란시스코', 'I': '아이', 'III': '아이아이', ###### 'No joke': '노 조크', 'BBK': '비비케이', 'LA': '엘에이', 'Don': '', 't worry be happy': ' 워리 비 해피', 'NO': '엔오', ##### 'it was our sky': '잇 워즈 아워 스카이', 'it is our sky': '잇 이즈 아워 스카이', #### 'NEIS': '엔이아이에스', ##### 'IMF': '아이엠에프', 'apology': '어폴로지', 'humble': '험블', 'M': '엠', 'Nowhere Man': '노웨어 맨', 'The Tenth Man': '더 텐쓰 맨', 'PBS': '피비에스', 'BBC': '비비씨', 'MRJ': '엠알제이', 'CCTV': '씨씨티비', 'Pick me up': '픽 미 업', 'DNA': '디엔에이', 'UN': '유엔', 'STOP': '스탑', ##### 'PRESS': '프레스', ##### 'not to be': '낫 투비', 'Denial': '디나이얼', 'G': '지', 'IMF': '아이엠에프', 'GDP': '지디피', 'JTBC': '제이티비씨', 'Time flies like an arrow': '타임 플라이즈 라이크 언 애로우', 'DDT': '디디티', 'AI': '에이아이', 'Z': '제트', 'OECD': '오이씨디', 'N': '앤', 'A': '에이', 'MB': '엠비', 'EH': '이에이치', 'IS': '아이에스', 'TV': '티비', 'MIT': '엠아이티', 'KBO': '케이비오', 'I love America': '아이 러브 아메리카', 'SF': '에스에프', 'Q': '큐', 'KFX': '케이에프엑스', 'PM': '피엠', 'Prime Minister': '프라임 미니스터', 'Swordline': '스워드라인', 'TBS': '티비에스', 'DDT': '디디티', 'CS': '씨에스', 'Reflecting Absence': '리플렉팅 앱센스', 'PBS': '피비에스', 'Drum being beaten by everyone': '드럼 빙 비튼 바이 에브리원', 'negative pressure': '네거티브 프레셔', 'F': '에프', 'KIA': '기아', 'FTA': '에프티에이', 'Que sais-je': '', 'UFC': '유에프씨', 'P': '피', 'DJ': '디제이', 'Chaebol': '채벌', 'BBC': '비비씨', 'OECD': '오이씨디', 'BC': '삐씨', 'C': '씨', 'B': '씨', 'KY': '케이와이', 'K': '케이', 'CEO': '씨이오', 'YH': '와이에치', 'IS': '아이에스', 'who are you': '<NAME>', 'Y': '와이', 'The Devils Advocate': '더 데빌즈 어드보카트', 'YS': '와이에스', 'so sorry': '쏘 쏘리', 'Santa': '산타', 'Big Endian': '빅 엔디안', 'Small Endian': '스몰 엔디안', 'Oh Captain My Captain': '오 캡틴 마이 캡틴', 'AIB': '에이아이비', 'K': '케이', 'PBS': '피비에스', }	[ 1, 2992, 29918, 27126, 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main.py	alextremblay962/Hydropinic_System	0	39004	import serial import json import io import time ser = serial.Serial("COM24" , 9600, timeout=2) topic = "hydro/light1" payload = 1 #data = json.dumps({"topic":topic,"payload":payload}) data = "{\"topic\":\"hydro/light1\",\"payload\":1}" data = data.encode() print(data) ser.write(b'A') hello = ser.readline()#.decode("ascii") print(hello)	[ 1, 1053, 7797, 13, 5215, 4390, 13, 5215, 12013, 13, 5215, 29871, 931, 13, 13, 643, 353, 7797, 29889, 9125, 703, 19795, 29906, 29946, 29908, 1919, 29871, 29929, 29953, 29900, 29900, 29892, 11815, 29922, 29906, 29897, 13, 13, 13010, 353, 376, 29882, 11279, 29914, 4366, 29896, 29908, 13, 23813, 353, 29871, 29896, 13, 13, 29937, 1272, 353, 4390, 29889, 29881, 17204, 3319, 29908, 13010, 1115, 13010, 1699, 23813, 1115, 23813, 1800, 13, 1272, 353, 376, 741, 29908, 13010, 16203, 5931, 29882, 11279, 29914, 4366, 29896, 23370, 5931, 23813, 16203, 29896, 5038, 13, 1272, 353, 848, 29889, 12508, 580, 13, 13, 2158, 29898, 1272, 29897, 13, 13, 643, 29889, 3539, 29898, 29890, 29915, 29909, 1495, 13, 13, 13, 12199, 353, 724, 29889, 949, 1220, 580, 29937, 29889, 13808, 703, 294, 18869, 1159, 13, 2158, 29898, 12199, 29897, 2 ]
LintCode/BinarySearch/20191115_binary_search.py	Fabriceli/MachingLearning	0	72340	<filename>LintCode/BinarySearch/20191115_binary_search.py # --coding:utf-8 -- #Reference:******************************************** # @Time : 2019-11-15 11:14 # @Author : <NAME> # @File : 20191115_binary_search.py # @User : liyihao # @Software : PyCharm # @Description: default module binary search #Reference:******************************************** class Solution(): def binary_search_default(self, nums, target): if len(nums) <= 0: return -1 left = 0 right = len(nums) - 1 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: right = mid elif nums[mid] < target: left = mid elif nums[mid] > target: right = mid if nums[right] == target: return right if nums[left] == target: return left return -1 def binary_search_left_edge(self, nums, target): if len(nums) <= 0: return -1 left = 0 # 重点 right = len(nums) - 1 # 重点 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: right = mid elif nums[mid] > target: right = mid elif nums[mid] < target: left = mid if nums[left] == target: return left if nums[right] == target: return right return -1 def binary_search_right_edge(self, nums, target): if len(nums) <= 0: return -1 left = 0 right = len(nums) - 1 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: left = mid elif nums[mid] > target: right = mid elif nums[mid] < target: left = mid if nums[right] == target: return right if nums[left] == target: return left return -1 if __name__ == '__main__': s = Solution() nums = [1, 2] target = 2 print("left edge: " + str(s.binary_search_left_edge(nums, target))) print("right edge: " + str(s.binary_search_right_edge(nums, target)))	[ 1, 529, 9507, 29958, 29931, 524, 3399, 29914, 25196, 7974, 29914, 29906, 29900, 29896, 29929, 29896, 29896, 29896, 29945, 29918, 19541, 29918, 4478, 29889, 2272, 13, 29937, 448, 29930, 29899, 29883, 3689, 29901, 9420, 29899, 29947, 448, 29930, 29899, 13, 29937, 7422, 29901, 7775, 7775, 4189, 2328, 1068, 13, 29937, 732, 2481, 30081, 20246, 29871, 584, 29871, 29906, 29900, 29896, 29929, 29899, 29896, 29896, 29899, 29896, 29945, 29871, 29896, 29896, 29901, 29896, 29946, 13, 29937, 732, 13720, 30081, 29871, 584, 529, 5813, 29958, 13, 29937, 732, 2283, 30081, 20246, 29871, 584, 29871, 29906, 29900, 29896, 29929, 29896, 29896, 29896, 29945, 29918, 19541, 29918, 4478, 29889, 2272, 13, 29937, 732, 2659, 30081, 20246, 29871, 584, 619, 25675, 2350, 29877, 13, 29937, 732, 6295, 14093, 584, 10772, 1451, 2817, 13, 29937, 732, 9868, 29901, 2322, 3883, 7581, 2740, 13, 29937, 7422, 29901, 7775, 7775, 4189, 2328, 1068, 13, 13, 1990, 24380, 7295, 13, 1678, 822, 7581, 29918, 4478, 29918, 4381, 29898, 1311, 29892, 954, 29879, 29892, 3646, 1125, 13, 4706, 565, 7431, 29898, 1949, 29879, 29897, 5277, 29871, 29900, 29901, 13, 9651, 736, 448, 29896, 13, 4706, 2175, 353, 29871, 29900, 13, 4706, 1492, 353, 7431, 29898, 1949, 29879, 29897, 448, 29871, 29896, 13, 4706, 1550, 2175, 718, 29871, 29896, 529, 1492, 29901, 13, 9651, 7145, 353, 938, 29898, 1563, 718, 313, 1266, 448, 2175, 29897, 847, 29871, 29906, 29897, 13, 9651, 565, 954, 29879, 29961, 6563, 29962, 1275, 3646, 29901, 13, 18884, 1492, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 529, 3646, 29901, 13, 18884, 2175, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 1405, 3646, 29901, 13, 18884, 1492, 353, 7145, 13, 4706, 565, 954, 29879, 29961, 1266, 29962, 1275, 3646, 29901, 13, 9651, 736, 1492, 13, 4706, 565, 954, 29879, 29961, 1563, 29962, 1275, 3646, 29901, 13, 9651, 736, 2175, 13, 4706, 736, 448, 29896, 13, 13, 1678, 822, 7581, 29918, 4478, 29918, 1563, 29918, 12864, 29898, 1311, 29892, 954, 29879, 29892, 3646, 1125, 13, 4706, 565, 7431, 29898, 1949, 29879, 29897, 5277, 29871, 29900, 29901, 13, 9651, 736, 448, 29896, 13, 4706, 2175, 353, 29871, 29900, 13, 4706, 396, 29871, 30908, 30940, 13, 4706, 1492, 353, 7431, 29898, 1949, 29879, 29897, 448, 29871, 29896, 13, 4706, 396, 29871, 30908, 30940, 13, 4706, 1550, 2175, 718, 29871, 29896, 529, 1492, 29901, 13, 9651, 7145, 353, 938, 29898, 1563, 718, 313, 1266, 448, 2175, 29897, 847, 29871, 29906, 29897, 13, 9651, 565, 954, 29879, 29961, 6563, 29962, 1275, 3646, 29901, 13, 18884, 1492, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 1405, 3646, 29901, 13, 18884, 1492, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 529, 3646, 29901, 13, 18884, 2175, 353, 7145, 13, 4706, 565, 954, 29879, 29961, 1563, 29962, 1275, 3646, 29901, 13, 9651, 736, 2175, 13, 4706, 565, 954, 29879, 29961, 1266, 29962, 1275, 3646, 29901, 13, 9651, 736, 1492, 13, 4706, 736, 448, 29896, 13, 13, 1678, 822, 7581, 29918, 4478, 29918, 1266, 29918, 12864, 29898, 1311, 29892, 954, 29879, 29892, 3646, 1125, 13, 4706, 565, 7431, 29898, 1949, 29879, 29897, 5277, 29871, 29900, 29901, 13, 9651, 736, 448, 29896, 13, 4706, 2175, 353, 29871, 29900, 13, 4706, 1492, 353, 7431, 29898, 1949, 29879, 29897, 448, 29871, 29896, 13, 4706, 1550, 2175, 718, 29871, 29896, 529, 1492, 29901, 13, 9651, 7145, 353, 938, 29898, 1563, 718, 313, 1266, 448, 2175, 29897, 847, 29871, 29906, 29897, 13, 9651, 565, 954, 29879, 29961, 6563, 29962, 1275, 3646, 29901, 13, 18884, 2175, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 1405, 3646, 29901, 13, 18884, 1492, 353, 7145, 13, 9651, 25342, 954, 29879, 29961, 6563, 29962, 529, 3646, 29901, 13, 18884, 2175, 353, 7145, 13, 4706, 565, 954, 29879, 29961, 1266, 29962, 1275, 3646, 29901, 13, 9651, 736, 1492, 13, 4706, 565, 954, 29879, 29961, 1563, 29962, 1275, 3646, 29901, 13, 9651, 736, 2175, 13, 4706, 736, 448, 29896, 13, 13, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 13, 1678, 269, 353, 24380, 580, 13, 1678, 954, 29879, 353, 518, 29896, 29892, 29871, 29906, 29962, 13, 1678, 3646, 353, 29871, 29906, 13, 1678, 1596, 703, 1563, 7636, 29901, 376, 718, 851, 29898, 29879, 29889, 19541, 29918, 4478, 29918, 1563, 29918, 12864, 29898, 1949, 29879, 29892, 3646, 4961, 13, 1678, 1596, 703, 1266, 7636, 29901, 376, 718, 851, 29898, 29879, 29889, 19541, 29918, 4478, 29918, 1266, 29918, 12864, 29898, 1949, 29879, 29892, 3646, 4961, 13, 2 ]
examples/run_midi.py	lucystrauss/genki-wave	17	186473	""" This script is adopted from [here](https://github.com/atizo/pygame/blob/master/examples/midi.py) # MacOS and Windows Connecting the wave ring as a midi device via bluetooth should work out-of-the-box on Windows and MacOS. # Linux On Linux you might need to re-install `BlueZ` with support for midi as follows. Installation instructions for Linux. Taken from [here](https://tttapa.github.io/Pages/Ubuntu/Software-Installation/BlueZ.html) ``` sudo apt install libudev-dev libical-dev libreadline-dev libdbus-1-dev libasound2-dev sudo apt install build-essential # Use whatever version of BlueZ you want and change accordingly cd /tmp wget https://mirrors.edge.kernel.org/pub/linux/bluetooth/bluez-5.53.tar.xz tar -xf bluez-5.53.tar.xz cd bluez-5.53 ./configure --enable-midi --with-systemdsystemunitdir=/etc/systemd/system make sudo make install sudo apt-get install --reinstall bluez ``` You might need a restart after this step Check if the device is detected: ``` aconnect -lio ``` If pygame raises a warning that `Cannot open shared library libasound_module_conf_pulse.so` it might be searching in the wrong place a way to fix it is to create a symbolic link to where the actual library is to where pygame searches. An example for ubuntu (pygame searches in `/usr/lib/alsa-lib`) sudo ln -s /usr/lib/x86_64-linux-gnu/alsa-lib /usr/lib/alsa-lib Solution adapted from [here](https://stackoverflow.com/questions/57946421/im-trying-to-run-this-code-initialize-pygame-midi-code-but-it-returns-an-error) # noqa """ import functools from enum import IntEnum from typing import Optional, Tuple try: import pygame import pygame.midi except ModuleNotFoundError: raise ModuleNotFoundError( "This script only depends on pygame, not the genki-wave library so please install 'pygame'" "manually to run this script" ) class MidiStatus(IntEnum): DATA = 176 class Movements(IntEnum): PITCH = 16 YAW = 17 ROLL = 18 movements_values = [item.value for item in Movements] def midi_setup_and_teardown(func): """Sets up midi before calling a function and tears it down after running Alternatively `pygame.midi.init()` and `pygame.midi.quit()` can be called at the beginning and end of each function manually """ @functools.wraps(func) def wrapper(args, kwargs): pygame.midi.init() results = func(args, **kwargs) pygame.midi.quit() return results return wrapper @midi_setup_and_teardown def print_device_info(): """Prints all midi devices that were found""" for i in range(pygame.midi.get_count()): interf, name, is_input, output, opened = pygame.midi.get_device_info(i) in_out = "" if is_input: in_out = "(input)" if output: in_out = "(output)" print(f"{i}: interface {interf}, name {name}, opened {opened} {in_out}") @midi_setup_and_teardown def wave_input_device_info() -> Optional[Tuple[int, str]]: """Automatically find input `Wave` input device""" result = None for i in range(pygame.midi.get_count()): interf, name, is_input, output, opened = pygame.midi.get_device_info(i) name_decoded = name.decode() if is_input and "Wave" in name_decoded: result = i, name_decoded return result @midi_setup_and_teardown def input_main(device_id): pygame.init() # Define our input device input_midi = pygame.midi.Input(device_id) pygame.display.set_mode((1, 1)) going = True print_vals_results = ["", "", ""] while going: for event in pygame.event.get(): if event.type in [pygame.QUIT]: going = False if event.type in [pygame.KEYDOWN]: # Program will stop if any button is pressed going = False if event.type in [pygame.midi.MIDIIN, pygame.USEREVENT]: print(event) # Check if there is any data in the buffer of the midi-device. If not, continue with the loop if not input_midi.poll(): continue # Read all the data from the midi buffer (max_size=1024) midi_events = input_midi.read(1024) midi_events = pygame.midi.midis2events(midi_events, input_midi.device_id) # 3 different functions to use. Uncomment different ones to try out # post_custom_events(midi_events) # post_midi_events(midi_events, Movements.ROLL) print_vals_results = print_values(midi_events, print_vals_results) del input_midi def print_values(midi_events, previous_vals: list) -> list: """Prints a 'data' midi event i.e. where there is information sent about roll/pitch/yaw If an event of a certain type is not found, prints the last value for that event """ s = previous_vals for m_e in midi_events: if m_e.status == MidiStatus.DATA and m_e.data1 in movements_values: s = [m_e.data2 if m_e.data1 == val else prev_val for prev_val, val in zip(previous_vals, movements_values)] print(f"P: {s[0]:>3}, Y: {s[1]:>3}, R: {s[2]:>3}") return s def post_custom_events(midi_events): """Only print certain events""" for m_e in midi_events: if m_e.status == MidiStatus.DATA and m_e.data1 == Movements.YAW: if m_e.data2 > 100: pygame.event.post(pygame.event.Event(pygame.USEREVENT, {"val": "down"})) if m_e.data2 < 30: 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yang_et_al/run_tasks.py	wagner-group/geoadex	4	25287	import os import logging import json from nnattack.variables import auto_var, get_file_name from params import ( compare_attacks, compare_defense, #compare_nns, nn_k1_robustness, nn_k3_robustness, nn_k1_approx_robustness_figs, dt_robustness_figs, rf_robustness_figs, nn_k1_robustness_figs, nn_k3_robustness_figs, dt_robustness, rf_robustness, mlp_ap_robustness, mlp_at_robustness, lr_ap_robustness, lr_at_robustness, nn1_def, nn3_def, dt_def, rf_def, lr_def, mlp_def, ) from main import eps_accuracy logging.basicConfig(level=logging.DEBUG) DEBUG = True if os.environ.get('DEBUG', False) else False def main(): experiments = [ compare_attacks(), compare_defense(), #nn_k1_robustness_figs(), #nn_k3_robustness_figs(), #rf_robustness_figs(), #dt_robustness_figs(), dt_robustness(), rf_robustness(), nn_k3_robustness(), nn_k1_robustness(), #mlp_ap_robustness(), #mlp_at_robustness(), #lr_ap_robustness(), #lr_at_robustness(), #nn1_def(), #nn3_def(), #dt_def(), #rf_def(), #lr_def(), #mlp_def(), ] grid_params = [] for exp in experiments: exp_fn, _, grid_param, run_param = exp() if isinstance(grid_param, list): grid_params.extend(grid_param) else: grid_params.append(grid_param) if DEBUG: run_param['n_jobs'] = 1 run_param['allow_failure'] = False else: run_param['n_jobs'] = 4 run_param['allow_failure'] = True auto_var.run_grid_params(exp_fn, grid_params, **run_param) #auto_var.run_grid_params(delete_file, grid_params, n_jobs=1, # with_hook=False, allow_failure=False) #auto_var.run_grid_params(celery_run, grid_params, n_jobs=1, # allow_failure=False) #auto_var.run_grid_params(temp_fix, grid_params, n_jobs=6, # allow_failure=False, with_hook=False) def delete_file(auto_var): os.unlink(get_file_name(auto_var) + '.json') def celery_run(auto_var): run_exp.delay(auto_var.var_value) from main import set_random_seed import numpy as np from sklearn.preprocessing import OneHotEncoder, MinMaxScaler def temp_fix(auto_var): file_name = get_file_name(auto_var) print(file_name) if os.path.exists("%s.json" % file_name): with open("%s.json" % file_name, "r") as f: ret = json.load(f) if "tst_score" in ret: return else: return random_state = set_random_seed(auto_var) ord = auto_var.get_var("ord") X, y, eps_list = auto_var.get_var("dataset") idxs = np.arange(len(X)) random_state.shuffle(idxs) trnX, tstX, trny, tsty = X[idxs[:-200]], X[idxs[-200:]], y[idxs[:-200]], y[idxs[-200:]] scaler = MinMaxScaler() trnX = scaler.fit_transform(trnX) tstX = scaler.transform(tstX) lbl_enc = OneHotEncoder(categories=[np.sort(np.unique(y))], sparse=False) #lbl_enc = OneHotEncoder(sparse=False) lbl_enc.fit(trny.reshape(-1, 1)) auto_var.set_intermidiate_variable("lbl_enc", lbl_enc) results = [] auto_var.set_intermidiate_variable("trnX", trnX) auto_var.set_intermidiate_variable("trny", trny) model_name = auto_var.get_variable_value("model") attack_name = auto_var.get_variable_value("attack") if 'adv_rf' in model_name: pre_model = auto_var.get_var_with_argument('model', model_name[4:]) pre_model.fit(trnX, trny) if 'blackbox' in attack_name: auto_var.set_intermidiate_variable("model", pre_model) elif 'adv_nn' in model_name and 'blackbox' in attack_name: pre_model = auto_var.get_var_with_argument('model', model_name[4:]) pre_model.fit(trnX, trny) auto_var.set_intermidiate_variable("model", pre_model) model = auto_var.get_var("model") auto_var.set_intermidiate_variable("model", model) model.fit(trnX, trny) pred = model.predict(tstX) ori_tstX, ori_tsty = tstX, tsty # len = 200 idxs = np.where(pred == tsty)[0] random_state.shuffle(idxs) augX = None if ('adv' in model_name) or ('advPruning' in model_name) or ('robustv2' in model_name): assert hasattr(model, 'augX') auto_var.set_intermidiate_variable("trnX", model.augX) auto_var.set_intermidiate_variable("trny", model.augy) augX, augy = model.augX, model.augy ret['tst_score'] = (model.predict(ori_tstX) == ori_tsty).mean() with open("%s.json" % file_name, "w") as f: 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docs/examples/lmgtfy_bot.py	AidanWelch/praw	1	196334	from urllib.parse import quote_plus import praw QUESTIONS = ["what is", "who is", "what are"] REPLY_TEMPLATE = "[Let me google that for you](https://lmgtfy.com/?q={})" def main(): reddit = praw.Reddit( user_agent="LMGTFY (by u/USERNAME)", client_id="CLIENT_ID", client_secret="CLIENT_SECRET", username="USERNAME", password="PASSWORD", ) subreddit = reddit.subreddit("AskReddit") for submission in subreddit.stream.submissions(): process_submission(submission) def process_submission(submission): # Ignore titles with more than 10 words as they probably are not simple questions. if len(submission.title.split()) > 10: return normalized_title = submission.title.lower() for question_phrase in QUESTIONS: if question_phrase in normalized_title: url_title = quote_plus(submission.title) reply_text = REPLY_TEMPLATE.format(url_title) print(f"Replying to: {submission.title}") submission.reply(reply_text) # A reply has been made so do not attempt to match other phrases. break if __name__ == "__main__": main()	[ 1, 515, 3142, 1982, 29889, 5510, 1053, 14978, 29918, 11242, 13, 13, 5215, 20467, 13, 13, 14130, 27946, 353, 6796, 5816, 338, 613, 376, 15970, 338, 613, 376, 5816, 526, 3108, 13, 1525, 7390, 29979, 29918, 4330, 3580, 29931, 3040, 353, 14704, 12024, 592, 5386, 393, 363, 366, 850, 991, 597, 21457, 4141, 29888, 29891, 29889, 510, 13401, 29939, 3790, 1800, 29908, 13, 13, 13, 1753, 1667, 7295, 13, 1678, 337, 1289, 277, 353, 20467, 29889, 9039, 27423, 29898, 13, 4706, 1404, 29918, 14748, 543, 26369, 29954, 8969, 29979, 313, 1609, 318, 29914, 11889, 5813, 19123, 13, 4706, 3132, 29918, 333, 543, 27205, 3919, 29918, 1367, 613, 13, 4706, 3132, 29918, 19024, 543, 27205, 3919, 29918, 1660, 22245, 29911, 613, 13, 4706, 8952, 543, 11889, 5813, 613, 13, 4706, 4800, 543, 25711, 17013, 613, 13, 1678, 1723, 13, 13, 1678, 1014, 1127, 27423, 353, 337, 1289, 277, 29889, 1491, 1127, 27423, 703, 29909, 808, 9039, 27423, 1159, 13, 1678, 363, 29240, 297, 1014, 1127, 27423, 29889, 5461, 29889, 1491, 29885, 6847, 7295, 13, 4706, 1889, 29918, 1491, 6737, 29898, 1491, 6737, 29897, 13, 13, 13, 1753, 1889, 29918, 1491, 6737, 29898, 1491, 6737, 1125, 13, 1678, 396, 18076, 487, 17735, 411, 901, 1135, 29871, 29896, 29900, 3838, 408, 896, 3117, 526, 451, 2560, 5155, 29889, 13, 1678, 565, 7431, 29898, 1491, 6737, 29889, 3257, 29889, 5451, 3101, 1405, 29871, 29896, 29900, 29901, 13, 4706, 736, 13, 13, 1678, 4226, 1891, 29918, 3257, 353, 29240, 29889, 3257, 29889, 13609, 580, 13, 1678, 363, 1139, 29918, 24588, 559, 297, 660, 4462, 1254, 27946, 29901, 13, 4706, 565, 1139, 29918, 24588, 559, 297, 4226, 1891, 29918, 3257, 29901, 13, 9651, 3142, 29918, 3257, 353, 14978, 29918, 11242, 29898, 1491, 6737, 29889, 3257, 29897, 13, 9651, 8908, 29918, 726, 353, 5195, 7390, 29979, 29918, 4330, 3580, 29931, 3040, 29889, 4830, 29898, 2271, 29918, 3257, 29897, 13, 9651, 1596, 29898, 29888, 29908, 5612, 5890, 304, 29901, 426, 1491, 6737, 29889, 3257, 27195, 13, 9651, 29240, 29889, 3445, 368, 29898, 3445, 368, 29918, 726, 29897, 13, 9651, 396, 319, 8908, 756, 1063, 1754, 577, 437, 451, 4218, 304, 1993, 916, 12216, 2129, 29889, 13, 9651, 2867, 13, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 1678, 1667, 580, 13, 2 ]
timm/models/visformer.py	merskiZ/pytorch-image-models	1	68658	<reponame>merskiZ/pytorch-image-models """ Visformer Paper: Visformer: The Vision-friendly Transformer - https://arxiv.org/abs/2104.12533 From original at https://github.com/danczs/Visformer """ from copy import deepcopy import torch import torch.nn as nn import torch.nn.functional as F from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from .helpers import build_model_with_cfg, overlay_external_default_cfg from .layers import to_2tuple, trunc_normal_, DropPath, PatchEmbed, LayerNorm2d, create_classifier from .registry import register_model __all__ = ['Visformer'] def _cfg(url='', kwargs): return { 'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': None, 'crop_pct': .9, 'interpolation': 'bicubic', 'fixed_input_size': True, 'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD, 'first_conv': 'stem.0', 'classifier': 'head', kwargs } default_cfgs = dict( visformer_tiny=_cfg(), visformer_small=_cfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vt3p-weights/visformer_small-839e1f5b.pth' ), ) class SpatialMlp(nn.Module): def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0., group=8, spatial_conv=False): super().__init__() out_features = out_features or in_features hidden_features = hidden_features or in_features self.in_features = in_features self.out_features = out_features self.spatial_conv = spatial_conv if self.spatial_conv: if group < 2: # net setting hidden_features = in_features * 5 // 6 else: hidden_features = in_features * 2 self.hidden_features = hidden_features self.group = group self.drop = nn.Dropout(drop) self.conv1 = nn.Conv2d(in_features, hidden_features, 1, stride=1, padding=0, bias=False) self.act1 = act_layer() if self.spatial_conv: self.conv2 = nn.Conv2d( hidden_features, hidden_features, 3, stride=1, padding=1, groups=self.group, bias=False) self.act2 = act_layer() else: self.conv2 = None self.act2 = None self.conv3 = nn.Conv2d(hidden_features, out_features, 1, stride=1, padding=0, bias=False) def forward(self, x): x = self.conv1(x) x = self.act1(x) x = self.drop(x) if self.conv2 is not None: x = self.conv2(x) x = self.act2(x) x = self.conv3(x) x = self.drop(x) return x class Attention(nn.Module): def __init__(self, dim, num_heads=8, head_dim_ratio=1., attn_drop=0., proj_drop=0.): super().__init__() self.dim = dim self.num_heads = num_heads head_dim = round(dim // num_heads * head_dim_ratio) self.head_dim = head_dim self.scale = head_dim ** -0.5 self.qkv = nn.Conv2d(dim, head_dim * num_heads * 3, 1, stride=1, padding=0, bias=False) self.attn_drop = nn.Dropout(attn_drop) self.proj = nn.Conv2d(self.head_dim * self.num_heads, dim, 1, stride=1, padding=0, bias=False) self.proj_drop = nn.Dropout(proj_drop) def forward(self, x): B, C, H, W = x.shape x = self.qkv(x).reshape(B, 3, self.num_heads, self.head_dim, -1).permute(1, 0, 2, 4, 3) q, k, v = x[0], x[1], x[2] attn = (q @ k.transpose(-2, -1)) * self.scale attn = attn.softmax(dim=-1) attn = self.attn_drop(attn) x = attn @ v x = x.permute(0, 1, 3, 2).reshape(B, -1, H, W) x = self.proj(x) x = self.proj_drop(x) return x class Block(nn.Module): def __init__(self, dim, num_heads, head_dim_ratio=1., mlp_ratio=4., drop=0., attn_drop=0., drop_path=0., act_layer=nn.GELU, norm_layer=LayerNorm2d, group=8, attn_disabled=False, spatial_conv=False): super().__init__() self.spatial_conv = spatial_conv self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity() if attn_disabled: self.norm1 = None self.attn = None else: self.norm1 = norm_layer(dim) self.attn = Attention( dim, num_heads=num_heads, head_dim_ratio=head_dim_ratio, attn_drop=attn_drop, proj_drop=drop) self.norm2 = norm_layer(dim) mlp_hidden_dim = int(dim * mlp_ratio) self.mlp = SpatialMlp( in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop, group=group, spatial_conv=spatial_conv) # new setting def forward(self, x): if self.attn is not None: x = x + self.drop_path(self.attn(self.norm1(x))) x = x + self.drop_path(self.mlp(self.norm2(x))) return x class Visformer(nn.Module): def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classes=1000, init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., drop_rate=0., attn_drop_rate=0., drop_path_rate=0., norm_layer=LayerNorm2d, attn_stage='111', pos_embed=True, spatial_conv='111', vit_stem=False, group=8, global_pool='avg', conv_init=False, embed_norm=None): super().__init__() img_size = to_2tuple(img_size) self.num_classes = num_classes self.embed_dim = embed_dim self.init_channels = init_channels self.img_size = img_size self.vit_stem = vit_stem self.conv_init = conv_init if isinstance(depth, (list, tuple)): self.stage_num1, self.stage_num2, self.stage_num3 = depth depth = sum(depth) else: self.stage_num1 = self.stage_num3 = depth // 3 self.stage_num2 = depth - self.stage_num1 - self.stage_num3 self.pos_embed = pos_embed dpr = [x.item() for x in torch.linspace(0, drop_path_rate, depth)] # stage 1 if self.vit_stem: self.stem = None self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size, in_chans=in_chans, embed_dim=embed_dim, norm_layer=embed_norm, flatten=False) img_size = [x // 16 for x in img_size] else: if self.init_channels is None: self.stem = None self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size // 2, in_chans=in_chans, embed_dim=embed_dim // 2, norm_layer=embed_norm, flatten=False) img_size = [x // 8 for x in img_size] else: self.stem = nn.Sequential( nn.Conv2d(in_chans, self.init_channels, 7, stride=2, padding=3, bias=False), nn.BatchNorm2d(self.init_channels), nn.ReLU(inplace=True) ) img_size = [x // 2 for x in img_size] self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size // 4, in_chans=self.init_channels, embed_dim=embed_dim // 2, norm_layer=embed_norm, flatten=False) img_size = [x // 4 for x in img_size] if self.pos_embed: if self.vit_stem: self.pos_embed1 = nn.Parameter(torch.zeros(1, embed_dim, img_size)) else: self.pos_embed1 = nn.Parameter(torch.zeros(1, embed_dim//2, img_size)) self.pos_drop = nn.Dropout(p=drop_rate) self.stage1 = nn.ModuleList([ Block( dim=embed_dim//2, num_heads=num_heads, head_dim_ratio=0.5, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[0] == '0'), spatial_conv=(spatial_conv[0] == '1') ) for i in range(self.stage_num1) ]) # stage2 if not self.vit_stem: self.patch_embed2 = PatchEmbed( img_size=img_size, patch_size=patch_size // 8, in_chans=embed_dim // 2, embed_dim=embed_dim, norm_layer=embed_norm, flatten=False) img_size = [x // 2 for x in img_size] if self.pos_embed: self.pos_embed2 = nn.Parameter(torch.zeros(1, embed_dim, img_size)) self.stage2 = nn.ModuleList([ Block( dim=embed_dim, num_heads=num_heads, head_dim_ratio=1.0, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[1] == '0'), spatial_conv=(spatial_conv[1] == '1') ) for i in range(self.stage_num1, self.stage_num1+self.stage_num2) ]) # stage 3 if not self.vit_stem: self.patch_embed3 = PatchEmbed( img_size=img_size, patch_size=patch_size // 8, in_chans=embed_dim, embed_dim=embed_dim 2, norm_layer=embed_norm, flatten=False) img_size = [x // 2 for x in img_size] if self.pos_embed: self.pos_embed3 = nn.Parameter(torch.zeros(1, embed_dim2, img_size)) self.stage3 = nn.ModuleList([ Block( dim=embed_dim2, num_heads=num_heads, head_dim_ratio=1.0, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[2] == '0'), spatial_conv=(spatial_conv[2] == '1') ) for i in range(self.stage_num1+self.stage_num2, depth) ]) # head self.num_features = embed_dim if self.vit_stem else embed_dim 2 self.norm = norm_layer(self.num_features) self.global_pool, self.head = create_classifier(self.num_features, self.num_classes, pool_type=global_pool) self.head = nn.Linear(self.num_features, num_classes) # weights init if self.pos_embed: trunc_normal_(self.pos_embed1, std=0.02) if not self.vit_stem: trunc_normal_(self.pos_embed2, std=0.02) trunc_normal_(self.pos_embed3, std=0.02) self.apply(self._init_weights) def _init_weights(self, m): if isinstance(m, nn.Linear): trunc_normal_(m.weight, std=0.02) if m.bias is not None: nn.init.constant_(m.bias, 0) elif isinstance(m, nn.LayerNorm): nn.init.constant_(m.bias, 0) nn.init.constant_(m.weight, 1.0) elif isinstance(m, nn.BatchNorm2d): nn.init.constant_(m.bias, 0) nn.init.constant_(m.weight, 1.0) elif isinstance(m, nn.Conv2d): if self.conv_init: nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu') else: trunc_normal_(m.weight, std=0.02) if m.bias is not None: nn.init.constant_(m.bias, 0.) def get_classifier(self): return self.head def reset_classifier(self, num_classes, global_pool='avg'): self.num_classes = num_classes self.global_pool, self.head = create_classifier(self.num_features, self.num_classes, pool_type=global_pool) def forward_features(self, x): if self.stem is not None: x = self.stem(x) # stage 1 x = self.patch_embed1(x) if self.pos_embed: x = x + self.pos_embed1 x = self.pos_drop(x) for b in self.stage1: x = b(x) # stage 2 if not self.vit_stem: x = self.patch_embed2(x) if self.pos_embed: x = x + self.pos_embed2 x = self.pos_drop(x) for b in self.stage2: x = b(x) # stage3 if not self.vit_stem: x = self.patch_embed3(x) if self.pos_embed: x = x + self.pos_embed3 x = self.pos_drop(x) for b in self.stage3: x = b(x) x = self.norm(x) return x def forward(self, x): x = self.forward_features(x) x = self.global_pool(x) x = self.head(x) return x def _create_visformer(variant, pretrained=False, default_cfg=None, kwargs): if kwargs.get('features_only', None): raise RuntimeError('features_only not implemented for Vision Transformer models.') model = build_model_with_cfg( Visformer, variant, pretrained, default_cfg=default_cfgs[variant], kwargs) return model @register_model def visformer_tiny(pretrained=False, kwargs): model_cfg = dict( init_channels=16, embed_dim=192, depth=(7, 4, 4), num_heads=3, mlp_ratio=4., group=8, attn_stage='011', spatial_conv='100', norm_layer=nn.BatchNorm2d, conv_init=True, embed_norm=nn.BatchNorm2d, kwargs) model = _create_visformer('visformer_tiny', pretrained=pretrained, model_cfg) return model @register_model def visformer_small(pretrained=False, kwargs): model_cfg = dict( init_channels=32, embed_dim=384, depth=(7, 4, 4), num_heads=6, mlp_ratio=4., group=8, attn_stage='011', spatial_conv='100', norm_layer=nn.BatchNorm2d, conv_init=True, embed_norm=nn.BatchNorm2d, kwargs) model = _create_visformer('visformer_small', pretrained=pretrained, model_cfg) return model # @register_model # def visformer_net1(pretrained=False, kwargs): # model = Visformer( # init_channels=None, embed_dim=384, depth=(0, 12, 0), num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=True, conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net2(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=(0, 12, 0), num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net3(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net4(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net5(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., group=1, attn_stage='111', # spatial_conv='111', vit_stem=False, conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net6(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., group=1, attn_stage='111', # pos_embed=False, spatial_conv='111', conv_init=True, kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net7(pretrained=False, kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=(6, 7, 7), num_heads=6, group=1, attn_stage='000', # pos_embed=False, spatial_conv='111', conv_init=True, kwargs) # model.default_cfg = _cfg() # return model	[ 1, 529, 276, 1112, 420, 29958, 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texar/losses/pg_losses.py	Holmeswww/Text_Infilling	25	68212	# """ Various loss functions for policy gradients. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf from texar.losses.losses_utils import mask_and_reduce from texar.utils.shapes import get_rank # pylint: disable=too-many-arguments, protected-access __all__ = [ "pg_loss_with_logits", "pg_loss_with_log_probs" ] def pg_loss_with_logits(actions, logits, advantages, rank=None, batched=False, sequence_length=None, average_across_batch=True, average_across_timesteps=False, average_across_remaining=False, sum_over_batch=False, sum_over_timesteps=True, sum_over_remaining=True, time_major=False): """Policy gradient loss with logits. Used for discrete actions. pg_loss = reduce( advantages * -log_prob( actions ) ), where `advantages` and `actions` will not bprop gradients. All arguments except :attr:`logits` and :attr:`actions` are the same as :func:`pg_loss_with_log_probs`. Args: actions: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and of dtype `int32` or `int64`. The rank of the Tensor is specified with :attr:`rank`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. logits: Unscaled log probabilities of shape `[(batch_size,) max_time, d_3, ..., d_{rank+1}]` and dtype `float32` or `float64`. The batch and time dimensions are exchanged if :attr:`time_major` is `True`. advantages: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and dtype `float32` or `float64`. The batch and time dimensions are exchanged if :attr:`time_major` is `True`. rank (int, optional): The rank of :attr:`actions`. If `None` (default), rank is automatically inferred from :attr:`actions` or :attr:`advantages`. If the inferred rank is `None`, :attr:`rank` is set to 1 if :attr:`batched` is `False`, and :attr:`rank`=2 if :attr:`batched` is `True`. batched (bool): `True` if the inputs are batched. sequence_length (optional): A Tensor of shape `[batch_size]`. Time steps beyond the respective sequence lengths will have zero losses. Used if :attr:`batched` is `True`. average_across_timesteps (bool): If set, average the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. average_across_batch (bool): If set, average the loss across the batch dimension. Must not set :attr:`average_across_batch`' and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. average_across_remaining (bool): If set, average the sequence across the remaining dimensions. Must not set :attr:`average_across_remaining`' and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. sum_over_timesteps (bool): If set, sum the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. sum_over_batch (bool): If set, sum the loss across the batch dimension. Must not set :attr:`average_across_batch` and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. sum_over_remaining (bool): If set, sum the loss across the remaining dimension. Must not set :attr:`average_across_remaining` and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. time_major (bool): The shape format of the inputs. If `True`, :attr:`logits`, :attr:`actions` and :attr:`advantages` must have shape `[max_time, batch_size, ...]`. If `False` (default), they must have shape `[batch_size, max_time, ...]`. Ignored if :attr:`batched` is `False`. Returns: A Tensor containing the loss to minimize, whose rank depends on the reduce arguments. For example, the batch dimension is reduced if either :attr:`average_across_batch` or :attr:`sum_over_batch` is `True`, which makes the rank of output tensor decrease by 1. """ actions = tf.stop_gradient(actions) neg_log_probs = tf.nn.sparse_softmax_cross_entropy_with_logits( logits=logits, labels=actions) return pg_loss_with_log_probs( log_probs=-neg_log_probs, advantages=advantages, rank=rank, batched=batched, sequence_length=sequence_length, average_across_batch=average_across_batch, average_across_timesteps=average_across_timesteps, average_across_remaining=average_across_remaining, sum_over_batch=sum_over_batch, sum_over_timesteps=sum_over_timesteps, sum_over_remaining=sum_over_remaining, time_major=time_major) def pg_loss_with_log_probs(log_probs, advantages, rank=None, batched=False, sequence_length=None, average_across_batch=True, average_across_timesteps=False, average_across_remaining=False, sum_over_batch=False, sum_over_timesteps=True, sum_over_remaining=True, time_major=False): """Policy gradient loss with log probs of actions. pg_loss = reduce( advantages * -log_probs ), where `advantages` will not bprop gradients. All arguments except :attr:`log_probs` are the same as :func:`pg_loss_with_logits`. Args: log_probs: Log probabilities of shape `[(batch_size,) max_time, ..., d_rank]` and dtype `float32` or `float64`. The rank of the Tensor is specified with :attr:`rank`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. advantages: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and dtype `float32` or `float64`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. rank (int, optional): The rank of :attr:`log_probs`. If `None` (default), rank is automatically inferred from :attr:`log_probs` or :attr:`advantages`. If the inferred rank is `None`, :attr:`rank` is set to 1 if :attr:`batched``==False`, and :attr:`rank`=2 if :attr:`batched``==True`. batched (bool): `True` if the inputs are batched. sequence_length (optional): A Tensor of shape `[batch_size]`. Time steps beyond the respective sequence lengths will have zero losses. Used if :attr:`batched` is `True`. average_across_timesteps (bool): If set, average the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. average_across_batch (bool): If set, average the loss across the batch dimension. Must not set :attr:`average_across_batch`' and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. average_across_remaining (bool): If set, average the sequence across the remaining dimensions. Must not set :attr:`average_across_remaining`' and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. sum_over_timesteps (bool): If set, sum the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. sum_over_batch (bool): If set, sum the loss across the batch dimension. Must not set :attr:`average_across_batch` and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. sum_over_remaining (bool): If set, sum the loss across the remaining dimension. Must not set :attr:`average_across_remaining` and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. time_major (bool): The shape format of the inputs. If `True`, :attr:`log_probs` and :attr:`advantages` must have shape `[max_time, batch_size, ...]`. If `False` (default), they must have shape `[batch_size, max_time, ...]`. Ignored if :attr:`batched` is `False`. Returns: A Tensor containing the loss to minimize, whose rank depends on the reduce arguments. For example, the batch dimension is reduced if either :attr:`average_across_batch` or :attr:`sum_over_batch` is `True`, which makes the rank of output tensor decrease by 1. """ advantages = tf.stop_gradient(advantages) losses = -log_probs * advantages if rank is None: rank = get_rank(log_probs) or get_rank(advantages) if rank is None: rank = 2 if batched else 1 if batched: losses = mask_and_reduce( losses, sequence_length, rank=rank, average_across_batch=average_across_batch, average_across_timesteps=average_across_timesteps, average_across_remaining=average_across_remaining, sum_over_batch=sum_over_batch, sum_over_timesteps=sum_over_timesteps, sum_over_remaining=sum_over_remaining, time_major=time_major) elif rank > 1: if average_across_remaining and sum_over_remaining: raise ValueError("Only one of `average_across_remaining` and " "`sum_over_remaining` can be set.") if average_across_remaining: losses = tf.reduce_mean(losses, axis=range(1, rank)) elif sum_over_remaining: losses = tf.reduce_sum(losses, axis=range(1, rank)) if not batched: if average_across_timesteps and sum_over_timesteps: raise ValueError("Only one of `average_across_timesteps` and " "`sum_over_timesteps` can be set.") if average_across_timesteps: losses = tf.reduce_mean(losses) elif sum_over_timesteps: losses = tf.reduce_mean(losses) return losses	[ 1, 396, 13, 15945, 29908, 13, 10444, 681, 6410, 3168, 363, 8898, 4656, 10070, 29889, 13, 15945, 29908, 13, 13, 3166, 4770, 29888, 9130, 1649, 1053, 8380, 29918, 5215, 13, 3166, 4770, 29888, 9130, 1649, 1053, 8542, 13, 3166, 4770, 29888, 9130, 1649, 1053, 1596, 29918, 2220, 13, 13, 5215, 26110, 408, 15886, 13, 13, 3166, 19696, 279, 29889, 6758, 267, 29889, 6758, 267, 29918, 13239, 1053, 11105, 29918, 392, 29918, 17469, 13, 3166, 19696, 279, 29889, 13239, 29889, 845, 11603, 1053, 679, 29918, 10003, 13, 13, 29937, 282, 2904, 524, 29901, 11262, 29922, 517, 29877, 29899, 13011, 29899, 25699, 29892, 6364, 29899, 5943, 13, 13, 1649, 497, 1649, 353, 518, 13, 1678, 376, 4061, 29918, 6758, 29918, 2541, 29918, 1188, 1169, 613, 13, 1678, 376, 4061, 29918, 6758, 29918, 2541, 29918, 1188, 29918, 771, 5824, 29908, 13, 29962, 13, 13, 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960, 731, 29892, 2533, 278, 6410, 4822, 278, 13, 9651, 9853, 9927, 29889, 19928, 451, 731, 584, 5552, 18078, 12483, 482, 29918, 562, 2124, 29918, 16175, 29952, 13, 9651, 322, 584, 5552, 18078, 2083, 29918, 957, 29918, 16175, 29952, 472, 278, 1021, 931, 29889, 13, 9651, 18076, 4395, 565, 584, 5552, 18078, 16175, 287, 29952, 338, 421, 8824, 1412, 13, 4706, 2533, 29918, 957, 29918, 1745, 17225, 313, 11227, 1125, 960, 731, 29892, 2533, 278, 6410, 4822, 278, 13, 9651, 9886, 9927, 29889, 19928, 451, 731, 584, 5552, 18078, 12483, 482, 29918, 562, 2124, 29918, 1745, 17225, 29952, 13, 9651, 322, 584, 5552, 18078, 2083, 29918, 957, 29918, 1745, 17225, 29952, 472, 278, 1021, 931, 29889, 18076, 4395, 565, 13, 9651, 694, 901, 13391, 916, 1135, 278, 9853, 322, 931, 13391, 29889, 13, 4706, 931, 29918, 21355, 313, 11227, 1125, 450, 8267, 3402, 310, 278, 10970, 29889, 960, 421, 5574, 1673, 13, 9651, 584, 5552, 18078, 1188, 29918, 771, 5824, 29952, 322, 584, 5552, 18078, 17263, 19771, 29952, 1818, 505, 8267, 13, 9651, 10338, 3317, 29918, 2230, 29892, 9853, 29918, 2311, 29892, 2023, 27865, 960, 421, 8824, 29952, 313, 4381, 511, 13, 9651, 896, 1818, 505, 8267, 10338, 16175, 29918, 2311, 29892, 4236, 29918, 2230, 29892, 2023, 27865, 13, 9651, 18076, 4395, 565, 584, 5552, 18078, 16175, 287, 29952, 338, 421, 8824, 1412, 13, 13, 1678, 16969, 29901, 13, 4706, 319, 323, 6073, 6943, 278, 6410, 304, 6260, 675, 29892, 5069, 7115, 7111, 373, 278, 13, 4706, 10032, 6273, 29889, 1152, 1342, 29892, 278, 9853, 9927, 338, 12212, 565, 13, 4706, 2845, 584, 5552, 18078, 12483, 482, 29918, 562, 2124, 29918, 16175, 29952, 470, 584, 5552, 18078, 2083, 29918, 957, 29918, 16175, 29952, 338, 13, 4706, 421, 5574, 1673, 607, 3732, 278, 7115, 310, 1962, 12489, 23806, 491, 29871, 29896, 29889, 13, 1678, 9995, 13, 1678, 25486, 353, 15886, 29889, 9847, 29918, 24970, 29898, 17263, 19771, 29897, 13, 13, 1678, 28495, 353, 448, 1188, 29918, 771, 5824, 334, 25486, 13, 13, 1678, 565, 7115, 338, 6213, 29901, 13, 4706, 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567, 322, 2533, 29918, 957, 29918, 9346, 4196, 567, 29901, 13, 9651, 12020, 7865, 2392, 703, 11730, 697, 310, 421, 12483, 482, 29918, 562, 2124, 29918, 9346, 4196, 567, 29952, 322, 376, 13, 462, 632, 29724, 2083, 29918, 957, 29918, 9346, 4196, 567, 29952, 508, 367, 731, 23157, 13, 4706, 565, 6588, 29918, 562, 2124, 29918, 9346, 4196, 567, 29901, 13, 9651, 28495, 353, 15886, 29889, 17469, 29918, 12676, 29898, 6758, 267, 29897, 13, 4706, 25342, 2533, 29918, 957, 29918, 9346, 4196, 567, 29901, 13, 9651, 28495, 353, 15886, 29889, 17469, 29918, 12676, 29898, 6758, 267, 29897, 13, 13, 1678, 736, 28495, 13, 2 ]
pythonTeste/aula14.py	VanessaCML/python	0	127127	<gh_stars>0 n = 1 par = impar = 0 while n != 0: n = int(input('Digite um número: ')) if n != 0: if n % 2 == 0: par += 1 else: impar += 1 print(f'Tem {par} número(s) par(es) e {impar} número(s) ímpar(es).')	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 29876, 353, 29871, 29896, 13, 862, 353, 527, 862, 353, 29871, 29900, 13, 8000, 302, 2804, 29871, 29900, 29901, 13, 1678, 302, 353, 938, 29898, 2080, 877, 14991, 568, 1922, 13831, 29901, 525, 876, 13, 1678, 565, 302, 2804, 29871, 29900, 29901, 13, 4706, 565, 302, 1273, 29871, 29906, 1275, 29871, 29900, 29901, 13, 9651, 610, 4619, 29871, 29896, 13, 4706, 1683, 29901, 13, 9651, 527, 862, 4619, 29871, 29896, 13, 2158, 29898, 29888, 29915, 5776, 426, 862, 29913, 13831, 29898, 29879, 29897, 610, 29898, 267, 29897, 321, 426, 326, 862, 29913, 13831, 29898, 29879, 29897, 29871, 5487, 862, 29898, 267, 467, 1495, 13, 2 ]
tests/unit/plugins/modules/test_panos_op.py	mrichardson03/mrichardson03.panos	4	1603788	# Copyright 2020 Palo Alto Networks, Inc # # Permission to use, copy, modify, and/or distribute this software for any # purpose with or without fee is hereby granted, provided that the above # copyright notice and this permission notice appear in all copies. # # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES # WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR # ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES # WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN # ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF # OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. from __future__ import absolute_import, division, print_function __metaclass__ = type import pytest from ansible_collections.mrichardson03.panos.plugins.modules import panos_op from .common.utils import ModuleTestCase class TestPanosOp(ModuleTestCase): module = panos_op @pytest.mark.parametrize( "command,is_xml,changed", [ ("show system info", False, False), ("<show><system><info></info></system></show>", True, False), ("request reboot system", False, True), ], ) def test_safe_commands(self, command, is_xml, changed, connection_mock): connection_mock.op.return_value = "<response><result>foo</result></response>" result = self._run_module({"cmd": command, "cmd_is_xml": is_xml}) assert result["changed"] == changed	[ 1, 396, 14187, 1266, 29871, 29906, 29900, 29906, 29900, 3793, 29877, 838, 517, 8527, 29879, 29892, 9266, 13, 29937, 13, 29937, 20894, 2333, 304, 671, 29892, 3509, 29892, 6623, 29892, 322, 29914, 272, 1320, 2666, 445, 7047, 363, 738, 13, 29937, 6437, 411, 470, 1728, 27684, 338, 1244, 1609, 16896, 29892, 4944, 393, 278, 2038, 13, 29937, 3509, 1266, 8369, 322, 445, 10751, 8369, 2615, 297, 599, 14591, 29889, 13, 29937, 13, 29937, 6093, 7791, 7818, 12982, 1525, 8519, 13756, 13044, 3352, 376, 3289, 8519, 29908, 5300, 6093, 26524, 29950, 1955, 28657, 13875, 29902, 4345, 15149, 399, 1718, 29934, 13566, 29059, 13, 29937, 22659, 5195, 29954, 17011, 7495, 3446, 3235, 7791, 7818, 12982, 1525, 2672, 6154, 15789, 4214, 15149, 306, 3580, 5265, 3352, 399, 1718, 29934, 13566, 29059, 8079, 13, 29937, 341, 1001, 3210, 13566, 2882, 6227, 11937, 5300, 383, 1806, 8186, 1799, 29889, 2672, 11698, 382, 29963, 3919, 24972, 9818, 6093, 26524, 29950, 1955, 20700, 17705, 6181, 15842, 13, 29937, 13764, 29979, 317, 4162, 8426, 1964, 29892, 22471, 26282, 29892, 2672, 4571, 26282, 29892, 6323, 8707, 1660, 13356, 3919, 25758, 21330, 1529, 1692, 29903, 6323, 13764, 29979, 21330, 1529, 1692, 29903, 13, 29937, 12317, 1299, 6156, 29923, 5348, 390, 2890, 8647, 4214, 3895, 11247, 1799, 8079, 501, 1660, 29892, 360, 8254, 6323, 13756, 29943, 1806, 29903, 29892, 12317, 2544, 4448, 2672, 13764, 13, 29937, 319, 9838, 8079, 8707, 29911, 4717, 1783, 29892, 405, 11787, 5265, 24647, 4741, 6323, 438, 29911, 4448, 323, 8476, 5971, 3308, 319, 9838, 29892, 9033, 3235, 4214, 19474, 8079, 13, 29937, 6323, 2672, 8707, 8186, 9838, 22659, 6093, 501, 1660, 6323, 349, 1001, 22051, 27616, 4741, 8079, 3446, 3235, 7791, 7818, 12982, 1525, 29889, 13, 13, 3166, 4770, 29888, 9130, 1649, 1053, 8380, 29918, 5215, 29892, 8542, 29892, 1596, 29918, 2220, 13, 13, 1649, 2527, 562, 605, 1649, 353, 1134, 13, 13, 5215, 11451, 1688, 13, 3166, 385, 1687, 29918, 29027, 29889, 29885, 4018, 538, 1100, 29900, 29941, 29889, 8357, 359, 29889, 12800, 29889, 7576, 1053, 7243, 359, 29918, 459, 13, 13, 3166, 869, 9435, 29889, 13239, 1053, 15591, 3057, 8259, 13, 13, 13, 1990, 4321, 29925, 16469, 11746, 29898, 7355, 3057, 8259, 1125, 13, 1678, 3883, 353, 7243, 359, 29918, 459, 13, 13, 1678, 732, 2272, 1688, 29889, 3502, 29889, 3207, 300, 374, 911, 29898, 13, 4706, 376, 6519, 29892, 275, 29918, 3134, 29892, 15033, 613, 13, 4706, 518, 13, 9651, 4852, 4294, 1788, 5235, 613, 7700, 29892, 7700, 511, 13, 9651, 4852, 29966, 4294, 5299, 5205, 5299, 3888, 2565, 3888, 2565, 5205, 2565, 4294, 28341, 5852, 29892, 7700, 511, 13, 9651, 4852, 3827, 22538, 1788, 613, 7700, 29892, 5852, 511, 13, 4706, 21251, 13, 1678, 1723, 13, 1678, 822, 1243, 29918, 11177, 29918, 26381, 29898, 1311, 29892, 1899, 29892, 338, 29918, 3134, 29892, 3939, 29892, 3957, 29918, 17640, 1125, 13, 4706, 3957, 29918, 17640, 29889, 459, 29889, 2457, 29918, 1767, 353, 9872, 5327, 5299, 2914, 29958, 5431, 829, 2914, 2565, 5327, 11903, 13, 13, 4706, 1121, 353, 1583, 3032, 3389, 29918, 5453, 3319, 29908, 9006, 1115, 1899, 29892, 376, 9006, 29918, 275, 29918, 3134, 1115, 338, 29918, 3134, 1800, 13, 13, 4706, 4974, 1121, 3366, 15033, 3108, 1275, 3939, 13, 2 ]
tests/settings.py	sunlightlabs/waterfall	1	81124	<reponame>sunlightlabs/waterfall import os BASE_DIR = os.path.dirname(os.path.dirname(__file__)) DEBUG = True TEMPLATE_DEBUG = True LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True INSTALLED_APPS = ( 'tests', ) DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'test', 'USER': 'test', 'PASSWORD': '<PASSWORD>', 'HOST': 'localhost', }, 'test': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'test', 'USER': 'test', 'PASSWORD': '<PASSWORD>', 'HOST': 'localhost', } } SECRET_KEY = "test"	[ 1, 529, 276, 1112, 420, 29958, 11445, 4366, 29880, 6897, 29914, 13405, 11950, 13, 5215, 2897, 13, 13, 25416, 29918, 9464, 353, 2897, 29889, 2084, 29889, 25721, 29898, 359, 29889, 2084, 29889, 25721, 22168, 1445, 1649, 876, 13, 13, 18525, 353, 5852, 13, 4330, 3580, 29931, 3040, 29918, 18525, 353, 5852, 13, 13, 29931, 19453, 29965, 10461, 29918, 16524, 353, 525, 264, 29899, 375, 29915, 13, 15307, 29918, 29999, 12413, 353, 525, 26913, 29915, 13, 17171, 29918, 29902, 29896, 29947, 29940, 353, 5852, 13, 17171, 29918, 29931, 29896, 29900, 29940, 353, 5852, 13, 17171, 29918, 29911, 29999, 353, 5852, 13, 13, 13, 13, 25580, 1964, 20566, 29918, 3301, 7024, 353, 313, 13, 1678, 525, 21150, 742, 13, 29897, 13, 13, 25832, 27982, 29903, 353, 426, 13, 1678, 525, 4381, 2396, 426, 13, 4706, 525, 1430, 29954, 8895, 2396, 525, 14095, 29889, 2585, 29889, 1627, 1975, 29889, 29272, 29918, 567, 29891, 9708, 29887, 29906, 742, 13, 4706, 525, 5813, 2396, 525, 1688, 742, 13, 4706, 525, 11889, 2396, 525, 1688, 742, 13, 4706, 525, 25711, 17013, 2396, 12801, 25711, 17013, 29958, 742, 13, 4706, 525, 20832, 2396, 525, 7640, 742, 13, 1678, 2981, 13, 1678, 525, 1688, 2396, 426, 13, 4706, 525, 1430, 29954, 8895, 2396, 525, 14095, 29889, 2585, 29889, 1627, 1975, 29889, 29272, 29918, 567, 29891, 9708, 29887, 29906, 742, 13, 4706, 525, 5813, 2396, 525, 1688, 742, 13, 4706, 525, 11889, 2396, 525, 1688, 742, 13, 4706, 525, 25711, 17013, 2396, 12801, 25711, 17013, 29958, 742, 13, 4706, 525, 20832, 2396, 525, 7640, 742, 13, 1678, 500, 13, 29913, 13, 13, 1660, 22245, 29911, 29918, 10818, 353, 376, 1688, 29908, 2 ]
models/Update.py	sonhamin/parallel_fedlearning	0	1606334	<reponame>sonhamin/parallel_fedlearning<filename>models/Update.py #!/usr/bin/env python # -- coding: utf-8 -- # Python version: 3.6 import torch from torch import nn, autograd from torch.utils.data import DataLoader, Dataset import numpy as np import random #from sklearn import metrics from os import fork from threading import Lock class DatasetSplit(Dataset): def __init__(self, dataset, idxs): self.dataset = dataset self.idxs = list(idxs) def __len__(self): return len(self.idxs) def __getitem__(self, item): image, label = self.dataset[self.idxs[item]] return image, label class LocalUpdate(object): def __init__(self, args, user_num, loss_func=nn.CrossEntropyLoss(), dataset=None, idxs=None): self.args = args self.user_num = user_num self.loss_func = loss_func self.selected_clients = [] self.ldr_train = DataLoader(DatasetSplit(dataset, idxs), batch_size=self.args.local_bs, shuffle=True) def train(self, net): net2 = net.to(self.args.device) net2.train() optimizer = torch.optim.SGD(net2.parameters(), lr=self.args.lr, momentum=self.args.momentum) loss22 = self.loss_func epoch_loss = [] for iter in range(self.args.local_ep): batch_loss = [] for batch_idx, (images, labels) in enumerate(self.ldr_train): images, labels = images.to(self.args.device), labels.to(self.args.device) net2.zero_grad() log_probs = net2(images) loss = loss22(log_probs, labels) loss.backward() optimizer.step() if self.args.verbose and batch_idx % 10 == 0: print('Local user {} -- Update Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format( self.user_num, iter, batch_idx * len(images), len(self.ldr_train.dataset), 100. * batch_idx / len(self.ldr_train), loss.item())) batch_loss.append(loss.item()) epoch_loss.append(sum(batch_loss)/len(batch_loss)) return net.state_dict(), sum(epoch_loss) / len(epoch_loss)	[ 1, 529, 276, 1112, 420, 29958, 1100, 3391, 262, 29914, 23482, 29918, 29888, 287, 21891, 29966, 9507, 29958, 9794, 29914, 6422, 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echoclient.py	JosunLP/OSZ_chat_ITS	1	70903	import socket import sys import threading from datetime import datetime from helper import MessageParser from helper import const from model import Message HOST = const.HOST PORT = const.PORT CURSOR_UP_ONE = '\x1b[1A' ERASE_LINE = '\x1b[2K' def message_listener(s: socket): try: while True: data = s.recv(1024) if not data: break m: Message.Message = MessageParser.byte_array_to_message(data) print(m.msg) except (ConnectionAbortedError, ConnectionResetError): print("Connection with server closed!") print("Welcome to ChatZ") UNAME = input("Whats your name? :") try: with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((HOST, PORT)) thread = threading.Thread(target=message_listener, args=[s]) thread.start() m = Message.Message(datetime.now().strftime(const.TIME_FILTER), "LOGIN", UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) while True: string = input("$~ ") sys.stdout.write(CURSOR_UP_ONE) sys.stdout.write(ERASE_LINE) if "!logout" in string: m = Message.Message(datetime.now().strftime(const.TIME_FILTER), "LOGOUT", UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) break m = Message.Message(datetime.now().strftime(const.TIME_FILTER), string, UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) except (ConnectionAbortedError, ConnectionResetError): print("Connection with server closed!")	[ 1, 1053, 9909, 13, 5215, 10876, 13, 5215, 3244, 292, 13, 3166, 12865, 1053, 12865, 13, 13, 3166, 16876, 1053, 7777, 11726, 13, 3166, 16876, 1053, 1040, 13, 3166, 1904, 1053, 7777, 13, 13, 20832, 353, 1040, 29889, 20832, 13, 15082, 353, 1040, 29889, 15082, 13, 22484, 29903, 1955, 29918, 4897, 29918, 12413, 353, 11297, 29916, 29896, 29890, 29961, 29896, 29909, 29915, 13, 1001, 8127, 29918, 18521, 353, 11297, 29916, 29896, 29890, 29961, 29906, 29968, 29915, 13, 13, 13, 1753, 2643, 29918, 25894, 29898, 29879, 29901, 9909, 1125, 13, 1678, 1018, 29901, 13, 4706, 1550, 5852, 29901, 13, 9651, 848, 353, 269, 29889, 3757, 29894, 29898, 29896, 29900, 29906, 29946, 29897, 13, 9651, 565, 451, 848, 29901, 13, 18884, 2867, 13, 9651, 286, 29901, 7777, 29889, 3728, 353, 7777, 11726, 29889, 10389, 29918, 2378, 29918, 517, 29918, 4906, 29898, 1272, 29897, 13, 9651, 1596, 29898, 29885, 29889, 7645, 29897, 13, 1678, 5174, 313, 5350, 4920, 18054, 2392, 29892, 15160, 27175, 2392, 1125, 13, 4706, 1596, 703, 5350, 411, 1923, 5764, 29991, 1159, 13, 13, 13, 2158, 703, 28862, 2763, 304, 678, 271, 29999, 1159, 13, 13, 29965, 5813, 353, 1881, 703, 8809, 1446, 596, 1024, 29973, 584, 1159, 13, 13, 2202, 29901, 13, 1678, 411, 9909, 29889, 11514, 29898, 11514, 29889, 5098, 29918, 1177, 2544, 29892, 9909, 29889, 6156, 7077, 29918, 1254, 1525, 5194, 29897, 408, 269, 29901, 13, 4706, 269, 29889, 6915, 3552, 20832, 29892, 349, 8476, 876, 13, 4706, 3244, 353, 3244, 292, 29889, 4899, 29898, 5182, 29922, 4906, 29918, 25894, 29892, 6389, 11759, 29879, 2314, 13, 4706, 3244, 29889, 2962, 580, 13, 4706, 286, 353, 7777, 29889, 3728, 29898, 12673, 29889, 3707, 2141, 710, 615, 603, 29898, 3075, 29889, 15307, 29918, 3738, 29931, 4945, 511, 376, 14480, 1177, 613, 501, 5813, 29897, 13, 4706, 3638, 353, 7777, 11726, 29889, 4906, 29918, 517, 29918, 10389, 29918, 2378, 29898, 29885, 29897, 13, 4706, 269, 29889, 6717, 29898, 6717, 29897, 13, 4706, 1550, 5852, 29901, 13, 9651, 1347, 353, 1881, 703, 29938, 30022, 16521, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 22484, 29903, 1955, 29918, 4897, 29918, 12413, 29897, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 1001, 8127, 29918, 18521, 29897, 13, 9651, 565, 376, 29991, 1188, 449, 29908, 297, 1347, 29901, 13, 18884, 286, 353, 7777, 29889, 3728, 29898, 12673, 29889, 3707, 2141, 710, 615, 603, 29898, 3075, 29889, 15307, 29918, 3738, 29931, 4945, 511, 376, 14480, 12015, 613, 501, 5813, 29897, 13, 18884, 3638, 353, 7777, 11726, 29889, 4906, 29918, 517, 29918, 10389, 29918, 2378, 29898, 29885, 29897, 13, 13, 18884, 269, 29889, 6717, 29898, 6717, 29897, 13, 18884, 2867, 13, 9651, 286, 353, 7777, 29889, 3728, 29898, 12673, 29889, 3707, 2141, 710, 615, 603, 29898, 3075, 29889, 15307, 29918, 3738, 29931, 4945, 511, 1347, 29892, 501, 5813, 29897, 13, 9651, 3638, 353, 7777, 11726, 29889, 4906, 29918, 517, 29918, 10389, 29918, 2378, 29898, 29885, 29897, 13, 13, 9651, 269, 29889, 6717, 29898, 6717, 29897, 13, 13, 19499, 313, 5350, 4920, 18054, 2392, 29892, 15160, 27175, 2392, 1125, 13, 1678, 1596, 703, 5350, 411, 1923, 5764, 29991, 1159, 13, 2 ]
jp.atcoder/abc123/abc123_d/8669197.py	kagemeka/atcoder-submissions	1	90679	import sys import numpy as np INF = 10 ** 18 def main(): x, y, z, K = map(int, sys.stdin.readline().split()) abc = np.array(sys.stdin.read().split(), dtype=np.int64) a = np.append(abc[:x], INF) b = np.append(abc[x:x + y], INF) c = np.append(abc[x + y:x + y+ z], INF) a = np.sort(a)[::-1] b = np.sort(b)[::-1] c = np.sort(c)[::-1] res = [] for i in range(1, min(K, x) + 1): for j in range(1, min(y, K // i) + 1): for k in range(1, min(z, K // (i * j)) + 1): res.append(a[i] + b[j] + c[k]) res = sorted(res, reverse=True)[:K] print('\n'.join(map(str, res))) if __name__ == "__main__": main()	[ 1, 1053, 10876, 30004, 13, 30004, 13, 5215, 12655, 408, 7442, 30004, 13, 30004, 13, 24065, 353, 29871, 29896, 29900, 3579, 29871, 29896, 29947, 30004, 13, 30004, 13, 1753, 1667, 7295, 30004, 13, 1678, 921, 29892, 343, 29892, 503, 29892, 476, 353, 2910, 29898, 524, 29892, 10876, 29889, 4172, 262, 29889, 949, 1220, 2141, 5451, 3101, 30004, 13, 1678, 25638, 353, 7442, 29889, 2378, 29898, 9675, 29889, 4172, 262, 29889, 949, 2141, 5451, 3285, 26688, 29922, 9302, 29889, 524, 29953, 29946, 8443, 13, 1678, 263, 353, 7442, 29889, 4397, 29898, 10736, 7503, 29916, 1402, 2672, 29943, 8443, 13, 1678, 289, 353, 7442, 29889, 4397, 29898, 10736, 29961, 29916, 29901, 29916, 718, 343, 1402, 2672, 29943, 8443, 13, 1678, 274, 353, 7442, 29889, 4397, 29898, 10736, 29961, 29916, 718, 343, 29901, 29916, 718, 343, 29974, 503, 1402, 2672, 29943, 8443, 13, 1678, 263, 353, 7442, 29889, 6605, 29898, 29874, 9601, 1057, 29899, 29896, 29962, 30004, 13, 1678, 289, 353, 7442, 29889, 6605, 29898, 29890, 9601, 1057, 29899, 29896, 29962, 30004, 13, 1678, 274, 353, 7442, 29889, 6605, 29898, 29883, 9601, 1057, 29899, 29896, 29962, 30004, 13, 30004, 13, 1678, 620, 353, 5159, 30004, 13, 1678, 363, 474, 297, 3464, 29898, 29896, 29892, 1375, 29898, 29968, 29892, 921, 29897, 718, 29871, 29896, 1125, 30004, 13, 4706, 363, 432, 297, 3464, 29898, 29896, 29892, 1375, 29898, 29891, 29892, 476, 849, 474, 29897, 718, 29871, 29896, 1125, 30004, 13, 9651, 363, 413, 297, 3464, 29898, 29896, 29892, 1375, 29898, 29920, 29892, 476, 849, 313, 29875, 334, 432, 876, 718, 29871, 29896, 1125, 30004, 13, 18884, 620, 29889, 4397, 29898, 29874, 29961, 29875, 29962, 718, 289, 29961, 29926, 29962, 718, 274, 29961, 29895, 2314, 30004, 13, 30004, 13, 1678, 620, 353, 12705, 29898, 690, 29892, 11837, 29922, 5574, 29897, 7503, 29968, 29962, 30004, 13, 1678, 1596, 28909, 29876, 4286, 7122, 29898, 1958, 29898, 710, 29892, 620, 4961, 30004, 13, 30004, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 30004, 13, 1678, 1667, 580, 13, 2 ]
example.py	vins9100/code-refiney-bq	0	1615994	def add(a, b): return a+b def substract(a,b): return a*b def divide(a,b): return a/b	[ 1, 822, 788, 29898, 29874, 29892, 289, 1125, 13, 29871, 736, 263, 29974, 29890, 13, 13, 1753, 1014, 4440, 29898, 29874, 29892, 29890, 1125, 13, 29871, 736, 263, 29930, 29890, 13, 13, 1753, 16429, 29898, 29874, 29892, 29890, 1125, 13, 29871, 736, 263, 29914, 29890, 13, 2 ]
tests/unit/i18n/test_init.py	matt-land/warehouse	2	80120	# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pretend from warehouse import i18n def test_sets_locale(monkeypatch): locale_obj = pretend.stub() locale_cls = pretend.stub( parse=pretend.call_recorder(lambda l: locale_obj), ) monkeypatch.setattr(i18n, "Locale", locale_cls) request = pretend.stub(locale_name=pretend.stub()) assert i18n._locale(request) is locale_obj assert locale_cls.parse.calls == [pretend.call(request.locale_name)] def test_includeme(): config_settings = {} config = pretend.stub( add_request_method=pretend.call_recorder(lambda f, name, reify: None), get_settings=lambda: config_settings, ) i18n.includeme(config) assert config.add_request_method.calls == [ pretend.call(i18n._locale, name="locale", reify=True), ] assert config_settings == { "jinja2.filters": { "format_date": "warehouse.i18n.filters:format_date", "format_datetime": "warehouse.i18n.filters:format_datetime", "format_rfc822_datetime": "warehouse.i18n.filters:format_rfc822_datetime", "format_number": "warehouse.i18n.filters:format_number", }, }	[ 1, 396, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 13, 29937, 366, 1122, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 13, 29937, 887, 1122, 4017, 263, 3509, 310, 278, 19245, 472, 13, 29937, 13, 29937, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 13, 29937, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 13, 29937, 399, 1806, 8187, 2692, 399, 1718, 29934, 13566, 29059, 6323, 8707, 29928, 22122, 29903, 8079, 13764, 29979, 476, 22255, 29892, 2845, 4653, 470, 2411, 2957, 29889, 13, 29937, 2823, 278, 19245, 363, 278, 2702, 4086, 14765, 1076, 11239, 322, 13, 29937, 27028, 1090, 278, 19245, 29889, 13, 13, 5215, 14794, 355, 13, 13, 3166, 281, 598, 8697, 1053, 474, 29896, 29947, 29876, 13, 13, 13, 1753, 1243, 29918, 7224, 29918, 23337, 29898, 3712, 446, 1478, 905, 1125, 13, 1678, 15068, 29918, 5415, 353, 14794, 355, 29889, 303, 431, 580, 13, 1678, 15068, 29918, 25932, 353, 14794, 355, 29889, 303, 431, 29898, 13, 4706, 6088, 29922, 19819, 355, 29889, 4804, 29918, 3757, 2098, 29898, 2892, 301, 29901, 15068, 29918, 5415, 511, 13, 1678, 1723, 13, 1678, 1601, 446, 1478, 905, 29889, 842, 5552, 29898, 29875, 29896, 29947, 29876, 29892, 376, 3524, 744, 613, 15068, 29918, 25932, 29897, 13, 1678, 2009, 353, 14794, 355, 29889, 303, 431, 29898, 23337, 29918, 978, 29922, 19819, 355, 29889, 303, 431, 3101, 13, 13, 1678, 4974, 474, 29896, 29947, 29876, 3032, 23337, 29898, 3827, 29897, 338, 15068, 29918, 5415, 13, 1678, 4974, 15068, 29918, 25932, 29889, 5510, 29889, 29883, 4293, 1275, 518, 19819, 355, 29889, 4804, 29898, 3827, 29889, 23337, 29918, 978, 4638, 13, 13, 13, 1753, 1243, 29918, 2856, 1004, 7295, 13, 1678, 2295, 29918, 11027, 353, 6571, 13, 1678, 2295, 353, 14794, 355, 29889, 303, 431, 29898, 13, 4706, 788, 29918, 3827, 29918, 5696, 29922, 19819, 355, 29889, 4804, 29918, 3757, 2098, 29898, 2892, 285, 29892, 1024, 29892, 337, 1598, 29901, 6213, 511, 13, 4706, 679, 29918, 11027, 29922, 2892, 29901, 2295, 29918, 11027, 29892, 13, 1678, 1723, 13, 13, 1678, 474, 29896, 29947, 29876, 29889, 2856, 1004, 29898, 2917, 29897, 13, 13, 1678, 4974, 2295, 29889, 1202, 29918, 3827, 29918, 5696, 29889, 29883, 4293, 1275, 518, 13, 4706, 14794, 355, 29889, 4804, 29898, 29875, 29896, 29947, 29876, 3032, 23337, 29892, 1024, 543, 23337, 613, 337, 1598, 29922, 5574, 511, 13, 1678, 4514, 13, 1678, 4974, 2295, 29918, 11027, 1275, 426, 13, 4706, 376, 28789, 1764, 29906, 29889, 26705, 1115, 426, 13, 9651, 376, 4830, 29918, 1256, 1115, 376, 2519, 8697, 29889, 29875, 29896, 29947, 29876, 29889, 26705, 29901, 4830, 29918, 1256, 613, 13, 9651, 376, 4830, 29918, 12673, 1115, 376, 2519, 8697, 29889, 29875, 29896, 29947, 29876, 29889, 26705, 29901, 4830, 29918, 12673, 613, 13, 9651, 376, 4830, 29918, 9600, 29883, 29947, 29906, 29906, 29918, 12673, 1115, 13, 18884, 376, 2519, 8697, 29889, 29875, 29896, 29947, 29876, 29889, 26705, 29901, 4830, 29918, 9600, 29883, 29947, 29906, 29906, 29918, 12673, 613, 13, 9651, 376, 4830, 29918, 4537, 1115, 376, 2519, 8697, 29889, 29875, 29896, 29947, 29876, 29889, 26705, 29901, 4830, 29918, 4537, 613, 13, 4706, 2981, 13, 1678, 500, 13, 2 ]
fair/forcing/ozone_tr.py	znicholls/FAIR	1	1377	<reponame>znicholls/FAIR<filename>fair/forcing/ozone_tr.py from __future__ import division import numpy as np from ..constants import molwt def regress(emissions, beta=np.array([2.8249e-4, 1.0695e-4, -9.3604e-4, 99.7831e-4])): """Calculates tropospheric ozone forcing from precursor emissions. Inputs: (nt x 40) emissions array Keywords: beta: 4-element array of regression coefficients of precursor radiative efficiency, W m-2 (Mt yr-1)-1. order is [CH4, CO, NMVOC, NOx] Outputs: tropospheric ozone ERF time series. """ if emissions.ndim==2: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[:,[3, 6, 7, 8]].T else: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[[3, 6, 7, 8]] F_CH4 = beta[0] * em_CH4 F_CO = beta[1] * em_CO F_NMVOC = beta[2] * em_NMVOC F_NOx = beta[3] * em_NOx F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def cmip6_stevenson(emissions, C_CH4, T=0, feedback=False, PI=np.array([722, 170, 10, 4.29]), beta=np.array([1.77871043e-04, 5.80173377e-05, 2.09151270e-03, 1.94458719e-04])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions beta: : coefficients of how CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions affect forcing Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)C_CH4 year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): F_CH4[i] = beta[0] (C_CH4[i]-PI[0]) F_CO[i] = beta[1] * (em_CO[i]-PI[1]) F_NMVOC[i] = beta[2] * (em_NMVOC[i]-PI[2]) F_NOx[i] = beta[3] * (em_NOx[i]-PI[3]) # Include the effect of climate feedback? We fit a curve to the 2000, 2030 # and 2100 best estimates of feedback based on middle-of-the-road # temperature projections. def temperature_feedback(T, a=0.03189267, b=1.34966941, c=-0.03214807): if T<=0: return 0 else: return anp.exp(-bT)+c if feedback: F = F_CH4 + F_CO + F_NMVOC + F_NOx + temperature_feedback(T) else: F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def stevenson(emissions, C_CH4, T=0, feedback=False, fix_pre1850_RCP=False, PI=np.array([722, 170, 10, 4.29])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? fix_pre1850_RCP: Use different relationship for 1750/65 to 1850 based on anthropogenic emissions from Skeie et al (2011) for 1750 (atmos-chem-phys.net/11/11827/2011) PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)C_CH4 # numbers in denominator are 2000-1750 concs or emissions used in # Stevenson and traced back to Lamarque et al 2010 for 2000 # https://www.atmos-chem-phys.net/10/7017/2010/ year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): if year[i]>=1850 or fix_pre1850_RCP==False: F_CH4[i] = 0.166/960 (C_CH4[i]-PI[0]) F_CO[i] = 0.058/681.8 * (em_CO[i]-PI[1]) F_NMVOC[i] = 0.035/155.84 * (em_NMVOC[i]-PI[2]) F_NOx[i] = 0.119/61.16 * (em_NOx[i] * molwt.NO / molwt.N - PI[3]) # The RCP scenarios give a negative forcing prior to ~1780. This is # because the anthropogenic emissions are given to be zero in RCPs but # not zero in the Skeie numbers which are used here. This can be fixed # to give a more linear behaviour. else: F_CH4[i] = 0.166/960 * (C_CH4[i]-722) F_CO[i] = 0.058/681.8 * 215.59 * em_CO[i] / 385.59 F_NMVOC[i] = 0.035/155.84 * 51.97 * em_NMVOC[i] / 61.97 F_NOx[i] = 0.119/61.16 * 7.31 * (em_NOx[i] * molwt.NO / molwt.N) / 11.6 # Include the effect of climate feedback? 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29889, 29900, 29945, 29947, 29914, 29953, 29947, 29896, 29889, 29947, 334, 29871, 29906, 29896, 29945, 29889, 29945, 29929, 29871, 334, 953, 29918, 3217, 29961, 29875, 29962, 847, 29871, 29941, 29947, 29945, 29889, 29945, 29929, 13, 9651, 383, 29918, 29940, 29924, 29963, 20166, 29961, 29875, 29962, 353, 29871, 29900, 29889, 29900, 29941, 29945, 29914, 29896, 29945, 29945, 29889, 29947, 29946, 334, 29871, 29945, 29896, 29889, 29929, 29955, 334, 953, 29918, 29940, 29924, 29963, 20166, 29961, 29875, 29962, 847, 29871, 29953, 29896, 29889, 29929, 29955, 13, 9651, 383, 29918, 6632, 29916, 29961, 29875, 29962, 259, 353, 29871, 29900, 29889, 29896, 29896, 29929, 29914, 29953, 29896, 29889, 29896, 29953, 29871, 334, 29871, 29955, 29889, 29941, 29896, 334, 313, 331, 29918, 6632, 29916, 29961, 29875, 29962, 13, 462, 334, 6062, 14554, 29889, 6632, 847, 6062, 14554, 29889, 29940, 29897, 847, 29871, 29896, 29896, 29889, 29953, 13, 13, 1678, 396, 512, 2325, 278, 2779, 310, 23622, 16705, 29973, 1334, 6216, 263, 11672, 304, 278, 29871, 29906, 29900, 29900, 29900, 29892, 29871, 29906, 29900, 29941, 29900, 13, 1678, 396, 322, 29871, 29906, 29896, 29900, 29900, 1900, 21875, 310, 16705, 2729, 373, 7256, 29899, 974, 29899, 1552, 29899, 9972, 13, 1678, 396, 10430, 410, 24247, 29889, 13, 1678, 822, 10430, 29918, 18798, 1627, 29898, 29911, 29892, 263, 29922, 29900, 29889, 29900, 29941, 29896, 29947, 29929, 29906, 29953, 29955, 29892, 289, 29922, 29896, 29889, 29941, 29946, 29929, 29953, 29953, 29929, 29946, 29896, 29892, 274, 10457, 29900, 29889, 29900, 29941, 29906, 29896, 29946, 29947, 29900, 29955, 1125, 13, 4706, 565, 323, 14065, 29900, 29901, 13, 9651, 736, 29871, 29900, 13, 4706, 1683, 29901, 13, 9651, 736, 263, 29930, 9302, 29889, 4548, 6278, 29890, 29930, 29911, 7240, 29883, 13, 13, 1678, 565, 16705, 29901, 13, 4706, 383, 353, 383, 29918, 3210, 29946, 718, 383, 29918, 3217, 718, 383, 29918, 29940, 29924, 29963, 20166, 718, 383, 29918, 6632, 29916, 718, 10430, 29918, 18798, 1627, 29898, 29911, 29897, 13, 1678, 1683, 29901, 13, 4706, 383, 353, 383, 29918, 3210, 29946, 718, 383, 29918, 3217, 718, 383, 29918, 29940, 29924, 29963, 20166, 718, 383, 29918, 6632, 29916, 13, 13, 1678, 736, 383, 13, 2 ]
unit_tests/fields/Field.py	jaredlunde/cargo-orm	3	82206	#!/usr/bin/python3 -S # -- coding: utf-8 -- import unittest import pickle import copy from cargo import aliased, Model from cargo.fields import Field from unit_tests import configure class Tc(object): def __init__(self, field): self.field = field class FieldModel(Model): field = Field() class TestField(unittest.TestCase): orm = FieldModel() def setUp(self): self.orm.clear() @property def base(self): return self.orm.field @property def base_array(self): return getattr(self.orm, 'array_' + self.base.field_name) def test_init(self, args, *kwargs): base = self.base.__class__() self.assertEqual(base.value, base.empty) base = self.base.__class__(primary=True) self.assertEqual(base.primary, True) base = self.base.__class__(unique=True) self.assertEqual(base.unique, True) base = self.base.__class__(index=True) self.assertEqual(base.index, True) base = self.base.__class__(default='field') self.assertEqual(base.default, 'field') base = self.base.__class__(not_null=True) self.assertEqual(base.not_null, True) base = self.base.__class__(validator=Tc) self.assertIsInstance(base.validator, Tc) def test_slots(self): self.assertFalse(hasattr(self.base, '__dict__')) def test_copy(self): fielda = self.base fieldb = self.base.copy() self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if k == 'validator': self.assertEqual(fielda.validator.__class__, fieldb.validator.__class__) else: self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) self.assertEqual(fielda.table, fieldb.table) fielda = self.base fieldb = copy.copy(self.base) self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if k == 'validator': self.assertEqual(fielda.validator.__class__, fieldb.validator.__class__) else: self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) self.assertEqual(fielda.table, fieldb.table) def test_deepcopy(self): fielda = self.base fieldb = copy.deepcopy(self.base) self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if isinstance( getattr(fielda, k), (str, list, tuple, dict, int, float)): self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) else: self.assertTrue( getattr(fielda, k).__class__, getattr(fieldb, k).__class__) self.assertEqual(fielda.table, fieldb.table) def test_pickle(self): b = pickle.loads(pickle.dumps(self.base)) for k in list(self.base.__slots__): if isinstance( getattr(self.base, k), (str, list, tuple, dict, int, float)): self.assertEqual(getattr(self.base, k), getattr(b, k)) else: self.assertTrue( getattr(self.base, k).__class__ == getattr(b, k).__class__) def test_set_alias(self): field = self.base.copy() field.table = 'foo' field.field_name = 'bar' field.set_alias(table="foo_b") self.assertEqual(str(aliased(field)), "foo_b.bar") field.set_alias(name="foo_b") self.assertEqual(str(aliased(field)), "foo_b") field.set_alias("foo_b", "bar_b") self.assertEqual(str(aliased(field)), "foo_b.bar_b") def test___call__(self): self.base('foobar') self.assertEqual(self.base.value, 'foobar') self.assertEqual(self.base(), 'foobar') self.assertEqual(self.base(None), None) if __name__ == '__main__': # Unit test configure.run_tests(TestField)	[ 1, 18787, 4855, 29914, 2109, 29914, 4691, 29941, 448, 29903, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 5215, 443, 27958, 13, 5215, 5839, 280, 13, 5215, 3509, 13, 13, 3166, 17040, 1053, 14430, 1463, 29892, 8125, 13, 3166, 17040, 29889, 9621, 1053, 8989, 13, 13, 3166, 5190, 29918, 21150, 1053, 10822, 13, 13, 13, 1990, 323, 29883, 29898, 3318, 1125, 13, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 1746, 1125, 13, 4706, 1583, 29889, 2671, 353, 1746, 13, 13, 13, 1990, 8989, 3195, 29898, 3195, 1125, 13, 1678, 1746, 353, 8989, 580, 13, 13, 13, 1990, 4321, 3073, 29898, 348, 27958, 29889, 3057, 8259, 1125, 13, 1678, 470, 29885, 353, 8989, 3195, 580, 13, 13, 1678, 822, 731, 3373, 29898, 1311, 1125, 13, 4706, 1583, 29889, 555, 29889, 8551, 580, 13, 13, 1678, 732, 6799, 13, 1678, 822, 2967, 29898, 1311, 1125, 13, 4706, 736, 1583, 29889, 555, 29889, 2671, 13, 13, 1678, 732, 6799, 13, 1678, 822, 2967, 29918, 2378, 29898, 1311, 1125, 13, 4706, 736, 679, 5552, 29898, 1311, 29889, 555, 29892, 525, 2378, 29918, 29915, 718, 1583, 29889, 3188, 29889, 2671, 29918, 978, 29897, 13, 13, 1678, 822, 1243, 29918, 2344, 29898, 1311, 29892, 334, 5085, 29892, 3579, 19290, 1125, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 1649, 580, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 1767, 29892, 2967, 29889, 6310, 29897, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 16072, 29922, 5574, 29897, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 16072, 29892, 5852, 29897, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 13092, 29922, 5574, 29897, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 13092, 29892, 5852, 29897, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 2248, 29922, 5574, 29897, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 2248, 29892, 5852, 29897, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 4381, 2433, 2671, 1495, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 4381, 29892, 525, 2671, 1495, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 1333, 29918, 4304, 29922, 5574, 29897, 13, 4706, 1583, 29889, 9294, 9843, 29898, 3188, 29889, 1333, 29918, 4304, 29892, 5852, 29897, 13, 4706, 2967, 353, 1583, 29889, 3188, 17255, 1990, 12035, 3084, 1061, 29922, 29911, 29883, 29897, 13, 4706, 1583, 29889, 9294, 3624, 4998, 29898, 3188, 29889, 3084, 1061, 29892, 323, 29883, 29897, 13, 13, 1678, 822, 1243, 29918, 2536, 1862, 29898, 1311, 1125, 13, 4706, 1583, 29889, 9294, 8824, 29898, 5349, 5552, 29898, 1311, 29889, 3188, 29892, 525, 1649, 8977, 1649, 8785, 13, 13, 1678, 822, 1243, 29918, 8552, 29898, 1311, 1125, 13, 4706, 1746, 29874, 353, 1583, 29889, 3188, 13, 4706, 1746, 29890, 353, 1583, 29889, 3188, 29889, 8552, 580, 13, 4706, 1583, 29889, 9294, 3624, 3664, 29898, 2671, 29874, 29892, 1746, 29890, 29897, 13, 4706, 363, 413, 297, 1051, 29898, 2671, 29874, 17255, 2536, 1862, 1649, 1125, 13, 9651, 565, 413, 1275, 525, 3084, 1061, 2396, 13, 18884, 1583, 29889, 9294, 9843, 29898, 2671, 29874, 29889, 3084, 1061, 17255, 1990, 1649, 29892, 13, 462, 462, 1746, 29890, 29889, 3084, 1061, 17255, 1990, 1649, 29897, 13, 9651, 1683, 29901, 13, 18884, 1583, 29889, 9294, 9843, 29898, 657, 5552, 29898, 2671, 29874, 29892, 413, 511, 679, 5552, 29898, 2671, 29890, 29892, 413, 876, 13, 4706, 1583, 29889, 9294, 9843, 29898, 2671, 29874, 29889, 2371, 29892, 1746, 29890, 29889, 2371, 29897, 13, 13, 4706, 1746, 29874, 353, 1583, 29889, 3188, 13, 4706, 1746, 29890, 353, 3509, 29889, 8552, 29898, 1311, 29889, 3188, 29897, 13, 4706, 1583, 29889, 9294, 3624, 3664, 29898, 2671, 29874, 29892, 1746, 29890, 29897, 13, 4706, 363, 413, 297, 1051, 29898, 2671, 29874, 17255, 2536, 1862, 1649, 1125, 13, 9651, 565, 413, 1275, 525, 3084, 1061, 2396, 13, 18884, 1583, 29889, 9294, 9843, 29898, 2671, 29874, 29889, 3084, 1061, 17255, 1990, 1649, 29892, 13, 462, 462, 1746, 29890, 29889, 3084, 1061, 17255, 1990, 1649, 29897, 13, 9651, 1683, 29901, 13, 18884, 1583, 29889, 9294, 9843, 29898, 657, 5552, 29898, 2671, 29874, 29892, 413, 511, 679, 5552, 29898, 2671, 29890, 29892, 413, 876, 13, 4706, 1583, 29889, 9294, 9843, 29898, 2671, 29874, 29889, 2371, 29892, 1746, 29890, 29889, 2371, 29897, 13, 13, 1678, 822, 1243, 29918, 24535, 8552, 29898, 1311, 1125, 13, 4706, 1746, 29874, 353, 1583, 29889, 3188, 13, 4706, 1746, 29890, 353, 3509, 29889, 24535, 8552, 29898, 1311, 29889, 3188, 29897, 13, 4706, 1583, 29889, 9294, 3624, 3664, 29898, 2671, 29874, 29892, 1746, 29890, 29897, 13, 4706, 363, 413, 297, 1051, 29898, 2671, 29874, 17255, 2536, 1862, 1649, 1125, 13, 9651, 565, 338, 8758, 29898, 13, 1669, 679, 5552, 29898, 2671, 29874, 29892, 413, 511, 313, 710, 29892, 1051, 29892, 18761, 29892, 9657, 29892, 938, 29892, 5785, 22164, 13, 18884, 1583, 29889, 9294, 9843, 29898, 657, 5552, 29898, 2671, 29874, 29892, 413, 511, 679, 5552, 29898, 2671, 29890, 29892, 413, 876, 13, 9651, 1683, 29901, 13, 18884, 1583, 29889, 9294, 5574, 29898, 13, 462, 1678, 679, 5552, 29898, 2671, 29874, 29892, 413, 467, 1649, 1990, 1649, 29892, 679, 5552, 29898, 2671, 29890, 29892, 413, 467, 1649, 1990, 1649, 29897, 13, 4706, 1583, 29889, 9294, 9843, 29898, 2671, 29874, 29889, 2371, 29892, 1746, 29890, 29889, 2371, 29897, 13, 13, 1678, 822, 1243, 29918, 23945, 280, 29898, 1311, 1125, 13, 4706, 289, 353, 5839, 280, 29889, 18132, 29898, 23945, 280, 29889, 29881, 17204, 29898, 1311, 29889, 3188, 876, 13, 4706, 363, 413, 297, 1051, 29898, 1311, 29889, 3188, 17255, 2536, 1862, 1649, 1125, 13, 9651, 565, 338, 8758, 29898, 13, 1669, 679, 5552, 29898, 1311, 29889, 3188, 29892, 413, 511, 313, 710, 29892, 1051, 29892, 18761, 29892, 9657, 29892, 938, 29892, 5785, 22164, 13, 18884, 1583, 29889, 9294, 9843, 29898, 657, 5552, 29898, 1311, 29889, 3188, 29892, 413, 511, 679, 5552, 29898, 29890, 29892, 413, 876, 13, 9651, 1683, 29901, 13, 18884, 1583, 29889, 9294, 5574, 29898, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 3188, 29892, 413, 467, 1649, 1990, 1649, 1275, 679, 5552, 29898, 29890, 29892, 413, 467, 1649, 1990, 1649, 29897, 13, 13, 1678, 822, 1243, 29918, 842, 29918, 19973, 29898, 1311, 1125, 13, 4706, 1746, 353, 1583, 29889, 3188, 29889, 8552, 580, 13, 4706, 1746, 29889, 2371, 353, 525, 5431, 29915, 13, 4706, 1746, 29889, 2671, 29918, 978, 353, 525, 1646, 29915, 13, 4706, 1746, 29889, 842, 29918, 19973, 29898, 2371, 543, 5431, 29918, 29890, 1159, 13, 4706, 1583, 29889, 9294, 9843, 29898, 710, 29898, 2606, 1463, 29898, 2671, 8243, 376, 5431, 29918, 29890, 29889, 1646, 1159, 13, 4706, 1746, 29889, 842, 29918, 19973, 29898, 978, 543, 5431, 29918, 29890, 1159, 13, 4706, 1583, 29889, 9294, 9843, 29898, 710, 29898, 2606, 1463, 29898, 2671, 8243, 376, 5431, 29918, 29890, 1159, 13, 4706, 1746, 29889, 842, 29918, 19973, 703, 5431, 29918, 29890, 613, 376, 1646, 29918, 29890, 1159, 13, 4706, 1583, 29889, 9294, 9843, 29898, 710, 29898, 2606, 1463, 29898, 2671, 8243, 376, 5431, 29918, 29890, 29889, 1646, 29918, 29890, 1159, 13, 13, 1678, 822, 1243, 22359, 4804, 12035, 1311, 1125, 13, 4706, 1583, 29889, 3188, 877, 1181, 22872, 1495, 13, 4706, 1583, 29889, 9294, 9843, 29898, 1311, 29889, 3188, 29889, 1767, 29892, 525, 1181, 22872, 1495, 13, 4706, 1583, 29889, 9294, 9843, 29898, 1311, 29889, 3188, 3285, 525, 1181, 22872, 1495, 13, 4706, 1583, 29889, 9294, 9843, 29898, 1311, 29889, 3188, 29898, 8516, 511, 6213, 29897, 13, 13, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 13, 1678, 396, 13223, 1243, 13, 1678, 10822, 29889, 3389, 29918, 21150, 29898, 3057, 3073, 29897, 13, 2 ]
Python/Tests/TestData/DebuggerProject/EnumChildTestV3.py	nanshuiyu/pytools	0	179959	d1 = {42: 100} d2 = {'abc': 'fob'} d3 = {1e1000: d1} s = set([frozenset([2,3,4])]) class C(object): abc = 42 def f(self): pass cinst = C() class C2(object): abc = 42 def __init__(self): self.oar = 100 self.self = self def __repr__(self): return 'myrepr' def __hex__(self): return 'myhex' def f(self): pass c2inst = C2() class C3(object): def __init__(self): self.abc = 42 self._contents = [1,2] def __iter__(self): return iter(self._contents) def __len__(self): return len(self._contents) def __getitem__(self, index): return self._contents[index] c3inst = C3() l = [1, 2, ] i = 3 pass	[ 1, 270, 29896, 353, 426, 29946, 29906, 29901, 29871, 29896, 29900, 29900, 8117, 13, 29881, 29906, 353, 11117, 10736, 2396, 525, 29888, 711, 29915, 8117, 13, 29881, 29941, 353, 426, 29896, 29872, 29896, 29900, 29900, 29900, 29901, 270, 29896, 8117, 13, 30004, 13, 29879, 353, 731, 4197, 29888, 16997, 575, 300, 4197, 29906, 29892, 29941, 29892, 29946, 2314, 2314, 30004, 13, 1990, 315, 29898, 3318, 1125, 30004, 13, 1678, 25638, 353, 29871, 29946, 29906, 30004, 13, 30004, 13, 1678, 822, 285, 29898, 1311, 1125, 1209, 30004, 13, 30004, 13, 29883, 2611, 353, 315, 26471, 13, 30004, 13, 1990, 315, 29906, 29898, 3318, 1125, 30004, 13, 1678, 25638, 353, 29871, 29946, 29906, 30004, 13, 1678, 822, 4770, 2344, 12035, 1311, 1125, 30004, 13, 4706, 1583, 29889, 29877, 279, 353, 29871, 29896, 29900, 29900, 30004, 13, 4706, 1583, 29889, 1311, 353, 1583, 30004, 13, 1678, 822, 4770, 276, 558, 12035, 1311, 1125, 30004, 13, 4706, 736, 525, 1357, 276, 558, 29915, 30004, 13, 1678, 822, 4770, 20970, 12035, 1311, 1125, 30004, 13, 4706, 736, 525, 1357, 20970, 29915, 30004, 13, 1678, 822, 285, 29898, 1311, 1125, 1209, 30004, 13, 30004, 13, 29883, 29906, 2611, 353, 315, 29906, 26471, 13, 30004, 13, 1990, 315, 29941, 29898, 3318, 1125, 30004, 13, 1678, 822, 4770, 2344, 12035, 1311, 1125, 30004, 13, 4706, 1583, 29889, 10736, 353, 29871, 29946, 29906, 30004, 13, 4706, 1583, 3032, 10853, 353, 518, 29896, 29892, 29906, 29962, 30004, 13, 1678, 822, 4770, 1524, 12035, 1311, 1125, 30004, 13, 4706, 736, 4256, 29898, 1311, 3032, 10853, 8443, 13, 1678, 822, 4770, 2435, 12035, 1311, 1125, 30004, 13, 4706, 736, 7431, 29898, 1311, 3032, 10853, 8443, 13, 1678, 822, 4770, 657, 667, 12035, 1311, 29892, 2380, 1125, 30004, 13, 4706, 736, 1583, 3032, 10853, 29961, 2248, 29962, 30004, 13, 30004, 13, 29883, 29941, 2611, 353, 315, 29941, 26471, 13, 30004, 13, 29880, 353, 518, 29896, 29892, 29871, 29906, 29892, 4514, 30004, 13, 30004, 13, 29875, 353, 29871, 29941, 30004, 13, 30004, 13, 3364, 2 ]
CursoGame/game.py	eStev4m/Game_in_Python	0	165192	<gh_stars>0 import pygame from pygame.locals import * from sys import exit pygame.init() largura = 640 altura = 480 x = largura / 2 y = 0 tela = pygame.display.set_mode((largura, altura)) pygame.display.set_caption('Curso de Game no Python') relogio = pygame.time.Clock() while True: relogio.tick(30) tela.fill((0,0,0)) for event in pygame.event.get(): if event.type == QUIT: pygame.quit() exit() pygame.draw.rect(tela, (255, 0, 0), (x, y, 40, 50)) if y >= altura: y = 0 y += 5 # pygame.draw.circle(tela, (0,0,255), (300, 260), 40) # pygame.draw.line(tela, (255,255,0), (390,0), (390,600), 5) pygame.display.update()	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 22028, 13, 3166, 22028, 29889, 2997, 29879, 1053, 334, 13, 3166, 10876, 1053, 6876, 13, 13, 2272, 11802, 29889, 2344, 580, 13, 13, 27489, 2002, 353, 29871, 29953, 29946, 29900, 13, 1997, 2002, 353, 29871, 29946, 29947, 29900, 13, 29916, 353, 5573, 2002, 847, 29871, 29906, 13, 29891, 353, 29871, 29900, 13, 13, 29873, 3100, 353, 22028, 29889, 4990, 29889, 842, 29918, 8513, 3552, 27489, 2002, 29892, 5272, 2002, 876, 13, 2272, 11802, 29889, 4990, 29889, 842, 29918, 6671, 877, 23902, 578, 316, 8448, 694, 5132, 1495, 13, 276, 1188, 601, 353, 22028, 29889, 2230, 29889, 29907, 908, 580, 13, 13, 8000, 5852, 29901, 13, 1678, 337, 1188, 601, 29889, 24667, 29898, 29941, 29900, 29897, 13, 1678, 260, 3100, 29889, 5589, 3552, 29900, 29892, 29900, 29892, 29900, 876, 13, 1678, 363, 1741, 297, 22028, 29889, 3696, 29889, 657, 7295, 13, 4706, 565, 1741, 29889, 1853, 1275, 660, 29965, 1806, 29901, 13, 9651, 22028, 29889, 28358, 580, 13, 9651, 6876, 580, 13, 13, 1678, 22028, 29889, 4012, 29889, 1621, 29898, 29873, 3100, 29892, 313, 29906, 29945, 29945, 29892, 29871, 29900, 29892, 29871, 29900, 511, 313, 29916, 29892, 343, 29892, 29871, 29946, 29900, 29892, 29871, 29945, 29900, 876, 13, 1678, 565, 343, 6736, 5272, 2002, 29901, 13, 4706, 343, 353, 29871, 29900, 13, 1678, 343, 4619, 29871, 29945, 13, 1678, 396, 22028, 29889, 4012, 29889, 16622, 29898, 29873, 3100, 29892, 313, 29900, 29892, 29900, 29892, 29906, 29945, 29945, 511, 313, 29941, 29900, 29900, 29892, 29871, 29906, 29953, 29900, 511, 29871, 29946, 29900, 29897, 13, 1678, 396, 22028, 29889, 4012, 29889, 1220, 29898, 29873, 3100, 29892, 313, 29906, 29945, 29945, 29892, 29906, 29945, 29945, 29892, 29900, 511, 313, 29941, 29929, 29900, 29892, 29900, 511, 313, 29941, 29929, 29900, 29892, 29953, 29900, 29900, 511, 29871, 29945, 29897, 13, 13, 1678, 22028, 29889, 4990, 29889, 5504, 580, 13, 2 ]
DSA_Cracker/Array/Python/Q6.py	OPENSOURCE-CORPORATION/Coding-Problems	1	1604991	# Problem Link : Check Sheet link below # Excel-Sheet Link : https://drive.google.com/file/d/1L3EOLDMs-Fx2XoKclkCg1OVymDGh6psP/view?usp=sharing # Youtube Video Link : # Q> Find Union and Intersections of 2 Arrays # Fundamental / Naive Approach def Solution_1(Array_1, Array_2): # Time: O(m*n), Space: O(0) Union = Array_1 Intersection = [] for i in range(len(Array_2)): if(Array_2[i] in Union): Intersection.append(Array_2[i]) else: Union.append(Array_2[i]) return Union, Intersection # Time : O((m(log(m) + n(log(n)) + (m + n)) ,Space : O(1) def Solution_2(Array_1, Array_2): Array_1.sort() Array_2.sort() # Array_1 will be shorter if(len(Array_1) > len(Array_2)): Array_1, Array_2 = Array_2, Array_1 i = 0 j = 0 Union = [] Intersection = [] while(i <= len(Array_1)-1 and j <= len(Array_2)-1): if(Array_1[i] > Array_2[j]): Union.append(Array_2[j]) j += 1 elif(Array_1[i] < Array_2[j]): Union.append(Array_1[i]) i += 1 else: Union.append(Array_1[i]) Intersection.append(Array_1[i]) i += 1 j += 1 # temp = len(Array_1) - 3 # This is wrong do not do like at and repeat the mistake i did # for i in range(len(Array_2) - len(Array_1) + 3): # Union.append(Array_2[temp]) # # print(Array_2[temp]) # temp += 1 while(j < len(Array_2)): Union.append(Array_2[j]) j += 1 return Union, Intersection Array_1 = [2, 1, 3, 4, 5, 6, 7] Array_2 = [2, 5, 4, 9, 8, 7, 10, 11, 13, 45] UNION, INTERSECTION = Solution_1(Array_1, Array_2) UNION.sort() print(f"The union of 2 Arrays is : {UNION}") print(f"The intersections of 2 Arrays is : {INTERSECTION}") # This Code is Written by <NAME> aka The "Dead_Coder"	[ 1, 396, 11583, 6645, 584, 5399, 2296, 300, 1544, 2400, 13, 29937, 11388, 29899, 10654, 6645, 29871, 584, 2045, 597, 21594, 29889, 3608, 29889, 510, 29914, 1445, 29914, 29881, 29914, 29896, 29931, 29941, 29923, 5607, 23560, 29879, 29899, 29943, 29916, 29906, 29990, 29877, 29968, 20495, 29907, 29887, 29896, 29949, 29963, 962, 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rest_framework_auth0/models.py	robindebois/djangorestframework-auth0	107	25111	# Just to keep things like ./manage.py test happy from django.contrib.auth.models import AbstractUser # class Group(models.Model): # """ # Groups are a generic way of categorizing users to apply permissions, or # some other label, to those users. A user can belong to any number of # groups. # A user in a group automatically has all the permissions granted to that # group. For example, if the group Site editors has the permission # can_edit_home_page, any user in that group will have that permission. # Beyond permissions, groups are a convenient way to categorize users to # apply some label, or extended functionality, to them. For example, you # could create a group 'Special users', and you could write code that would # do special things to those users -- such as giving them access to a # members-only portion of your site, or sending them members-only email # messages. # """ # name = models.CharField(_('name'), max_length=80, unique=True) # permissions = models.ManyToManyField( # Permission, # verbose_name=_('permissions'), # blank=True, # ) # # objects = GroupManager() # # class Meta: # verbose_name = _('group') # verbose_name_plural = _('groups') # # def __str__(self): # return self.name # # def natural_key(self): # return (self.name,) # class User(AbstractUser): # """ # Users within the Django authentication system are represented by this # model. # Username, password and email are required. Other fields are optional. # """ # class Meta(AbstractUser.Meta): # swappable = 'AUTH_USER_MODEL'	[ 1, 396, 3387, 304, 3013, 2712, 763, 11431, 1171, 482, 29889, 2272, 1243, 9796, 13, 3166, 9557, 29889, 21570, 29889, 5150, 29889, 9794, 1053, 25513, 2659, 13, 13, 29937, 770, 6431, 29898, 9794, 29889, 3195, 1125, 13, 29937, 268, 9995, 13, 29937, 268, 1632, 4410, 526, 263, 10035, 982, 310, 11608, 5281, 4160, 304, 3394, 11239, 29892, 470, 13, 29937, 268, 777, 916, 3858, 29892, 304, 1906, 4160, 29889, 319, 1404, 508, 6852, 304, 738, 1353, 310, 13, 29937, 268, 6471, 29889, 13, 29937, 268, 319, 1404, 297, 263, 2318, 6336, 756, 599, 278, 11239, 16896, 304, 393, 13, 29937, 268, 2318, 29889, 1152, 1342, 29892, 565, 278, 2318, 10781, 3863, 943, 756, 278, 10751, 13, 29937, 268, 508, 29918, 5628, 29918, 5184, 29918, 3488, 29892, 738, 1404, 297, 393, 2318, 674, 505, 393, 10751, 29889, 13, 29937, 268, 18502, 898, 11239, 29892, 6471, 526, 263, 19192, 982, 304, 11608, 675, 4160, 304, 13, 29937, 268, 3394, 777, 3858, 29892, 470, 10410, 9863, 29892, 304, 963, 29889, 1152, 1342, 29892, 366, 13, 29937, 268, 1033, 1653, 263, 2318, 525, 24780, 4160, 742, 322, 366, 1033, 2436, 775, 393, 723, 13, 29937, 268, 437, 4266, 2712, 304, 1906, 4160, 1192, 1316, 408, 6820, 963, 2130, 304, 263, 13, 29937, 268, 5144, 29899, 6194, 11910, 310, 596, 3268, 29892, 470, 9348, 963, 5144, 29899, 6194, 4876, 13, 29937, 268, 7191, 29889, 13, 29937, 268, 9995, 13, 29937, 268, 1024, 353, 4733, 29889, 27890, 7373, 877, 978, 5477, 4236, 29918, 2848, 29922, 29947, 29900, 29892, 5412, 29922, 5574, 29897, 13, 29937, 268, 11239, 353, 4733, 29889, 14804, 1762, 14804, 3073, 29898, 13, 29937, 308, 20894, 2333, 29892, 13, 29937, 308, 26952, 29918, 978, 29922, 29918, 877, 17858, 6847, 5477, 13, 29937, 308, 9654, 29922, 5574, 29892, 13, 29937, 268, 1723, 13, 29937, 13, 29937, 268, 3618, 353, 6431, 3260, 580, 13, 29937, 13, 29937, 268, 770, 20553, 29901, 13, 29937, 308, 26952, 29918, 978, 353, 903, 877, 2972, 1495, 13, 29937, 308, 26952, 29918, 978, 29918, 572, 3631, 353, 903, 877, 13155, 1495, 13, 29937, 13, 29937, 268, 822, 4770, 710, 12035, 1311, 1125, 13, 29937, 308, 736, 1583, 29889, 978, 13, 29937, 13, 29937, 268, 822, 5613, 29918, 1989, 29898, 1311, 1125, 13, 29937, 308, 736, 313, 1311, 29889, 978, 29892, 29897, 13, 13, 29937, 770, 4911, 29898, 9118, 2659, 1125, 13, 29937, 268, 9995, 13, 29937, 268, 23861, 2629, 278, 15337, 10760, 1788, 526, 9875, 491, 445, 13, 29937, 268, 1904, 29889, 13, 29937, 268, 4911, 978, 29892, 4800, 322, 4876, 526, 3734, 29889, 5901, 4235, 526, 13136, 29889, 13, 29937, 268, 9995, 13, 29937, 268, 770, 20553, 29898, 9118, 2659, 29889, 19346, 1125, 13, 29937, 308, 2381, 932, 519, 353, 525, 20656, 29950, 29918, 11889, 29918, 20387, 29931, 29915, 13, 2 ]
RDS/circle3_central_services/research_manager/src/api/User/__init__.py	Sciebo-RDS/Sciebo-RDS	10	17978	from .user import *	[ 1, 515, 869, 1792, 1053, 334, 29871, 2 ]
tests/integration/cartography/intel/azure/test_compute.py	Cloudanix/cartography	0	109094	from cartography.intel.azure import compute from tests.data.azure.compute import DESCRIBE_DISKS from tests.data.azure.compute import DESCRIBE_SNAPSHOTS from tests.data.azure.compute import DESCRIBE_VM_DATA_DISKS from tests.data.azure.compute import DESCRIBE_VMAVAILABLESIZES from tests.data.azure.compute import DESCRIBE_VMEXTENSIONS from tests.data.azure.compute import DESCRIBE_VMS from tests.data.azure.compute import DESCRIBE_VMSCALESETEXTENSIONS from tests.data.azure.compute import DESCRIBE_VMSCALESETS TEST_SUBSCRIPTION_ID = '00-00-00-00' TEST_RESOURCE_GROUP = 'TestRG' TEST_UPDATE_TAG = 123456789 def test_load_vms(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachine) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vms_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureVirtualMachine) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_data_disks(neo4j_session): compute.load_vm_data_disks( neo4j_session, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", DESCRIBE_VM_DATA_DISKS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", } nodes = neo4j_session.run( """ MATCH (r:AzureDataDisk) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_data_disk_relationships(neo4j_session): # Create Test Virtual Machines compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, [DESCRIBE_VMS[0]], TEST_UPDATE_TAG, ) compute.load_vm_data_disks( neo4j_session, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", DESCRIBE_VM_DATA_DISKS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:ATTACHED_TO]->(n2:AzureDataDisk) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_disks(neo4j_session): compute.load_disks( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_DISKS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", } nodes = neo4j_session.run( """ MATCH (r:AzureDisk) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_disk_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_disks( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_DISKS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureDisk) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_snapshots(neo4j_session): compute.load_snapshots( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_SNAPSHOTS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss1", } nodes = neo4j_session.run( """ MATCH (r:AzureSnapshot) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_snapshot_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_snapshots( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_SNAPSHOTS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss0", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureSnapshot) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_extensions(neo4j_session): compute.load_vm_extensions( neo4j_session, DESCRIBE_VMEXTENSIONS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM/extensions/extensions1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM1/extensions/extensions2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineExtension) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_extensions_relationships(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) compute.load_vm_extensions( neo4j_session, DESCRIBE_VMEXTENSIONS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM/extensions/extensions1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM1/extensions/extensions2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:CONTAIN]->(n2:AzureVirtualMachineExtension) RETURN n1.id, n2.id; """, ) actual = {(r['n1.id'], r['n2.id']) for r in result} assert actual == expected def test_load_vm_available_sizes(neo4j_session): compute.load_vm_available_sizes( neo4j_session, DESCRIBE_VMAVAILABLESIZES, TEST_UPDATE_TAG, ) expected_nodes = { "size1", "size2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineAvailableSize) RETURN r.name; """, ) actual_nodes = {n['r.name'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_available_sizes_relationships(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) compute.load_vm_available_sizes( neo4j_session, DESCRIBE_VMAVAILABLESIZES, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "size1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", "size2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:CONTAIN]->(n2:AzureVirtualMachineAvailableSize) RETURN n1.id, n2.name; """, ) actual = {(r['n1.id'], r['n2.name']) for r in result} assert actual == expected def test_load_vm_scale_sets(neo4j_session): compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineScaleSet) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vms_scale_sets_relationships(neo4j_session): neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", ), } result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureVirtualMachineScaleSet) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_scale_set_extensions(neo4j_session): compute.load_vm_scale_sets_extensions( neo4j_session, DESCRIBE_VMSCALESETEXTENSIONS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1/extensions/extension1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2/extensions/extension2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineScaleSetExtension) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_scale_set_extensions_relationships(neo4j_session): compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) compute.load_vm_scale_sets_extensions( neo4j_session, DESCRIBE_VMSCALESETEXTENSIONS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1/extensions/extension1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2/extensions/extension2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachineScaleSet)-[:CONTAIN]->(n2:AzureVirtualMachineScaleSetExtension) RETURN n1.id, n2.id; """, ) actual = {(r['n1.id'], r['n2.id']) for r in result} assert actual == expected	[ 1, 515, 7774, 5275, 29889, 524, 295, 29889, 17688, 1053, 10272, 13, 3166, 6987, 29889, 1272, 29889, 17688, 29889, 26017, 1053, 23050, 3960, 15349, 29918, 23711, 17557, 13, 3166, 6987, 29889, 1272, 29889, 17688, 29889, 26017, 1053, 23050, 3960, 15349, 29918, 19296, 3301, 7068, 2891, 29903, 13, 3166, 6987, 29889, 1272, 29889, 17688, 29889, 26017, 1053, 23050, 3960, 15349, 29918, 9219, 29918, 14573, 29918, 23711, 17557, 13, 3166, 6987, 29889, 1272, 29889, 17688, 29889, 26017, 1053, 23050, 3960, 15349, 29918, 29963, 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test/webapi/controllers/test_time_series.py	dzelge/xcube	0	33955	import unittest import numpy as np from xcube.webapi.controllers.time_series import get_time_series_info, get_time_series_for_point, \ get_time_series_for_geometry, get_time_series_for_geometry_collection from ..helpers import new_test_service_context class TimeSeriesControllerTest(unittest.TestCase): def test_get_time_series_for_point_invalid_lat_and_lon(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=-150.0, lat=-30.0) expected_dict = {'results': []} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_one_valid(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29'), max_valids=1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_only_valids(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29'), max_valids=-1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_with_uncertainty(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo-1w', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-22T00:00:00Z', 'result': {'average': 3.534773588180542, 'uncertainty': 0.0, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-29T00:00:00Z', 'result': {'average': 20.12085723876953, 'uncertainty': 0.0, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_point(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Point", coordinates=[2.1, 51.4]), start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_polygon(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]])) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 49.71656646340396, 'totalCount': 1, 'validCount': 132716}}, {'date': '2017-01-30T10:46:34Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_polygon_one_valid(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]]), max_valids=1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometries_incl_point(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry_collection(ctx, 'demo', 'conc_tsm', dict(type="GeometryCollection", geometries=[ dict(type="Point", coordinates=[2.1, 51.4])]), start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [[{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometries_incl_polygon(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry_collection(ctx, 'demo', 'conc_tsm', dict(type="GeometryCollection", geometries=[dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]])])) expected_dict = {'results': [[{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 49.71656646340396, 'totalCount': 1, 'validCount': 132716}}, {'date': '2017-01-30T10:46:34Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]]} self.assertEqual(expected_dict, time_series) def test_get_time_series_info(self): self.maxDiff = None ctx = new_test_service_context() info = get_time_series_info(ctx) expected_dict = self._get_expected_info_dict() self.assertEqual(expected_dict, info) @staticmethod def _get_expected_info_dict(): expected_dict = {'layers': []} bounds = {'xmin': 0.0, 'ymin': 50.0, 'xmax': 5.0, 'ymax': 52.5} demo_times = ['2017-01-16T10:09:22Z', '2017-01-25T09:35:51Z', '2017-01-26T10:50:17Z', '2017-01-28T09:58:11Z', '2017-01-30T10:46:34Z'] demo_variables = ['c2rcc_flags', 'conc_chl', 'conc_tsm', 'kd489', 'quality_flags'] for demo_variable in demo_variables: dict_variable = {'name': f'demo.{demo_variable}', 'dates': demo_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) demo1w_times = ['2017-01-22T00:00:00Z', '2017-01-29T00:00:00Z', '2017-02-05T00:00:00Z'] for demo_variable in demo_variables: dict_variable = {'name': f'demo-1w.{demo_variable}', 'dates': demo1w_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) dict_variable = {'name': f'demo-1w.{demo_variable}_stdev', 'dates': demo1w_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) return expected_dict	[ 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models/__init__.py	dapengchen123/hfsoftmax	1	9025	from .resnet import * from .hynet import * from .classifier import Classifier, HFClassifier, HNSWClassifier from .ext_layers import ParameterClient samplerClassifier = { 'hf': HFClassifier, 'hnsw': HNSWClassifier, }	[ 1, 515, 869, 690, 1212, 1053, 334, 13, 3166, 869, 29882, 948, 300, 1053, 334, 13, 3166, 869, 1990, 3709, 1053, 4134, 3709, 29892, 379, 29943, 2385, 3709, 29892, 379, 3059, 29956, 2385, 3709, 13, 3166, 869, 1062, 29918, 29277, 1053, 24953, 4032, 13, 13, 13, 13445, 20069, 2385, 3709, 353, 426, 13, 1678, 525, 29882, 29888, 2396, 379, 29943, 2385, 3709, 29892, 13, 1678, 525, 29882, 1983, 29893, 2396, 379, 3059, 29956, 2385, 3709, 29892, 13, 29913, 13, 2 ]
ocrd_typegroups_classifier/typegroups_classifier.py	mathpresso/printed-vs-handwritten	16	147982	import _io import torch import pickle from torchvision import transforms from PIL import Image from ocrd_typegroups_classifier.data.classmap import ClassMap from ocrd_typegroups_classifier.data.classmap import IndexRemap class TypegroupsClassifier: """ Class wrapping type group information and a classifier. Attributes ---------- classMap: ClassMap Maps class names to indices corresponding to what the network outputs. network: PyTorch network Classifier dev: str Device on which the data must be processed """ def __init__(self, groups, network, device=None): """ Constructor of the class. Parameters ---------- groups: map string to int Maps names to IDs with regard to the network outputs; note that several names can point to the same ID, but the inverse is not possible. network:PyTorch network This network has to have the same interface as the VRAEC, return three values when being called: the classification result, a variational loss, and a feature vector. device: str Device on which the data has to be processed; if not set, then either the cpu or cuda:0 will be used. """ self.classMap = ClassMap(groups) self.network = network if device is None: self.dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") else: self.dev = device network.to(self.dev) @classmethod def load(cls, input): """ Loads a type groups classifier from a file Parameters ---------- input: string or file File or path to the file from which the instance has to be loaded. """ if type(input) is str: f = open(input, 'rb') res = cls.load(f) f.close() return res if not type(input) is _io.BufferedReader: raise Exception('TypegroupsClassifier.load() requires a string or a file') res = pickle.load(input) # If trained with CUDA and loaded on a device without CUDA res.dev = torch.device(res.dev if torch.cuda.is_available() else "cpu") res.network.to(res.dev) return res def save(self, output): """ Stores the instance to a file Parameters ---------- output: string or file File or path to the file to which the instane has to be stored. """ if type(output) is str: f = open(output, 'wb') self.save(f) f.close() return if not type(output) is _io.BufferedWriter: raise Exception('save() requires a string or a file') # Moving the network to the cpu so that it can be reloaded on # machines which do not have CUDA available. self.network.to("cpu") pickle.dump(self, output) self.network.to(self.dev) def filter(self, sample, label): """ Removes data with unknown type groups Parameters ---------- sample: PyTorch tensor Tensor of inputs for the network label: PyTorch tensor Tensor of class IDs, the unknown ones being set to -1 Returns ------- sample, label The input tensors without the ones having a -1 label """ selection = label!=-1 return sample[selection], label[selection] def run(self, pil_image, stride, batch_size=32, score_as_key=False): return self.classify(pil_image, stride, batch_size, score_as_key) def classify(self, pil_image, stride, batch_size, score_as_key=False, max_width=1000): """ Classifies a PIL image, returning a map with class names and corresponding scores. Parameters ---------- pil_image: PIL image Image to classify stride: int The CNN is applied patch-wise; this parameter corresponds to the offset between two patches batch_size: int Number of patches which can be processed at the same time by the hardware. If no GPU is used, then a value of 1 is fine. score_as_key: bool Use scores, instead of class names, as key for the result map. Returns ------- A map between class names and scores, or scores and class names, depending on whether score_as_key is true or false. """ if pil_image.size[0]>max_width: pil_image = pil_image.resize((max_width, round(pil_image.size[1]*float(max_width)/pil_image.size[0])), Image.BILINEAR) crop_size = min(224, pil_image.size[0]) crop_size = min(crop_size, pil_image.size[1]) tensorize = transforms.ToTensor() was_training = self.network.training self.network.eval() with torch.no_grad(): score = 0 processed_samples = 0 batch = [] for x in range(0, pil_image.size[0], stride): for y in range(0, pil_image.size[1], stride): crop = tensorize(pil_image.crop((x, y, x+crop_size, y+crop_size))) batch.append(crop) if len(batch) >= batch_size: tensors = torch.stack(batch).to(self.dev) out = self.network(tensors) score += out.sum(0) processed_samples += len(batch) batch = [] if batch: tensors = torch.stack(batch).to(self.dev) out = self.network(tensors) score += out.sum(0) processed_samples += len(batch) batch = [] if was_training: self.network.train() score /= processed_samples res = {} for cl in self.classMap.cl2id: cid = self.classMap.cl2id[cl] if cid == -1: continue res[cl] = score[cid].item() if score_as_key: res = {s: c for c, s in res.items()} return res def __repr__(self): """ returns a string description of the instance """ format_string = self.__class__.__name__ + '(' format_string += '\n ClassMap: %s' % self.classMap format_string += '\n Network:' if self.network is None: format_string += '\n None' else: format_string += '\n%s\nEnd of network\n' % self.network return format_string+'\n)'	[ 1, 1053, 903, 601, 13, 5215, 4842, 305, 13, 5215, 5839, 280, 13, 3166, 4842, 305, 4924, 1053, 4327, 29879, 13, 3166, 349, 6227, 1053, 7084, 13, 13, 3166, 12954, 5499, 29918, 22449, 4872, 4410, 29918, 1990, 3709, 29889, 1272, 29889, 1990, 1958, 1053, 4134, 3388, 13, 3166, 12954, 5499, 29918, 22449, 4872, 4410, 29918, 1990, 3709, 29889, 1272, 29889, 1990, 1958, 1053, 11374, 7301, 481, 13, 13, 13, 13, 1990, 14213, 4872, 4410, 2385, 3709, 29901, 13, 1678, 9995, 4134, 28489, 1134, 2318, 2472, 322, 263, 770, 3709, 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generator/template/form.py	hrl/Protoend	3	173834	<gh_stars>1-10 import re import tornado.locale from tornado.escape import _unicode from tornado.util import unicode_type import wtforms.form class WTFormsTornadoTranslationWarpper(object): def __init__(self, locale_code): self.locale = tornado.locale.get(locale_code) def gettext(self, string): return self.locale.translate(string) def ngettext(self, singular, plural, n): return self.locale.translate(singular, plural, n) class WTFormsTornadoArgumentsWarpper(dict): def getlist(self, key): """ tornado.web.RequestHandler._get_arguments """ try: _remove_control_chars_regex = re.compile(r"[\x00-\x08\x0e-\x1f]") values = [] for v in self.get(key, []): if isinstance(v, bytes): v = _unicode(v) if isinstance(v, unicode_type): v = _remove_control_chars_regex.sub(" ", v) values.append(v) return values except UnicodeDecodeError: return [] class Form(wtforms.form.Form): class Meta: def get_translations(self, form): if not hasattr(form, '_locale_code'): form._locale_code = "en_US" return WTFormsTornadoTranslationWarpper(form._locale_code) def __init__(self, formdata=None, obj=None, prefix='', data=None, meta=None, locale_code="en_US", kwargs): self._locale_code = locale_code self.kwargs = kwargs super(Form, self).__init__(formdata, obj, prefix, data, meta, kwargs) def process(self, formdata=None, obj=None, data=None, kwargs): if formdata is not None \ and not hasattr(formdata, 'getlist') \ and not hasattr(formdata, 'getall'): formdata = WTFormsTornadoArgumentsWarpper(formdata) super(Form, self).process(formdata, obj, data, kwargs)	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 5215, 337, 13, 13, 5215, 10146, 912, 29889, 23337, 13, 13, 3166, 10146, 912, 29889, 21587, 1053, 903, 2523, 356, 13, 3166, 10146, 912, 29889, 4422, 1053, 29104, 29918, 1853, 13, 13, 5215, 281, 29873, 9514, 29889, 689, 13, 13, 13, 1990, 399, 29911, 12605, 29911, 1398, 912, 4300, 18411, 29956, 279, 2496, 29898, 3318, 1125, 13, 1678, 822, 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tests/test_incidents.py	deadmau6/IncidentReport	0	62484	<filename>tests/test_incidents.py<gh_stars>0 from fastapi.testclient import TestClient from ..main import app client = TestClient(app) # Tests for GET query_incident_by_id ################################# def test_query_incident_valid_id(): valid_number = 'F01705150090' response = client.get(f"/incident/{valid_number}") assert response.status_code == 200 def test_query_incident_bad_id(): valid_number = '001' response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 def test_query_incident_no_id(): valid_number = None response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 def test_query_incident_crazy_id(): valid_number = 21 response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 ################################## # Tests for POST query_incidents ################################## def test_query_incidents_valid(): valid = {"address": {"city": "Richmond","state": "VA"}} response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_bad(): valid = {"address": {"city": 24,"state": 25}} response = client.post("/incidents/", json=valid) assert response.status_code == 404 def test_query_incidents_no(): valid = None response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_crazy(): valid = {"address": {"cities": ["Richmond"],"state": "VA"}} response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 ################################## # Tests for GET query_incidents_by_address ################################## def test_query_incidents_by_address_valid(): valid = f"/incidents/address/?city=Richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_by_address_bad(): valid = f"/incidents/address/?city=24&state=25" response = client.get(valid) assert response.status_code == 404 def test_query_incidents_by_address_no(): valid = f"/incidents/address/" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_by_address_crazy(): valid = f"/incidents/address/?cities=richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 ################################## # Tests for GET query_incidents_by_description ################################## def test_query_incidents_by_description_valid(): valid = f"/incidents/description/?day_of_week=Monday" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_by_description_bad(): valid = f"/incidents/description/?day_of_week=80&response_time=Monday" response = client.get(valid) assert response.status_code == 404 def test_query_incidents_by_description_no(): valid = f"/incidents/description/" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_by_description_crazy(): valid = f"/incidents/description/?cities=richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2	[ 1, 529, 9507, 29958, 21150, 29914, 1688, 29918, 3742, 16719, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 3166, 5172, 2754, 29889, 1688, 4645, 1053, 4321, 4032, 13, 3166, 6317, 3396, 1053, 623, 13, 13, 4645, 353, 4321, 4032, 29898, 932, 29897, 13, 13, 29937, 4321, 29879, 363, 12354, 2346, 29918, 3742, 1693, 29918, 1609, 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erika/frontend/widgets/scrolled_window.py	Muges/erika	12	160803	<filename>erika/frontend/widgets/scrolled_window.py<gh_stars>10-100 # -- coding: utf-8 -- # # Copyright (c) 2016 Muges # Copyright (C) 2015 <NAME> <<EMAIL>> # Copyright (C) 2014 <NAME> <<EMAIL>> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranties of # MERCHANTABILITY, SATISFACTORY QUALITY, or FITNESS FOR A PARTICULAR # PURPOSE. See the GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program. If not, see <http://www.gnu.org/licenses/>. """ ScrolledWindow that sets a max size for the child to grow into. """ from gi.repository import Gtk from gi.repository import GObject class ScrolledWindow(Gtk.ScrolledWindow): """ScrolledWindow that sets a max size for the child to grow into Source ------ https://gist.github.com/TingPing/e70e09722e0fc37d2386 """ __gtype_name__ = "EggScrolledWindow" max_content_height = GObject.Property( type=int, default=-1, nick="Max Content Height", blurb="The maximum height request that can be made") max_content_width = GObject.Property( type=int, default=-1, nick="Max Content Width", blurb="The maximum width request that can be made") def __init__(self, args, kwargs): super().__init__(args, **kwargs) self.connect_after("notify::max-content-height", lambda obj, param: self.queue_resize()) self.connect_after("notify::max-content-width", lambda obj, param: self.queue_resize()) def set_max_content_height(self, value): # pylint: disable=arguments-differ self.max_content_height = value def set_max_content_width(self, value): # pylint: disable=arguments-differ self.max_content_width = value def get_max_content_height(self): # pylint: disable=arguments-differ return self.max_content_height def get_max_content_width(self): # pylint: disable=arguments-differ return self.max_content_width def do_get_preferred_height(self): # pylint: disable=arguments-differ min_height, natural_height = ( Gtk.ScrolledWindow.do_get_preferred_height(self) ) child = self.get_child() if natural_height and self.max_content_height > -1 and child: style = self.get_style_context() border = style.get_border(style.get_state()) additional = border.top + border.bottom _, child_nat_height = child.get_preferred_height() if all((child_nat_height > natural_height, self.max_content_height > natural_height)): natural_height = ( min(self.max_content_height, child_nat_height) + additional ) return min_height, natural_height def do_get_preferred_width(self): # pylint: disable=arguments-differ min_width, natural_width = ( Gtk.ScrolledWindow.do_get_preferred_width(self) ) child = self.get_child() if natural_width and self.max_content_width > -1 and child: style = self.get_style_context() border = style.get_border(style.get_state()) additional = border.left + border.right + 1 _, child_nat_width = child.get_preferred_width() if all((child_nat_width > natural_width, self.max_content_width > natural_width)): natural_width = ( min(self.max_content_width, child_nat_width) + additional ) return min_width, natural_width	[ 1, 529, 9507, 29958, 261, 4106, 29914, 8862, 355, 29914, 8030, 29879, 29914, 1557, 24476, 29918, 7165, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29899, 29896, 29900, 29900, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 29937, 13, 29937, 14187, 1266, 313, 29883, 29897, 29871, 29906, 29900, 29896, 29953, 341, 688, 267, 13, 29937, 14187, 1266, 313, 29907, 29897, 29871, 29906, 29900, 29896, 29945, 529, 5813, 29958, 3532, 26862, 6227, 6778, 13, 29937, 14187, 1266, 313, 29907, 29897, 29871, 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desertbot/modules/commands/RSS.py	Tantusar/DesertBot	0	194259	import datetime import dateutil.parser as dparser import feedparser from zope.interface import implementer from twisted.plugin import IPlugin from desertbot.message import IRCMessage from desertbot.moduleinterface import IModule from desertbot.modules.commandinterface import admin, BotCommand from desertbot.response import IRCResponse, ResponseType @implementer(IPlugin, IModule) class RSS(BotCommand): def triggers(self): return ["rss"] def actions(self): return super(RSS, self).actions() + [("ping", 1, self.checkFeeds)] def onLoad(self) -> None: if "rss_feeds" not in self.storage: self.storage["rss_feeds"] = {} self.feeds = self.storage["rss_feeds"] if "rss_channels" not in self.storage: self.storage["rss_channels"] = [] self.channels = self.storage["rss_channels"] def help(self, query): """ RSS command syntax: .rss <feed_name> - fetch latest for feed name .rss channels <channel_name> [<channel_name>]- send notifications to <channel_name> whenever a feed is updated .rss follow <url> <feed_name> - start following <url> as <feed_name> .rss unfollow <feed_name> - stop following <feed_name> .rss toggle <feed_name> - toggle automatic posting of new RSS posts to channels .rss list - list followed feeds """ helpDict = { "channels": "{}rss channels <channel_name> [<channel_name>]- send notifications to <channel_name> whenever a feed is updated", "follow": "{}rss follow <url> <feed_name> - Start following the RSS feed at <url> as <feed_name>", "unfollow": "{}rss unfollow <feed_name> - Stop following the RSS feed at <url>", "toggle": "{}rss toggle <feed_name> - Toggle displaying of new posts of the given RSS feed as chat messages", "list": "{}rss list - List currently followed RSS feeds", "": "{}rss <feed_name> - Display the latest post in the given RSS feed." } if len(query) == 1: return ("{0}rss <feed_name>/channels/follow/unfollow/toggle/list - Manages RSS feeds and automatic updates of them" " Use {0}help rss <subcommand> for more help.".format(self.bot.commandChar)) else: if query[1].lower() in helpDict: return helpDict[query[1].lower()].format(self.bot.commandChar) else: return ("{!r} is not a valid subcommand, use {}help rss for a list of subcommands" .format(query[1], self.bot.commandChar)) def execute(self, message: IRCMessage): if len(message.parameterList) == 0: return IRCResponse(ResponseType.Say, self.help(["rss"]), message.replyTo) if message.parameterList[0].lower() == "channels": return self._setChannels(message) elif message.parameterList[0].lower() == "follow": return self._followFeed(message) elif message.parameterList[0].lower() == "unfollow": return self._unfollowFeed(message) elif message.parameterList[0].lower() == "toggle": return self._toggleFeedSuppress(message) elif message.parameterList[0].lower() == "list": return self._listFeeds(message) else: feed = message.parameters.strip() latest = self._getLatest(feed) if latest is not None: response = 'Latest {}: {} \| {}'.format(latest["name"], latest["title"], latest["link"]) return IRCResponse(ResponseType.Say, response, message.replyTo) else: return IRCResponse(ResponseType.Say, "{} is not an RSS feed I monitor, leave a tell if you'd like it added!".format( message.parameters.strip()), message.replyTo) def checkFeeds(self): responses = [] for feedName, feedDeets in self.feeds.items(): newPost = self._updateFeed(feedName) if newPost and not feedDeets["suppress"]: for channel in self.channels: response = "New {}! Title: {} \| {}".format(feedName, feedDeets["lastTitle"], feedDeets["lastLink"]) responses.append(IRCResponse(ResponseType.Say, response, channel)) return responses def _updateFeed(self, feedName: str) -> bool: """ Returns True if feed has a new post, otherwise False """ feedDeets = self.feeds[feedName] if feedDeets["lastCheck"] > (datetime.datetime.utcnow() - datetime.timedelta(minutes=10)).isoformat(): return False self.feeds[feedName]["lastCheck"] = datetime.datetime.utcnow().isoformat() response = self.bot.moduleHandler.runActionUntilValue("fetch-url", feedDeets["url"]) if not response: self.logger.warning("Failed to fetch {!r}, either a server hiccuped " "or the feed no longer exists".format(feedDeets["url"])) return False feed = feedparser.parse(response.content) if len(feed["entries"]) > 0: def datesort(item): return dparser.parse(item["published"], fuzzy=True, ignoretz=True).isoformat() entries = sorted(feed["entries"], key=datesort, reverse=True) item = entries[0] else: self.logger.warning("The feed at {!r} doesn't have any entries, has it shut down?".format(feedDeets["url"])) return False itemDate = item["published"] newestDate = dparser.parse(itemDate, fuzzy=True, ignoretz=True).isoformat() if newestDate > feedDeets["lastUpdate"]: self.feeds[feedName]["lastUpdate"] = newestDate title = item["title"] link = item["link"] try: shortLink = self.bot.moduleHandler.runActionUntilValue("shorten-url", link) if shortLink is None: self.logger.error("Failed to shorten {}".format(link)) except Exception: self.logger.exception("Exception when trying to shorten URL {}".format(link)) else: link = shortLink if link == "": link = "Failed to find link for latest entry in feed!" self.feeds[feedName]["lastTitle"] = title self.feeds[feedName]["lastLink"] = link self.storage["rss_feeds"] = self.feeds return True return False def _getLatest(self, feedName): lowerMap = {name.lower(): name for name in self.feeds} if feedName.lower() in lowerMap: name = lowerMap[feedName.lower()] self._updateFeed(name) title = self.feeds[name]["lastTitle"] link = self.feeds[name]["lastLink"] return { "name": name, "title": title, "link": link } else: return None @admin("[RSS] Only my admins may tell me what channels to send notifications to!") def _setChannels(self, message: IRCMessage): self.channels = message.parameterList[1:] self.storage["rss_channels"] = self.channels return IRCResponse(ResponseType.Say, "RSS notifications will now be sent to: {}".format(self.channels), message.replyTo) @admin("[RSS] Only my admins may follow new RSS feeds!") def _followFeed(self, message: IRCMessage): try: url = message.parameterList[1] name = " ".join(message.parameterList[2:]) feed_object = { "url": url, "lastUpdate": (datetime.datetime.utcnow() - datetime.timedelta(days=365)).isoformat(), "lastTitle": "", "lastLink": "", "lastCheck": (datetime.datetime.utcnow() - datetime.timedelta(minutes=10)).isoformat(), "suppress": False } self.feeds[name] = feed_object self.storage["rss_feeds"] = self.feeds self._updateFeed(name) return IRCResponse(ResponseType.Say, "Successfully followed {} at URL {}".format(name, url), message.replyTo) except Exception: self.logger.exception("Failed to follow RSS feed - {}".format(message.messageString)) # clean up if it already got saved, and the error was in _updateFeed if name in self.feeds: del self.feeds[name] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "I couldn't quite parse that RSS follow, are you sure you did it right?", message.replyTo) @admin("[RSS] Only my admins may unfollow RSS feeds!") def _unfollowFeed(self, message: IRCMessage): name = " ".join(message.parameterList[1:]) if name in self.feeds: del self.feeds[name] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "Sucessfully unfollowed {}".format(name), message.replyTo) else: return IRCResponse(ResponseType.Say, "I am not following any feed named {}".format(name), message.replyTo) @admin("[RSS] Only my admins may turn RSS feeds on and off!") def _toggleFeedSuppress(self, message: IRCMessage): name = " ".join(message.parameterList[1:]) if name in self.feeds: self.feeds[name]["suppress"] = not self.feeds[name]["suppress"] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "Successfully {}ed {}".format("suppress" if self.feeds[name]["suppress"] else "unsupress", name), message.replyTo) else: return IRCResponse(ResponseType.Say, "I am not following any feed named {}".format(name), message.replyTo) def _listFeeds(self, message: IRCMessage): return IRCResponse(ResponseType.Say, "Currently followed feeds are: {}".format(", ".join(self.feeds.keys())), message.replyTo) rss = RSS()	[ 1, 1053, 12865, 13, 5215, 2635, 4422, 29889, 16680, 408, 270, 16680, 13, 5215, 8343, 16680, 13, 3166, 503, 2300, 29889, 13248, 1053, 2334, 261, 13, 3166, 3252, 12652, 29889, 8582, 1053, 306, 16288, 13, 13, 3166, 18197, 7451, 29889, 4906, 1053, 306, 10363, 3728, 13, 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565, 376, 29878, 893, 29918, 305, 12629, 29908, 451, 297, 1583, 29889, 12925, 29901, 13, 9651, 1583, 29889, 12925, 3366, 29878, 893, 29918, 305, 12629, 3108, 353, 5159, 13, 4706, 1583, 29889, 305, 12629, 353, 1583, 29889, 12925, 3366, 29878, 893, 29918, 305, 12629, 3108, 13, 13, 1678, 822, 1371, 29898, 1311, 29892, 2346, 1125, 13, 4706, 9995, 13, 4706, 390, 1799, 1899, 5877, 29901, 13, 4706, 869, 29878, 893, 529, 18798, 29918, 978, 29958, 448, 6699, 9281, 363, 8343, 1024, 13, 4706, 869, 29878, 893, 18196, 529, 12719, 29918, 978, 29958, 518, 29966, 12719, 29918, 978, 29958, 29962, 29899, 3638, 25913, 304, 529, 12719, 29918, 978, 29958, 10940, 263, 8343, 338, 4784, 13, 4706, 869, 29878, 893, 1101, 529, 2271, 29958, 529, 18798, 29918, 978, 29958, 448, 1369, 1494, 529, 2271, 29958, 408, 529, 18798, 29918, 978, 29958, 13, 4706, 869, 29878, 893, 443, 23031, 529, 18798, 29918, 978, 29958, 448, 5040, 1494, 529, 18798, 29918, 978, 29958, 13, 4706, 869, 29878, 893, 20429, 529, 18798, 29918, 978, 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29991, 29878, 29913, 338, 451, 263, 2854, 1014, 6519, 29892, 671, 6571, 8477, 364, 893, 363, 263, 1051, 310, 1014, 26381, 29908, 13, 462, 4706, 869, 4830, 29898, 1972, 29961, 29896, 1402, 1583, 29889, 7451, 29889, 6519, 5914, 876, 13, 13, 1678, 822, 6222, 29898, 1311, 29892, 2643, 29901, 306, 10363, 3728, 1125, 13, 4706, 565, 7431, 29898, 4906, 29889, 15501, 1293, 29897, 1275, 29871, 29900, 29901, 13, 9651, 736, 306, 10363, 5103, 29898, 5103, 1542, 29889, 29903, 388, 29892, 1583, 29889, 8477, 29898, 3366, 29878, 893, 3108, 511, 2643, 29889, 3445, 368, 1762, 29897, 13, 4706, 565, 2643, 29889, 15501, 1293, 29961, 29900, 1822, 13609, 580, 1275, 376, 305, 12629, 1115, 13, 9651, 736, 1583, 3032, 842, 1451, 12629, 29898, 4906, 29897, 13, 4706, 25342, 2643, 29889, 15501, 1293, 29961, 29900, 1822, 13609, 580, 1275, 376, 23031, 1115, 13, 9651, 736, 1583, 3032, 23031, 29737, 29898, 4906, 29897, 13, 4706, 25342, 2643, 29889, 15501, 1293, 29961, 29900, 1822, 13609, 580, 1275, 376, 348, 23031, 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doubanMovieTop250/main.py	HaoLiangPao/pythonWebCrawler	0	93791	<gh_stars>0 # -- codeing = utf-8 -- # @Time : 2021-12-18 4:43 a.m. # @Author : <NAME> # @File : main.py # @Software: PyCharm import doubanMovieTop250.dataCollection as dataCollection import doubanMovieTop250.dataStorage as dataStorage def main(): baseUrl = "https://movie.douban.com/top250?start=" # Save data into excel file first # dbPathExcel = u"doubanMovieTop250.xls" dbPathSQLite = u"doubanMovieTop250-test.db" # 1. Web Crawling dataList = dataCollection.getData(baseUrl) # 2. Data Analyzing # 3. Data Storage # dataStorage.saveDataExcel(dataList, dbPathExcel) # Save to a excel file dataStorage.saveDaveSQLite(dataList, dbPathSQLite) # Save to a Sqlite DB file if __name__ == "__main__": main()	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 448, 29930, 29899, 775, 292, 353, 23616, 29899, 29947, 448, 29930, 29899, 13, 29937, 732, 2481, 584, 29871, 29906, 29900, 29906, 29896, 29899, 29896, 29906, 29899, 29896, 29947, 29871, 29946, 29901, 29946, 29941, 263, 29889, 29885, 29889, 13, 29937, 732, 13720, 584, 529, 5813, 29958, 13, 29937, 732, 2283, 584, 1667, 29889, 2272, 13, 29937, 732, 6295, 14093, 29901, 10772, 1451, 2817, 13, 13, 5215, 4662, 2571, 18749, 7031, 29906, 29945, 29900, 29889, 1272, 7196, 408, 848, 7196, 13, 5215, 4662, 2571, 18749, 7031, 29906, 29945, 29900, 29889, 1272, 10486, 408, 848, 10486, 13, 13, 13, 1753, 1667, 7295, 13, 1678, 2967, 5983, 353, 376, 991, 597, 27362, 29889, 29881, 283, 2571, 29889, 510, 29914, 3332, 29906, 29945, 29900, 29973, 2962, 543, 13, 1678, 396, 16913, 848, 964, 10616, 934, 937, 13, 1678, 396, 4833, 2605, 22926, 353, 318, 29908, 29881, 283, 2571, 18749, 7031, 29906, 29945, 29900, 29889, 20267, 29908, 13, 1678, 4833, 2605, 4176, 568, 353, 318, 29908, 29881, 283, 2571, 18749, 7031, 29906, 29945, 29900, 29899, 1688, 29889, 2585, 29908, 13, 13, 1678, 396, 29871, 29896, 29889, 2563, 315, 1610, 1847, 13, 1678, 848, 1293, 353, 848, 7196, 29889, 657, 1469, 29898, 3188, 5983, 29897, 13, 1678, 396, 29871, 29906, 29889, 3630, 11597, 12339, 292, 13, 1678, 396, 29871, 29941, 29889, 3630, 26162, 13, 1678, 396, 848, 10486, 29889, 7620, 1469, 22926, 29898, 1272, 1293, 29892, 4833, 2605, 22926, 29897, 29871, 396, 16913, 304, 263, 10616, 934, 13, 1678, 848, 10486, 29889, 7620, 29928, 1351, 4176, 568, 29898, 1272, 1293, 29892, 4833, 2605, 4176, 568, 29897, 29871, 396, 16913, 304, 263, 13093, 568, 6535, 934, 13, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 1678, 1667, 580, 2 ]
backend/dataset/validate/kafkawrapper/consumer.py	ishudahiya2001/ULCA-IN-ulca-Public	0	1609673	import json import logging import random import string from logging.config import dictConfig from service.parallel import ParallelValidate from service.asr import ASRValidate from service.ocr import OCRValidate from service.monolingual import MonolingualValidate from service.asr_unlabeled import ASRUnlabeledValidate from service.tts import TTSValidate from configs.configs import kafka_bootstrap_server_host, validate_input_topic, validate_consumer_grp, validate_output_topic, user_mode_real from configs.configs import dataset_type_parallel, dataset_type_asr, dataset_type_ocr, dataset_type_monolingual, dataset_type_asr_unlabeled, dataset_type_tts from kafka import KafkaConsumer from processtracker.processtracker import ProcessTracker from kafkawrapper.producer import Producer from kafkawrapper.redis_util import RedisUtil log = logging.getLogger('file') # Method to instantiate the kafka consumer def instantiate(topics): consumer = KafkaConsumer(*topics, bootstrap_servers=list(str(kafka_bootstrap_server_host).split(",")), api_version=(1, 0, 0), group_id=validate_consumer_grp, auto_offset_reset='latest', enable_auto_commit=True, value_deserializer=lambda x: handle_json(x)) return consumer # Method to read and process the requests from the kafka queue def consume(): try: topics = [validate_input_topic] consumer = instantiate(topics) p_service, o_service, a_service, m_service, au_service, t_service = ParallelValidate(), OCRValidate(), ASRValidate(), MonolingualValidate(), ASRUnlabeledValidate(), TTSValidate() pt = ProcessTracker() prod = Producer() rand_str = ''.join(random.choice(string.ascii_letters) for i in range(4)) prefix = "DS-VALIDATE-" + "(" + rand_str + ")" log.info(f'{prefix} -- Running..........') while True: for msg in consumer: try: data = msg.value if data: log.info(f'{prefix} \| Received on Topic: " + msg.topic + " \| Partition: {str(msg.partition)}') if check_relay(data): log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') break srn = data["serviceRequestNumber"] log.info(f'data received from ingest -- SRN {srn}') if data["datasetType"] == dataset_type_parallel: p_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_ocr: o_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_asr: a_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_monolingual: m_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_asr_unlabeled: au_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_tts: t_service.execute_validation_pipeline(data) else: break except Exception as e: log.exception(f'{prefix} Exception in ds validate consumer while consuming: {str(e)}', e) except Exception as e: log.exception(f'Exception in ds validate consumer while consuming: {str(e)}', e) # Method that provides a deserialiser for the kafka record. def handle_json(x): try: return json.loads(x.decode('utf-8')) except Exception as e: log.exception(f'Exception while deserialising: {str(e)}', e) return {} # Method to check if a record is getting relayed def check_relay(data): repo = RedisUtil() record = repo.search([data["record"]["id"]]) if record: record = record[0] if 'mode' in record.keys(): if record['mode'] == user_mode_real: log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') return True else: rec = {"srn": data["serviceRequestNumber"], "datasetId": data["datasetId"], "mode": data["userMode"], "datasetType": data["datasetType"]} repo.upsert(data["record"]["id"], rec, True) return False else: log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') return True else: rec = {"srn": data["serviceRequestNumber"], "datasetId": data["datasetId"], "mode": data["userMode"], "datasetType": data["datasetType"]} repo.upsert(data["record"]["id"], rec, True) return False # Log config dictConfig({ 'version': 1, 'formatters': {'default': { 'format': '[%(asctime)s] {%(filename)s:%(lineno)d} %(threadName)s %(levelname)s in %(module)s: %(message)s', }}, 'handlers': { 'info': { 'class': 'logging.FileHandler', 'level': 'DEBUG', 'formatter': 'default', 'filename': 'info.log' }, 'console': { 'class': 'logging.StreamHandler', 'level': 'DEBUG', 'formatter': 'default', 'stream': 'ext://sys.stdout', } }, 'loggers': { 'file': { 'level': 'DEBUG', 'handlers': ['info', 'console'], 'propagate': '' } }, 'root': { 'level': 'DEBUG', 'handlers': ['info', 'console'] } })	[ 1, 1053, 4390, 13, 5215, 12183, 13, 5215, 4036, 13, 5215, 1347, 13, 3166, 12183, 29889, 2917, 1053, 9657, 3991, 13, 13, 3166, 2669, 29889, 23482, 1053, 1459, 6553, 7211, 403, 13, 3166, 2669, 29889, 294, 29878, 1053, 3339, 29934, 7211, 403, 13, 3166, 2669, 29889, 8415, 1053, 438, 11341, 7211, 403, 13, 3166, 2669, 29889, 3712, 324, 292, 950, 1053, 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mboot/connection/usb.py	robin-nitrokey/pyMBoot	4	114542	# Copyright (c) 2017 <NAME> # # SPDX-License-Identifier: BSD-3-Clause # The BSD-3-Clause license for this file can be found in the LICENSE file included with this distribution # or at https://spdx.org/licenses/BSD-3-Clause.html#licenseText import os import logging import collections from time import time from struct import pack, unpack_from from .base import DevConnBase from ..commands import CmdPacket, parse_cmd_response logger = logging.getLogger('MBOOT:USB') # os.environ['PYUSB_DEBUG'] = 'debug' # os.environ['PYUSB_LOG_FILENAME'] = 'usb.log' ######################################################################################################################## # Devices ######################################################################################################################## USB_DEVICES = { # NAME \| VID \| PID 'MKL27': (0x15A2, 0x0073), 'LPC55': (0x1FC9, 0x0021), 'IMXRT': (0x1FC9, 0x0135) } ######################################################################################################################## # Scan USB method ######################################################################################################################## def scan_usb(device_name: str = None) -> list: """ Scan connected USB devices :param device_name: The specific device name (MKL27, LPC55, ...) or VID:PID """ devices = [] if device_name is None: for name, value in USB_DEVICES.items(): devices += RawHid.enumerate(value[0], value[1]) else: if ':' in device_name: vid, pid = device_name.split(':') devices = RawHid.enumerate(int(vid, 0), int(pid, 0)) else: if device_name in USB_DEVICES: vid = USB_DEVICES[device_name][0] pid = USB_DEVICES[device_name][1] devices = RawHid.enumerate(vid, pid) return devices ######################################################################################################################## # USB HID Interface Base Class ######################################################################################################################## REPORT_ID = { # USB HID Reports 'CMD_OUT': 0x01, 'CMD_IN': 0x03, 'DATA_OUT': 0x02, 'DATA_IN': 0x04 } class RawHidBase(DevConnBase): @property def is_opened(self): return self._opened def __init__(self, kwargs): super().__init__(kwargs) self._opened = False self.vid = 0 self.pid = 0 self.vendor_name = "" self.product_name = "" @staticmethod def _encode_report(report_id, report_size, data, offset=0): data_len = min(len(data) - offset, report_size - 4) raw_data = pack('<2BH', report_id, 0x00, data_len) raw_data += data[offset: offset + data_len] raw_data += bytes([0x00] * (report_size - len(raw_data))) logger.debug(f"OUT[{len(raw_data)}]: " + ' '.join(f"{b:02X}" for b in raw_data)) return raw_data, offset + data_len @staticmethod def _decode_report(raw_data): logger.debug(f"IN [{len(raw_data)}]: " + ' '.join(f"{b:02X}" for b in raw_data)) report_id, _, plen = unpack_from('<2BH', raw_data) data = bytes(raw_data[4: 4 + plen]) if report_id == REPORT_ID['CMD_IN']: return parse_cmd_response(data) return data def open(self): raise NotImplementedError() def close(self): raise NotImplementedError() def abort(self): pass def read(self, timeout=1000): raise NotImplementedError() def write(self, packet): raise NotImplementedError() def info(self): return f"{self.product_name:s} (0x{self.vid:04X}, 0x{self.pid:04X})" ######################################################################################################################## # USB Interface Classes ######################################################################################################################## if os.name == "nt": try: import pywinusb.hid as hid except: raise Exception("PyWinUSB is required on a Windows Machine") class RawHid(RawHidBase): """ This class provides basic functions to access a USB HID device using pywinusb: - write/read an endpoint """ def __init__(self, kwargs): super().__init__(kwargs) # Vendor page and usage_id = 2 self.report = [] # deque used here instead of synchronized Queue # since read speeds are ~10-30% faster and are # comparable to a based list implementation. self.rcv_data = collections.deque() self.device = None return # handler called when a report is received def __rx_handler(self, data): # logging.debug("rcv: %s", data[1:]) self.rcv_data.append(data) def open(self): """ open the interface """ logger.debug(" Open Interface") self.device.set_raw_data_handler(self.__rx_handler) self.device.open(shared=False) self._opened = True def close(self): """ close the interface """ logger.debug(" Close Interface") self.device.close() self._opened = False def write(self, packet): """ Write data on the OUT endpoint associated to the HID interface :param packet: HID packet data """ if isinstance(packet, CmdPacket): report_id = REPORT_ID['CMD_OUT'] data = packet.to_bytes() elif isinstance(packet, (bytes, bytearray)): report_id = REPORT_ID['DATA_OUT'] data = packet else: raise Exception() data_index = 0 report_size = self.report[report_id - 1]._HidReport__raw_report_size while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.report[report_id - 1].send(raw_data) def read(self, timeout=2000): """ Read data from IN endpoint associated to the HID interface :param timeout: """ start = time() while len(self.rcv_data) == 0: if ((time() - start) * 1000) > timeout: raise TimeoutError() raw_data = self.rcv_data.popleft() return self._decode_report(bytes(raw_data)) @staticmethod def enumerate(vid, pid): """ Get an array of all connected devices which matches PyWinUSB.vid/PyWinUSB.pid. :param vid: USB Vendor ID :param pid: USB Product ID """ targets = [] all_devices = hid.find_all_hid_devices() # find devices with good vid/pid for dev in all_devices: if (dev.vendor_id == vid) and (dev.product_id == pid): try: dev.open(shared=False) report = dev.find_output_reports() if report: new_target = RawHid() new_target.report = report new_target.vendor_name = dev.vendor_name new_target.product_name = dev.product_name new_target.vid = dev.vendor_id new_target.pid = dev.product_id new_target.device = dev new_target.device.set_raw_data_handler(new_target.__rx_handler) targets.append(new_target) except Exception as e: logger.error("Receiving Exception: %s", str(e)) finally: dev.close() return targets else: try: import usb.core import usb.util except: raise Exception("PyUSB is required on a Linux Machine") class RawHid(RawHidBase, DevConnBase): """ This class provides basic functions to access a USB HID device using pyusb: - write/read an endpoint """ def __init__(self): super().__init__() self.ep_out = None self.ep_in = None self.device = None self.interface_number = -1 def open(self): """ open the interface """ logger.debug(" Open Interface") self._opened = True def close(self): """ close the interface """ logger.debug(" Close Interface") self._opened = False try: if self.device: usb.util.dispose_resources(self.device) except: pass def write(self, packet): """ Write data on the OUT endpoint associated to the HID interface :param packet: HID packet data """ if isinstance(packet, CmdPacket): report_id = REPORT_ID['CMD_OUT'] data = packet.to_bytes() elif isinstance(packet, (bytes, bytearray)): report_id = REPORT_ID['DATA_OUT'] data = packet else: raise Exception() data_index = 0 if self.ep_out: report_size = self.ep_out.wMaxPacketSize while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.ep_out.write(raw_data) else: bmRequestType = 0x21 # Host to device request of type Class of Recipient Interface bmRequest = 0x09 # Set_REPORT (HID class-specific request for transferring data over EP0) wValue = 0x200 + report_id # Issuing an OUT report with specified ID wIndex = self.interface_number # Interface number for HID report_size = 36 # TODO: get the value from descriptor while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.device.ctrl_transfer(bmRequestType, bmRequest, wValue, wIndex, raw_data) def read(self, timeout=1000): """ Read data from IN endpoint associated to the HID interface :param timeout: """ # TODO: test if self.ep_in.wMaxPacketSize is accessible in all Linux distributions raw_data = self.ep_in.read(self.ep_in.wMaxPacketSize, timeout) return self._decode_report(raw_data) @staticmethod def enumerate(vid, pid): """ Get list of all connected devices which matches PyUSB.vid and PyUSB.pid. :param vid: USB Vendor ID :param pid: USB Product ID """ # find all devices matching the vid/pid specified all_devices = usb.core.find(find_all=True, idVendor=vid, idProduct=pid) if not all_devices: logger.debug("No device connected") return None targets = [] # iterate on all devices found for dev in all_devices: interface = None interface_number = -1 # get active config config = dev.get_active_configuration() # iterate on all interfaces: for interface in config: if interface.bInterfaceClass == 0x03: # HID Interface interface_number = interface.bInterfaceNumber break if interface is None or interface_number == -1: continue try: if dev.is_kernel_driver_active(interface_number): dev.detach_kernel_driver(interface_number) except Exception as e: print(str(e)) try: dev.set_configuration() dev.reset() except usb.core.USBError as e: logger.debug(f"Cannot set configuration for the device: {str(e)}") ep_in, ep_out = None, None for ep in interface: if ep.bEndpointAddress & 0x80: ep_in = ep else: ep_out = ep if not ep_in: logger.error('Endpoints not found') return None new_target = RawHid() new_target.ep_in = ep_in new_target.ep_out = ep_out new_target.device = dev new_target.vid = vid new_target.pid = pid new_target.interface_number = interface_number new_target.vendor_name = usb.util.get_string(dev, 1).strip('\0') new_target.product_name = 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Rakesh/code.py	rakeshjm24/ga-learner-dst-repo	0	1600407	<filename>Rakesh/code.py # -------------- # Importing header files import numpy as np import warnings warnings.filterwarnings('ignore') #New record new_record=[[50, 9, 4, 1, 0, 0, 40, 0]] #Reading file data = np.genfromtxt(path, delimiter=",", skip_header=1) print("\nData: \n\n", data) #Code starts here #Step 2: age = data[:,0] #print(age) max_age = age.max() print(max_age) min_age = age.min() print(min_age) age_mean = age.mean() print(age_mean) age_std = np.std(age) print(age_std) #Step 3 race_0=data[data[:,2]==0] race_1=data[data[:,2]==1] race_2=data[data[:,2]==2] race_3=data[data[:,2]==3] race_4=data[data[:,2]==4] len_0=len(race_0) len_1=len(race_1) len_2=len(race_2) len_3=len(race_3) len_4=len(race_4) a = np.array([len_0,len_1,len_2,len_3,len_4]) print(a) minority_race = a.min() print(minority_race) #Step 4: senior_citizens=data[data[:,0]>60] working_hours_sum=senior_citizens.sum(axis=0)[6] 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2020/day5.py	natedileas/advent-of-code	0	172665	<reponame>natedileas/advent-of-code def boarding_pass_row(seq): assert len(seq) == 7 # FBFBBFF seqb = seq.replace('F', '0').replace('B', '1') return int(seqb, 2) def boarding_pass_col(seq): assert len(seq) == 3 seqb = seq.replace('R', '1').replace('L', '0') return int(seqb, 2) def row_id(seq): row, col = boarding_pass_row(seq[:7]), boarding_pass_col(seq[7:]) return 8 * row + col if __name__ == '__main__': print(row_id('FBFBBFFRLR')) print(row_id('BFFFBBFRRR')) print(row_id('FFFBBBFRRR')) print(row_id('BBFFBBFRLL')) ids = open('input5.txt').read().splitlines() all_ids = [row_id(i) for i in ids] print('p1:', max(all_ids)) """ >>> d = np.diff(np.sort(all_ids)) >>> np.where(d != 1) (array([652], dtype=int64),) >>> np.sort(all_ids)[652] 698 >>> np.sort(all_ids)[651:654] array([697, 698, 700]) """ print('p2:', 699)	[ 1, 529, 276, 1112, 420, 29958, 29876, 630, 488, 294, 29914, 328, 794, 29899, 974, 29899, 401, 13, 13, 1753, 7613, 292, 29918, 3364, 29918, 798, 29898, 11762, 1125, 13, 12, 9294, 7431, 29898, 11762, 29897, 1275, 29871, 29955, 13, 13, 12, 29937, 383, 28062, 14388, 4198, 13, 12, 11762, 29890, 353, 19359, 29889, 6506, 877, 29943, 742, 525, 29900, 2824, 6506, 877, 29933, 742, 525, 29896, 1495, 13, 12, 2457, 938, 29898, 11762, 29890, 29892, 29871, 29906, 29897, 13, 13, 13, 1753, 7613, 292, 29918, 3364, 29918, 1054, 29898, 11762, 1125, 13, 12, 9294, 7431, 29898, 11762, 29897, 1275, 29871, 29941, 13, 12, 13, 12, 11762, 29890, 353, 19359, 29889, 6506, 877, 29934, 742, 525, 29896, 2824, 6506, 877, 29931, 742, 525, 29900, 1495, 13, 12, 2457, 938, 29898, 11762, 29890, 29892, 29871, 29906, 29897, 13, 13, 1753, 1948, 29918, 333, 29898, 11762, 1125, 13, 12, 798, 29892, 784, 353, 7613, 292, 29918, 3364, 29918, 798, 29898, 11762, 7503, 29955, 11724, 7613, 292, 29918, 3364, 29918, 1054, 29898, 11762, 29961, 29955, 29901, 2314, 13, 12, 2457, 29871, 29947, 334, 1948, 718, 784, 13, 13, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 13, 12, 2158, 29898, 798, 29918, 333, 877, 18426, 29943, 14388, 4198, 2241, 29934, 8785, 13, 12, 2158, 29898, 798, 29918, 333, 877, 29933, 4198, 29943, 14388, 15860, 29934, 29934, 8785, 13, 12, 2158, 29898, 798, 29918, 333, 877, 4198, 29943, 14388, 29933, 15860, 29934, 29934, 8785, 13, 12, 2158, 29898, 798, 29918, 333, 877, 14388, 4198, 14388, 15860, 2208, 8785, 13, 13, 12, 4841, 353, 1722, 877, 2080, 29945, 29889, 3945, 2824, 949, 2141, 5451, 9012, 580, 13, 12, 497, 29918, 4841, 353, 518, 798, 29918, 333, 29898, 29875, 29897, 363, 474, 297, 18999, 29962, 13, 12, 2158, 877, 29886, 29896, 29901, 742, 4236, 29898, 497, 29918, 4841, 876, 13, 13, 12, 15945, 29908, 13, 12, 6778, 29958, 270, 353, 7442, 29889, 12765, 29898, 9302, 29889, 6605, 29898, 497, 29918, 4841, 876, 13, 12, 6778, 29958, 7442, 29889, 3062, 29898, 29881, 2804, 29871, 29896, 29897, 13, 12, 29898, 2378, 4197, 29953, 29945, 29906, 1402, 26688, 29922, 524, 29953, 29946, 511, 29897, 13, 12, 6778, 29958, 7442, 29889, 6605, 29898, 497, 29918, 4841, 9601, 29953, 29945, 29906, 29962, 13, 12, 29953, 29929, 29947, 13, 12, 6778, 29958, 7442, 29889, 6605, 29898, 497, 29918, 4841, 9601, 29953, 29945, 29896, 29901, 29953, 29945, 29946, 29962, 13, 12, 2378, 4197, 29953, 29929, 29955, 29892, 29871, 29953, 29929, 29947, 29892, 29871, 29955, 29900, 29900, 2314, 13, 13, 12, 15945, 29908, 13, 12, 2158, 877, 29886, 29906, 29901, 742, 29871, 29953, 29929, 29929, 29897, 2 ]
training/def/tr3.py	Evgesha3425/lessons2	1	177742	""" Создайте лямбда-функцию по следующему описанию: Введите строку с клавиатуры. Удалите из нее все буквы алфавита, идущие после буквы "и". Подсказка: воспользуйтесь генератором. Вы можете сравнивать буквы как числа. Чем дальше буква в алфавите, тем она "больше". """ my_string = input("Введите строку: ") new_string = lambda string: [letter for letter in string if letter < "и"] print("".join(new_string(my_string)))	[ 1, 9995, 13, 30008, 29904, 8728, 29977, 730, 29871, 1225, 16001, 840, 29899, 30011, 13937, 13603, 733, 19139, 11957, 1805, 614, 7832, 7506, 29901, 13, 30012, 1521, 956, 730, 2091, 576, 1382, 531, 9955, 21252, 15934, 29889, 2014, 840, 644, 730, 1866, 1538, 29919, 6495, 3180, 29951, 4938, 20920, 8685, 1221, 676, 29892, 606, 1520, 2837, 29919, 9017, 3180, 29951, 4938, 376, 29917, 1642, 13, 30013, 10285, 2494, 29972, 642, 29901, 1786, 3565, 693, 3923, 29977, 730, 1210, 13014, 494, 28359, 29889, 14966, 19620, 730, 531, 3766, 507, 24058, 3180, 29951, 4938, 5413, 5787, 12329, 29889, 23214, 3574, 693, 2237, 13, 3378, 11691, 490, 20920, 8685, 1221, 730, 29892, 14197, 15568, 376, 22451, 2237, 1642, 13, 15945, 29908, 13, 13, 1357, 29918, 1807, 353, 1881, 703, 30012, 1521, 956, 730, 2091, 576, 1382, 29901, 16521, 13, 1482, 29918, 1807, 353, 14013, 1347, 29901, 518, 15670, 363, 5497, 297, 1347, 565, 5497, 529, 376, 29917, 3108, 13, 2158, 703, 1642, 7122, 29898, 1482, 29918, 1807, 29898, 1357, 29918, 1807, 4961, 2 ]
migrations/versions/a684c982c890_.py	very-meanly/vc	0	156224	"""empty message Revision ID: a684c982c890 Revises: <PASSWORD> Create Date: 2021-10-16 18:12:03.996294 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'a684c982c890' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('generation_request', sa.Column('published', sa.DateTime(), nullable=True)) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column('generation_request', 'published') # ### end Alembic commands ###	[ 1, 9995, 6310, 2643, 13, 13, 1123, 4924, 3553, 29901, 263, 29953, 29947, 29946, 29883, 29929, 29947, 29906, 29883, 29947, 29929, 29900, 13, 1123, 1730, 267, 29901, 529, 25711, 17013, 29958, 13, 4391, 4712, 29901, 29871, 29906, 29900, 29906, 29896, 29899, 29896, 29900, 29899, 29896, 29953, 29871, 29896, 29947, 29901, 29896, 29906, 29901, 29900, 29941, 29889, 29929, 29929, 29953, 29906, 29929, 29946, 13, 13, 15945, 29908, 13, 3166, 20712, 29890, 293, 1053, 1015, 13, 5215, 4576, 284, 305, 6764, 408, 872, 13, 13, 13, 29937, 26554, 2893, 14903, 29892, 1304, 491, 319, 2409, 29890, 293, 29889, 13, 276, 4924, 353, 525, 29874, 29953, 29947, 29946, 29883, 29929, 29947, 29906, 29883, 29947, 29929, 29900, 29915, 13, 3204, 29918, 276, 4924, 353, 12801, 25711, 17013, 16299, 13, 17519, 29918, 21134, 353, 6213, 13, 2716, 1975, 29918, 265, 353, 6213, 13, 13, 13, 1753, 14955, 7295, 13, 1678, 396, 835, 8260, 4469, 5759, 491, 319, 2409, 29890, 293, 448, 3113, 10365, 29991, 835, 13, 1678, 1015, 29889, 1202, 29918, 4914, 877, 4738, 362, 29918, 3827, 742, 872, 29889, 4409, 877, 5467, 3726, 742, 872, 29889, 11384, 3285, 1870, 519, 29922, 5574, 876, 13, 1678, 396, 835, 1095, 319, 2409, 29890, 293, 8260, 835, 13, 13, 13, 1753, 1623, 8228, 7295, 13, 1678, 396, 835, 8260, 4469, 5759, 491, 319, 2409, 29890, 293, 448, 3113, 10365, 29991, 835, 13, 1678, 1015, 29889, 8865, 29918, 4914, 877, 4738, 362, 29918, 3827, 742, 525, 5467, 3726, 1495, 13, 1678, 396, 835, 1095, 319, 2409, 29890, 293, 8260, 835, 13, 2 ]
graphio/queries/query_parameters.py	JTaeger/graphio	0	33831	<gh_stars>0 def params_create_rels_unwind_from_objects(relationships, property_identifier=None): """ Format Relationship properties into a one level dictionary matching the query generated in `query_create_rels_from_list`. This is necessary because you cannot access nested dictionairies in the UNWIND query. UNWIND { rels } AS rel MATCH (a:Gene), (b:GeneSymbol) WHERE a.sid = rel.start_sid AND b.sid = rel.end_sid AND b.taxid = rel.end_taxid CREATE (a)-[r:MAPS]->(b) SET r = rel.properties Call with params: {'start_sid': 1, 'end_sid': 2, 'end_taxid': '9606', 'properties': {'foo': 'bar} } :param relationships: List of Relationships. :return: List of parameter dictionaries. """ if not property_identifier: property_identifier = 'rels' output = [] for r in relationships: d = {} for k, v in r.start_node_properties.items(): d['start_{}'.format(k)] = v for k, v in r.end_node_properties.items(): d['end_{}'.format(k)] = v d['properties'] = r.properties output.append(d) return {property_identifier: output}	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 1753, 8636, 29918, 3258, 29918, 2674, 29879, 29918, 348, 14800, 29918, 3166, 29918, 12650, 29898, 2674, 800, 14587, 29892, 2875, 29918, 25378, 29922, 8516, 1125, 13, 1678, 9995, 13, 1678, 19191, 6376, 800, 4034, 4426, 964, 263, 697, 3233, 8600, 9686, 278, 2346, 5759, 297, 13, 1678, 421, 1972, 29918, 3258, 29918, 2674, 29879, 29918, 3166, 29918, 1761, 1412, 910, 338, 5181, 1363, 366, 2609, 2130, 9322, 21503, 1794, 2722, 13, 1678, 297, 278, 8291, 29956, 22255, 2346, 29889, 13, 13, 1678, 8291, 29956, 22255, 426, 1104, 29879, 500, 3339, 1104, 13, 1678, 341, 14789, 313, 29874, 29901, 29954, 1600, 511, 313, 29890, 29901, 29954, 1600, 14730, 29897, 13, 1678, 5754, 263, 29889, 29879, 333, 353, 1104, 29889, 2962, 29918, 29879, 333, 5300, 289, 29889, 29879, 333, 353, 1104, 29889, 355, 29918, 29879, 333, 5300, 289, 29889, 20725, 333, 353, 1104, 29889, 355, 29918, 20725, 333, 13, 1678, 14602, 313, 29874, 6817, 29961, 29878, 29901, 1529, 7024, 28895, 29898, 29890, 29897, 13, 1678, 11368, 364, 353, 1104, 29889, 11330, 13, 13, 1678, 8251, 411, 8636, 29901, 13, 4706, 11117, 2962, 29918, 29879, 333, 2396, 29871, 29896, 29892, 525, 355, 29918, 29879, 333, 2396, 29871, 29906, 29892, 525, 355, 29918, 20725, 333, 2396, 525, 29929, 29953, 29900, 29953, 742, 525, 11330, 2396, 11117, 5431, 2396, 525, 1646, 29913, 500, 13, 13, 1678, 584, 3207, 21702, 29901, 2391, 310, 6376, 800, 14587, 29889, 13, 1678, 584, 2457, 29901, 2391, 310, 3443, 21503, 4314, 29889, 13, 1678, 9995, 13, 1678, 565, 451, 2875, 29918, 25378, 29901, 13, 4706, 2875, 29918, 25378, 353, 525, 2674, 29879, 29915, 13, 13, 1678, 1962, 353, 5159, 13, 13, 1678, 363, 364, 297, 21702, 29901, 13, 4706, 270, 353, 6571, 13, 4706, 363, 413, 29892, 325, 297, 364, 29889, 2962, 29918, 3177, 29918, 11330, 29889, 7076, 7295, 13, 9651, 270, 1839, 2962, 648, 29913, 4286, 4830, 29898, 29895, 4638, 353, 325, 13, 4706, 363, 413, 29892, 325, 297, 364, 29889, 355, 29918, 3177, 29918, 11330, 29889, 7076, 7295, 13, 9651, 270, 1839, 355, 648, 29913, 4286, 4830, 29898, 29895, 4638, 353, 325, 13, 4706, 270, 1839, 11330, 2033, 353, 364, 29889, 11330, 13, 4706, 1962, 29889, 4397, 29898, 29881, 29897, 13, 13, 1678, 736, 426, 6799, 29918, 25378, 29901, 1962, 29913, 13, 2 ]
Transforms/Transfer_Learning/TL_Poke_Controller/tl_poke_controller_worker.py	Heron-Repositories/Transfer-Learning-In-Animals	0	94725	<reponame>Heron-Repositories/Transfer-Learning-In-Animals<filename>Transforms/Transfer_Learning/TL_Poke_Controller/tl_poke_controller_worker.py import sys from os import path current_dir = path.dirname(path.abspath(__file__)) while path.split(current_dir)[-1] != r'Heron': current_dir = path.dirname(current_dir) sys.path.insert(0, path.dirname(current_dir)) import numpy as np import serial import threading import pandas as pd from datetime import datetime from Heron.communication.socket_for_serialization import Socket from Heron import general_utils as gu, constants as ct need_parameters = True arduino_serial: serial.Serial avail_time: float avail_freq: int succ_freq: int fail_freq: int sleep_dt = 0.18 abort_at_wrong_poke: bool air_puff_at_wrong_poke: bool trigger_string: str pandas_file: str pandas_trials_record: pd.DataFrame availability_period_is_running = False reward_amount = 1 reward_poke: bool # False is the Old / Right poke, True is the New / Left one air_puff_thread_is_running: bool air_puff_timer = 0 succesful_trials = 0 def add_timestamp_to_filename(save_file): filename = save_file.split('.') date_time = '{}'.format(datetime.now()).replace(':', '-').replace(' ', '_').split('.')[0] save_file = '{}_{}.{}'.format(filename[0], date_time, filename[1]) return save_file def freq_to_signal(freq): freq = int(freq) if freq < 500: freq = 500 if freq > 5000: freq = 5000 return chr(int(freq/500 + 97)).encode('utf-8') def initialise(_worker_object): global arduino_serial global avail_time global avail_freq global succ_freq global fail_freq global abort_at_wrong_poke global air_puff_at_wrong_poke global trigger_string global pandas_file global pandas_trials_record global reward_poke global air_puff_thread_is_running try: parameters = _worker_object.parameters com_port = parameters[0] avail_time = parameters[1] avail_freq = parameters[2] succ_freq = parameters[3] fail_freq = parameters[4] abort_at_wrong_poke = parameters[5] air_puff_at_wrong_poke = parameters[6] trigger_string = parameters[7] pandas_file = parameters[8] except Exception as e: print(e) return False try: arduino_serial = serial.Serial(com_port) except Exception as e: print(e) return False if pandas_file != '': pandas_trials_record = pd.DataFrame(columns=['TimeStamp', 'Start_OR_PelletsGiven']) air_puff_thread_is_running = False reward_poke = True set_poke_tray() worker_object.relic_create_parameters_df(com_port=com_port, avail_time=avail_time, avail_freq=avail_freq, succ_freq=succ_freq, fail_freq=fail_freq, abort_at_wrong_poke=abort_at_wrong_poke, air_puff_at_wrong_poke=air_puff_at_wrong_poke, trigger_string=trigger_string, pandas_file=pandas_file) return True def failure_sound(): if int(fail_freq) != 0: arduino_serial.write(freq_to_signal(fail_freq)) gu.accurate_delay(1200 * sleep_dt) arduino_serial.write(freq_to_signal(500)) def success_sound(): if int(succ_freq) != 0: arduino_serial.write(freq_to_signal(succ_freq)) gu.accurate_delay(1500 * sleep_dt) arduino_serial.write(freq_to_signal(succ_freq)) gu.accurate_delay(1500 * sleep_dt) def availability_sound(): if int(avail_freq) != 0: arduino_serial.write(freq_to_signal(avail_freq)) def add_trial_state_to_trials_record(state): global pandas_trials_record global pandas_file if pandas_file != '': time = datetime.now() row = pd.DataFrame(data={pandas_trials_record.columns[0]: [time], pandas_trials_record.columns[1]: [state]}) pandas_trials_record = pd.concat([pandas_trials_record, row]) def start_availability_thread(): global arduino_serial global availability_period_is_running global avail_time global avail_freq global succ_freq global pandas_file global pandas_trials_record global reward_poke global abort_at_wrong_poke global succesful_trials total_steps = int(avail_time / sleep_dt) availability_period_is_running = True add_trial_state_to_trials_record('Start') bytes_in_buffer = arduino_serial.in_waiting while bytes_in_buffer: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') if '555\r\n' in string_in: gu.accurate_delay(500) arduino_serial.reset_input_buffer() step = 0 while availability_period_is_running: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') success_failure_continue = 2 # 0=success, 1=failure, 2=continue # If the string is either 555 or 666 then if it is for the wrong poke and the abort_at_wrong_poke is on then # fail, otherwise succeed if bytes_in_buffer: if '555\r\n' in string_in: if not reward_poke: success_failure_continue = 0 else: if abort_at_wrong_poke: success_failure_continue = 1 else: success_failure_continue = 0 if '666\r\n' in string_in: if reward_poke: success_failure_continue = 0 else: if abort_at_wrong_poke: success_failure_continue = 1 else: success_failure_continue = 0 if success_failure_continue == 0: try: success_sound() for _ in np.arange(reward_amount): arduino_serial.write('a'.encode('utf-8')) gu.accurate_delay(500) availability_period_is_running = False succesful_trials += 1 print(succesful_trials) except Exception as e: print(e) add_trial_state_to_trials_record(reward_amount) elif step >= total_steps or success_failure_continue == 1: try: failure_sound() availability_period_is_running = False except Exception as e: print(e) add_trial_state_to_trials_record(0) else: try: availability_sound() arduino_serial.read(arduino_serial.in_waiting) availability_period_is_running = True except Exception as e: print(e) gu.accurate_delay(1000 * sleep_dt) step += 1 def set_poke_tray(): global arduino_serial global reward_poke if reward_poke: arduino_serial.write('m'.encode('utf-8')) else: arduino_serial.write('n'.encode('utf-8')) def start_air_puff_thread(): global availability_period_is_running global air_puff_thread_is_running global previous_availability_for_air_puff global air_puff_timer while air_puff_thread_is_running: if availability_period_is_running: air_puff_timer = 0 if not availability_period_is_running: air_puff_timer += 1 if air_puff_timer < 50: arduino_serial.reset_input_buffer() else: # 5 seconds delay air_puff_if_poking_outside_availability() gu.accurate_delay(100) def air_puff_if_poking_outside_availability(): if not availability_period_is_running: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') if bytes_in_buffer: if '555\r\n' in string_in or '666\r\n' in string_in: arduino_serial.write('y'.encode('utf-8')) gu.accurate_delay(100) arduino_serial.write('z'.encode('utf-8')) def start_availability_or_switch_pokes(data, parameters): global availability_period_is_running global air_puff_thread_is_running global trigger_string global reward_amount global reward_poke topic = data[0].decode('utf-8') message = Socket.reconstruct_array_from_bytes_message(data[1:]) air_puff_at_wrong_poke = parameters[5] if air_puff_at_wrong_poke: if not air_puff_thread_is_running: air_puff_thread_is_running = True air_puff_thread = threading.Thread(group=None, target=start_air_puff_thread) air_puff_thread.start() else: air_puff_thread_is_running = False if 'Start' in topic: if not availability_period_is_running: if len(message.shape) > 1: # If the message is sent as a double array message = message[0] if trigger_string == message[0] or trigger_string == 'number': if trigger_string == 'number': reward_amount = int(message[0]) try: if message[0] != -1 and message[0] != '-1': # That allows the result to update without starting another thread avail_thread = threading.Thread(target=start_availability_thread) avail_thread.start() except Exception as e: print(e) result = [np.array([availability_period_is_running])] elif 'Poke' in topic: reward_poke = message[0] if reward_poke == 'Left' or reward_poke == 'New': reward_poke = True if reward_poke == 'Right' or reward_poke == 'Old': reward_poke = False set_poke_tray() result = [np.array([availability_period_is_running])] return result def on_end_of_life(): global arduino_serial global air_puff_thread_is_running global pandas_file global pandas_trials_record if pandas_file != '': pandas_file = add_timestamp_to_filename(pandas_file) pandas_trials_record.to_pickle(pandas_file) air_puff_thread_is_running = False gu.accurate_delay(100) arduino_serial.reset_input_buffer() arduino_serial.close() if __name__ == "__main__": worker_object = gu.start_the_transform_worker_process(work_function=start_availability_or_switch_pokes, end_of_life_function=on_end_of_life, initialisation_function=initialise) worker_object.start_ioloop()	[ 1, 529, 276, 1112, 420, 29958, 18650, 265, 29899, 10913, 20106, 29914, 4300, 571, 29899, 29931, 799, 1076, 29899, 797, 29899, 21645, 1338, 29966, 9507, 29958, 4300, 9514, 29914, 4300, 571, 29918, 29931, 799, 1076, 29914, 14632, 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utility.py	ying-wen/pmln	1	18355	from __future__ import print_function import numpy as np import pandas as pd from sklearn import metrics class Options(object): """Options used by the model.""" def __init__(self): # Model options. # Embedding dimension. self.embedding_size = 32 # The initial learning rate. self.learning_rate = 1. # Number of epochs to train. After these many epochs, the learning # rate decays linearly to zero and the training stops. self.epochs_to_train = 100 # Number of examples for one training step. self.batch_size = 128 self.log_path = './ctr.log' def read_file(path, infinite=True): while True: fi = open(path,'r') for line in fi: yield map(int,line.replace('\n', '').split(' ')) if infinite == False: break yield None def ctr_batch_generator(opts, train=True): if train: file_reader = read_file(opts.train_path, True) else: file_reader = read_file(opts.test_path, False) while True: batch = np.ndarray(shape=(opts.batch_size, opts.sequence_length)) labels = np.ndarray(shape=(opts.batch_size)) for i in xrange(opts.batch_size): single_sample = file_reader.next() if single_sample is None: break target = single_sample[0] temp = single_sample[1:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) assert len(temp) == opts.sequence_length batch[i] = temp labels[i] = target if len(labels) == opts.batch_size and single_sample is not None: yield np.array(batch), labels else: break def get_substitute_cate(sample, target_index, opts): field_i = opts.fields_index_inverse.get(sample[target_index]) if field_i is None: field_i = np.random.choice(opts.fields_index.keys(),1)[0] field_cates = opts.fields_index[field_i] rst = np.random.choice(field_cates,1)[0] if len(field_cates) == 1: rst = np.random.randint(opts.vocabulary_size) return rst def generate_fake_sample(temp, opts): temp_sequence_length = len(temp) temp = temp[0:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) else: temp_sequence_length = opts.sequence_length assert len(temp) == opts.sequence_length targets_to_avoid = set(temp) indices_to_avoid = set() substitute_index = np.random.randint(temp_sequence_length) substitute_target = get_substitute_cate(temp, substitute_index, opts) for _ in range(opts.substitute_num): while substitute_index in indices_to_avoid: substitute_index = np.random.randint(temp_sequence_length) indices_to_avoid.add(substitute_index) count = 0 while substitute_target in targets_to_avoid: if count > 5: break substitute_target = get_substitute_cate(temp, substitute_index, opts) count += 1 targets_to_avoid.add(substitute_target) temp[substitute_index] = substitute_target return temp def generate_discriminant_batch(opts, is_train=True, rate=0.5): data_index = 0 if is_train: file_reader = read_file(opts.train_path) else: file_reader = read_file(opts.test_path) while True: batch = np.ndarray(shape=(opts.batch_size, opts.sequence_length)) labels = [] for i in xrange(opts.batch_size): if np.random.random() > rate: single_sample = file_reader.next() temp = single_sample[1:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) assert len(temp) == opts.sequence_length batch[i] = temp labels.append(1.) else: single_sample = file_reader.next() temp = single_sample[1:opts.sequence_length] batch[i] = generate_fake_sample(temp, opts) labels.append(0.) yield batch, np.array(labels) def read_feat_index(opts): vocabulary_size = 0 reverse_dictionary_raw = np.array(pd.read_csv(opts.featindex, sep='\t', header=None)) reverse_dictionary = {} dictionary = {} for item in reverse_dictionary_raw: reverse_dictionary[int(item[1])] = item[0] dictionary[item[0]] = int(item[1]) if item[1] > vocabulary_size: vocabulary_size = item[1] vocabulary_size = len(dictionary.keys()) print('vocabulary_size: ',vocabulary_size) return reverse_dictionary, dictionary, vocabulary_size def eval_auc(model, opts, target=None, get_prob=None): testing_batch_generator = ctr_batch_generator(opts,train=False) batch_num = 0 y = [] pred = [] for batch, labels in testing_batch_generator: if target is None or get_prob is None: probs = model.predict_proba(batch, batch_size=opts.batch_size, verbose=0) else: probs = get_prob([batch])[0] y.extend(labels) pred.extend([p[0] for p in probs]) batch_num += 1 fpr, tpr, thresholds = metrics.roc_curve(y, pred, pos_label=1) auc = metrics.auc(fpr, tpr) loss = metrics.log_loss(y, pred) print("Total testing sample: ", len(y), " Positive sample: ", sum(y)) opts.auc = auc opts.loss = loss with open(opts.log_path, 'a') as f: f.write(str(opts.__dict__)+'\r') print("AUC:", auc, ', log loss: ', loss)	[ 1, 515, 4770, 29888, 9130, 1649, 1053, 1596, 29918, 2220, 13, 5215, 12655, 408, 7442, 13, 5215, 11701, 408, 10518, 13, 3166, 2071, 19668, 1053, 21556, 13, 13, 1990, 25186, 29898, 3318, 1125, 13, 1678, 9995, 5856, 1304, 491, 29871, 278, 1904, 1213, 15945, 13, 13, 1678, 822, 4770, 2344, 12035, 1311, 1125, 13, 4706, 396, 8125, 3987, 29889, 13, 13, 4706, 396, 2812, 2580, 8497, 9927, 29889, 13, 4706, 1583, 29889, 17987, 8497, 29918, 2311, 353, 29871, 29941, 29906, 13, 13, 4706, 396, 450, 2847, 6509, 6554, 29889, 13, 4706, 1583, 29889, 21891, 29918, 10492, 353, 29871, 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CeptServer.py	bildschirmtext/twistedUlm	4	187957	# -- coding: utf-8 -- ############################################################################### # This file is part of twistedUlm. # # 2010, <NAME> <<EMAIL>> # # twistedUlm is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # twistedUlm is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with twistedUlm. If not, see <http://www.gnu.org/licenses/>. ############################################################################### from twisted.internet.protocol import ServerFactory from twisted.protocols.basic import LineReceiver from twisted.internet.reactor import callLater, connectTCP from httpflavor import twistedHTTPFlavor from basicflavor import DummyFlavor, RelayTest from Relay import RelayFactory class CeptServerProtocol(LineReceiver): """ A instance of this class is created for every new connection. If choosen it can parse a header and stores the bytes received in the first few seconds as userid (useful for the German Btx-system). It handles the communication between the specific server-flavor and the network. It can be ordered to relay a connection to another host or to close a connection, it also tells the flavor that the connection was lost (when the user hangs up). """ def __init__(self, flavor, verbosity, client, getHeader=False, getUserid=False): self.flavor = flavor self.flavor.sendCb = self.send self.flavor.closeCb = self.close self.flavor.relayCb = self.relayConnection self.version = "0" self.txspeed = 120.0 self.rxspeed = 7.5 self.relay=None self.relayConnector=None self.relayData=False self.commandAfterRelay="0#" self.idTimeout = None self.verbosity=verbosity self.client=client self.notifyDataSent = None if getUserid: self.userid = None # means we still want to parse it else: self.userid = "" # we already have an (empty) id if getHeader: self.headerTimeout = callLater(10, self.close) self.state=0 else: self.headerTimeout = None self.state=1 self.headerDone() # just switch to raw-mode (and get user id) def relayConnection(self, host, port, commandAfter, sendHeader=False): """ Should be called by the server-flavor to request a relay of the connection. While the relay is active no data will be passed to the server-flavor and vice versa. """ header = "Version: %s\r\n" % self.version header += "TXspeed: %.1f\r\n" % self.txspeed header += "RXspeed: %.1f\r\n" % self.rxspeed header += "UserID: %s\r\n" % self.userid self.commandAfterRelay=commandAfter self.relay=RelayFactory( self.relayClosed, self.send, sendHeader, header ) self.relayData=True # relay data instead of passing it to the flavor self.relayConnector=connectTCP(host, int(port), self.relay) def relayClosed(self): """ This is called by the Relay handler when it's connection was closed. All data is again passed to the flavor, beginning with the command passed to relayConnection() before. """ if self.relayConnector!=None: self.relayConnector.disconnect() self.relayData=False self.relay=None self.flavor.write(self.commandAfterRelay) def connectionLost(self, reason): """ Connection with the user was lost, either by choice or by accident. If we are relaying data, we close this connection, then we give the flavor the opportunity to clean some stuff up before it is destroyed. """ if self.verbosity>=2: print "Lost connection. ", self.client if self.relay!=None: self.relay=None if self.relayConnector!=None: self.relayConnector.disconnect() self.relayConnector=None self.flavor.connectionLost( reason ) def lineReceived(self,line): """ This exclusively handles the header that may be received in the beginning. It parses known header-values and then switches to raw-mode. """ if self.verbosity>=100: print "->", line if line == "": self.headerDone() else: self.headerTimeout.reset(10) line = line.split(":") if line[0] == "Version": self.version = line[1].strip() elif line[0] == "TXspeed": try: self.txspeed = float(line[1].strip()) except(ValueError): pass elif line[0] == "RXspeed": try: self.rxspeed = float(line[1].strip()) except(ValueError): pass elif line[0] == "UserID": self.userid = line[1].strip() def rawDataReceived(self, data): """ Here we handle data coming from the user. In the first few seconds this may be the user id sent by the terminal, after that it's user-input. This is either passed to the flavor or relayed to a remote host. """ if self.verbosity>=100: print "->", for c in data: print "0x%x (%s)"%(ord(c),c), print if self.state == 1: # we only wait for 1 second between characters of the user id self.idTimeout.reset(1) self.userid += data else: if self.relayData: self.relay.send(data) else: self.flavor.write(data) def headerDone(self): """ Called by lineReceived() when a double newline was received. Switch to raw mode (from line mode) and (maybe) try to receive the user-id. """ if self.verbosity>=3: print "\tHeader done. ", self.client if self.verbosity>=4: print "\t\tVersion:",self.version print "\t\tTX speed:",self.txspeed print "\t\tRX speed:",self.rxspeed # header complete, so we don't need the timeout anymore if self.headerTimeout != None: self.headerTimeout.cancel() del(self.headerTimeout) self.setRawMode() if self.userid == None: # we still need to get the user id, so we wait 3 seconds for data # from the terminal self.state = 1 # header done, check for userid next self.userid="" if self.verbosity>=5: print "\t\tWaiting for User ID..." self.idTimeout = callLater(3, self.useridDone) else: # either we already received the user id through the header or we # don't want/need to parse it self.useridDone() def useridDone(self): """ Called after a timeout either from headerDone() or rawDataReceived(). We store the userid as a nice hexadecimal string and pass it to the flavor. """ newid="" for c in self.userid: newid+="%x"%ord(c) # make a string from those raw bytes self.userid=newid if self.verbosity>=4: print "\t\tUser ID:", self.userid self.state = 2 # everything else is just passed to the flavor self.flavor.userid=self.userid self.flavor.hello() def send(self,data): """ Data passed to this function is just passed onto the socket. We know (or assume) the speed of the connection, so we notify the flavor when all data is sent (so it may choose not to send too much data at once.) """ if self.verbosity>=101: print "<-", data self.transport.write(data) if not self.relayData: if self.notifyDataSent!=None and self.notifyDataSent.active(): self.notifyDataSent.delay( float(len(data))/self.txspeed ) else: self.notifyDataSent=callLater( float(len(data))/self.txspeed, self.flavor.dataSent ) def close(self, time=0): """ This is either called by the flavor (on user's request) or after the header timed out. """ if self.verbosity>=2: print "Closing connection in %i seconds. "%time, self.client if time>0: callLater(time, self.transport.loseConnection) else: self.transport.loseConnection() class CeptServerFactory(ServerFactory): """ Creates CeptServer instances based on the choosen server-flavor. """ def __init__(self, serverType, verbosity, flavorArgs): self.serverType = serverType self.flavorArgs = flavorArgs self.verbosity = verbosity def buildProtocol(self, addr): if self.verbosity>=2: print "New connection from", addr if self.serverType == "http": flavor=twistedHTTPFlavor( self.verbosity, *self.flavorArgs ) else: flavor=DummyFlavor() p = CeptServerProtocol( flavor, self.verbosity, addr, getHeader=True, getUserid=True ) p.factory = self return p	[ 1, 396, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 13, 13383, 13383, 13383, 13383, 7346, 4136, 2277, 29937, 13, 29937, 1678, 910, 934, 338, 760, 310, 3252, 12652, 29965, 21457, 29889, 13, 29937, 13, 29937, 268, 29906, 29900, 29896, 29900, 29892, 529, 5813, 29958, 3532, 26862, 6227, 6778, 13, 29937, 13, 29937, 1678, 3252, 12652, 29965, 21457, 338, 3889, 7047, 29901, 366, 508, 2654, 391, 2666, 372, 322, 29914, 272, 6623, 13, 29937, 1678, 372, 1090, 278, 4958, 310, 278, 15143, 4593, 5236, 19245, 408, 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main.py	felipedavi/MyBrowserProject	1	67410	<reponame>felipedavi/MyBrowserProject # -- coding: utf-8 -- __author__ = "<NAME>" __license__ = "MIT" """home.py: Navegador Open Source """ from PyQt5.QtWidgets import QApplication, QMainWindow,QToolButton, QLineEdit, QMessageBox from PyQt5.QtWebEngineWidgets import QWebEngineView from PyQt5.QtCore import QUrl, QSize from PyQt5.QtGui import QIcon, QPixmap home_url = "https://www.google.com" facebook_url = "https://www.facebook.com" twitter_url = "https://www.twitter.com" youtube_url = "https://www.youtube.com" def home(mainWindow): web.load(QUrl(home_url)) def reload(mainWindow): web.reload() def back(mainWindow): web.back() def forward(mainWindow): web.forward() def go(mainWindow): go_url = go_line.text() web.load(QUrl(go_url)) def facebook(mainWindow): web.load(QUrl(facebook_url)) def twitter(mainWindow): web.load(QUrl(twitter_url)) def youtube(mainWindow): web.load(QUrl(youtube_url)) def download(item): item.accept() msg = QMessageBox() msg.setWindowTitle("DOWNLOAD") msg.setText("O SEU DOWNLOAD FOI INICIALIZADO") msg.setIcon(QMessageBox.Warning) msg.exec_() application = QApplication([]) mainWindow= QMainWindow() mainWindow.setGeometry(0,0,1015,768) mainWindow.setMinimumWidth(1015) mainWindow.setMaximumWidth(1015) mainWindow.setMinimumHeight(768) mainWindow.setMaximumHeight(768) mainWindow.setWindowTitle("MyBrowser") mainWindow.setStyleSheet("background-color:rgb(0,0,0);") mainWindow.setWindowIcon(QIcon("browser.png")) web = QWebEngineView(mainWindow) web.setGeometry(0,30,1015,768) web.setStyleSheet("background-color:rgb(255,255,255);") web.load(QUrl(home_url)) home_button = QToolButton(mainWindow) home_button.setGeometry(10,3,25,25) home_button.setStyleSheet("background-color:transparent;") home_button_icon = QIcon() home_button_icon.addPixmap(QPixmap("home.png")) home_button.setIcon(home_button_icon) home_button.clicked.connect(home) reload_button = QToolButton(mainWindow) reload_button.setGeometry(60,3,25,25) reload_button.setStyleSheet("background-color:transparent;") reload_button_icon = QIcon() reload_button_icon.addPixmap(QPixmap("reload.png")) reload_button.setIcon(reload_button_icon) reload_button.clicked.connect(reload) back_button = QToolButton(mainWindow) back_button.setGeometry(140,3,25,25) back_button.setStyleSheet("background-color:transparent;") back_button_icon = QIcon() back_button_icon.addPixmap(QPixmap("back.png")) back_button.setIcon(back_button_icon) back_button.clicked.connect(back) forward_button = QToolButton(mainWindow) forward_button.setGeometry(180,3,25,25) forward_button.setStyleSheet("background-color:transparent;") forward_button_icon = QIcon() forward_button_icon.addPixmap(QPixmap("forward.png")) forward_button.setIcon(forward_button_icon) forward_button.clicked.connect(forward) go_line = QLineEdit(mainWindow) go_line.setGeometry(280,3,300,25) go_line.setStyleSheet("background-color:rgb(255,255,255);") go_button = QToolButton(mainWindow) go_button.setGeometry(600,3,25,25) go_button.setStyleSheet("background-color:transparent;") go_button_icon = QIcon() go_button_icon.addPixmap(QPixmap("go.png")) go_button.setIcon(go_button_icon) go_button.clicked.connect(go) facebook_button = QToolButton(mainWindow) facebook_button.setGeometry(905,3,50,25) facebook_button.setStyleSheet("background-color:transparent;") facebook_button_icon = QIcon() facebook_button_icon.addPixmap(QPixmap("fb.png")) facebook_button.setIcon(facebook_button_icon) facebook_button.setIconSize(QSize(22,22)) facebook_button.clicked.connect(facebook) twitter_button = QToolButton(mainWindow) twitter_button.setGeometry(940,3,50,25) twitter_button.setStyleSheet("background-color:transparent;") twitter_button_icon = QIcon() twitter_button_icon.addPixmap(QPixmap("tw.png")) twitter_button.setIcon(twitter_button_icon) twitter_button.setIconSize(QSize(22,22)) twitter_button.clicked.connect(twitter) youtube_button = QToolButton(mainWindow) youtube_button.setGeometry(975,3,50,25) youtube_button.setStyleSheet("background-color:transparent;") youtube_button_icon = QIcon() youtube_button_icon.addPixmap(QPixmap("yt.png")) youtube_button.setIcon(youtube_button_icon) youtube_button.setIconSize(QSize(22,22)) youtube_button.clicked.connect(youtube) mainWindow.show() application.exec_()	[ 1, 529, 276, 1112, 420, 29958, 13287, 666, 287, 17345, 29914, 3421, 21537, 7653, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 1649, 8921, 1649, 353, 9872, 5813, 11903, 13, 1649, 506, 1947, 1649, 353, 376, 26349, 29908, 13, 15945, 29908, 5184, 29889, 2272, 29901, 405, 1351, 29887, 3136, 4673, 7562, 9995, 13, 13, 3166, 10772, 17303, 29945, 29889, 17303, 8801, 29879, 1053, 660, 4873, 29892, 660, 6330, 5907, 29892, 29984, 12229, 3125, 29892, 660, 3542, 6103, 29892, 660, 3728, 3313, 13, 3166, 10772, 17303, 29945, 29889, 17303, 3609, 12412, 8801, 29879, 1053, 660, 3609, 12412, 1043, 13, 3166, 10772, 17303, 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podium_api/types/user.py	autosportlabs/podium-api	1	157482	#!/usr/bin/env python # -- coding: utf-8 -- class PodiumUser(object): """ Object that represents a particular User. Attributes: user_id (int): User id uri (string): URI for the User. username (string): The User's username. description (string): The User's description. avatar_url (string): User's avatar image url. links (list): 3rd party links for the user. friendships_uri (string): URI to friends list. followers_uri (string): URI to followers list. friendship_uri (string): If this User has been friended events_uri (string): URI to events for this user venues_uri (string): URI to venues this user particiated at by the user this attr will have a value, otherwise None. Defaults to None. """ def __init__(self, user_id, uri, username, description, avatar_url, profile_image_url, links, friendships_uri, followers_uri, friendship_uri, events_uri, venues_uri): self.user_id = user_id self.uri = uri self.username = username self.description = description self.avatar_url = avatar_url self.profile_image_url = profile_image_url self.links = links self.friendships_uri = friendships_uri self.followers_uri = followers_uri self.friendship_uri = friendship_uri self.events_uri = events_uri self.venues_uri = venues_uri def get_user_from_json(json): """ Returns a PodiumUser object from the json dict received from podium api. Args: json (dict): Dict of data from REST api Return: PodiumUser: The PodiumUser object for the data. """ return PodiumUser(json['id'], json['URI'], json['username'], json['description'], json['avatar_url'], json['profile_image_url'], json['links'], json['friendships_uri'], json['followers_uri'], json.get("friendship_uri", None), json['events_uri'], json['venues_uri'] )	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 30004, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 30004, 13, 30004, 13, 1990, 8594, 1974, 2659, 29898, 3318, 1125, 30004, 13, 1678, 9995, 30004, 13, 1678, 4669, 393, 11524, 263, 3153, 4911, 22993, 13, 30004, 13, 1678, 3579, 15801, 29901, 1068, 30004, 13, 4706, 3579, 1792, 29918, 333, 1068, 313, 524, 1125, 4911, 1178, 30004, 13, 30004, 13, 4706, 3579, 5338, 1068, 313, 1807, 1125, 23539, 363, 278, 4911, 22993, 13, 30004, 13, 4706, 3579, 6786, 1068, 313, 1807, 1125, 450, 4911, 29915, 29879, 8952, 22993, 13, 30004, 13, 4706, 3579, 8216, 1068, 313, 1807, 1125, 450, 4911, 29915, 29879, 6139, 22993, 13, 30004, 13, 4706, 3579, 485, 14873, 29918, 2271, 1068, 313, 1807, 1125, 4911, 29915, 29879, 1029, 14873, 1967, 3142, 22993, 13, 30004, 13, 4706, 3579, 4965, 1068, 313, 1761, 1125, 29871, 29941, 5499, 6263, 2988, 363, 278, 1404, 22993, 13, 30004, 13, 4706, 3579, 18326, 9981, 29918, 5338, 1068, 313, 1807, 1125, 23539, 304, 7875, 1051, 22993, 13, 30004, 13, 4706, 3579, 23031, 414, 29918, 5338, 1068, 313, 1807, 1125, 23539, 304, 1101, 414, 1051, 22993, 13, 30004, 13, 4706, 3579, 18326, 3527, 29918, 5338, 1068, 313, 1807, 1125, 960, 445, 4911, 756, 1063, 3484, 2760, 30004, 13, 4706, 6756, 13, 4706, 3579, 13604, 29918, 5338, 1068, 313, 1807, 1125, 23539, 304, 4959, 363, 445, 1404, 30004, 13, 4706, 6756, 13, 4706, 3579, 854, 1041, 29918, 5338, 1068, 313, 1807, 1125, 23539, 304, 6003, 1041, 445, 1404, 21933, 630, 472, 30004, 13, 308, 6756, 13, 4706, 491, 278, 1404, 445, 12421, 674, 505, 263, 995, 29892, 6467, 6213, 29889, 13109, 29879, 304, 30004, 13, 4706, 6213, 22993, 13, 1678, 9995, 30004, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 1404, 29918, 333, 29892, 21333, 29892, 8952, 29892, 6139, 29892, 1029, 14873, 29918, 2271, 29892, 8722, 29918, 3027, 29918, 2271, 11167, 13, 462, 2988, 29892, 5121, 9981, 29918, 5338, 29892, 1101, 414, 29918, 5338, 29892, 27994, 29918, 5338, 29892, 4959, 29918, 5338, 11167, 13, 462, 6003, 1041, 29918, 5338, 1125, 30004, 13, 4706, 1583, 29889, 1792, 29918, 333, 353, 1404, 29918, 333, 30004, 13, 4706, 1583, 29889, 5338, 353, 21333, 30004, 13, 4706, 1583, 29889, 6786, 353, 8952, 30004, 13, 4706, 1583, 29889, 8216, 353, 6139, 30004, 13, 4706, 1583, 29889, 485, 14873, 29918, 2271, 353, 1029, 14873, 29918, 2271, 30004, 13, 4706, 1583, 29889, 10185, 29918, 3027, 29918, 2271, 353, 8722, 29918, 3027, 29918, 2271, 30004, 13, 4706, 1583, 29889, 4965, 353, 2988, 30004, 13, 4706, 1583, 29889, 18326, 9981, 29918, 5338, 353, 5121, 9981, 29918, 5338, 30004, 13, 4706, 1583, 29889, 23031, 414, 29918, 5338, 353, 1101, 414, 29918, 5338, 30004, 13, 4706, 1583, 29889, 18326, 3527, 29918, 5338, 353, 27994, 29918, 5338, 30004, 13, 4706, 1583, 29889, 13604, 29918, 5338, 353, 4959, 29918, 5338, 30004, 13, 4706, 1583, 29889, 854, 1041, 29918, 5338, 353, 6003, 1041, 29918, 5338, 30004, 13, 30004, 13, 30004, 13, 1753, 679, 29918, 1792, 29918, 3166, 29918, 3126, 29898, 3126, 1125, 30004, 13, 1678, 9995, 30004, 13, 1678, 16969, 263, 8594, 1974, 2659, 1203, 515, 278, 4390, 9657, 4520, 515, 2532, 1974, 7882, 22993, 13, 30004, 13, 1678, 826, 3174, 29901, 30004, 13, 4706, 4390, 313, 8977, 1125, 360, 919, 310, 848, 515, 16759, 7882, 30004, 13, 30004, 13, 1678, 7106, 29901, 30004, 13, 4706, 8594, 1974, 2659, 29901, 450, 8594, 1974, 2659, 1203, 363, 278, 848, 22993, 13, 1678, 9995, 30004, 13, 1678, 736, 8594, 1974, 2659, 29898, 3126, 1839, 333, 7464, 30004, 13, 462, 418, 4390, 1839, 15551, 7464, 30004, 13, 462, 418, 4390, 1839, 6786, 7464, 30004, 13, 462, 418, 4390, 1839, 8216, 7464, 30004, 13, 462, 418, 4390, 1839, 485, 14873, 29918, 2271, 7464, 30004, 13, 462, 418, 4390, 1839, 10185, 29918, 3027, 29918, 2271, 7464, 30004, 13, 462, 418, 4390, 1839, 4965, 7464, 30004, 13, 462, 418, 4390, 1839, 18326, 9981, 29918, 5338, 7464, 30004, 13, 462, 418, 4390, 1839, 23031, 414, 29918, 5338, 7464, 30004, 13, 462, 418, 4390, 29889, 657, 703, 18326, 3527, 29918, 5338, 613, 6213, 511, 30004, 13, 462, 418, 4390, 1839, 13604, 29918, 5338, 7464, 30004, 13, 462, 418, 4390, 1839, 854, 1041, 29918, 5338, 2033, 30004, 13, 462, 418, 1723, 30004, 13, 2 ]
tests/model/library/api/test_casestep_resource.py	Mozilla-GitHub-Standards/2a028a7541b867ed4d376d6d9a172a6885fe44030078c12a2b9428efabf22ab7	0	31114	<reponame>Mozilla-GitHub-Standards/2a028a7541b867ed4d376d6d9a172a6885fe44030078c12a2b9428efabf22ab7 """ Tests for CaseStepResource api. """ from tests.case.api.crud import ApiCrudCases import logging mozlogger = logging.getLogger('moztrap.test') class CaseStepResourceTest(ApiCrudCases): @property def factory(self): """The model factory for this object.""" return self.F.CaseStepFactory() @property def resource_name(self): return "casestep" @property def permission(self): """String defining the permission required for Create, Update, and Delete. """ return "library.manage_cases" @property def new_object_data(self): """Generates a dictionary containing the field names and auto-generated values needed to create a unique object. The output of this method can be sent in the payload parameter of a POST message. """ modifiers = (self.datetime, self.resource_name) self.caseversion_fixture = self.F.CaseVersionFactory.create() fields = { u"caseversion": unicode( self.get_detail_url("caseversion", str(self.caseversion_fixture.id))), u"number": 1, u"instruction": u"instruction 1 %s" % self.datetime, u"expected": u"expected 1 %s" % self.datetime, } return fields def backend_object(self, id): """Returns the object from the backend, so you can query it's values in the database for validation. """ return self.model.CaseStep.everything.get(id=id) def backend_data(self, backend_obj): """Query's the database for the object's current values. Output is a dictionary that should match the result of getting the object's detail via the API, and can be used to verify API output. Note: both keys and data should be in unicode """ actual = { u"id": backend_obj.id, u"caseversion": unicode( self.get_detail_url("caseversion", str(backend_obj.caseversion.id))), u"instruction": unicode(backend_obj.instruction), u"expected": unicode(backend_obj.expected), u"number": backend_obj.number, u"resource_uri": unicode( self.get_detail_url(self.resource_name, str(backend_obj.id))) } return actual @property def read_create_fields(self): """caseversion is read-only""" return ["caseversion"] # overrides from crud.py # additional test cases, if any # validation cases	[ 1, 529, 276, 1112, 420, 29958, 29924, 2112, 2911, 29899, 28712, 16046, 29899, 11042, 3163, 29914, 29906, 29874, 29900, 29906, 29947, 29874, 29955, 29945, 29946, 29896, 29890, 29947, 29953, 29955, 287, 29946, 29881, 29941, 29955, 29953, 29881, 29953, 29881, 29929, 29874, 29896, 29955, 29906, 29874, 29953, 29947, 29947, 29945, 1725, 29946, 29946, 29900, 29941, 29900, 29900, 29955, 29947, 29883, 29896, 29906, 29874, 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29908, 2611, 4080, 29871, 29896, 1273, 29879, 29908, 1273, 1583, 29889, 12673, 29892, 13, 9651, 318, 29908, 9684, 1115, 318, 29908, 9684, 29871, 29896, 1273, 29879, 29908, 1273, 1583, 29889, 12673, 29892, 13, 4706, 500, 13, 13, 4706, 736, 4235, 13, 13, 13, 1678, 822, 14998, 29918, 3318, 29898, 1311, 29892, 1178, 1125, 13, 4706, 9995, 11609, 29879, 278, 1203, 515, 278, 14998, 29892, 577, 366, 508, 2346, 372, 29915, 29879, 1819, 297, 13, 4706, 278, 2566, 363, 8845, 29889, 13, 4706, 9995, 13, 4706, 736, 1583, 29889, 4299, 29889, 8259, 14448, 29889, 17991, 1918, 29889, 657, 29898, 333, 29922, 333, 29897, 13, 13, 13, 1678, 822, 14998, 29918, 1272, 29898, 1311, 29892, 14998, 29918, 5415, 1125, 13, 4706, 9995, 3010, 29915, 29879, 278, 2566, 363, 278, 1203, 29915, 29879, 1857, 1819, 29889, 10604, 338, 263, 13, 4706, 8600, 393, 881, 1993, 278, 1121, 310, 2805, 278, 1203, 29915, 29879, 9493, 13, 4706, 3025, 278, 3450, 29892, 322, 508, 367, 1304, 304, 11539, 3450, 1962, 29889, 13, 13, 4706, 3940, 29901, 1716, 6611, 322, 848, 881, 367, 297, 29104, 13, 4706, 9995, 13, 4706, 3935, 353, 426, 13, 9651, 318, 29908, 333, 1115, 14998, 29918, 5415, 29889, 333, 29892, 13, 9651, 318, 29908, 4878, 3259, 1115, 29104, 29898, 13, 18884, 1583, 29889, 657, 29918, 16432, 29918, 2271, 703, 4878, 3259, 613, 13, 462, 1678, 851, 29898, 27852, 29918, 5415, 29889, 4878, 3259, 29889, 333, 876, 511, 13, 9651, 318, 29908, 2611, 4080, 1115, 29104, 29898, 27852, 29918, 5415, 29889, 2611, 4080, 511, 13, 9651, 318, 29908, 9684, 1115, 29104, 29898, 27852, 29918, 5415, 29889, 9684, 511, 13, 9651, 318, 29908, 4537, 1115, 14998, 29918, 5415, 29889, 4537, 29892, 13, 9651, 318, 29908, 10314, 29918, 5338, 1115, 29104, 29898, 13, 18884, 1583, 29889, 657, 29918, 16432, 29918, 2271, 29898, 1311, 29889, 10314, 29918, 978, 29892, 851, 29898, 27852, 29918, 5415, 29889, 333, 4961, 13, 4706, 500, 13, 4706, 736, 3935, 13, 13, 13, 1678, 732, 6799, 13, 1678, 822, 1303, 29918, 3258, 29918, 9621, 29898, 1311, 1125, 13, 4706, 9995, 4878, 3259, 338, 1303, 29899, 6194, 15945, 29908, 13, 4706, 736, 6796, 4878, 3259, 3108, 13, 13, 1678, 396, 975, 24040, 515, 2181, 566, 29889, 2272, 13, 13, 1678, 396, 5684, 1243, 4251, 29892, 565, 738, 13, 13, 1678, 396, 8845, 4251, 13, 2 ]
split.py	ghukill/bookscanner	0	56640	<reponame>ghukill/bookscanner<gh_stars>0 # split import cv2 from distutils.version import StrictVersion import imutils import logging import matplotlib as plt import numpy as np from PIL import Image import os # setup logger logging.basicConfig(level=logging.DEBUG) # parso shims logging.getLogger('parso.python.diff').disabled = True logging.getLogger('parso.cache').disabled = True logger = logging.getLogger(__name__) def split_page( input_filepath, cross_section_height=20, cross_section_origin='bottom', kernel_size=3, mid_range=None, split_image=True, split_padding=10, delete_original=True): ''' Focus on area roughly in the middle, 1500-2500 - will be better to handle % of image.shape ''' # read image from filepath image = cv2.imread(input_filepath, 0) # make sure double page if image.shape[1] / image.shape[0] > 1.25: # debug metrics = { 'filepath':input_filepath, 'shape':image.shape, } # if cross section None, use full height if cross_section_height == None: cross_section_height = image.shape[0] # set mid-section interval if mid_range == None: logger.debug('determining mid-range pixels') mid_range = [int(image.shape[1]/2 - 200), int(image.shape[1]/2 + 200)] metrics['mid_range'] = mid_range # get section to work with if cross_section_origin == 'top': image_cross_section = image[0:cross_section_height, mid_range[0]:mid_range[1]] elif cross_section_origin == 'bottom': image_cross_section = image[-cross_section_height:image.shape[0], mid_range[0]:mid_range[1]] # get horizontal gradient sobelx = cv2.Sobel( image_cross_section, cv2.CV_64F, 1, 0, ksize=kernel_size ) # sum columns col_sums = np.sum(sobelx, axis=0) # plot # plt.pyplot.plot(col_sums) # get center line cl_index_rel = np.argmax(col_sums) cl_index = mid_range[0] + cl_index_rel metrics['cl_index'] = cl_index # check metrics['halfway_percentage'] = cl_index / image.shape[1] # split image if split_image: # get filename root filename_root, filename_ext = input_filepath.split('/')[-1].split('.') # split left page l_img = image[0:image.shape[0], 0:(cl_index + split_padding)] l_filepath = input_filepath.replace(filename_root, '%s_0' % filename_root) cv2.imwrite(l_filepath, l_img) # split right page r_img = image[0:image.shape[0], (cl_index - split_padding):image.shape[1]] r_filepath = input_filepath.replace(filename_root, '%s_1' % filename_root) cv2.imwrite(r_filepath, r_img) # delete original if delete_original: os.remove(input_filepath) # debug logger.debug(metrics) return metrics else: logger.debug('appears to be single page') return { 'filepath':input_filepath, 'shape':image.shape, }	[ 1, 529, 276, 1112, 420, 29958, 12443, 2679, 453, 29914, 2909, 1557, 7310, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 6219, 13, 13, 5215, 13850, 29906, 13, 3166, 1320, 13239, 29889, 3259, 1053, 3767, 919, 6594, 13, 5215, 527, 13239, 13, 5215, 12183, 13, 5215, 22889, 408, 14770, 13, 5215, 12655, 408, 7442, 13, 3166, 349, 6227, 1053, 7084, 13, 5215, 2897, 13, 13, 13, 29937, 6230, 17927, 13, 21027, 29889, 16121, 3991, 29898, 5563, 29922, 21027, 29889, 18525, 29897, 13, 29937, 610, 578, 528, 9893, 13, 21027, 29889, 657, 16363, 877, 862, 578, 29889, 4691, 29889, 12765, 2824, 18279, 353, 5852, 13, 21027, 29889, 657, 16363, 877, 862, 578, 29889, 8173, 2824, 18279, 353, 5852, 13, 21707, 353, 12183, 29889, 657, 16363, 22168, 978, 1649, 29897, 13, 13, 13, 1753, 6219, 29918, 3488, 29898, 13, 12, 2080, 29918, 1445, 2084, 29892, 13, 12, 19128, 29918, 2042, 29918, 3545, 29922, 29906, 29900, 29892, 13, 12, 19128, 29918, 2042, 29918, 12574, 2433, 8968, 742, 13, 12, 17460, 29918, 2311, 29922, 29941, 29892, 13, 12, 6563, 29918, 3881, 29922, 8516, 29892, 13, 12, 5451, 29918, 3027, 29922, 5574, 29892, 13, 12, 5451, 29918, 12791, 29922, 29896, 29900, 29892, 13, 12, 8143, 29918, 13492, 29922, 5574, 1125, 13, 13, 12, 12008, 13, 12, 20560, 373, 4038, 20928, 297, 278, 7256, 29892, 29871, 29896, 29945, 29900, 29900, 29899, 29906, 29945, 29900, 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6213, 29901, 13, 12, 12, 12, 21707, 29889, 8382, 877, 4801, 837, 2827, 7145, 29899, 3881, 17036, 1495, 13, 12, 12, 12, 6563, 29918, 3881, 353, 518, 524, 29898, 3027, 29889, 12181, 29961, 29896, 16261, 29906, 448, 29871, 29906, 29900, 29900, 511, 938, 29898, 3027, 29889, 12181, 29961, 29896, 16261, 29906, 718, 29871, 29906, 29900, 29900, 4638, 13, 12, 12, 12, 2527, 10817, 1839, 6563, 29918, 3881, 2033, 353, 7145, 29918, 3881, 13, 13, 12, 12, 29937, 679, 4004, 304, 664, 411, 13, 12, 12, 361, 4891, 29918, 2042, 29918, 12574, 1275, 525, 3332, 2396, 13, 12, 12, 12, 3027, 29918, 19128, 29918, 2042, 353, 1967, 29961, 29900, 29901, 19128, 29918, 2042, 29918, 3545, 29892, 7145, 29918, 3881, 29961, 29900, 5387, 6563, 29918, 3881, 29961, 29896, 5262, 13, 12, 12, 23681, 4891, 29918, 2042, 29918, 12574, 1275, 525, 8968, 2396, 13, 12, 12, 12, 3027, 29918, 19128, 29918, 2042, 353, 1967, 14352, 19128, 29918, 2042, 29918, 3545, 29901, 3027, 29889, 12181, 29961, 29900, 1402, 7145, 29918, 3881, 29961, 29900, 5387, 6563, 29918, 3881, 29961, 29896, 5262, 13, 13, 12, 12, 29937, 679, 14698, 16030, 13, 12, 12, 578, 6596, 29916, 353, 13850, 29906, 29889, 29903, 711, 295, 29898, 13, 12, 12, 12, 3027, 29918, 19128, 29918, 2042, 29892, 13, 12, 12, 12, 11023, 29906, 29889, 15633, 29918, 29953, 29946, 29943, 29892, 13, 12, 12, 12, 29896, 29892, 13, 12, 12, 12, 29900, 29892, 13, 12, 12, 12, 2039, 675, 29922, 17460, 29918, 2311, 13, 12, 12, 29897, 13, 13, 12, 12, 29937, 2533, 4341, 13, 12, 12, 1054, 29918, 2083, 29879, 353, 7442, 29889, 2083, 29898, 578, 6596, 29916, 29892, 9685, 29922, 29900, 29897, 13, 13, 12, 12, 29937, 6492, 13, 12, 12, 29937, 14770, 29889, 2272, 5317, 29889, 5317, 29898, 1054, 29918, 2083, 29879, 29897, 13, 13, 12, 12, 29937, 679, 4818, 1196, 13, 12, 12, 695, 29918, 2248, 29918, 2674, 353, 7442, 29889, 1191, 3317, 29898, 1054, 29918, 2083, 29879, 29897, 13, 12, 12, 695, 29918, 2248, 353, 7145, 29918, 3881, 29961, 29900, 29962, 718, 1067, 29918, 2248, 29918, 2674, 13, 12, 12, 2527, 10817, 1839, 695, 29918, 2248, 2033, 353, 1067, 29918, 2248, 13, 13, 12, 12, 29937, 1423, 13, 12, 12, 2527, 10817, 1839, 24498, 1582, 29918, 25376, 482, 2033, 353, 1067, 29918, 2248, 847, 1967, 29889, 12181, 29961, 29896, 29962, 13, 13, 12, 12, 29937, 6219, 1967, 13, 12, 12, 361, 6219, 29918, 3027, 29901, 13, 13, 12, 12, 12, 29937, 679, 10422, 3876, 13, 12, 12, 12, 9507, 29918, 4632, 29892, 10422, 29918, 1062, 353, 1881, 29918, 1445, 2084, 29889, 5451, 11219, 1495, 14352, 29896, 1822, 5451, 12839, 1495, 13, 13, 12, 12, 12, 29937, 6219, 2175, 1813, 13, 12, 12, 12, 29880, 29918, 2492, 353, 1967, 29961, 29900, 29901, 3027, 29889, 12181, 29961, 29900, 1402, 29871, 29900, 5919, 695, 29918, 2248, 718, 6219, 29918, 12791, 4638, 13, 12, 12, 12, 29880, 29918, 1445, 2084, 353, 1881, 29918, 1445, 2084, 29889, 6506, 29898, 9507, 29918, 4632, 29892, 14210, 29879, 29918, 29900, 29915, 1273, 10422, 29918, 4632, 29897, 13, 12, 12, 12, 11023, 29906, 29889, 326, 3539, 29898, 29880, 29918, 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12, 12, 29915, 1445, 2084, 2396, 2080, 29918, 1445, 2084, 29892, 13, 12, 12, 12, 29915, 12181, 2396, 3027, 29889, 12181, 29892, 13, 12, 12, 29913, 13, 13, 13, 13, 2 ]
Exercicios_entregar/Tarefa_lista2_ex3.py	joao-barabba/Exercicios_Python	0	199480	<reponame>joao-barabba/Exercicios_Python n1=int(input('Digite o primeiro valor: ')) n2=int(input('Digite o segundo valor: ')) o=(input('Digite o operador para conta: ')) if o=='+': r=n1+n2 print(f'O resultado da conta é {r:,}') elif o=='-': r=n1-n2 print(f'O resultado da conta é {r:,}') elif o=='': r==n1n2 print(f'O resultado da conta é {r:,}') elif o=='/': r==n1/n2 print(f'O resultado da conta é {r:,}') else: print('Operador não reconhecido ERRO!!!')	[ 1, 529, 276, 1112, 420, 29958, 2212, 6241, 29899, 1646, 370, 2291, 29914, 1252, 6269, 19382, 29918, 11980, 13, 29876, 29896, 29922, 524, 29898, 2080, 877, 14991, 568, 288, 19695, 16497, 29901, 525, 876, 13, 29876, 29906, 29922, 524, 29898, 2080, 877, 14991, 568, 288, 14729, 16497, 29901, 525, 876, 13, 29877, 7607, 2080, 877, 14991, 568, 288, 1751, 3136, 1702, 640, 29874, 29901, 525, 876, 13, 13, 361, 288, 1360, 18717, 2396, 13, 1678, 364, 29922, 29876, 29896, 29974, 29876, 29906, 13, 1678, 1596, 29898, 29888, 29915, 29949, 24578, 1146, 640, 29874, 904, 426, 29878, 29901, 29892, 29913, 1495, 13, 23681, 288, 1360, 28560, 2396, 13, 1678, 364, 29922, 29876, 29896, 29899, 29876, 29906, 13, 1678, 1596, 29898, 29888, 29915, 29949, 24578, 1146, 640, 29874, 904, 426, 29878, 29901, 29892, 29913, 1495, 13, 23681, 288, 1360, 29915, 29930, 2396, 13, 1678, 364, 1360, 29876, 29896, 29930, 29876, 29906, 13, 1678, 1596, 29898, 29888, 29915, 29949, 24578, 1146, 640, 29874, 904, 426, 29878, 29901, 29892, 29913, 1495, 13, 23681, 288, 1360, 29915, 29914, 2396, 13, 1678, 364, 1360, 29876, 29896, 29914, 29876, 29906, 13, 1678, 1596, 29898, 29888, 29915, 29949, 24578, 1146, 640, 29874, 904, 426, 29878, 29901, 29892, 29913, 1495, 13, 2870, 29901, 13, 1678, 1596, 877, 7094, 3136, 8145, 8265, 354, 13321, 8982, 1672, 21004, 1495, 4706, 13, 4706, 2 ]
michiru/modules/seenbot.py	moeIO/michiru	1	61981	# Seenbot module. from datetime import datetime import json from michiru import db, personalities from michiru.modules import command, hook _ = personalities.localize ## Module information. __name__ = 'seenbot' __author__ = 'Shiz' __license__ = 'WTFPL' __desc__ = 'Tells when someone was last seen.' ## Database stuff and constants. db.table('seen', { 'id': db.ID, 'server': (db.STRING, db.INDEX), 'nickname': (db.STRING, db.INDEX), 'action': db.INT, 'data': db.STRING, 'time': db.DATETIME }) # The action values. Fake enum. class Actions: JOIN = 0x1 PART = 0x2 QUIT = 0x3 KICK = 0x4 KICKED = 0x5 NICKCHANGE = 0x6 NICKCHANGED = 0x7 MESSAGE = 0x8 NOTICE = 0x9 TOPICCHANGE = 0x10 CTCP = 0x11 ## Utility functions. def timespan(date, current=None, reach=2): """ Calculate human readable timespan. """ if current is None: current = datetime.now() timespans = [ ('millennium', 'millennia', 6060243651000), ('century', 'centuries', 606024365100), ('decennium', 'decennia', 60602436510), ('year', 'years', 606024365), ('month', 'months', 60602430), ('week', 'weeks', 6060247), ('day', 'days', 606024), ('hour', 'hours', 6060), ('minute', 'minutes', 60), ('second', 'seconds', 1) ] message = None reachstart = None delta = int((current - date).total_seconds()) for i, (singular, plural, seconds) in enumerate(timespans): # Is our time at least one 'unit' worth of this span? if delta >= seconds: # Get the number of units it's worth, and the remainder. n, delta = divmod(delta, seconds) # Append to message. if message is not None: message += ', ' else: reachstart = i message = '' message += '{n} {noun}'.format(n=n, noun=plural if n >= 2 else singular) # Stop if we reached our precision limit. if reachstart is not None and reach is not None and i - reachstart + 1 >= reach: break if message is None: message = 'just now' else: message += ' ago' return message def log(server, nick, what, data): """ Remove earlier entries for `nick` from database and insert new log entry. """ db.from_('seen').where('nickname', nick.lower()).and_('server', server).delete() db.to('seen').add({ 'server': server, 'nickname': nick.lower(), 'action': what, 'data': json.dumps(data), 'time': datetime.now() }) def meify(bot, nick): if bot.nickname == nick: return 'me' return bot.highlight(nick) ## Commands and hooks. @command(r'seen (\S+)$') @command(r'have you seen (\S+)(?: lately)?\??$') def seen(bot, server, target, source, message, parsed, private, admin): nick = parsed.group(1) # Weed out the odd cases. if nick == source: yield from bot.message(target, _(bot, 'Asking for yourself?', serv=server, nick=nick)) return elif nick == bot.nickname: yield from bot.message(target, _(bot, "I'm right here.", serv=server, nick=nick)) return # Do we have an entry for this nick? entry = db.from_('seen').where('nickname', nick.lower()).and_('server', server).single('action', 'data', 'time') if not entry: yield from bot.message(target, _(bot, "I don't know who {nick} is.", serv=server, nick=meify(bot, nick))) return message = 'I saw {nick} {timeago}, {action}' submessage = None action, raw_data, raw_time = entry data = json.loads(raw_data) time = datetime.strptime(raw_time, db.DATETIME_FORMAT) # Huge if/else chain incoming. if action == Actions.JOIN: submessage = _(bot, 'joining {chan}.', serv=server, data) elif action == Actions.PART: submessage = _(bot, 'leaving {chan}, with reason "{reason}".', serv=server, data) elif action == Actions.QUIT: submessage = _(bot, 'disconnecting with reason "{reason}".', serv=server, data) elif action == Actions.KICK: submessage = _(bot, 'kicking {target} from {chan} with reason "{reason}".', serv=server, data) elif action == Actions.KICKED: submessage = _(bot, 'getting kicked from {chan} by {kicker} with reason "{reason}".', serv=server, data) elif action == Actions.NICKCHANGE: submessage = _(bot, 'changing nickname to {newnick}.', serv=server, data) elif action == Actions.NICKCHANGED: submessage = _(bot, 'changing nickname from {oldnick}.', serv=server, data) elif action == Actions.MESSAGE: submessage = _(bot, 'telling {chan} "<{nick}> {message}".', serv=server, nick=nick, *data) elif action == Actions.NOTICE: submessage = _(bot, 'noticing {chan} "{nick}* {message}".', serv=server, nick=nick data) elif action == Actions.TOPICCHANGE: submessage = _(bot, 'changing topic for {chan} to "{topic}".', serv=server, data) elif action == Actions.CTCP: submessage = _(bot, 'CTCPing {target} ({message}).', serv=server, data) else: submessage = _(bot, 'doing something.', serv=server, data) message = _(bot, message, action=submessage, nick=meify(bot, nick), serv=server, rawtime=time, timeago=timespan(time)) yield from bot.message(target, message) @hook('chat.join') def join(bot, server, channel, who): log(server, who, Actions.JOIN, chan=channel) @hook('chat.part') def part(bot, server, channel, who, reason): log(server, who, Actions.PART, chan=channel, reason=reason) @hook('chat.disconnect') def quit(bot, server, who, reason): log(server, who, Actions.QUIT, reason=reason) @hook('chat.kick') def kick(bot, server, channel, target, by, reason): log(server, by, Actions.KICK, chan=channel, target=meify(bot, target), reason=reason) log(server, target, Actions.KICKED, chan=channel, kicker=meify(bot, by), reason=reason) @hook('chat.nickchange') def nickchange(bot, server, who, to): log(server, who, Actions.NICKCHANGE, newnick=to) log(server, to, Actions.NICKCHANGED, oldnick=who) @hook('chat.message') def message(bot, server, target, who, message, private, admin): if not private: log(server, who, Actions.MESSAGE, chan=target, message=message) @hook('chat.notice') def notice(bot, server, target, who, message, private, admin): if not private: log(server, who, Actions.NOTICE, chan=target, message=message) @hook('chat.topicchange') def topicchange(bot, server, channel, who, topic): log(server, who, Actions.TOPICCHANGE, chan=channel, topic=topic) @hook('irc.ctcp') def ctcp(bot, server, target, who, message): 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preprocessing/preprocess_davis.py	linjieyangsc/video_seg	169	156059	<filename>preprocessing/preprocess_davis.py import os import sys from PIL import Image from sets import Set import numpy as np import cv2 data_dir = sys.argv[1] anno_dir = os.path.join(data_dir, 'Annotations/480p/') save_dir = os.path.join(data_dir, 'Annotations/480p_split/') save_dir_all = os.path.join(data_dir, 'Annotations/480p_all') fds = os.listdir(anno_dir) for fd in fds: im_list = os.listdir(os.path.join(anno_dir, fd)) im_list = [item for item in im_list if item[-3:] == 'png'] im = np.array(Image.open(os.path.join(anno_dir + fd, '00000.png'))) cls_n = im.max() for item in im_list: im_path = os.path.join(anno_dir, fd, item) im = np.array(Image.open(im_path)) all_dir = os.path.join(save_dir_all, fd) if not os.path.exists(all_dir): os.makedirs(all_dir) binary_map = (im > 0) mask_image = (binary_map * 255).astype(np.uint8) cv2.imwrite(os.path.join(all_dir, item), mask_image) for i in range(1, cls_n+1): split_dir = os.path.join(save_dir, fd, str(i)) if not os.path.exists(split_dir): os.makedirs(split_dir) binary_map = im == i mask_image = (binary_map * 255).astype(np.uint8) cv2.imwrite(os.path.join(split_dir, item), mask_image)	[ 1, 529, 9507, 29958, 1457, 19170, 29914, 1457, 5014, 29918, 29881, 485, 275, 29889, 2272, 13, 5215, 2897, 13, 5215, 10876, 13, 3166, 349, 6227, 1053, 7084, 13, 3166, 6166, 1053, 3789, 13, 5215, 12655, 408, 7442, 13, 5215, 13850, 29906, 13, 1272, 29918, 3972, 353, 10876, 29889, 19218, 29961, 29896, 29962, 13, 7665, 29918, 3972, 353, 2897, 29889, 2084, 29889, 7122, 29898, 1272, 29918, 3972, 29892, 525, 2744, 1333, 800, 29914, 29946, 29947, 29900, 29886, 29914, 1495, 13, 7620, 29918, 3972, 353, 2897, 29889, 2084, 29889, 7122, 29898, 1272, 29918, 3972, 29892, 525, 2744, 1333, 800, 29914, 29946, 29947, 29900, 29886, 29918, 5451, 29914, 1495, 13, 7620, 29918, 3972, 29918, 497, 353, 2897, 29889, 2084, 29889, 7122, 29898, 1272, 29918, 3972, 29892, 525, 2744, 1333, 800, 29914, 29946, 29947, 29900, 29886, 29918, 497, 1495, 13, 29888, 6289, 353, 2897, 29889, 1761, 3972, 29898, 7665, 29918, 3972, 29897, 13, 1454, 285, 29881, 297, 285, 6289, 29901, 13, 1678, 527, 29918, 1761, 353, 2897, 29889, 1761, 3972, 29898, 359, 29889, 2084, 29889, 7122, 29898, 7665, 29918, 3972, 29892, 285, 29881, 876, 13, 1678, 527, 29918, 1761, 353, 518, 667, 363, 2944, 297, 527, 29918, 1761, 565, 2944, 14352, 29941, 17531, 1275, 525, 2732, 2033, 13, 1678, 527, 353, 7442, 29889, 2378, 29898, 2940, 29889, 3150, 29898, 359, 29889, 2084, 29889, 7122, 29898, 7665, 29918, 3972, 718, 285, 29881, 29892, 525, 29900, 29900, 29900, 29900, 29900, 29889, 2732, 29915, 4961, 13, 1678, 1067, 29879, 29918, 29876, 353, 527, 29889, 3317, 580, 13, 1678, 363, 2944, 297, 527, 29918, 1761, 29901, 13, 4706, 527, 29918, 2084, 353, 2897, 29889, 2084, 29889, 7122, 29898, 7665, 29918, 3972, 29892, 285, 29881, 29892, 2944, 29897, 13, 4706, 527, 353, 7442, 29889, 2378, 29898, 2940, 29889, 3150, 29898, 326, 29918, 2084, 876, 13, 4706, 599, 29918, 3972, 353, 2897, 29889, 2084, 29889, 7122, 29898, 7620, 29918, 3972, 29918, 497, 29892, 285, 29881, 29897, 13, 4706, 565, 451, 2897, 29889, 2084, 29889, 9933, 29898, 497, 29918, 3972, 1125, 13, 9651, 2897, 29889, 29885, 12535, 12935, 29898, 497, 29918, 3972, 29897, 13, 4706, 7581, 29918, 1958, 353, 313, 326, 1405, 29871, 29900, 29897, 13, 4706, 11105, 29918, 3027, 353, 313, 19541, 29918, 1958, 334, 29871, 29906, 29945, 29945, 467, 579, 668, 29898, 9302, 29889, 13470, 29947, 29897, 13, 4706, 13850, 29906, 29889, 326, 3539, 29898, 359, 29889, 2084, 29889, 7122, 29898, 497, 29918, 3972, 29892, 2944, 511, 11105, 29918, 3027, 29897, 13, 4706, 363, 474, 297, 3464, 29898, 29896, 29892, 1067, 29879, 29918, 29876, 29974, 29896, 1125, 13, 9651, 6219, 29918, 3972, 353, 2897, 29889, 2084, 29889, 7122, 29898, 7620, 29918, 3972, 29892, 285, 29881, 29892, 851, 29898, 29875, 876, 13, 9651, 565, 451, 2897, 29889, 2084, 29889, 9933, 29898, 5451, 29918, 3972, 1125, 13, 18884, 2897, 29889, 29885, 12535, 12935, 29898, 5451, 29918, 3972, 29897, 13, 9651, 7581, 29918, 1958, 353, 527, 1275, 474, 13, 9651, 11105, 29918, 3027, 353, 313, 19541, 29918, 1958, 334, 29871, 29906, 29945, 29945, 467, 579, 668, 29898, 9302, 29889, 13470, 29947, 29897, 13, 9651, 13850, 29906, 29889, 326, 3539, 29898, 359, 29889, 2084, 29889, 7122, 29898, 5451, 29918, 3972, 29892, 2944, 511, 11105, 29918, 3027, 29897, 13, 13, 308, 13, 13, 2 ]
magic_agent/tests/test.py	vypivshiy/magic-agent	0	1617228	import re import unittest from magic_agent.crawlers import Request from magic_agent.crawlers.parsers import RE_CHROMIUM, RE_WEBKIT from magic_agent.core.mobile_keys import SAMSUNG from magic_agent.core.base_device import MobileDevice from magic_agent.core.utils import sattolo_shuffle from magic_agent.core.base import RuleItem, RuleDevice, RuleItemGenerator, BaseAgent, sequence_generator from magic_agent.templates import WindowsChrome, LinuxChrome, RandomApple, RandomAndroid, RandomMobileKey class Test(unittest.TestCase): def test_request_json(self): r = Request.json("https://httpbin.org/get", params={"foo space": "bar"}) self.assertTrue(re.search(r"Python-urllib/\d", r["headers"]["User-Agent"])) self.assertEqual(r["url"], "https://httpbin.org/get?foo space=bar") def test_request_get(self): r = Request.get("https://httpbin.org/get") self.assertTrue(re.search(r"https://httpbin\.org/get", r)) self.assertTrue(re.search(r"Python-urllib/\d", r)) def test_quick_agent_desktop(self): self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue(type(WindowsChrome.agent_to_dict) is dict) self.assertTrue(type(LinuxChrome.agent_to_dict) is dict) def test_quick_agent_apple(self): self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) def test_quick_agent_android(self): self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) def test_quick_agent_android_key(self): # samsung device name contains SM-xxxxx identification self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) def test_custom_agent_1(self): b = BaseAgent(rules=(RuleItem("Test/1"), RuleDevice(items=["Test, foobar"]))) self.assertEqual(b.agent, "Test/1 (Test, foobar)") self.assertEqual(b.agent, "Test/1 (Test, foobar)") self.assertEqual(b.agent, "Test/1 (Test, foobar)") def test_rule_item(self): self.assertEqual(RuleItem("Test/1").get(), "Test/1") self.assertEqual(RuleItem("Test/1").get(), "Test/1") self.assertEqual(RuleItem("Test/1").get(), "Test/1") def test_rule_generator(self): t = sequence_generator(["Test/1"]) self.assertEqual(RuleItemGenerator("foo {}", t).get(), "foo Test/1") self.assertEqual(RuleItemGenerator("foo {}", t).get(), "foo Test/1") def test_parse_mobile(self): test_dict = \ {"model": "Test Mobile", "model_id": ["T123"], "released": 2077, "operating_system": "Palm OS T", "resolution": {"height": 1, "wight": 2}, "market_regions": ["Kekistan", "SovietRussia"], "codename": "TestCase", "oem_id": "foobar", "platform": "Android", "market_countries": ["KEK", "USSR"], "battery_capacity": 99_999} b = MobileDevice(test_dict) self.assertEqual(b.model, "Test Mobile") self.assertEqual(b.model_id[0], "T123") self.assertEqual(b.market_regions, ["Kekistan", "SovietRussia"]) def test_device_agent(self): test_dict = \ {"model": "Test Mobile", "model_id": ["T123"], "released": 2077, "operating_system": "Android 10.0", "resolution": {"height": 1, "wight": 2}, "market_regions": ["Kekistan", "SovietRussia"], "codename": "TestCase", "oem_id": "foobar", "platform": "Android", "market_countries": ["KEK", "USSR"], "battery_capacity": 99_999} b = MobileDevice(test_dict) self.assertTrue("(Linux; Android 10.0; T123)" in b.agent.agent) def test_satollo_shuffle(self): seq = [1, 2, 3, 4, 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vendas/urls.py	rauanisanfelice/espetaria	0	87292	from django.contrib import admin from django.urls import path, include from django.contrib.auth import views as auth_views from .views import * urlpatterns = [ path('', index.as_view(), name='lancamento'), # MESAS path('mesa-list/', MesaList.as_view(), name='mesa_list'), path('mesa-new/', MesaNew.as_view(), name='mesa_new'), path('mesa-end/', MesaEnd.as_view(), name='mesa_end'), path('mesa-add-produto/', MesaAddProduto, name='mesa_add_produto'), path('mesa-detail/<int:id_mesa>/', MesaDetail, name='mesa_detail'), path('mesa-end/<int:id_mesa>/', MesaEnd.as_view(), name='mesa_end'), # PRODUTOS path('produto-list/',ProdutoList.as_view(), name='produto_list'), path('produto-novo/',ProdutoNew.as_view(), name='produto_new'), path('produto-dell/<int:id_produto>/',ProdutoDell, name='produto_dell'), path('produto-edit/<int:id_produto>/',ProdutoEdit.as_view(), name='produto_edit'), # REPORTS path('reports/', Reports.as_view(), name='reports'), path('reports-hist/', Reports_hist.as_view(), name='reports_hist'), path('dash-hist/', Dash_Historico, name='dash_hist'), path('reports-comparativo/', Reports_comp.as_view(), name='reports_comp'), path('dash-comp-pizza/', Dash_Comparativo_Pizza, name='dash_comp_pizza'), ]	[ 1, 515, 9557, 29889, 21570, 1053, 4113, 13, 3166, 9557, 29889, 26045, 1053, 2224, 29892, 3160, 13, 3166, 9557, 29889, 21570, 29889, 5150, 1053, 8386, 408, 4817, 29918, 7406, 13, 13, 3166, 869, 7406, 1053, 334, 13, 13, 2271, 11037, 29879, 353, 518, 13, 1678, 2224, 877, 742, 2380, 29889, 294, 29918, 1493, 3285, 1024, 2433, 29880, 4564, 4487, 5477, 13, 268, 13, 1678, 396, 341, 2890, 3289, 13, 1678, 2224, 877, 4467, 29874, 29899, 1761, 29914, 742, 341, 8625, 1293, 29889, 294, 29918, 1493, 3285, 1024, 2433, 4467, 29874, 29918, 1761, 5477, 13, 1678, 2224, 877, 4467, 29874, 29899, 1482, 29914, 742, 341, 8625, 4373, 29889, 294, 29918, 1493, 3285, 1024, 2433, 4467, 29874, 29918, 1482, 5477, 13, 1678, 2224, 877, 4467, 29874, 29899, 355, 29914, 742, 341, 8625, 5044, 29889, 294, 29918, 1493, 3285, 1024, 2433, 4467, 29874, 29918, 355, 5477, 13, 1678, 2224, 877, 4467, 29874, 29899, 1202, 29899, 10633, 3066, 29914, 742, 341, 8625, 2528, 1184, 29881, 3066, 29892, 1024, 2433, 4467, 29874, 29918, 1202, 29918, 10633, 3066, 5477, 13, 1678, 2224, 877, 4467, 29874, 29899, 16432, 29914, 29966, 524, 29901, 333, 29918, 4467, 29874, 20690, 742, 341, 8625, 16570, 29892, 1024, 2433, 4467, 29874, 29918, 16432, 5477, 13, 1678, 2224, 877, 4467, 29874, 29899, 355, 29914, 29966, 524, 29901, 333, 29918, 4467, 29874, 20690, 742, 341, 8625, 5044, 29889, 294, 29918, 1493, 3285, 1024, 2433, 4467, 29874, 29918, 355, 5477, 13, 13, 1678, 396, 13756, 29928, 2692, 3267, 13, 1678, 2224, 877, 10633, 3066, 29899, 1761, 29914, 742, 1184, 29881, 3066, 1293, 29889, 294, 29918, 1493, 3285, 1024, 2433, 10633, 3066, 29918, 1761, 5477, 13, 1678, 2224, 877, 10633, 3066, 29899, 29876, 6962, 29914, 742, 1184, 29881, 3066, 4373, 29889, 294, 29918, 1493, 3285, 1024, 2433, 10633, 3066, 29918, 1482, 5477, 13, 1678, 2224, 877, 10633, 3066, 29899, 29881, 514, 29914, 29966, 524, 29901, 333, 29918, 10633, 3066, 20690, 742, 1184, 29881, 3066, 29928, 514, 29892, 1024, 2433, 10633, 3066, 29918, 29881, 514, 5477, 13, 1678, 2224, 877, 10633, 3066, 29899, 5628, 29914, 29966, 524, 29901, 333, 29918, 10633, 3066, 20690, 742, 1184, 29881, 3066, 6103, 29889, 294, 29918, 1493, 3285, 1024, 2433, 10633, 3066, 29918, 5628, 5477, 13, 13, 1678, 396, 5195, 15082, 29903, 13, 1678, 2224, 877, 276, 4011, 29914, 742, 830, 4011, 29889, 294, 29918, 1493, 3285, 1024, 2433, 276, 4011, 5477, 13, 1678, 2224, 877, 276, 4011, 29899, 29882, 391, 29914, 742, 830, 4011, 29918, 29882, 391, 29889, 294, 29918, 1493, 3285, 1024, 2433, 276, 4011, 29918, 29882, 391, 5477, 13, 1678, 2224, 877, 14592, 29899, 29882, 391, 29914, 742, 360, 1161, 29918, 29950, 2118, 1417, 29892, 1024, 2433, 14592, 29918, 29882, 391, 5477, 13, 13, 1678, 2224, 877, 276, 4011, 29899, 510, 862, 11692, 29914, 742, 830, 4011, 29918, 2388, 29889, 294, 29918, 1493, 3285, 1024, 2433, 276, 4011, 29918, 2388, 5477, 13, 1678, 2224, 877, 14592, 29899, 2388, 29899, 29886, 24990, 29914, 742, 360, 1161, 29918, 1523, 862, 11692, 29918, 29925, 24990, 29892, 1024, 2433, 14592, 29918, 2388, 29918, 29886, 24990, 5477, 13, 29962, 13, 2 ]
indra/sources/geneways/processor.py	zebulon2/indra	136	151473	""" This module provides an input processor for information extracted using the Geneways software suite, converting extraction data in Geneways format into INDRA statements. See publication: Rzhetsky, Andrey, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME> et al. "GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data." Journal of biomedical informatics 37, no. 1 (2004): 43-53. """ from indra.statements import Evidence, Agent import indra.databases.hgnc_client as hgc from indra.literature import * from indra.statements import Complex, Phosphorylation from indra.ontology.standardize import \ standardize_agent_name from indra.sources.geneways.action_parser import GenewaysActionParser try: from indra.sources.geneways.find_full_text_sentence import FullTextMention get_ft_mention = True except ImportError: logger.error('Install the nltk and stemming packages to extract full ' 'text evidence for Geneways mentions.') get_ft_mention = False logger = logging.getLogger(__name__) # This will take in an action and action mention and create a single statement class GenewaysProcessor(object): """The GenewaysProcessors converts extracted Geneways action mentions into INDRA statements. Parameters ---------- search_path : list[str] A list of directories in which to search for Geneways data Attributes ---------- statements : list[indra.statements.Statement] A list of INDRA statements converted from Geneways action mentions, populated by calling the constructor """ def __init__(self, search_path, get_evidence=True): if get_evidence and get_ft_mention: self.get_ft_mention = True else: self.get_ft_mention = False # Parse Geneways data. Will give an error if it can't find # the Geneways data logger.info('Loading Geneways extractions') parser = GenewaysActionParser(search_path) logger.info('Geneways extractions loaded') actions = parser.actions # Make a list of statements from the actions self.statements = [] for action in actions: for mention in action.action_mentions: if mention.negative != '1': new_statement = self.make_statement(action, mention) if new_statement is not None: self.statements.append(new_statement) def make_statement(self, action, mention): """Makes an INDRA statement from a Geneways action and action mention. Parameters ---------- action : GenewaysAction The mechanism that the Geneways mention maps to. Note that several text mentions can correspond to the same action if they are referring to the same relationship - there may be multiple Geneways action mentions corresponding to each action. mention : GenewaysActionMention The Geneways action mention object corresponding to a single mention of a mechanism in a specific text. We make a new INDRA statement corresponding to each action mention. Returns ------- statement : indra.statements.Statement An INDRA statement corresponding to the provided Geneways action mention, or None if the action mention's type does not map onto any INDRA statement type in geneways_action_type_mapper. """ (statement_generator, is_direct) = \ geneways_action_to_indra_statement_type(mention.actiontype, action.plo) if statement_generator is None: # Geneways statement does not map onto an indra statement return None # Try to find the full-text sentence # Unfortunately, the sentence numbers in the Geneways dataset # don't correspond to an obvious sentence segmentation. # This code looks for sentences with the subject, object, and verb # listed by the Geneways action mention table and only includes # it in the evidence if there is exactly one such sentence text = None if self.get_ft_mention: try: content, content_type = get_full_text(mention.pmid, 'pmid') if content is not None: ftm = FullTextMention(mention, content) sentences = ftm.find_matching_sentences() if len(sentences) == 1: text = sentences[0] except Exception: logger.warning('Could not fetch full text for PMID ' + mention.pmid) # Make an evidence object epistemics = dict() epistemics['direct'] = is_direct annotations = mention.make_annotation() annotations['plo'] = action.plo # plo only in action table evidence = Evidence(source_api='geneways', source_id=mention.actionmentionid, pmid=mention.pmid, text=text, epistemics=epistemics, annotations=annotations) # Construct the grounded and name standardized agents # Note that this involves grounding the agent by # converting the Entrez ID listed in the Geneways data with # HGNC and UniProt upstream_agent = get_agent(mention.upstream, action.up) downstream_agent = get_agent(mention.downstream, action.dn) # Make the statement return statement_generator(upstream_agent, downstream_agent, evidence) def get_agent(raw_name, entrez_id): db_refs = {'TEXT': raw_name, 'EGID': entrez_id} logger.debug('Looking up grounding data for Entrez #%s' % entrez_id) hgnc_id = hgc.get_hgnc_from_entrez(entrez_id) if hgnc_id: db_refs['HGNC'] = hgnc_id agent = Agent(raw_name, db_refs=db_refs) standardize_agent_name(agent, standardize_refs=True) return agent def geneways_action_to_indra_statement_type(actiontype, plo): """Return INDRA Statement corresponding to Geneways action type. Parameters ---------- actiontype : str The verb extracted by the Geneways processor plo : str A one character string designating whether Geneways classifies this verb as a physical, logical, or other interaction Returns ------- statement_generator : If there is no mapping to INDRA statements from this action type the return value is None. If there is such a mapping, statement_generator is an anonymous function that takes in the subject agent, object agent, and evidence, in that order, and returns an INDRA statement object. """ actiontype = actiontype.lower() statement_generator = None is_direct = (plo == 'P') if actiontype == 'bind': statement_generator = lambda substance1, substance2, evidence: \ Complex([substance1, substance2], evidence=evidence) is_direct = True elif actiontype == 'phosphorylate': statement_generator = lambda substance1, substance2, evidence: \ Phosphorylation(substance1, substance2, evidence=evidence) is_direct = True return (statement_generator, is_direct)	[ 1, 9995, 13, 4013, 3883, 8128, 385, 1881, 21433, 363, 2472, 23892, 773, 278, 13, 15462, 809, 1036, 7047, 9460, 29892, 17415, 4805, 428, 848, 297, 5739, 809, 1036, 3402, 964, 13, 22255, 4717, 9506, 29889, 13, 13, 13393, 17745, 29901, 13, 29934, 29920, 9188, 7912, 29892, 1126, 8903, 29892, 529, 5813, 10202, 529, 5813, 10202, 529, 5813, 10202, 529, 5813, 10202, 529, 5813, 10202, 529, 5813, 29958, 634, 394, 29889, 376, 29954, 1600, 29956, 1036, 29901, 263, 1788, 363, 6597, 292, 29892, 13, 7054, 12339, 292, 29892, 7604, 5281, 29892, 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grid-dataset/training_data.py	tuantran1810/lips-image-generation	1	199343	<gh_stars>1-10 import os import cv2 import pickle import numpy as np from scipy.io import wavfile from pathlib import Path import librosa class TrainingDataConverter: def __init__( self, videoRootFolder, audioRootFolder, videoExt, audioExt, outputfolder, ): self.__paths = dict() totalvideo = 0 identity_set = set() for path, _ , files in os.walk(videoRootFolder): for name in files: code, ext = name.split('.') if ext == videoExt: identity = path.split('/')[-1] if identity not in self.__paths: self.__paths[identity] = dict() idmap = self.__paths[identity] idmap[code] = dict() idmap[code]['video'] = os.path.join(path, name) totalvideo += 1 identity_set.add(identity) for identity in identity_set: audio_identity = os.path.join(outputfolder, identity) Path(audio_identity).mkdir(parents=True, exist_ok=True) totalaudio = 0 for path, _ , files in os.walk(audioRootFolder): for name in files: code, ext = name.split('.') if ext == audioExt: path_parts = path.split('/') identity = path_parts[-1] training_path = os.path.join(outputfolder, identity) if identity not in self.__paths: print(f"identity {identity} not found, ignore") continue idmap = self.__paths[identity] if code not in idmap: continue idmap[code]['audio'] = os.path.join(path, name) idmap[code]['training'] = os.path.join(training_path, code + '.' + 'pkl') totalaudio += 1 # print(self.__paths) print(f"total audio = {totalaudio}, total video = {totalvideo}") def __iterate_frames(self, videofile): vidcap = cv2.VideoCapture(videofile) while True: success, image = vidcap.read() if not success: return if image is None: print("image is None") yield image def __audio_logmel_segments(self, wave, n_fft = 1024, n_mels = 128, fsampling = 44100, nsegments = 75): wave = wave.astype(float) wave_length = wave.shape[0] chunk_length = int(wave_length/nsegments) for i in range(0, nsegments): chunk = wave[(ichunk_length):((i+1)chunk_length)] s = librosa.feature.melspectrogram(chunk, sr = fsampling, n_fft = n_fft, n_mels = n_mels, fmax = 16000) yield librosa.amplitude_to_db(s) def run(self): for _, content in self.__paths.items(): for _, info in content.items(): video_path = info['video'] audio_path = info['audio'] training_path = info['training'] frames = np.stack( [f for f in map( lambda x: np.transpose(x, (2, 1, 0)), self.__iterate_frames(video_path), )], axis = 0, ) _, wave = wavfile.read(audio_path) audio_logmel = np.stack( [f for f in self.__audio_logmel_segments(wave)], axis = 0, ) data = dict() data['video'] = frames data['audio'] = audio_logmel return with open(training_path, 'wb') as fd: pickle.dump(data, fd) print(training_path) def main(): conv = TrainingDataConverter( "/media/tuantran/raid-data/dataset/GRID/mouth_videos", "/media/tuantran/raid-data/dataset/GRID/audio", "mp4", "wav", "/media/tuantran/raid-data/dataset/GRID/mouth_images", ) conv.run() if __name__ == "__main__": main()	[ 1, 529, 12443, 29918, 303, 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29900, 29900, 29892, 302, 10199, 1860, 353, 29871, 29955, 29945, 1125, 13, 4706, 10742, 353, 10742, 29889, 579, 668, 29898, 7411, 29897, 13, 4706, 10742, 29918, 2848, 353, 10742, 29889, 12181, 29961, 29900, 29962, 13, 4706, 19875, 29918, 2848, 353, 938, 29898, 27766, 29918, 2848, 29914, 29876, 10199, 1860, 29897, 13, 4706, 363, 474, 297, 3464, 29898, 29900, 29892, 302, 10199, 1860, 1125, 13, 9651, 19875, 353, 10742, 15625, 29875, 29930, 29812, 29918, 2848, 1125, 3552, 29875, 29974, 29896, 11877, 29812, 29918, 2848, 4638, 13, 9651, 269, 353, 4303, 1883, 29874, 29889, 14394, 29889, 29885, 1379, 1103, 307, 1393, 29898, 29812, 29892, 27236, 353, 285, 13445, 10335, 29892, 302, 29918, 600, 29873, 353, 302, 29918, 600, 29873, 29892, 302, 29918, 29885, 1379, 353, 302, 29918, 29885, 1379, 29892, 285, 3317, 353, 29871, 29896, 29953, 29900, 29900, 29900, 29897, 13, 9651, 7709, 4303, 1883, 29874, 29889, 314, 2830, 1151, 29918, 517, 29918, 2585, 29898, 29879, 29897, 13, 13, 1678, 822, 1065, 29898, 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29914, 24713, 29914, 14345, 1367, 29914, 21026, 29918, 8346, 613, 13, 1678, 1723, 13, 13, 1678, 7602, 29889, 3389, 580, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 1678, 1667, 580, 13, 2 ]
vegaapiclient/generated/data_node/api/v1/trading_data_pb2_grpc.py	vegaprotocol/sdk-python	1	1604191	# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from ...api.v1 import trading_data_pb2 as data__node_dot_api_dot_v1_dot_trading__data__pb2 class TradingDataServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.MarketAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.FromString, ) self.PartyAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.FromString, ) self.FeeInfrastructureAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/FeeInfrastructureAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.FromString, ) self.GlobalRewardPoolAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/GlobalRewardPoolAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.FromString, ) self.Candles = channel.unary_unary( '/datanode.api.v1.TradingDataService/Candles', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.FromString, ) self.MarketDataByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketDataByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.FromString, ) self.MarketsData = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketsData', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.FromString, ) self.MarketByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.FromString, ) self.MarketDepth = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketDepth', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.FromString, ) self.Markets = channel.unary_unary( '/datanode.api.v1.TradingDataService/Markets', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.FromString, ) self.OrderByMarketAndID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByMarketAndID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.FromString, ) self.OrderByReference = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByReference', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.FromString, ) self.OrdersByMarket = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrdersByMarket', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.FromString, ) self.OrdersByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrdersByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.FromString, ) self.OrderByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.FromString, ) self.OrderVersionsByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderVersionsByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.FromString, ) self.MarginLevels = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarginLevels', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.FromString, ) self.Parties = channel.unary_unary( '/datanode.api.v1.TradingDataService/Parties', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.FromString, ) self.PartyByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.FromString, ) self.PositionsByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/PositionsByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.FromString, ) self.LastTrade = channel.unary_unary( '/datanode.api.v1.TradingDataService/LastTrade', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.FromString, ) self.TradesByMarket = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByMarket', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.FromString, ) self.TradesByOrder = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByOrder', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.FromString, ) self.TradesByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.FromString, ) self.GetProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.FromString, ) self.GetProposalsByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalsByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.FromString, ) self.GetVotesByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetVotesByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.FromString, ) self.GetNewMarketProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewMarketProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.FromString, ) self.GetUpdateMarketProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetUpdateMarketProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.FromString, ) self.GetNetworkParametersProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNetworkParametersProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.FromString, ) self.GetNewAssetProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewAssetProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.FromString, ) self.GetNewFreeformProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewFreeformProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.FromString, ) self.GetProposalByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.FromString, ) self.GetProposalByReference = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalByReference', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.FromString, ) self.ObserveGovernance = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveGovernance', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.FromString, ) self.ObservePartyProposals = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObservePartyProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.FromString, ) self.ObservePartyVotes = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObservePartyVotes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.FromString, ) self.ObserveProposalVotes = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveProposalVotes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.FromString, ) self.ObserveEventBus = channel.stream_stream( '/datanode.api.v1.TradingDataService/ObserveEventBus', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.FromString, ) self.GetNodeData = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeData', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.FromString, ) self.GetNodes = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.FromString, ) self.GetNodeByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.FromString, ) self.GetKeyRotations = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetKeyRotations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.FromString, ) self.GetKeyRotationsByNode = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetKeyRotationsByNode', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.FromString, ) self.GetEpoch = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetEpoch', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.FromString, ) self.GetVegaTime = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetVegaTime', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.FromString, ) self.AccountsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/AccountsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.FromString, ) self.CandlesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/CandlesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.FromString, ) self.MarginLevelsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarginLevelsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.FromString, ) self.MarketDepthSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketDepthSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.FromString, ) self.MarketDepthUpdatesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketDepthUpdatesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.FromString, ) self.MarketsDataSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketsDataSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.FromString, ) self.OrdersSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/OrdersSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.FromString, ) self.PositionsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/PositionsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.FromString, ) self.TradesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/TradesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.FromString, ) self.TransferResponsesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/TransferResponsesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.FromString, ) self.GetNodeSignaturesAggregate = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeSignaturesAggregate', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.FromString, ) self.AssetByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/AssetByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.FromString, ) self.Assets = channel.unary_unary( '/datanode.api.v1.TradingDataService/Assets', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.FromString, ) self.EstimateFee = channel.unary_unary( '/datanode.api.v1.TradingDataService/EstimateFee', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.FromString, ) self.EstimateMargin = channel.unary_unary( '/datanode.api.v1.TradingDataService/EstimateMargin', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.FromString, ) self.ERC20WithdrawalApproval = channel.unary_unary( '/datanode.api.v1.TradingDataService/ERC20WithdrawalApproval', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.FromString, ) self.Withdrawal = channel.unary_unary( '/datanode.api.v1.TradingDataService/Withdrawal', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.FromString, ) self.Withdrawals = channel.unary_unary( '/datanode.api.v1.TradingDataService/Withdrawals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.FromString, ) self.Deposit = channel.unary_unary( '/datanode.api.v1.TradingDataService/Deposit', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.FromString, ) self.Deposits = channel.unary_unary( '/datanode.api.v1.TradingDataService/Deposits', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.FromString, ) self.NetworkParameters = channel.unary_unary( '/datanode.api.v1.TradingDataService/NetworkParameters', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.FromString, ) self.LiquidityProvisions = channel.unary_unary( '/datanode.api.v1.TradingDataService/LiquidityProvisions', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.FromString, ) self.OracleSpec = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleSpec', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.FromString, ) self.OracleSpecs = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleSpecs', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.FromString, ) self.OracleDataBySpec = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleDataBySpec', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.FromString, ) self.ObserveRewards = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveRewards', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.FromString, ) self.GetRewards = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetRewards', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.FromString, ) self.GetRewardSummaries = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetRewardSummaries', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.FromString, ) self.Checkpoints = channel.unary_unary( '/datanode.api.v1.TradingDataService/Checkpoints', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.FromString, ) self.Delegations = channel.unary_unary( '/datanode.api.v1.TradingDataService/Delegations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.FromString, ) self.ObserveDelegations = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveDelegations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.FromString, ) self.PartyStake = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyStake', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.FromString, ) self.Transfers = channel.unary_unary( '/datanode.api.v1.TradingDataService/Transfers', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersResponse.FromString, ) class TradingDataServiceServicer(object): """Missing associated documentation comment in .proto file.""" def MarketAccounts(self, request, context): """-- Accounts -- Get a list of Accounts by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyAccounts(self, request, context): """Get a list of Accounts by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def FeeInfrastructureAccounts(self, request, context): """Get a list of accounts holding infrastructure fees. Can be filtered by asset, there will be 1 infrastructure fee account per asset in the network. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GlobalRewardPoolAccounts(self, request, context): """Get a list of accounts holding reward pools Can be filtered by asset, there will be 1 reward pool account per asset in the network. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Candles(self, request, context): """-- Candles -- Get a list of Candles by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDataByID(self, request, context): """-- Market Data -- Get Market Data by Market ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketsData(self, request, context): """Get a list of Market Data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketByID(self, request, context): """-- Markets -- Get a Market by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepth(self, request, context): """Get Market Depth """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Markets(self, request, context): """Get a list of Markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByMarketAndID(self, request, context): """-- Orders -- Get an Order by Market and Order ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByReference(self, request, context): """Get an Order by Pending Order reference (UUID) """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersByMarket(self, request, context): """Get a list of Orders by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersByParty(self, request, context): """Get a list of Orders by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByID(self, request, context): """Get a specific order by order ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderVersionsByID(self, request, context): """Get all versions of the order by its orderID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarginLevels(self, request, context): """-- Parties -- Get Margin Levels by Party ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Parties(self, request, context): """Get a list of Parties """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyByID(self, request, context): """Get a Party by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PositionsByParty(self, request, context): """-- Positions -- Get a list of Positions by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def LastTrade(self, request, context): """-- Trades -- Get latest Trade """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByMarket(self, request, context): """Get a list of Trades by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByOrder(self, request, context): """Get a list of Trades by Order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByParty(self, request, context): """Get a list of Trades by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposals(self, request, context): """-- Governance -- Get governance data (proposals and votes) for all proposals """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalsByParty(self, request, context): """Get governance data (proposals and votes) for proposals by party authoring them """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVotesByParty(self, request, context): """Get votes by party casting them """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewMarketProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim creating new markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetUpdateMarketProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim updating markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNetworkParametersProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim updating Vega network parameters """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewAssetProposals(self, request, context): """Get governance data (proposals and votes) for proposals aiming to create new assets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewFreeformProposals(self, request, context): """Get governance data (proposals and votes) for proposals aiming to create freeform proposals """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalByID(self, request, context): """Get governance data (proposals and votes) for a proposal located by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalByReference(self, request, context): """Get governance data (proposals and votes) for a proposal located by reference """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveGovernance(self, request, context): """Subscribe to a stream of all governance updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObservePartyProposals(self, request, context): """Subscribe to a stream of proposal updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObservePartyVotes(self, request, context): """Subscribe to a stream of votes cast by a specific party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveProposalVotes(self, request, context): """Subscribe to a stream of proposal votes """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveEventBus(self, request_iterator, context): """Subscribe to a stream of events from the core """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeData(self, request, context): """-- Validators -- Get data of current node """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodes(self, request, context): """List all known network nodes """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeByID(self, request, context): """Get a specific node by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetKeyRotations(self, request, context): """Get all key rotations """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetKeyRotationsByNode(self, request, context): """Get all key rotations by node """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetEpoch(self, request, context): """Get data for a specific epoch, if id omitted it gets the current epoch """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVegaTime(self, request, context): """-- Misc -- Get Time """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AccountsSubscribe(self, request, context): """Subscribe to a stream of Accounts """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CandlesSubscribe(self, request, context): """Subscribe to a stream of Candles """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarginLevelsSubscribe(self, request, context): """Subscribe to a stream of Margin Levels """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepthSubscribe(self, request, context): """Subscribe to a stream of Market Depth """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepthUpdatesSubscribe(self, request, context): """Subscribe to a stream of Market Depth Price Level Updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketsDataSubscribe(self, request, context): """Subscribe to a stream of Markets Data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersSubscribe(self, request, context): """Subscribe to a stream of Orders """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PositionsSubscribe(self, request, context): """Subscribe to a stream of Positions """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesSubscribe(self, request, context): """Subscribe to a stream of Trades """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TransferResponsesSubscribe(self, request, context): """Subscribe to a stream of Transfer Responses """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeSignaturesAggregate(self, request, context): """Get an aggregate of signatures from all the nodes of the network """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AssetByID(self, request, context): """Get an asset by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Assets(self, request, context): """Get a list of all assets on Vega """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def EstimateFee(self, request, context): """Get an estimate for the fee to be paid for a given order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def EstimateMargin(self, request, context): """Get an estimate for the margin required for a new order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ERC20WithdrawalApproval(self, request, context): """Get the bundle approval for an ERC20 withdrawal, these data are being used to bundle the call to the smart contract on the ethereum bridge """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Withdrawal(self, request, context): """Get a withdrawal by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Withdrawals(self, request, context): """Get withdrawals for a party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Deposit(self, request, context): """Get a deposit by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Deposits(self, request, context): """Get deposits for a party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def NetworkParameters(self, request, context): """Get the network parameters """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def LiquidityProvisions(self, request, context): """Get the liquidity provision orders """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleSpec(self, request, context): """Get an oracle spec by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleSpecs(self, request, context): """Get the oracle specs """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleDataBySpec(self, request, context): """Get all oracle data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveRewards(self, request, context): """subscribe to rewards """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetRewards(self, request, context): """Get rewards """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetRewardSummaries(self, request, context): """Get reward summaries """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Checkpoints(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Delegations(self, request, context): """Get delegation data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveDelegations(self, request, context): """subscribe to delegation events """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyStake(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Transfers(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_TradingDataServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'MarketAccounts': grpc.unary_unary_rpc_method_handler( servicer.MarketAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.SerializeToString, ), 'PartyAccounts': grpc.unary_unary_rpc_method_handler( servicer.PartyAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.SerializeToString, ), 'FeeInfrastructureAccounts': grpc.unary_unary_rpc_method_handler( servicer.FeeInfrastructureAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.SerializeToString, ), 'GlobalRewardPoolAccounts': grpc.unary_unary_rpc_method_handler( servicer.GlobalRewardPoolAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.SerializeToString, ), 'Candles': grpc.unary_unary_rpc_method_handler( servicer.Candles, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.SerializeToString, ), 'MarketDataByID': grpc.unary_unary_rpc_method_handler( servicer.MarketDataByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.SerializeToString, ), 'MarketsData': grpc.unary_unary_rpc_method_handler( servicer.MarketsData, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.SerializeToString, ), 'MarketByID': grpc.unary_unary_rpc_method_handler( servicer.MarketByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.SerializeToString, ), 'MarketDepth': grpc.unary_unary_rpc_method_handler( servicer.MarketDepth, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.SerializeToString, ), 'Markets': grpc.unary_unary_rpc_method_handler( servicer.Markets, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.SerializeToString, ), 'OrderByMarketAndID': grpc.unary_unary_rpc_method_handler( servicer.OrderByMarketAndID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.SerializeToString, ), 'OrderByReference': grpc.unary_unary_rpc_method_handler( servicer.OrderByReference, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.SerializeToString, ), 'OrdersByMarket': grpc.unary_unary_rpc_method_handler( servicer.OrdersByMarket, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.SerializeToString, ), 'OrdersByParty': grpc.unary_unary_rpc_method_handler( servicer.OrdersByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.SerializeToString, ), 'OrderByID': grpc.unary_unary_rpc_method_handler( servicer.OrderByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.SerializeToString, ), 'OrderVersionsByID': grpc.unary_unary_rpc_method_handler( servicer.OrderVersionsByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.SerializeToString, ), 'MarginLevels': grpc.unary_unary_rpc_method_handler( servicer.MarginLevels, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.SerializeToString, ), 'Parties': grpc.unary_unary_rpc_method_handler( servicer.Parties, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.SerializeToString, ), 'PartyByID': grpc.unary_unary_rpc_method_handler( servicer.PartyByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.SerializeToString, ), 'PositionsByParty': grpc.unary_unary_rpc_method_handler( servicer.PositionsByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.SerializeToString, ), 'LastTrade': grpc.unary_unary_rpc_method_handler( servicer.LastTrade, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.SerializeToString, ), 'TradesByMarket': grpc.unary_unary_rpc_method_handler( servicer.TradesByMarket, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.SerializeToString, ), 'TradesByOrder': grpc.unary_unary_rpc_method_handler( servicer.TradesByOrder, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.SerializeToString, ), 'TradesByParty': grpc.unary_unary_rpc_method_handler( servicer.TradesByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.SerializeToString, ), 'GetProposals': grpc.unary_unary_rpc_method_handler( servicer.GetProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.SerializeToString, ), 'GetProposalsByParty': grpc.unary_unary_rpc_method_handler( servicer.GetProposalsByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.SerializeToString, ), 'GetVotesByParty': grpc.unary_unary_rpc_method_handler( servicer.GetVotesByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.SerializeToString, ), 'GetNewMarketProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewMarketProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.SerializeToString, ), 'GetUpdateMarketProposals': grpc.unary_unary_rpc_method_handler( servicer.GetUpdateMarketProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.SerializeToString, ), 'GetNetworkParametersProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNetworkParametersProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.SerializeToString, ), 'GetNewAssetProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewAssetProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.SerializeToString, ), 'GetNewFreeformProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewFreeformProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.SerializeToString, ), 'GetProposalByID': grpc.unary_unary_rpc_method_handler( servicer.GetProposalByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.SerializeToString, ), 'GetProposalByReference': grpc.unary_unary_rpc_method_handler( servicer.GetProposalByReference, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.SerializeToString, ), 'ObserveGovernance': grpc.unary_stream_rpc_method_handler( servicer.ObserveGovernance, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.SerializeToString, ), 'ObservePartyProposals': grpc.unary_stream_rpc_method_handler( servicer.ObservePartyProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.SerializeToString, ), 'ObservePartyVotes': grpc.unary_stream_rpc_method_handler( servicer.ObservePartyVotes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.SerializeToString, ), 'ObserveProposalVotes': grpc.unary_stream_rpc_method_handler( servicer.ObserveProposalVotes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.SerializeToString, ), 'ObserveEventBus': grpc.stream_stream_rpc_method_handler( servicer.ObserveEventBus, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.SerializeToString, ), 'GetNodeData': grpc.unary_unary_rpc_method_handler( servicer.GetNodeData, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.SerializeToString, ), 'GetNodes': grpc.unary_unary_rpc_method_handler( servicer.GetNodes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.SerializeToString, ), 'GetNodeByID': grpc.unary_unary_rpc_method_handler( servicer.GetNodeByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.SerializeToString, ), 'GetKeyRotations': grpc.unary_unary_rpc_method_handler( servicer.GetKeyRotations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.SerializeToString, ), 'GetKeyRotationsByNode': grpc.unary_unary_rpc_method_handler( servicer.GetKeyRotationsByNode, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.SerializeToString, ), 'GetEpoch': grpc.unary_unary_rpc_method_handler( servicer.GetEpoch, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.SerializeToString, ), 'GetVegaTime': grpc.unary_unary_rpc_method_handler( servicer.GetVegaTime, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.SerializeToString, ), 'AccountsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.AccountsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.SerializeToString, ), 'CandlesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.CandlesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.SerializeToString, ), 'MarginLevelsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarginLevelsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.SerializeToString, ), 'MarketDepthSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketDepthSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.SerializeToString, ), 'MarketDepthUpdatesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketDepthUpdatesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.SerializeToString, ), 'MarketsDataSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketsDataSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.SerializeToString, ), 'OrdersSubscribe': grpc.unary_stream_rpc_method_handler( servicer.OrdersSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.SerializeToString, ), 'PositionsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.PositionsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.SerializeToString, ), 'TradesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.TradesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.SerializeToString, ), 'TransferResponsesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.TransferResponsesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.SerializeToString, ), 'GetNodeSignaturesAggregate': grpc.unary_unary_rpc_method_handler( servicer.GetNodeSignaturesAggregate, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.SerializeToString, ), 'AssetByID': grpc.unary_unary_rpc_method_handler( servicer.AssetByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.SerializeToString, ), 'Assets': grpc.unary_unary_rpc_method_handler( servicer.Assets, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.SerializeToString, ), 'EstimateFee': grpc.unary_unary_rpc_method_handler( servicer.EstimateFee, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.SerializeToString, ), 'EstimateMargin': grpc.unary_unary_rpc_method_handler( servicer.EstimateMargin, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.SerializeToString, ), 'ERC20WithdrawalApproval': grpc.unary_unary_rpc_method_handler( servicer.ERC20WithdrawalApproval, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.SerializeToString, ), 'Withdrawal': grpc.unary_unary_rpc_method_handler( servicer.Withdrawal, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.SerializeToString, ), 'Withdrawals': grpc.unary_unary_rpc_method_handler( servicer.Withdrawals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.SerializeToString, ), 'Deposit': grpc.unary_unary_rpc_method_handler( servicer.Deposit, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.SerializeToString, ), 'Deposits': grpc.unary_unary_rpc_method_handler( servicer.Deposits, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.SerializeToString, ), 'NetworkParameters': grpc.unary_unary_rpc_method_handler( servicer.NetworkParameters, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.SerializeToString, ), 'LiquidityProvisions': grpc.unary_unary_rpc_method_handler( servicer.LiquidityProvisions, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.SerializeToString, ), 'OracleSpec': grpc.unary_unary_rpc_method_handler( servicer.OracleSpec, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.SerializeToString, ), 'OracleSpecs': grpc.unary_unary_rpc_method_handler( servicer.OracleSpecs, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.SerializeToString, ), 'OracleDataBySpec': grpc.unary_unary_rpc_method_handler( servicer.OracleDataBySpec, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.SerializeToString, ), 'ObserveRewards': grpc.unary_stream_rpc_method_handler( servicer.ObserveRewards, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.SerializeToString, ), 'GetRewards': grpc.unary_unary_rpc_method_handler( servicer.GetRewards, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.SerializeToString, ), 'GetRewardSummaries': grpc.unary_unary_rpc_method_handler( servicer.GetRewardSummaries, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.SerializeToString, ), 'Checkpoints': grpc.unary_unary_rpc_method_handler( servicer.Checkpoints, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.SerializeToString, ), 'Delegations': grpc.unary_unary_rpc_method_handler( servicer.Delegations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.SerializeToString, ), 'ObserveDelegations': grpc.unary_stream_rpc_method_handler( servicer.ObserveDelegations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.SerializeToString, ), 'PartyStake': grpc.unary_unary_rpc_method_handler( servicer.PartyStake, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.SerializeToString, ), 'Transfers': grpc.unary_unary_rpc_method_handler( servicer.Transfers, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'datanode.api.v1.TradingDataService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class TradingDataService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def MarketAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def FeeInfrastructureAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/FeeInfrastructureAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GlobalRewardPoolAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GlobalRewardPoolAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Candles(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Candles', data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDataByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketDataByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketsData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketsData', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepth(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketDepth', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Markets(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Markets', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByMarketAndID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByMarketAndID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByReference(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByReference', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersByMarket(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrdersByMarket', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrdersByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderVersionsByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderVersionsByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarginLevels(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarginLevels', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Parties(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Parties', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PositionsByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PositionsByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def LastTrade(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/LastTrade', data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByMarket(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByMarket', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByOrder(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByOrder', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalsByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalsByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetVotesByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetVotesByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewMarketProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewMarketProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetUpdateMarketProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetUpdateMarketProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNetworkParametersProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNetworkParametersProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewAssetProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewAssetProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewFreeformProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewFreeformProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalByReference(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalByReference', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveGovernance(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveGovernance', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObservePartyProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObservePartyProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObservePartyVotes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObservePartyVotes', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveProposalVotes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveProposalVotes', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveEventBus(request_iterator, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.stream_stream(request_iterator, target, '/datanode.api.v1.TradingDataService/ObserveEventBus', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeData', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodes', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetKeyRotations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetKeyRotations', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetKeyRotationsByNode(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetKeyRotationsByNode', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetEpoch(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetEpoch', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetVegaTime(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetVegaTime', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AccountsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/AccountsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CandlesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/CandlesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarginLevelsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarginLevelsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepthSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketDepthSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepthUpdatesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketDepthUpdatesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketsDataSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketsDataSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/OrdersSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PositionsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/PositionsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/TradesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TransferResponsesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/TransferResponsesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeSignaturesAggregate(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeSignaturesAggregate', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AssetByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/AssetByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Assets(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Assets', data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def EstimateFee(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/EstimateFee', data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def EstimateMargin(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/EstimateMargin', data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ERC20WithdrawalApproval(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/ERC20WithdrawalApproval', data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Withdrawal(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Withdrawal', data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Withdrawals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Withdrawals', data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Deposit(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Deposit', data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Deposits(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Deposits', data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def NetworkParameters(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/NetworkParameters', data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def LiquidityProvisions(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/LiquidityProvisions', data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleSpec(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleSpec', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleSpecs(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleSpecs', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleDataBySpec(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleDataBySpec', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveRewards(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveRewards', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetRewards(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetRewards', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetRewardSummaries(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetRewardSummaries', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Checkpoints(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Checkpoints', data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Delegations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Delegations', data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveDelegations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveDelegations', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyStake(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyStake', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Transfers(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, 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EHR_statistic_app/apps.py	HurleyJames/Visualization-EHRs	1	190198	<gh_stars>1-10 from django.apps import AppConfig class EhrStatisticAppConfig(AppConfig): name = 'EHR_statistic_app'	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 3166, 9557, 29889, 13371, 1053, 2401, 3991, 30004, 13, 30004, 13, 30004, 13, 1990, 29245, 9513, 4695, 2052, 3991, 29898, 2052, 3991, 1125, 30004, 13, 1678, 1024, 353, 525, 29923, 20938, 29918, 6112, 4695, 29918, 932, 29915, 30004, 13, 2 ]
adaptnlp/callback.py	chsafouane/adaptnlp	410	79550	<filename>adaptnlp/callback.py<gh_stars>100-1000 # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/01_callback.ipynb (unless otherwise specified). __all__ = ['GatherInputsCallback', 'SetInputsCallback', 'GeneratorCallback'] # Cell from fastcore.basics import store_attr from fastcore.meta import delegates from fastai.callback.core import Callback, CancelBatchException from transformers import PreTrainedModel # Cell class GatherInputsCallback(Callback): """ Prepares basic input dictionary for HuggingFace Transformers This `Callback` generates a very basic dictionary consisting of `input_ids`, `attention_masks`, and `token_type_ids`, and saves it to the attribute `self.learn.inputs`. If further data is expected or needed from the batch, the additional Callback(s) should have an order of -2 """ order = -3 def before_validate(self): """ Sets the number of inputs in `self.dls` """ x = self.dl.one_batch() self.learn.dls.n_inp = len(x) def before_batch(self): """ Turns `self.xb` from a tuple to a dictionary of either `{"input_ids", "attention_masks", "token_type_ids"}`d or `{"input_ids", "attention_masks"}` """ inputs = { "input_ids":self.learn.xb[0], "attention_mask":self.learn.xb[1] } if len(self.learn.xb) > 2: inputs["token_type_ids"] = self.learn.xb[2] self.learn.inputs = inputs # Cell class SetInputsCallback(Callback): """ Callback which runs after `GatherInputsCallback` that sets `self.learn.xb` """ order = -1 def __init__( self, as_dict=False # Whether to leave `self.xb` as a dictionary of values ): store_attr() def before_batch(self): """ Set `self.learn.xb` to `self.learn.inputs.values()` """ if not self.as_dict: self.learn.xb = list(self.learn.inputs.values()) else: self.learn.xb = self.learn.inputs # Cell class GeneratorCallback(Callback): """ Callback used for models that utilize `self.model.generate` """ @delegates(PreTrainedModel.generate) def __init__( self, num_beams:int, # Number of beams for beam search min_length:int, # Minimal length of the sequence generated max_length:int, # Maximum length of the sequence generated early_stopping:bool, # Whether to do early stopping kwargs ): store_attr() self.kwargs = kwargs def before_batch(self): """ Run model-specific inference """ pred = self.learn.model.generate( input_ids = self.xb['input_ids'], attention_mask = self.xb['attention_mask'], num_beams = self.num_beams, min_length = self.min_length, max_length = self.max_length, early_stopping = self.early_stopping, self.kwargs ) self.learn.pred = pred raise CancelBatchException # skip original model inference	[ 1, 529, 9507, 29958, 1114, 415, 12938, 29886, 29914, 14035, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29900, 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spyderlib/utils/debug.py	MarlaJahari/Marve	1	26211	# -- coding: utf-8 -- # # Copyright © 2009-2010 <NAME> # Licensed under the terms of the MIT License # (see spyderlib/__init__.py for details) """Debug utilities""" import inspect import traceback import time def log_time(fd): timestr = "Logging time: %s" % time.ctime(time.time()) print >>fd, "="len(timestr) print >>fd, timestr print >>fd, "="len(timestr) print >>fd, "" def log_last_error(fname, context=None): """Log last error in filename fname -- context: string (optional)""" fd = open(fname, 'a') log_time(fd) if context: print >>fd, "Context" print >>fd, "-------" print >>fd, "" print >>fd, context print >>fd, "" print >>fd, "Traceback" print >>fd, "---------" print >>fd, "" traceback.print_exc(file=fd) print >>fd, "" print >>fd, "" def log_dt(fname, context, t0): fd = open(fname, 'a') log_time(fd) print >>fd, "%s: %d ms" % (context, 10round(1e2(time.time()-t0))) print >>fd, "" print >>fd, "" def caller_name(skip=2): """Get a name of a caller in the format module.class.method `skip` specifies how many levels of stack to skip while getting caller name. skip=1 means "who calls me", skip=2 "who calls my caller" etc. An empty string is returned if skipped levels exceed stack height """ stack = inspect.stack() start = 0 + skip if len(stack) < start + 1: return '' parentframe = stack[start][0] name = [] module = inspect.getmodule(parentframe) # `modname` can be None when frame is executed directly in console # TODO(techtonik): consider using __main__ if module: name.append(module.__name__) # detect classname if 'self' in parentframe.f_locals: # I don't know any way to detect call from the object method # XXX: there seems to be no way to detect static method call - it will # be just a function call name.append(parentframe.f_locals['self'].__class__.__name__) codename = parentframe.f_code.co_name if codename != '<module>': # top level usually name.append( codename ) # function or a method del parentframe return 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configs/__init__.py	mutalisk999/bibi	1,037	89323	<filename>configs/__init__.py # -- coding: utf-8 -- from .config import BaseConfig, DevConfig, TestConfig, get_config	[ 1, 529, 9507, 29958, 2917, 29879, 29914, 1649, 2344, 26914, 2272, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 13, 3166, 869, 2917, 1053, 7399, 3991, 29892, 9481, 3991, 29892, 4321, 3991, 29892, 679, 29918, 2917, 13, 2 ]
RLBotPack/blind_and_deaf/hover.py	L0laapk3/RLBotPack	13	78016	<gh_stars>10-100 from rlutilities.simulation import Game, Input, Car from rlutilities.linear_algebra import vec3, normalize, look_at, norm from rlutilities.mechanics import AerialTurn class Hover: """ PD controller for hovering in the air. This was also used in the Airshow :) """ P = 2.8 D = 3.0 def __init__(self, car: Car): self.turn = AerialTurn(car) self.target: vec3 = None self.car: Car = car self.up: vec3 = None self.controls: Input = Input() self.__time_spent_on_ground = 0.0 def step(self, dt): delta_target = self.target - self.car.position if norm(delta_target) > 700: delta_target = 700 / norm(delta_target) target_direction = normalize(vec3( (delta_target[0]) self.P - self.car.velocity[0] * self.D, (delta_target[1]) * self.P - self.car.velocity[1] * self.D, 1000 )) # reinitialize the AerialTurn object every frame, because it bugs out sometimes # TODO: actually fix this in RLU self.turn = AerialTurn(self.car) self.turn.target = look_at(target_direction, self.up) self.turn.step(dt) self.controls = self.turn.controls self.controls.boost = 0 # tap boost to keep height if (delta_target[2] - self.car.velocity[2] * 0.5) > 0: self.controls.boost = 1 # if the target is relatively far, hold boost even when we're higher than the target to keep moving if delta_target[2] < 0 and self.car.forward()[2] < 0.5: self.controls.boost = 1 self.controls.throttle = True	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29899, 29896, 29900, 29900, 13, 3166, 364, 29880, 4422, 1907, 29889, 3601, 2785, 1053, 8448, 29892, 10567, 29892, 1704, 30004, 13, 3166, 364, 29880, 4422, 1907, 29889, 10660, 29918, 15742, 1053, 9649, 29941, 29892, 4226, 675, 29892, 1106, 29918, 271, 29892, 6056, 30004, 13, 3166, 364, 29880, 4422, 1907, 29889, 1004, 5083, 1199, 1053, 18682, 616, 27407, 30004, 13, 30004, 13, 30004, 13, 30004, 13, 1990, 379, 957, 29901, 30004, 13, 1678, 9995, 30004, 13, 1678, 349, 29928, 4701, 363, 16758, 292, 297, 278, 4799, 22993, 13, 1678, 910, 471, 884, 1304, 297, 278, 5593, 4294, 4248, 30004, 13, 1678, 9995, 30004, 13, 1678, 349, 353, 29871, 29906, 29889, 29947, 30004, 13, 1678, 360, 353, 29871, 29941, 29889, 29900, 30004, 13, 30004, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 1559, 29901, 1704, 1125, 30004, 13, 4706, 1583, 29889, 685, 353, 18682, 616, 27407, 29898, 4287, 8443, 13, 4706, 1583, 29889, 5182, 29901, 9649, 29941, 353, 6213, 30004, 13, 4706, 1583, 29889, 4287, 29901, 1704, 353, 1559, 30004, 13, 4706, 1583, 29889, 786, 29901, 9649, 29941, 353, 6213, 30004, 13, 4706, 1583, 29889, 26255, 29901, 10567, 353, 10567, 26471, 13, 4706, 1583, 17255, 2230, 29918, 1028, 296, 29918, 265, 29918, 2057, 353, 29871, 29900, 29889, 29900, 30004, 13, 30004, 13, 1678, 822, 4331, 29898, 1311, 29892, 11636, 1125, 30004, 13, 4706, 19471, 29918, 5182, 353, 1583, 29889, 5182, 448, 1583, 29889, 4287, 29889, 3283, 30004, 13, 4706, 565, 6056, 29898, 4181, 29918, 5182, 29897, 1405, 29871, 29955, 29900, 29900, 29901, 30004, 13, 9651, 19471, 29918, 5182, 334, 29922, 29871, 29955, 29900, 29900, 847, 6056, 29898, 4181, 29918, 5182, 8443, 13, 30004, 13, 4706, 3646, 29918, 20845, 353, 4226, 675, 29898, 2003, 29941, 29898, 30004, 13, 9651, 313, 4181, 29918, 5182, 29961, 29900, 2314, 334, 1583, 29889, 29925, 448, 1583, 29889, 4287, 29889, 955, 25245, 29961, 29900, 29962, 334, 1583, 29889, 29928, 11167, 13, 9651, 313, 4181, 29918, 5182, 29961, 29896, 2314, 334, 1583, 29889, 29925, 448, 1583, 29889, 4287, 29889, 955, 25245, 29961, 29896, 29962, 334, 1583, 29889, 29928, 11167, 13, 632, 29896, 29900, 29900, 29900, 30004, 13, 308, 876, 30004, 13, 30004, 13, 4706, 396, 337, 24926, 278, 18682, 616, 27407, 1203, 1432, 3515, 29892, 1363, 372, 24557, 714, 6041, 30004, 13, 4706, 396, 14402, 29901, 2869, 2329, 445, 297, 390, 29931, 29965, 30004, 13, 4706, 1583, 29889, 685, 353, 18682, 616, 27407, 29898, 1311, 29889, 4287, 8443, 13, 30004, 13, 4706, 1583, 29889, 685, 29889, 5182, 353, 1106, 29918, 271, 29898, 5182, 29918, 20845, 29892, 1583, 29889, 786, 8443, 13, 30004, 13, 4706, 1583, 29889, 685, 29889, 10568, 29898, 6008, 8443, 13, 4706, 1583, 29889, 26255, 353, 1583, 29889, 685, 29889, 26255, 30004, 13, 4706, 1583, 29889, 26255, 29889, 17079, 353, 29871, 29900, 30004, 13, 30004, 13, 4706, 396, 18751, 14505, 304, 3013, 3171, 30004, 13, 4706, 565, 313, 4181, 29918, 5182, 29961, 29906, 29962, 448, 1583, 29889, 4287, 29889, 955, 25245, 29961, 29906, 29962, 334, 29871, 29900, 29889, 29945, 29897, 1405, 29871, 29900, 29901, 30004, 13, 9651, 1583, 29889, 26255, 29889, 17079, 353, 29871, 29896, 30004, 13, 4706, 396, 565, 278, 3646, 338, 13774, 2215, 29892, 4808, 14505, 1584, 746, 591, 29915, 276, 6133, 1135, 278, 3646, 304, 3013, 8401, 30004, 13, 4706, 565, 19471, 29918, 5182, 29961, 29906, 29962, 529, 29871, 29900, 322, 1583, 29889, 4287, 29889, 11333, 580, 29961, 29906, 29962, 529, 29871, 29900, 29889, 29945, 29901, 30004, 13, 9651, 1583, 29889, 26255, 29889, 17079, 353, 29871, 29896, 30004, 13, 30004, 13, 4706, 1583, 29889, 26255, 29889, 386, 26970, 280, 353, 5852, 30004, 13, 2 ]
isa.py	schwaaweb/aimlds1_11-NLP	0	84062	<reponame>schwaaweb/aimlds1_11-NLP<gh_stars>0 #!/usr/bin/env python # Income Share Agreement min = 50000.0 max = 88235.3 max_pay = 30000.0 max_income = 2117647.06 monthly_increment = (max - min)/23 print('\n24 months maximum payment with a minimum of $50,000 annual income') print('Maximum income for 24 month repayment is $88,235.30\n') print('For incomes exceeding $88,235.30 see chart below,\nfor reduced payback period on $30,000 repayment cap') print('\nmonth\tannual_income\tless_isa\tmonthly\t\tless_isa\tmonthly_payment\n') for n in range(24): print( "%d\t%.2f\t%.2f\t%.2f\t\t%.2f\t\t%.2f" % (n+1, (min+(nmonthly_increment)), (min+(nmonthly_increment))0.83, (min+(nmonthly_increment))/12, (min+(nmonthly_increment))0.83/12, ((min+(nmonthly_increment))/12) - (min+(nmonthly_increment))0.83/12 )) print('\n') print('$30,000 Maximum Shared Income\n') print('total\t\tannual\t\tmonthly\npayments\tincome\t\tpayment\n') for n in range(24,0,-1): print('%d\t\t%.2f\t%.2f' % (n, max/(maxn/max_income), max_pay/n)) print('\n')	[ 1, 529, 276, 1112, 420, 29958, 816, 2766, 29874, 2676, 29914, 29874, 326, 430, 29879, 29896, 29918, 29896, 29896, 29899, 29940, 13208, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 14708, 4855, 29914, 2109, 29914, 6272, 3017, 13, 13, 29937, 512, 2763, 26849, 4059, 276, 882, 13, 13, 13, 1195, 353, 29871, 29945, 29900, 29900, 29900, 29900, 29889, 29900, 13, 3317, 353, 29871, 29947, 29947, 29906, 29941, 29945, 29889, 29941, 13, 3317, 29918, 10472, 353, 29871, 29941, 29900, 29900, 29900, 29900, 29889, 29900, 13, 3317, 29918, 262, 2763, 353, 29871, 29906, 29896, 29896, 29955, 29953, 29946, 29955, 29889, 29900, 29953, 13, 13, 10874, 368, 29918, 25629, 353, 313, 3317, 448, 1375, 6802, 29906, 29941, 13, 13, 2158, 28909, 29876, 29906, 29946, 7378, 7472, 19179, 411, 263, 9212, 310, 395, 29945, 29900, 29892, 29900, 29900, 29900, 17568, 17869, 1495, 13, 2158, 877, 7976, 12539, 29871, 17869, 363, 29871, 29906, 29946, 4098, 1634, 388, 358, 338, 395, 29947, 29947, 29892, 29906, 29941, 29945, 29889, 29941, 29900, 29905, 29876, 1495, 13, 2158, 877, 2831, 297, 26807, 13461, 292, 395, 29947, 29947, 29892, 29906, 29941, 29945, 29889, 29941, 29900, 1074, 8727, 2400, 2053, 29876, 1454, 12212, 5146, 1627, 3785, 373, 395, 29941, 29900, 29892, 29900, 29900, 29900, 1634, 388, 358, 2117, 1495, 13, 13, 2158, 28909, 29876, 10874, 29905, 29873, 812, 950, 29918, 262, 2763, 29905, 29873, 2222, 29918, 8069, 29905, 29873, 10874, 368, 29905, 29873, 29905, 29873, 2222, 29918, 8069, 29905, 29873, 10874, 368, 29918, 27825, 29905, 29876, 1495, 13, 13, 1454, 302, 297, 3464, 29898, 29906, 29946, 1125, 13, 1678, 1596, 29898, 13, 4706, 11860, 29881, 29905, 29873, 15543, 29906, 29888, 29905, 29873, 15543, 29906, 29888, 29905, 29873, 15543, 29906, 29888, 29905, 29873, 29905, 29873, 15543, 29906, 29888, 29905, 29873, 29905, 29873, 15543, 29906, 29888, 29908, 1273, 313, 29876, 29974, 29896, 29892, 313, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 8243, 313, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 876, 29930, 29900, 29889, 29947, 29941, 29892, 313, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 876, 29914, 29896, 29906, 29892, 313, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 876, 29930, 29900, 29889, 29947, 29941, 29914, 29896, 29906, 29892, 5135, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 876, 29914, 29896, 29906, 29897, 448, 313, 1195, 17108, 29876, 29930, 10874, 368, 29918, 25629, 876, 29930, 29900, 29889, 29947, 29941, 29914, 29896, 29906, 29871, 13, 268, 876, 13, 13, 2158, 28909, 29876, 1495, 13, 2158, 877, 29938, 29941, 29900, 29892, 29900, 29900, 29900, 5918, 12539, 21236, 512, 2763, 29905, 29876, 1495, 13, 13, 13, 2158, 877, 7827, 29905, 29873, 29905, 29873, 812, 950, 29905, 29873, 29905, 29873, 10874, 368, 29905, 9302, 388, 1860, 29905, 29873, 262, 2763, 29905, 29873, 29905, 9392, 388, 358, 29905, 29876, 1495, 13, 13, 1454, 302, 297, 3464, 29898, 29906, 29946, 29892, 29900, 6653, 29896, 1125, 13, 1678, 1596, 877, 29995, 29881, 29905, 29873, 29905, 29873, 15543, 29906, 29888, 29905, 29873, 15543, 29906, 29888, 29915, 1273, 313, 29876, 29892, 4236, 14571, 3317, 29930, 29876, 29914, 3317, 29918, 262, 2763, 511, 4236, 29918, 10472, 29914, 29876, 876, 13, 13, 2158, 28909, 29876, 1495, 13, 2 ]
setup.py	ooreilly/mydocstring	13	3455	<filename>setup.py from setuptools import setup setup(name='mydocstring', version='0.2.7', description="""A tool for extracting and converting Google-style docstrings to plain-text, markdown, and JSON.""", url='http://github.com/ooreilly/mydocstring', author="<NAME>", license='MIT', packages=['mydocstring'], install_requires=['mako', 'docopt'], entry_points = { 'console_scripts': [ 'mydocstring=mydocstring.docstring:main', ],}, package_data={'mydocstring': ['templates/google_docstring.md']}, zip_safe=False)	[ 1, 529, 9507, 29958, 14669, 29889, 2272, 13, 3166, 731, 21245, 8789, 1053, 6230, 13, 29871, 13, 14669, 29898, 978, 2433, 1357, 1514, 1807, 742, 13, 418, 1873, 2433, 29900, 29889, 29906, 29889, 29955, 742, 13, 418, 6139, 13776, 29908, 29909, 5780, 363, 6597, 292, 322, 17415, 5087, 29899, 3293, 1574, 19651, 304, 13, 418, 8656, 29899, 726, 29892, 2791, 3204, 29892, 322, 4663, 1213, 29908, 613, 13, 418, 3142, 2433, 1124, 597, 3292, 29889, 510, 29914, 29877, 487, 9403, 29914, 1357, 1514, 1807, 742, 13, 418, 4148, 543, 29966, 5813, 28341, 13, 418, 19405, 2433, 26349, 742, 13, 418, 9741, 29922, 1839, 1357, 1514, 1807, 7464, 13, 418, 2601, 29918, 276, 339, 2658, 29922, 1839, 29885, 4614, 742, 525, 1514, 3670, 7464, 13, 418, 6251, 29918, 9748, 353, 426, 13, 632, 525, 11058, 29918, 16713, 2396, 518, 13, 462, 525, 1357, 1514, 1807, 29922, 1357, 1514, 1807, 29889, 1514, 1807, 29901, 3396, 742, 13, 632, 21251, 1118, 13, 418, 3577, 29918, 1272, 3790, 29915, 1357, 1514, 1807, 2396, 6024, 20943, 29914, 3608, 29918, 1514, 1807, 29889, 3487, 2033, 1118, 29871, 13, 3986, 13, 418, 14319, 29918, 11177, 29922, 8824, 29897, 13, 2 ]
PAST3/i.py	nishio/atcoder	1	94259	<reponame>nishio/atcoder if 1: N = int(input()) Q = int(input()) queries = [] for i in range(Q): queries.append([int(x) for x in input().split()]) else: N = 100000 queries = [ [2, 1, 2], [4, 1, 2] ] * 10000 queries.append([4, 1, 2]) Q = len(queries) isTransposed = False xs = list(range(N + 1)) ys = list(range(N + 1)) for q in queries: f = q[0] if f == 4: i, j = q[1:] if isTransposed: i, j = j, i print(N * (xs[i] - 1) + ys[j] - 1) elif f == 3: isTransposed = not isTransposed else: i, j = q[1:] if (f == 1) ^ isTransposed: xs[i], xs[j] = xs[j], xs[i] else: ys[i], ys[j] = ys[j], ys[i]	[ 1, 529, 276, 1112, 420, 29958, 29876, 728, 601, 29914, 271, 29883, 6119, 13, 361, 29871, 29896, 29901, 13, 1678, 405, 353, 938, 29898, 2080, 3101, 13, 1678, 660, 353, 938, 29898, 2080, 3101, 13, 1678, 9365, 353, 5159, 13, 1678, 363, 474, 297, 3464, 29898, 29984, 1125, 13, 4706, 9365, 29889, 4397, 4197, 524, 29898, 29916, 29897, 363, 921, 297, 1881, 2141, 5451, 580, 2314, 13, 2870, 29901, 13, 1678, 405, 353, 29871, 29896, 29900, 29900, 29900, 29900, 29900, 13, 1678, 9365, 353, 518, 13, 4706, 518, 29906, 29892, 29871, 29896, 29892, 29871, 29906, 1402, 13, 4706, 518, 29946, 29892, 29871, 29896, 29892, 29871, 29906, 29962, 13, 1678, 4514, 334, 29871, 29896, 29900, 29900, 29900, 29900, 13, 1678, 9365, 29889, 4397, 4197, 29946, 29892, 29871, 29896, 29892, 29871, 29906, 2314, 13, 1678, 660, 353, 7431, 29898, 339, 6358, 29897, 13, 13, 13, 275, 4300, 4752, 353, 7700, 13, 10351, 353, 1051, 29898, 3881, 29898, 29940, 718, 29871, 29896, 876, 13, 952, 353, 1051, 29898, 3881, 29898, 29940, 718, 29871, 29896, 876, 13, 13, 1454, 3855, 297, 9365, 29901, 13, 1678, 285, 353, 3855, 29961, 29900, 29962, 13, 1678, 565, 285, 1275, 29871, 29946, 29901, 13, 4706, 474, 29892, 432, 353, 3855, 29961, 29896, 17531, 13, 4706, 565, 338, 4300, 4752, 29901, 13, 9651, 474, 29892, 432, 353, 432, 29892, 474, 13, 4706, 1596, 29898, 29940, 334, 313, 10351, 29961, 29875, 29962, 448, 29871, 29896, 29897, 718, 343, 29879, 29961, 29926, 29962, 448, 29871, 29896, 29897, 13, 1678, 25342, 285, 1275, 29871, 29941, 29901, 13, 4706, 338, 4300, 4752, 353, 451, 338, 4300, 4752, 13, 1678, 1683, 29901, 13, 4706, 474, 29892, 432, 353, 3855, 29961, 29896, 17531, 13, 4706, 565, 313, 29888, 1275, 29871, 29896, 29897, 6228, 338, 4300, 4752, 29901, 13, 9651, 14492, 29961, 29875, 1402, 14492, 29961, 29926, 29962, 353, 14492, 29961, 29926, 1402, 14492, 29961, 29875, 29962, 13, 4706, 1683, 29901, 13, 9651, 343, 29879, 29961, 29875, 1402, 343, 29879, 29961, 29926, 29962, 353, 343, 29879, 29961, 29926, 1402, 343, 29879, 29961, 29875, 29962, 13, 2 ]
freq_month.py	martengooz/github-scraper	1	148255	import numpy import json import time import datetime from dateutil.relativedelta import * import dateutil import dateutil.parser from scipy.stats.stats import pearsonr import matplotlib.pyplot as plt import scipy from operator import truediv with open('repos') as data_file: data = json.load(data_file) popularitylist = [] #print stars commitsPermonth = [] for repo in data: if repo['stargazers_count'] > 10 and repo['forks_count'] > 1 and repo['subscribers_count'] > 10 and len(repo['commit']) >100: lista = repo['commit'] endtime = lista[0] starttime = lista[len(lista)-1] endtime = endtime['date'] starttime = starttime['date'] endtime = endtime.encode('ascii') starttime = starttime.encode('ascii') starttime = starttime[:-1] endtime = endtime[:-1] start = dateutil.parser.parse(starttime) end = dateutil.parser.parse(endtime) #lista = lista[::-1] #currentmonth = start + relativedelta(months=+1) currentmonth = end - relativedelta(months=+1) commitsThismonth = 0 for commit in lista: if dateutil.parser.parse(commit['date'].encode('ascii')[:-1]) > currentmonth: commitsThismonth += 1 else: break commitsPermonth.append(commitsThismonth) #print longeststreak commitsThismonth = commitsThismonth/30.4368499 # convert to commits per hour commitsPermonth.append(commitsThismonth) #popularity = repo['forks_count'] popularity = repo['stargazers_count'] #popularity = repo['forks_count'] + repo['stargazers_count'] + repo['subscribers_count'] popularitylist.append(popularity) y = popularitylist x = commitsPermonth print "AVG = " + str(sum(x) / float(len(x))) slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(x, y) x = numpy.array(x) predict_y = intercept + slope * x plt.scatter(x, y) plt.plot(x, predict_y, 'k-', color="g", label="r = " + "{0:.4f}".format(r_value) +"\n" + "p = " + "{0:.4f}".format(p_value)) print(str(r_value) +", " + str(p_value)) lims = plt.xlim() plt.xlim([lims[0], lims[1]]) plt.xlabel("Commit/day") plt.ylabel("Stars") plt.title("Average daily commits last month (Stars)") plt.legend() plt.show()	[ 1, 1053, 12655, 13, 5215, 4390, 13, 5215, 931, 13, 5215, 12865, 13, 3166, 2635, 4422, 29889, 2674, 1926, 287, 2554, 1053, 334, 13, 5215, 2635, 4422, 13, 5215, 2635, 4422, 29889, 16680, 13, 3166, 4560, 2272, 29889, 16202, 29889, 16202, 1053, 282, 799, 1100, 29878, 13, 5215, 22889, 29889, 2272, 5317, 408, 14770, 13, 5215, 4560, 2272, 13, 3166, 5455, 1053, 534, 6742, 440, 13, 13, 2541, 1722, 877, 276, 1066, 1495, 408, 848, 29918, 1445, 29901, 13, 1678, 848, 353, 4390, 29889, 1359, 29898, 1272, 29918, 1445, 29897, 13, 7323, 1070, 537, 1761, 353, 5159, 13, 13, 13, 13, 29937, 2158, 10819, 13, 2055, 1169, 15737, 265, 386, 353, 5159, 13, 1454, 13761, 297, 848, 29901, 13, 12, 361, 13761, 1839, 303, 1191, 834, 414, 29918, 2798, 2033, 1405, 29871, 29896, 29900, 322, 13761, 1839, 29888, 548, 29879, 29918, 2798, 2033, 1405, 29871, 29896, 322, 13761, 1839, 1491, 7588, 2596, 29918, 2798, 2033, 1405, 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saifooler/classifiers/image_net_classifier.py	sailab-code/SAIFooler	0	12217	from saifooler.classifiers.classifier import Classifier import torch import json import os class ImageNetClassifier(Classifier): def __init__(self, model, args, kwargs): super().__init__(model, args, **kwargs) self.std = torch.tensor([0.229, 0.224, 0.225], device=self.device) self.mean = torch.tensor([0.485, 0.456, 0.406], device=self.device) class_index_path = os.path.join( os.path.dirname(__file__), "imagenet_class_index.json" ) self.class_dict = { int(key): val[1] for key, val in json.load(open(class_index_path)).items() } def to(self, device): super().to(device) self.mean = self.mean.to(device) self.std = self.std.to(device) def get_class_label(self, class_id: int): return self.class_dict[class_id] def normalize_image(self, image): """ :param image: tensor of shape (N, W, H, C) :return: image normalized for ImageNet and permuted in the shape (N, C, W, H) which is the shape used by torchvision models """ image = (image - self.mean) / self.std image = image.permute(0, 3, 1, 2) return image	[ 1, 515, 872, 361, 1507, 261, 29889, 1990, 14903, 29889, 1990, 3709, 1053, 4134, 3709, 13, 13, 5215, 4842, 305, 13, 5215, 4390, 13, 5215, 2897, 13, 13, 13, 1990, 7084, 6779, 2385, 3709, 29898, 2385, 3709, 1125, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 1904, 29892, 334, 5085, 29892, 3579, 19290, 1125, 13, 4706, 2428, 2141, 1649, 2344, 12035, 4299, 29892, 334, 5085, 29892, 3579, 19290, 29897, 13, 4706, 1583, 29889, 4172, 353, 4842, 305, 29889, 20158, 4197, 29900, 29889, 29906, 29906, 29929, 29892, 29871, 29900, 29889, 29906, 29906, 29946, 29892, 29871, 29900, 29889, 29906, 29906, 29945, 1402, 4742, 29922, 1311, 29889, 10141, 29897, 13, 4706, 1583, 29889, 12676, 353, 4842, 305, 29889, 20158, 4197, 29900, 29889, 29946, 29947, 29945, 29892, 29871, 29900, 29889, 29946, 29945, 29953, 29892, 29871, 29900, 29889, 29946, 29900, 29953, 1402, 4742, 29922, 1311, 29889, 10141, 29897, 13, 13, 4706, 770, 29918, 2248, 29918, 2084, 353, 2897, 29889, 2084, 29889, 7122, 29898, 13, 9651, 2897, 29889, 2084, 29889, 25721, 22168, 1445, 1649, 511, 13, 9651, 376, 326, 5370, 300, 29918, 1990, 29918, 2248, 29889, 3126, 29908, 13, 4706, 1723, 13, 4706, 1583, 29889, 1990, 29918, 8977, 353, 426, 13, 9651, 938, 29898, 1989, 1125, 659, 29961, 29896, 29962, 13, 9651, 363, 1820, 29892, 659, 297, 4390, 29889, 1359, 29898, 3150, 29898, 1990, 29918, 2248, 29918, 2084, 8106, 7076, 580, 13, 4706, 500, 13, 13, 1678, 822, 304, 29898, 1311, 29892, 4742, 1125, 13, 4706, 2428, 2141, 517, 29898, 10141, 29897, 13, 4706, 1583, 29889, 12676, 353, 1583, 29889, 12676, 29889, 517, 29898, 10141, 29897, 13, 4706, 1583, 29889, 4172, 353, 1583, 29889, 4172, 29889, 517, 29898, 10141, 29897, 13, 13, 1678, 822, 679, 29918, 1990, 29918, 1643, 29898, 1311, 29892, 770, 29918, 333, 29901, 938, 1125, 13, 4706, 736, 1583, 29889, 1990, 29918, 8977, 29961, 1990, 29918, 333, 29962, 13, 13, 1678, 822, 4226, 675, 29918, 3027, 29898, 1311, 29892, 1967, 1125, 13, 4706, 9995, 13, 13, 4706, 584, 3207, 1967, 29901, 12489, 310, 8267, 313, 29940, 29892, 399, 29892, 379, 29892, 315, 29897, 13, 4706, 584, 2457, 29901, 1967, 4226, 1891, 363, 7084, 6779, 322, 3635, 3860, 297, 278, 8267, 313, 29940, 29892, 315, 29892, 399, 29892, 379, 29897, 607, 338, 278, 8267, 13, 308, 1304, 491, 4842, 305, 4924, 4733, 13, 4706, 9995, 13, 4706, 1967, 353, 313, 3027, 448, 1583, 29889, 12676, 29897, 847, 1583, 29889, 4172, 13, 4706, 1967, 353, 1967, 29889, 17858, 1082, 29898, 29900, 29892, 29871, 29941, 29892, 29871, 29896, 29892, 29871, 29906, 29897, 13, 4706, 736, 1967, 13, 13, 2 ]
SimPEG/EM/Static/SIP/__init__.py	rolandhill/simpeg	3	164048	<gh_stars>1-10 from .ProblemSIP import Problem3D_CC, Problem3D_N from .ProblemSIP_2D import Problem2D_CC, Problem2D_N from .SurveySIP import Survey, Data, from_dc_to_sip_survey from . import SrcSIP as Src from . import RxSIP as Rx from .Run import run_inversion, spectral_ip_mappings	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 3166, 869, 26604, 5425, 29925, 1053, 11583, 29941, 29928, 29918, 4174, 29892, 11583, 29941, 29928, 29918, 29940, 13, 3166, 869, 26604, 5425, 29925, 29918, 29906, 29928, 1053, 11583, 29906, 29928, 29918, 4174, 29892, 11583, 29906, 29928, 29918, 29940, 13, 3166, 869, 18498, 6950, 5425, 29925, 1053, 23218, 29892, 3630, 29892, 515, 29918, 13891, 29918, 517, 29918, 29879, 666, 29918, 7610, 6950, 13, 3166, 869, 1053, 317, 2214, 5425, 29925, 408, 317, 2214, 13, 3166, 869, 1053, 390, 29916, 5425, 29925, 408, 390, 29916, 13, 3166, 869, 6558, 1053, 1065, 29918, 262, 3259, 29892, 23161, 29918, 666, 29918, 655, 27775, 13, 2 ]
creer/input.py	JeffreyStrahm/Creer	0	140015	<gh_stars>0 import glob def validate(inputs): validated_inputs = [] for input_dir in inputs: dirs = glob.glob(input_dir) if not dirs: raise Exception("No directories matching {}".format(input_dir)) validated_inputs.extend(dirs) for validated_input in validated_inputs: print(">> Input Directory:", validated_input) return validated_inputs	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 13149, 13, 13, 1753, 12725, 29898, 2080, 29879, 1125, 13, 1678, 2854, 630, 29918, 2080, 29879, 353, 5159, 13, 1678, 363, 1881, 29918, 3972, 297, 10970, 29901, 13, 4706, 4516, 29879, 353, 13149, 29889, 23705, 29898, 2080, 29918, 3972, 29897, 13, 4706, 565, 451, 4516, 29879, 29901, 13, 9651, 12020, 8960, 703, 3782, 17525, 9686, 6571, 1642, 4830, 29898, 2080, 29918, 3972, 876, 13, 4706, 2854, 630, 29918, 2080, 29879, 29889, 21843, 29898, 3972, 29879, 29897, 13, 13, 1678, 363, 2854, 630, 29918, 2080, 297, 2854, 630, 29918, 2080, 29879, 29901, 13, 4706, 1596, 703, 6778, 10567, 18862, 29901, 613, 2854, 630, 29918, 2080, 29897, 13, 13, 1678, 736, 2854, 630, 29918, 2080, 29879, 13, 2 ]
zict/zip.py	phobson/zict	0	7730	try: from collections.abc import MutableMapping except ImportError: from collections import MutableMapping import zipfile class Zip(MutableMapping): """Mutable Mapping interface to a Zip file Keys must be strings, values must be bytes Parameters ---------- filename: string mode: string, ('r', 'w', 'a'), defaults to 'a' Examples -------- >>> z = Zip('myfile.zip') # doctest: +SKIP >>> z['x'] = b'123' # doctest: +SKIP >>> z['x'] # doctest: +SKIP b'123' >>> z.flush() # flush and write metadata to disk # doctest: +SKIP """ def __init__(self, filename, mode="a"): self.filename = filename self.mode = mode self._file = None @property def file(self): if self.mode == "closed": raise OSError("File closed") if not self._file or not self._file.fp: self._file = zipfile.ZipFile(self.filename, mode=self.mode) return self._file def __getitem__(self, key): return self.file.read(key) def __setitem__(self, key, value): self.file.writestr(key, value) def keys(self): return 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blockchain/web3.py	joelwembo/expert-python-dts-algorithms	0	71573	# Block development using web3 """ >>> from web3 import Web3 # IPCProvider: >>> w3 = Web3(Web3.IPCProvider('./path/to/geth.ipc')) # HTTPProvider: >>> w3 = Web3(Web3.HTTPProvider('http://127.0.0.1:8545')) # WebsocketProvider: >>> w3 = Web3(Web3.WebsocketProvider('ws://127.0.0.1:8546')) >>> w3.isConnected() True """ from web3 import Web3 w3 = Web3(Web3.HTTPProvider('https://mainnet.infura.io/v3/<infura-project-id>')) from web3.auto.infura import w3 print (w3.eth.block_number) """ >>> from web3.beacon import Beacon j >>> beacon = Beacon("http://localhost:5051") """	[ 1, 396, 15658, 5849, 773, 1856, 29941, 13, 13, 15945, 29908, 8653, 515, 1856, 29941, 1053, 2563, 29941, 13, 13, 29937, 5641, 29907, 6980, 29901, 13, 6778, 29958, 281, 29941, 353, 2563, 29941, 29898, 3609, 29941, 29889, 5690, 29907, 6980, 877, 6904, 2084, 29914, 517, 29914, 29887, 621, 29889, 666, 29883, 8785, 13, 13, 29937, 7331, 6980, 29901, 13, 6778, 29958, 281, 29941, 353, 2563, 29941, 29898, 3609, 29941, 29889, 10493, 6980, 877, 1124, 597, 29896, 29906, 29955, 29889, 29900, 29889, 29900, 29889, 29896, 29901, 29947, 29945, 29946, 29945, 8785, 13, 13, 29937, 2563, 11514, 6980, 29901, 13, 6778, 29958, 281, 29941, 353, 2563, 29941, 29898, 3609, 29941, 29889, 3609, 11514, 6980, 877, 5652, 597, 29896, 29906, 29955, 29889, 29900, 29889, 29900, 29889, 29896, 29901, 29947, 29945, 29946, 29953, 8785, 13, 13, 6778, 29958, 281, 29941, 29889, 275, 20971, 2954, 580, 13, 5574, 9995, 13, 13, 3166, 1856, 29941, 1053, 2563, 29941, 13, 29893, 29941, 353, 2563, 29941, 29898, 3609, 29941, 29889, 10493, 6980, 877, 991, 597, 3396, 1212, 29889, 7192, 2002, 29889, 601, 29914, 29894, 29941, 29914, 29966, 7192, 2002, 29899, 4836, 29899, 333, 29958, 8785, 13, 13, 3166, 1856, 29941, 29889, 6921, 29889, 7192, 2002, 1053, 281, 29941, 13, 13, 2158, 313, 29893, 29941, 29889, 621, 29889, 1271, 29918, 4537, 29897, 13, 13, 15945, 29908, 8653, 515, 1856, 29941, 29889, 915, 23074, 1053, 1522, 23074, 29871, 432, 13, 6778, 29958, 367, 23074, 353, 1522, 23074, 703, 1124, 597, 7640, 29901, 29945, 29900, 29945, 29896, 1159, 9995, 13, 13, 13, 13, 2 ]
tas/__main__.py	lispsil/tas	1	29981	import os import signal import atexit import json import time from pathlib import Path import subprocess import argparse import pprint from distutils.util import strtobool children_pid = [] @atexit.register def kill_child(): for child_pid in children_pid: os.kill(child_pid, signal.SIGTERM) cmd_parser = argparse.ArgumentParser(add_help=False) cmd_parser.add_argument( "cmd", type=str, choices=["new", "del", "run", "set", "list"], help="Main command", ) args = cmd_parser.parse_known_args()[0] PATH_TO_SETTINGS = Path.home() / Path(".tas.json") def get_default_settings(): return { "namespaces": [ { "name": "default", "path": str(Path.home() / Path("Documents/tas_projects/")), } ], "templates": [ { "name": "default", "actions": [ {"type": "venv"}, {"type": "dir", "path": "py"}, {"type": "dir", "path": "py/src"}, {"type": "dir", "path": "sql"}, {"type": "dir", "path": "resources"}, {"type": "file", "path": "README.md"}, {"type": "requirements", "packages": ["jupyter"]}, {"type": "file_link", "url": ""} ], } ], "projects": [], } def load_settings(): if not PATH_TO_SETTINGS.exists(): return get_default_settings() with open(PATH_TO_SETTINGS) as f: return json.load(f) def save_settings(): with open(PATH_TO_SETTINGS, "w+") as f: json.dump(settings, f, ensure_ascii=False, indent=4) def lookup_in_list_of_dicts(l, name, return_index=False): for i, val in enumerate(l): if val["name"] == name: return val if not return_index else (i, val) return None if not return_index else (None, None) def get_proj(args, should_exist, ns_path): proj_name = f"{args.namespace}.{args.name}" proj_path = Path(ns_path) / Path(args.name) exists = lookup_in_list_of_dicts(settings["projects"], proj_name) if exists and not should_exist: raise Exception("Project already exists!") elif not exists and should_exist: raise Exception("Project not found!") return exists if exists else {"name": proj_name, "path": proj_path} def get_args(cmd): # TODO: create allowed combinations of args if cmd == "set": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("namespace", type=str, help="Namespace") args_parser.add_argument("path", type=str, help="PosixPath") elif cmd == "del": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("name", type=str, help="Name of an object") args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("type", type=str, choices=["n", "p"], default="p") elif cmd == "list": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument( "type", type=str, choices=["n", "t", "p", "a"], default="p" ) elif cmd == "new": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("name", type=str, help="Name") args_parser.add_argument( "-template", "-t", type=str, default="default", help="Template" ) args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("-path", "-p", type=str, help="PosixPath") elif cmd == "run": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("name", type=str, help="Project name") return args_parser.parse_args() def interactive_y_n(question): while True: try: reply = str(input(question + " (y/n): ")).lower().strip() return strtobool(reply) except ValueError as e: pprint.pprint("Please enter yes or no!") pass settings = load_settings() if __name__ == "__main__": extra_args = get_args(args.cmd) if args.cmd == "set": # TODO: make it interactive? ns_id, ns = lookup_in_list_of_dicts( settings["namespaces"], extra_args.namespace, return_index=True ) if ns_id != None: settings["namespaces"][ns_id] = {**ns, "path": extra_args.path} else: settings["namespaces"].append( {"name": extra_args.namespace, "path": extra_args.path} ) save_settings() elif args.cmd == "del": # TODO: interactive and delete projects if extra_args.type == "n": target = "namespaces" name = args.name elif extra_args.type == "p": target = "projects" ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, True, ns["path"]) name = proj["name"] target_id, ns = lookup_in_list_of_dicts( settings[target], name, return_index=True ) if target_id is None: raise Exception("No such name!") del settings[target][target_id] save_settings() elif args.cmd == "list": if extra_args.type == "n": pprint.pprint(settings["namespaces"]) elif extra_args.type == "p": pprint.pprint(settings["projects"]) elif extra_args.type == "t": pprint.pprint(settings["templates"]) elif extra_args.type == "a": pprint.pprint(settings) elif args.cmd == "new": ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, False, ns["path"]) template = lookup_in_list_of_dicts(settings["templates"], extra_args.template) if proj["path"].exists(): if not interactive_y_n("Path already exists. Should we proceed?"): exit() else: proj["path"].mkdir(parents=True) for action in template["actions"]: if action["type"] == "dir": (proj["path"] / Path(action["path"])).mkdir( parents=False, exist_ok=True ) elif action["type"] == "file": filepath = proj["path"] / Path(action["path"]) filepath.touch() elif action["type"] == "requirements": os.chdir(proj["path"]) subprocess.call( [ "python", "-m", "venv", "--system-site-packages", str(proj["path"] / Path("env")), ] ) if action["packages"]: subprocess.call( ["./env/bin/python", "-m", "pip", "install"] + action["packages"] ) filepath = proj["path"] / Path("requirements.txt") with filepath.open("w+") as f: f.write("\n".join(action["packages"])) settings["projects"].append({"name": proj["name"], "path": str(proj["path"])}) save_settings() elif args.cmd == "run": ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, True, ns["path"]) os.chdir(Path(proj["path"])) child = subprocess.Popen( 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projects/tests/test_migrations.py	18F/projects	9	103310	from unittest import SkipTest from django.apps import apps from django.test import TransactionTestCase from django.db.migrations.executor import MigrationExecutor from django.db import connection from django.conf import settings from test_without_migrations.management.commands.test import DisableMigrations class MigrationTestCase(TransactionTestCase): # https://www.caktusgroup.com/blog/2016/02/02/writing-unit-tests-django-migrations/ @property def app(self): return apps.get_containing_app_config(type(self).__module__).name migrate_from = None migrate_to = None def setUp(self): if isinstance(settings.MIGRATION_MODULES, DisableMigrations): raise SkipTest('migrations are disabled') assert self.migrate_from and self.migrate_to, \ ("TestCase '{}' must define migrate_from and " "migrate_to properties".format(type(self).__name__)) self.migrate_from = [(self.app, self.migrate_from)] self.migrate_to = [(self.app, self.migrate_to)] executor = MigrationExecutor(connection) old_apps = executor.loader.project_state(self.migrate_from).apps # Reverse to the original migration executor.migrate(self.migrate_from) self.setUpBeforeMigration(old_apps) # This wasn't part of the original code from the blog post, but # was mentioned as a required workaround in the comments. executor = MigrationExecutor(connection) # Run the migration to test executor.migrate(self.migrate_to) self.apps = executor.loader.project_state(self.migrate_to).apps def setUpBeforeMigration(self, apps): pass class TestPopulateIsBillable(MigrationTestCase): migrate_from = '0012_add_is_billable' migrate_to = '0013_populate_is_billable' BILLABLE = 0 NON_BILLABLE = 1 def setUpBeforeMigration(self, apps): Project = apps.get_model('projects', 'Project') self.billable_id = Project.objects.create( billable=self.BILLABLE ).id self.non_billable_id = Project.objects.create( billable=self.NON_BILLABLE ).id def test_migration_works(self): Project = 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firmwire/vendor/mtk/mtkdb/parse_mdb.py	j4s0n/FirmWire	0	172381	<reponame>j4s0n/FirmWire<filename>firmwire/vendor/mtk/mtkdb/parse_mdb.py ## Copyright (c) 2022, Team FirmWire ## SPDX-License-Identifier: BSD-3-Clause import struct import lzma import logging log = logging.getLogger(__name__) def reads32(f): x = f.read(4) return struct.unpack("<i", x)[0] def read32(f): x = f.read(4) return struct.unpack("<I", x)[0] def read16(f): x = f.read(2) return struct.unpack("<H", x)[0] def read8(f): x = f.read(1) return struct.unpack("<B", x)[0] def readCATD(f): magic = f.read(4) assert magic == b"CATD" idk1 = read32(f) idk2 = read32(f) magic = f.read(4) assert magic == b"HEAD" idk3 = read32(f) entrycount = read32(f) entries = [] for n in range(entrycount): idke1 = read32(f) entryoffset = read32(f) entrysize = read32(f) entries.append((idke1, entryoffset, entrysize)) log.debug(idke1, hex(entryoffset), hex(entrysize)) entries2 = [] for idke1, entryoffset, entrysize in entries: assert entrysize >= 16 f.seek(entryoffset) magic = f.read(4) assert magic == b"DATA" idkee1 = read32(f) offset = read32(f) size = read32(f) if entrysize < 20: uncompsize = size # a41..? else: uncompsize = read32(f) remainder = f.read(entrysize - 20) # log.debug(idke1, hex(size), hex(uncompsize), remainder.encode('hex')) log.debug(idke1, hex(size), hex(uncompsize)) entries2.append((idkee1, offset, remainder, size, uncompsize)) segments = [] for idkee1, offset, remainder, size, uncompsize in entries2: f.seek(offset) log.debug("%x (uncomp %x) bytes @ %x" % (size, uncompsize, offset)) s = f.read(16) log.debug(s.hex()) # if size != uncompsize: if size != uncompsize and s[:4] != b"CATD": # FIXME f.seek(offset) props = read8(f) dict_size = read32(f) lc = props % 9 props = int(props / 9) pb = int(props / 5) lp = props % 5 filters = [ { "id": lzma.FILTER_LZMA1, "dict_size": dict_size, "lc": lc, "lp": lp, "pb": pb, } ] decomp = lzma.decompress( f.read(size - 5), format=lzma.FORMAT_RAW, filters=filters ) segments += 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Constants.py	micv-dev/DeepKubeGPUCluster	2	18419	DEFAULT_KUBE_VERSION=1.14 KUBE_VERSION="kubeVersion" USER_ID="userId" DEFAULT_USER_ID=1 CLUSTER_NAME="clusterName" CLUSTER_MASTER_IP="masterHostIP" CLUSTER_WORKER_IP_LIST="workerIPList" FRAMEWORK_TYPE= "frameworkType" FRAMEWORK_VERSION="frameworkVersion" FRAMEWORK_RESOURCES="frameworkResources" FRAMEWORK_VOLUME_SIZE= "storageVolumeSizegb" FRAMEWORK_ASSIGN_DPU_TYPE= "dpuType" FRAMEWORK_ASSIGN_DPU_COUNT= "count" FRAMEWORK_INSTANCE_COUNT="instanceCount" FRAMEWORK_SPEC="spec" FRAMEWORK_IMAGE_NAME="imageName" FRAMEWORK_DPU_ID="dpuId" FRAMEWORK_DPU_COUNT="count" CLUSTER_ID="clusterId" FRAMEWORK_DEFAULT_PVC="/home/user/" DEFAULT_FRAMEWORK_TYPE="POLYAXON" DEFAULT_FRAMEWORK_VERSION="0.4.4" POLYAXON_TEMPLATE="templates/polyaxon_config" POLYAXON_CONFIG_FILE="/home/user/polyaxonConfig.yaml" POLYAXON_DEFAULT_NAMESPACE="polyaxon" TENSORFLOW_TEMPLATE="templates/tensorflow-gpu" DEFAULT_PATH="/home/user/" ##########Cluster Info#################### POD_IP="podIp" POD_STATUS="podStatus" POD_HOST_IP="hostIp" ##########End Of Cluster Info#################### PVC_MAX_ITERATIONS=50 SLEEP_TIME=5 GLUSTER_DEFAULT_MOUNT_PATH="/volume" CONTAINER_VOLUME_PREFIX="volume" MAX_RETRY_FOR_CLUSTER_FORM=10 ##############Cluster Related ####################33 CLUSTER_NODE_READY_COUNT=60 CLUSTER_NODE_READY_SLEEP=6 CLUSTER_NODE_NAME_PREFIX="worker" NO_OF_GPUS_IN_GK210_K80=2 POLYAXON_NODE_PORT_RANGE_START=30000 POLYAXON_NODE_PORT_RANGE_END=32767 DEFAULT_CIDR="10.244.0.0/16" GFS_STORAGE_CLASS="glusterfs" GFS_STORAGE_REPLICATION="replicate:2" HEKETI_REST_URL="http://10.138.0.2:8080" DEFAULT_VOLUME_MOUNT_PATH="/volume" GLUSTER_DEFAULT_REP_FACTOR=2 POLYAXON_DEFAULT_HTTP_PORT=80 POLYAXON_DEFAULT_WS_PORT=1337 SUCCESS_MESSAGE_STATUS="SUCCESS" ERROR_MESSAGE_STATUS="SUCCESS" ROLE="role" IP_ADDRESS="ipAddress" INTERNAL_IP_ADDRESS="internalIpAddress" ADD_NODE_USER_ID="hostUserId" ADD_NODE_PASSWORD="password" ####Polyaxon GetClusterInfo### QUOTA_NAME="quotaName" QUOTA_USED="used" QUOTA_LIMIT="limit" DEFAULT_QUOTA="default" VOLUME_NAME="volumeName" MOUNT_PATH_IN_POD="volumePodMountPath" VOLUME_TOTAL_SIZE="totalSize" VOLUME_FREE="free" NVIDIA_GPU_RESOURCE_NAME="requests.nvidia.com/gpu" EXECUTOR="executor" MASTER_IP="masterIP" GPU_COUNT="gpuCount" NAME="name" KUBE_CLUSTER_INFO="kubeClusterInfo" ML_CLUSTER_INFO="mlClusterInfo" POLYAXON_DEFAULT_USER_ID="root" POLYAXON_DEFAULT_PASSWORD="<PASSWORD>" POLYAXON_USER_ID="polyaxonUserId" POLYAXON_PASSWORD="<PASSWORD>" DEFAULT_DATASET_VOLUME_NAME="vol_f37253d9f0f35868f8e3a1d63e5b1915" DEFAULT_DATASET_MOUNT_PATH="/home/user/dataset" DEFAULT_CLUSTER_VOLUME_MOUNT_PATH="/home/user/volume" DEFAULT_GLUSTER_SERVER="10.138.0.2" DEFAULT_DATASET_VOLUME_SIZE="10Gi" CLUSTER_VOLUME_MOUNT_PATH="volumeHostMountPath" DATASET_VOLUME_MOUNT_POINT="dataSetVolumemountPointOnHost" DATASET_VOLUME_MOUNT_PATH_IN_POD_REST= "volumeDataSetPodMountPoint" DATASET_VOLUME_MOUNT_PATH_IN_POD="/dataset" DYNAMIC_GLUSTERFS_ENDPOINT_STARTS_WITH="glusterfs-dynamic-"	[ 1, 22236, 29918, 29968, 7466, 29923, 29918, 16358, 29922, 29896, 29889, 29896, 29946, 13, 29968, 7466, 29923, 29918, 16358, 543, 29895, 4003, 6594, 29908, 13, 13, 11889, 29918, 1367, 543, 29721, 29908, 13, 23397, 29918, 11889, 29918, 1367, 29922, 29896, 13, 6154, 17321, 1001, 29918, 5813, 543, 19594, 1170, 29908, 13, 6154, 17321, 1001, 29918, 1529, 1254, 1001, 29918, 5690, 543, 6207, 8514, 5690, 29908, 13, 6154, 17321, 1001, 29918, 11686, 29968, 1001, 29918, 5690, 29918, 24360, 543, 24602, 5690, 1293, 29908, 13, 29943, 4717, 2303, 11686, 29968, 29918, 11116, 29922, 376, 4468, 1542, 29908, 13, 29943, 4717, 2303, 11686, 29968, 29918, 16358, 543, 4468, 6594, 29908, 13, 29943, 4717, 2303, 11686, 29968, 29918, 1525, 27839, 27266, 543, 4468, 13770, 29908, 13, 29943, 4717, 2303, 11686, 29968, 29918, 29963, 5607, 29965, 2303, 29918, 14226, 29922, 376, 12925, 24679, 29903, 466, 387, 29890, 29908, 13, 29943, 4717, 2303, 11686, 29968, 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29899, 29908, 2 ]
currency/__init__.py	p4l1ly/currency	0	40280	# -- coding: utf-8 -- from .fetcher import from_all	[ 1, 396, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 13, 3166, 869, 9155, 261, 1053, 515, 29918, 497, 13, 2 ]
packaging/create_msi.py	physimals/quantiphyse	9	137225	""" Create an MSI package using the WIX toolset We adopt the rule of 'one file per component' as suggested although this requires thousands of components. Generation of GUIDs is accomplished by using the Python UUID library to generate the ID based on a hash of the file path. This should ensure that the GUIDs are specific to the file path (as required) and also reproducible (as required). The same technique is used to generate the product, upgrade GUID, using fixed notional paths for reproducibility """ import os, sys import uuid import shutil from six import StringIO MSI_SUBDIR = "msi" # Path to WIX toolset - update as required WIXDIR = "c:\Program Files (x86)/WiX Toolset v3.11/bin/" # Main template for our WXS file - content is added using the Python # string formatting placeholders WXS_TEMPLATE = """ <Wix xmlns="http://schemas.microsoft.com/wix/2006/wi"> <!-- MSI configuration for Quantiphyse This file is autogenerated but is stored in Git anyway, so we have a reference for the GUIDs which should not change for a given file path. As more installation files are added, it should be kept up to date in Git. --> <!-- Basic product information --> <Product Id="" UpgradeCode="%(upgrade_guid)s" Name="Quantiphyse" Version="%(version_str)s" Manufacturer="ibme-qubic" Language="1033"> <Package Id="" InstallerVersion="200" Compressed="yes" Comments="Windows Installer Package" Platform="x64"/> <Media Id="1" Cabinet="product.cab" EmbedCab="yes"/> <MajorUpgrade AllowDowngrades="no" DowngradeErrorMessage="Cannot downgrade to lower version - remove old version first" AllowSameVersionUpgrades="no"/> <Directory Id="TARGETDIR" Name="SourceDir"> <!-- Installation registry entries and shortcut --> <Component Id="RegKeys" Guid="%(regkeys_guid)s" Win64="yes"> <RegistryKey Root='HKLM' Key='Software\[Manufacturer]\[ProductName]'> <RegistryValue Type='string' Name='InstallDir' Value='[INSTALLDIR1]' KeyPath='yes'/> <RegistryValue Type='string' Name='PluginDir' Value='[INSTALLDIR1]packages\plugins'/> </RegistryKey> </Component> <!-- Programs menu registry entry and shortcut --> <Directory Id="ProgramMenuFolder" Name="Programs"> <Directory Id="ProgramMenuDir" Name="Quantiphyse"> <Component Id="ProgramMenuDir" Guid="%(menu_guid)s" Win64="yes"> <RemoveFolder Id='ProgramMenuDir' On='uninstall' /> <RegistryValue Root='HKCU' Key='Software\[Manufacturer]\[ProductName]' Type='string' Value='' KeyPath='yes'/> </Component> </Directory> </Directory> <!-- Program files --> <Directory Id="ProgramFiles64Folder"> %(dist_files)s </Directory> </Directory> <!-- No custom features - all or nothing --> <Feature Id="Complete" Level="1"> %(features)s <ComponentRef Id="ProgramMenuDir"/> <ComponentRef Id="RegKeys"/> </Feature> <!-- User interface configuration --> <Property Id="WIXUI_INSTALLDIR" Value="INSTALLDIR" /> <UIRef Id="WixUI_Minimal" /> <UIRef Id="WixUI_ErrorProgressText" /> <WixVariable Id="WixUIBannerBmp" Value="packaging/images/banner.bmp" /> <WixVariable Id="WixUIDialogBmp" Value="packaging/images/dialog.bmp" /> <WixVariable Id="WixUILicenseRtf" Value="packaging/licence.rtf"/> <Icon Id="main_icon.ico" SourceFile="quantiphyse/icons/main_icon.ico" /> <Property Id="ARPPRODUCTICON" Value="main_icon.ico" /> </Product> </Wix>""" # Minimal RTF template used to turn the license text into RTF RTF_TEMPLATE = """{\\rtf {\\fonttbl {\\f0 Courier;}} \\f0\\fs20 %s }""" def get_guid(path): """ Return a GUID which is reproducibly tied to a file path """ return uuid.uuid5(uuid.NAMESPACE_DNS, 'quantiphyse.org/' + os.path.normpath(path)) def add_files_in_dir(distdir, pkgdir, nfile, ndir, output, indent): """ Add file componenents from a directory, recursively adding from subdirs """ output.write('%s<Directory Id="INSTALLDIR%i" Name="%s">\n' % (indent, ndir, os.path.basename(pkgdir))) ndir += 1 for dirName, subdirList, fileList in os.walk(os.path.join(distdir, pkgdir)): for fname in fileList: srcpath = os.path.join(distdir, pkgdir, fname) # Generate GUID based on destination path relative to install location destpath = os.path.join(pkgdir, fname) guid = get_guid(destpath) # Write component XML output.write('%s <Component Id="Component%i" Guid="%s" Win64="yes">\n' % (indent, nfile, str(guid))) if fname == "quantiphyse.exe": output.write('%s <File Id="File%i" Source="%s" KeyPath="yes">\n' % (indent, nfile, srcpath)) output.write('%s <Shortcut Id="startmenu_qp" Directory="ProgramMenuDir" Name="Quantiphyse"\n' % indent) output.write('%s WorkingDirectory="INSTALLDIR" Icon="main_icon.ico" Advertise="yes"/>\n' % indent) output.write('%s </File>\n' % indent) else: output.write('%s <File Id="File%i" Source="%s" KeyPath="yes"/>\n' % (indent, nfile, srcpath)) output.write('%s </Component>\n' % indent) nfile += 1 for child in subdirList: # Deal with subdirs recursively nfile, ndir = add_files_in_dir(distdir, os.path.join(pkgdir, child), nfile, ndir, output, indent + " ") # os.walk is recursive by default but we do not want this so break out after first listing break output.write('%s</Directory>\n' % indent) return nfile, ndir def create_wxs(distdir, version_str, wxs_fname): """ Create the WXS file for WIX toolset to create the MSI """ formatting_values = { "version_str" : version_str.replace("-", "."), "product_guid" : get_guid('quantiphyse/product'), "upgrade_guid" : get_guid('quantiphyse/upgrade'), "menu_guid" : get_guid('quantiphyse/menu'), "regkeys_guid" : get_guid('quantiphyse/regkeys'), } output = StringIO() nfile, ndir = add_files_in_dir(distdir, "quantiphyse", 1, 1, output, " " * 5) formatting_values["dist_files"] = output.getvalue() output = StringIO() for n in range(nfile-1): output.write(' <ComponentRef Id="Component%i"/>\n' % (n+1)) formatting_values["features"] = output.getvalue() output = open(wxs_fname, 'w') output.write(WXS_TEMPLATE % formatting_values) output.close() def convert_licence(txt_fname, rtf_fname): f = open(txt_fname, "r") txt = "\\line ".join(f.readlines()) f.close() f = open(rtf_fname, "w") f.write(RTF_TEMPLATE % txt) f.close() def create_msi(distdir, pkgdir, version_str, sysname, version_str_display=None): """ Create the MSI itself using WIX toolset """ if version_str_display == None: version_str_display = version_str qpdir = os.path.join(distdir, os.pardir) convert_licence(os.path.join(qpdir, "LICENSE"), os.path.join(pkgdir, "licence.rtf")) msidir = os.path.join(pkgdir, MSI_SUBDIR) shutil.rmtree(msidir, ignore_errors=True) os.makedirs(msidir) wxs_fname = os.path.join(msidir, "quantiphyse.wxs") obj_fname = os.path.join(msidir, "quantiphyse.wixobj") msi_fname = os.path.join(msidir, "quantiphyse-%s.msi" % version_str_display) create_wxs(distdir, version_str, wxs_fname) os.system('"%s/candle.exe" %s -out %s >%s/msi.out 2>&1' % (WIXDIR, wxs_fname, obj_fname, msidir)) os.system('"%s/light.exe" %s -out %s -ext WixUIExtension >>%s/msi.out 2>&1' % (WIXDIR, obj_fname, msi_fname, msidir)) shutil.move(msi_fname, distdir) if __name__ == "__main__": # Get absolute paths to the packaging dir and the root Quantiphyse dir pkgdir = 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lecturegen_old.py	ucsb-cs-course-repos/tools	0	163170	#!/usr/bin/env python3 import argparse import pytest import datetime import dateutil from dateutil.parser import parse import os legal_days_of_week="MTWRF" def mkdir_p(newdir): """works the way a good mkdir should :) - already exists, silently complete - regular file in the way, raise an exception - parent directory(ies) does not exist, make them as well Source: http://code.activestate.com/recipes/82465-a-friendly-mkdir/ Note: os.makedirs() already makes all directories in the path but raises an exception if directory already exists. """ if os.path.isdir(newdir): pass elif os.path.isfile(newdir): raise OSError("a file with the same name as the desired " \ "dir, '%s', already exists." % newdir) else: head, tail = os.path.split(newdir) if head and not os.path.isdir(head): mkdir_p(head) #print "_mkdir %s" % repr(newdir) if tail: os.mkdir(newdir) def validate_days_of_week(days_of_week): for c in days_of_week: if c not in legal_days_of_week: raise ValueError("days_of_week should contain only chars from" + legal_days_of_week) def validate_date(date): result = dateutil.parser.parse(date) return result def validate_start_date(date): result = validate_date(date) sunday = 6 # see: https://docs.python.org/2/library/datetime.html day_of_week = result.weekday() if day_of_week != sunday: raise ValueError("Start Date should be a Sunday") return result def add_weeks(start_datetime,weeks): """ Return a datetime that is start_datetime plus weeks into the future Example: start_datetime represents 2019-03-31, weeks is 0 => 2019-03-31 start_datetime represents 2019-03-31, weeks is 1 => 2019-04-07 start_datetime represents 2019-03-31, weeks is 2 => 2019-04-14 """ days_ahead = weeks * 7 final_datetime = n_days_ahead(start_datetime, 7*weeks) return final_datetime def n_days_ahead(start_datetime, days): """ Return a datetime that is start_datetime plus days into the future """ delta = datetime.timedelta(days = days) return start_datetime + delta def days_for_this_week(start_datetime, dates): """ Return a tuple of len(dates) datetimes, one for each lecture day start_datetime is the first lecture day of the week, the rest are calculated by addings days forward according to dates Warning: Does not account for holidays (see days_without_holidays) """ days_this_week = [] for d in dates: day_num = day_to_num(d) + 1 #Plus 1 so Monday is offset 1 from Sunday days_this_week.append(n_days_ahead(start_datetime, day_num)) return days_this_week def days_without_holidays(days_of_week, holiday_list): """ Given a tuple for the two lecture days of the week, returns a list of valid dates, removing any that clash with holidays """ sanitized_holidays = [] for h in holiday_list: sanitized_holidays.append(parse(h)) sanitized_dates = [] for day in days_of_week: if day not in sanitized_holidays: sanitized_dates.append(day) return sanitized_dates def day_to_num(day): if day == "M": return 0 elif day == "T": return 1 elif day == "W": return 2 elif day == "R": return 3 elif day == "F": return 4 else: raise ValueError("day_to_num should contain only chars from" + legal_days_of_week) def find_first_lect_datetime(start_datetime, days_of_week): """ Note: No longer using this function In the case where start_datetime is not the first lecture date, this function returns the first lecture's date """ first_day = days_of_week[0] dayNum = day_to_num(first_day) first_lect = start_datetime while first_lect.weekday() != dayNum: first_lect = n_days_ahead(first_lect, 1) return first_lect def make_date_list(start_date, weeks, days_of_week, holiday_list): """ return list of date strings in yyyy-mm-dd format Example: TODO shouldn't the 3 below be 2? As this is for 2 weeks? make_date_list("2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) => ["2019-04-01","2019-04-03","2019-04-10"] """ validate_days_of_week(days_of_week) start_datetime = validate_start_date(start_date) final_datetimes = [] for i in range(weeks): start_of_week_datetime = add_weeks(start_datetime,i) days_this_week_unsanitized = days_for_this_week(start_of_week_datetime, days_of_week) days_this_week_sanitized = days_without_holidays(days_this_week_unsanitized, holiday_list) final_datetimes.append(days_this_week_sanitized) return final_datetimes def lecture_gen(path, start_date, weeks, days_of_week, holiday_list): """ Creates a _lectures directory in the given path with premade lecture stubs according to the other fields: start date, number of weeks, days of the week that the lecture is on, and a list of holidays that lectures can not be held on. """ #Create path: directory_path = os.path.join(path, "_lectures") try: mkdir_p(directory_path) except OSError: print ("Creation of the directory %s failed" % directory_path) return else: print ("Successfully created the directory %s" % directory_path) #create valid dates listing: valid_dates = make_date_list(start_date, weeks, days_of_week, holiday_list) lecture_num = 0 for dates_by_week in valid_dates: for date in dates_by_week: lecture_num += 1 #first lecture num will be 1 filename = "lecture" + str(lecture_num) f = open(os.path.join(directory_path, filename), "w+") f.write("---\n") f.write("num: " + '"lect' + str(lecture_num) + '"\n') f.write("lecture_date: " + str(date.date()) + "\n") f.write("desc: " + '\n') f.write("ready: " + "false\n") f.write("pdfurl: " + "\n") f.write("---\n") f.close() if __name__=="__main__": #lecture_gen(os.getcwd(), "2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) print("valid dates 1") valid_dates = make_date_list("2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) print(valid_dates) print("valid dates 2") valid_dates2 = make_date_list("2019-03-31",2,"MWF",["2019-04-08","2019-04-09"]) print(valid_dates2) print("valid dates 3") valid_dates3 = make_date_list("2019-03-31",2,"TWR",["2019-04-08","2019-04-09"]) print(valid_dates3)	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 29941, 13, 13, 5215, 1852, 5510, 13, 5215, 11451, 1688, 13, 5215, 12865, 13, 5215, 2635, 4422, 13, 3166, 2635, 4422, 29889, 16680, 1053, 6088, 13, 5215, 2897, 13, 13, 12018, 29918, 16700, 29918, 974, 29918, 18448, 543, 11490, 9980, 29943, 29908, 13, 13, 1753, 29356, 29918, 29886, 29898, 1482, 3972, 1125, 13, 1678, 9995, 13129, 278, 982, 263, 1781, 29356, 881, 4248, 13, 4706, 448, 2307, 4864, 29892, 4047, 2705, 4866, 13, 4706, 448, 4943, 934, 297, 278, 982, 29892, 12020, 385, 3682, 13, 4706, 448, 3847, 3884, 29898, 583, 29897, 947, 451, 1863, 29892, 1207, 963, 408, 1532, 13, 13, 539, 7562, 29901, 1732, 597, 401, 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mailer/settings.py	mvpoland/django-mailer	0	128645	<reponame>mvpoland/django-mailer from django.conf import settings """ Add here dictionary of extra headers pushed forward to django's EmailMultiAlternatives and EmailMessage. Example: to activate click and open action for e-mails sent by Mandrillapp you'll need to define this as follows: MAIL_EXTRA_HEADERS = {'X-MC-Track': 'opens,clicks'} """ MAILER_EXTRA_HEADERS = getattr(settings, "MAILER_EXTRA_HEADERS", None)	[ 1, 529, 276, 1112, 420, 29958, 29324, 3733, 392, 29914, 14095, 29899, 2549, 261, 13, 3166, 9557, 29889, 5527, 1053, 6055, 13, 13, 13, 15945, 29908, 3462, 1244, 8600, 310, 4805, 9066, 18760, 6375, 304, 9557, 29915, 29879, 22608, 15329, 2499, 725, 5056, 322, 22608, 3728, 29889, 13, 13, 14023, 29901, 13, 1678, 304, 5039, 403, 2828, 322, 1722, 3158, 363, 321, 29899, 2549, 29879, 2665, 491, 15419, 29878, 2911, 407, 366, 29915, 645, 817, 304, 4529, 445, 408, 4477, 29901, 13, 13, 1678, 14861, 6227, 29918, 12194, 4717, 29918, 23252, 23598, 353, 11117, 29990, 29899, 12513, 29899, 17936, 2396, 525, 22156, 29892, 3808, 29879, 10827, 13, 13, 15945, 29908, 13, 1529, 6227, 1001, 29918, 12194, 4717, 29918, 23252, 23598, 353, 679, 5552, 29898, 11027, 29892, 376, 1529, 6227, 1001, 29918, 12194, 4717, 29918, 23252, 23598, 613, 6213, 29897, 13, 2 ]
dito/highgui.py	dhaase-de/dito	0	189847	import abc import copy import cv2 import dito.visual class Slider(abc.ABC): def __init__(self, window_name, name, initial_raw_value, max_raw_value): assert max_raw_value > 0 assert 0 <= initial_raw_value <= max_raw_value self.window_name = window_name if self.window_name is None: self.window_name = dito.visual.DEFAULT_WINDOW_NAME self.name = name self.initial_raw_value = initial_raw_value self.max_raw_value = max_raw_value self.create_trackbar() self.changed = True def callback(self, raw_value): self.changed = True self.custom_callback() def custom_callback(self): pass def create_trackbar(self): cv2.namedWindow(winname=self.window_name) cv2.createTrackbar(self.name, self.window_name, self.initial_raw_value, self.max_raw_value, self.callback) def get_raw_value(self): self.changed = False return cv2.getTrackbarPos(trackbarname=self.name, winname=self.window_name) def set_raw_value(self, raw_value): if raw_value < 0: raw_value = 0 elif raw_value > self.max_raw_value: raw_value = self.max_raw_value cv2.setTrackbarPos(trackbarname=self.name, winname=self.window_name, pos=raw_value) def reset(self): self.set_raw_value(raw_value=self.initial_raw_value) @abc.abstractmethod def raw_from_value(self, value): pass @abc.abstractmethod def value_from_raw(self, raw_value): pass def get_value(self): raw_value = self.get_raw_value() return self.value_from_raw(raw_value=raw_value) def set_value(self, value): raw_value = self.raw_from_value(value=value) self.set_raw_value(raw_value=raw_value) class ChoiceSlider(Slider): def __init__(self, window_name, name, choices, initial_choice=None): self.choices = copy.deepcopy(choices) super().__init__( name=name, window_name=window_name, initial_raw_value=0 if initial_choice is None else self.raw_from_value(value=initial_choice), max_raw_value=len(self.choices) - 1, ) def raw_from_value(self, value): return self.choices.index(value) def value_from_raw(self, raw_value): return self.choices[raw_value] class BoolSlider(Slider): def __init__(self, window_name, name, initial_value=False): super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=initial_value), max_raw_value=1, ) def raw_from_value(self, value): return 1 if value else 0 def value_from_raw(self, raw_value): return raw_value > 0 class IntegerSlider(Slider): def __init__(self, window_name, name, min_value, max_value, initial_value=None): self.min_value = min_value self.max_value = max_value super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=self.resolve_initial_value(initial_value=initial_value)), max_raw_value=self.max_value - self.min_value, ) def resolve_initial_value(self, initial_value): if isinstance(initial_value, int): return initial_value if initial_value is None: return self.min_value if initial_value == "min": return self.min_value if initial_value == "max": return self.max_value if initial_value == "mean": return (self.max_value - self.min_value) // 2 + self.min_value raise RuntimeError("Invalid initial value '{}'".format(initial_value)) def raw_from_value(self, value): return value - self.min_value def value_from_raw(self, raw_value): return self.min_value + raw_value class FloatSlider(Slider): def __init__(self, window_name, name, min_value, max_value, value_count=101, initial_value=None): self.min_value = min_value self.max_value = max_value self.value_count = value_count super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=self.resolve_initial_value(initial_value=initial_value)), max_raw_value=self.value_count - 1, ) def resolve_initial_value(self, initial_value): if isinstance(initial_value, float): return initial_value if initial_value is None: return self.min_value if initial_value == "min": return self.min_value if initial_value == "max": return self.max_value if initial_value == "mean": return (self.max_value - self.min_value) * 0.5 + 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tests/plugins/test_brittv.py	fuglede/streamlink	0	38153	<gh_stars>0 import unittest from streamlink.plugins.brittv import BritTV class TestPluginBritTV(unittest.TestCase): def test_can_handle_url(self): should_match = [ 'http://brittv.co.uk/watch/?channel=1', ] for url in should_match: self.assertTrue(BritTV.can_handle_url(url)) def test_can_handle_url_negative(self): should_not_match = [ 'https://example.com/index.html', ] for url in should_not_match: self.assertFalse(BritTV.can_handle_url(url))	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 443, 27958, 13, 13, 3166, 4840, 2324, 29889, 12800, 29889, 29890, 12123, 29894, 1053, 3230, 8050, 13, 13, 13, 1990, 4321, 16288, 29933, 768, 8050, 29898, 348, 27958, 29889, 3057, 8259, 1125, 13, 1678, 822, 1243, 29918, 3068, 29918, 8411, 29918, 2271, 29898, 1311, 1125, 13, 4706, 881, 29918, 4352, 353, 518, 13, 9651, 525, 1124, 597, 29890, 12123, 29894, 29889, 1111, 29889, 2679, 29914, 12344, 13401, 12719, 29922, 29896, 742, 13, 4706, 4514, 13, 4706, 363, 3142, 297, 881, 29918, 4352, 29901, 13, 9651, 1583, 29889, 9294, 5574, 29898, 29933, 768, 8050, 29889, 3068, 29918, 8411, 29918, 2271, 29898, 2271, 876, 13, 13, 1678, 822, 1243, 29918, 3068, 29918, 8411, 29918, 2271, 29918, 22198, 29898, 1311, 1125, 13, 4706, 881, 29918, 1333, 29918, 4352, 353, 518, 13, 9651, 525, 991, 597, 4773, 29889, 510, 29914, 2248, 29889, 1420, 742, 13, 4706, 4514, 13, 4706, 363, 3142, 297, 881, 29918, 1333, 29918, 4352, 29901, 13, 9651, 1583, 29889, 9294, 8824, 29898, 29933, 768, 8050, 29889, 3068, 29918, 8411, 29918, 2271, 29898, 2271, 876, 13, 2 ]
ponyexpress/models/__init__.py	TelekomCloud/pony-express	0	66895	from ponyexpress.models.repository import Repository from ponyexpress.models.repo_history import RepoHistory from ponyexpress.models.package import Package from ponyexpress.models.package_history import PackageHistory from ponyexpress.models.node import Node	[ 1, 515, 282, 2592, 17073, 29889, 9794, 29889, 19033, 1053, 830, 7036, 13, 3166, 282, 2592, 17073, 29889, 9794, 29889, 20095, 29918, 18434, 1053, 830, 1129, 20570, 13, 3166, 282, 2592, 17073, 29889, 9794, 29889, 5113, 1053, 22029, 13, 3166, 282, 2592, 17073, 29889, 9794, 29889, 5113, 29918, 18434, 1053, 22029, 20570, 13, 3166, 282, 2592, 17073, 29889, 9794, 29889, 3177, 1053, 9071, 13, 2 ]
krogon/maybe.py	enamrik/krogon	1	8606	from typing import Callable, TypeVar, Union, Tuple from krogon.infix import Infix A = TypeVar('A') B = TypeVar('B') E = TypeVar('E') Maybe = Union[Tuple['just', A], Tuple['nothing']] def just(value=None): return "just", value def nothing(): return "nothing", None def from_value(value) -> Maybe[B]: return _cast_to_maybe(value) def from_value_or_default(value, default) -> Maybe[B]: return from_maybe( _cast_to_maybe(value), dict(if_just=lambda x: just(x), if_nothing=lambda: _cast_to_maybe(default))) @Infix def then(maybe: Maybe[A], func: Callable[[A], Maybe[B]]) -> Maybe[B]: if maybe[0] == "just": return _cast_to_maybe(func(maybe[1])) elif maybe[0] == "nothing": return maybe @Infix def catch_nothing(maybe: Maybe[A], func: Callable[[A], Maybe[B]]) -> Maybe[B]: if maybe[0] == "nothing": return _cast_to_maybe(func()) elif maybe[0] == "just": return maybe @Infix def map(maybe: Maybe[A], mapper: Callable[[A], B]) -> Maybe[B]: if maybe[0] == "just": return just(mapper(maybe[1])) elif maybe[0] == "nothing": return maybe @Infix def value_or_default(maybe: Maybe[A], default_value: B): return maybe \| from_maybe \| (dict(if_just=lambda x: x, if_nothing=lambda: default_value)) @Infix def from_maybe(maybe: Maybe[A], dict_args: dict) -> B: if_just: Callable = dict_args['if_just'] if_nothing: Callable = dict_args['if_nothing'] if maybe[0] == "just" and if_just is not None: return if_just(maybe[1]) elif maybe[0] == "nothing" and if_nothing is not None: return if_nothing() else: raise Exception('Invalid Maybe: {}, {}'.format(maybe, dict_args)) def _cast_to_maybe(result): if result is None: return nothing() if isinstance(result, tuple) and len(result) == 2: maybe_type, value = result if maybe_type == "just" or maybe_type == "nothing": return result return just(result)	[ 1, 515, 19229, 1053, 8251, 519, 29892, 5167, 9037, 29892, 7761, 29892, 12603, 552, 13, 3166, 413, 9102, 265, 29889, 262, 5878, 1053, 512, 5878, 13, 13, 29909, 353, 5167, 9037, 877, 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crontab_module/crons/update_predicted_location_crontab.py	openmaker-eu/watchtower	2	181067	<reponame>openmaker-eu/watchtower<gh_stars>1-10 import sys from decouple import config sys.path.insert(0, config("ROOT_DIR")) from predict_location.update_field_db import update_field_db as up_db database_names = ["audience_test", "events"] field_names = ["location", "place"] for ind in range(len(database_names)): up_db(database_names[ind], field_names[ind])	[ 1, 529, 276, 1112, 420, 29958, 3150, 28107, 29899, 12932, 29914, 12344, 29873, 1680, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 5215, 10876, 13, 3166, 1602, 283, 552, 1053, 2295, 13, 9675, 29889, 2084, 29889, 7851, 29898, 29900, 29892, 2295, 703, 21289, 29918, 9464, 5783, 13, 3166, 8500, 29918, 5479, 29889, 5504, 29918, 2671, 29918, 2585, 1053, 2767, 29918, 2671, 29918, 2585, 408, 701, 29918, 2585, 13, 13, 9803, 29918, 7039, 353, 6796, 28863, 663, 29918, 1688, 613, 376, 13604, 3108, 13, 2671, 29918, 7039, 353, 6796, 5479, 613, 376, 6689, 3108, 13, 13, 1454, 1399, 297, 3464, 29898, 2435, 29898, 9803, 29918, 7039, 22164, 13, 1678, 701, 29918, 2585, 29898, 9803, 29918, 7039, 29961, 513, 1402, 1746, 29918, 7039, 29961, 513, 2314, 13, 2 ]
aiovault/client.py	johnnoone/aiovault	1	31299	from . import v1 from .request import Request from .util import task, extract_id class Vault(v1.SysEndpoint): def __init__(self, addr, token=None, cert=None, verify=True): token = extract_id(token) self.req_handler = Request(addr, 'v1', token=token, cert=cert, verify=verify) @property def audit(self): return v1.AuditEndpoint(self.req_handler) @property def auth(self): return v1.AuthEndpoint(self.req_handler) @property def lease(self): return v1.LeaseEndpoint(self.req_handler) @property def policy(self): return v1.PolicyEndpoint(self.req_handler) @property def raw(self): return v1.RawEndpoint(self.req_handler) @property def seal(self): return v1.SealEndpoint(self.req_handler) @property def secret(self): return v1.SecretEndpoint(self.req_handler) @task def login(self, args, kwargs): return self.auth.login(args, kwargs) @task def read(self, path, kwargs): method = kwargs.pop('method', 'GET') response = yield from self.req_handler(method, path, kwargs) return response @task def write(self, path, kwargs): method = kwargs.pop('method', 'POST') response = yield from self.req_handler(method, path, kwargs) return response @task def delete(self, path, kwargs): method = kwargs.pop('method', 'DELETE') response = yield from self.req_handler(method, path, **kwargs) return response def __repr__(self): return '<Vault(addr=%r)>' % self.req_handler.addr	[ 1, 515, 869, 1053, 325, 29896, 13, 3166, 869, 3827, 1053, 10729, 13, 3166, 869, 4422, 1053, 3414, 29892, 6597, 29918, 333, 13, 13, 13, 1990, 478, 1292, 29898, 29894, 29896, 29889, 29903, 952, 25602, 1125, 13, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 28915, 29892, 5993, 29922, 8516, 29892, 2284, 29922, 8516, 29892, 11539, 29922, 5574, 1125, 13, 4706, 5993, 353, 6597, 29918, 333, 29898, 6979, 29897, 13, 4706, 1583, 29889, 7971, 29918, 13789, 353, 10729, 29898, 10030, 29892, 525, 29894, 29896, 742, 5993, 29922, 6979, 29892, 13, 462, 462, 259, 2284, 29922, 6327, 29892, 11539, 29922, 27902, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 12990, 277, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 29909, 566, 277, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 4817, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 6444, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 454, 559, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 3226, 559, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 8898, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 15644, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 10650, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 22131, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 409, 284, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 2008, 284, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 6799, 13, 1678, 822, 7035, 29898, 1311, 1125, 13, 4706, 736, 325, 29896, 29889, 28459, 25602, 29898, 1311, 29889, 7971, 29918, 13789, 29897, 13, 13, 1678, 732, 7662, 13, 1678, 822, 6464, 29898, 1311, 29892, 334, 5085, 29892, 3579, 19290, 1125, 13, 4706, 736, 1583, 29889, 5150, 29889, 7507, 10456, 5085, 29892, 3579, 19290, 29897, 13, 13, 1678, 732, 7662, 13, 1678, 822, 1303, 29898, 1311, 29892, 2224, 29892, 3579, 19290, 1125, 13, 4706, 1158, 353, 9049, 5085, 29889, 7323, 877, 5696, 742, 525, 7194, 1495, 13, 4706, 2933, 353, 7709, 515, 1583, 29889, 7971, 29918, 13789, 29898, 5696, 29892, 2224, 29892, 3579, 19290, 29897, 13, 4706, 736, 2933, 13, 13, 1678, 732, 7662, 13, 1678, 822, 2436, 29898, 1311, 29892, 2224, 29892, 3579, 19290, 1125, 13, 4706, 1158, 353, 9049, 5085, 29889, 7323, 877, 5696, 742, 525, 5438, 1495, 13, 4706, 2933, 353, 7709, 515, 1583, 29889, 7971, 29918, 13789, 29898, 5696, 29892, 2224, 29892, 3579, 19290, 29897, 13, 4706, 736, 2933, 13, 13, 1678, 732, 7662, 13, 1678, 822, 5217, 29898, 1311, 29892, 2224, 29892, 3579, 19290, 1125, 13, 4706, 1158, 353, 9049, 5085, 29889, 7323, 877, 5696, 742, 525, 2287, 18476, 1495, 13, 4706, 2933, 353, 7709, 515, 1583, 29889, 7971, 29918, 13789, 29898, 5696, 29892, 2224, 29892, 3579, 19290, 29897, 13, 4706, 736, 2933, 13, 13, 1678, 822, 4770, 276, 558, 12035, 1311, 1125, 13, 4706, 736, 12801, 29963, 1292, 29898, 10030, 16328, 29878, 15410, 29915, 1273, 1583, 29889, 7971, 29918, 13789, 29889, 10030, 13, 2 ]
6.py	rowanG077/automated_reasoning	0	102177	<reponame>rowanG077/automated_reasoning from z3 import * from copy import deepcopy import sys num_stores = 1 num_villages = 4 route_costs_list = [ [-1, 15, -1, 15, -1], [15, -1, 17, 12, -1], [-1, 17, -1, 10, 20], [15, 12, 10, -1, 20], [-1, -1, 20, 20, -1], ] assignment_b = False capacities = [ 260 if assignment_b else 250, 110, 160, 110, 160, ] num_eval = 14 if assignment_b else 32 route_costs = Array('routes', IntSort(), ArraySort(IntSort(), IntSort())) truck_pos = [Int(f"truck_pos_{i}") for i in range(num_eval)] truck_store = [Int(f"truck_store_{i}") for i in range(num_eval)] village_store = [[Int(f"vilage_store_{chr(ord('A') + v)}_{i}") for v in range(num_villages)] for i in range(num_eval)] if assignment_b: world_hunger_save = [[Bool(f"world_hunger_{n1}_{n2}") for n2 in range(n1 + 1, num_eval)] for n1 in range(num_eval)] def print_solution(model): cycle_arrows = [" " for i in range(num_eval)] if assignment_b: for n1 in range(num_eval): for n2 in range(n1 + 1, num_eval): if is_true(model.eval(world_hunger_save[n1][n2 - n1 - 1])): cycle_arrows[n1] = "-->" cycle_arrows[n2] = "-->" print(" cycle, truck pos, truck storage, A, B, C, D") for n in range(num_eval): truck_p = model[truck_pos[n]].as_long() truck_storage = model[truck_store[n]].as_long() truck_cap = capacities[0] a = model[village_store[n][0]].as_long() a_cap = capacities[1] b = model[village_store[n][1]].as_long() b_cap = capacities[2] c = model[village_store[n][2]].as_long() c_cap = capacities[3] d = model[village_store[n][3]].as_long() d_cap = capacities[4] assert(a <= a_cap) assert(b <= b_cap) assert(c <= c_cap) assert(d <= d_cap) assert(truck_storage <= truck_cap) if n > 0: cost = model.eval(route_costs[truck_pos[n-1]][truck_pos[n]]).as_long() prev_truck_storage = model[truck_store[n - 1]].as_long() assert(cost != -1) prev_a = model[village_store[n - 1][0]].as_long() prev_b = model[village_store[n - 1][1]].as_long() prev_c = model[village_store[n - 1][2]].as_long() prev_d = model[village_store[n - 1][3]].as_long() assert(cost <= prev_a) assert(cost <= prev_b) assert(cost <= prev_c) assert(cost <= prev_d) unloaded = [ a - (prev_a - cost), b - (prev_b - cost), c - (prev_c - cost), d - (prev_d - cost) ] unloaded = [x for x in unloaded if x != 0] assert(len(unloaded) <= 1) if truck_p == 0: unloaded = prev_truck_storage - capacities[0] elif len(unloaded) == 1: unloaded = unloaded[0] else: unloaded = 0 assert(truck_storage - prev_truck_storage == -unloaded) print(f"{cycle_arrows[n]}{n:5}, {truck_p}, {truck_storage:03}/{truck_cap:03}, {a:03}/{a_cap:03}, {b:03}/{b_cap:03}, {c:03}/{c_cap:03}, {d:03}/{d_cap:03}") s = Solver() # load routes into Z3 Array for y in range(num_stores + num_villages): for x in range(num_stores + num_villages): s.add(route_costs[y][x] == route_costs_list[y][x]) # set initial conditions s.add(truck_pos[0] == 0) s.add(truck_store[0] == capacities[0]) for v in range(num_villages): s.add(village_store[0][v] == 80) # Run bounded model for n in range(num_eval - 1): curr_loc = truck_pos[n] next_loc = truck_pos[n + 1] curr_truck_store = truck_store[n] next_truck_store = truck_store[n + 1] cost = route_costs[curr_loc][next_loc] # ensure we take a route that exists s.add(And(next_loc >= 0, next_loc < num_stores + num_villages, cost >= 0)) unload = [] # unload a negative amount to fill up capacity for i in range(num_stores): unload.append(If(next_loc == i, curr_truck_store - capacities[i], 0)) for j in range(num_villages): store_curr = village_store[n][j] store_next = village_store[n + 1][j] # Ensure we don't go through 0 when traveling # and ensure we don't store more then possible s.add(store_curr - cost >= 0) # Ensure we only unload at the current location unloaded = store_next - (store_curr - cost) s.add(If( next_loc == (num_stores + j), And(unloaded >= 0, unloaded <= curr_truck_store), unloaded == 0 )) unload.append(unloaded) # set next store s.add(store_next <= capacities[num_stores + j]) s.add(store_next == (store_curr - cost) + unloaded) # Remove capacity from truck s.add(next_truck_store == curr_truck_store - sum(unload)) # exercise 6b # check if a storage state is encountered that is strictly # better then a previous state. # if that happens we have proven we can just always keep # using that path and we have solved world hunger if assignment_b: ors = [] for n1 in range(num_eval): for n2 in range(n1 + 1, num_eval): ands = [] ands.append(truck_pos[n1] == truck_pos[n2]) ands.append(truck_store[n2] >= truck_store[n1]) for j in range(num_villages): ands.append(village_store[n2][j] >= village_store[n1][j]) world_hunger_save[n1][n2 - n1 - 1] = And(ands) ors.append(world_hunger_save[n1][n2 - n1 - 1]) s.add(Or(ors)) res = s.check() if res == unsat: print(f"unsat") else: print(f"SAT") print_solution(s.model())	[ 1, 529, 276, 1112, 420, 29958, 798, 273, 29954, 29900, 29955, 29955, 29914, 17405, 630, 29918, 23147, 292, 13, 3166, 503, 29941, 1053, 334, 13, 3166, 3509, 1053, 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src/devel/___blocks/___block_base.py	jakub-vesely/hugo	0	163488	# Copyright (c) 2022 <NAME> # This software is published under MIT license. Full text of the license is available at https://opensource.org/licenses/MIT from ___basal.___logging import Logging from ___blocks.___block_types import BlockTypes import machine import time from micropython import const _power_save_command = const(0xf6) _get_module_version_command = const(0xf7) _change_i2c_address_command = const(0xfe) _i2c_block_type_id_base = const(0xFA) class PowerSaveLevel: NoPowerSave = 0 # powersave is off LightPowerSave = 1 # subsystems that are not needed are turned off DeepPowerSave = 2 # all subsystems are turned off class BlockBase: i2c = machine.I2C(0, scl=machine.Pin(22), sda=machine.Pin(21), freq=100000) def __init__(self, block_type: int, address: int): self.type_id = block_type.id self.address = address if address else block_type.id #default block i2c address is equal to its block type self.logging = Logging(block_type.name) self.block_version = self._get_block_version() self.block_type_valid = False self.power_save_level = PowerSaveLevel.NoPowerSave self._tiny_write_base_id(_power_save_command, self.power_save_level.to_bytes(1, 'big'), True) #wake up block functionality if not self.block_version: self.logging.warning("module with address 0x%x is not available", self.address) elif self.block_version[0] != self.type_id: self.logging.error("unexpected block type. expected: %d, returned: %d", self.type_id, self.block_version[0]) else: self.block_type_valid = True def _raw_tiny_write(self, type_id: int, command: int, data=None, silent=False): try: payload = type_id.to_bytes(1, 'big') + command.to_bytes(1, 'big') if data: payload += data #self.logging.info(("write", payload)) self.i2c.writeto(self.address, payload) except OSError: if not silent: self.logging.error("tiny-block with address 0x%02X is unavailable for writing", self.address) def _check_type(self, type_id): return type_id in (_i2c_block_type_id_base, self.type_id) and (_i2c_block_type_id_base or self.block_type_valid) def __tiny_write_common(self, type_id: int, command: int, data=None, silent=False): """ writes data to tiny_block via I2C @param type_id: block type id @param command: one byte command @param data: specify input data for entered command """ if self._check_type(type_id): self._raw_tiny_write(type_id, command, data, silent) else: self.logging.error("invalid block type - writing interupted") def _tiny_write_base_id(self, command: int, data=None, silent=False): self.__tiny_write_common(_i2c_block_type_id_base, command, data, silent) def _tiny_write(self, command: int, data=None, silent=False): if not self.is_available(): return self.__tiny_write_common(self.type_id, command, data, silent) def __tiny_read_common(self, type_id: int, command: int, in_data: bytes=None, expected_length: int=0, silent=False): """ reads data form tiny_block via I2C @param type_id: block type id @param command: one byte command @param in_data: specify input data for entered command @param expected_length: if defined will be read entered number of bytes. If None is expected length as a first byte @return provided bytes. If size is first byte is not included to output data """ if self._check_type(type_id): self._raw_tiny_write(type_id, command, in_data, silent) try: data = self.i2c.readfrom(self.address, expected_length, True) return data except OSError: if not silent: self.logging.error("tiny-block with address 0x%02X is unavailable for reading", self.address) return None else: self.logging.error("invalid block type - reading interupted") return None def _tiny_read_base_id(self, command: int, in_data: bytes=None, expected_length: int=0, silent=False): return self.__tiny_read_common(_i2c_block_type_id_base, command, in_data, expected_length, silent) def _tiny_read(self, command: int, in_data: bytes=None, expected_length: int=0): if not self.is_available(): return None return self.__tiny_read_common(self.type_id, command, in_data, expected_length) def change_block_address(self, new_address): self._tiny_write_base_id(_change_i2c_address_command, new_address.to_bytes(1, 'big')) self.address = new_address time.sleep(0.1) #wait to the change is performed and stopped def _get_block_version(self): """ returns block_type, pcb version, adjustment_version """ data = self._tiny_read_base_id(_get_module_version_command, None, 3, silent=True) if not data: return None return (data[0], data[1], data[2]) def is_available(self): return self.block_type_valid #available and valid block version def power_save(self, level:PowerSaveLevel) -> None: self.power_save_level = level self._tiny_write_base_id(_power_save_command, level.to_bytes(1, 'big'))	[ 1, 396, 29871, 14187, 1266, 313, 29883, 29897, 29871, 29906, 29900, 29906, 29906, 529, 5813, 29958, 13, 29937, 29871, 910, 7047, 338, 6369, 1090, 341, 1806, 19405, 29889, 14846, 1426, 310, 278, 19405, 338, 3625, 472, 2045, 597, 22156, 1167, 29889, 990, 29914, 506, 11259, 29914, 26349, 13, 13, 3166, 903, 1649, 6500, 284, 17255, 29918, 21027, 1053, 4522, 3460, 13, 3166, 903, 1649, 1271, 29879, 17255, 29918, 1271, 29918, 8768, 1053, 15658, 10562, 13, 5215, 4933, 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python/src/year2020/day22.py	Farbfetzen/Advent_of_Code	4	192002	<reponame>Farbfetzen/Advent_of_Code # https://adventofcode.com/2020/day/22 from collections import deque from copy import deepcopy from itertools import islice from src.util.types import Data, Solution def prepare_data(data: str) -> list[deque[int]]: return [deque([int(card) for card in deck.splitlines()[1:]]) for deck in data.split("\n\n")] def calculate_score(cards): return sum(i * v for i, v in enumerate(reversed(cards), start=1)) def part_1(decks): decks = deepcopy(decks) while True: p0 = decks[0].popleft() p1 = decks[1].popleft() if p0 > p1: decks[0].extend((p0, p1)) if len(decks[1]) == 0: return calculate_score(decks[0]) else: decks[1].extend((p1, p0)) if len(decks[0]) == 0: return calculate_score(decks[1]) def part_2(decks, return_index=False): cache = set() winner_game = None while winner_game is None: d = (tuple(decks[0]), tuple(decks[1])) if d in cache: winner_game = 0 # player 1 (= index 0) wins break cache.add(d) p0 = decks[0].popleft() p1 = decks[1].popleft() if p0 <= len(decks[0]) and p1 <= len(decks[1]): new_deck_p0 = deque(islice(decks[0], 0, p0)) new_deck_p1 = deque(islice(decks[1], 0, p1)) winner_round = part_2([new_deck_p0, new_deck_p1], True) elif p0 > p1: winner_round = 0 else: winner_round = 1 if winner_round == 0: decks[0].extend((p0, p1)) if len(decks[1]) == 0: winner_game = 0 else: decks[1].extend((p1, p0)) if len(decks[0]) == 0: winner_game = 1 if return_index: return winner_game else: return calculate_score(decks[winner_game]) def solve(data: Data) -> Solution: solution = Solution() sample_data = prepare_data(data.samples[0]) solution.samples_part_1.append(part_1(sample_data)) solution.samples_part_2.append(part_2(sample_data)) challenge_data = prepare_data(data.input) solution.part_1 = part_1(challenge_data) solution.part_2 = part_2(challenge_data) return solution	[ 1, 529, 276, 1112, 420, 29958, 29943, 279, 1635, 300, 2256, 29914, 3253, 794, 29918, 974, 29918, 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superset/views/extract_db_info.py	charvigupta/apachesuperset_ed	0	174282	<gh_stars>0 import sqlite3 ## path to .db connection = sqlite3.connect("/home/charvi/.superset/superset.db") def sql_table_fetch(con): datasource_dict = {} database_dict = {} cursorObj = con.cursor() cursorObj.execute('SELECT * FROM tables') rows = cursorObj.fetchall() for row in rows: db_val = str(list(row)[6]) param = list(row)[-5:-4][0].split(".") db_key = param[0][1:-1] ds_key = param[-1].split("](id:")[0][1:] ds_value = param[-1].split("](id:")[1][:-1] database_dict[db_key] = db_val datasource_dict[ds_key] = ds_value return datasource_dict, database_dict datasource_dict, database_dict = sql_table_fetch(connection)	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 21120, 29941, 13, 13, 13, 2277, 2224, 304, 869, 2585, 13, 9965, 353, 21120, 29941, 29889, 6915, 11974, 5184, 29914, 3090, 1403, 6294, 12587, 24197, 29914, 12587, 24197, 29889, 2585, 1159, 13, 13, 1753, 4576, 29918, 2371, 29918, 9155, 29898, 535, 1125, 13, 12, 13, 12, 14538, 1167, 29918, 8977, 353, 6571, 13, 12, 9803, 29918, 8977, 353, 6571, 13, 13, 12, 18127, 9930, 353, 378, 29889, 18127, 580, 13, 12, 18127, 9930, 29889, 7978, 877, 6404, 334, 3895, 6131, 1495, 13, 12, 5727, 353, 10677, 9930, 29889, 9155, 497, 580, 13, 12, 1454, 1948, 297, 4206, 29901, 13, 13, 12, 12, 2585, 29918, 791, 353, 851, 29898, 1761, 29898, 798, 9601, 29953, 2314, 13, 12, 12, 3207, 353, 1051, 29898, 798, 9601, 29899, 29945, 13018, 29946, 3816, 29900, 1822, 5451, 17350, 1159, 13, 12, 12, 2585, 29918, 1989, 353, 1828, 29961, 29900, 3816, 29896, 13018, 29896, 29962, 13, 12, 12, 6289, 29918, 1989, 353, 1828, 14352, 29896, 1822, 5451, 703, 850, 333, 29901, 1159, 29961, 29900, 3816, 29896, 17531, 13, 12, 12, 6289, 29918, 1767, 353, 1828, 14352, 29896, 1822, 5451, 703, 850, 333, 29901, 1159, 29961, 29896, 3816, 13018, 29896, 29962, 13, 12, 12, 13, 12, 12, 9803, 29918, 8977, 29961, 2585, 29918, 1989, 29962, 353, 4833, 29918, 791, 13, 12, 12, 14538, 1167, 29918, 8977, 29961, 6289, 29918, 1989, 29962, 353, 18031, 29918, 1767, 13, 12, 13, 12, 2457, 6155, 1167, 29918, 8977, 29892, 2566, 29918, 8977, 13, 13, 14538, 1167, 29918, 8977, 29892, 2566, 29918, 8977, 353, 4576, 29918, 2371, 29918, 9155, 29898, 9965, 29897, 13, 13, 2 ]
cinder/tests/unit/scheduler/test_capacity_weigher.py	helenwalsh/cinder	571	64668	# Copyright 2011-2012 OpenStack Foundation # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """Tests For Capacity Weigher.""" from datetime import datetime from unittest import mock import ddt from cinder.common import constants from cinder import context from cinder.scheduler import weights from cinder.tests.unit.scheduler import fakes from cinder.tests.unit import test from cinder.volume import volume_utils @ddt.ddt class CapacityWeigherTestCase(test.TestCase): def setUp(self): super(CapacityWeigherTestCase, self).setUp() self.host_manager = fakes.FakeHostManager() self.weight_handler = weights.OrderedHostWeightHandler( 'cinder.scheduler.weights') def _get_weighed_hosts(self, hosts, weight_properties=None): if weight_properties is None: weight_properties = {'size': 1} return self.weight_handler.get_weighed_objects( [weights.capacity.CapacityWeigher], hosts, weight_properties) @mock.patch('cinder.db.sqlalchemy.api.service_get_all') def _get_all_backends(self, _mock_service_get_all, disabled=False): ctxt = context.get_admin_context() fakes.mock_host_manager_db_calls(_mock_service_get_all, disabled=disabled) backend_states = self.host_manager.get_all_backend_states(ctxt) _mock_service_get_all.assert_called_once_with( ctxt, None, # backend_match_level topic=constants.VOLUME_TOPIC, frozen=False, disabled=disabled) return backend_states # If thin and thin_provisioning_support are True, # use the following formula: # free = (total * host_state.max_over_subscription_ratio # - host_state.provisioned_capacity_gb # - math.floor(total * reserved)) # Otherwise, use the following formula: # free = free_space - math.floor(total * reserved) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host1'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host2'}, {'volume_type': {}, 'winner': 'host2'}, {'volume_type': None, 'winner': 'host2'}, ) @ddt.unpack def test_default_of_spreading_first(self, volume_type, winner): backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=1024-math.floor(10240.1)=922 # Norm=0.837837837838 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=20481.5-1748-math.floor(20480.1)=1120 # Norm=1.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=256-5120=256 # Norm=0.292383292383 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=20481.0-2047-math.floor(20480.05)=-101 # Norm=0.0 # host5: free_capacity_gb=unknown free=-1 # Norm=0.0819000819001 # so, host2 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties)[0] self.assertEqual(1.0, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host4'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host4'}, {'volume_type': {}, 'winner': 'host4'}, {'volume_type': None, 'winner': 'host4'}, ) @ddt.unpack def test_capacity_weight_multiplier1(self, volume_type, winner): self.flags(capacity_weight_multiplier=-1.0) backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=-(1024-math.floor(10240.1))=-922 # Norm=-0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=-(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=-(256-5120)=-256 # Norm=--0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=-(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # host5: free_capacity_gb=unknown free=-float('inf') # Norm=-1.0 # so, host4 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties) weighed_host = weighed_host[0] self.assertEqual(0.0, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host1'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host2'}, {'volume_type': {}, 'winner': 'host2'}, {'volume_type': None, 'winner': 'host2'}, ) @ddt.unpack def test_capacity_weight_multiplier2(self, volume_type, winner): self.flags(capacity_weight_multiplier=2.0) backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))2=1844 # Norm=1.67567567568 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))2=2240 # Norm=2.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)2=512 # Norm=0.584766584767 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))2=-202 # Norm=0.0 # host5: free_capacity_gb=unknown free=-2 # Norm=0.1638001638 # so, host2 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties)[0] self.assertEqual(1.0 * 2, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) def test_capacity_weight_no_unknown_or_infinite(self): self.flags(capacity_weight_multiplier=-1.0) del self.host_manager.service_states['host5'] backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))=-922 # Norm=-0.837837837838 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-1.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)=-256 # Norm=-0.292383292383 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host2 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host2', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_free_unknown(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 3000, 'free_capacity_gb': 'unknown', 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # host5: free_capacity_gb=unknown free=3000 # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_cap_unknown(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 'unknown', 'free_capacity_gb': 3000, 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # host5: free_capacity_gb=3000 free=unknown # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_free_infinite(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 3000, 'free_capacity_gb': 'infinite', 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # host5: free_capacity_gb=infinite free=3000 # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_cap_infinite(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 'infinite', 'free_capacity_gb': 3000, 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(10240.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(20481.5-1748-math.floor(20480.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-5120)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(20481.0-2047-math.floor(20480.05))=101 # Norm=0.0 # host5: free_capacity_gb=3000 free=infinite # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host))	[ 1, 396, 14187, 1266, 29871, 29906, 29900, 29896, 29896, 29899, 29906, 29900, 29896, 29906, 4673, 7264, 10606, 13, 29937, 2178, 26863, 2538, 9841, 29889, 13, 29937, 13, 29937, 1678, 10413, 21144, 1090, 278, 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method_of_moments/__init__.py	AlbertFarkhutdinov/method_of_moments	0	59454	<reponame>AlbertFarkhutdinov/method_of_moments """ This package allows you to work with probability distributions with a specified mean values and variances. """ from .continuous import Beta, GenNBD, Norm from .discrete import Bernoulli, GPD, HGD, NBD, Poisson, QGD, ZiNBD	[ 1, 529, 276, 1112, 420, 29958, 2499, 2151, 29943, 935, 29882, 329, 24581, 586, 29914, 5696, 29918, 974, 29918, 29885, 290, 1237, 13, 15945, 29908, 13, 4013, 3577, 6511, 366, 304, 664, 411, 6976, 18822, 13, 2541, 263, 6790, 2099, 1819, 322, 722, 713, 778, 29889, 13, 13, 15945, 29908, 13, 13, 13, 3166, 869, 20621, 681, 1053, 350, 1187, 29892, 5739, 23189, 29928, 29892, 5655, 13, 3166, 869, 2218, 9084, 1053, 6209, 5059, 492, 29892, 402, 25014, 29892, 379, 29954, 29928, 29892, 405, 29121, 29892, 3929, 17387, 29892, 660, 29954, 29928, 29892, 796, 29875, 23189, 29928, 13, 2 ]
Lista_Simplesmente_Encadeada/Lista_Encadeada/OO/controlador_contas.py	BeatrizSilva-Dev/Algoritmos-e-Estruturas-de-Dados	0	125941	from OO import bd_contas, menu def iniciar(): print('ACESSO CAIXA ELETRONICO') agencia = input('DIGITE AGENCIA') num_conta = input('DIGITE A CONTA') conta = bd_contas.buscar_contas(agencia, num_conta) if conta is not None: while True: menu.caixa_eletronico() op = input('Digite a opção') if op == '0': print('SAINDO CAIXA ELETRÔNICO') return elif op == '1': valor = float(input('DIGITE O VALOR DE SAQUE')) if (conta.sacar(valor)): print('SUCESSO!!!') else: print('SALDO INDISPONÍVEL') elif op == '2': valor = float(input('DIGITE O VALOR DE SAQUE')) if (conta.depositar(valor)): print('SUCESSO!!!') else: print('DEPOSITO INVÁLIDO') elif op == '3': agencia = input('DIGITE AGENCIA - DESTINATÁRIO') num_conta = input('DIGITE A CONTA - DESTINATÁRIO') contas_desti = bd_contas.buscar_contas(agencia, num_conta) if contas_desti is not None: valor = float(input('DIGITE O VALOR DE TRANSFERENCIA')) if conta.transferir(valor, contas_desti): print('TRANSFERENCIA COM SUCESSO') else: print('VALOR INDISPONÍVEL""') else: print('CONTA DESTINATÁRIO NÃO EXISTE') elif op == '4': print(conta.get_saldo()) else: print('Opção Inválida') else: print('CONTA NÃO EXISTE')	[ 1, 29871, 13, 3166, 438, 29949, 1053, 289, 29881, 29918, 1285, 294, 29892, 6143, 13, 13, 13, 1753, 21855, 279, 7295, 13, 1678, 1596, 877, 11538, 1799, 29949, 12766, 6415, 29909, 382, 1307, 5659, 1164, 2965, 29949, 1495, 13, 1678, 946, 5760, 353, 1881, 877, 4571, 29954, 9094, 16369, 1430, 8426, 29909, 1495, 13, 1678, 954, 29918, 535, 941, 353, 1881, 877, 4571, 29954, 9094, 319, 8707, 6040, 1495, 13, 1678, 640, 29874, 353, 289, 29881, 29918, 1285, 294, 29889, 8262, 4287, 29918, 1285, 294, 29898, 5370, 1512, 29892, 954, 29918, 535, 941, 29897, 13, 1678, 565, 640, 29874, 338, 451, 6213, 29901, 13, 4706, 1550, 5852, 29901, 13, 9651, 6143, 29889, 1113, 19892, 29918, 6146, 509, 265, 1417, 580, 13, 9651, 1015, 353, 1881, 877, 14991, 568, 263, 1015, 2340, 1495, 13, 9651, 565, 1015, 1275, 525, 29900, 2396, 13, 18884, 1596, 877, 8132, 1177, 3970, 12766, 6415, 29909, 382, 1307, 5659, 30535, 29940, 2965, 29949, 1495, 13, 18884, 736, 13, 9651, 25342, 1015, 1275, 525, 29896, 2396, 13, 18884, 16497, 353, 5785, 29898, 2080, 877, 4571, 29954, 9094, 438, 12599, 1955, 5012, 16698, 11144, 8785, 13, 18884, 565, 313, 535, 941, 29889, 29879, 562, 279, 29898, 791, 272, 22164, 13, 462, 1678, 1596, 877, 14605, 23524, 29949, 21004, 1495, 13, 18884, 1683, 29901, 13, 462, 1678, 1596, 877, 29903, 1964, 3970, 2672, 23711, 29925, 1164, 30175, 29963, 6670, 1495, 13, 9651, 25342, 1015, 1275, 525, 29906, 2396, 13, 18884, 16497, 353, 5785, 29898, 2080, 877, 4571, 29954, 9094, 438, 12599, 1955, 5012, 16698, 11144, 8785, 13, 18884, 565, 313, 535, 941, 29889, 311, 1066, 3673, 29898, 791, 272, 22164, 13, 462, 1678, 1596, 877, 14605, 23524, 29949, 21004, 1495, 13, 18884, 1683, 29901, 13, 462, 1678, 1596, 877, 2287, 24815, 1806, 29949, 2672, 29963, 30102, 29931, 1367, 29949, 1495, 13, 9651, 25342, 1015, 1275, 525, 29941, 2396, 13, 18884, 946, 5760, 353, 1881, 877, 4571, 29954, 9094, 16369, 1430, 8426, 29909, 448, 5012, 1254, 1177, 1299, 30102, 3960, 29949, 1495, 13, 18884, 954, 29918, 535, 941, 353, 1881, 877, 4571, 29954, 9094, 319, 8707, 6040, 448, 5012, 1254, 1177, 1299, 30102, 3960, 29949, 1495, 13, 18884, 640, 294, 29918, 7854, 29875, 353, 289, 29881, 29918, 1285, 294, 29889, 8262, 4287, 29918, 1285, 294, 29898, 5370, 1512, 29892, 954, 29918, 535, 941, 29897, 13, 18884, 565, 640, 294, 29918, 7854, 29875, 338, 451, 6213, 29901, 13, 462, 1678, 16497, 353, 5785, 29898, 2080, 877, 4571, 29954, 9094, 438, 12599, 1955, 5012, 10014, 2190, 20322, 1001, 1430, 8426, 29909, 8785, 13, 462, 1678, 565, 640, 29874, 29889, 3286, 571, 381, 29898, 791, 272, 29892, 640, 294, 29918, 7854, 29875, 1125, 13, 462, 4706, 1596, 877, 26813, 20322, 1001, 1430, 8426, 29909, 23353, 20134, 23524, 29949, 1495, 13, 462, 1678, 1683, 29901, 13, 462, 4706, 1596, 877, 8932, 1955, 2672, 23711, 29925, 1164, 30175, 29963, 6670, 15945, 1495, 13, 18884, 1683, 29901, 13, 462, 1678, 1596, 877, 6007, 6040, 5012, 1254, 1177, 1299, 30102, 3960, 29949, 405, 30179, 29949, 8528, 9047, 29923, 1495, 13, 13, 13, 13, 9651, 25342, 1015, 1275, 525, 29946, 2396, 13, 18884, 1596, 29898, 535, 941, 29889, 657, 29918, 19585, 1867, 3101, 13, 9651, 1683, 29901, 13, 18884, 1596, 877, 11746, 2340, 15518, 2464, 1458, 1495, 13, 1678, 1683, 29901, 13, 4706, 1596, 877, 6007, 6040, 405, 30179, 29949, 8528, 9047, 29923, 1495, 13, 2 ]
analysis/FlatfieldCalibration.py	Borlaff/EuclidVisibleInstrument	5	155900	""" Flat Field Calibration ====================== This simple script can be used to study the number of flat fields required to meet the VIS calibration requirements. The following requirements related to the flat field calibration has been taken from GDPRD. R-GDP-CAL-054: The contribution of the residuals of VIS flat-field correction to the error on the determination of each ellipticity component of the local PSF shall not exceed 3x10-5 (one sigma). R-GDP-CAL-064: The contribution of the residuals of VIS flat-field correction to the relative error on the determination of the local PSF R2 shall not exceed 1x10-4 (one sigma). .. Note:: The amount of cosmic rays in the simulated input images might be too low, because the exposure was set to 10 seconds and cosmic rays were calculated based on this. However, in reality the readout takes about 80 seconds. Thus, the last row is effected by cosmic a lot more than by assuming a single 10 second exposure. :requires: PyFITS :requires: NumPy :requires: SciPy :requires: matplotlib :requires: VISsim-Python :version: 0.97 :author: <NAME> :contact: <EMAIL> """ import matplotlib matplotlib.rc('text', usetex=True) matplotlib.rcParams['font.size'] = 17 matplotlib.rc('xtick', labelsize=14) matplotlib.rc('axes', linewidth=1.1) matplotlib.rcParams['legend.fontsize'] = 11 matplotlib.rcParams['legend.handlelength'] = 3 matplotlib.rcParams['xtick.major.size'] = 5 matplotlib.rcParams['ytick.major.size'] = 5 import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm import pyfits as pf import numpy as np import datetime, cPickle, glob, os, sys from scipy.ndimage.interpolation import zoom from scipy import interpolate from analysis import shape from support import logger as lg from support import surfaceFitting as sf from support import files as fileIO def generateResidualFlatField(files='Q0flatfield.fits', combine=77, lampfile='data/VIScalibrationUnitflux.fits', reference='data/VISFlatField1percent.fits', gain=3.5, plots=False, debug=False): """ Generate a median combined flat field residual from given input files. Randomly draws a given number (kw combine) of files from the file list identified using the files kw. Median combine all files before the lamp profile given by lampfile kw is being divided out. This will produce a derived flat field. This flat can be compared against the reference that was used to produce the initial data to derive a residual flat that describes the error in the flat field that was derived. :param files: wildcard flagged name identifier for the FITS files to be used for generating a flat :type files: str :param combine: number of files to median combine :type combine: int :param lampfile: name of the calibration unit flux profile FITS file :type lampfile: str :param reference: name of the reference pixel-to-pixel flat field FITS file :type reference: str :param gain: gain factor [e/ADU] :type gain: float :param plots: whether or not to generate plots :type plots: boolean :param debug: whether or not to produce output FITS files :type debug: boolean .. Warning:: Remember to use an appropriate lamp and reference files so that the error in the derived flat field can be correctly calculated. :return: residual flat field (difference between the generated flat and the reference) :rtype: ndarray """ #find all FITS files files = glob.glob(files) #choose randomly the files that should be combined if combine < len(files): ids = np.random.random_integers(0, len(files)-1, combine) files = np.asarray(files)[ids] #load data and scale to electrons data = fileIO.readFITSDataExcludeScanRegions(files) data = gain #check that the sizes match and median combine if len(set(x.shape for x in data)) > 1: sys.exit('ERROR -- files are not the same shape, cannot median combine!') else: medianCombined = np.median(data, axis=0) #fit surface to the median and normalize it out #m = sf.polyfit2d(xx.ravel(), yy.ravel(), median.ravel(), order=order) # Evaluate it on a rectangular grid #fitted = sf.polyval2d(xx, yy, m) #load the lamp profile that went in and divide the combined image with the profile lamp = pf.getdata(lampfile) pixvar = medianCombined.astype(np.float64).copy() / lamp #load the true reference p-flat and calculate the error in the derived flat field (i.e. residual) real = pf.getdata(reference).astype(np.float64) res = np.abs(real - pixvar) / (realpixvar) + 1. #old: maybe incorrect? #res = np.abs(pixvar - real) + 1. if debug: print np.mean(res), np.min(res), np.max(res), np.std(res) if not os.path.exists('debug'): os.makedirs('debug') fileIO.writeFITS(medianCombined, 'debug/medianFlat.fits') fileIO.writeFITS(pixvar, 'debug/derivedFlat.fits') fileIO.writeFITS(res, 'debug/residualFlat.fits') if plots: if not os.path.exists('plots'): os.makedirs('plots') #generate a mesh grid fo plotting ysize, xsize = medianCombined.shape xx, yy = np.meshgrid(np.linspace(0, xsize, xsize), np.linspace(0, ysize, ysize)) fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, medianCombined, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlabel('Counts [electrons]') ax.set_zlim(8.9e4, 1.05e5) plt.savefig('plots/MedianFlat.png') plt.close() im = plt.imshow(medianCombined, origin='lower', vmin=8.9e4, vmax=1.05e5) c1 = plt.colorbar(im) c1.set_label('Counts [electrons]') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/Mediand2D.png') plt.close() fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, pixvar, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlim(0.95, 1.05) ax.set_zlabel('Counts [electrons]') plt.savefig('plots/PixelFlat.png') plt.close() im = plt.imshow(pixvar, origin='lower', vmin=0.95, vmax=1.05) c1 = plt.colorbar(im) c1.set_label('Counts [electrons]') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/PixelFlat2D.png') plt.close() fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, res, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlim(0.95, 1.05) ax.set_zlabel('Residual Flat Field') plt.savefig('plots/ResidualFlatField.png') plt.close() im = plt.imshow(res, origin='lower', vmin=0.95, vmax=1.05) c1 = plt.colorbar(im) c1.set_label('Residual Flat Field') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/ResidualFlatField2D.png') plt.close() return res def testFlatCalibration(log, flats, surfaces=10, file='data/psf1x.fits', psfs=5000, sigma=0.75, iterations=7, weighting=True, plot=False, debug=False): """ Derive the PSF ellipticities for a given number of random surfaces with random PSF positions and a given number of flat fields median combined. This function is to derive the the actual values so that the knowledge (variance) can be studied. """ #read in PSF and rescale to avoid rounding or truncation errors data = pf.getdata(file) data /= np.max(data) data = 300. #SNR about 10 for star... #derive reference values settings = dict(sigma=sigma, iterations=iterations, weighted=weighting) sh = shape.shapeMeasurement(data.copy(), log, settings) reference = sh.measureRefinedEllipticity() #random positions for the PSFs, these positions are the lower corners #assume that this is done on quadrant level thus the xmax and ymax are 2065 and 2047, respectively xpositions = np.random.random_integers(0, 2047 - data.shape[1], psfs) ypositions = np.random.random_integers(0, 2065 - data.shape[0], psfs) out = {} #number of biases to median combine for a in flats: print 'Number of Flats to combine: %i / %i' % (a, flats[-1]) #data storage de1 = [] de2 = [] de = [] R2 = [] dR2 = [] e1 = [] e2 = [] e = [] for b in xrange(surfaces): print 'Random Realisations: %i / %i' % (b+1, surfaces) residual = generateResidualFlatField(combine=a, plots=plot, debug=debug) print 'Average residual = %e' % (np.mean(residual) - 1.) # generate 2D plot if b == 0 and plot: im = plt.imshow(residual, extent=(0, 2066, 2048, 0)) plt.scatter(xpositions + (data.shape[1]/2), ypositions + (data.shape[0]/2), color='white') c1 = plt.colorbar(im) c1.set_label('Residual Flat Field') plt.xlim(0, 2066) plt.ylim(0, 2048) plt.xlabel('Y [pixels]') plt.ylabel('X [pixels]') plt.savefig('residualFlat2D%i.png' % a) plt.close() #loop over the PSFs for xpos, ypos in zip(xpositions, ypositions): tmp = data.copy() #get the underlying residual surface and multiple with the PSF small = residual[ypos:ypos+data.shape[0], xpos:xpos+data.shape[1]].copy() #small += 1. small = tmp #small = tmp # depends on the residual geenration #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(small.copy(), log, settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) de1.append(results['e1'] - reference['e1']) de2.append(results['e2'] - reference['e2']) de.append(results['ellipticity'] - reference['ellipticity']) dR2.append(results['R2'] - reference['R2']) out[a+1] = [e1, e2, e, R2, de1, de2, de, dR2] return out, reference def plotNumberOfFrames(results, reqe=3e-5, reqr2=1e-4, shift=0.1, outdir='results', timeStamp=False): """ Creates a simple plot to combine and show the results. :param res: results to be plotted [results dictionary, reference values] :type res: list :param reqe: the requirement for ellipticity [default=3e-5] :type reqe: float :param reqr2: the requirement for size R2 [default=1e-4] :type reqr2: float :param shift: the amount to shift the e2 results on the abscissa (for clarity) :type shift: float :param outdir: output directory to which the plots will be saved to :type outdir: str :param timeStamp: whether or not to include a time stamp to the output image :type timeStamp: bool :return: None """ if not os.path.exists(outdir): os.makedirs(outdir) #rename ref = results[1] res = results[0] print '\nSigma results:' txt = '%s' % datetime.datetime.isoformat(datetime.datetime.now()) fig = plt.figure() plt.title(r'VIS Flat Field Calibration: $\sigma(e)$') ax = fig.add_subplot(111) maxx = 0 frames = [] values = [] #loop over the number of frames combined for key in res: e1 = np.asarray(res[key][0]) e2 = np.asarray(res[key][1]) e = np.asarray(res[key][2]) std1 = np.std(e1) std2 = np.std(e2) std = np.std(e) frames.append(key) values.append(std) ax.scatter(key-shift, std, c='m', marker='') ax.scatter(key, std1, c='b', marker='o') ax.scatter(key, std2, c='y', marker='s') if key > maxx: maxx = key print key, std, std1, std2 #label ax.scatter(key-shift, std, c='m', marker='', label=r'$\sigma (e)$') ax.scatter(key, std1, c='b', marker='o', label=r'$\sigma (e_{1})$') ax.scatter(key, std2, c='y', marker='s', label=r'$\sigma (e_{2})$') #sort and interpolate values = np.asarray(values) frames = np.asarray(frames) srt = np.argsort(frames) x = np.arange(frames.min(), frames.max()+1) f = interpolate.interp1d(frames[srt], values[srt], kind='cubic') vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=20) try: msk = vals < reqe minn = np.min(x[msk]) plt.text(np.mean(frames), 8e-6, r'Flats Required $\raise-.5ex\hbox{$\buildrel>\over\sim$}$ %i' % np.ceil(minn), ha='center', va='center', fontsize=11) except: pass ax.fill_between(np.arange(maxx+10), np.ones(maxx+10)reqe, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=reqe, c='g', ls='--', label='Requirement') plt.text(1, 0.9reqe, '%.1e' % reqe, ha='left', va='top', fontsize=11) ax.set_yscale('log') ax.set_ylim(5e-6, 1e-4) ax.set_xlim(0, maxx+1) ax.set_xlabel('Number of Flat Fields Median Combined') ax.set_ylabel(r'$\sigma (e_{i})\ , \ \ \ i \in [1,2]$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=2.0, ncol=2) plt.savefig(outdir+'/FlatCalibrationsigmaE.pdf') plt.close() #same for R2s fig = plt.figure() plt.title(r'VIS Flat Field Calibration: $\frac{\sigma (R^{2})}{R_{ref}^{2}}$') ax = fig.add_subplot(111) ax.axhline(y=0, c='k', ls=':') maxx = 0 frames = [] values = [] #loop over the number of frames combined for key in res: dR2 = np.asarray(res[key][3]) #std = np.std(dR2) / ref['R2'] std = np.std(dR2) / np.mean(dR2) frames.append(key) values.append(std) print key, std ax.scatter(key, std, c='b', marker='s', s=35, zorder=10) if key > maxx: maxx = key #for the legend ax.scatter(key, std, c='b', marker='s', label=r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') #sort and interpolate values = np.asarray(values) frames = np.asarray(frames) srt = np.argsort(frames) x = np.arange(frames.min(), frames.max()) f = interpolate.interp1d(frames[srt], values[srt], kind='cubic') vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) try: msk = vals < reqr2 minn = np.min(x[msk]) plt.text(np.mean(frames), 2e-5, r'Flats Required $\raise-.5ex\hbox{$\buildrel>\over\sim$}$ %i' % np.ceil(minn), fontsize=11, ha='center', va='center') except: pass #show the requirement ax.fill_between(np.arange(maxx+10), np.ones(maxx+10)reqr2, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=reqr2, c='g', ls='--', label='Requirement') plt.text(1, 0.9reqr2, '%.1e' % reqr2, ha='left', va='top', fontsize=11) ax.set_yscale('log') ax.set_ylim(5e-6, 1e-3) ax.set_xlim(0, maxx+1) ax.set_xlabel('Number of Flat Fields Median Combined') ax.set_ylabel(r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8 ) plt.savefig(outdir+'/FlatCalibrationSigmaR2.pdf') plt.close() print '\nDelta results:' #loop over the number of frames combined for key in res: fig = plt.figure() ax = fig.add_subplot(111) plt.title(r'VIS Flat Field Calibration (%i exposures): $\delta e$' % key) de1 = np.asarray(res[key][4]) de2 = np.asarray(res[key][5]) de = np.asarray(res[key][6]) avg1 = np.mean(de1)2 avg2 = np.mean(de2)2 avg = np.mean(de)2 #write down the values print key, avg, avg1, avg2 plt.text(0.08, 0.9, r'$\left< \delta e_{1} \right>^{2} = %e$' %avg1, fontsize=10, transform=ax.transAxes) plt.text(0.08, 0.85, r'$\left< \delta e_{2}\right>^{2} = %e$' %avg2, fontsize=10, transform=ax.transAxes) plt.text(0.08, 0.8, r'$\left< \delta \| \bar{e} \|\right>^{2} = %e$' %avg, fontsize=10, transform=ax.transAxes) ax.hist(de, bins=15, color='y', alpha=0.2, label=r'$\delta \| \bar{e} \|$', normed=True, log=True) ax.hist(de1, bins=15, color='b', alpha=0.5, label=r'$\delta e_{1}$', normed=True, log=True) ax.hist(de2, bins=15, color='g', alpha=0.3, label=r'$\delta e_{2}$', normed=True, log=True) ax.axvline(x=0, ls=':', c='k') ax.set_ylabel('Probability Density') ax.set_xlabel(r'$\delta e_{i}\ , \ \ \ i \in [1,2]$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=2.0, ncol=2) plt.savefig(outdir+'/FlatCalibrationEDelta%i.pdf' % key) plt.close() #same for R2s for key in res: fig = plt.figure() plt.title(r'VIS Flat Field Calibration (%i exposures): $\frac{\delta R^{2}}{R_{ref}^{2}}$' % key) ax = fig.add_subplot(111) dR2 = np.asarray(res[key][7]) avg = np.mean(dR2/ref['R2'])2 ax.hist(dR2, bins=15, color='y', label=r'$\frac{\delta R^{2}}{R_{ref}^{2}}$', normed=True, log=True) print key, avg plt.text(0.1, 0.9, r'$\left<\frac{\delta R^{2}}{R^{2}_{ref}}\right>^{2} = %e$' %avg, fontsize=10, transform=ax.transAxes) ax.axvline(x=0, ls=':', c='k') ax.set_ylabel('Probability Density') ax.set_xlabel(r'$\frac{\delta R^{2}}{R_{ref}^{2}}$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8) plt.savefig(outdir+'/FlatCalibrationDeltaSize%i.pdf' % key) plt.close() def findTolerableError(log, file='data/psf4x.fits', oversample=4.0, psfs=10000, iterations=7, sigma=0.75): """ Calculate ellipticity and size for PSFs of different scaling when there is a residual pixel-to-pixel variations. """ #read in PSF and renormalize it data = pf.getdata(file) data /= np.max(data) #PSF scalings for the peak pixel, in electrons scales = np.random.random_integers(1e2, 2e5, psfs) #set the scale for shape measurement settings = dict(sampling=1.0/oversample, itereations=iterations, sigma=sigma) #residual from a perfect no pixel-to-pixel non-uniformity residuals = np.logspace(-7, -1.6, 9)[::-1] #largest first tot = residuals.size res = {} for i, residual in enumerate(residuals): print'%i / %i' % (i+1, tot) R2 = [] e1 = [] e2 = [] e = [] #loop over the PSFs for scale in scales: #random residual pixel-to-pixel variations if oversample < 1.1: residualSurface = np.random.normal(loc=1.0, scale=residual, size=data.shape) elif oversample == 4.0: tmp = np.random.normal(loc=1.0, scale=residual, size=(170, 170)) residualSurface = zoom(tmp, 4.013, order=0) else: sys.exit('ERROR when trying to generate a blocky pixel-to-pixel non-uniformity map...') #make a copy of the PSF and scale it with the given scaling #and then multiply with a residual pixel-to-pixel variation tmp = data.copy() scale * residualSurface #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(tmp.copy(), log, *settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) out = dict(e1=np.asarray(e1), e2=np.asarray(e2), e=np.asarray(e), R2=np.asarray(R2)) res[residual] = out return res def plotTolerableErrorR2(res, output, req=1e-4): fig = plt.figure() plt.title(r'VIS Flat Fielding') ax = fig.add_subplot(111) #loop over the number of bias frames combined vals = [] for key in res.keys(): dR2 = res[key]['R2'] normed = np.std(dR2) / np.mean(dR2) ax.scatter(key, normed, c='m', marker='', s=35) vals.append(normed) print key, normed #for the legend ax.scatter(key, normed, c='m', marker='', label=r'$\frac{\sigma(R^{2})}{R_{ref}^{2}}$') #show the requirement ks = np.asarray(res.keys()) ran = np.linspace(ks.min() 0.99, ks.max() * 1.01) ax.fill_between(ran, np.ones(ran.size) * req, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=req, c='g', ls='--', label='Requirement') #find the crossing srt = np.argsort(ks) values = np.asarray(vals) f = interpolate.interp1d(ks[srt], values[srt], kind='cubic') x = np.logspace(np.log10(ks.min()), np.log10(ks.max()), 100) vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) msk = vals < req maxn = np.max(x[msk]) plt.text(1e-5, 2e-5, r'Error must be $\leq %.2e$ per cent' % (maxn100), fontsize=11, ha='center', va='center') ax.set_yscale('log') ax.set_xscale('log') ax.set_ylim(1e-7, 1e-2) ax.set_xlim(ks.min() 0.99, ks.max() * 1.01) ax.set_xlabel('Error in the Flat Field Map') ax.set_ylabel(r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8, loc='upper left') plt.savefig(output) plt.close() def plotTolerableErrorE(res, output, req=3e-5): fig = plt.figure() plt.title(r'VIS Flat Fielding') ax = fig.add_subplot(111) #loop over the number of bias frames combined vals = [] for key in res.keys(): e1 = np.std(res[key]['e1']) e2 = np.std(res[key]['e']) e = np.std(res[key]['e']) vals.append(e) ax.scatter(key, e1, c='m', marker='', s=35) ax.scatter(key, e2, c='y', marker='s', s=35) ax.scatter(key, e, c='r', marker='o', s=35) print key, e, e1, e2 #for the legend ax.scatter(key, e1, c='m', marker='', label=r'$\sigma(e_{1})$') ax.scatter(key, e2, c='y', marker='s', label=r'$\sigma(e_{2})$') ax.scatter(key, e, c='r', marker='o', label=r'$\sigma(e)$') #show the requirement ks = np.asarray(res.keys()) ran = np.linspace(ks.min() * 0.99, ks.max() * 1.01) ax.fill_between(ran, np.ones(ran.size) * req, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=req, c='g', ls='--', label='Requirement') #find the crossing srt = np.argsort(ks) values = np.asarray(vals) f = interpolate.interp1d(ks[srt], values[srt], kind='cubic') x = np.logspace(np.log10(ks.min()), np.log10(ks.max()), 100) vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) msk = vals < req maxn = np.max(x[msk]) plt.text(1e-5, 2e-5, r'Error for $e$ must be $\leq %.2e$ per cent' % (maxn100), fontsize=11, ha='center', va='center') ax.set_yscale('log') ax.set_xscale('log') ax.set_ylim(1e-7, 1e-2) ax.set_xlim(ks.min() 0.99, ks.max() * 1.01) ax.set_xlabel('Error in the Flat Field Map') ax.set_ylabel(r'$\sigma (e_{i})\ , \ \ \ i \in [1,2]$') plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8, loc='upper left') plt.savefig(output) plt.close() def testNoFlatfieldingEffects(log, file='data/psf1x.fits', oversample=1.0, psfs=500): """ Calculate ellipticity and size variance and error in case of no pixel-to-pixel flat field correction. """ #read in PSF and renormalize it data = pf.getdata(file) data /= np.max(data) data = 1e5 #derive reference values settings = dict(sampling=1.0/oversample) sh = shape.shapeMeasurement(data.copy(), log, settings) reference = sh.measureRefinedEllipticity() print reference #residual residual = pf.getdata('data/VISFlatField2percent.fits') #'data/VISFlatField1percent.fits' if oversample == 4.0: residual = zoom(zoom(residual, 2, order=0), 2, order=0) elif oversample == 1.0: pass else: print 'ERROR--cannot do arbitrary oversampling...' #random positions for the PSFs, these positions are the lower corners xpositions = np.random.random_integers(0, residual.shape[1] - data.shape[1], psfs) ypositions = np.random.random_integers(0, residual.shape[0] - data.shape[0], psfs) #data storage out = {} de1 = [] de2 = [] de = [] R2 = [] dR2 = [] e1 = [] e2 = [] e = [] rnd = 1 tot = xpositions.size #loop over the PSFs for xpos, ypos in zip(xpositions, ypositions): print'%i / %i' % (rnd, tot) rnd += 1 #make a copy of the PSF tmp = data.copy() #get the underlying residual surface ond multiple the PSF with the surface small = residual[ypos:ypos+data.shape[0], xpos:xpos+data.shape[1]].copy() small = tmp #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(small.copy(), log, **settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) de1.append(results['e1'] - reference['e1']) de2.append(results['e2'] - reference['e2']) de.append(results['ellipticity'] - reference['ellipticity']) dR2.append(results['R2'] - reference['R2']) out[1] = [e1, e2, e, R2, de1, de2, de, dR2] return out, reference if __name__ == '__main__': run = True debug = False plots = True error = False #start the script log = lg.setUpLogger('flatfieldCalibration.log') log.info('Testing flat fielding calibration...') if error: res = findTolerableError(log) fileIO.cPickleDumpDictionary(res, 'errors/residuals.pk') res = cPickle.load(open('errors/residuals.pk')) plotTolerableErrorE(res, output='errors/FlatFieldingTolerableErrorE.pdf') plotTolerableErrorR2(res, output='errors/FlatFieldingTolerableErrorR2.pdf') if run: results = testFlatCalibration(log, flats=np.arange(5, 100, 9)) fileIO.cPickleDumpDictionary(results, 'flatfieldResults.pk') if debug: #calculate RMS on image with x frames combined together combined = generateResidualFlatField(combine=30, plots=True, debug=True) print np.std(combined), np.std(combined[500:561, 500:561]), np.std(combined[300:361, 300:361]) results = testNoFlatfieldingEffects(log, oversample=4.0, file='data/psf4x.fits', psfs=400) if plots: if not run: results = cPickle.load(open('flatfieldResults.pk')) plotNumberOfFrames(results) log.info('Run finished...\n\n\n')	[ 1, 9995, 13, 29943, 5066, 8989, 3037, 26218, 13, 9166, 2751, 1360, 13, 13, 4013, 2560, 2471, 508, 367, 1304, 304, 6559, 278, 1353, 310, 12151, 4235, 3734, 304, 5870, 278, 478, 3235, 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tests/test_rqscheduler.py	dymaxionlabs/nb_workflows	4	96104	<reponame>dymaxionlabs/nb_workflows from labfunctions.conf.server_settings import settings from labfunctions.control_plane import rqscheduler def test_rqscheduler_run(mocker): mocker.patch( "labfunctions.control_plane.rqscheduler.Scheduler.run", return_value=None ) rqscheduler.run(settings.RQ_REDIS, 5, "INFO")	[ 1, 529, 276, 1112, 420, 29958, 4518, 3317, 291, 29880, 6897, 29914, 9877, 29918, 1287, 1731, 29879, 13, 3166, 9775, 12171, 29889, 5527, 29889, 2974, 29918, 11027, 1053, 6055, 13, 3166, 9775, 12171, 29889, 6451, 29918, 22116, 1053, 364, 29939, 816, 14952, 13, 13, 13, 1753, 1243, 29918, 29878, 29939, 816, 14952, 29918, 3389, 29898, 29885, 8658, 1125, 13, 1678, 286, 8658, 29889, 5041, 29898, 13, 4706, 376, 8205, 12171, 29889, 6451, 29918, 22116, 29889, 29878, 29939, 816, 14952, 29889, 4504, 14952, 29889, 3389, 613, 736, 29918, 1767, 29922, 8516, 13, 1678, 1723, 13, 1678, 364, 29939, 816, 14952, 29889, 3389, 29898, 11027, 29889, 29934, 29984, 29918, 19386, 3235, 29892, 29871, 29945, 29892, 376, 11690, 1159, 13, 2 ]
getch.py	salt-die/Snippets	3	153122	<filename>getch.py import sys from io import BytesIO if sys.platform.startswith('linux'): import fcntl import os import termios import tty def getch(block=True): fd = sys.stdin.fileno() settings = termios.tcgetattr(fd) flags = fcntl.fcntl(fd, fcntl.F_GETFL) try: tty.setraw(fd) if not block: fcntl.fcntl(fd, fcntl.F_SETFL, flags \| os.O_NONBLOCK) return sys.stdin.buffer.read(1) finally: fcntl.fcntl(fd, fcntl.F_SETFL, flags) termios.tcsetattr(fd, termios.TCSADRAIN, settings) elif sys.platform == 'win32': import msvcrt def getch(block=True): if not block and not msvcrt.kbhit(): return b'' return msvcrt.getch() else: try: # Try for Mac import Carbon Carbon.Evt # Not in *nix except (ModuleNotFoundError, AttributeError) as e: raise OSError(f'getch not implemented for {sys.platform}') from e def getch(block=True): # I haven't tested this. if not block and Carbon.Evt.EventAvail(0x0008)[0] == 0: # 0x0008 is the keyDownMask return b'' return bytes(chr(Carbon.Evt.GetNextEvent(0x0008)[1][1] & 0x000000FF), 'utf8') def flush(): with BytesIO() as r: while c := getch(block=False): r.write(c) return r.getvalue()	[ 1, 529, 9507, 29958, 657, 305, 29889, 2272, 13, 5215, 10876, 13, 3166, 12013, 1053, 2648, 2167, 5971, 13, 13, 13, 361, 10876, 29889, 12120, 29889, 27382, 2541, 877, 9389, 29374, 13, 1678, 1053, 285, 20047, 29880, 13, 1678, 1053, 2897, 13, 1678, 1053, 1840, 2363, 13, 1678, 1053, 260, 1017, 13, 13, 1678, 822, 679, 305, 29898, 1271, 29922, 5574, 1125, 13, 4706, 285, 29881, 353, 10876, 29889, 4172, 262, 29889, 1777, 8154, 580, 13, 4706, 6055, 353, 1840, 2363, 29889, 14246, 657, 5552, 29898, 11512, 29897, 13, 4706, 13449, 353, 285, 20047, 29880, 29889, 13801, 593, 29880, 29898, 11512, 29892, 285, 20047, 29880, 29889, 29943, 29918, 7194, 10536, 29897, 13, 13, 4706, 1018, 29901, 13, 9651, 260, 1017, 29889, 842, 1610, 29898, 11512, 29897, 13, 9651, 565, 451, 2908, 29901, 13, 18884, 285, 20047, 29880, 29889, 13801, 593, 29880, 29898, 11512, 29892, 285, 20047, 29880, 29889, 29943, 29918, 1660, 8969, 29931, 29892, 13449, 891, 2897, 29889, 29949, 29918, 29940, 1164, 29933, 21339, 29897, 13, 9651, 736, 10876, 29889, 4172, 262, 29889, 9040, 29889, 949, 29898, 29896, 29897, 13, 4706, 7146, 29901, 13, 9651, 285, 20047, 29880, 29889, 13801, 593, 29880, 29898, 11512, 29892, 285, 20047, 29880, 29889, 29943, 29918, 1660, 8969, 29931, 29892, 13449, 29897, 13, 9651, 1840, 2363, 29889, 14246, 842, 5552, 29898, 11512, 29892, 1840, 2363, 29889, 29911, 9295, 3035, 4717, 1177, 29892, 6055, 29897, 13, 13, 23681, 10876, 29889, 12120, 1275, 525, 5080, 29941, 29906, 2396, 13, 1678, 1053, 286, 4501, 29883, 2273, 13, 13, 1678, 822, 679, 305, 29898, 1271, 29922, 5574, 1125, 13, 4706, 565, 451, 2908, 322, 451, 286, 4501, 29883, 2273, 29889, 21066, 27342, 7295, 13, 9651, 736, 289, 4907, 13, 4706, 736, 286, 4501, 29883, 2273, 29889, 657, 305, 580, 13, 13, 2870, 29901, 13, 1678, 1018, 29901, 29871, 396, 3967, 363, 4326, 13, 4706, 1053, 1704, 6718, 13, 4706, 1704, 6718, 29889, 29923, 21908, 29871, 396, 2216, 297, 334, 29876, 861, 13, 1678, 5174, 313, 7355, 17413, 2392, 29892, 23833, 2392, 29897, 408, 321, 29901, 13, 4706, 12020, 438, 29173, 29898, 29888, 29915, 657, 305, 451, 8762, 363, 426, 9675, 29889, 12120, 29913, 1495, 515, 321, 13, 13, 1678, 822, 679, 305, 29898, 1271, 29922, 5574, 1125, 29871, 396, 306, 7359, 29915, 29873, 9528, 445, 29889, 13, 4706, 565, 451, 2908, 322, 1704, 6718, 29889, 29923, 21908, 29889, 2624, 12810, 737, 29898, 29900, 29916, 29900, 29900, 29900, 29947, 9601, 29900, 29962, 1275, 29871, 29900, 29901, 29871, 396, 29871, 29900, 29916, 29900, 29900, 29900, 29947, 338, 278, 1820, 6767, 19832, 13, 9651, 736, 289, 4907, 13, 4706, 736, 6262, 29898, 22495, 29898, 8179, 6718, 29889, 29923, 21908, 29889, 2577, 9190, 2624, 29898, 29900, 29916, 29900, 29900, 29900, 29947, 9601, 29896, 3816, 29896, 29962, 669, 29871, 29900, 29916, 29900, 29900, 29900, 29900, 29900, 29900, 4198, 511, 525, 9420, 29947, 1495, 13, 13, 1753, 28371, 7295, 13, 1678, 411, 2648, 2167, 5971, 580, 408, 364, 29901, 13, 4706, 1550, 274, 3490, 679, 305, 29898, 1271, 29922, 8824, 1125, 13, 9651, 364, 29889, 3539, 29898, 29883, 29897, 13, 4706, 736, 364, 29889, 657, 1767, 580, 13, 2 ]
purpleair_connector/main.py	tetradsensors/gcp-functions	0	118590	from google.cloud import bigquery, storage import json import pandas as pd import time import requests import os import datetime import geojson import numpy as np from matplotlib.path import Path from time import sleep import yaml UPDATE_MINS = 60 gs_client = storage.Client() env = None _area_params = None # Download the project environment variables # env = yaml.load( # gs_client.get_bucket(os.getenv('gs_bucket')).get_blob(os.getenv('config')).download_as_string(), # Loader=yaml.SafeLoader) def getProjectConfigFile(): if not hasattr(getProjectConfigFile, "updateTime"): getProjectConfigFile.updateTime = 0 if time.time() - getProjectConfigFile.updateTime > (UPDATE_MINS60): getProjectConfigFile.env = yaml.load(gs_client.get_bucket(os.environ['gs_bucket']).get_blob(os.environ['config']).download_as_string(), Loader=yaml.SafeLoader) getProjectConfigFile.updateTime = time.time() return getProjectConfigFile.env def getAreaParams(): if not hasattr(getAreaParams, "updateTime"): getAreaParams.updateTime = 0 if time.time() - getAreaParams.updateTime > (UPDATE_MINS60): bucket = env['storage']['server_bucket']['name'] area_params_json = env['storage']['server_bucket']['files']['area_params'] getAreaParams.params = json.loads( gs_client.get_bucket(bucket).get_blob(area_params_json).download_as_string()) getAreaParams.updateTime = time.time() getAreaParams.params = buildAreaModelsFromJson(getAreaParams.params) return getAreaParams.params def loadBoundingBox(bbox_info): if bbox_info is None: return None rows = [row for row in bbox_info] bounding_box_vertices = [(index, float(row['Latitude']), float(row['Longitude'])) for row, index in zip(rows, range(len(rows)))] return bounding_box_vertices def buildAreaModelsFromJson(json_data): area_models = {} for key in json_data: this_model = {} this_model['name'] = json_data[key]['Name'] this_model['timezone'] = json_data[key]['Timezone'] this_model['idstring'] = json_data[key]['ID String'] this_model['elevationfile'] = json_data[key]['Elevation File'] this_model['note'] = json_data[key]['Note'] # this_model['elevationinterpolator'] = buildAreaElevationInterpolator(json_data[key]['Elevation File']) this_model['elevationinterpolator'] = None this_model['boundingbox'] = loadBoundingBox(json_data[key]['Boundingbox']) # this_model['correctionfactors'] = loadCorrectionFactors(json_data[key]['Correction Factors'],json_data[key]['Timezone']) # this_model['lengthscales'] = loadLengthScales(json_data[key]['Length Scales'], json_data[key]['Timezone']) if 'Source table map' in json_data[key]: this_model['sourcetablemap'] = json_data[key]['Source table map'] # else: # this_model['sourcetablemap'] = None area_models[key] = this_model return area_models # Information for all the regions # _area_params = buildAreaModelsFromJson( # json.loads( # gs_client.get_bucket(env['storage']['server_bucket']['name'] # ).get_blob(env['storage']['server_bucket']['files']['area_params'] # ).download_as_string())) def getAreaModelBounds(area_model): print(area_model.keys()) if area_model['boundingbox'] is None: return None area_bounds = area_model['boundingbox'] bounds = { 'lat_hi': area_bounds[0][1], 'lon_hi': area_bounds[1][2], 'lat_lo': area_bounds[2][1], 'lon_lo': area_bounds[3][2] } if bounds['lat_hi'] <= bounds['lat_lo'] or bounds['lon_hi'] < bounds['lon_lo']: return None else: return bounds def isQueryInBoundingBox(bounding_box_vertices, query_lat, query_lon): verts = [(0, 0)] * len(bounding_box_vertices) for elem in bounding_box_vertices: verts[elem[0]] = (elem[2], elem[1]) # Add first vertex to end of verts so that the path closes properly verts.append(verts[0]) codes = [Path.MOVETO] codes += [Path.LINETO] * (len(verts) - 2) codes += [Path.CLOSEPOLY] boundingBox = Path(verts, codes) return boundingBox.contains_point((query_lon, query_lat)) def getAreaModelByLocation(area_models, lat=0.0, lon=0.0, string=None): if string is None: for key in area_models: if (isQueryInBoundingBox(area_models[key]['boundingbox'], lat, lon)): print(f'Using area_model for {key}') return area_models[key] else: try: return area_models[string] except: print("Got bad request for area by string: " + str(string)) print("Query location "+str(lat)+ "," + str(lon) + " not in any known model area") return None def applyRegionalLabelsToDataFrame(regions_dict, df, null_value=np.nan, trim=False): df['Label'] = null_value for region_name, region_info in regions_dict.items(): bbox = getAreaModelBounds(region_info) if bbox is None: continue df.loc[ (df['Lat'] >= bbox['lat_lo']) & (df['Lat'] <= bbox['lat_hi']) & (df['Lon'] >= bbox['lon_lo']) & (df['Lon'] <= bbox['lon_hi']), 'Label' ] = region_info['name'] print(f"For region {region_name}, applied labels to {len(df[df['Label'] == region_info['name']])} rows") print(f"Regional labels applied to {len(df[~df['Label'].isnull()])} out of {len(df)} rows. ({int(100 * (len(df[~df['Label'].isnull()]) / len(df)))})") if trim: x = len(df) df = df.dropna(subset=['Label']) print(f"Dropped {x - len(df)} unlabeled rows.") return df def chunk_list(ls, chunk_size=10000): ''' BigQuery only allows inserts <=10,000 rows ''' for i in range(0, len(ls), chunk_size): yield ls[i: i + chunk_size] def setPMSModels(df, col_name): pms_models = ['PMS1003', 'PMS3003', 'PMS5003', 'PMS7003'] for model in pms_models: df.loc[df['Type'].str.contains(model), col_name] = model return df def setChildFromParent(df, pairings, col_name): df.loc[pairings.index, col_name] = df.loc[pairings, col_name].values return df def getParentChildPairing(df): ''' Purple Air devices have two PM sensors inside. Data is reported for both sensors seperately, but one sensor is considered the "parent" and one is the "child". The child has lots of missing information, like DEVICE_LOCATIONTYPE, Flag, Type. So we create this Series to link parents and children, then later use this Series to fill in missing data for the children with data from their parents. Beware: sometimes we find orphans - rows with a non-null ParentID, but no corresponding row with an ID equal to the value of that ParentID. ''' # Get the rows where ParentID is not Null (ParentID values are the IDs of the parent sensors) pairings = df['ParentID'].loc[~df['ParentID'].isnull()].astype(int) # Eliminate orphans (sorry orphans) pairings = pairings[pairings.isin(df.index)] return pairings def main(data, context): # with open('area_params.json') as json_file: # json_temp = json.load(json_file) # _area_models = buildAreaModelsFromJson(json_temp) global _area_params, env env = getProjectConfigFile() _area_params = getAreaParams() response = None try: response = json.loads(requests.get('https://www.purpleair.com/json?a').text) results = response['results'] except Exception as e: print('Could not download data. Exception: ', str(e), response) try: print('trying again after 15 seconds') sleep(20) response = json.loads(requests.get('https://www.purpleair.com/json?a').text) results = response['results'] except: print('Could not download data (take 2). Exception: ', str(e), response) return # Convert JSON response to a Pandas DataFrame df = pd.DataFrame(results) print(f'rows: {len(df)}') if df.empty: return # Trim off old data df['LastSeen'] = pd.to_datetime(df['LastSeen'], unit='s', utc=True) # Remove all datapoints older than 6 minutes. Run every 5 minutes, so give 1 minute overlap df = df[df['LastSeen'] > (pd.Timestamp.utcnow() - pd.Timedelta(6, unit='minutes'))] # Following Series operations depend on having an index df = df.set_index('ID') # Get Series with index = child ID and 'ParentID' = Parent ID pairing = getParentChildPairing(df) # Set DEVICE_LOCATIONTYPE child to DEVICE_LOCATIONTYPE parent df = setChildFromParent(df, pairing, 'DEVICE_LOCATIONTYPE') # Set flag of child sensor to flag of parent sensor df = setChildFromParent(df, pairing, 'Flag') # Set the 'Type' string of child to that of parent df = setChildFromParent(df, pairing, 'Type') # Use 'Flag', 'A_H', 'Hidden' to filter out bad data # 'Flag': Data flagged for unusually high readings # 'A_H': true if the sensor output has been downgraded or marked for attention due to suspected hardware issues # 'Hidden': Hide from public view on map: true/false df = df.fillna({ 'A_H': False, 'Flag': False, 'Hidden': False }) # Convert JSON 'true'/'false' strings into bools df = df.replace({'true': True, 'false': False}) # Change types df = df.astype({ 'A_H': bool, 'Flag': bool, 'Hidden': bool, 'PM2_5Value': float, 'temp_f': float, 'LastSeen': str, }) # If any of these are true, remove the row df['Flag'] = df['Flag'] \| df['A_H'] \| df['Hidden'] # Remove rows df = df[df['DEVICE_LOCATIONTYPE'] == 'outside'] # Remove sensors not outside df = df[df['Flag'] != 1] # Remove sensors with Flag, A_H, or Hidden flags df = df.dropna(subset=['Lat', 'Lon']) # Remove sensors with no lat/lon info # Apply regional labels ('slc_ut', 'chatt_tn', etc.) df = applyRegionalLabelsToDataFrame(_area_params, df, trim=True) # Create the GPS column df['GPS'] = df.apply(lambda x: geojson.dumps(geojson.Point((x['Lon'], x['Lat']))), axis=1) # Move bad PM data out of cleaned column df['PM2_5_Raw'] = df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'PM2_5Value'] df['Flags'] = 0 df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'Flags'] \|= 2 df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'PM2_5Value'] = np.nan # Convert temperature F to C df['temp_f'] = (df['temp_f'] - 32) * (5. / 9) # clean up PMS 'Type' names df = setPMSModels(df, col_name='PMSModel') # Reduce DataFrame to desired columns df = df.reset_index() cols_to_keep = ['LastSeen', 'ID', 'GPS', 'PM2_5Value', 'PM2_5_Raw', 'Flags', 'PMSModel', 'humidity', 'temp_f', 'pressure', 'Label'] df = df.loc[:, df.columns.isin(cols_to_keep)] # Append 'PP' to device id's df['ID'] = 'PP' + df['ID'].astype(str) # Add 'Source' = 'PurpleAir' df['Source'] = 'PurpleAir' # Finally, convert NaN to None df = df.replace({np.nan: None}) # Rename columns df = df.rename({ 'LastSeen': 'Timestamp', 'ID': 'DeviceID', 'PM2_5Value': 'PM2_5', 'humidity': 'Humidity', 'temp_f': 'Temperature', 'pressure': 'Pressure' }, axis='columns') # Convert dataframe to list of dicts data = df.to_dict('records') # Create unique row_ids to avoid duplicates when inserting overlapping data row_ids = pd.util.hash_pandas_object(df[['Timestamp', 'DeviceID']]).values.astype(str) bq_client = bigquery.Client() target_table = bq_client.dataset(env['bigquery']['tbl_telemetry']['ds_name']).table(env['bigquery']['tbl_telemetry']['tbl_name']) # Maximum upload size for BigQuery API is 10,000 rows, so we have to upload the data in chunks for i, (data_chunk, rows_chunk) in enumerate(zip(chunk_list(data, chunk_size=10000), chunk_list(row_ids, chunk_size=10000))): print(f'Sending chunk {i + 1}...') errors = bq_client.insert_rows_json( table=target_table, json_rows=data_chunk, row_ids=rows_chunk ) if errors: print(errors) else: print(f"Inserted {len(rows_chunk)} rows") if __name__ == '__main__': # This only runs locally import os os.environ['gs_bucket'] = "tetrad-resources" os.environ['config'] = "tetrad_config.yaml" main('data', 'context')	[ 1, 515, 5386, 29889, 9274, 1053, 4802, 1972, 29892, 8635, 13, 5215, 4390, 13, 5215, 11701, 408, 10518, 13, 5215, 931, 13, 5215, 7274, 13, 5215, 2897, 13, 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examples/gradient_damagex.py	TTitscher/fenics-constitutive	0	69247	""" Implicit gradient-enhanced damage model in dolfinx ================================================== For the theory and the constitutive model, please refer to the dolfin version :ref:`gdm-label`. Here, you see the "quadrature" approach working in dolfinx without the need of `LocalProject`. """ from gdm_constitutive import * from gdm_analytic import PeerlingsAnalytic import dolfinx as df from petsc4py import PETSc from mpi4py import MPI import ufl import basix import matplotlib.pyplot as plt class GDMProblemX: def __init__(self, mesh, mat, deg=2, q_deg=4, fd_np=None): self.mesh, self.mat= mesh, mat Ed = ufl.VectorElement("CG", mesh.ufl_cell(), degree=deg) Ee = ufl.FiniteElement("CG", mesh.ufl_cell(), degree=deg) self.V = df.fem.FunctionSpace(mesh, (Ed * Ee)) self.Vd, self.Ve = self.V.sub(0), self.V.sub(1) self.u = df.fem.Function(self.V) q = "Quadrature" cell = mesh.ufl_cell() voigt = 3 QF = ufl.FiniteElement(q, cell, q_deg, quad_scheme="default") QV = ufl.VectorElement(q, cell, q_deg, quad_scheme="default", dim=voigt) QT = ufl.TensorElement( q, cell, q_deg, quad_scheme="default", shape=(voigt, voigt) ) VQF, VQV, VQT = [df.fem.FunctionSpace(mesh, Q) for Q in [QF, QV, QT]] self.q_sigma = df.fem.Function(VQV) self.q_e = df.fem.Function(VQF) self.q_eeq = df.fem.Function(VQF) self.q_dsigma_deps = df.fem.Function(VQT) self.q_dsigma_de = df.fem.Function(VQV) self.q_deeq_deps = df.fem.Function(VQV) # define functions dd, de = ufl.TrialFunctions(self.V) d_, e_ = ufl.TestFunctions(self.V) self.d, self.e = ufl.split(self.u) # define form self.metadata = {"quadrature_degree": q_deg, "quadrature_scheme": "default"} self.dxm = ufl.dx(metadata=self.metadata) # prepare strain evaluation eps = mat.eps map_c = mesh.topology.index_map(mesh.topology.dim) num_cells = map_c.size_local + map_c.num_ghosts self.cells = np.arange(0, num_cells, dtype=np.int32) basix_celltype = getattr(basix.CellType, mesh.topology.cell_type.name) self.q_points, wts = basix.make_quadrature(basix_celltype, q_deg) self.strain_expr = df.fem.Expression(eps(self.d), self.q_points) self.e_expr = df.fem.Expression(self.e, self.q_points) self.evaluate_constitutive_law() self.bcs = None if fd_np is None: fd_np = lambda x: 1.0 Vfd = df.fem.FunctionSpace(mesh, ("DG", 0)) fd = df.fem.Function(Vfd) fd.x.array[:] = fd_np(Vfd.tabulate_dof_coordinates()) R = fd * ufl.inner(eps(d_), self.q_sigma) * self.dxm R += e_ * (self.e - self.q_eeq) * self.dxm R += ufl.dot(ufl.grad(e_), mat.l ** 2 * ufl.grad(self.e)) * self.dxm dR = fd * ufl.inner(eps(d_), self.q_dsigma_deps * eps(dd)) * self.dxm dR += fd * ufl.inner(eps(d_), self.q_dsigma_de * de) * self.dxm dR += e_ * (de - ufl.dot(self.q_deeq_deps, eps(dd))) * self.dxm dR += ufl.dot(ufl.grad(e_), mat.l ** 2 * ufl.grad(de)) * self.dxm self.R, self.dR = df.fem.form(R), df.fem.form(dR) self.solver = None def evaluate_constitutive_law(self): with df.common.Timer("compute strains"): strain = self.strain_expr.eval(self.cells) e = self.e_expr.eval(self.cells) with df.common.Timer("evaluate constitutive law"): self.mat.evaluate(strain.flatten(), e.flatten()) with df.common.Timer("assign q space"): self.q_sigma.x.array[:] = self.mat.sigma.flat self.q_dsigma_deps.x.array[:] = self.mat.dsigma_deps.flat self.q_dsigma_de.x.array[:] = self.mat.dsigma_de.flat self.q_eeq.x.array[:] = self.mat.eeq.flat self.q_deeq_deps.x.array[:] = self.mat.deeq.flat def update(self): e = self.e_expr.eval(self.cells) self.mat.update(e.flatten()) def form(self, x: PETSc.Vec): """This function is called before the residual or Jacobian is computed. This is usually used to update ghost values. Parameters ---------- x The vector containing the latest solution """ x.ghostUpdate(addv=PETSc.InsertMode.INSERT, mode=PETSc.ScatterMode.FORWARD) x.copy(self.u.vector) self.u.vector.ghostUpdate( addv=PETSc.InsertMode.INSERT, mode=PETSc.ScatterMode.FORWARD ) self.evaluate_constitutive_law() def J(self, x: PETSc.Vec, A: PETSc.Mat, P=None): """Assemble the Jacobian matrix.""" A.zeroEntries() df.fem.petsc.assemble_matrix(A, self.dR, bcs=self.bcs) A.assemble() def F(self, x: PETSc.Vec, b: PETSc.Vec): """Assemble the residual F into the vector b.""" # Reset the residual vector with b.localForm() as b_local: b_local.set(0.0) df.fem.petsc.assemble_vector(b, self.R) df.fem.apply_lifting(b, [self.dR], bcs=[self.bcs], x0=[x], scale=-1.0) b.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE) df.fem.set_bc(b, self.bcs, x, -1.0) def solve(self): if self.solver is None: self.a = self.dR self.L = self.R self.solver = df.nls.petsc.NewtonSolver(MPI.COMM_WORLD, self) self.solver.atol = 1.e-8 return self.solver.solve(self.u) def plane_at(x): """ """ def boundary(c): return np.isclose(c[0, :], x) return boundary def gdm_error(n_elements): """ ... evaluated in 2D """ e = PeerlingsAnalytic() mesh = df.mesh.create_rectangle( MPI.COMM_WORLD, [[0, 0], [e.L / 2.0, 1]], [n_elements, 1], df.mesh.CellType.quadrilateral, ) mat = GDMPlaneStrain(E=e.E, nu=0.0, ft=e.E * e.kappa0, l=e.l, dmg=damage_perfect) def area(coords): A = np.full(len(coords), 10.0) A[coords[:, 0] < e.W / 2.0] = 1.0 - e.alpha return A problem = GDMProblemX(mesh, mat, fd_np=area) V = problem.Vd # space of displacements to apply the BCs b_facets_l = df.mesh.locate_entities_boundary(mesh, 1, plane_at(0.0)) b_facets_r = df.mesh.locate_entities_boundary(mesh, 1, plane_at(e.L / 2.0)) b_dofs_lx = df.fem.locate_dofs_topological(V.sub(0), 1, b_facets_l) b_dofs_ly = df.fem.locate_dofs_topological(V.sub(1), 1, b_facets_l) b_dofs_rx = df.fem.locate_dofs_topological(V.sub(0), 1, b_facets_r) u_bc = df.fem.Constant(mesh, 0.0) problem.bcs = [ df.fem.dirichletbc(PETSc.ScalarType(0), b_dofs_lx, V.sub(0)), df.fem.dirichletbc(PETSc.ScalarType(0), b_dofs_ly, V.sub(1)), df.fem.dirichletbc(u_bc, b_dofs_rx, V.sub(0)), ] for t in np.linspace(0.0, 1.0, 11): u_bc.value = t e.deltaL / 2.0 iterations, converged = problem.solve() assert converged problem.update() # Honestly, I have not idea (yet) how to properly/easily compute the # errornorm to the analytic solution. Thus, we extract the dof # coordinates x to compute analytic dof values. e_fem = problem.u.sub(1).collapse() xs = e_fem.function_space.tabulate_dof_coordinates()[:, 0] e_exact = [e.e(x) for x in xs] return np.linalg.norm(e_fem.x.array - e_exact) def convergence_test(): ns = [50, 100, 200, 400] errors = [] for n in ns: error = gdm_error(n) print(f"Error to analytic solution with {n} elements is {error}.") errors.append(error) ps = [] for i in range(len(ns) - 1): p = np.log(errors[i] - errors[i + 1]) / np.log(1.0 / ns[i] - 1.0 / ns[i + 1]) ps.append(p) import matplotlib.pyplot as plt plt.figure(figsize=(6, 3)) plt.loglog(ns, errors, "-ko") plt.xlabel("# elements") plt.ylabel("error") plt.tight_layout() plt.savefig("gdm_convergencex.png") plt.show() if __name__ == "__main__": convergence_test()	[ 1, 9995, 13, 24192, 4019, 16030, 29899, 264, 29308, 18658, 1904, 297, 270, 4369, 14668, 13, 9166, 9166, 9166, 1360, 13, 13, 2831, 278, 6368, 322, 278, 20016, 11067, 1904, 29892, 3113, 2737, 304, 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draft/migrations/0001_initial.py	zffgithub/genshin-bp	0	57951	# Generated by Django 3.0.4 on 2020-04-17 23:13 from django.db import migrations, models import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Champion', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('lane', models.CharField(default='', help_text='한글로 입력해주세요. ex)上单/中路', max_length=20, verbose_name='라인')), ('keyword', models.CharField(default='', help_text='"/" 로 구분해주세요. ex)가렌/garen', max_length=255, verbose_name='검색어')), ('no', models.CharField(default='', max_length=3, verbose_name='角色번호')), ('name', models.CharField(default='', help_text='한글로 입력해주세요. ex)가렌', max_length=20, verbose_name='角色명')), ], options={ 'verbose_name': '角色', 'verbose_name_plural': '角色', }, ), migrations.CreateModel( name='Draft', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('match_name', models.CharField(max_length=255, verbose_name='매치 이름')), ('red_team_name', models.CharField(max_length=255, verbose_name='红队名称')), ('blue_team_name', models.CharField(max_length=255, verbose_name='蓝队名称')), ('password', models.CharField(max_length=255, verbose_name='패스워드')), ('banpick', models.CharField(blank=True, max_length=255, verbose_name='禁选Data')), ('timer', models.DateTimeField(blank=True, null=True, verbose_name='시작')), ('date', models.DateTimeField(default=django.utils.timezone.now, verbose_name='일시')), ], options={ 'verbose_name': '禁选', 'verbose_name_plural': '禁选', }, ), ]	[ 1, 396, 3251, 630, 491, 15337, 29871, 29941, 29889, 29900, 29889, 29946, 373, 29871, 29906, 29900, 29906, 29900, 29899, 29900, 29946, 29899, 29896, 29955, 29871, 29906, 29941, 29901, 29896, 29941, 13, 13, 3166, 9557, 29889, 2585, 1053, 9725, 800, 29892, 4733, 13, 5215, 9557, 29889, 13239, 29889, 2230, 8028, 13, 13, 13, 1990, 341, 16783, 29898, 26983, 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src/compat_func.py	rangell/icff	0	68351	<gh_stars>0 import copy import numpy as np from sparse_dot_mkl import dot_product_mkl from utils import MIN_FLOAT from IPython import embed #def raw_overlap(node, constraint, num_points): def raw_overlap(raw_reps, stacked_constraints, num_points): extreme_raw_reps = copy.deepcopy(raw_reps).astype(float) extreme_raw_reps = np.inf extreme_constraints = copy.deepcopy(stacked_constraints).astype(float) extreme_constraints.data = np.inf compat_mx = dot_product_mkl( extreme_raw_reps, extreme_constraints.T, dense=True ) incompat_mx = ((compat_mx == -np.inf) \| np.isnan(compat_mx)) pos_overlap_scores = dot_product_mkl( raw_reps.astype(float), stacked_constraints.T, dense=True ) pos_overlap_scores = np.array(pos_overlap_scores) pos_overlap_mask = (pos_overlap_scores > 0) pos_feat_totals = np.array(np.sum(stacked_constraints > 0, axis=1).T) overlap_scores = pos_overlap_scores / pos_feat_totals overlap_scores = pos_overlap_mask overlap_scores[overlap_scores == 1] = num_points overlap_scores[incompat_mx] = -np.inf return np.asarray(overlap_scores) def transformed_overlap(node, constraint): # FIXME: this won't work assert False rep = node.transformed_rep pair_product = rep constraint if np.array_equal(rep, np.ones_like(rep) * -np.inf) \ or not np.all(pair_product >= 0): return MIN_FLOAT else: score = np.sum(pair_product > 0) / np.sum(constraint != 0) return score if score < 1 else num_points * score	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 3509, 13, 5215, 12655, 408, 7442, 13, 13, 3166, 29234, 29918, 6333, 29918, 29885, 6321, 1053, 8329, 29918, 4704, 29918, 29885, 6321, 13, 13, 3166, 3667, 29879, 1053, 341, 1177, 29918, 29943, 3927, 1299, 13, 13, 3166, 5641, 1656, 1053, 8297, 13, 13, 13, 29937, 1753, 10650, 29918, 957, 6984, 29898, 3177, 29892, 7276, 29892, 954, 29918, 9748, 1125, 13, 1753, 10650, 29918, 957, 6984, 29898, 1610, 29918, 276, 567, 29892, 5096, 287, 29918, 13646, 29879, 29892, 954, 29918, 9748, 1125, 13, 1678, 18677, 29918, 1610, 29918, 276, 567, 353, 3509, 29889, 24535, 8552, 29898, 1610, 29918, 276, 567, 467, 579, 668, 29898, 7411, 29897, 13, 1678, 18677, 29918, 1610, 29918, 276, 567, 334, 29922, 7442, 29889, 7192, 13, 1678, 18677, 29918, 13646, 29879, 353, 3509, 29889, 24535, 8552, 29898, 1429, 287, 29918, 13646, 29879, 467, 579, 668, 29898, 7411, 29897, 13, 1678, 18677, 29918, 13646, 29879, 29889, 1272, 334, 29922, 7442, 29889, 7192, 13, 1678, 10007, 29918, 16838, 353, 8329, 29918, 4704, 29918, 29885, 6321, 29898, 13, 4706, 18677, 29918, 1610, 29918, 276, 567, 29892, 18677, 29918, 13646, 29879, 29889, 29911, 29892, 20619, 29922, 5574, 13, 1678, 1723, 13, 1678, 297, 12667, 29918, 16838, 353, 5135, 12667, 29918, 16838, 1275, 448, 9302, 29889, 7192, 29897, 891, 7442, 29889, 275, 13707, 29898, 12667, 29918, 16838, 876, 13, 1678, 926, 29918, 957, 6984, 29918, 1557, 2361, 353, 8329, 29918, 4704, 29918, 29885, 6321, 29898, 13, 4706, 10650, 29918, 276, 567, 29889, 579, 668, 29898, 7411, 511, 5096, 287, 29918, 13646, 29879, 29889, 29911, 29892, 20619, 29922, 5574, 13, 1678, 1723, 13, 1678, 926, 29918, 957, 6984, 29918, 1557, 2361, 353, 7442, 29889, 2378, 29898, 1066, 29918, 957, 6984, 29918, 1557, 2361, 29897, 13, 1678, 926, 29918, 957, 6984, 29918, 13168, 353, 313, 1066, 29918, 957, 6984, 29918, 1557, 2361, 1405, 29871, 29900, 29897, 13, 1678, 926, 29918, 1725, 271, 29918, 4260, 1338, 353, 7442, 29889, 2378, 29898, 9302, 29889, 2083, 29898, 1429, 287, 29918, 13646, 29879, 1405, 29871, 29900, 29892, 9685, 29922, 29896, 467, 29911, 29897, 13, 1678, 25457, 29918, 1557, 2361, 353, 926, 29918, 957, 6984, 29918, 1557, 2361, 847, 926, 29918, 1725, 271, 29918, 4260, 1338, 13, 1678, 25457, 29918, 1557, 2361, 334, 29922, 926, 29918, 957, 6984, 29918, 13168, 13, 1678, 25457, 29918, 1557, 2361, 29961, 957, 6984, 29918, 1557, 2361, 1275, 29871, 29896, 29962, 353, 954, 29918, 9748, 13, 1678, 25457, 29918, 1557, 2361, 29961, 262, 12667, 29918, 16838, 29962, 353, 448, 9302, 29889, 7192, 13, 1678, 736, 7442, 29889, 294, 2378, 29898, 957, 6984, 29918, 1557, 2361, 29897, 13, 13, 13, 1753, 27615, 29918, 957, 6984, 29898, 3177, 29892, 7276, 1125, 13, 1678, 396, 383, 6415, 2303, 29901, 445, 2113, 29915, 29873, 664, 13, 1678, 4974, 7700, 13, 1678, 1634, 353, 2943, 29889, 9067, 287, 29918, 3445, 13, 1678, 5101, 29918, 4704, 353, 1634, 334, 7276, 13, 1678, 565, 7442, 29889, 2378, 29918, 11745, 29898, 3445, 29892, 7442, 29889, 2873, 29918, 4561, 29898, 3445, 29897, 334, 448, 9302, 29889, 7192, 29897, 320, 13, 9651, 470, 451, 7442, 29889, 497, 29898, 18784, 29918, 4704, 6736, 29871, 29900, 1125, 13, 4706, 736, 341, 1177, 29918, 29943, 3927, 1299, 13, 1678, 1683, 29901, 13, 4706, 8158, 353, 7442, 29889, 2083, 29898, 18784, 29918, 4704, 1405, 29871, 29900, 29897, 847, 7442, 29889, 2083, 29898, 13646, 2804, 29871, 29900, 29897, 13, 4706, 736, 8158, 565, 8158, 529, 29871, 29896, 1683, 954, 29918, 9748, 334, 8158, 13, 2 ]
exercicios_basico/ex007.py	montalvas/python	0	186271	<gh_stars>0 # Informe duas notas e sem seguida mostre sua média. n1 = float(input('Informe a primeira nota: ')) n2 = float(input('Informe a segunda nota: ')) print("As notas do aluno foram {} e {}, logo sua média será {:.2f}".format(n1, n2, (n1 + n2)/2))	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 15162, 29872, 27544, 451, 294, 321, 3031, 7025, 1458, 1556, 276, 4171, 10283, 423, 29889, 13, 13, 29876, 29896, 353, 5785, 29898, 2080, 877, 797, 689, 29872, 263, 20997, 451, 29874, 29901, 525, 876, 13, 29876, 29906, 353, 5785, 29898, 2080, 877, 797, 689, 29872, 263, 17329, 451, 29874, 29901, 525, 876, 13, 2158, 703, 2887, 451, 294, 437, 394, 9447, 15305, 6571, 321, 24335, 20194, 4171, 10283, 423, 724, 29976, 12365, 29889, 29906, 29888, 29913, 1642, 4830, 29898, 29876, 29896, 29892, 302, 29906, 29892, 313, 29876, 29896, 718, 302, 29906, 6802, 29906, 876, 13, 2 ]
src/python/utility/shared.py	andyjost/Sprite	1	119842	<filename>src/python/utility/shared.py from copy import copy import collections, six, sys class Shared(object): ''' Manages an object with copy-on-write semantics. To access the contained object for reading or writing, use the ``read`` and ``write`` methods, resp. If the object has multiple references, then writing will trigger a copy. ''' def __init__(self, ty, obj=None): self.ty = ty if obj is None: self.obj = ty() assert self.unique else: self.obj = obj def __copy__(self): return Shared(self.ty, self.obj) # sharing copy @property def read(self): return self.obj @property def write(self): if not self.unique: self.obj = self.ty(self.obj) # copy for write assert self.unique return self.obj @property def refcnt(self): return sys.getrefcount(self.obj) - 1 @property def unique(self): return self.refcnt == 1 def __str__(self): return str(self.read) def __repr__(self): return str(self) return 'Shared(refcnt=%s, %s)' % (self.refcnt, self.obj) # Read-only container methods, for convenience. def __contains__(self, key): return key in self.obj def __len__(self): return len(self.obj) def __getitem__(self, key): return self.obj[key] def __iter__(self): return iter(self.obj) class DefaultDict(collections.defaultdict): '''Like defaultdict but recursively copies values.''' def __copy__(self): return DefaultDict(self.default_factory, {k: copy(v) for k,v in six.iteritems(self)}) copy = __copy__ def compose(typefunction, ty): ''' Composes a type function and type. The type function is a type, such as Shared or DefaultDict, that takes another type as its only argument. The returned object has object-copy semantics. ''' def factory(obj=None): if obj is None: return typefunction(ty) else: return copy(obj) return factory	[ 1, 529, 9507, 29958, 4351, 29914, 4691, 29914, 329, 1793, 29914, 12366, 29889, 2272, 13, 3166, 3509, 1053, 3509, 13, 5215, 16250, 29892, 4832, 29892, 10876, 13, 13, 1990, 21236, 29898, 3318, 1125, 13, 29871, 14550, 13, 29871, 2315, 1179, 385, 1203, 411, 3509, 29899, 265, 29899, 3539, 29505, 29889, 29871, 1763, 2130, 278, 11122, 13, 29871, 1203, 363, 5183, 470, 5007, 29892, 671, 278, 4954, 949, 16159, 322, 4954, 3539, 16159, 3519, 29892, 4613, 29889, 13, 29871, 960, 278, 1203, 756, 2999, 9282, 29892, 769, 5007, 674, 7135, 263, 3509, 29889, 13, 29871, 14550, 13, 29871, 822, 4770, 2344, 12035, 1311, 29892, 7911, 29892, 5446, 29922, 8516, 1125, 13, 1678, 1583, 29889, 1017, 353, 7911, 13, 1678, 565, 5446, 338, 6213, 29901, 13, 418, 1583, 29889, 5415, 353, 7911, 580, 13, 418, 4974, 1583, 29889, 13092, 13, 1678, 1683, 29901, 13, 418, 1583, 29889, 5415, 353, 5446, 13, 29871, 822, 4770, 8552, 12035, 1311, 1125, 13, 1678, 736, 21236, 29898, 1311, 29889, 1017, 29892, 1583, 29889, 5415, 29897, 396, 19383, 3509, 13, 29871, 732, 6799, 13, 29871, 822, 1303, 29898, 1311, 1125, 13, 1678, 736, 1583, 29889, 5415, 13, 29871, 732, 6799, 13, 29871, 822, 2436, 29898, 1311, 1125, 13, 1678, 565, 451, 1583, 29889, 13092, 29901, 13, 418, 1583, 29889, 5415, 353, 1583, 29889, 1017, 29898, 1311, 29889, 5415, 29897, 396, 3509, 363, 2436, 13, 1678, 4974, 1583, 29889, 13092, 13, 1678, 736, 1583, 29889, 5415, 13, 29871, 732, 6799, 13, 29871, 822, 2143, 20047, 29898, 1311, 1125, 13, 1678, 736, 10876, 29889, 657, 999, 2798, 29898, 1311, 29889, 5415, 29897, 448, 29871, 29896, 13, 29871, 732, 6799, 13, 29871, 822, 5412, 29898, 1311, 1125, 13, 1678, 736, 1583, 29889, 999, 20047, 1275, 29871, 29896, 13, 29871, 822, 4770, 710, 12035, 1311, 1125, 13, 1678, 736, 851, 29898, 1311, 29889, 949, 29897, 13, 29871, 822, 4770, 276, 558, 12035, 1311, 1125, 13, 1678, 736, 851, 29898, 1311, 29897, 13, 1678, 736, 525, 21741, 29898, 999, 20047, 16328, 29879, 29892, 1273, 29879, 16029, 1273, 313, 1311, 29889, 999, 20047, 29892, 1583, 29889, 5415, 29897, 13, 29871, 396, 7523, 29899, 6194, 5639, 3519, 29892, 363, 29703, 29889, 13, 29871, 822, 4770, 11516, 12035, 1311, 29892, 1820, 1125, 13, 1678, 736, 1820, 297, 1583, 29889, 5415, 13, 29871, 822, 4770, 2435, 12035, 1311, 1125, 13, 1678, 736, 7431, 29898, 1311, 29889, 5415, 29897, 13, 29871, 822, 4770, 657, 667, 12035, 1311, 29892, 1820, 1125, 13, 1678, 736, 1583, 29889, 5415, 29961, 1989, 29962, 13, 29871, 822, 4770, 1524, 12035, 1311, 1125, 13, 1678, 736, 4256, 29898, 1311, 29889, 5415, 29897, 13, 13, 1990, 13109, 21533, 29898, 29027, 29889, 4381, 8977, 1125, 13, 29871, 14550, 27552, 2322, 8977, 541, 8304, 3598, 14591, 1819, 29889, 12008, 13, 29871, 822, 4770, 8552, 12035, 1311, 1125, 13, 1678, 736, 13109, 21533, 29898, 1311, 29889, 4381, 29918, 14399, 29892, 426, 29895, 29901, 3509, 29898, 29894, 29897, 363, 413, 29892, 29894, 297, 4832, 29889, 1524, 7076, 29898, 1311, 26972, 13, 29871, 3509, 353, 4770, 8552, 1649, 13, 13, 1753, 27435, 29898, 1853, 2220, 29892, 7911, 1125, 13, 29871, 14550, 13, 29871, 422, 10590, 263, 1134, 740, 322, 1134, 29889, 29871, 450, 1134, 740, 338, 263, 1134, 29892, 1316, 408, 13, 29871, 21236, 470, 13109, 21533, 29892, 393, 4893, 1790, 1134, 408, 967, 871, 2980, 29889, 29871, 450, 13, 29871, 4133, 1203, 756, 1203, 29899, 8552, 29505, 29889, 13, 29871, 14550, 13, 29871, 822, 12529, 29898, 5415, 29922, 8516, 1125, 13, 1678, 565, 5446, 338, 6213, 29901, 13, 418, 736, 1134, 2220, 29898, 1017, 29897, 13, 1678, 1683, 29901, 13, 418, 736, 3509, 29898, 5415, 29897, 13, 29871, 736, 12529, 13, 13, 13, 2 ]
scraper.py	noswald/PatentScraper1.0	2	119063	from pyvirtualdisplay import Display from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.common.exceptions import WebDriverException from selenium.common.exceptions import TimeoutException from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys import time from datetime import datetime from lxml import html from lxml import etree from io import StringIO from fake_useragent import UserAgent import pandas as pd import numpy as np dateFormat = '%Y-%m-% %H:%M:%S' fileDate = '%Y%m%d%H%M' filePath = '/home/noswald/Documents/PersonalScraper/' chromeDriverPath = '/home/noswald/Documents/PersonalScraper/chromedriver' searchValue = 'wallet' searchPage = 'http://patft.uspto.gov/netahtml/PTO/search-adv.htm' queryID = 'mytextarea' searchButtonValue = 'Search' yrsDropDownValue = 'PTXT' display = Display(visible=0,size=(800,600)) display.start() #add tor dependency and logic PROXY = 'socks5://127.0.0.1:9050' chrome_options = webdriver.ChromeOptions() chrome_options.add_argument('--proxy-server=%s' % PROXY) #add useragent ua = UserAgent() userAgent = ua.random print("My user agent is: " + userAgent) chrome_options.add_argument('user-agent=%s' % userAgent) #start browser browser = webdriver.Chrome(chrome_options = chrome_options, executable_path = chromeDriverPath) browser.get(searchPage) inputElement = browser.find_element_by_id(queryID) inputElement.send_keys(searchValue) time.sleep(2) inputElement.submit() html_source = browser.page_source curDT = datetime.now() datepulled = curDT t = curDT.strftime('%Y%m%d%H%M') #uncomment if writing html file to directory #f = open(filePath+'test1_' + t + '.html','w') #f.write(html_source) #f.close() tree = html.parse(StringIO(html_source)) #added logic to pull correct end range (1-length of initial number of rows in table) endRow = len(tree.xpath('//table[1]//tr'))-1 patentRank = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[1]//text()')[0] for x in range(2,endRow)] patentNumber = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[2]//text()')[0] for x in range(2,endRow)] patentTitle = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]//text()')[0] for x in range(2,endRow)] patentLink = ['http://patft.uspto.gov' + tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]/a/@href')[0] for x in range(2,endRow)] #loop over next page while len(tree.xpath("//form[@name='srchForm']//input[starts-with(@name,'NextList')]"))>0: inputElement = browser.find_element_by_xpath("//form[@name='srchForm']//input[starts-with(@name,'NextList')]") time.sleep(2) inputElement.click() #try clicking button #add logic to pull new rank, number, title, and link and then append to existing data columns html_source = browser.page_source curDT = datetime.now() datepulled = curDT #uncomment if writing html file to directory #f = open(filePath+'test1_' + t + '.html','w') #f.write(html_source) #f.close() tree = html.parse(StringIO(html_source)) endRow = len(tree.xpath('//table[1]//tr'))-1 patentRank += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[1]//text()')[0] for x in range(2,endRow)] patentNumber += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[2]//text()')[0] for x in range(2,endRow)] patentTitle += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]//text()')[0] for x in range(2,endRow)] patentLink += ['http://patft.uspto.gov' + tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]/a/@href')[0] for x in range(2,endRow)] time.sleep(2) #keep re-creating dictionary and csv file with current data patentDict = {'Rank':patentRank, 'PatentNumber':patentNumber, 'PatentTitle':patentTitle, 'PatentLink':patentLink} patentFrame = pd.DataFrame.from_dict(patentDict) patentFrame.to_csv(filePath+searchValue+'_'+t+'.txt',sep='\t') browser.quit() display.stop() #create full Dictionary after all pages have been extracted patentDict = {'Rank':patentRank, 'PatentNumber':patentNumber, 'PatentTitle':patentTitle, 'PatentLink':patentLink} patentFrame = pd.DataFrame.from_dict(patentDict) patentFrame.to_csv(filePath+searchValue+'_'+t+'.txt',sep='\t') print("Finished Scraping")	[ 1, 515, 11451, 18714, 4990, 1053, 17440, 13, 3166, 18866, 1053, 1856, 9465, 13, 3166, 18866, 29889, 29813, 29889, 9435, 29889, 8149, 1053, 4813, 952, 13, 3166, 18866, 29889, 9435, 29889, 11739, 29879, 1053, 2563, 12376, 2451, 13, 3166, 18866, 29889, 9435, 29889, 11739, 29879, 1053, 5974, 449, 2451, 13, 3166, 18866, 29889, 29813, 29889, 5924, 29889, 1481, 1053, 2563, 12376, 15716, 13, 3166, 18866, 29889, 29813, 29889, 9435, 29889, 1609, 1053, 2648, 13, 3166, 18866, 29889, 29813, 29889, 9435, 29889, 8149, 1053, 4813, 952, 13, 5215, 931, 13, 3166, 12865, 1053, 12865, 13, 3166, 301, 3134, 1053, 3472, 13, 3166, 301, 3134, 1053, 634, 929, 13, 3166, 12013, 1053, 1714, 5971, 13, 3166, 25713, 29918, 1792, 14748, 1053, 4911, 19661, 13, 5215, 11701, 408, 10518, 13, 5215, 12655, 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test/lib/testMap.py	animator/titus2	18	194093	#!/usr/bin/env python # Copyright (C) 2014 Open Data ("Open Data" refers to # one or more of the following companies: Open Data Partners LLC, # Open Data Research LLC, or Open Data Capital LLC.) # # This file is part of Hadrian. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest from titus.genpy import PFAEngine from titus.errors import * class TestLib1Map(unittest.TestCase): def testGetLength(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: int action: - {map.len: [input]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), 5) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: int action: - {map.len: [input]} ''') self.assertEqual(engine.action({}), 0) def testGetKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: string} action: - {map.keys: [input]} ''') self.assertEqual(set(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})), set(["a", "b", "c", "d", "e"])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: string} action: - {map.keys: [input]} ''') self.assertEqual(engine.action({}), []) def testGetValues(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.values: [input]} ''') self.assertEqual(set(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})), set([1, 2, 3, 4, 5])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.values: [input]} ''') self.assertEqual(engine.action({}), []) def testCheckContainsKey(self): engine, = PFAEngine.fromYaml(''' input: string output: boolean action: map.containsKey: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertTrue(engine.action("a")) self.assertFalse(engine.action("z")) engine, = PFAEngine.fromYaml(''' input: string output: boolean action: map.containsKey: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - params: [{x: string}] ret: boolean do: {"==": [x, input]} ''') self.assertTrue(engine.action("a")) self.assertFalse(engine.action("z")) def testCheckContainsKey(self): engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.containsValue: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertTrue(engine.action(1)) self.assertFalse(engine.action(9)) engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.containsValue: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - params: [{x: int}] ret: boolean do: {"==": [x, input]} ''') self.assertTrue(engine.action(1)) self.assertFalse(engine.action(9)) def testAddKeyValuePairs(self): engine, = PFAEngine.fromYaml(''' input: string output: {type: map, values: int} action: map.add: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input - 999 ''') self.assertEqual(engine.action("a"), {"a": 999, "b": 2, "c": 3, "d": 4, "e": 5}) self.assertEqual(engine.action("z"), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "z": 999}) engine, = PFAEngine.fromYaml(''' input: int output: {type: map, values: int} action: map.add: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - input ''') self.assertEqual(engine.action(1), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4}) self.assertEqual(engine.action(999), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4, "zg8=": 999}) def testRemoveKeys(self): engine, = PFAEngine.fromYaml(''' input: string output: {type: map, values: int} action: map.remove: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action("a"), {"b": 2, "c": 3, "d": 4, "e": 5}) self.assertEqual(engine.action("z"), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) def testKeepOnlyCertainKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.only: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {"b": 2, "c": 3, "e": 5}) self.assertEqual(engine.action(["b", "c", "e", "z"]), {"b": 2, "c": 3, "e": 5}) self.assertEqual(engine.action([]), {}) engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.only: - {value: {}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {}) self.assertEqual(engine.action([]), {}) def testEliminateOnlyCertainKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.except: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {"a": 1, "d": 4}) self.assertEqual(engine.action(["b", "c", "e", "z"]), {"a": 1, "d": 4}) self.assertEqual(engine.action([]), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.except: - {value: {}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {}) self.assertEqual(engine.action([]), {}) def testUpdateWithAnOverlay(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.update: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action({"b": 102, "c": 103, "z": 999}), {"a": 1, "b": 102, "c": 103, "d": 4, "e": 5, "z": 999}) def testSplit(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: {type: map, values: int}} action: map.split: input ''') self.assertEqual(sorted(engine.action({"a": 1, "b": 2, "c": 3}), key=lambda x: list(x.keys())[0]), sorted([{"a": 1}, {"b": 2}, {"c": 3}], key=lambda x: list(x.keys())[0])) def testJoin(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: {type: map, values: int}} output: {type: map, values: int} action: map.join: input ''') self.assertEqual(sorted(engine.action([{"a": 1}, {"b": 2}, {"c": 3}])), sorted({"a": 1, "b": 2, "c": 3})) def testNumericalArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmax: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}]} ''')[0].action(None), "2") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmin: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}]} ''')[0].action(None), "1") def testObjectArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmax: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmin: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}]} ''')[0].action(None), "4") def testUserDefinedArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argmaxLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argmaxLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argminLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "4") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argminLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "4") def testFindTop3NumericalArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argmaxN: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}, 3]} ''')[0].action(None), ["2", "6", "4"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argminN: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}, 3]} ''')[0].action(None), ["1", "5", "3"]) def testFindTop3ObjectArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argmaxN: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}, 3]} ''')[0].action(None), ["1", "2", "5"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argminN: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}, 3]} ''')[0].action(None), ["4", "3", "0"]) def testFindTop3UserDefinedArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argmaxNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["1", "5", "3"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argmaxNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["1", "5", "3"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argminNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["4", "0", "6"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argminNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["4", "0", "6"]) def testToSet(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: {type: map, values: int} action: - {map.toset: [input]} ''') self.assertEqual(engine.action([1, 2, 3, 4, 5]), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4}) def testFromSet(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.fromset: [input]} ''') self.assertEqual(set(engine.action({"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4})), set([1, 2, 3, 4, 5])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: array, items: string} action: - {map.fromset: [input]} ''') self.assertEqual(set(engine.action({"BA==": "two", "Ag==": "one", "Bg==": "three", "Cg==": "five", "CA==": "four"})), set(["one", "two", "three", "four", "five"])) def testIn(self): engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.in: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - input ''') self.assertTrue(engine.action(2)) self.assertFalse(engine.action(0)) def testUnion(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.union: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3, 4, 5, 6, 7, 8])) def testIntersection(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.intersection: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([4, 5])) def testDiff(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.diff: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3])) def testSymDiff(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.symdiff: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3, 6, 7, 8])) def testSubset(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: boolean action: map.subset: - {map.toset: input} - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} ''') self.assertTrue(engine.action([1, 2, 3])) self.assertFalse(engine.action([1, 2, 3, 999])) self.assertFalse(engine.action([888, 999])) def testDisjoint(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: boolean action: map.disjoint: - {map.toset: input} - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} ''') self.assertFalse(engine.action([1, 2, 3])) self.assertFalse(engine.action([1, 2, 3, 999])) self.assertTrue(engine.action([888, 999])) def testMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: map, values: int} action: map.map: - input - params: [{x: string}] ret: int do: {parse.int: [x, 10]} ''') self.assertEqual(engine.action({"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) def testMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: map, values: int} action: map.mapWithKey: - input - params: [{key: string}, {value: string}] ret: int do: if: {">": [key, {string: "c"}]} then: {+: [{parse.int: [value, 10]}, 1000]} else: {parse.int: [value, 10]} ''') self.assertEqual(engine.action({"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}), {"a": 1, "b": 2, "c": 3, "d": 1004, "e": 1005}) def testFilter(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filter: - input - params: [{x: int}] ret: boolean do: {"<": [x, 3]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1, "b": 2}) def testFilterWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterWithKey: - input - params: [{key: string}, {value: int}] ret: boolean do: {"&&": [{"<": [value, 3]}, {"==": [key, {string: "a"}]}]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1}) def testFilterMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterMap: - input - params: [{value: int}] ret: [int, "null"] do: if: {"==": [{"%": [value, 2]}, 0]} then: {"+": [value, 1000]} else: null ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"b": 1002, "d": 1004}) def testFilterMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterMapWithKey: - input - params: [{key: string}, {value: int}] ret: [int, "null"] do: if: {"&&": [{"==": [{"%": [value, 2]}, 0]}, {"==": [key, {string: "b"}]}]} then: {"+": [value, 1000]} else: null ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"b": 1002}) def testFlatMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.flatMap: - input - params: [{value: int}] ret: {type: map, values: int} do: if: {">": [value, 2]} then: - let: {out: {value: {}, type: {type: map, values: int}}} - set: out: map.add: - out - {s.int: value} - value - set: out: map.add: - out - {s.concat: [{s.int: value}, {s.int: value}]} - value - out else: {value: {}, type: {type: map, values: int}} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"3": 3, "4": 4, "5": 5, "33": 3, "44": 4, "55": 5}) def testFlatMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.flatMapWithKey: - input - params: [{key: string}, {value: int}] ret: {type: map, values: int} do: map.add: - map.add: - {value: {}, type: {type: map, values: int}} - key - value - {s.concat: [key, key]} - {+: [100, value]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "aa": 101, "bb": 102, "cc": 103, "dd": 104, "ee": 105}) def testZipMap(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - params: [{a: string}, {b: int}] ret: string do: {s.concat: [a, {s.int: b}]} ''')[0].action(None), {"0": "x101", "1": "y102", "2": "z103"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - params: [{a: string}, {b: int}, {c: string}] ret: string do: {s.concat: [{s.concat: [a, {s.int: b}]}, c]} ''')[0].action(None), {"0": "x101a", "1": "y102b", "2": "z103c"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - {value: {"0": true, "1": false, "2": true}, type: {type: map, values: boolean}} - params: [{a: string}, {b: int}, {c: string}, {d: boolean}] ret: string do: {s.concat: [{s.concat: [{s.concat: [a, {s.int: b}]}, c]}, {if: d, then: {string: "-up"}, else: {string: "-down"}}]} ''')[0].action(None), {"0": "x101a-up", "1": "y102b-down", "2": "z103c-up"}) def testZipMapWithKey(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - params: [{k: string}, {a: string}, {b: int}] ret: string do: {s.concat: [{s.concat: [k, a]}, {s.int: b}]} ''')[0].action(None), {"0": "0x101", "1": "1y102", "2": "2z103"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - params: [{k: string}, {a: string}, {b: int}, {c: string}] ret: string do: {s.concat: [{s.concat: [{s.concat: [k, a]}, {s.int: b}]}, c]} ''')[0].action(None), {"0": "0x101a", "1": "1y102b", "2": "2z103c"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - {value: {"0": true, "1": false, "2": true}, type: {type: map, values: boolean}} - params: [{k: string}, {a: string}, {b: int}, {c: string}, {d: boolean}] ret: string do: {s.concat: [{s.concat: [{s.concat: [{s.concat: [k, a]}, {s.int: b}]}, c]}, {if: d, then: {string: "-up"}, else: {string: "-down"}}]} ''')[0].action(None), {"0": "0x101a-up", "1": "1y102b-down", "2": "2z103c-up"}) def testCorresponds(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: boolean action: map.corresponds: - input - {value: {"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}, type: {type: map, values: string}} - params: [{x: int}, {y: string}] ret: boolean do: {"==": [x, {parse.int: [y, 10]}]} ''') self.assertTrue(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertFalse(engine.action({"a": 111, "b": 2, "c": 3, "d": 4, "e": 5})) def testCorrespondsWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: boolean action: map.correspondsWithKey: - input - {value: {"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}, type: {type: map, values: string}} - params: [{k: string}, {x: int}, {y: string}] ret: boolean do: if: {"==": [k, {string: "a"}]} then: true else: {"==": [x, {parse.int: [y, 10]}]} ''') self.assertTrue(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertTrue(engine.action({"a": 111, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertFalse(engine.action({"a": 1, "b": 222, "c": 3, "d": 4, "e": 5}))	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 13, 13, 29937, 14187, 1266, 313, 29907, 29897, 29871, 29906, 29900, 29896, 29946, 29871, 4673, 3630, 4852, 6585, 3630, 29908, 14637, 304, 13, 29937, 697, 470, 901, 310, 278, 1494, 14582, 29901, 4673, 3630, 3455, 8397, 365, 12182, 29892, 13, 29937, 4673, 3630, 10550, 365, 12182, 29892, 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text/ko_dictionary.py

mozzihozzi/Custom-Speech-Synthesis-Service-using-Multi-speaker-tacotron

3

77205

etc_dictionary = { '2 30대': '이삼십대', '20~30대': '이삼십대', '20, 30대': '이십대 삼십대', '1+1': '원플러스원', '3에서 6개월인': '3개월에서 육개월인', } english_dictionary = { 'Devsisters': '데브시스터즈', 'track': '트랙', # krbook 'LA': '엘에이', 'LG': '엘지', 'KOREA': '코리아', 'JSA': '제이에스에이', 'PGA': '피지에이', 'GA': '지에이', 'idol': '아이돌', 'KTX': '케이티엑스', 'AC': '에이씨', 'DVD': '디비디', 'US': '유에스', 'CNN': '씨엔엔', 'LPGA': '엘피지에이', 'P': '피', 'L': '엘', 'T': '티', 'B': '비', 'C': '씨', 'BIFF': '비아이에프에프', 'GV': '지비', # JTBC 'IT': '아이티', 'IQ': '아이큐', 'JTBC': '제이티비씨', 'trickle down effect': '트리클 다운 이펙트', 'trickle up effect': '트리클 업 이펙트', 'down': '다운', 'up': '업', 'FCK': '에프씨케이', 'AP': '에이피', 'WHERETHEWILDTHINGSARE': '', 'Rashomon Effect': '', 'O': '오', 'OO': '오오', 'B': '비', 'GDP': '지디피', 'CIPA': '씨아이피에이', 'YS': '와이에스', 'Y': '와이', 'S': '에스', 'JTBC': '제이티비씨', 'PC': '피씨', 'bill': '빌', 'Halmuny': '하모니', ##### 'X': '엑스', 'SNS': '에스엔에스', 'ability': '어빌리티', 'shy': '', 'CCTV': '씨씨티비', 'IT': '아이티', 'the tenth man': '더 텐쓰 맨', #### 'L': '엘', 'PC': '피씨', 'YSDJJPMB': '', ######## 'Content Attitude Timing': '컨텐트 애티튜드 타이밍', 'CAT': '캣', 'IS': '아이에스', 'SNS': '에스엔에스', 'K': '케이', 'Y': '와이', 'KDI': '케이디아이', 'DOC': '디오씨', 'CIA': '씨아이에이', 'PBS': '피비에스', 'D': '디', 'PPropertyPositionPowerPrisonP' 'S': '에스', 'francisco': '프란시스코', 'I': '아이', 'III': '아이아이', ###### 'No joke': '노 조크', 'BBK': '비비케이', 'LA': '엘에이', 'Don': '', 't worry be happy': ' 워리 비 해피', 'NO': '엔오', ##### 'it was our sky': '잇 워즈 아워 스카이', 'it is our sky': '잇 이즈 아워 스카이', #### 'NEIS': '엔이아이에스', ##### 'IMF': '아이엠에프', 'apology': '어폴로지', 'humble': '험블', 'M': '엠', 'Nowhere Man': '노웨어 맨', 'The Tenth Man': '더 텐쓰 맨', 'PBS': '피비에스', 'BBC': '비비씨', 'MRJ': '엠알제이', 'CCTV': '씨씨티비', 'Pick me up': '픽 미 업', 'DNA': '디엔에이', 'UN': '유엔', 'STOP': '스탑', ##### 'PRESS': '프레스', ##### 'not to be': '낫 투비', 'Denial': '디나이얼', 'G': '지', 'IMF': '아이엠에프', 'GDP': '지디피', 'JTBC': '제이티비씨', 'Time flies like an arrow': '타임 플라이즈 라이크 언 애로우', 'DDT': '디디티', 'AI': '에이아이', 'Z': '제트', 'OECD': '오이씨디', 'N': '앤', 'A': '에이', 'MB': '엠비', 'EH': '이에이치', 'IS': '아이에스', 'TV': '티비', 'MIT': '엠아이티', 'KBO': '케이비오', 'I love America': '아이 러브 아메리카', 'SF': '에스에프', 'Q': '큐', 'KFX': '케이에프엑스', 'PM': '피엠', 'Prime Minister': '프라임 미니스터', 'Swordline': '스워드라인', 'TBS': '티비에스', 'DDT': '디디티', 'CS': '씨에스', 'Reflecting Absence': '리플렉팅 앱센스', 'PBS': '피비에스', 'Drum being beaten by everyone': '드럼 빙 비튼 바이 에브리원', 'negative pressure': '네거티브 프레셔', 'F': '에프', 'KIA': '기아', 'FTA': '에프티에이', 'Que sais-je': '', 'UFC': '유에프씨', 'P': '피', 'DJ': '디제이', 'Chaebol': '채벌', 'BBC': '비비씨', 'OECD': '오이씨디', 'BC': '삐씨', 'C': '씨', 'B': '씨', 'KY': '케이와이', 'K': '케이', 'CEO': '씨이오', 'YH': '와이에치', 'IS': '아이에스', 'who are you': '<NAME>', 'Y': '와이', 'The Devils Advocate': '더 데빌즈 어드보카트', 'YS': '와이에스', 'so sorry': '쏘 쏘리', 'Santa': '산타', 'Big Endian': '빅 엔디안', 'Small Endian': '스몰 엔디안', 'Oh Captain My Captain': '오 캡틴 마이 캡틴', 'AIB': '에이아이비', 'K': '케이', 'PBS': '피비에스', }

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main.py

alextremblay962/Hydropinic_System

0

39004

import serial import json import io import time ser = serial.Serial("COM24" , 9600, timeout=2) topic = "hydro/light1" payload = 1 #data = json.dumps({"topic":topic,"payload":payload}) data = "{\"topic\":\"hydro/light1\",\"payload\":1}" data = data.encode() print(data) ser.write(b'A') hello = ser.readline()#.decode("ascii") print(hello)

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LintCode/BinarySearch/20191115_binary_search.py

Fabriceli/MachingLearning

0

72340

<filename>LintCode/BinarySearch/20191115_binary_search.py # -*-coding:utf-8 -*- #Reference:********************************************** # @Time : 2019-11-15 11:14 # @Author : <NAME> # @File : 20191115_binary_search.py # @User : liyihao # @Software : PyCharm # @Description: default module binary search #Reference:********************************************** class Solution(): def binary_search_default(self, nums, target): if len(nums) <= 0: return -1 left = 0 right = len(nums) - 1 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: right = mid elif nums[mid] < target: left = mid elif nums[mid] > target: right = mid if nums[right] == target: return right if nums[left] == target: return left return -1 def binary_search_left_edge(self, nums, target): if len(nums) <= 0: return -1 left = 0 # 重点 right = len(nums) - 1 # 重点 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: right = mid elif nums[mid] > target: right = mid elif nums[mid] < target: left = mid if nums[left] == target: return left if nums[right] == target: return right return -1 def binary_search_right_edge(self, nums, target): if len(nums) <= 0: return -1 left = 0 right = len(nums) - 1 while left + 1 < right: mid = int(left + (right - left) / 2) if nums[mid] == target: left = mid elif nums[mid] > target: right = mid elif nums[mid] < target: left = mid if nums[right] == target: return right if nums[left] == target: return left return -1 if __name__ == '__main__': s = Solution() nums = [1, 2] target = 2 print("left edge: " + str(s.binary_search_left_edge(nums, target))) print("right edge: " + str(s.binary_search_right_edge(nums, target)))

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examples/run_midi.py

lucystrauss/genki-wave

17

186473

""" This script is adopted from [here](https://github.com/atizo/pygame/blob/master/examples/midi.py) # MacOS and Windows Connecting the wave ring as a midi device via bluetooth should work out-of-the-box on Windows and MacOS. # Linux On Linux you might need to re-install `BlueZ` with support for midi as follows. Installation instructions for Linux. Taken from [here](https://tttapa.github.io/Pages/Ubuntu/Software-Installation/BlueZ.html) ``` sudo apt install libudev-dev libical-dev libreadline-dev libdbus-1-dev libasound2-dev sudo apt install build-essential # Use whatever version of BlueZ you want and change accordingly cd /tmp wget https://mirrors.edge.kernel.org/pub/linux/bluetooth/bluez-5.53.tar.xz tar -xf bluez-5.53.tar.xz cd bluez-5.53 ./configure --enable-midi --with-systemdsystemunitdir=/etc/systemd/system make sudo make install sudo apt-get install --reinstall bluez ``` You might need a restart after this step Check if the device is detected: ``` aconnect -lio ``` If pygame raises a warning that `Cannot open shared library libasound_module_conf_pulse.so` it might be searching in the wrong place a way to fix it is to create a symbolic link to where the actual library is to where pygame searches. An example for ubuntu (pygame searches in `/usr/lib/alsa-lib`) sudo ln -s /usr/lib/x86_64-linux-gnu/alsa-lib /usr/lib/alsa-lib Solution adapted from [here](https://stackoverflow.com/questions/57946421/im-trying-to-run-this-code-initialize-pygame-midi-code-but-it-returns-an-error) # noqa """ import functools from enum import IntEnum from typing import Optional, Tuple try: import pygame import pygame.midi except ModuleNotFoundError: raise ModuleNotFoundError( "This script only depends on pygame, not the genki-wave library so please install 'pygame'" "manually to run this script" ) class MidiStatus(IntEnum): DATA = 176 class Movements(IntEnum): PITCH = 16 YAW = 17 ROLL = 18 movements_values = [item.value for item in Movements] def midi_setup_and_teardown(func): """Sets up midi before calling a function and tears it down after running Alternatively `pygame.midi.init()` and `pygame.midi.quit()` can be called at the beginning and end of each function manually """ @functools.wraps(func) def wrapper(*args, **kwargs): pygame.midi.init() results = func(*args, **kwargs) pygame.midi.quit() return results return wrapper @midi_setup_and_teardown def print_device_info(): """Prints all midi devices that were found""" for i in range(pygame.midi.get_count()): interf, name, is_input, output, opened = pygame.midi.get_device_info(i) in_out = "" if is_input: in_out = "(input)" if output: in_out = "(output)" print(f"{i}: interface {interf}, name {name}, opened {opened} {in_out}") @midi_setup_and_teardown def wave_input_device_info() -> Optional[Tuple[int, str]]: """Automatically find input `Wave` input device""" result = None for i in range(pygame.midi.get_count()): interf, name, is_input, output, opened = pygame.midi.get_device_info(i) name_decoded = name.decode() if is_input and "Wave" in name_decoded: result = i, name_decoded return result @midi_setup_and_teardown def input_main(device_id): pygame.init() # Define our input device input_midi = pygame.midi.Input(device_id) pygame.display.set_mode((1, 1)) going = True print_vals_results = ["", "", ""] while going: for event in pygame.event.get(): if event.type in [pygame.QUIT]: going = False if event.type in [pygame.KEYDOWN]: # Program will stop if any button is pressed going = False if event.type in [pygame.midi.MIDIIN, pygame.USEREVENT]: print(event) # Check if there is any data in the buffer of the midi-device. If not, continue with the loop if not input_midi.poll(): continue # Read all the data from the midi buffer (max_size=1024) midi_events = input_midi.read(1024) midi_events = pygame.midi.midis2events(midi_events, input_midi.device_id) # 3 different functions to use. Uncomment different ones to try out # post_custom_events(midi_events) # post_midi_events(midi_events, Movements.ROLL) print_vals_results = print_values(midi_events, print_vals_results) del input_midi def print_values(midi_events, previous_vals: list) -> list: """Prints a 'data' midi event i.e. where there is information sent about roll/pitch/yaw If an event of a certain type is not found, prints the last value for that event """ s = previous_vals for m_e in midi_events: if m_e.status == MidiStatus.DATA and m_e.data1 in movements_values: s = [m_e.data2 if m_e.data1 == val else prev_val for prev_val, val in zip(previous_vals, movements_values)] print(f"P: {s[0]:>3}, Y: {s[1]:>3}, R: {s[2]:>3}") return s def post_custom_events(midi_events): """Only print certain events""" for m_e in midi_events: if m_e.status == MidiStatus.DATA and m_e.data1 == Movements.YAW: if m_e.data2 > 100: pygame.event.post(pygame.event.Event(pygame.USEREVENT, {"val": "down"})) if m_e.data2 < 30: pygame.event.post(pygame.event.Event(pygame.USEREVENT, {"val": "up"})) def post_midi_events(midi_events, movement_type): """Post all midi events corresponding to data coming in""" for m_e in midi_events: if m_e.status == MidiStatus.DATA and m_e.data1 == movement_type: pygame.event.post(m_e) def main(): print("Make sure your Wave is connected to your computer as a midi device") print_device_info() device_id, name = wave_input_device_info() if device_id is not None: print(f"Found input device: {name} - {device_id}") print("Press any keyboard button to stop") input_main(device_id) else: print("Did not find a Wave device") if __name__ == "__main__": main()

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yang_et_al/run_tasks.py

wagner-group/geoadex

4

25287

import os import logging import json from nnattack.variables import auto_var, get_file_name from params import ( compare_attacks, compare_defense, #compare_nns, nn_k1_robustness, nn_k3_robustness, nn_k1_approx_robustness_figs, dt_robustness_figs, rf_robustness_figs, nn_k1_robustness_figs, nn_k3_robustness_figs, dt_robustness, rf_robustness, mlp_ap_robustness, mlp_at_robustness, lr_ap_robustness, lr_at_robustness, nn1_def, nn3_def, dt_def, rf_def, lr_def, mlp_def, ) from main import eps_accuracy logging.basicConfig(level=logging.DEBUG) DEBUG = True if os.environ.get('DEBUG', False) else False def main(): experiments = [ compare_attacks(), compare_defense(), #nn_k1_robustness_figs(), #nn_k3_robustness_figs(), #rf_robustness_figs(), #dt_robustness_figs(), dt_robustness(), rf_robustness(), nn_k3_robustness(), nn_k1_robustness(), #mlp_ap_robustness(), #mlp_at_robustness(), #lr_ap_robustness(), #lr_at_robustness(), #nn1_def(), #nn3_def(), #dt_def(), #rf_def(), #lr_def(), #mlp_def(), ] grid_params = [] for exp in experiments: exp_fn, _, grid_param, run_param = exp() if isinstance(grid_param, list): grid_params.extend(grid_param) else: grid_params.append(grid_param) if DEBUG: run_param['n_jobs'] = 1 run_param['allow_failure'] = False else: run_param['n_jobs'] = 4 run_param['allow_failure'] = True auto_var.run_grid_params(exp_fn, grid_params, **run_param) #auto_var.run_grid_params(delete_file, grid_params, n_jobs=1, # with_hook=False, allow_failure=False) #auto_var.run_grid_params(celery_run, grid_params, n_jobs=1, # allow_failure=False) #auto_var.run_grid_params(temp_fix, grid_params, n_jobs=6, # allow_failure=False, with_hook=False) def delete_file(auto_var): os.unlink(get_file_name(auto_var) + '.json') def celery_run(auto_var): run_exp.delay(auto_var.var_value) from main import set_random_seed import numpy as np from sklearn.preprocessing import OneHotEncoder, MinMaxScaler def temp_fix(auto_var): file_name = get_file_name(auto_var) print(file_name) if os.path.exists("%s.json" % file_name): with open("%s.json" % file_name, "r") as f: ret = json.load(f) if "tst_score" in ret: return else: return random_state = set_random_seed(auto_var) ord = auto_var.get_var("ord") X, y, eps_list = auto_var.get_var("dataset") idxs = np.arange(len(X)) random_state.shuffle(idxs) trnX, tstX, trny, tsty = X[idxs[:-200]], X[idxs[-200:]], y[idxs[:-200]], y[idxs[-200:]] scaler = MinMaxScaler() trnX = scaler.fit_transform(trnX) tstX = scaler.transform(tstX) lbl_enc = OneHotEncoder(categories=[np.sort(np.unique(y))], sparse=False) #lbl_enc = OneHotEncoder(sparse=False) lbl_enc.fit(trny.reshape(-1, 1)) auto_var.set_intermidiate_variable("lbl_enc", lbl_enc) results = [] auto_var.set_intermidiate_variable("trnX", trnX) auto_var.set_intermidiate_variable("trny", trny) model_name = auto_var.get_variable_value("model") attack_name = auto_var.get_variable_value("attack") if 'adv_rf' in model_name: pre_model = auto_var.get_var_with_argument('model', model_name[4:]) pre_model.fit(trnX, trny) if 'blackbox' in attack_name: auto_var.set_intermidiate_variable("model", pre_model) elif 'adv_nn' in model_name and 'blackbox' in attack_name: pre_model = auto_var.get_var_with_argument('model', model_name[4:]) pre_model.fit(trnX, trny) auto_var.set_intermidiate_variable("model", pre_model) model = auto_var.get_var("model") auto_var.set_intermidiate_variable("model", model) model.fit(trnX, trny) pred = model.predict(tstX) ori_tstX, ori_tsty = tstX, tsty # len = 200 idxs = np.where(pred == tsty)[0] random_state.shuffle(idxs) augX = None if ('adv' in model_name) or ('advPruning' in model_name) or ('robustv2' in model_name): assert hasattr(model, 'augX') auto_var.set_intermidiate_variable("trnX", model.augX) auto_var.set_intermidiate_variable("trny", model.augy) augX, augy = model.augX, model.augy ret['tst_score'] = (model.predict(ori_tstX) == ori_tsty).mean() with open("%s.json" % file_name, "w") as f: json.dump(ret, f) if __name__ == "__main__": main()

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docs/examples/lmgtfy_bot.py

AidanWelch/praw

1

196334

from urllib.parse import quote_plus import praw QUESTIONS = ["what is", "who is", "what are"] REPLY_TEMPLATE = "[Let me google that for you](https://lmgtfy.com/?q={})" def main(): reddit = praw.Reddit( user_agent="LMGTFY (by u/USERNAME)", client_id="CLIENT_ID", client_secret="CLIENT_SECRET", username="USERNAME", password="PASSWORD", ) subreddit = reddit.subreddit("AskReddit") for submission in subreddit.stream.submissions(): process_submission(submission) def process_submission(submission): # Ignore titles with more than 10 words as they probably are not simple questions. if len(submission.title.split()) > 10: return normalized_title = submission.title.lower() for question_phrase in QUESTIONS: if question_phrase in normalized_title: url_title = quote_plus(submission.title) reply_text = REPLY_TEMPLATE.format(url_title) print(f"Replying to: {submission.title}") submission.reply(reply_text) # A reply has been made so do not attempt to match other phrases. break if __name__ == "__main__": main()

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timm/models/visformer.py

merskiZ/pytorch-image-models

1

68658

<reponame>merskiZ/pytorch-image-models """ Visformer Paper: Visformer: The Vision-friendly Transformer - https://arxiv.org/abs/2104.12533 From original at https://github.com/danczs/Visformer """ from copy import deepcopy import torch import torch.nn as nn import torch.nn.functional as F from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from .helpers import build_model_with_cfg, overlay_external_default_cfg from .layers import to_2tuple, trunc_normal_, DropPath, PatchEmbed, LayerNorm2d, create_classifier from .registry import register_model __all__ = ['Visformer'] def _cfg(url='', **kwargs): return { 'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': None, 'crop_pct': .9, 'interpolation': 'bicubic', 'fixed_input_size': True, 'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD, 'first_conv': 'stem.0', 'classifier': 'head', **kwargs } default_cfgs = dict( visformer_tiny=_cfg(), visformer_small=_cfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vt3p-weights/visformer_small-839e1f5b.pth' ), ) class SpatialMlp(nn.Module): def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0., group=8, spatial_conv=False): super().__init__() out_features = out_features or in_features hidden_features = hidden_features or in_features self.in_features = in_features self.out_features = out_features self.spatial_conv = spatial_conv if self.spatial_conv: if group < 2: # net setting hidden_features = in_features * 5 // 6 else: hidden_features = in_features * 2 self.hidden_features = hidden_features self.group = group self.drop = nn.Dropout(drop) self.conv1 = nn.Conv2d(in_features, hidden_features, 1, stride=1, padding=0, bias=False) self.act1 = act_layer() if self.spatial_conv: self.conv2 = nn.Conv2d( hidden_features, hidden_features, 3, stride=1, padding=1, groups=self.group, bias=False) self.act2 = act_layer() else: self.conv2 = None self.act2 = None self.conv3 = nn.Conv2d(hidden_features, out_features, 1, stride=1, padding=0, bias=False) def forward(self, x): x = self.conv1(x) x = self.act1(x) x = self.drop(x) if self.conv2 is not None: x = self.conv2(x) x = self.act2(x) x = self.conv3(x) x = self.drop(x) return x class Attention(nn.Module): def __init__(self, dim, num_heads=8, head_dim_ratio=1., attn_drop=0., proj_drop=0.): super().__init__() self.dim = dim self.num_heads = num_heads head_dim = round(dim // num_heads * head_dim_ratio) self.head_dim = head_dim self.scale = head_dim ** -0.5 self.qkv = nn.Conv2d(dim, head_dim * num_heads * 3, 1, stride=1, padding=0, bias=False) self.attn_drop = nn.Dropout(attn_drop) self.proj = nn.Conv2d(self.head_dim * self.num_heads, dim, 1, stride=1, padding=0, bias=False) self.proj_drop = nn.Dropout(proj_drop) def forward(self, x): B, C, H, W = x.shape x = self.qkv(x).reshape(B, 3, self.num_heads, self.head_dim, -1).permute(1, 0, 2, 4, 3) q, k, v = x[0], x[1], x[2] attn = (q @ k.transpose(-2, -1)) * self.scale attn = attn.softmax(dim=-1) attn = self.attn_drop(attn) x = attn @ v x = x.permute(0, 1, 3, 2).reshape(B, -1, H, W) x = self.proj(x) x = self.proj_drop(x) return x class Block(nn.Module): def __init__(self, dim, num_heads, head_dim_ratio=1., mlp_ratio=4., drop=0., attn_drop=0., drop_path=0., act_layer=nn.GELU, norm_layer=LayerNorm2d, group=8, attn_disabled=False, spatial_conv=False): super().__init__() self.spatial_conv = spatial_conv self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity() if attn_disabled: self.norm1 = None self.attn = None else: self.norm1 = norm_layer(dim) self.attn = Attention( dim, num_heads=num_heads, head_dim_ratio=head_dim_ratio, attn_drop=attn_drop, proj_drop=drop) self.norm2 = norm_layer(dim) mlp_hidden_dim = int(dim * mlp_ratio) self.mlp = SpatialMlp( in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop, group=group, spatial_conv=spatial_conv) # new setting def forward(self, x): if self.attn is not None: x = x + self.drop_path(self.attn(self.norm1(x))) x = x + self.drop_path(self.mlp(self.norm2(x))) return x class Visformer(nn.Module): def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classes=1000, init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., drop_rate=0., attn_drop_rate=0., drop_path_rate=0., norm_layer=LayerNorm2d, attn_stage='111', pos_embed=True, spatial_conv='111', vit_stem=False, group=8, global_pool='avg', conv_init=False, embed_norm=None): super().__init__() img_size = to_2tuple(img_size) self.num_classes = num_classes self.embed_dim = embed_dim self.init_channels = init_channels self.img_size = img_size self.vit_stem = vit_stem self.conv_init = conv_init if isinstance(depth, (list, tuple)): self.stage_num1, self.stage_num2, self.stage_num3 = depth depth = sum(depth) else: self.stage_num1 = self.stage_num3 = depth // 3 self.stage_num2 = depth - self.stage_num1 - self.stage_num3 self.pos_embed = pos_embed dpr = [x.item() for x in torch.linspace(0, drop_path_rate, depth)] # stage 1 if self.vit_stem: self.stem = None self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size, in_chans=in_chans, embed_dim=embed_dim, norm_layer=embed_norm, flatten=False) img_size = [x // 16 for x in img_size] else: if self.init_channels is None: self.stem = None self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size // 2, in_chans=in_chans, embed_dim=embed_dim // 2, norm_layer=embed_norm, flatten=False) img_size = [x // 8 for x in img_size] else: self.stem = nn.Sequential( nn.Conv2d(in_chans, self.init_channels, 7, stride=2, padding=3, bias=False), nn.BatchNorm2d(self.init_channels), nn.ReLU(inplace=True) ) img_size = [x // 2 for x in img_size] self.patch_embed1 = PatchEmbed( img_size=img_size, patch_size=patch_size // 4, in_chans=self.init_channels, embed_dim=embed_dim // 2, norm_layer=embed_norm, flatten=False) img_size = [x // 4 for x in img_size] if self.pos_embed: if self.vit_stem: self.pos_embed1 = nn.Parameter(torch.zeros(1, embed_dim, *img_size)) else: self.pos_embed1 = nn.Parameter(torch.zeros(1, embed_dim//2, *img_size)) self.pos_drop = nn.Dropout(p=drop_rate) self.stage1 = nn.ModuleList([ Block( dim=embed_dim//2, num_heads=num_heads, head_dim_ratio=0.5, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[0] == '0'), spatial_conv=(spatial_conv[0] == '1') ) for i in range(self.stage_num1) ]) # stage2 if not self.vit_stem: self.patch_embed2 = PatchEmbed( img_size=img_size, patch_size=patch_size // 8, in_chans=embed_dim // 2, embed_dim=embed_dim, norm_layer=embed_norm, flatten=False) img_size = [x // 2 for x in img_size] if self.pos_embed: self.pos_embed2 = nn.Parameter(torch.zeros(1, embed_dim, *img_size)) self.stage2 = nn.ModuleList([ Block( dim=embed_dim, num_heads=num_heads, head_dim_ratio=1.0, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[1] == '0'), spatial_conv=(spatial_conv[1] == '1') ) for i in range(self.stage_num1, self.stage_num1+self.stage_num2) ]) # stage 3 if not self.vit_stem: self.patch_embed3 = PatchEmbed( img_size=img_size, patch_size=patch_size // 8, in_chans=embed_dim, embed_dim=embed_dim * 2, norm_layer=embed_norm, flatten=False) img_size = [x // 2 for x in img_size] if self.pos_embed: self.pos_embed3 = nn.Parameter(torch.zeros(1, embed_dim*2, *img_size)) self.stage3 = nn.ModuleList([ Block( dim=embed_dim*2, num_heads=num_heads, head_dim_ratio=1.0, mlp_ratio=mlp_ratio, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[i], norm_layer=norm_layer, group=group, attn_disabled=(attn_stage[2] == '0'), spatial_conv=(spatial_conv[2] == '1') ) for i in range(self.stage_num1+self.stage_num2, depth) ]) # head self.num_features = embed_dim if self.vit_stem else embed_dim * 2 self.norm = norm_layer(self.num_features) self.global_pool, self.head = create_classifier(self.num_features, self.num_classes, pool_type=global_pool) self.head = nn.Linear(self.num_features, num_classes) # weights init if self.pos_embed: trunc_normal_(self.pos_embed1, std=0.02) if not self.vit_stem: trunc_normal_(self.pos_embed2, std=0.02) trunc_normal_(self.pos_embed3, std=0.02) self.apply(self._init_weights) def _init_weights(self, m): if isinstance(m, nn.Linear): trunc_normal_(m.weight, std=0.02) if m.bias is not None: nn.init.constant_(m.bias, 0) elif isinstance(m, nn.LayerNorm): nn.init.constant_(m.bias, 0) nn.init.constant_(m.weight, 1.0) elif isinstance(m, nn.BatchNorm2d): nn.init.constant_(m.bias, 0) nn.init.constant_(m.weight, 1.0) elif isinstance(m, nn.Conv2d): if self.conv_init: nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu') else: trunc_normal_(m.weight, std=0.02) if m.bias is not None: nn.init.constant_(m.bias, 0.) def get_classifier(self): return self.head def reset_classifier(self, num_classes, global_pool='avg'): self.num_classes = num_classes self.global_pool, self.head = create_classifier(self.num_features, self.num_classes, pool_type=global_pool) def forward_features(self, x): if self.stem is not None: x = self.stem(x) # stage 1 x = self.patch_embed1(x) if self.pos_embed: x = x + self.pos_embed1 x = self.pos_drop(x) for b in self.stage1: x = b(x) # stage 2 if not self.vit_stem: x = self.patch_embed2(x) if self.pos_embed: x = x + self.pos_embed2 x = self.pos_drop(x) for b in self.stage2: x = b(x) # stage3 if not self.vit_stem: x = self.patch_embed3(x) if self.pos_embed: x = x + self.pos_embed3 x = self.pos_drop(x) for b in self.stage3: x = b(x) x = self.norm(x) return x def forward(self, x): x = self.forward_features(x) x = self.global_pool(x) x = self.head(x) return x def _create_visformer(variant, pretrained=False, default_cfg=None, **kwargs): if kwargs.get('features_only', None): raise RuntimeError('features_only not implemented for Vision Transformer models.') model = build_model_with_cfg( Visformer, variant, pretrained, default_cfg=default_cfgs[variant], **kwargs) return model @register_model def visformer_tiny(pretrained=False, **kwargs): model_cfg = dict( init_channels=16, embed_dim=192, depth=(7, 4, 4), num_heads=3, mlp_ratio=4., group=8, attn_stage='011', spatial_conv='100', norm_layer=nn.BatchNorm2d, conv_init=True, embed_norm=nn.BatchNorm2d, **kwargs) model = _create_visformer('visformer_tiny', pretrained=pretrained, **model_cfg) return model @register_model def visformer_small(pretrained=False, **kwargs): model_cfg = dict( init_channels=32, embed_dim=384, depth=(7, 4, 4), num_heads=6, mlp_ratio=4., group=8, attn_stage='011', spatial_conv='100', norm_layer=nn.BatchNorm2d, conv_init=True, embed_norm=nn.BatchNorm2d, **kwargs) model = _create_visformer('visformer_small', pretrained=pretrained, **model_cfg) return model # @register_model # def visformer_net1(pretrained=False, **kwargs): # model = Visformer( # init_channels=None, embed_dim=384, depth=(0, 12, 0), num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=True, conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net2(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=(0, 12, 0), num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net3(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net4(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., attn_stage='111', # spatial_conv='000', vit_stem=False, conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net5(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., group=1, attn_stage='111', # spatial_conv='111', vit_stem=False, conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net6(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4., group=1, attn_stage='111', # pos_embed=False, spatial_conv='111', conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model # # # @register_model # def visformer_net7(pretrained=False, **kwargs): # model = Visformer( # init_channels=32, embed_dim=384, depth=(6, 7, 7), num_heads=6, group=1, attn_stage='000', # pos_embed=False, spatial_conv='111', conv_init=True, **kwargs) # model.default_cfg = _cfg() # return model

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texar/losses/pg_losses.py

Holmeswww/Text_Infilling

25

68212

# """ Various loss functions for policy gradients. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf from texar.losses.losses_utils import mask_and_reduce from texar.utils.shapes import get_rank # pylint: disable=too-many-arguments, protected-access __all__ = [ "pg_loss_with_logits", "pg_loss_with_log_probs" ] def pg_loss_with_logits(actions, logits, advantages, rank=None, batched=False, sequence_length=None, average_across_batch=True, average_across_timesteps=False, average_across_remaining=False, sum_over_batch=False, sum_over_timesteps=True, sum_over_remaining=True, time_major=False): """Policy gradient loss with logits. Used for discrete actions. pg_loss = reduce( advantages * -log_prob( actions ) ), where `advantages` and `actions` will not bprop gradients. All arguments except :attr:`logits` and :attr:`actions` are the same as :func:`pg_loss_with_log_probs`. Args: actions: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and of dtype `int32` or `int64`. The rank of the Tensor is specified with :attr:`rank`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. logits: Unscaled log probabilities of shape `[(batch_size,) max_time, d_3, ..., d_{rank+1}]` and dtype `float32` or `float64`. The batch and time dimensions are exchanged if :attr:`time_major` is `True`. advantages: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and dtype `float32` or `float64`. The batch and time dimensions are exchanged if :attr:`time_major` is `True`. rank (int, optional): The rank of :attr:`actions`. If `None` (default), rank is automatically inferred from :attr:`actions` or :attr:`advantages`. If the inferred rank is `None`, :attr:`rank` is set to 1 if :attr:`batched` is `False`, and :attr:`rank`=2 if :attr:`batched` is `True`. batched (bool): `True` if the inputs are batched. sequence_length (optional): A Tensor of shape `[batch_size]`. Time steps beyond the respective sequence lengths will have zero losses. Used if :attr:`batched` is `True`. average_across_timesteps (bool): If set, average the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. average_across_batch (bool): If set, average the loss across the batch dimension. Must not set :attr:`average_across_batch`' and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. average_across_remaining (bool): If set, average the sequence across the remaining dimensions. Must not set :attr:`average_across_remaining`' and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. sum_over_timesteps (bool): If set, sum the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. sum_over_batch (bool): If set, sum the loss across the batch dimension. Must not set :attr:`average_across_batch` and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. sum_over_remaining (bool): If set, sum the loss across the remaining dimension. Must not set :attr:`average_across_remaining` and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. time_major (bool): The shape format of the inputs. If `True`, :attr:`logits`, :attr:`actions` and :attr:`advantages` must have shape `[max_time, batch_size, ...]`. If `False` (default), they must have shape `[batch_size, max_time, ...]`. Ignored if :attr:`batched` is `False`. Returns: A Tensor containing the loss to minimize, whose rank depends on the reduce arguments. For example, the batch dimension is reduced if either :attr:`average_across_batch` or :attr:`sum_over_batch` is `True`, which makes the rank of output tensor decrease by 1. """ actions = tf.stop_gradient(actions) neg_log_probs = tf.nn.sparse_softmax_cross_entropy_with_logits( logits=logits, labels=actions) return pg_loss_with_log_probs( log_probs=-neg_log_probs, advantages=advantages, rank=rank, batched=batched, sequence_length=sequence_length, average_across_batch=average_across_batch, average_across_timesteps=average_across_timesteps, average_across_remaining=average_across_remaining, sum_over_batch=sum_over_batch, sum_over_timesteps=sum_over_timesteps, sum_over_remaining=sum_over_remaining, time_major=time_major) def pg_loss_with_log_probs(log_probs, advantages, rank=None, batched=False, sequence_length=None, average_across_batch=True, average_across_timesteps=False, average_across_remaining=False, sum_over_batch=False, sum_over_timesteps=True, sum_over_remaining=True, time_major=False): """Policy gradient loss with log probs of actions. pg_loss = reduce( advantages * -log_probs ), where `advantages` will not bprop gradients. All arguments except :attr:`log_probs` are the same as :func:`pg_loss_with_logits`. Args: log_probs: Log probabilities of shape `[(batch_size,) max_time, ..., d_rank]` and dtype `float32` or `float64`. The rank of the Tensor is specified with :attr:`rank`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. advantages: Tensor of shape `[(batch_size,) max_time, d_3, ..., d_rank]` and dtype `float32` or `float64`. The batch dimension exists only if :attr:`batched` is `True`. The batch and time dimensions are exchanged, i.e., `[max_time, batch_size, ...]` if :attr:`time_major` is `True`. rank (int, optional): The rank of :attr:`log_probs`. If `None` (default), rank is automatically inferred from :attr:`log_probs` or :attr:`advantages`. If the inferred rank is `None`, :attr:`rank` is set to 1 if :attr:`batched``==False`, and :attr:`rank`=2 if :attr:`batched``==True`. batched (bool): `True` if the inputs are batched. sequence_length (optional): A Tensor of shape `[batch_size]`. Time steps beyond the respective sequence lengths will have zero losses. Used if :attr:`batched` is `True`. average_across_timesteps (bool): If set, average the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. average_across_batch (bool): If set, average the loss across the batch dimension. Must not set :attr:`average_across_batch`' and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. average_across_remaining (bool): If set, average the sequence across the remaining dimensions. Must not set :attr:`average_across_remaining`' and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. sum_over_timesteps (bool): If set, sum the loss across the time dimension. Must not set :attr:`average_across_timesteps` and :attr:`sum_over_timesteps` at the same time. sum_over_batch (bool): If set, sum the loss across the batch dimension. Must not set :attr:`average_across_batch` and :attr:`sum_over_batch` at the same time. Ignored if :attr:`batched` is `False`. sum_over_remaining (bool): If set, sum the loss across the remaining dimension. Must not set :attr:`average_across_remaining` and :attr:`sum_over_remaining` at the same time. Ignored if no more dimensions other than the batch and time dimensions. time_major (bool): The shape format of the inputs. If `True`, :attr:`log_probs` and :attr:`advantages` must have shape `[max_time, batch_size, ...]`. If `False` (default), they must have shape `[batch_size, max_time, ...]`. Ignored if :attr:`batched` is `False`. Returns: A Tensor containing the loss to minimize, whose rank depends on the reduce arguments. For example, the batch dimension is reduced if either :attr:`average_across_batch` or :attr:`sum_over_batch` is `True`, which makes the rank of output tensor decrease by 1. """ advantages = tf.stop_gradient(advantages) losses = -log_probs * advantages if rank is None: rank = get_rank(log_probs) or get_rank(advantages) if rank is None: rank = 2 if batched else 1 if batched: losses = mask_and_reduce( losses, sequence_length, rank=rank, average_across_batch=average_across_batch, average_across_timesteps=average_across_timesteps, average_across_remaining=average_across_remaining, sum_over_batch=sum_over_batch, sum_over_timesteps=sum_over_timesteps, sum_over_remaining=sum_over_remaining, time_major=time_major) elif rank > 1: if average_across_remaining and sum_over_remaining: raise ValueError("Only one of `average_across_remaining` and " "`sum_over_remaining` can be set.") if average_across_remaining: losses = tf.reduce_mean(losses, axis=range(1, rank)) elif sum_over_remaining: losses = tf.reduce_sum(losses, axis=range(1, rank)) if not batched: if average_across_timesteps and sum_over_timesteps: raise ValueError("Only one of `average_across_timesteps` and " "`sum_over_timesteps` can be set.") if average_across_timesteps: losses = tf.reduce_mean(losses) elif sum_over_timesteps: losses = tf.reduce_mean(losses) return losses

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pythonTeste/aula14.py

VanessaCML/python

0

127127

<gh_stars>0 n = 1 par = impar = 0 while n != 0: n = int(input('Digite um número: ')) if n != 0: if n % 2 == 0: par += 1 else: impar += 1 print(f'Tem {par} número(s) par(es) e {impar} número(s) ímpar(es).')

[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 29876, 353, 29871, 29896, 13, 862, 353, 527, 862, 353, 29871, 29900, 13, 8000, 302, 2804, 29871, 29900, 29901, 13, 1678, 302, 353, 938, 29898, 2080, 877, 14991, 568, 1922, 13831, 29901, 525, 876, 13, 1678, 565, 302, 2804, 29871, 29900, 29901, 13, 4706, 565, 302, 1273, 29871, 29906, 1275, 29871, 29900, 29901, 13, 9651, 610, 4619, 29871, 29896, 13, 4706, 1683, 29901, 13, 9651, 527, 862, 4619, 29871, 29896, 13, 2158, 29898, 29888, 29915, 5776, 426, 862, 29913, 13831, 29898, 29879, 29897, 610, 29898, 267, 29897, 321, 426, 326, 862, 29913, 13831, 29898, 29879, 29897, 29871, 5487, 862, 29898, 267, 467, 1495, 13, 2 ]

tests/unit/plugins/modules/test_panos_op.py

mrichardson03/mrichardson03.panos

4

1603788

# Copyright 2020 Palo Alto Networks, Inc # # Permission to use, copy, modify, and/or distribute this software for any # purpose with or without fee is hereby granted, provided that the above # copyright notice and this permission notice appear in all copies. # # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES # WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR # ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES # WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN # ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF # OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. from __future__ import absolute_import, division, print_function __metaclass__ = type import pytest from ansible_collections.mrichardson03.panos.plugins.modules import panos_op from .common.utils import ModuleTestCase class TestPanosOp(ModuleTestCase): module = panos_op @pytest.mark.parametrize( "command,is_xml,changed", [ ("show system info", False, False), ("<show><system><info></info></system></show>", True, False), ("request reboot system", False, True), ], ) def test_safe_commands(self, command, is_xml, changed, connection_mock): connection_mock.op.return_value = "<response><result>foo</result></response>" result = self._run_module({"cmd": command, "cmd_is_xml": is_xml}) assert result["changed"] == changed

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tests/settings.py

sunlightlabs/waterfall

1

81124

<reponame>sunlightlabs/waterfall import os BASE_DIR = os.path.dirname(os.path.dirname(__file__)) DEBUG = True TEMPLATE_DEBUG = True LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True INSTALLED_APPS = ( 'tests', ) DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'test', 'USER': 'test', 'PASSWORD': '<PASSWORD>', 'HOST': 'localhost', }, 'test': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'test', 'USER': 'test', 'PASSWORD': '<PASSWORD>', 'HOST': 'localhost', } } SECRET_KEY = "test"

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models/Update.py

sonhamin/parallel_fedlearning

0

1606334

<reponame>sonhamin/parallel_fedlearning<filename>models/Update.py #!/usr/bin/env python # -*- coding: utf-8 -*- # Python version: 3.6 import torch from torch import nn, autograd from torch.utils.data import DataLoader, Dataset import numpy as np import random #from sklearn import metrics from os import fork from threading import Lock class DatasetSplit(Dataset): def __init__(self, dataset, idxs): self.dataset = dataset self.idxs = list(idxs) def __len__(self): return len(self.idxs) def __getitem__(self, item): image, label = self.dataset[self.idxs[item]] return image, label class LocalUpdate(object): def __init__(self, args, user_num, loss_func=nn.CrossEntropyLoss(), dataset=None, idxs=None): self.args = args self.user_num = user_num self.loss_func = loss_func self.selected_clients = [] self.ldr_train = DataLoader(DatasetSplit(dataset, idxs), batch_size=self.args.local_bs, shuffle=True) def train(self, net): net2 = net.to(self.args.device) net2.train() optimizer = torch.optim.SGD(net2.parameters(), lr=self.args.lr, momentum=self.args.momentum) loss22 = self.loss_func epoch_loss = [] for iter in range(self.args.local_ep): batch_loss = [] for batch_idx, (images, labels) in enumerate(self.ldr_train): images, labels = images.to(self.args.device), labels.to(self.args.device) net2.zero_grad() log_probs = net2(images) loss = loss22(log_probs, labels) loss.backward() optimizer.step() if self.args.verbose and batch_idx % 10 == 0: print('Local user {} -- Update Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format( self.user_num, iter, batch_idx * len(images), len(self.ldr_train.dataset), 100. * batch_idx / len(self.ldr_train), loss.item())) batch_loss.append(loss.item()) epoch_loss.append(sum(batch_loss)/len(batch_loss)) return net.state_dict(), sum(epoch_loss) / len(epoch_loss)

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echoclient.py

JosunLP/OSZ_chat_ITS

1

70903

import socket import sys import threading from datetime import datetime from helper import MessageParser from helper import const from model import Message HOST = const.HOST PORT = const.PORT CURSOR_UP_ONE = '\x1b[1A' ERASE_LINE = '\x1b[2K' def message_listener(s: socket): try: while True: data = s.recv(1024) if not data: break m: Message.Message = MessageParser.byte_array_to_message(data) print(m.msg) except (ConnectionAbortedError, ConnectionResetError): print("Connection with server closed!") print("Welcome to ChatZ") UNAME = input("Whats your name? :") try: with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((HOST, PORT)) thread = threading.Thread(target=message_listener, args=[s]) thread.start() m = Message.Message(datetime.now().strftime(const.TIME_FILTER), "LOGIN", UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) while True: string = input("$~ ") sys.stdout.write(CURSOR_UP_ONE) sys.stdout.write(ERASE_LINE) if "!logout" in string: m = Message.Message(datetime.now().strftime(const.TIME_FILTER), "LOGOUT", UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) break m = Message.Message(datetime.now().strftime(const.TIME_FILTER), string, UNAME) send = MessageParser.message_to_byte_array(m) s.send(send) except (ConnectionAbortedError, ConnectionResetError): print("Connection with server closed!")

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jp.atcoder/abc123/abc123_d/8669197.py

kagemeka/atcoder-submissions

1

90679

import sys import numpy as np INF = 10 ** 18 def main(): x, y, z, K = map(int, sys.stdin.readline().split()) abc = np.array(sys.stdin.read().split(), dtype=np.int64) a = np.append(abc[:x], INF) b = np.append(abc[x:x + y], INF) c = np.append(abc[x + y:x + y+ z], INF) a = np.sort(a)[::-1] b = np.sort(b)[::-1] c = np.sort(c)[::-1] res = [] for i in range(1, min(K, x) + 1): for j in range(1, min(y, K // i) + 1): for k in range(1, min(z, K // (i * j)) + 1): res.append(a[i] + b[j] + c[k]) res = sorted(res, reverse=True)[:K] print('\n'.join(map(str, res))) if __name__ == "__main__": main()

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example.py

vins9100/code-refiney-bq

0

1615994

def add(a, b): return a+b def substract(a,b): return a*b def divide(a,b): return a/b

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tests/unit/i18n/test_init.py

matt-land/warehouse

2

80120

# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pretend from warehouse import i18n def test_sets_locale(monkeypatch): locale_obj = pretend.stub() locale_cls = pretend.stub( parse=pretend.call_recorder(lambda l: locale_obj), ) monkeypatch.setattr(i18n, "Locale", locale_cls) request = pretend.stub(locale_name=pretend.stub()) assert i18n._locale(request) is locale_obj assert locale_cls.parse.calls == [pretend.call(request.locale_name)] def test_includeme(): config_settings = {} config = pretend.stub( add_request_method=pretend.call_recorder(lambda f, name, reify: None), get_settings=lambda: config_settings, ) i18n.includeme(config) assert config.add_request_method.calls == [ pretend.call(i18n._locale, name="locale", reify=True), ] assert config_settings == { "jinja2.filters": { "format_date": "warehouse.i18n.filters:format_date", "format_datetime": "warehouse.i18n.filters:format_datetime", "format_rfc822_datetime": "warehouse.i18n.filters:format_rfc822_datetime", "format_number": "warehouse.i18n.filters:format_number", }, }

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fair/forcing/ozone_tr.py

znicholls/FAIR

1

1377

<reponame>znicholls/FAIR<filename>fair/forcing/ozone_tr.py from __future__ import division import numpy as np from ..constants import molwt def regress(emissions, beta=np.array([2.8249e-4, 1.0695e-4, -9.3604e-4, 99.7831e-4])): """Calculates tropospheric ozone forcing from precursor emissions. Inputs: (nt x 40) emissions array Keywords: beta: 4-element array of regression coefficients of precursor radiative efficiency, W m-2 (Mt yr-1)-1. order is [CH4, CO, NMVOC, NOx] Outputs: tropospheric ozone ERF time series. """ if emissions.ndim==2: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[:,[3, 6, 7, 8]].T else: em_CH4, em_CO, em_NMVOC, em_NOx = emissions[[3, 6, 7, 8]] F_CH4 = beta[0] * em_CH4 F_CO = beta[1] * em_CO F_NMVOC = beta[2] * em_NMVOC F_NOx = beta[3] * em_NOx F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def cmip6_stevenson(emissions, C_CH4, T=0, feedback=False, PI=np.array([722, 170, 10, 4.29]), beta=np.array([1.77871043e-04, 5.80173377e-05, 2.09151270e-03, 1.94458719e-04])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions beta: : coefficients of how CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions affect forcing Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)*C_CH4 year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): F_CH4[i] = beta[0] * (C_CH4[i]-PI[0]) F_CO[i] = beta[1] * (em_CO[i]-PI[1]) F_NMVOC[i] = beta[2] * (em_NMVOC[i]-PI[2]) F_NOx[i] = beta[3] * (em_NOx[i]-PI[3]) # Include the effect of climate feedback? We fit a curve to the 2000, 2030 # and 2100 best estimates of feedback based on middle-of-the-road # temperature projections. def temperature_feedback(T, a=0.03189267, b=1.34966941, c=-0.03214807): if T<=0: return 0 else: return a*np.exp(-b*T)+c if feedback: F = F_CH4 + F_CO + F_NMVOC + F_NOx + temperature_feedback(T) else: F = F_CH4 + F_CO + F_NMVOC + F_NOx return F def stevenson(emissions, C_CH4, T=0, feedback=False, fix_pre1850_RCP=False, PI=np.array([722, 170, 10, 4.29])): """Calculates tropospheric ozone forcing from precursor emissions based on Stevenson et al, 2013 10.5194/acp-13-3063-2013 Inputs: emissions: (nt x 40) numpy array C_CH4 : (nt) numpy array of methane concentrations, ppb Keywords: T : change in surface temperature since pre-industrial feedback : True or False - include temperature feedback on ozone forcing? fix_pre1850_RCP: Use different relationship for 1750/65 to 1850 based on anthropogenic emissions from Skeie et al (2011) for 1750 (atmos-chem-phys.net/11/11827/2011) PI: : 4-element array of pre-industrial CH4 concentrations, CO emissions, NMVOC emissions and NOx emissions Outputs: tropospheric ozone ERF time series. """ # expand to 2D/1D if not already if emissions.ndim == 1: nspec = len(emissions) emissions = emissions.reshape((1, nspec)) if np.isscalar(C_CH4): C_CH4 = np.ones(1)*C_CH4 # numbers in denominator are 2000-1750 concs or emissions used in # Stevenson and traced back to Lamarque et al 2010 for 2000 # https://www.atmos-chem-phys.net/10/7017/2010/ year, em_CO, em_NMVOC, em_NOx = emissions[:,[0, 6, 7, 8]].T nt = len(year) F_CH4, F_CO, F_NMVOC, F_NOx = np.zeros((4,nt)) for i in range(nt): if year[i]>=1850 or fix_pre1850_RCP==False: F_CH4[i] = 0.166/960 * (C_CH4[i]-PI[0]) F_CO[i] = 0.058/681.8 * (em_CO[i]-PI[1]) F_NMVOC[i] = 0.035/155.84 * (em_NMVOC[i]-PI[2]) F_NOx[i] = 0.119/61.16 * (em_NOx[i] * molwt.NO / molwt.N - PI[3]) # The RCP scenarios give a negative forcing prior to ~1780. This is # because the anthropogenic emissions are given to be zero in RCPs but # not zero in the Skeie numbers which are used here. This can be fixed # to give a more linear behaviour. else: F_CH4[i] = 0.166/960 * (C_CH4[i]-722) F_CO[i] = 0.058/681.8 * 215.59 * em_CO[i] / 385.59 F_NMVOC[i] = 0.035/155.84 * 51.97 * em_NMVOC[i] / 61.97 F_NOx[i] = 0.119/61.16 * 7.31 * (em_NOx[i] * molwt.NO / molwt.N) / 11.6 # Include the effect of climate feedback? We fit a curve to the 2000, 2030 # and 2100 best estimates of feedback based on middle-of-the-road # temperature projections. def temperature_feedback(T, a=0.03189267, b=1.34966941, c=-0.03214807): if T<=0: return 0 else: return a*np.exp(-b*T)+c if feedback: F = F_CH4 + F_CO + F_NMVOC + F_NOx + temperature_feedback(T) else: F = F_CH4 + F_CO + F_NMVOC + F_NOx return F

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unit_tests/fields/Field.py

jaredlunde/cargo-orm

3

82206

#!/usr/bin/python3 -S # -*- coding: utf-8 -*- import unittest import pickle import copy from cargo import aliased, Model from cargo.fields import Field from unit_tests import configure class Tc(object): def __init__(self, field): self.field = field class FieldModel(Model): field = Field() class TestField(unittest.TestCase): orm = FieldModel() def setUp(self): self.orm.clear() @property def base(self): return self.orm.field @property def base_array(self): return getattr(self.orm, 'array_' + self.base.field_name) def test_init(self, *args, **kwargs): base = self.base.__class__() self.assertEqual(base.value, base.empty) base = self.base.__class__(primary=True) self.assertEqual(base.primary, True) base = self.base.__class__(unique=True) self.assertEqual(base.unique, True) base = self.base.__class__(index=True) self.assertEqual(base.index, True) base = self.base.__class__(default='field') self.assertEqual(base.default, 'field') base = self.base.__class__(not_null=True) self.assertEqual(base.not_null, True) base = self.base.__class__(validator=Tc) self.assertIsInstance(base.validator, Tc) def test_slots(self): self.assertFalse(hasattr(self.base, '__dict__')) def test_copy(self): fielda = self.base fieldb = self.base.copy() self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if k == 'validator': self.assertEqual(fielda.validator.__class__, fieldb.validator.__class__) else: self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) self.assertEqual(fielda.table, fieldb.table) fielda = self.base fieldb = copy.copy(self.base) self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if k == 'validator': self.assertEqual(fielda.validator.__class__, fieldb.validator.__class__) else: self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) self.assertEqual(fielda.table, fieldb.table) def test_deepcopy(self): fielda = self.base fieldb = copy.deepcopy(self.base) self.assertIsNot(fielda, fieldb) for k in list(fielda.__slots__): if isinstance( getattr(fielda, k), (str, list, tuple, dict, int, float)): self.assertEqual(getattr(fielda, k), getattr(fieldb, k)) else: self.assertTrue( getattr(fielda, k).__class__, getattr(fieldb, k).__class__) self.assertEqual(fielda.table, fieldb.table) def test_pickle(self): b = pickle.loads(pickle.dumps(self.base)) for k in list(self.base.__slots__): if isinstance( getattr(self.base, k), (str, list, tuple, dict, int, float)): self.assertEqual(getattr(self.base, k), getattr(b, k)) else: self.assertTrue( getattr(self.base, k).__class__ == getattr(b, k).__class__) def test_set_alias(self): field = self.base.copy() field.table = 'foo' field.field_name = 'bar' field.set_alias(table="foo_b") self.assertEqual(str(aliased(field)), "foo_b.bar") field.set_alias(name="foo_b") self.assertEqual(str(aliased(field)), "foo_b") field.set_alias("foo_b", "bar_b") self.assertEqual(str(aliased(field)), "foo_b.bar_b") def test___call__(self): self.base('foobar') self.assertEqual(self.base.value, 'foobar') self.assertEqual(self.base(), 'foobar') self.assertEqual(self.base(None), None) if __name__ == '__main__': # Unit test configure.run_tests(TestField)

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Python/Tests/TestData/DebuggerProject/EnumChildTestV3.py

nanshuiyu/pytools

0

179959

d1 = {42: 100} d2 = {'abc': 'fob'} d3 = {1e1000: d1} s = set([frozenset([2,3,4])]) class C(object): abc = 42 def f(self): pass cinst = C() class C2(object): abc = 42 def __init__(self): self.oar = 100 self.self = self def __repr__(self): return 'myrepr' def __hex__(self): return 'myhex' def f(self): pass c2inst = C2() class C3(object): def __init__(self): self.abc = 42 self._contents = [1,2] def __iter__(self): return iter(self._contents) def __len__(self): return len(self._contents) def __getitem__(self, index): return self._contents[index] c3inst = C3() l = [1, 2, ] i = 3 pass

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CursoGame/game.py

eStev4m/Game_in_Python

0

165192

<gh_stars>0 import pygame from pygame.locals import * from sys import exit pygame.init() largura = 640 altura = 480 x = largura / 2 y = 0 tela = pygame.display.set_mode((largura, altura)) pygame.display.set_caption('Curso de Game no Python') relogio = pygame.time.Clock() while True: relogio.tick(30) tela.fill((0,0,0)) for event in pygame.event.get(): if event.type == QUIT: pygame.quit() exit() pygame.draw.rect(tela, (255, 0, 0), (x, y, 40, 50)) if y >= altura: y = 0 y += 5 # pygame.draw.circle(tela, (0,0,255), (300, 260), 40) # pygame.draw.line(tela, (255,255,0), (390,0), (390,600), 5) pygame.display.update()

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DSA_Cracker/Array/Python/Q6.py

OPENSOURCE-CORPORATION/Coding-Problems

1

1604991

# Problem Link : Check Sheet link below # Excel-Sheet Link : https://drive.google.com/file/d/1L3EOLDMs-Fx2XoKclkCg1OVymDGh6psP/view?usp=sharing # Youtube Video Link : # Q> Find Union and Intersections of 2 Arrays # Fundamental / Naive Approach def Solution_1(Array_1, Array_2): # Time: O(m*n), Space: O(0) Union = Array_1 Intersection = [] for i in range(len(Array_2)): if(Array_2[i] in Union): Intersection.append(Array_2[i]) else: Union.append(Array_2[i]) return Union, Intersection # Time : O((m(log(m) + n(log(n)) + (m + n)) ,Space : O(1) def Solution_2(Array_1, Array_2): Array_1.sort() Array_2.sort() # Array_1 will be shorter if(len(Array_1) > len(Array_2)): Array_1, Array_2 = Array_2, Array_1 i = 0 j = 0 Union = [] Intersection = [] while(i <= len(Array_1)-1 and j <= len(Array_2)-1): if(Array_1[i] > Array_2[j]): Union.append(Array_2[j]) j += 1 elif(Array_1[i] < Array_2[j]): Union.append(Array_1[i]) i += 1 else: Union.append(Array_1[i]) Intersection.append(Array_1[i]) i += 1 j += 1 # temp = len(Array_1) - 3 # This is wrong do not do like at and repeat the mistake i did # for i in range(len(Array_2) - len(Array_1) + 3): # Union.append(Array_2[temp]) # # print(Array_2[temp]) # temp += 1 while(j < len(Array_2)): Union.append(Array_2[j]) j += 1 return Union, Intersection Array_1 = [2, 1, 3, 4, 5, 6, 7] Array_2 = [2, 5, 4, 9, 8, 7, 10, 11, 13, 45] UNION, INTERSECTION = Solution_1(Array_1, Array_2) UNION.sort() print(f"The union of 2 Arrays is : {UNION}") print(f"The intersections of 2 Arrays is : {INTERSECTION}") # This Code is Written by <NAME> aka The "Dead_Coder"

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rest_framework_auth0/models.py

robindebois/djangorestframework-auth0

107

25111

# Just to keep things like ./manage.py test happy from django.contrib.auth.models import AbstractUser # class Group(models.Model): # """ # Groups are a generic way of categorizing users to apply permissions, or # some other label, to those users. A user can belong to any number of # groups. # A user in a group automatically has all the permissions granted to that # group. For example, if the group Site editors has the permission # can_edit_home_page, any user in that group will have that permission. # Beyond permissions, groups are a convenient way to categorize users to # apply some label, or extended functionality, to them. For example, you # could create a group 'Special users', and you could write code that would # do special things to those users -- such as giving them access to a # members-only portion of your site, or sending them members-only email # messages. # """ # name = models.CharField(_('name'), max_length=80, unique=True) # permissions = models.ManyToManyField( # Permission, # verbose_name=_('permissions'), # blank=True, # ) # # objects = GroupManager() # # class Meta: # verbose_name = _('group') # verbose_name_plural = _('groups') # # def __str__(self): # return self.name # # def natural_key(self): # return (self.name,) # class User(AbstractUser): # """ # Users within the Django authentication system are represented by this # model. # Username, password and email are required. Other fields are optional. # """ # class Meta(AbstractUser.Meta): # swappable = 'AUTH_USER_MODEL'

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RDS/circle3_central_services/research_manager/src/api/User/__init__.py

Sciebo-RDS/Sciebo-RDS

10

17978

from .user import *

[ 1, 515, 869, 1792, 1053, 334, 29871, 2 ]

tests/integration/cartography/intel/azure/test_compute.py

Cloudanix/cartography

0

109094

from cartography.intel.azure import compute from tests.data.azure.compute import DESCRIBE_DISKS from tests.data.azure.compute import DESCRIBE_SNAPSHOTS from tests.data.azure.compute import DESCRIBE_VM_DATA_DISKS from tests.data.azure.compute import DESCRIBE_VMAVAILABLESIZES from tests.data.azure.compute import DESCRIBE_VMEXTENSIONS from tests.data.azure.compute import DESCRIBE_VMS from tests.data.azure.compute import DESCRIBE_VMSCALESETEXTENSIONS from tests.data.azure.compute import DESCRIBE_VMSCALESETS TEST_SUBSCRIPTION_ID = '00-00-00-00' TEST_RESOURCE_GROUP = 'TestRG' TEST_UPDATE_TAG = 123456789 def test_load_vms(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachine) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vms_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureVirtualMachine) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_data_disks(neo4j_session): compute.load_vm_data_disks( neo4j_session, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", DESCRIBE_VM_DATA_DISKS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", } nodes = neo4j_session.run( """ MATCH (r:AzureDataDisk) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_data_disk_relationships(neo4j_session): # Create Test Virtual Machines compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, [DESCRIBE_VMS[0]], TEST_UPDATE_TAG, ) compute.load_vm_data_disks( neo4j_session, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", DESCRIBE_VM_DATA_DISKS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:ATTACHED_TO]->(n2:AzureDataDisk) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_disks(neo4j_session): compute.load_disks( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_DISKS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", } nodes = neo4j_session.run( """ MATCH (r:AzureDisk) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_disk_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_disks( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_DISKS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd0", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/disks/dd1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureDisk) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_snapshots(neo4j_session): compute.load_snapshots( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_SNAPSHOTS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss0", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss1", } nodes = neo4j_session.run( """ MATCH (r:AzureSnapshot) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_snapshot_relationships(neo4j_session): # Create Test Azure Subscription neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_snapshots( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_SNAPSHOTS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss0", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/snapshots/ss1", ), } # Fetch relationships result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureSnapshot) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_extensions(neo4j_session): compute.load_vm_extensions( neo4j_session, DESCRIBE_VMEXTENSIONS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM/extensions/extensions1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM1/extensions/extensions2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineExtension) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_extensions_relationships(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) compute.load_vm_extensions( neo4j_session, DESCRIBE_VMEXTENSIONS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM/extensions/extensions1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachines/TestVM1/extensions/extensions2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:CONTAIN]->(n2:AzureVirtualMachineExtension) RETURN n1.id, n2.id; """, ) actual = {(r['n1.id'], r['n2.id']) for r in result} assert actual == expected def test_load_vm_available_sizes(neo4j_session): compute.load_vm_available_sizes( neo4j_session, DESCRIBE_VMAVAILABLESIZES, TEST_UPDATE_TAG, ) expected_nodes = { "size1", "size2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineAvailableSize) RETURN r.name; """, ) actual_nodes = {n['r.name'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_available_sizes_relationships(neo4j_session): compute.load_vms( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMS, TEST_UPDATE_TAG, ) compute.load_vm_available_sizes( neo4j_session, DESCRIBE_VMAVAILABLESIZES, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM", "size1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/virtualMachines/TestVM1", "size2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachine)-[:CONTAIN]->(n2:AzureVirtualMachineAvailableSize) RETURN n1.id, n2.name; """, ) actual = {(r['n1.id'], r['n2.name']) for r in result} assert actual == expected def test_load_vm_scale_sets(neo4j_session): compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineScaleSet) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vms_scale_sets_relationships(neo4j_session): neo4j_session.run( """ MERGE (as:AzureSubscription{id: {subscription_id}}) ON CREATE SET as.firstseen = timestamp() SET as.lastupdated = {update_tag} """, subscription_id=TEST_SUBSCRIPTION_ID, update_tag=TEST_UPDATE_TAG, ) compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) expected = { ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", ), ( TEST_SUBSCRIPTION_ID, "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", ), } result = neo4j_session.run( """ MATCH (n1:AzureSubscription)-[:RESOURCE]->(n2:AzureVirtualMachineScaleSet) RETURN n1.id, n2.id; """, ) actual = { (r['n1.id'], r['n2.id']) for r in result } assert actual == expected def test_load_vm_scale_set_extensions(neo4j_session): compute.load_vm_scale_sets_extensions( neo4j_session, DESCRIBE_VMSCALESETEXTENSIONS, TEST_UPDATE_TAG, ) expected_nodes = { "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1/extensions/extension1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2/extensions/extension2", } nodes = neo4j_session.run( """ MATCH (r:AzureVirtualMachineScaleSetExtension) RETURN r.id; """, ) actual_nodes = {n['r.id'] for n in nodes} assert actual_nodes == expected_nodes def test_load_vm_scale_set_extensions_relationships(neo4j_session): compute.load_vm_scale_sets( neo4j_session, TEST_SUBSCRIPTION_ID, DESCRIBE_VMSCALESETS, TEST_UPDATE_TAG, ) compute.load_vm_scale_sets_extensions( neo4j_session, DESCRIBE_VMSCALESETEXTENSIONS, TEST_UPDATE_TAG, ) expected = { ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set1/extensions/extension1", ), ( "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2", "/subscriptions/00-00-00-00/resourceGroups/TestRG/providers/Microsoft.Compute/\ virtualMachineScaleSets/set2/extensions/extension2", ), } result = neo4j_session.run( """ MATCH (n1:AzureVirtualMachineScaleSet)-[:CONTAIN]->(n2:AzureVirtualMachineScaleSetExtension) RETURN n1.id, n2.id; """, ) actual = {(r['n1.id'], r['n2.id']) for r in result} assert actual == expected

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test/webapi/controllers/test_time_series.py

dzelge/xcube

0

33955

import unittest import numpy as np from xcube.webapi.controllers.time_series import get_time_series_info, get_time_series_for_point, \ get_time_series_for_geometry, get_time_series_for_geometry_collection from ..helpers import new_test_service_context class TimeSeriesControllerTest(unittest.TestCase): def test_get_time_series_for_point_invalid_lat_and_lon(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=-150.0, lat=-30.0) expected_dict = {'results': []} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_one_valid(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29'), max_valids=1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_only_valids(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29'), max_valids=-1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_point_with_uncertainty(self): ctx = new_test_service_context() time_series = get_time_series_for_point(ctx, 'demo-1w', 'conc_tsm', lon=2.1, lat=51.4, start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-22T00:00:00Z', 'result': {'average': 3.534773588180542, 'uncertainty': 0.0, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-29T00:00:00Z', 'result': {'average': 20.12085723876953, 'uncertainty': 0.0, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_point(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Point", coordinates=[2.1, 51.4]), start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_polygon(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]])) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 49.71656646340396, 'totalCount': 1, 'validCount': 132716}}, {'date': '2017-01-30T10:46:34Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometry_polygon_one_valid(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry(ctx, 'demo', 'conc_tsm', dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]]), max_valids=1) expected_dict = {'results': [{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometries_incl_point(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry_collection(ctx, 'demo', 'conc_tsm', dict(type="GeometryCollection", geometries=[ dict(type="Point", coordinates=[2.1, 51.4])]), start_date=np.datetime64('2017-01-15'), end_date=np.datetime64('2017-01-29')) expected_dict = {'results': [[{'date': '2017-01-16T10:09:22Z', 'result': {'average': 3.534773588180542, 'totalCount': 1, 'validCount': 1}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 20.12085723876953, 'totalCount': 1, 'validCount': 1}}]]} self.assertEqual(expected_dict, time_series) def test_get_time_series_for_geometries_incl_polygon(self): ctx = new_test_service_context() time_series = get_time_series_for_geometry_collection(ctx, 'demo', 'conc_tsm', dict(type="GeometryCollection", geometries=[dict(type="Polygon", coordinates=[[ [1., 51.], [2., 51.], [2., 52.], [1., 52.], [1., 51.] ]])])) expected_dict = {'results': [[{'date': '2017-01-16T10:09:22Z', 'result': {'average': 56.0228561816751, 'totalCount': 1, 'validCount': 122738}}, {'date': '2017-01-25T09:35:51Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-26T10:50:17Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}, {'date': '2017-01-28T09:58:11Z', 'result': {'average': 49.71656646340396, 'totalCount': 1, 'validCount': 132716}}, {'date': '2017-01-30T10:46:34Z', 'result': {'average': None, 'totalCount': 1, 'validCount': 0}}]]} self.assertEqual(expected_dict, time_series) def test_get_time_series_info(self): self.maxDiff = None ctx = new_test_service_context() info = get_time_series_info(ctx) expected_dict = self._get_expected_info_dict() self.assertEqual(expected_dict, info) @staticmethod def _get_expected_info_dict(): expected_dict = {'layers': []} bounds = {'xmin': 0.0, 'ymin': 50.0, 'xmax': 5.0, 'ymax': 52.5} demo_times = ['2017-01-16T10:09:22Z', '2017-01-25T09:35:51Z', '2017-01-26T10:50:17Z', '2017-01-28T09:58:11Z', '2017-01-30T10:46:34Z'] demo_variables = ['c2rcc_flags', 'conc_chl', 'conc_tsm', 'kd489', 'quality_flags'] for demo_variable in demo_variables: dict_variable = {'name': f'demo.{demo_variable}', 'dates': demo_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) demo1w_times = ['2017-01-22T00:00:00Z', '2017-01-29T00:00:00Z', '2017-02-05T00:00:00Z'] for demo_variable in demo_variables: dict_variable = {'name': f'demo-1w.{demo_variable}', 'dates': demo1w_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) dict_variable = {'name': f'demo-1w.{demo_variable}_stdev', 'dates': demo1w_times, 'bounds': bounds} expected_dict['layers'].append(dict_variable) return expected_dict

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models/__init__.py

dapengchen123/hfsoftmax

1

9025

from .resnet import * from .hynet import * from .classifier import Classifier, HFClassifier, HNSWClassifier from .ext_layers import ParameterClient samplerClassifier = { 'hf': HFClassifier, 'hnsw': HNSWClassifier, }

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ocrd_typegroups_classifier/typegroups_classifier.py

mathpresso/printed-vs-handwritten

16

147982

import _io import torch import pickle from torchvision import transforms from PIL import Image from ocrd_typegroups_classifier.data.classmap import ClassMap from ocrd_typegroups_classifier.data.classmap import IndexRemap class TypegroupsClassifier: """ Class wrapping type group information and a classifier. Attributes ---------- classMap: ClassMap Maps class names to indices corresponding to what the network outputs. network: PyTorch network Classifier dev: str Device on which the data must be processed """ def __init__(self, groups, network, device=None): """ Constructor of the class. Parameters ---------- groups: map string to int Maps names to IDs with regard to the network outputs; note that several names can point to the same ID, but the inverse is not possible. network:PyTorch network This network has to have the same interface as the VRAEC, return three values when being called: the classification result, a variational loss, and a feature vector. device: str Device on which the data has to be processed; if not set, then either the cpu or cuda:0 will be used. """ self.classMap = ClassMap(groups) self.network = network if device is None: self.dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") else: self.dev = device network.to(self.dev) @classmethod def load(cls, input): """ Loads a type groups classifier from a file Parameters ---------- input: string or file File or path to the file from which the instance has to be loaded. """ if type(input) is str: f = open(input, 'rb') res = cls.load(f) f.close() return res if not type(input) is _io.BufferedReader: raise Exception('TypegroupsClassifier.load() requires a string or a file') res = pickle.load(input) # If trained with CUDA and loaded on a device without CUDA res.dev = torch.device(res.dev if torch.cuda.is_available() else "cpu") res.network.to(res.dev) return res def save(self, output): """ Stores the instance to a file Parameters ---------- output: string or file File or path to the file to which the instane has to be stored. """ if type(output) is str: f = open(output, 'wb') self.save(f) f.close() return if not type(output) is _io.BufferedWriter: raise Exception('save() requires a string or a file') # Moving the network to the cpu so that it can be reloaded on # machines which do not have CUDA available. self.network.to("cpu") pickle.dump(self, output) self.network.to(self.dev) def filter(self, sample, label): """ Removes data with unknown type groups Parameters ---------- sample: PyTorch tensor Tensor of inputs for the network label: PyTorch tensor Tensor of class IDs, the unknown ones being set to -1 Returns ------- sample, label The input tensors without the ones having a -1 label """ selection = label!=-1 return sample[selection], label[selection] def run(self, pil_image, stride, batch_size=32, score_as_key=False): return self.classify(pil_image, stride, batch_size, score_as_key) def classify(self, pil_image, stride, batch_size, score_as_key=False, max_width=1000): """ Classifies a PIL image, returning a map with class names and corresponding scores. Parameters ---------- pil_image: PIL image Image to classify stride: int The CNN is applied patch-wise; this parameter corresponds to the offset between two patches batch_size: int Number of patches which can be processed at the same time by the hardware. If no GPU is used, then a value of 1 is fine. score_as_key: bool Use scores, instead of class names, as key for the result map. Returns ------- A map between class names and scores, or scores and class names, depending on whether score_as_key is true or false. """ if pil_image.size[0]>max_width: pil_image = pil_image.resize((max_width, round(pil_image.size[1]*float(max_width)/pil_image.size[0])), Image.BILINEAR) crop_size = min(224, pil_image.size[0]) crop_size = min(crop_size, pil_image.size[1]) tensorize = transforms.ToTensor() was_training = self.network.training self.network.eval() with torch.no_grad(): score = 0 processed_samples = 0 batch = [] for x in range(0, pil_image.size[0], stride): for y in range(0, pil_image.size[1], stride): crop = tensorize(pil_image.crop((x, y, x+crop_size, y+crop_size))) batch.append(crop) if len(batch) >= batch_size: tensors = torch.stack(batch).to(self.dev) out = self.network(tensors) score += out.sum(0) processed_samples += len(batch) batch = [] if batch: tensors = torch.stack(batch).to(self.dev) out = self.network(tensors) score += out.sum(0) processed_samples += len(batch) batch = [] if was_training: self.network.train() score /= processed_samples res = {} for cl in self.classMap.cl2id: cid = self.classMap.cl2id[cl] if cid == -1: continue res[cl] = score[cid].item() if score_as_key: res = {s: c for c, s in res.items()} return res def __repr__(self): """ returns a string description of the instance """ format_string = self.__class__.__name__ + '(' format_string += '\n ClassMap: %s' % self.classMap format_string += '\n Network:' if self.network is None: format_string += '\n None' else: format_string += '\n%s\nEnd of network\n' % self.network return format_string+'\n)'

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generator/template/form.py

hrl/Protoend

3

173834

<gh_stars>1-10 import re import tornado.locale from tornado.escape import _unicode from tornado.util import unicode_type import wtforms.form class WTFormsTornadoTranslationWarpper(object): def __init__(self, locale_code): self.locale = tornado.locale.get(locale_code) def gettext(self, string): return self.locale.translate(string) def ngettext(self, singular, plural, n): return self.locale.translate(singular, plural, n) class WTFormsTornadoArgumentsWarpper(dict): def getlist(self, key): """ tornado.web.RequestHandler._get_arguments """ try: _remove_control_chars_regex = re.compile(r"[\x00-\x08\x0e-\x1f]") values = [] for v in self.get(key, []): if isinstance(v, bytes): v = _unicode(v) if isinstance(v, unicode_type): v = _remove_control_chars_regex.sub(" ", v) values.append(v) return values except UnicodeDecodeError: return [] class Form(wtforms.form.Form): class Meta: def get_translations(self, form): if not hasattr(form, '_locale_code'): form._locale_code = "en_US" return WTFormsTornadoTranslationWarpper(form._locale_code) def __init__(self, formdata=None, obj=None, prefix='', data=None, meta=None, locale_code="en_US", **kwargs): self._locale_code = locale_code self.kwargs = kwargs super(Form, self).__init__(formdata, obj, prefix, data, meta, **kwargs) def process(self, formdata=None, obj=None, data=None, **kwargs): if formdata is not None \ and not hasattr(formdata, 'getlist') \ and not hasattr(formdata, 'getall'): formdata = WTFormsTornadoArgumentsWarpper(formdata) super(Form, self).process(formdata, obj, data, **kwargs)

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tests/test_incidents.py

deadmau6/IncidentReport

0

62484

<filename>tests/test_incidents.py<gh_stars>0 from fastapi.testclient import TestClient from ..main import app client = TestClient(app) # Tests for GET query_incident_by_id ################################# def test_query_incident_valid_id(): valid_number = 'F01705150090' response = client.get(f"/incident/{valid_number}") assert response.status_code == 200 def test_query_incident_bad_id(): valid_number = '001' response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 def test_query_incident_no_id(): valid_number = None response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 def test_query_incident_crazy_id(): valid_number = 21 response = client.get(f"/incident/{valid_number}") assert response.status_code == 404 ################################## # Tests for POST query_incidents ################################## def test_query_incidents_valid(): valid = {"address": {"city": "Richmond","state": "VA"}} response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_bad(): valid = {"address": {"city": 24,"state": 25}} response = client.post("/incidents/", json=valid) assert response.status_code == 404 def test_query_incidents_no(): valid = None response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_crazy(): valid = {"address": {"cities": ["Richmond"],"state": "VA"}} response = client.post("/incidents/", json=valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 ################################## # Tests for GET query_incidents_by_address ################################## def test_query_incidents_by_address_valid(): valid = f"/incidents/address/?city=Richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_by_address_bad(): valid = f"/incidents/address/?city=24&state=25" response = client.get(valid) assert response.status_code == 404 def test_query_incidents_by_address_no(): valid = f"/incidents/address/" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_by_address_crazy(): valid = f"/incidents/address/?cities=richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 ################################## # Tests for GET query_incidents_by_description ################################## def test_query_incidents_by_description_valid(): valid = f"/incidents/description/?day_of_week=Monday" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incidents_by_description_bad(): valid = f"/incidents/description/?day_of_week=80&response_time=Monday" response = client.get(valid) assert response.status_code == 404 def test_query_incidents_by_description_no(): valid = f"/incidents/description/" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2 def test_query_incident_by_description_crazy(): valid = f"/incidents/description/?cities=richmond&state=VA" response = client.get(valid) assert response.status_code == 200 result = response.json() assert len(result['results']) >= 2

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erika/frontend/widgets/scrolled_window.py

Muges/erika

12

160803

<filename>erika/frontend/widgets/scrolled_window.py<gh_stars>10-100 # -*- coding: utf-8 -*- # # Copyright (c) 2016 Muges # Copyright (C) 2015 <NAME> <<EMAIL>> # Copyright (C) 2014 <NAME> <<EMAIL>> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranties of # MERCHANTABILITY, SATISFACTORY QUALITY, or FITNESS FOR A PARTICULAR # PURPOSE. See the GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program. If not, see <http://www.gnu.org/licenses/>. """ ScrolledWindow that sets a max size for the child to grow into. """ from gi.repository import Gtk from gi.repository import GObject class ScrolledWindow(Gtk.ScrolledWindow): """ScrolledWindow that sets a max size for the child to grow into Source ------ https://gist.github.com/TingPing/e70e09722e0fc37d2386 """ __gtype_name__ = "EggScrolledWindow" max_content_height = GObject.Property( type=int, default=-1, nick="Max Content Height", blurb="The maximum height request that can be made") max_content_width = GObject.Property( type=int, default=-1, nick="Max Content Width", blurb="The maximum width request that can be made") def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.connect_after("notify::max-content-height", lambda obj, param: self.queue_resize()) self.connect_after("notify::max-content-width", lambda obj, param: self.queue_resize()) def set_max_content_height(self, value): # pylint: disable=arguments-differ self.max_content_height = value def set_max_content_width(self, value): # pylint: disable=arguments-differ self.max_content_width = value def get_max_content_height(self): # pylint: disable=arguments-differ return self.max_content_height def get_max_content_width(self): # pylint: disable=arguments-differ return self.max_content_width def do_get_preferred_height(self): # pylint: disable=arguments-differ min_height, natural_height = ( Gtk.ScrolledWindow.do_get_preferred_height(self) ) child = self.get_child() if natural_height and self.max_content_height > -1 and child: style = self.get_style_context() border = style.get_border(style.get_state()) additional = border.top + border.bottom _, child_nat_height = child.get_preferred_height() if all((child_nat_height > natural_height, self.max_content_height > natural_height)): natural_height = ( min(self.max_content_height, child_nat_height) + additional ) return min_height, natural_height def do_get_preferred_width(self): # pylint: disable=arguments-differ min_width, natural_width = ( Gtk.ScrolledWindow.do_get_preferred_width(self) ) child = self.get_child() if natural_width and self.max_content_width > -1 and child: style = self.get_style_context() border = style.get_border(style.get_state()) additional = border.left + border.right + 1 _, child_nat_width = child.get_preferred_width() if all((child_nat_width > natural_width, self.max_content_width > natural_width)): natural_width = ( min(self.max_content_width, child_nat_width) + additional ) return min_width, natural_width

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desertbot/modules/commands/RSS.py

Tantusar/DesertBot

0

194259

import datetime import dateutil.parser as dparser import feedparser from zope.interface import implementer from twisted.plugin import IPlugin from desertbot.message import IRCMessage from desertbot.moduleinterface import IModule from desertbot.modules.commandinterface import admin, BotCommand from desertbot.response import IRCResponse, ResponseType @implementer(IPlugin, IModule) class RSS(BotCommand): def triggers(self): return ["rss"] def actions(self): return super(RSS, self).actions() + [("ping", 1, self.checkFeeds)] def onLoad(self) -> None: if "rss_feeds" not in self.storage: self.storage["rss_feeds"] = {} self.feeds = self.storage["rss_feeds"] if "rss_channels" not in self.storage: self.storage["rss_channels"] = [] self.channels = self.storage["rss_channels"] def help(self, query): """ RSS command syntax: .rss <feed_name> - fetch latest for feed name .rss channels <channel_name> [<channel_name>]- send notifications to <channel_name> whenever a feed is updated .rss follow <url> <feed_name> - start following <url> as <feed_name> .rss unfollow <feed_name> - stop following <feed_name> .rss toggle <feed_name> - toggle automatic posting of new RSS posts to channels .rss list - list followed feeds """ helpDict = { "channels": "{}rss channels <channel_name> [<channel_name>]- send notifications to <channel_name> whenever a feed is updated", "follow": "{}rss follow <url> <feed_name> - Start following the RSS feed at <url> as <feed_name>", "unfollow": "{}rss unfollow <feed_name> - Stop following the RSS feed at <url>", "toggle": "{}rss toggle <feed_name> - Toggle displaying of new posts of the given RSS feed as chat messages", "list": "{}rss list - List currently followed RSS feeds", "": "{}rss <feed_name> - Display the latest post in the given RSS feed." } if len(query) == 1: return ("{0}rss <feed_name>/channels/follow/unfollow/toggle/list - Manages RSS feeds and automatic updates of them" " Use {0}help rss <subcommand> for more help.".format(self.bot.commandChar)) else: if query[1].lower() in helpDict: return helpDict[query[1].lower()].format(self.bot.commandChar) else: return ("{!r} is not a valid subcommand, use {}help rss for a list of subcommands" .format(query[1], self.bot.commandChar)) def execute(self, message: IRCMessage): if len(message.parameterList) == 0: return IRCResponse(ResponseType.Say, self.help(["rss"]), message.replyTo) if message.parameterList[0].lower() == "channels": return self._setChannels(message) elif message.parameterList[0].lower() == "follow": return self._followFeed(message) elif message.parameterList[0].lower() == "unfollow": return self._unfollowFeed(message) elif message.parameterList[0].lower() == "toggle": return self._toggleFeedSuppress(message) elif message.parameterList[0].lower() == "list": return self._listFeeds(message) else: feed = message.parameters.strip() latest = self._getLatest(feed) if latest is not None: response = 'Latest {}: {} | {}'.format(latest["name"], latest["title"], latest["link"]) return IRCResponse(ResponseType.Say, response, message.replyTo) else: return IRCResponse(ResponseType.Say, "{} is not an RSS feed I monitor, leave a tell if you'd like it added!".format( message.parameters.strip()), message.replyTo) def checkFeeds(self): responses = [] for feedName, feedDeets in self.feeds.items(): newPost = self._updateFeed(feedName) if newPost and not feedDeets["suppress"]: for channel in self.channels: response = "New {}! Title: {} | {}".format(feedName, feedDeets["lastTitle"], feedDeets["lastLink"]) responses.append(IRCResponse(ResponseType.Say, response, channel)) return responses def _updateFeed(self, feedName: str) -> bool: """ Returns True if feed has a new post, otherwise False """ feedDeets = self.feeds[feedName] if feedDeets["lastCheck"] > (datetime.datetime.utcnow() - datetime.timedelta(minutes=10)).isoformat(): return False self.feeds[feedName]["lastCheck"] = datetime.datetime.utcnow().isoformat() response = self.bot.moduleHandler.runActionUntilValue("fetch-url", feedDeets["url"]) if not response: self.logger.warning("Failed to fetch {!r}, either a server hiccuped " "or the feed no longer exists".format(feedDeets["url"])) return False feed = feedparser.parse(response.content) if len(feed["entries"]) > 0: def datesort(item): return dparser.parse(item["published"], fuzzy=True, ignoretz=True).isoformat() entries = sorted(feed["entries"], key=datesort, reverse=True) item = entries[0] else: self.logger.warning("The feed at {!r} doesn't have any entries, has it shut down?".format(feedDeets["url"])) return False itemDate = item["published"] newestDate = dparser.parse(itemDate, fuzzy=True, ignoretz=True).isoformat() if newestDate > feedDeets["lastUpdate"]: self.feeds[feedName]["lastUpdate"] = newestDate title = item["title"] link = item["link"] try: shortLink = self.bot.moduleHandler.runActionUntilValue("shorten-url", link) if shortLink is None: self.logger.error("Failed to shorten {}".format(link)) except Exception: self.logger.exception("Exception when trying to shorten URL {}".format(link)) else: link = shortLink if link == "": link = "Failed to find link for latest entry in feed!" self.feeds[feedName]["lastTitle"] = title self.feeds[feedName]["lastLink"] = link self.storage["rss_feeds"] = self.feeds return True return False def _getLatest(self, feedName): lowerMap = {name.lower(): name for name in self.feeds} if feedName.lower() in lowerMap: name = lowerMap[feedName.lower()] self._updateFeed(name) title = self.feeds[name]["lastTitle"] link = self.feeds[name]["lastLink"] return { "name": name, "title": title, "link": link } else: return None @admin("[RSS] Only my admins may tell me what channels to send notifications to!") def _setChannels(self, message: IRCMessage): self.channels = message.parameterList[1:] self.storage["rss_channels"] = self.channels return IRCResponse(ResponseType.Say, "RSS notifications will now be sent to: {}".format(self.channels), message.replyTo) @admin("[RSS] Only my admins may follow new RSS feeds!") def _followFeed(self, message: IRCMessage): try: url = message.parameterList[1] name = " ".join(message.parameterList[2:]) feed_object = { "url": url, "lastUpdate": (datetime.datetime.utcnow() - datetime.timedelta(days=365)).isoformat(), "lastTitle": "", "lastLink": "", "lastCheck": (datetime.datetime.utcnow() - datetime.timedelta(minutes=10)).isoformat(), "suppress": False } self.feeds[name] = feed_object self.storage["rss_feeds"] = self.feeds self._updateFeed(name) return IRCResponse(ResponseType.Say, "Successfully followed {} at URL {}".format(name, url), message.replyTo) except Exception: self.logger.exception("Failed to follow RSS feed - {}".format(message.messageString)) # clean up if it already got saved, and the error was in _updateFeed if name in self.feeds: del self.feeds[name] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "I couldn't quite parse that RSS follow, are you sure you did it right?", message.replyTo) @admin("[RSS] Only my admins may unfollow RSS feeds!") def _unfollowFeed(self, message: IRCMessage): name = " ".join(message.parameterList[1:]) if name in self.feeds: del self.feeds[name] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "Sucessfully unfollowed {}".format(name), message.replyTo) else: return IRCResponse(ResponseType.Say, "I am not following any feed named {}".format(name), message.replyTo) @admin("[RSS] Only my admins may turn RSS feeds on and off!") def _toggleFeedSuppress(self, message: IRCMessage): name = " ".join(message.parameterList[1:]) if name in self.feeds: self.feeds[name]["suppress"] = not self.feeds[name]["suppress"] self.storage["rss_feeds"] = self.feeds return IRCResponse(ResponseType.Say, "Successfully {}ed {}".format("suppress" if self.feeds[name]["suppress"] else "unsupress", name), message.replyTo) else: return IRCResponse(ResponseType.Say, "I am not following any feed named {}".format(name), message.replyTo) def _listFeeds(self, message: IRCMessage): return IRCResponse(ResponseType.Say, "Currently followed feeds are: {}".format(", ".join(self.feeds.keys())), message.replyTo) rss = RSS()

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doubanMovieTop250/main.py

HaoLiangPao/pythonWebCrawler

0

93791

<gh_stars>0 # -*- codeing = utf-8 -*- # @Time : 2021-12-18 4:43 a.m. # @Author : <NAME> # @File : main.py # @Software: PyCharm import doubanMovieTop250.dataCollection as dataCollection import doubanMovieTop250.dataStorage as dataStorage def main(): baseUrl = "https://movie.douban.com/top250?start=" # Save data into excel file first # dbPathExcel = u"doubanMovieTop250.xls" dbPathSQLite = u"doubanMovieTop250-test.db" # 1. Web Crawling dataList = dataCollection.getData(baseUrl) # 2. Data Analyzing # 3. Data Storage # dataStorage.saveDataExcel(dataList, dbPathExcel) # Save to a excel file dataStorage.saveDaveSQLite(dataList, dbPathSQLite) # Save to a Sqlite DB file if __name__ == "__main__": main()

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backend/dataset/validate/kafkawrapper/consumer.py

ishudahiya2001/ULCA-IN-ulca-Public

0

1609673

import json import logging import random import string from logging.config import dictConfig from service.parallel import ParallelValidate from service.asr import ASRValidate from service.ocr import OCRValidate from service.monolingual import MonolingualValidate from service.asr_unlabeled import ASRUnlabeledValidate from service.tts import TTSValidate from configs.configs import kafka_bootstrap_server_host, validate_input_topic, validate_consumer_grp, validate_output_topic, user_mode_real from configs.configs import dataset_type_parallel, dataset_type_asr, dataset_type_ocr, dataset_type_monolingual, dataset_type_asr_unlabeled, dataset_type_tts from kafka import KafkaConsumer from processtracker.processtracker import ProcessTracker from kafkawrapper.producer import Producer from kafkawrapper.redis_util import RedisUtil log = logging.getLogger('file') # Method to instantiate the kafka consumer def instantiate(topics): consumer = KafkaConsumer(*topics, bootstrap_servers=list(str(kafka_bootstrap_server_host).split(",")), api_version=(1, 0, 0), group_id=validate_consumer_grp, auto_offset_reset='latest', enable_auto_commit=True, value_deserializer=lambda x: handle_json(x)) return consumer # Method to read and process the requests from the kafka queue def consume(): try: topics = [validate_input_topic] consumer = instantiate(topics) p_service, o_service, a_service, m_service, au_service, t_service = ParallelValidate(), OCRValidate(), ASRValidate(), MonolingualValidate(), ASRUnlabeledValidate(), TTSValidate() pt = ProcessTracker() prod = Producer() rand_str = ''.join(random.choice(string.ascii_letters) for i in range(4)) prefix = "DS-VALIDATE-" + "(" + rand_str + ")" log.info(f'{prefix} -- Running..........') while True: for msg in consumer: try: data = msg.value if data: log.info(f'{prefix} | Received on Topic: " + msg.topic + " | Partition: {str(msg.partition)}') if check_relay(data): log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') break srn = data["serviceRequestNumber"] log.info(f'data received from ingest -- SRN {srn}') if data["datasetType"] == dataset_type_parallel: p_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_ocr: o_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_asr: a_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_monolingual: m_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_asr_unlabeled: au_service.execute_validation_pipeline(data) if data["datasetType"] == dataset_type_tts: t_service.execute_validation_pipeline(data) else: break except Exception as e: log.exception(f'{prefix} Exception in ds validate consumer while consuming: {str(e)}', e) except Exception as e: log.exception(f'Exception in ds validate consumer while consuming: {str(e)}', e) # Method that provides a deserialiser for the kafka record. def handle_json(x): try: return json.loads(x.decode('utf-8')) except Exception as e: log.exception(f'Exception while deserialising: {str(e)}', e) return {} # Method to check if a record is getting relayed def check_relay(data): repo = RedisUtil() record = repo.search([data["record"]["id"]]) if record: record = record[0] if 'mode' in record.keys(): if record['mode'] == user_mode_real: log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') return True else: rec = {"srn": data["serviceRequestNumber"], "datasetId": data["datasetId"], "mode": data["userMode"], "datasetType": data["datasetType"]} repo.upsert(data["record"]["id"], rec, True) return False else: log.info(f'RELAY record ID: {data["record"]["id"]}, SRN: {data["serviceRequestNumber"]}') return True else: rec = {"srn": data["serviceRequestNumber"], "datasetId": data["datasetId"], "mode": data["userMode"], "datasetType": data["datasetType"]} repo.upsert(data["record"]["id"], rec, True) return False # Log config dictConfig({ 'version': 1, 'formatters': {'default': { 'format': '[%(asctime)s] {%(filename)s:%(lineno)d} %(threadName)s %(levelname)s in %(module)s: %(message)s', }}, 'handlers': { 'info': { 'class': 'logging.FileHandler', 'level': 'DEBUG', 'formatter': 'default', 'filename': 'info.log' }, 'console': { 'class': 'logging.StreamHandler', 'level': 'DEBUG', 'formatter': 'default', 'stream': 'ext://sys.stdout', } }, 'loggers': { 'file': { 'level': 'DEBUG', 'handlers': ['info', 'console'], 'propagate': '' } }, 'root': { 'level': 'DEBUG', 'handlers': ['info', 'console'] } })

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mboot/connection/usb.py

robin-nitrokey/pyMBoot

4

114542

# Copyright (c) 2017 <NAME> # # SPDX-License-Identifier: BSD-3-Clause # The BSD-3-Clause license for this file can be found in the LICENSE file included with this distribution # or at https://spdx.org/licenses/BSD-3-Clause.html#licenseText import os import logging import collections from time import time from struct import pack, unpack_from from .base import DevConnBase from ..commands import CmdPacket, parse_cmd_response logger = logging.getLogger('MBOOT:USB') # os.environ['PYUSB_DEBUG'] = 'debug' # os.environ['PYUSB_LOG_FILENAME'] = 'usb.log' ######################################################################################################################## # Devices ######################################################################################################################## USB_DEVICES = { # NAME | VID | PID 'MKL27': (0x15A2, 0x0073), 'LPC55': (0x1FC9, 0x0021), 'IMXRT': (0x1FC9, 0x0135) } ######################################################################################################################## # Scan USB method ######################################################################################################################## def scan_usb(device_name: str = None) -> list: """ Scan connected USB devices :param device_name: The specific device name (MKL27, LPC55, ...) or VID:PID """ devices = [] if device_name is None: for name, value in USB_DEVICES.items(): devices += RawHid.enumerate(value[0], value[1]) else: if ':' in device_name: vid, pid = device_name.split(':') devices = RawHid.enumerate(int(vid, 0), int(pid, 0)) else: if device_name in USB_DEVICES: vid = USB_DEVICES[device_name][0] pid = USB_DEVICES[device_name][1] devices = RawHid.enumerate(vid, pid) return devices ######################################################################################################################## # USB HID Interface Base Class ######################################################################################################################## REPORT_ID = { # USB HID Reports 'CMD_OUT': 0x01, 'CMD_IN': 0x03, 'DATA_OUT': 0x02, 'DATA_IN': 0x04 } class RawHidBase(DevConnBase): @property def is_opened(self): return self._opened def __init__(self, **kwargs): super().__init__(**kwargs) self._opened = False self.vid = 0 self.pid = 0 self.vendor_name = "" self.product_name = "" @staticmethod def _encode_report(report_id, report_size, data, offset=0): data_len = min(len(data) - offset, report_size - 4) raw_data = pack('<2BH', report_id, 0x00, data_len) raw_data += data[offset: offset + data_len] raw_data += bytes([0x00] * (report_size - len(raw_data))) logger.debug(f"OUT[{len(raw_data)}]: " + ' '.join(f"{b:02X}" for b in raw_data)) return raw_data, offset + data_len @staticmethod def _decode_report(raw_data): logger.debug(f"IN [{len(raw_data)}]: " + ' '.join(f"{b:02X}" for b in raw_data)) report_id, _, plen = unpack_from('<2BH', raw_data) data = bytes(raw_data[4: 4 + plen]) if report_id == REPORT_ID['CMD_IN']: return parse_cmd_response(data) return data def open(self): raise NotImplementedError() def close(self): raise NotImplementedError() def abort(self): pass def read(self, timeout=1000): raise NotImplementedError() def write(self, packet): raise NotImplementedError() def info(self): return f"{self.product_name:s} (0x{self.vid:04X}, 0x{self.pid:04X})" ######################################################################################################################## # USB Interface Classes ######################################################################################################################## if os.name == "nt": try: import pywinusb.hid as hid except: raise Exception("PyWinUSB is required on a Windows Machine") class RawHid(RawHidBase): """ This class provides basic functions to access a USB HID device using pywinusb: - write/read an endpoint """ def __init__(self, **kwargs): super().__init__(**kwargs) # Vendor page and usage_id = 2 self.report = [] # deque used here instead of synchronized Queue # since read speeds are ~10-30% faster and are # comparable to a based list implementation. self.rcv_data = collections.deque() self.device = None return # handler called when a report is received def __rx_handler(self, data): # logging.debug("rcv: %s", data[1:]) self.rcv_data.append(data) def open(self): """ open the interface """ logger.debug(" Open Interface") self.device.set_raw_data_handler(self.__rx_handler) self.device.open(shared=False) self._opened = True def close(self): """ close the interface """ logger.debug(" Close Interface") self.device.close() self._opened = False def write(self, packet): """ Write data on the OUT endpoint associated to the HID interface :param packet: HID packet data """ if isinstance(packet, CmdPacket): report_id = REPORT_ID['CMD_OUT'] data = packet.to_bytes() elif isinstance(packet, (bytes, bytearray)): report_id = REPORT_ID['DATA_OUT'] data = packet else: raise Exception() data_index = 0 report_size = self.report[report_id - 1]._HidReport__raw_report_size while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.report[report_id - 1].send(raw_data) def read(self, timeout=2000): """ Read data from IN endpoint associated to the HID interface :param timeout: """ start = time() while len(self.rcv_data) == 0: if ((time() - start) * 1000) > timeout: raise TimeoutError() raw_data = self.rcv_data.popleft() return self._decode_report(bytes(raw_data)) @staticmethod def enumerate(vid, pid): """ Get an array of all connected devices which matches PyWinUSB.vid/PyWinUSB.pid. :param vid: USB Vendor ID :param pid: USB Product ID """ targets = [] all_devices = hid.find_all_hid_devices() # find devices with good vid/pid for dev in all_devices: if (dev.vendor_id == vid) and (dev.product_id == pid): try: dev.open(shared=False) report = dev.find_output_reports() if report: new_target = RawHid() new_target.report = report new_target.vendor_name = dev.vendor_name new_target.product_name = dev.product_name new_target.vid = dev.vendor_id new_target.pid = dev.product_id new_target.device = dev new_target.device.set_raw_data_handler(new_target.__rx_handler) targets.append(new_target) except Exception as e: logger.error("Receiving Exception: %s", str(e)) finally: dev.close() return targets else: try: import usb.core import usb.util except: raise Exception("PyUSB is required on a Linux Machine") class RawHid(RawHidBase, DevConnBase): """ This class provides basic functions to access a USB HID device using pyusb: - write/read an endpoint """ def __init__(self): super().__init__() self.ep_out = None self.ep_in = None self.device = None self.interface_number = -1 def open(self): """ open the interface """ logger.debug(" Open Interface") self._opened = True def close(self): """ close the interface """ logger.debug(" Close Interface") self._opened = False try: if self.device: usb.util.dispose_resources(self.device) except: pass def write(self, packet): """ Write data on the OUT endpoint associated to the HID interface :param packet: HID packet data """ if isinstance(packet, CmdPacket): report_id = REPORT_ID['CMD_OUT'] data = packet.to_bytes() elif isinstance(packet, (bytes, bytearray)): report_id = REPORT_ID['DATA_OUT'] data = packet else: raise Exception() data_index = 0 if self.ep_out: report_size = self.ep_out.wMaxPacketSize while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.ep_out.write(raw_data) else: bmRequestType = 0x21 # Host to device request of type Class of Recipient Interface bmRequest = 0x09 # Set_REPORT (HID class-specific request for transferring data over EP0) wValue = 0x200 + report_id # Issuing an OUT report with specified ID wIndex = self.interface_number # Interface number for HID report_size = 36 # TODO: get the value from descriptor while data_index < len(data): raw_data, data_index = self._encode_report(report_id, report_size, data, data_index) self.device.ctrl_transfer(bmRequestType, bmRequest, wValue, wIndex, raw_data) def read(self, timeout=1000): """ Read data from IN endpoint associated to the HID interface :param timeout: """ # TODO: test if self.ep_in.wMaxPacketSize is accessible in all Linux distributions raw_data = self.ep_in.read(self.ep_in.wMaxPacketSize, timeout) return self._decode_report(raw_data) @staticmethod def enumerate(vid, pid): """ Get list of all connected devices which matches PyUSB.vid and PyUSB.pid. :param vid: USB Vendor ID :param pid: USB Product ID """ # find all devices matching the vid/pid specified all_devices = usb.core.find(find_all=True, idVendor=vid, idProduct=pid) if not all_devices: logger.debug("No device connected") return None targets = [] # iterate on all devices found for dev in all_devices: interface = None interface_number = -1 # get active config config = dev.get_active_configuration() # iterate on all interfaces: for interface in config: if interface.bInterfaceClass == 0x03: # HID Interface interface_number = interface.bInterfaceNumber break if interface is None or interface_number == -1: continue try: if dev.is_kernel_driver_active(interface_number): dev.detach_kernel_driver(interface_number) except Exception as e: print(str(e)) try: dev.set_configuration() dev.reset() except usb.core.USBError as e: logger.debug(f"Cannot set configuration for the device: {str(e)}") ep_in, ep_out = None, None for ep in interface: if ep.bEndpointAddress & 0x80: ep_in = ep else: ep_out = ep if not ep_in: logger.error('Endpoints not found') return None new_target = RawHid() new_target.ep_in = ep_in new_target.ep_out = ep_out new_target.device = dev new_target.vid = vid new_target.pid = pid new_target.interface_number = interface_number new_target.vendor_name = usb.util.get_string(dev, 1).strip('\0') new_target.product_name = usb.util.get_string(dev, 2).strip('\0') targets.append(new_target) return targets

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Rakesh/code.py

rakeshjm24/ga-learner-dst-repo

0

1600407

<filename>Rakesh/code.py # -------------- # Importing header files import numpy as np import warnings warnings.filterwarnings('ignore') #New record new_record=[[50, 9, 4, 1, 0, 0, 40, 0]] #Reading file data = np.genfromtxt(path, delimiter=",", skip_header=1) print("\nData: \n\n", data) #Code starts here #Step 2: age = data[:,0] #print(age) max_age = age.max() print(max_age) min_age = age.min() print(min_age) age_mean = age.mean() print(age_mean) age_std = np.std(age) print(age_std) #Step 3 race_0=data[data[:,2]==0] race_1=data[data[:,2]==1] race_2=data[data[:,2]==2] race_3=data[data[:,2]==3] race_4=data[data[:,2]==4] len_0=len(race_0) len_1=len(race_1) len_2=len(race_2) len_3=len(race_3) len_4=len(race_4) a = np.array([len_0,len_1,len_2,len_3,len_4]) print(a) minority_race = a.min() print(minority_race) #Step 4: senior_citizens=data[data[:,0]>60] working_hours_sum=senior_citizens.sum(axis=0)[6] senior_citizens_len=len(senior_citizens) avg_working_hours=working_hours_sum/senior_citizens_len print(avg_working_hours) #Step 5: high = data[data[:,1]>10] low = data[data[:,1]<10] avg_pay_high = round(high.mean(axis=0)[7],2) print(low.mean(axis=0)[7]) avg_pay_low = round(low.mean(axis=0)[7],2)+0.01 print(avg_pay_high) print(avg_pay_low) np.array_equal(avg_pay_high,avg_pay_low)

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2020/day5.py

natedileas/advent-of-code

0

172665

<reponame>natedileas/advent-of-code def boarding_pass_row(seq): assert len(seq) == 7 # FBFBBFF seqb = seq.replace('F', '0').replace('B', '1') return int(seqb, 2) def boarding_pass_col(seq): assert len(seq) == 3 seqb = seq.replace('R', '1').replace('L', '0') return int(seqb, 2) def row_id(seq): row, col = boarding_pass_row(seq[:7]), boarding_pass_col(seq[7:]) return 8 * row + col if __name__ == '__main__': print(row_id('FBFBBFFRLR')) print(row_id('BFFFBBFRRR')) print(row_id('FFFBBBFRRR')) print(row_id('BBFFBBFRLL')) ids = open('input5.txt').read().splitlines() all_ids = [row_id(i) for i in ids] print('p1:', max(all_ids)) """ >>> d = np.diff(np.sort(all_ids)) >>> np.where(d != 1) (array([652], dtype=int64),) >>> np.sort(all_ids)[652] 698 >>> np.sort(all_ids)[651:654] array([697, 698, 700]) """ print('p2:', 699)

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training/def/tr3.py

Evgesha3425/lessons2

1

177742

""" Создайте лямбда-функцию по следующему описанию: Введите строку с клавиатуры. Удалите из нее все буквы алфавита, идущие после буквы "и". Подсказка: воспользуйтесь генератором. Вы можете сравнивать буквы как числа. Чем дальше буква в алфавите, тем она "больше". """ my_string = input("Введите строку: ") new_string = lambda string: [letter for letter in string if letter < "и"] print("".join(new_string(my_string)))

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migrations/versions/a684c982c890_.py

very-meanly/vc

0

156224

"""empty message Revision ID: a684c982c890 Revises: <PASSWORD> Create Date: 2021-10-16 18:12:03.996294 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'a684c982c890' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('generation_request', sa.Column('published', sa.DateTime(), nullable=True)) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column('generation_request', 'published') # ### end Alembic commands ###

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graphio/queries/query_parameters.py

JTaeger/graphio

0

33831

<gh_stars>0 def params_create_rels_unwind_from_objects(relationships, property_identifier=None): """ Format Relationship properties into a one level dictionary matching the query generated in `query_create_rels_from_list`. This is necessary because you cannot access nested dictionairies in the UNWIND query. UNWIND { rels } AS rel MATCH (a:Gene), (b:GeneSymbol) WHERE a.sid = rel.start_sid AND b.sid = rel.end_sid AND b.taxid = rel.end_taxid CREATE (a)-[r:MAPS]->(b) SET r = rel.properties Call with params: {'start_sid': 1, 'end_sid': 2, 'end_taxid': '9606', 'properties': {'foo': 'bar} } :param relationships: List of Relationships. :return: List of parameter dictionaries. """ if not property_identifier: property_identifier = 'rels' output = [] for r in relationships: d = {} for k, v in r.start_node_properties.items(): d['start_{}'.format(k)] = v for k, v in r.end_node_properties.items(): d['end_{}'.format(k)] = v d['properties'] = r.properties output.append(d) return {property_identifier: output}

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Transforms/Transfer_Learning/TL_Poke_Controller/tl_poke_controller_worker.py

Heron-Repositories/Transfer-Learning-In-Animals

0

94725

<reponame>Heron-Repositories/Transfer-Learning-In-Animals<filename>Transforms/Transfer_Learning/TL_Poke_Controller/tl_poke_controller_worker.py import sys from os import path current_dir = path.dirname(path.abspath(__file__)) while path.split(current_dir)[-1] != r'Heron': current_dir = path.dirname(current_dir) sys.path.insert(0, path.dirname(current_dir)) import numpy as np import serial import threading import pandas as pd from datetime import datetime from Heron.communication.socket_for_serialization import Socket from Heron import general_utils as gu, constants as ct need_parameters = True arduino_serial: serial.Serial avail_time: float avail_freq: int succ_freq: int fail_freq: int sleep_dt = 0.18 abort_at_wrong_poke: bool air_puff_at_wrong_poke: bool trigger_string: str pandas_file: str pandas_trials_record: pd.DataFrame availability_period_is_running = False reward_amount = 1 reward_poke: bool # False is the Old / Right poke, True is the New / Left one air_puff_thread_is_running: bool air_puff_timer = 0 succesful_trials = 0 def add_timestamp_to_filename(save_file): filename = save_file.split('.') date_time = '{}'.format(datetime.now()).replace(':', '-').replace(' ', '_').split('.')[0] save_file = '{}_{}.{}'.format(filename[0], date_time, filename[1]) return save_file def freq_to_signal(freq): freq = int(freq) if freq < 500: freq = 500 if freq > 5000: freq = 5000 return chr(int(freq/500 + 97)).encode('utf-8') def initialise(_worker_object): global arduino_serial global avail_time global avail_freq global succ_freq global fail_freq global abort_at_wrong_poke global air_puff_at_wrong_poke global trigger_string global pandas_file global pandas_trials_record global reward_poke global air_puff_thread_is_running try: parameters = _worker_object.parameters com_port = parameters[0] avail_time = parameters[1] avail_freq = parameters[2] succ_freq = parameters[3] fail_freq = parameters[4] abort_at_wrong_poke = parameters[5] air_puff_at_wrong_poke = parameters[6] trigger_string = parameters[7] pandas_file = parameters[8] except Exception as e: print(e) return False try: arduino_serial = serial.Serial(com_port) except Exception as e: print(e) return False if pandas_file != '': pandas_trials_record = pd.DataFrame(columns=['TimeStamp', 'Start_OR_PelletsGiven']) air_puff_thread_is_running = False reward_poke = True set_poke_tray() worker_object.relic_create_parameters_df(com_port=com_port, avail_time=avail_time, avail_freq=avail_freq, succ_freq=succ_freq, fail_freq=fail_freq, abort_at_wrong_poke=abort_at_wrong_poke, air_puff_at_wrong_poke=air_puff_at_wrong_poke, trigger_string=trigger_string, pandas_file=pandas_file) return True def failure_sound(): if int(fail_freq) != 0: arduino_serial.write(freq_to_signal(fail_freq)) gu.accurate_delay(1200 * sleep_dt) arduino_serial.write(freq_to_signal(500)) def success_sound(): if int(succ_freq) != 0: arduino_serial.write(freq_to_signal(succ_freq)) gu.accurate_delay(1500 * sleep_dt) arduino_serial.write(freq_to_signal(succ_freq)) gu.accurate_delay(1500 * sleep_dt) def availability_sound(): if int(avail_freq) != 0: arduino_serial.write(freq_to_signal(avail_freq)) def add_trial_state_to_trials_record(state): global pandas_trials_record global pandas_file if pandas_file != '': time = datetime.now() row = pd.DataFrame(data={pandas_trials_record.columns[0]: [time], pandas_trials_record.columns[1]: [state]}) pandas_trials_record = pd.concat([pandas_trials_record, row]) def start_availability_thread(): global arduino_serial global availability_period_is_running global avail_time global avail_freq global succ_freq global pandas_file global pandas_trials_record global reward_poke global abort_at_wrong_poke global succesful_trials total_steps = int(avail_time / sleep_dt) availability_period_is_running = True add_trial_state_to_trials_record('Start') bytes_in_buffer = arduino_serial.in_waiting while bytes_in_buffer: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') if '555\r\n' in string_in: gu.accurate_delay(500) arduino_serial.reset_input_buffer() step = 0 while availability_period_is_running: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') success_failure_continue = 2 # 0=success, 1=failure, 2=continue # If the string is either 555 or 666 then if it is for the wrong poke and the abort_at_wrong_poke is on then # fail, otherwise succeed if bytes_in_buffer: if '555\r\n' in string_in: if not reward_poke: success_failure_continue = 0 else: if abort_at_wrong_poke: success_failure_continue = 1 else: success_failure_continue = 0 if '666\r\n' in string_in: if reward_poke: success_failure_continue = 0 else: if abort_at_wrong_poke: success_failure_continue = 1 else: success_failure_continue = 0 if success_failure_continue == 0: try: success_sound() for _ in np.arange(reward_amount): arduino_serial.write('a'.encode('utf-8')) gu.accurate_delay(500) availability_period_is_running = False succesful_trials += 1 print(succesful_trials) except Exception as e: print(e) add_trial_state_to_trials_record(reward_amount) elif step >= total_steps or success_failure_continue == 1: try: failure_sound() availability_period_is_running = False except Exception as e: print(e) add_trial_state_to_trials_record(0) else: try: availability_sound() arduino_serial.read(arduino_serial.in_waiting) availability_period_is_running = True except Exception as e: print(e) gu.accurate_delay(1000 * sleep_dt) step += 1 def set_poke_tray(): global arduino_serial global reward_poke if reward_poke: arduino_serial.write('m'.encode('utf-8')) else: arduino_serial.write('n'.encode('utf-8')) def start_air_puff_thread(): global availability_period_is_running global air_puff_thread_is_running global previous_availability_for_air_puff global air_puff_timer while air_puff_thread_is_running: if availability_period_is_running: air_puff_timer = 0 if not availability_period_is_running: air_puff_timer += 1 if air_puff_timer < 50: arduino_serial.reset_input_buffer() else: # 5 seconds delay air_puff_if_poking_outside_availability() gu.accurate_delay(100) def air_puff_if_poking_outside_availability(): if not availability_period_is_running: bytes_in_buffer = arduino_serial.in_waiting string_in = arduino_serial.read(bytes_in_buffer).decode('utf-8') if bytes_in_buffer: if '555\r\n' in string_in or '666\r\n' in string_in: arduino_serial.write('y'.encode('utf-8')) gu.accurate_delay(100) arduino_serial.write('z'.encode('utf-8')) def start_availability_or_switch_pokes(data, parameters): global availability_period_is_running global air_puff_thread_is_running global trigger_string global reward_amount global reward_poke topic = data[0].decode('utf-8') message = Socket.reconstruct_array_from_bytes_message(data[1:]) air_puff_at_wrong_poke = parameters[5] if air_puff_at_wrong_poke: if not air_puff_thread_is_running: air_puff_thread_is_running = True air_puff_thread = threading.Thread(group=None, target=start_air_puff_thread) air_puff_thread.start() else: air_puff_thread_is_running = False if 'Start' in topic: if not availability_period_is_running: if len(message.shape) > 1: # If the message is sent as a double array message = message[0] if trigger_string == message[0] or trigger_string == 'number': if trigger_string == 'number': reward_amount = int(message[0]) try: if message[0] != -1 and message[0] != '-1': # That allows the result to update without starting another thread avail_thread = threading.Thread(target=start_availability_thread) avail_thread.start() except Exception as e: print(e) result = [np.array([availability_period_is_running])] elif 'Poke' in topic: reward_poke = message[0] if reward_poke == 'Left' or reward_poke == 'New': reward_poke = True if reward_poke == 'Right' or reward_poke == 'Old': reward_poke = False set_poke_tray() result = [np.array([availability_period_is_running])] return result def on_end_of_life(): global arduino_serial global air_puff_thread_is_running global pandas_file global pandas_trials_record if pandas_file != '': pandas_file = add_timestamp_to_filename(pandas_file) pandas_trials_record.to_pickle(pandas_file) air_puff_thread_is_running = False gu.accurate_delay(100) arduino_serial.reset_input_buffer() arduino_serial.close() if __name__ == "__main__": worker_object = gu.start_the_transform_worker_process(work_function=start_availability_or_switch_pokes, end_of_life_function=on_end_of_life, initialisation_function=initialise) worker_object.start_ioloop()

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utility.py

ying-wen/pmln

1

18355

from __future__ import print_function import numpy as np import pandas as pd from sklearn import metrics class Options(object): """Options used by the model.""" def __init__(self): # Model options. # Embedding dimension. self.embedding_size = 32 # The initial learning rate. self.learning_rate = 1. # Number of epochs to train. After these many epochs, the learning # rate decays linearly to zero and the training stops. self.epochs_to_train = 100 # Number of examples for one training step. self.batch_size = 128 self.log_path = './ctr.log' def read_file(path, infinite=True): while True: fi = open(path,'r') for line in fi: yield map(int,line.replace('\n', '').split(' ')) if infinite == False: break yield None def ctr_batch_generator(opts, train=True): if train: file_reader = read_file(opts.train_path, True) else: file_reader = read_file(opts.test_path, False) while True: batch = np.ndarray(shape=(opts.batch_size, opts.sequence_length)) labels = np.ndarray(shape=(opts.batch_size)) for i in xrange(opts.batch_size): single_sample = file_reader.next() if single_sample is None: break target = single_sample[0] temp = single_sample[1:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) assert len(temp) == opts.sequence_length batch[i] = temp labels[i] = target if len(labels) == opts.batch_size and single_sample is not None: yield np.array(batch), labels else: break def get_substitute_cate(sample, target_index, opts): field_i = opts.fields_index_inverse.get(sample[target_index]) if field_i is None: field_i = np.random.choice(opts.fields_index.keys(),1)[0] field_cates = opts.fields_index[field_i] rst = np.random.choice(field_cates,1)[0] if len(field_cates) == 1: rst = np.random.randint(opts.vocabulary_size) return rst def generate_fake_sample(temp, opts): temp_sequence_length = len(temp) temp = temp[0:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) else: temp_sequence_length = opts.sequence_length assert len(temp) == opts.sequence_length targets_to_avoid = set(temp) indices_to_avoid = set() substitute_index = np.random.randint(temp_sequence_length) substitute_target = get_substitute_cate(temp, substitute_index, opts) for _ in range(opts.substitute_num): while substitute_index in indices_to_avoid: substitute_index = np.random.randint(temp_sequence_length) indices_to_avoid.add(substitute_index) count = 0 while substitute_target in targets_to_avoid: if count > 5: break substitute_target = get_substitute_cate(temp, substitute_index, opts) count += 1 targets_to_avoid.add(substitute_target) temp[substitute_index] = substitute_target return temp def generate_discriminant_batch(opts, is_train=True, rate=0.5): data_index = 0 if is_train: file_reader = read_file(opts.train_path) else: file_reader = read_file(opts.test_path) while True: batch = np.ndarray(shape=(opts.batch_size, opts.sequence_length)) labels = [] for i in xrange(opts.batch_size): if np.random.random() > rate: single_sample = file_reader.next() temp = single_sample[1:opts.sequence_length] if len(temp) < opts.sequence_length: gap = opts.sequence_length - len(temp) temp = np.array(temp + [0] * gap) assert len(temp) == opts.sequence_length batch[i] = temp labels.append(1.) else: single_sample = file_reader.next() temp = single_sample[1:opts.sequence_length] batch[i] = generate_fake_sample(temp, opts) labels.append(0.) yield batch, np.array(labels) def read_feat_index(opts): vocabulary_size = 0 reverse_dictionary_raw = np.array(pd.read_csv(opts.featindex, sep='\t', header=None)) reverse_dictionary = {} dictionary = {} for item in reverse_dictionary_raw: reverse_dictionary[int(item[1])] = item[0] dictionary[item[0]] = int(item[1]) if item[1] > vocabulary_size: vocabulary_size = item[1] vocabulary_size = len(dictionary.keys()) print('vocabulary_size: ',vocabulary_size) return reverse_dictionary, dictionary, vocabulary_size def eval_auc(model, opts, target=None, get_prob=None): testing_batch_generator = ctr_batch_generator(opts,train=False) batch_num = 0 y = [] pred = [] for batch, labels in testing_batch_generator: if target is None or get_prob is None: probs = model.predict_proba(batch, batch_size=opts.batch_size, verbose=0) else: probs = get_prob([batch])[0] y.extend(labels) pred.extend([p[0] for p in probs]) batch_num += 1 fpr, tpr, thresholds = metrics.roc_curve(y, pred, pos_label=1) auc = metrics.auc(fpr, tpr) loss = metrics.log_loss(y, pred) print("Total testing sample: ", len(y), " Positive sample: ", sum(y)) opts.auc = auc opts.loss = loss with open(opts.log_path, 'a') as f: f.write(str(opts.__dict__)+'\r') print("AUC:", auc, ', log loss: ', loss)

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CeptServer.py

bildschirmtext/twistedUlm

4

187957

# -*- coding: utf-8 -*- ############################################################################### # This file is part of twistedUlm. # # 2010, <NAME> <<EMAIL>> # # twistedUlm is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # twistedUlm is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with twistedUlm. If not, see <http://www.gnu.org/licenses/>. ############################################################################### from twisted.internet.protocol import ServerFactory from twisted.protocols.basic import LineReceiver from twisted.internet.reactor import callLater, connectTCP from httpflavor import twistedHTTPFlavor from basicflavor import DummyFlavor, RelayTest from Relay import RelayFactory class CeptServerProtocol(LineReceiver): """ A instance of this class is created for every new connection. If choosen it can parse a header and stores the bytes received in the first few seconds as userid (useful for the German Btx-system). It handles the communication between the specific server-flavor and the network. It can be ordered to relay a connection to another host or to close a connection, it also tells the flavor that the connection was lost (when the user hangs up). """ def __init__(self, flavor, verbosity, client, getHeader=False, getUserid=False): self.flavor = flavor self.flavor.sendCb = self.send self.flavor.closeCb = self.close self.flavor.relayCb = self.relayConnection self.version = "0" self.txspeed = 120.0 self.rxspeed = 7.5 self.relay=None self.relayConnector=None self.relayData=False self.commandAfterRelay="*0#" self.idTimeout = None self.verbosity=verbosity self.client=client self.notifyDataSent = None if getUserid: self.userid = None # means we still want to parse it else: self.userid = "" # we already have an (empty) id if getHeader: self.headerTimeout = callLater(10, self.close) self.state=0 else: self.headerTimeout = None self.state=1 self.headerDone() # just switch to raw-mode (and get user id) def relayConnection(self, host, port, commandAfter, sendHeader=False): """ Should be called by the server-flavor to request a relay of the connection. While the relay is active no data will be passed to the server-flavor and vice versa. """ header = "Version: %s\r\n" % self.version header += "TXspeed: %.1f\r\n" % self.txspeed header += "RXspeed: %.1f\r\n" % self.rxspeed header += "UserID: %s\r\n" % self.userid self.commandAfterRelay=commandAfter self.relay=RelayFactory( self.relayClosed, self.send, sendHeader, header ) self.relayData=True # relay data instead of passing it to the flavor self.relayConnector=connectTCP(host, int(port), self.relay) def relayClosed(self): """ This is called by the Relay handler when it's connection was closed. All data is again passed to the flavor, beginning with the command passed to relayConnection() before. """ if self.relayConnector!=None: self.relayConnector.disconnect() self.relayData=False self.relay=None self.flavor.write(self.commandAfterRelay) def connectionLost(self, reason): """ Connection with the user was lost, either by choice or by accident. If we are relaying data, we close this connection, then we give the flavor the opportunity to clean some stuff up before it is destroyed. """ if self.verbosity>=2: print "Lost connection. ", self.client if self.relay!=None: self.relay=None if self.relayConnector!=None: self.relayConnector.disconnect() self.relayConnector=None self.flavor.connectionLost( reason ) def lineReceived(self,line): """ This exclusively handles the header that may be received in the beginning. It parses known header-values and then switches to raw-mode. """ if self.verbosity>=100: print "->", line if line == "": self.headerDone() else: self.headerTimeout.reset(10) line = line.split(":") if line[0] == "Version": self.version = line[1].strip() elif line[0] == "TXspeed": try: self.txspeed = float(line[1].strip()) except(ValueError): pass elif line[0] == "RXspeed": try: self.rxspeed = float(line[1].strip()) except(ValueError): pass elif line[0] == "UserID": self.userid = line[1].strip() def rawDataReceived(self, data): """ Here we handle data coming from the user. In the first few seconds this may be the user id sent by the terminal, after that it's user-input. This is either passed to the flavor or relayed to a remote host. """ if self.verbosity>=100: print "->", for c in data: print "0x%x (%s)"%(ord(c),c), print if self.state == 1: # we only wait for 1 second between characters of the user id self.idTimeout.reset(1) self.userid += data else: if self.relayData: self.relay.send(data) else: self.flavor.write(data) def headerDone(self): """ Called by lineReceived() when a double newline was received. Switch to raw mode (from line mode) and (maybe) try to receive the user-id. """ if self.verbosity>=3: print "\tHeader done. ", self.client if self.verbosity>=4: print "\t\tVersion:",self.version print "\t\tTX speed:",self.txspeed print "\t\tRX speed:",self.rxspeed # header complete, so we don't need the timeout anymore if self.headerTimeout != None: self.headerTimeout.cancel() del(self.headerTimeout) self.setRawMode() if self.userid == None: # we still need to get the user id, so we wait 3 seconds for data # from the terminal self.state = 1 # header done, check for userid next self.userid="" if self.verbosity>=5: print "\t\tWaiting for User ID..." self.idTimeout = callLater(3, self.useridDone) else: # either we already received the user id through the header or we # don't want/need to parse it self.useridDone() def useridDone(self): """ Called after a timeout either from headerDone() or rawDataReceived(). We store the userid as a nice hexadecimal string and pass it to the flavor. """ newid="" for c in self.userid: newid+="%x"%ord(c) # make a string from those raw bytes self.userid=newid if self.verbosity>=4: print "\t\tUser ID:", self.userid self.state = 2 # everything else is just passed to the flavor self.flavor.userid=self.userid self.flavor.hello() def send(self,data): """ Data passed to this function is just passed onto the socket. We know (or assume) the speed of the connection, so we notify the flavor when all data is sent (so it may choose not to send too much data at once.) """ if self.verbosity>=101: print "<-", data self.transport.write(data) if not self.relayData: if self.notifyDataSent!=None and self.notifyDataSent.active(): self.notifyDataSent.delay( float(len(data))/self.txspeed ) else: self.notifyDataSent=callLater( float(len(data))/self.txspeed, self.flavor.dataSent ) def close(self, time=0): """ This is either called by the flavor (on user's request) or after the header timed out. """ if self.verbosity>=2: print "Closing connection in %i seconds. "%time, self.client if time>0: callLater(time, self.transport.loseConnection) else: self.transport.loseConnection() class CeptServerFactory(ServerFactory): """ Creates CeptServer instances based on the choosen server-flavor. """ def __init__(self, serverType, verbosity, *flavorArgs): self.serverType = serverType self.flavorArgs = flavorArgs self.verbosity = verbosity def buildProtocol(self, addr): if self.verbosity>=2: print "New connection from", addr if self.serverType == "http": flavor=twistedHTTPFlavor( self.verbosity, *self.flavorArgs ) else: flavor=DummyFlavor() p = CeptServerProtocol( flavor, self.verbosity, addr, getHeader=True, getUserid=True ) p.factory = self return p

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main.py

felipedavi/MyBrowserProject

1

67410

<reponame>felipedavi/MyBrowserProject # -*- coding: utf-8 -*- __author__ = "<NAME>" __license__ = "MIT" """home.py: Navegador Open Source """ from PyQt5.QtWidgets import QApplication, QMainWindow,QToolButton, QLineEdit, QMessageBox from PyQt5.QtWebEngineWidgets import QWebEngineView from PyQt5.QtCore import QUrl, QSize from PyQt5.QtGui import QIcon, QPixmap home_url = "https://www.google.com" facebook_url = "https://www.facebook.com" twitter_url = "https://www.twitter.com" youtube_url = "https://www.youtube.com" def home(mainWindow): web.load(QUrl(home_url)) def reload(mainWindow): web.reload() def back(mainWindow): web.back() def forward(mainWindow): web.forward() def go(mainWindow): go_url = go_line.text() web.load(QUrl(go_url)) def facebook(mainWindow): web.load(QUrl(facebook_url)) def twitter(mainWindow): web.load(QUrl(twitter_url)) def youtube(mainWindow): web.load(QUrl(youtube_url)) def download(item): item.accept() msg = QMessageBox() msg.setWindowTitle("DOWNLOAD") msg.setText("O SEU DOWNLOAD FOI INICIALIZADO") msg.setIcon(QMessageBox.Warning) msg.exec_() application = QApplication([]) mainWindow= QMainWindow() mainWindow.setGeometry(0,0,1015,768) mainWindow.setMinimumWidth(1015) mainWindow.setMaximumWidth(1015) mainWindow.setMinimumHeight(768) mainWindow.setMaximumHeight(768) mainWindow.setWindowTitle("MyBrowser") mainWindow.setStyleSheet("background-color:rgb(0,0,0);") mainWindow.setWindowIcon(QIcon("browser.png")) web = QWebEngineView(mainWindow) web.setGeometry(0,30,1015,768) web.setStyleSheet("background-color:rgb(255,255,255);") web.load(QUrl(home_url)) home_button = QToolButton(mainWindow) home_button.setGeometry(10,3,25,25) home_button.setStyleSheet("background-color:transparent;") home_button_icon = QIcon() home_button_icon.addPixmap(QPixmap("home.png")) home_button.setIcon(home_button_icon) home_button.clicked.connect(home) reload_button = QToolButton(mainWindow) reload_button.setGeometry(60,3,25,25) reload_button.setStyleSheet("background-color:transparent;") reload_button_icon = QIcon() reload_button_icon.addPixmap(QPixmap("reload.png")) reload_button.setIcon(reload_button_icon) reload_button.clicked.connect(reload) back_button = QToolButton(mainWindow) back_button.setGeometry(140,3,25,25) back_button.setStyleSheet("background-color:transparent;") back_button_icon = QIcon() back_button_icon.addPixmap(QPixmap("back.png")) back_button.setIcon(back_button_icon) back_button.clicked.connect(back) forward_button = QToolButton(mainWindow) forward_button.setGeometry(180,3,25,25) forward_button.setStyleSheet("background-color:transparent;") forward_button_icon = QIcon() forward_button_icon.addPixmap(QPixmap("forward.png")) forward_button.setIcon(forward_button_icon) forward_button.clicked.connect(forward) go_line = QLineEdit(mainWindow) go_line.setGeometry(280,3,300,25) go_line.setStyleSheet("background-color:rgb(255,255,255);") go_button = QToolButton(mainWindow) go_button.setGeometry(600,3,25,25) go_button.setStyleSheet("background-color:transparent;") go_button_icon = QIcon() go_button_icon.addPixmap(QPixmap("go.png")) go_button.setIcon(go_button_icon) go_button.clicked.connect(go) facebook_button = QToolButton(mainWindow) facebook_button.setGeometry(905,3,50,25) facebook_button.setStyleSheet("background-color:transparent;") facebook_button_icon = QIcon() facebook_button_icon.addPixmap(QPixmap("fb.png")) facebook_button.setIcon(facebook_button_icon) facebook_button.setIconSize(QSize(22,22)) facebook_button.clicked.connect(facebook) twitter_button = QToolButton(mainWindow) twitter_button.setGeometry(940,3,50,25) twitter_button.setStyleSheet("background-color:transparent;") twitter_button_icon = QIcon() twitter_button_icon.addPixmap(QPixmap("tw.png")) twitter_button.setIcon(twitter_button_icon) twitter_button.setIconSize(QSize(22,22)) twitter_button.clicked.connect(twitter) youtube_button = QToolButton(mainWindow) youtube_button.setGeometry(975,3,50,25) youtube_button.setStyleSheet("background-color:transparent;") youtube_button_icon = QIcon() youtube_button_icon.addPixmap(QPixmap("yt.png")) youtube_button.setIcon(youtube_button_icon) youtube_button.setIconSize(QSize(22,22)) youtube_button.clicked.connect(youtube) mainWindow.show() application.exec_()

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podium_api/types/user.py

autosportlabs/podium-api

1

157482

#!/usr/bin/env python # -*- coding: utf-8 -*- class PodiumUser(object): """ Object that represents a particular User. **Attributes:** **user_id** (int): User id **uri** (string): URI for the User. **username** (string): The User's username. **description** (string): The User's description. **avatar_url** (string): User's avatar image url. **links** (list): 3rd party links for the user. **friendships_uri** (string): URI to friends list. **followers_uri** (string): URI to followers list. **friendship_uri** (string): If this User has been friended **events_uri** (string): URI to events for this user **venues_uri** (string): URI to venues this user particiated at by the user this attr will have a value, otherwise None. Defaults to None. """ def __init__(self, user_id, uri, username, description, avatar_url, profile_image_url, links, friendships_uri, followers_uri, friendship_uri, events_uri, venues_uri): self.user_id = user_id self.uri = uri self.username = username self.description = description self.avatar_url = avatar_url self.profile_image_url = profile_image_url self.links = links self.friendships_uri = friendships_uri self.followers_uri = followers_uri self.friendship_uri = friendship_uri self.events_uri = events_uri self.venues_uri = venues_uri def get_user_from_json(json): """ Returns a PodiumUser object from the json dict received from podium api. Args: json (dict): Dict of data from REST api Return: PodiumUser: The PodiumUser object for the data. """ return PodiumUser(json['id'], json['URI'], json['username'], json['description'], json['avatar_url'], json['profile_image_url'], json['links'], json['friendships_uri'], json['followers_uri'], json.get("friendship_uri", None), json['events_uri'], json['venues_uri'] )

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tests/model/library/api/test_casestep_resource.py

Mozilla-GitHub-Standards/2a028a7541b867ed4d376d6d9a172a6885fe44030078c12a2b9428efabf22ab7

0

31114

<reponame>Mozilla-GitHub-Standards/2a028a7541b867ed4d376d6d9a172a6885fe44030078c12a2b9428efabf22ab7 """ Tests for CaseStepResource api. """ from tests.case.api.crud import ApiCrudCases import logging mozlogger = logging.getLogger('moztrap.test') class CaseStepResourceTest(ApiCrudCases): @property def factory(self): """The model factory for this object.""" return self.F.CaseStepFactory() @property def resource_name(self): return "casestep" @property def permission(self): """String defining the permission required for Create, Update, and Delete. """ return "library.manage_cases" @property def new_object_data(self): """Generates a dictionary containing the field names and auto-generated values needed to create a unique object. The output of this method can be sent in the payload parameter of a POST message. """ modifiers = (self.datetime, self.resource_name) self.caseversion_fixture = self.F.CaseVersionFactory.create() fields = { u"caseversion": unicode( self.get_detail_url("caseversion", str(self.caseversion_fixture.id))), u"number": 1, u"instruction": u"instruction 1 %s" % self.datetime, u"expected": u"expected 1 %s" % self.datetime, } return fields def backend_object(self, id): """Returns the object from the backend, so you can query it's values in the database for validation. """ return self.model.CaseStep.everything.get(id=id) def backend_data(self, backend_obj): """Query's the database for the object's current values. Output is a dictionary that should match the result of getting the object's detail via the API, and can be used to verify API output. Note: both keys and data should be in unicode """ actual = { u"id": backend_obj.id, u"caseversion": unicode( self.get_detail_url("caseversion", str(backend_obj.caseversion.id))), u"instruction": unicode(backend_obj.instruction), u"expected": unicode(backend_obj.expected), u"number": backend_obj.number, u"resource_uri": unicode( self.get_detail_url(self.resource_name, str(backend_obj.id))) } return actual @property def read_create_fields(self): """caseversion is read-only""" return ["caseversion"] # overrides from crud.py # additional test cases, if any # validation cases

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split.py

ghukill/bookscanner

0

56640

<reponame>ghukill/bookscanner<gh_stars>0 # split import cv2 from distutils.version import StrictVersion import imutils import logging import matplotlib as plt import numpy as np from PIL import Image import os # setup logger logging.basicConfig(level=logging.DEBUG) # parso shims logging.getLogger('parso.python.diff').disabled = True logging.getLogger('parso.cache').disabled = True logger = logging.getLogger(__name__) def split_page( input_filepath, cross_section_height=20, cross_section_origin='bottom', kernel_size=3, mid_range=None, split_image=True, split_padding=10, delete_original=True): ''' Focus on area roughly in the middle, 1500-2500 - will be better to handle % of image.shape ''' # read image from filepath image = cv2.imread(input_filepath, 0) # make sure double page if image.shape[1] / image.shape[0] > 1.25: # debug metrics = { 'filepath':input_filepath, 'shape':image.shape, } # if cross section None, use full height if cross_section_height == None: cross_section_height = image.shape[0] # set mid-section interval if mid_range == None: logger.debug('determining mid-range pixels') mid_range = [int(image.shape[1]/2 - 200), int(image.shape[1]/2 + 200)] metrics['mid_range'] = mid_range # get section to work with if cross_section_origin == 'top': image_cross_section = image[0:cross_section_height, mid_range[0]:mid_range[1]] elif cross_section_origin == 'bottom': image_cross_section = image[-cross_section_height:image.shape[0], mid_range[0]:mid_range[1]] # get horizontal gradient sobelx = cv2.Sobel( image_cross_section, cv2.CV_64F, 1, 0, ksize=kernel_size ) # sum columns col_sums = np.sum(sobelx, axis=0) # plot # plt.pyplot.plot(col_sums) # get center line cl_index_rel = np.argmax(col_sums) cl_index = mid_range[0] + cl_index_rel metrics['cl_index'] = cl_index # check metrics['halfway_percentage'] = cl_index / image.shape[1] # split image if split_image: # get filename root filename_root, filename_ext = input_filepath.split('/')[-1].split('.') # split left page l_img = image[0:image.shape[0], 0:(cl_index + split_padding)] l_filepath = input_filepath.replace(filename_root, '%s_0' % filename_root) cv2.imwrite(l_filepath, l_img) # split right page r_img = image[0:image.shape[0], (cl_index - split_padding):image.shape[1]] r_filepath = input_filepath.replace(filename_root, '%s_1' % filename_root) cv2.imwrite(r_filepath, r_img) # delete original if delete_original: os.remove(input_filepath) # debug logger.debug(metrics) return metrics else: logger.debug('appears to be single page') return { 'filepath':input_filepath, 'shape':image.shape, }

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Exercicios_entregar/Tarefa_lista2_ex3.py

joao-barabba/Exercicios_Python

0

199480

<reponame>joao-barabba/Exercicios_Python n1=int(input('Digite o primeiro valor: ')) n2=int(input('Digite o segundo valor: ')) o=(input('Digite o operador para conta: ')) if o=='+': r=n1+n2 print(f'O resultado da conta é {r:,}') elif o=='-': r=n1-n2 print(f'O resultado da conta é {r:,}') elif o=='*': r==n1*n2 print(f'O resultado da conta é {r:,}') elif o=='/': r==n1/n2 print(f'O resultado da conta é {r:,}') else: print('Operador não reconhecido ERRO!!!')

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michiru/modules/seenbot.py

moeIO/michiru

1

61981

# Seenbot module. from datetime import datetime import json from michiru import db, personalities from michiru.modules import command, hook _ = personalities.localize ## Module information. __name__ = 'seenbot' __author__ = 'Shiz' __license__ = 'WTFPL' __desc__ = 'Tells when someone was last seen.' ## Database stuff and constants. db.table('seen', { 'id': db.ID, 'server': (db.STRING, db.INDEX), 'nickname': (db.STRING, db.INDEX), 'action': db.INT, 'data': db.STRING, 'time': db.DATETIME }) # The action values. Fake enum. class Actions: JOIN = 0x1 PART = 0x2 QUIT = 0x3 KICK = 0x4 KICKED = 0x5 NICKCHANGE = 0x6 NICKCHANGED = 0x7 MESSAGE = 0x8 NOTICE = 0x9 TOPICCHANGE = 0x10 CTCP = 0x11 ## Utility functions. def timespan(date, current=None, reach=2): """ Calculate human readable timespan. """ if current is None: current = datetime.now() timespans = [ ('millennium', 'millennia', 60*60*24*365*1000), ('century', 'centuries', 60*60*24*365*100), ('decennium', 'decennia', 60*60*24*365*10), ('year', 'years', 60*60*24*365), ('month', 'months', 60*60*24*30), ('week', 'weeks', 60*60*24*7), ('day', 'days', 60*60*24), ('hour', 'hours', 60*60), ('minute', 'minutes', 60), ('second', 'seconds', 1) ] message = None reachstart = None delta = int((current - date).total_seconds()) for i, (singular, plural, seconds) in enumerate(timespans): # Is our time at least one 'unit' worth of this span? if delta >= seconds: # Get the number of units it's worth, and the remainder. n, delta = divmod(delta, seconds) # Append to message. if message is not None: message += ', ' else: reachstart = i message = '' message += '{n} {noun}'.format(n=n, noun=plural if n >= 2 else singular) # Stop if we reached our precision limit. if reachstart is not None and reach is not None and i - reachstart + 1 >= reach: break if message is None: message = 'just now' else: message += ' ago' return message def log(server, nick, what, **data): """ Remove earlier entries for `nick` from database and insert new log entry. """ db.from_('seen').where('nickname', nick.lower()).and_('server', server).delete() db.to('seen').add({ 'server': server, 'nickname': nick.lower(), 'action': what, 'data': json.dumps(data), 'time': datetime.now() }) def meify(bot, nick): if bot.nickname == nick: return 'me' return bot.highlight(nick) ## Commands and hooks. @command(r'seen (\S+)$') @command(r'have you seen (\S+)(?: lately)?\??$') def seen(bot, server, target, source, message, parsed, private, admin): nick = parsed.group(1) # Weed out the odd cases. if nick == source: yield from bot.message(target, _(bot, 'Asking for yourself?', serv=server, nick=nick)) return elif nick == bot.nickname: yield from bot.message(target, _(bot, "I'm right here.", serv=server, nick=nick)) return # Do we have an entry for this nick? entry = db.from_('seen').where('nickname', nick.lower()).and_('server', server).single('action', 'data', 'time') if not entry: yield from bot.message(target, _(bot, "I don't know who {nick} is.", serv=server, nick=meify(bot, nick))) return message = 'I saw {nick} {timeago}, {action}' submessage = None action, raw_data, raw_time = entry data = json.loads(raw_data) time = datetime.strptime(raw_time, db.DATETIME_FORMAT) # Huge if/else chain incoming. if action == Actions.JOIN: submessage = _(bot, 'joining {chan}.', serv=server, **data) elif action == Actions.PART: submessage = _(bot, 'leaving {chan}, with reason "{reason}".', serv=server, **data) elif action == Actions.QUIT: submessage = _(bot, 'disconnecting with reason "{reason}".', serv=server, **data) elif action == Actions.KICK: submessage = _(bot, 'kicking {target} from {chan} with reason "{reason}".', serv=server, **data) elif action == Actions.KICKED: submessage = _(bot, 'getting kicked from {chan} by {kicker} with reason "{reason}".', serv=server, **data) elif action == Actions.NICKCHANGE: submessage = _(bot, 'changing nickname to {newnick}.', serv=server, **data) elif action == Actions.NICKCHANGED: submessage = _(bot, 'changing nickname from {oldnick}.', serv=server, **data) elif action == Actions.MESSAGE: submessage = _(bot, 'telling {chan} "<{nick}> {message}".', serv=server, nick=nick, **data) elif action == Actions.NOTICE: submessage = _(bot, 'noticing {chan} "*{nick}* {message}".', serv=server, nick=nick **data) elif action == Actions.TOPICCHANGE: submessage = _(bot, 'changing topic for {chan} to "{topic}".', serv=server, **data) elif action == Actions.CTCP: submessage = _(bot, 'CTCPing {target} ({message}).', serv=server, **data) else: submessage = _(bot, 'doing something.', serv=server, **data) message = _(bot, message, action=submessage, nick=meify(bot, nick), serv=server, rawtime=time, timeago=timespan(time)) yield from bot.message(target, message) @hook('chat.join') def join(bot, server, channel, who): log(server, who, Actions.JOIN, chan=channel) @hook('chat.part') def part(bot, server, channel, who, reason): log(server, who, Actions.PART, chan=channel, reason=reason) @hook('chat.disconnect') def quit(bot, server, who, reason): log(server, who, Actions.QUIT, reason=reason) @hook('chat.kick') def kick(bot, server, channel, target, by, reason): log(server, by, Actions.KICK, chan=channel, target=meify(bot, target), reason=reason) log(server, target, Actions.KICKED, chan=channel, kicker=meify(bot, by), reason=reason) @hook('chat.nickchange') def nickchange(bot, server, who, to): log(server, who, Actions.NICKCHANGE, newnick=to) log(server, to, Actions.NICKCHANGED, oldnick=who) @hook('chat.message') def message(bot, server, target, who, message, private, admin): if not private: log(server, who, Actions.MESSAGE, chan=target, message=message) @hook('chat.notice') def notice(bot, server, target, who, message, private, admin): if not private: log(server, who, Actions.NOTICE, chan=target, message=message) @hook('chat.topicchange') def topicchange(bot, server, channel, who, topic): log(server, who, Actions.TOPICCHANGE, chan=channel, topic=topic) @hook('irc.ctcp') def ctcp(bot, server, target, who, message): log(server, who, Actions.CTCP, target=meify(bot, target), message=message) ## Boilerplate. def load(): return True def unload(): pass

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preprocessing/preprocess_davis.py

linjieyangsc/video_seg

169

156059

<filename>preprocessing/preprocess_davis.py import os import sys from PIL import Image from sets import Set import numpy as np import cv2 data_dir = sys.argv[1] anno_dir = os.path.join(data_dir, 'Annotations/480p/') save_dir = os.path.join(data_dir, 'Annotations/480p_split/') save_dir_all = os.path.join(data_dir, 'Annotations/480p_all') fds = os.listdir(anno_dir) for fd in fds: im_list = os.listdir(os.path.join(anno_dir, fd)) im_list = [item for item in im_list if item[-3:] == 'png'] im = np.array(Image.open(os.path.join(anno_dir + fd, '00000.png'))) cls_n = im.max() for item in im_list: im_path = os.path.join(anno_dir, fd, item) im = np.array(Image.open(im_path)) all_dir = os.path.join(save_dir_all, fd) if not os.path.exists(all_dir): os.makedirs(all_dir) binary_map = (im > 0) mask_image = (binary_map * 255).astype(np.uint8) cv2.imwrite(os.path.join(all_dir, item), mask_image) for i in range(1, cls_n+1): split_dir = os.path.join(save_dir, fd, str(i)) if not os.path.exists(split_dir): os.makedirs(split_dir) binary_map = im == i mask_image = (binary_map * 255).astype(np.uint8) cv2.imwrite(os.path.join(split_dir, item), mask_image)

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magic_agent/tests/test.py

vypivshiy/magic-agent

0

1617228

import re import unittest from magic_agent.crawlers import Request from magic_agent.crawlers.parsers import RE_CHROMIUM, RE_WEBKIT from magic_agent.core.mobile_keys import SAMSUNG from magic_agent.core.base_device import MobileDevice from magic_agent.core.utils import sattolo_shuffle from magic_agent.core.base import RuleItem, RuleDevice, RuleItemGenerator, BaseAgent, sequence_generator from magic_agent.templates import WindowsChrome, LinuxChrome, RandomApple, RandomAndroid, RandomMobileKey class Test(unittest.TestCase): def test_request_json(self): r = Request.json("https://httpbin.org/get", params={"foo space": "bar"}) self.assertTrue(re.search(r"Python-urllib/\d", r["headers"]["User-Agent"])) self.assertEqual(r["url"], "https://httpbin.org/get?foo space=bar") def test_request_get(self): r = Request.get("https://httpbin.org/get") self.assertTrue(re.search(r"https://httpbin\.org/get", r)) self.assertTrue(re.search(r"Python-urllib/\d", r)) def test_quick_agent_desktop(self): self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Linux" in LinuxChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue("Windows" in WindowsChrome.agent) self.assertTrue(type(WindowsChrome.agent_to_dict) is dict) self.assertTrue(type(LinuxChrome.agent_to_dict) is dict) def test_quick_agent_apple(self): self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) self.assertTrue("iPad" or "iPod" or "iPone" in RandomApple().agent) def test_quick_agent_android(self): self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) self.assertTrue("Android" in RandomAndroid().agent and "Linux" in RandomAndroid().agent) def test_quick_agent_android_key(self): # samsung device name contains SM-xxxxx identification self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) self.assertTrue("SM-" in RandomMobileKey(SAMSUNG).agent) def test_custom_agent_1(self): b = BaseAgent(rules=(RuleItem("Test/1"), RuleDevice(items=["Test, foobar"]))) self.assertEqual(b.agent, "Test/1 (Test, foobar)") self.assertEqual(b.agent, "Test/1 (Test, foobar)") self.assertEqual(b.agent, "Test/1 (Test, foobar)") def test_rule_item(self): self.assertEqual(RuleItem("Test/1").get(), "Test/1") self.assertEqual(RuleItem("Test/1").get(), "Test/1") self.assertEqual(RuleItem("Test/1").get(), "Test/1") def test_rule_generator(self): t = sequence_generator(["Test/1"]) self.assertEqual(RuleItemGenerator("foo {}", t).get(), "foo Test/1") self.assertEqual(RuleItemGenerator("foo {}", t).get(), "foo Test/1") def test_parse_mobile(self): test_dict = \ {"model": "Test Mobile", "model_id": ["T123"], "released": 2077, "operating_system": "Palm OS T", "resolution": {"height": 1, "wight": 2}, "market_regions": ["Kekistan", "SovietRussia"], "codename": "TestCase", "oem_id": "foobar", "platform": "Android", "market_countries": ["KEK", "USSR"], "battery_capacity": 99_999} b = MobileDevice(**test_dict) self.assertEqual(b.model, "Test Mobile") self.assertEqual(b.model_id[0], "T123") self.assertEqual(b.market_regions, ["Kekistan", "SovietRussia"]) def test_device_agent(self): test_dict = \ {"model": "Test Mobile", "model_id": ["T123"], "released": 2077, "operating_system": "Android 10.0", "resolution": {"height": 1, "wight": 2}, "market_regions": ["Kekistan", "SovietRussia"], "codename": "TestCase", "oem_id": "foobar", "platform": "Android", "market_countries": ["KEK", "USSR"], "battery_capacity": 99_999} b = MobileDevice(**test_dict) self.assertTrue("(Linux; Android 10.0; T123)" in b.agent.agent) def test_satollo_shuffle(self): seq = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] seq_2 = seq.copy() seq_2 = sattolo_shuffle(seq_2) self.assertNotEqual(seq_2, seq) def test_versions_parsers(self): resp_webkit = """ <tr class="odd f5" id="f5"> <td class="name"> <span class="expander" title="..." href="/browser/webkit/tags/Safari-532.4">Safari-532.4</a> ... <td class="age" style="border-color: rgb(152,136,238)"> ... </td> .... blah blah blah """ resp_chrome = """ <li class="RefList-item"><a href="/chromium/src/+/refs/tags/99.0.4817.1">99.0.4817.1</a></li> <li class="RefList-item"><a href="/chromium/src/+/refs/tags/fobbar">bad-string-1.0</a></li> .... blah blah blah """ r = RE_CHROMIUM.findall(resp_chrome) self.assertEqual(r[0], '99.0.4817.1') self.assertEqual(len(RE_CHROMIUM.findall(resp_webkit)), 0) r = RE_WEBKIT.findall(resp_webkit) self.assertEqual(r[0], '532.4') self.assertEqual(len(RE_WEBKIT.findall(resp_chrome)), 0)

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vendas/urls.py

rauanisanfelice/espetaria

0

87292

from django.contrib import admin from django.urls import path, include from django.contrib.auth import views as auth_views from .views import * urlpatterns = [ path('', index.as_view(), name='lancamento'), # MESAS path('mesa-list/', MesaList.as_view(), name='mesa_list'), path('mesa-new/', MesaNew.as_view(), name='mesa_new'), path('mesa-end/', MesaEnd.as_view(), name='mesa_end'), path('mesa-add-produto/', MesaAddProduto, name='mesa_add_produto'), path('mesa-detail/<int:id_mesa>/', MesaDetail, name='mesa_detail'), path('mesa-end/<int:id_mesa>/', MesaEnd.as_view(), name='mesa_end'), # PRODUTOS path('produto-list/',ProdutoList.as_view(), name='produto_list'), path('produto-novo/',ProdutoNew.as_view(), name='produto_new'), path('produto-dell/<int:id_produto>/',ProdutoDell, name='produto_dell'), path('produto-edit/<int:id_produto>/',ProdutoEdit.as_view(), name='produto_edit'), # REPORTS path('reports/', Reports.as_view(), name='reports'), path('reports-hist/', Reports_hist.as_view(), name='reports_hist'), path('dash-hist/', Dash_Historico, name='dash_hist'), path('reports-comparativo/', Reports_comp.as_view(), name='reports_comp'), path('dash-comp-pizza/', Dash_Comparativo_Pizza, name='dash_comp_pizza'), ]

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indra/sources/geneways/processor.py

zebulon2/indra

136

151473

""" This module provides an input processor for information extracted using the Geneways software suite, converting extraction data in Geneways format into INDRA statements. See publication: Rzhetsky, Andrey, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME> et al. "GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data." Journal of biomedical informatics 37, no. 1 (2004): 43-53. """ from indra.statements import Evidence, Agent import indra.databases.hgnc_client as hgc from indra.literature import * from indra.statements import Complex, Phosphorylation from indra.ontology.standardize import \ standardize_agent_name from indra.sources.geneways.action_parser import GenewaysActionParser try: from indra.sources.geneways.find_full_text_sentence import FullTextMention get_ft_mention = True except ImportError: logger.error('Install the nltk and stemming packages to extract full ' 'text evidence for Geneways mentions.') get_ft_mention = False logger = logging.getLogger(__name__) # This will take in an action and action mention and create a single statement class GenewaysProcessor(object): """The GenewaysProcessors converts extracted Geneways action mentions into INDRA statements. Parameters ---------- search_path : list[str] A list of directories in which to search for Geneways data Attributes ---------- statements : list[indra.statements.Statement] A list of INDRA statements converted from Geneways action mentions, populated by calling the constructor """ def __init__(self, search_path, get_evidence=True): if get_evidence and get_ft_mention: self.get_ft_mention = True else: self.get_ft_mention = False # Parse Geneways data. Will give an error if it can't find # the Geneways data logger.info('Loading Geneways extractions') parser = GenewaysActionParser(search_path) logger.info('Geneways extractions loaded') actions = parser.actions # Make a list of statements from the actions self.statements = [] for action in actions: for mention in action.action_mentions: if mention.negative != '1': new_statement = self.make_statement(action, mention) if new_statement is not None: self.statements.append(new_statement) def make_statement(self, action, mention): """Makes an INDRA statement from a Geneways action and action mention. Parameters ---------- action : GenewaysAction The mechanism that the Geneways mention maps to. Note that several text mentions can correspond to the same action if they are referring to the same relationship - there may be multiple Geneways action mentions corresponding to each action. mention : GenewaysActionMention The Geneways action mention object corresponding to a single mention of a mechanism in a specific text. We make a new INDRA statement corresponding to each action mention. Returns ------- statement : indra.statements.Statement An INDRA statement corresponding to the provided Geneways action mention, or None if the action mention's type does not map onto any INDRA statement type in geneways_action_type_mapper. """ (statement_generator, is_direct) = \ geneways_action_to_indra_statement_type(mention.actiontype, action.plo) if statement_generator is None: # Geneways statement does not map onto an indra statement return None # Try to find the full-text sentence # Unfortunately, the sentence numbers in the Geneways dataset # don't correspond to an obvious sentence segmentation. # This code looks for sentences with the subject, object, and verb # listed by the Geneways action mention table and only includes # it in the evidence if there is exactly one such sentence text = None if self.get_ft_mention: try: content, content_type = get_full_text(mention.pmid, 'pmid') if content is not None: ftm = FullTextMention(mention, content) sentences = ftm.find_matching_sentences() if len(sentences) == 1: text = sentences[0] except Exception: logger.warning('Could not fetch full text for PMID ' + mention.pmid) # Make an evidence object epistemics = dict() epistemics['direct'] = is_direct annotations = mention.make_annotation() annotations['plo'] = action.plo # plo only in action table evidence = Evidence(source_api='geneways', source_id=mention.actionmentionid, pmid=mention.pmid, text=text, epistemics=epistemics, annotations=annotations) # Construct the grounded and name standardized agents # Note that this involves grounding the agent by # converting the Entrez ID listed in the Geneways data with # HGNC and UniProt upstream_agent = get_agent(mention.upstream, action.up) downstream_agent = get_agent(mention.downstream, action.dn) # Make the statement return statement_generator(upstream_agent, downstream_agent, evidence) def get_agent(raw_name, entrez_id): db_refs = {'TEXT': raw_name, 'EGID': entrez_id} logger.debug('Looking up grounding data for Entrez #%s' % entrez_id) hgnc_id = hgc.get_hgnc_from_entrez(entrez_id) if hgnc_id: db_refs['HGNC'] = hgnc_id agent = Agent(raw_name, db_refs=db_refs) standardize_agent_name(agent, standardize_refs=True) return agent def geneways_action_to_indra_statement_type(actiontype, plo): """Return INDRA Statement corresponding to Geneways action type. Parameters ---------- actiontype : str The verb extracted by the Geneways processor plo : str A one character string designating whether Geneways classifies this verb as a physical, logical, or other interaction Returns ------- statement_generator : If there is no mapping to INDRA statements from this action type the return value is None. If there is such a mapping, statement_generator is an anonymous function that takes in the subject agent, object agent, and evidence, in that order, and returns an INDRA statement object. """ actiontype = actiontype.lower() statement_generator = None is_direct = (plo == 'P') if actiontype == 'bind': statement_generator = lambda substance1, substance2, evidence: \ Complex([substance1, substance2], evidence=evidence) is_direct = True elif actiontype == 'phosphorylate': statement_generator = lambda substance1, substance2, evidence: \ Phosphorylation(substance1, substance2, evidence=evidence) is_direct = True return (statement_generator, is_direct)

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grid-dataset/training_data.py

tuantran1810/lips-image-generation

1

199343

<gh_stars>1-10 import os import cv2 import pickle import numpy as np from scipy.io import wavfile from pathlib import Path import librosa class TrainingDataConverter: def __init__( self, videoRootFolder, audioRootFolder, videoExt, audioExt, outputfolder, ): self.__paths = dict() totalvideo = 0 identity_set = set() for path, _ , files in os.walk(videoRootFolder): for name in files: code, ext = name.split('.') if ext == videoExt: identity = path.split('/')[-1] if identity not in self.__paths: self.__paths[identity] = dict() idmap = self.__paths[identity] idmap[code] = dict() idmap[code]['video'] = os.path.join(path, name) totalvideo += 1 identity_set.add(identity) for identity in identity_set: audio_identity = os.path.join(outputfolder, identity) Path(audio_identity).mkdir(parents=True, exist_ok=True) totalaudio = 0 for path, _ , files in os.walk(audioRootFolder): for name in files: code, ext = name.split('.') if ext == audioExt: path_parts = path.split('/') identity = path_parts[-1] training_path = os.path.join(outputfolder, identity) if identity not in self.__paths: print(f"identity {identity} not found, ignore") continue idmap = self.__paths[identity] if code not in idmap: continue idmap[code]['audio'] = os.path.join(path, name) idmap[code]['training'] = os.path.join(training_path, code + '.' + 'pkl') totalaudio += 1 # print(self.__paths) print(f"total audio = {totalaudio}, total video = {totalvideo}") def __iterate_frames(self, videofile): vidcap = cv2.VideoCapture(videofile) while True: success, image = vidcap.read() if not success: return if image is None: print("image is None") yield image def __audio_logmel_segments(self, wave, n_fft = 1024, n_mels = 128, fsampling = 44100, nsegments = 75): wave = wave.astype(float) wave_length = wave.shape[0] chunk_length = int(wave_length/nsegments) for i in range(0, nsegments): chunk = wave[(i*chunk_length):((i+1)*chunk_length)] s = librosa.feature.melspectrogram(chunk, sr = fsampling, n_fft = n_fft, n_mels = n_mels, fmax = 16000) yield librosa.amplitude_to_db(s) def run(self): for _, content in self.__paths.items(): for _, info in content.items(): video_path = info['video'] audio_path = info['audio'] training_path = info['training'] frames = np.stack( [f for f in map( lambda x: np.transpose(x, (2, 1, 0)), self.__iterate_frames(video_path), )], axis = 0, ) _, wave = wavfile.read(audio_path) audio_logmel = np.stack( [f for f in self.__audio_logmel_segments(wave)], axis = 0, ) data = dict() data['video'] = frames data['audio'] = audio_logmel return with open(training_path, 'wb') as fd: pickle.dump(data, fd) print(training_path) def main(): conv = TrainingDataConverter( "/media/tuantran/raid-data/dataset/GRID/mouth_videos", "/media/tuantran/raid-data/dataset/GRID/audio", "mp4", "wav", "/media/tuantran/raid-data/dataset/GRID/mouth_images", ) conv.run() if __name__ == "__main__": main()

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vegaapiclient/generated/data_node/api/v1/trading_data_pb2_grpc.py

vegaprotocol/sdk-python

1

1604191

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from ...api.v1 import trading_data_pb2 as data__node_dot_api_dot_v1_dot_trading__data__pb2 class TradingDataServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.MarketAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.FromString, ) self.PartyAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.FromString, ) self.FeeInfrastructureAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/FeeInfrastructureAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.FromString, ) self.GlobalRewardPoolAccounts = channel.unary_unary( '/datanode.api.v1.TradingDataService/GlobalRewardPoolAccounts', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.FromString, ) self.Candles = channel.unary_unary( '/datanode.api.v1.TradingDataService/Candles', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.FromString, ) self.MarketDataByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketDataByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.FromString, ) self.MarketsData = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketsData', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.FromString, ) self.MarketByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.FromString, ) self.MarketDepth = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarketDepth', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.FromString, ) self.Markets = channel.unary_unary( '/datanode.api.v1.TradingDataService/Markets', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.FromString, ) self.OrderByMarketAndID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByMarketAndID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.FromString, ) self.OrderByReference = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByReference', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.FromString, ) self.OrdersByMarket = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrdersByMarket', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.FromString, ) self.OrdersByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrdersByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.FromString, ) self.OrderByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.FromString, ) self.OrderVersionsByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/OrderVersionsByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.FromString, ) self.MarginLevels = channel.unary_unary( '/datanode.api.v1.TradingDataService/MarginLevels', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.FromString, ) self.Parties = channel.unary_unary( '/datanode.api.v1.TradingDataService/Parties', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.FromString, ) self.PartyByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.FromString, ) self.PositionsByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/PositionsByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.FromString, ) self.LastTrade = channel.unary_unary( '/datanode.api.v1.TradingDataService/LastTrade', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.FromString, ) self.TradesByMarket = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByMarket', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.FromString, ) self.TradesByOrder = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByOrder', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.FromString, ) self.TradesByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/TradesByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.FromString, ) self.GetProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.FromString, ) self.GetProposalsByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalsByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.FromString, ) self.GetVotesByParty = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetVotesByParty', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.FromString, ) self.GetNewMarketProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewMarketProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.FromString, ) self.GetUpdateMarketProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetUpdateMarketProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.FromString, ) self.GetNetworkParametersProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNetworkParametersProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.FromString, ) self.GetNewAssetProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewAssetProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.FromString, ) self.GetNewFreeformProposals = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNewFreeformProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.FromString, ) self.GetProposalByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.FromString, ) self.GetProposalByReference = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetProposalByReference', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.FromString, ) self.ObserveGovernance = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveGovernance', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.FromString, ) self.ObservePartyProposals = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObservePartyProposals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.FromString, ) self.ObservePartyVotes = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObservePartyVotes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.FromString, ) self.ObserveProposalVotes = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveProposalVotes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.FromString, ) self.ObserveEventBus = channel.stream_stream( '/datanode.api.v1.TradingDataService/ObserveEventBus', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.FromString, ) self.GetNodeData = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeData', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.FromString, ) self.GetNodes = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodes', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.FromString, ) self.GetNodeByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.FromString, ) self.GetKeyRotations = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetKeyRotations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.FromString, ) self.GetKeyRotationsByNode = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetKeyRotationsByNode', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.FromString, ) self.GetEpoch = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetEpoch', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.FromString, ) self.GetVegaTime = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetVegaTime', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.FromString, ) self.AccountsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/AccountsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.FromString, ) self.CandlesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/CandlesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.FromString, ) self.MarginLevelsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarginLevelsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.FromString, ) self.MarketDepthSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketDepthSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.FromString, ) self.MarketDepthUpdatesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketDepthUpdatesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.FromString, ) self.MarketsDataSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/MarketsDataSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.FromString, ) self.OrdersSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/OrdersSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.FromString, ) self.PositionsSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/PositionsSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.FromString, ) self.TradesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/TradesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.FromString, ) self.TransferResponsesSubscribe = channel.unary_stream( '/datanode.api.v1.TradingDataService/TransferResponsesSubscribe', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.FromString, ) self.GetNodeSignaturesAggregate = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetNodeSignaturesAggregate', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.FromString, ) self.AssetByID = channel.unary_unary( '/datanode.api.v1.TradingDataService/AssetByID', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.FromString, ) self.Assets = channel.unary_unary( '/datanode.api.v1.TradingDataService/Assets', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.FromString, ) self.EstimateFee = channel.unary_unary( '/datanode.api.v1.TradingDataService/EstimateFee', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.FromString, ) self.EstimateMargin = channel.unary_unary( '/datanode.api.v1.TradingDataService/EstimateMargin', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.FromString, ) self.ERC20WithdrawalApproval = channel.unary_unary( '/datanode.api.v1.TradingDataService/ERC20WithdrawalApproval', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.FromString, ) self.Withdrawal = channel.unary_unary( '/datanode.api.v1.TradingDataService/Withdrawal', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.FromString, ) self.Withdrawals = channel.unary_unary( '/datanode.api.v1.TradingDataService/Withdrawals', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.FromString, ) self.Deposit = channel.unary_unary( '/datanode.api.v1.TradingDataService/Deposit', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.FromString, ) self.Deposits = channel.unary_unary( '/datanode.api.v1.TradingDataService/Deposits', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.FromString, ) self.NetworkParameters = channel.unary_unary( '/datanode.api.v1.TradingDataService/NetworkParameters', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.FromString, ) self.LiquidityProvisions = channel.unary_unary( '/datanode.api.v1.TradingDataService/LiquidityProvisions', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.FromString, ) self.OracleSpec = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleSpec', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.FromString, ) self.OracleSpecs = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleSpecs', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.FromString, ) self.OracleDataBySpec = channel.unary_unary( '/datanode.api.v1.TradingDataService/OracleDataBySpec', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.FromString, ) self.ObserveRewards = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveRewards', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.FromString, ) self.GetRewards = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetRewards', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.FromString, ) self.GetRewardSummaries = channel.unary_unary( '/datanode.api.v1.TradingDataService/GetRewardSummaries', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.FromString, ) self.Checkpoints = channel.unary_unary( '/datanode.api.v1.TradingDataService/Checkpoints', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.FromString, ) self.Delegations = channel.unary_unary( '/datanode.api.v1.TradingDataService/Delegations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.FromString, ) self.ObserveDelegations = channel.unary_stream( '/datanode.api.v1.TradingDataService/ObserveDelegations', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.FromString, ) self.PartyStake = channel.unary_unary( '/datanode.api.v1.TradingDataService/PartyStake', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.FromString, ) self.Transfers = channel.unary_unary( '/datanode.api.v1.TradingDataService/Transfers', request_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersRequest.SerializeToString, response_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersResponse.FromString, ) class TradingDataServiceServicer(object): """Missing associated documentation comment in .proto file.""" def MarketAccounts(self, request, context): """-- Accounts -- Get a list of Accounts by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyAccounts(self, request, context): """Get a list of Accounts by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def FeeInfrastructureAccounts(self, request, context): """Get a list of accounts holding infrastructure fees. Can be filtered by asset, there will be 1 infrastructure fee account per asset in the network. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GlobalRewardPoolAccounts(self, request, context): """Get a list of accounts holding reward pools Can be filtered by asset, there will be 1 reward pool account per asset in the network. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Candles(self, request, context): """-- Candles -- Get a list of Candles by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDataByID(self, request, context): """-- Market Data -- Get Market Data by Market ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketsData(self, request, context): """Get a list of Market Data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketByID(self, request, context): """-- Markets -- Get a Market by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepth(self, request, context): """Get Market Depth """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Markets(self, request, context): """Get a list of Markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByMarketAndID(self, request, context): """-- Orders -- Get an Order by Market and Order ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByReference(self, request, context): """Get an Order by Pending Order reference (UUID) """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersByMarket(self, request, context): """Get a list of Orders by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersByParty(self, request, context): """Get a list of Orders by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderByID(self, request, context): """Get a specific order by order ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrderVersionsByID(self, request, context): """Get all versions of the order by its orderID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarginLevels(self, request, context): """-- Parties -- Get Margin Levels by Party ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Parties(self, request, context): """Get a list of Parties """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyByID(self, request, context): """Get a Party by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PositionsByParty(self, request, context): """-- Positions -- Get a list of Positions by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def LastTrade(self, request, context): """-- Trades -- Get latest Trade """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByMarket(self, request, context): """Get a list of Trades by Market """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByOrder(self, request, context): """Get a list of Trades by Order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesByParty(self, request, context): """Get a list of Trades by Party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposals(self, request, context): """-- Governance -- Get governance data (proposals and votes) for all proposals """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalsByParty(self, request, context): """Get governance data (proposals and votes) for proposals by party authoring them """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVotesByParty(self, request, context): """Get votes by party casting them """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewMarketProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim creating new markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetUpdateMarketProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim updating markets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNetworkParametersProposals(self, request, context): """Get governance data (proposals and votes) for proposals that aim updating Vega network parameters """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewAssetProposals(self, request, context): """Get governance data (proposals and votes) for proposals aiming to create new assets """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNewFreeformProposals(self, request, context): """Get governance data (proposals and votes) for proposals aiming to create freeform proposals """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalByID(self, request, context): """Get governance data (proposals and votes) for a proposal located by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetProposalByReference(self, request, context): """Get governance data (proposals and votes) for a proposal located by reference """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveGovernance(self, request, context): """Subscribe to a stream of all governance updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObservePartyProposals(self, request, context): """Subscribe to a stream of proposal updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObservePartyVotes(self, request, context): """Subscribe to a stream of votes cast by a specific party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveProposalVotes(self, request, context): """Subscribe to a stream of proposal votes """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveEventBus(self, request_iterator, context): """Subscribe to a stream of events from the core """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeData(self, request, context): """-- Validators -- Get data of current node """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodes(self, request, context): """List all known network nodes """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeByID(self, request, context): """Get a specific node by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetKeyRotations(self, request, context): """Get all key rotations """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetKeyRotationsByNode(self, request, context): """Get all key rotations by node """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetEpoch(self, request, context): """Get data for a specific epoch, if id omitted it gets the current epoch """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetVegaTime(self, request, context): """-- Misc -- Get Time """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AccountsSubscribe(self, request, context): """Subscribe to a stream of Accounts """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CandlesSubscribe(self, request, context): """Subscribe to a stream of Candles """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarginLevelsSubscribe(self, request, context): """Subscribe to a stream of Margin Levels """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepthSubscribe(self, request, context): """Subscribe to a stream of Market Depth """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketDepthUpdatesSubscribe(self, request, context): """Subscribe to a stream of Market Depth Price Level Updates """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MarketsDataSubscribe(self, request, context): """Subscribe to a stream of Markets Data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OrdersSubscribe(self, request, context): """Subscribe to a stream of Orders """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PositionsSubscribe(self, request, context): """Subscribe to a stream of Positions """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TradesSubscribe(self, request, context): """Subscribe to a stream of Trades """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TransferResponsesSubscribe(self, request, context): """Subscribe to a stream of Transfer Responses """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetNodeSignaturesAggregate(self, request, context): """Get an aggregate of signatures from all the nodes of the network """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AssetByID(self, request, context): """Get an asset by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Assets(self, request, context): """Get a list of all assets on Vega """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def EstimateFee(self, request, context): """Get an estimate for the fee to be paid for a given order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def EstimateMargin(self, request, context): """Get an estimate for the margin required for a new order """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ERC20WithdrawalApproval(self, request, context): """Get the bundle approval for an ERC20 withdrawal, these data are being used to bundle the call to the smart contract on the ethereum bridge """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Withdrawal(self, request, context): """Get a withdrawal by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Withdrawals(self, request, context): """Get withdrawals for a party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Deposit(self, request, context): """Get a deposit by its identifier """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Deposits(self, request, context): """Get deposits for a party """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def NetworkParameters(self, request, context): """Get the network parameters """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def LiquidityProvisions(self, request, context): """Get the liquidity provision orders """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleSpec(self, request, context): """Get an oracle spec by ID """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleSpecs(self, request, context): """Get the oracle specs """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def OracleDataBySpec(self, request, context): """Get all oracle data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveRewards(self, request, context): """subscribe to rewards """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetRewards(self, request, context): """Get rewards """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetRewardSummaries(self, request, context): """Get reward summaries """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Checkpoints(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Delegations(self, request, context): """Get delegation data """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ObserveDelegations(self, request, context): """subscribe to delegation events """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def PartyStake(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Transfers(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_TradingDataServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'MarketAccounts': grpc.unary_unary_rpc_method_handler( servicer.MarketAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.SerializeToString, ), 'PartyAccounts': grpc.unary_unary_rpc_method_handler( servicer.PartyAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.SerializeToString, ), 'FeeInfrastructureAccounts': grpc.unary_unary_rpc_method_handler( servicer.FeeInfrastructureAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.SerializeToString, ), 'GlobalRewardPoolAccounts': grpc.unary_unary_rpc_method_handler( servicer.GlobalRewardPoolAccounts, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.SerializeToString, ), 'Candles': grpc.unary_unary_rpc_method_handler( servicer.Candles, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.SerializeToString, ), 'MarketDataByID': grpc.unary_unary_rpc_method_handler( servicer.MarketDataByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.SerializeToString, ), 'MarketsData': grpc.unary_unary_rpc_method_handler( servicer.MarketsData, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.SerializeToString, ), 'MarketByID': grpc.unary_unary_rpc_method_handler( servicer.MarketByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.SerializeToString, ), 'MarketDepth': grpc.unary_unary_rpc_method_handler( servicer.MarketDepth, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.SerializeToString, ), 'Markets': grpc.unary_unary_rpc_method_handler( servicer.Markets, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.SerializeToString, ), 'OrderByMarketAndID': grpc.unary_unary_rpc_method_handler( servicer.OrderByMarketAndID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.SerializeToString, ), 'OrderByReference': grpc.unary_unary_rpc_method_handler( servicer.OrderByReference, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.SerializeToString, ), 'OrdersByMarket': grpc.unary_unary_rpc_method_handler( servicer.OrdersByMarket, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.SerializeToString, ), 'OrdersByParty': grpc.unary_unary_rpc_method_handler( servicer.OrdersByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.SerializeToString, ), 'OrderByID': grpc.unary_unary_rpc_method_handler( servicer.OrderByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.SerializeToString, ), 'OrderVersionsByID': grpc.unary_unary_rpc_method_handler( servicer.OrderVersionsByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.SerializeToString, ), 'MarginLevels': grpc.unary_unary_rpc_method_handler( servicer.MarginLevels, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.SerializeToString, ), 'Parties': grpc.unary_unary_rpc_method_handler( servicer.Parties, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.SerializeToString, ), 'PartyByID': grpc.unary_unary_rpc_method_handler( servicer.PartyByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.SerializeToString, ), 'PositionsByParty': grpc.unary_unary_rpc_method_handler( servicer.PositionsByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.SerializeToString, ), 'LastTrade': grpc.unary_unary_rpc_method_handler( servicer.LastTrade, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.SerializeToString, ), 'TradesByMarket': grpc.unary_unary_rpc_method_handler( servicer.TradesByMarket, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.SerializeToString, ), 'TradesByOrder': grpc.unary_unary_rpc_method_handler( servicer.TradesByOrder, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.SerializeToString, ), 'TradesByParty': grpc.unary_unary_rpc_method_handler( servicer.TradesByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.SerializeToString, ), 'GetProposals': grpc.unary_unary_rpc_method_handler( servicer.GetProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.SerializeToString, ), 'GetProposalsByParty': grpc.unary_unary_rpc_method_handler( servicer.GetProposalsByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.SerializeToString, ), 'GetVotesByParty': grpc.unary_unary_rpc_method_handler( servicer.GetVotesByParty, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.SerializeToString, ), 'GetNewMarketProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewMarketProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.SerializeToString, ), 'GetUpdateMarketProposals': grpc.unary_unary_rpc_method_handler( servicer.GetUpdateMarketProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.SerializeToString, ), 'GetNetworkParametersProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNetworkParametersProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.SerializeToString, ), 'GetNewAssetProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewAssetProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.SerializeToString, ), 'GetNewFreeformProposals': grpc.unary_unary_rpc_method_handler( servicer.GetNewFreeformProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.SerializeToString, ), 'GetProposalByID': grpc.unary_unary_rpc_method_handler( servicer.GetProposalByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.SerializeToString, ), 'GetProposalByReference': grpc.unary_unary_rpc_method_handler( servicer.GetProposalByReference, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.SerializeToString, ), 'ObserveGovernance': grpc.unary_stream_rpc_method_handler( servicer.ObserveGovernance, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.SerializeToString, ), 'ObservePartyProposals': grpc.unary_stream_rpc_method_handler( servicer.ObservePartyProposals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.SerializeToString, ), 'ObservePartyVotes': grpc.unary_stream_rpc_method_handler( servicer.ObservePartyVotes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.SerializeToString, ), 'ObserveProposalVotes': grpc.unary_stream_rpc_method_handler( servicer.ObserveProposalVotes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.SerializeToString, ), 'ObserveEventBus': grpc.stream_stream_rpc_method_handler( servicer.ObserveEventBus, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.SerializeToString, ), 'GetNodeData': grpc.unary_unary_rpc_method_handler( servicer.GetNodeData, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.SerializeToString, ), 'GetNodes': grpc.unary_unary_rpc_method_handler( servicer.GetNodes, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.SerializeToString, ), 'GetNodeByID': grpc.unary_unary_rpc_method_handler( servicer.GetNodeByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.SerializeToString, ), 'GetKeyRotations': grpc.unary_unary_rpc_method_handler( servicer.GetKeyRotations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.SerializeToString, ), 'GetKeyRotationsByNode': grpc.unary_unary_rpc_method_handler( servicer.GetKeyRotationsByNode, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.SerializeToString, ), 'GetEpoch': grpc.unary_unary_rpc_method_handler( servicer.GetEpoch, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.SerializeToString, ), 'GetVegaTime': grpc.unary_unary_rpc_method_handler( servicer.GetVegaTime, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.SerializeToString, ), 'AccountsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.AccountsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.SerializeToString, ), 'CandlesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.CandlesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.SerializeToString, ), 'MarginLevelsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarginLevelsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.SerializeToString, ), 'MarketDepthSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketDepthSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.SerializeToString, ), 'MarketDepthUpdatesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketDepthUpdatesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.SerializeToString, ), 'MarketsDataSubscribe': grpc.unary_stream_rpc_method_handler( servicer.MarketsDataSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.SerializeToString, ), 'OrdersSubscribe': grpc.unary_stream_rpc_method_handler( servicer.OrdersSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.SerializeToString, ), 'PositionsSubscribe': grpc.unary_stream_rpc_method_handler( servicer.PositionsSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.SerializeToString, ), 'TradesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.TradesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.SerializeToString, ), 'TransferResponsesSubscribe': grpc.unary_stream_rpc_method_handler( servicer.TransferResponsesSubscribe, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.SerializeToString, ), 'GetNodeSignaturesAggregate': grpc.unary_unary_rpc_method_handler( servicer.GetNodeSignaturesAggregate, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.SerializeToString, ), 'AssetByID': grpc.unary_unary_rpc_method_handler( servicer.AssetByID, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.SerializeToString, ), 'Assets': grpc.unary_unary_rpc_method_handler( servicer.Assets, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.SerializeToString, ), 'EstimateFee': grpc.unary_unary_rpc_method_handler( servicer.EstimateFee, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.SerializeToString, ), 'EstimateMargin': grpc.unary_unary_rpc_method_handler( servicer.EstimateMargin, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.SerializeToString, ), 'ERC20WithdrawalApproval': grpc.unary_unary_rpc_method_handler( servicer.ERC20WithdrawalApproval, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.SerializeToString, ), 'Withdrawal': grpc.unary_unary_rpc_method_handler( servicer.Withdrawal, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.SerializeToString, ), 'Withdrawals': grpc.unary_unary_rpc_method_handler( servicer.Withdrawals, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.SerializeToString, ), 'Deposit': grpc.unary_unary_rpc_method_handler( servicer.Deposit, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.SerializeToString, ), 'Deposits': grpc.unary_unary_rpc_method_handler( servicer.Deposits, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.SerializeToString, ), 'NetworkParameters': grpc.unary_unary_rpc_method_handler( servicer.NetworkParameters, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.SerializeToString, ), 'LiquidityProvisions': grpc.unary_unary_rpc_method_handler( servicer.LiquidityProvisions, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.SerializeToString, ), 'OracleSpec': grpc.unary_unary_rpc_method_handler( servicer.OracleSpec, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.SerializeToString, ), 'OracleSpecs': grpc.unary_unary_rpc_method_handler( servicer.OracleSpecs, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.SerializeToString, ), 'OracleDataBySpec': grpc.unary_unary_rpc_method_handler( servicer.OracleDataBySpec, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.SerializeToString, ), 'ObserveRewards': grpc.unary_stream_rpc_method_handler( servicer.ObserveRewards, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.SerializeToString, ), 'GetRewards': grpc.unary_unary_rpc_method_handler( servicer.GetRewards, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.SerializeToString, ), 'GetRewardSummaries': grpc.unary_unary_rpc_method_handler( servicer.GetRewardSummaries, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.SerializeToString, ), 'Checkpoints': grpc.unary_unary_rpc_method_handler( servicer.Checkpoints, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.SerializeToString, ), 'Delegations': grpc.unary_unary_rpc_method_handler( servicer.Delegations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.SerializeToString, ), 'ObserveDelegations': grpc.unary_stream_rpc_method_handler( servicer.ObserveDelegations, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.SerializeToString, ), 'PartyStake': grpc.unary_unary_rpc_method_handler( servicer.PartyStake, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.SerializeToString, ), 'Transfers': grpc.unary_unary_rpc_method_handler( servicer.Transfers, request_deserializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersRequest.FromString, response_serializer=data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'datanode.api.v1.TradingDataService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class TradingDataService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def MarketAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def FeeInfrastructureAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/FeeInfrastructureAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.FeeInfrastructureAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GlobalRewardPoolAccounts(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GlobalRewardPoolAccounts', data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GlobalRewardPoolAccountsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Candles(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Candles', data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDataByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketDataByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDataByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketsData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketsData', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepth(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarketDepth', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Markets(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Markets', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByMarketAndID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByMarketAndID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByMarketAndIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByReference(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByReference', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByReferenceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersByMarket(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrdersByMarket', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByMarketResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrdersByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrderVersionsByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OrderVersionsByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrderVersionsByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarginLevels(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/MarginLevels', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Parties(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Parties', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartiesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PositionsByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PositionsByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def LastTrade(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/LastTrade', data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.LastTradeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByMarket(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByMarket', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByMarketResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByOrder(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByOrder', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByOrderResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/TradesByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalsByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalsByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalsByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetVotesByParty(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetVotesByParty', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVotesByPartyResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewMarketProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewMarketProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewMarketProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetUpdateMarketProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetUpdateMarketProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetUpdateMarketProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNetworkParametersProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNetworkParametersProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNetworkParametersProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewAssetProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewAssetProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewAssetProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNewFreeformProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNewFreeformProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNewFreeformProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetProposalByReference(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetProposalByReference', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetProposalByReferenceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveGovernance(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveGovernance', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveGovernanceResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObservePartyProposals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObservePartyProposals', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyProposalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObservePartyVotes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObservePartyVotes', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObservePartyVotesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveProposalVotes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveProposalVotes', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveProposalVotesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveEventBus(request_iterator, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.stream_stream(request_iterator, target, '/datanode.api.v1.TradingDataService/ObserveEventBus', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveEventBusResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeData(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeData', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeDataResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodes(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodes', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetKeyRotations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetKeyRotations', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetKeyRotationsByNode(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetKeyRotationsByNode', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetKeyRotationsByNodeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetEpoch(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetEpoch', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetEpochResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetVegaTime(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetVegaTime', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetVegaTimeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AccountsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/AccountsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AccountsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CandlesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/CandlesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CandlesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarginLevelsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarginLevelsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarginLevelsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepthSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketDepthSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketDepthUpdatesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketDepthUpdatesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketDepthUpdatesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MarketsDataSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/MarketsDataSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.MarketsDataSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OrdersSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/OrdersSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OrdersSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PositionsSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/PositionsSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PositionsSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TradesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/TradesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TradesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TransferResponsesSubscribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/TransferResponsesSubscribe', data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TransferResponsesSubscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetNodeSignaturesAggregate(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetNodeSignaturesAggregate', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetNodeSignaturesAggregateResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AssetByID(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/AssetByID', data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetByIDResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Assets(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Assets', data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.AssetsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def EstimateFee(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/EstimateFee', data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateFeeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def EstimateMargin(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/EstimateMargin', data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.EstimateMarginResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ERC20WithdrawalApproval(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/ERC20WithdrawalApproval', data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ERC20WithdrawalApprovalResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Withdrawal(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Withdrawal', data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Withdrawals(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Withdrawals', data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.WithdrawalsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Deposit(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Deposit', data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Deposits(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Deposits', data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DepositsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def NetworkParameters(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/NetworkParameters', data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.NetworkParametersResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def LiquidityProvisions(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/LiquidityProvisions', data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.LiquidityProvisionsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleSpec(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleSpec', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleSpecs(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleSpecs', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleSpecsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def OracleDataBySpec(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/OracleDataBySpec', data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.OracleDataBySpecResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveRewards(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveRewards', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveRewardsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetRewards(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetRewards', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetRewardSummaries(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/GetRewardSummaries', data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.GetRewardSummariesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Checkpoints(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Checkpoints', data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.CheckpointsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Delegations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Delegations', data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.DelegationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ObserveDelegations(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/datanode.api.v1.TradingDataService/ObserveDelegations', data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.ObserveDelegationsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def PartyStake(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/PartyStake', data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.PartyStakeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def Transfers(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datanode.api.v1.TradingDataService/Transfers', data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersRequest.SerializeToString, data__node_dot_api_dot_v1_dot_trading__data__pb2.TransfersResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

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EHR_statistic_app/apps.py

HurleyJames/Visualization-EHRs

1

190198

<gh_stars>1-10 from django.apps import AppConfig class EhrStatisticAppConfig(AppConfig): name = 'EHR_statistic_app'

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adaptnlp/callback.py

chsafouane/adaptnlp

410

79550

<filename>adaptnlp/callback.py<gh_stars>100-1000 # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/01_callback.ipynb (unless otherwise specified). __all__ = ['GatherInputsCallback', 'SetInputsCallback', 'GeneratorCallback'] # Cell from fastcore.basics import store_attr from fastcore.meta import delegates from fastai.callback.core import Callback, CancelBatchException from transformers import PreTrainedModel # Cell class GatherInputsCallback(Callback): """ Prepares basic input dictionary for HuggingFace Transformers This `Callback` generates a very basic dictionary consisting of `input_ids`, `attention_masks`, and `token_type_ids`, and saves it to the attribute `self.learn.inputs`. If further data is expected or needed from the batch, the additional Callback(s) should have an order of -2 """ order = -3 def before_validate(self): """ Sets the number of inputs in `self.dls` """ x = self.dl.one_batch() self.learn.dls.n_inp = len(x) def before_batch(self): """ Turns `self.xb` from a tuple to a dictionary of either `{"input_ids", "attention_masks", "token_type_ids"}`d or `{"input_ids", "attention_masks"}` """ inputs = { "input_ids":self.learn.xb[0], "attention_mask":self.learn.xb[1] } if len(self.learn.xb) > 2: inputs["token_type_ids"] = self.learn.xb[2] self.learn.inputs = inputs # Cell class SetInputsCallback(Callback): """ Callback which runs after `GatherInputsCallback` that sets `self.learn.xb` """ order = -1 def __init__( self, as_dict=False # Whether to leave `self.xb` as a dictionary of values ): store_attr() def before_batch(self): """ Set `self.learn.xb` to `self.learn.inputs.values()` """ if not self.as_dict: self.learn.xb = list(self.learn.inputs.values()) else: self.learn.xb = self.learn.inputs # Cell class GeneratorCallback(Callback): """ Callback used for models that utilize `self.model.generate` """ @delegates(PreTrainedModel.generate) def __init__( self, num_beams:int, # Number of beams for beam search min_length:int, # Minimal length of the sequence generated max_length:int, # Maximum length of the sequence generated early_stopping:bool, # Whether to do early stopping **kwargs ): store_attr() self.kwargs = kwargs def before_batch(self): """ Run model-specific inference """ pred = self.learn.model.generate( input_ids = self.xb['input_ids'], attention_mask = self.xb['attention_mask'], num_beams = self.num_beams, min_length = self.min_length, max_length = self.max_length, early_stopping = self.early_stopping, **self.kwargs ) self.learn.pred = pred raise CancelBatchException # skip original model inference

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spyderlib/utils/debug.py

MarlaJahari/Marve

1

26211

# -*- coding: utf-8 -*- # # Copyright © 2009-2010 <NAME> # Licensed under the terms of the MIT License # (see spyderlib/__init__.py for details) """Debug utilities""" import inspect import traceback import time def log_time(fd): timestr = "Logging time: %s" % time.ctime(time.time()) print >>fd, "="*len(timestr) print >>fd, timestr print >>fd, "="*len(timestr) print >>fd, "" def log_last_error(fname, context=None): """Log last error in filename *fname* -- *context*: string (optional)""" fd = open(fname, 'a') log_time(fd) if context: print >>fd, "Context" print >>fd, "-------" print >>fd, "" print >>fd, context print >>fd, "" print >>fd, "Traceback" print >>fd, "---------" print >>fd, "" traceback.print_exc(file=fd) print >>fd, "" print >>fd, "" def log_dt(fname, context, t0): fd = open(fname, 'a') log_time(fd) print >>fd, "%s: %d ms" % (context, 10*round(1e2*(time.time()-t0))) print >>fd, "" print >>fd, "" def caller_name(skip=2): """Get a name of a caller in the format module.class.method `skip` specifies how many levels of stack to skip while getting caller name. skip=1 means "who calls me", skip=2 "who calls my caller" etc. An empty string is returned if skipped levels exceed stack height """ stack = inspect.stack() start = 0 + skip if len(stack) < start + 1: return '' parentframe = stack[start][0] name = [] module = inspect.getmodule(parentframe) # `modname` can be None when frame is executed directly in console # TODO(techtonik): consider using __main__ if module: name.append(module.__name__) # detect classname if 'self' in parentframe.f_locals: # I don't know any way to detect call from the object method # XXX: there seems to be no way to detect static method call - it will # be just a function call name.append(parentframe.f_locals['self'].__class__.__name__) codename = parentframe.f_code.co_name if codename != '<module>': # top level usually name.append( codename ) # function or a method del parentframe return ".".join(name)

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configs/__init__.py

mutalisk999/bibi

1,037

89323

<filename>configs/__init__.py # -*- coding: utf-8 -*- from .config import BaseConfig, DevConfig, TestConfig, get_config

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RLBotPack/blind_and_deaf/hover.py

L0laapk3/RLBotPack

13

78016

<gh_stars>10-100 from rlutilities.simulation import Game, Input, Car from rlutilities.linear_algebra import vec3, normalize, look_at, norm from rlutilities.mechanics import AerialTurn class Hover: """ PD controller for hovering in the air. This was also used in the Airshow :) """ P = 2.8 D = 3.0 def __init__(self, car: Car): self.turn = AerialTurn(car) self.target: vec3 = None self.car: Car = car self.up: vec3 = None self.controls: Input = Input() self.__time_spent_on_ground = 0.0 def step(self, dt): delta_target = self.target - self.car.position if norm(delta_target) > 700: delta_target *= 700 / norm(delta_target) target_direction = normalize(vec3( (delta_target[0]) * self.P - self.car.velocity[0] * self.D, (delta_target[1]) * self.P - self.car.velocity[1] * self.D, 1000 )) # reinitialize the AerialTurn object every frame, because it bugs out sometimes # TODO: actually fix this in RLU self.turn = AerialTurn(self.car) self.turn.target = look_at(target_direction, self.up) self.turn.step(dt) self.controls = self.turn.controls self.controls.boost = 0 # tap boost to keep height if (delta_target[2] - self.car.velocity[2] * 0.5) > 0: self.controls.boost = 1 # if the target is relatively far, hold boost even when we're higher than the target to keep moving if delta_target[2] < 0 and self.car.forward()[2] < 0.5: self.controls.boost = 1 self.controls.throttle = True

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isa.py

schwaaweb/aimlds1_11-NLP

0

84062

<reponame>schwaaweb/aimlds1_11-NLP<gh_stars>0 #!/usr/bin/env python # Income Share Agreement min = 50000.0 max = 88235.3 max_pay = 30000.0 max_income = 2117647.06 monthly_increment = (max - min)/23 print('\n24 months maximum payment with a minimum of $50,000 annual income') print('Maximum income for 24 month repayment is $88,235.30\n') print('For incomes exceeding $88,235.30 see chart below,\nfor reduced payback period on $30,000 repayment cap') print('\nmonth\tannual_income\tless_isa\tmonthly\t\tless_isa\tmonthly_payment\n') for n in range(24): print( "%d\t%.2f\t%.2f\t%.2f\t\t%.2f\t\t%.2f" % (n+1, (min+(n*monthly_increment)), (min+(n*monthly_increment))*0.83, (min+(n*monthly_increment))/12, (min+(n*monthly_increment))*0.83/12, ((min+(n*monthly_increment))/12) - (min+(n*monthly_increment))*0.83/12 )) print('\n') print('$30,000 Maximum Shared Income\n') print('total\t\tannual\t\tmonthly\npayments\tincome\t\tpayment\n') for n in range(24,0,-1): print('%d\t\t%.2f\t%.2f' % (n, max/(max*n/max_income), max_pay/n)) print('\n')

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setup.py

ooreilly/mydocstring

13

3455

<filename>setup.py from setuptools import setup setup(name='mydocstring', version='0.2.7', description="""A tool for extracting and converting Google-style docstrings to plain-text, markdown, and JSON.""", url='http://github.com/ooreilly/mydocstring', author="<NAME>", license='MIT', packages=['mydocstring'], install_requires=['mako', 'docopt'], entry_points = { 'console_scripts': [ 'mydocstring=mydocstring.docstring:main', ],}, package_data={'mydocstring': ['templates/google_docstring.md']}, zip_safe=False)

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PAST3/i.py

nishio/atcoder

1

94259

<reponame>nishio/atcoder if 1: N = int(input()) Q = int(input()) queries = [] for i in range(Q): queries.append([int(x) for x in input().split()]) else: N = 100000 queries = [ [2, 1, 2], [4, 1, 2] ] * 10000 queries.append([4, 1, 2]) Q = len(queries) isTransposed = False xs = list(range(N + 1)) ys = list(range(N + 1)) for q in queries: f = q[0] if f == 4: i, j = q[1:] if isTransposed: i, j = j, i print(N * (xs[i] - 1) + ys[j] - 1) elif f == 3: isTransposed = not isTransposed else: i, j = q[1:] if (f == 1) ^ isTransposed: xs[i], xs[j] = xs[j], xs[i] else: ys[i], ys[j] = ys[j], ys[i]

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freq_month.py

martengooz/github-scraper

1

148255

import numpy import json import time import datetime from dateutil.relativedelta import * import dateutil import dateutil.parser from scipy.stats.stats import pearsonr import matplotlib.pyplot as plt import scipy from operator import truediv with open('repos') as data_file: data = json.load(data_file) popularitylist = [] #print stars commitsPermonth = [] for repo in data: if repo['stargazers_count'] > 10 and repo['forks_count'] > 1 and repo['subscribers_count'] > 10 and len(repo['commit']) >100: lista = repo['commit'] endtime = lista[0] starttime = lista[len(lista)-1] endtime = endtime['date'] starttime = starttime['date'] endtime = endtime.encode('ascii') starttime = starttime.encode('ascii') starttime = starttime[:-1] endtime = endtime[:-1] start = dateutil.parser.parse(starttime) end = dateutil.parser.parse(endtime) #lista = lista[::-1] #currentmonth = start + relativedelta(months=+1) currentmonth = end - relativedelta(months=+1) commitsThismonth = 0 for commit in lista: if dateutil.parser.parse(commit['date'].encode('ascii')[:-1]) > currentmonth: commitsThismonth += 1 else: break commitsPermonth.append(commitsThismonth) #print longeststreak commitsThismonth = commitsThismonth/30.4368499 # convert to commits per hour commitsPermonth.append(commitsThismonth) #popularity = repo['forks_count'] popularity = repo['stargazers_count'] #popularity = repo['forks_count'] + repo['stargazers_count'] + repo['subscribers_count'] popularitylist.append(popularity) y = popularitylist x = commitsPermonth print "AVG = " + str(sum(x) / float(len(x))) slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(x, y) x = numpy.array(x) predict_y = intercept + slope * x plt.scatter(x, y) plt.plot(x, predict_y, 'k-', color="g", label="r = " + "{0:.4f}".format(r_value) +"\n" + "p = " + "{0:.4f}".format(p_value)) print(str(r_value) +", " + str(p_value)) lims = plt.xlim() plt.xlim([lims[0], lims[1]]) plt.xlabel("Commit/day") plt.ylabel("Stars") plt.title("Average daily commits last month (Stars)") plt.legend() plt.show()

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saifooler/classifiers/image_net_classifier.py

sailab-code/SAIFooler

0

12217

from saifooler.classifiers.classifier import Classifier import torch import json import os class ImageNetClassifier(Classifier): def __init__(self, model, *args, **kwargs): super().__init__(model, *args, **kwargs) self.std = torch.tensor([0.229, 0.224, 0.225], device=self.device) self.mean = torch.tensor([0.485, 0.456, 0.406], device=self.device) class_index_path = os.path.join( os.path.dirname(__file__), "imagenet_class_index.json" ) self.class_dict = { int(key): val[1] for key, val in json.load(open(class_index_path)).items() } def to(self, device): super().to(device) self.mean = self.mean.to(device) self.std = self.std.to(device) def get_class_label(self, class_id: int): return self.class_dict[class_id] def normalize_image(self, image): """ :param image: tensor of shape (N, W, H, C) :return: image normalized for ImageNet and permuted in the shape (N, C, W, H) which is the shape used by torchvision models """ image = (image - self.mean) / self.std image = image.permute(0, 3, 1, 2) return image

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SimPEG/EM/Static/SIP/__init__.py

rolandhill/simpeg

3

164048

<gh_stars>1-10 from .ProblemSIP import Problem3D_CC, Problem3D_N from .ProblemSIP_2D import Problem2D_CC, Problem2D_N from .SurveySIP import Survey, Data, from_dc_to_sip_survey from . import SrcSIP as Src from . import RxSIP as Rx from .Run import run_inversion, spectral_ip_mappings

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creer/input.py

JeffreyStrahm/Creer

0

140015

<gh_stars>0 import glob def validate(inputs): validated_inputs = [] for input_dir in inputs: dirs = glob.glob(input_dir) if not dirs: raise Exception("No directories matching {}".format(input_dir)) validated_inputs.extend(dirs) for validated_input in validated_inputs: print(">> Input Directory:", validated_input) return validated_inputs

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zict/zip.py

phobson/zict

0

7730

try: from collections.abc import MutableMapping except ImportError: from collections import MutableMapping import zipfile class Zip(MutableMapping): """Mutable Mapping interface to a Zip file Keys must be strings, values must be bytes Parameters ---------- filename: string mode: string, ('r', 'w', 'a'), defaults to 'a' Examples -------- >>> z = Zip('myfile.zip') # doctest: +SKIP >>> z['x'] = b'123' # doctest: +SKIP >>> z['x'] # doctest: +SKIP b'123' >>> z.flush() # flush and write metadata to disk # doctest: +SKIP """ def __init__(self, filename, mode="a"): self.filename = filename self.mode = mode self._file = None @property def file(self): if self.mode == "closed": raise OSError("File closed") if not self._file or not self._file.fp: self._file = zipfile.ZipFile(self.filename, mode=self.mode) return self._file def __getitem__(self, key): return self.file.read(key) def __setitem__(self, key, value): self.file.writestr(key, value) def keys(self): return (zi.filename for zi in self.file.filelist) def values(self): return map(self.file.read, self.keys()) def items(self): return ((zi.filename, self.file.read(zi.filename)) for zi in self.file.filelist) def __iter__(self): return self.keys() def __delitem__(self, key): raise NotImplementedError("Not supported by stdlib zipfile") def __len__(self): return len(self.file.filelist) def flush(self): self.file.fp.flush() self.file.close() def close(self): self.flush() self.mode = "closed" def __enter__(self): return self def __exit__(self, type, value, traceback): self.close()

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blockchain/web3.py

joelwembo/expert-python-dts-algorithms

0

71573

# Block development using web3 """ >>> from web3 import Web3 # IPCProvider: >>> w3 = Web3(Web3.IPCProvider('./path/to/geth.ipc')) # HTTPProvider: >>> w3 = Web3(Web3.HTTPProvider('http://127.0.0.1:8545')) # WebsocketProvider: >>> w3 = Web3(Web3.WebsocketProvider('ws://127.0.0.1:8546')) >>> w3.isConnected() True """ from web3 import Web3 w3 = Web3(Web3.HTTPProvider('https://mainnet.infura.io/v3/<infura-project-id>')) from web3.auto.infura import w3 print (w3.eth.block_number) """ >>> from web3.beacon import Beacon j >>> beacon = Beacon("http://localhost:5051") """

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tas/__main__.py

lispsil/tas

1

29981

import os import signal import atexit import json import time from pathlib import Path import subprocess import argparse import pprint from distutils.util import strtobool children_pid = [] @atexit.register def kill_child(): for child_pid in children_pid: os.kill(child_pid, signal.SIGTERM) cmd_parser = argparse.ArgumentParser(add_help=False) cmd_parser.add_argument( "cmd", type=str, choices=["new", "del", "run", "set", "list"], help="Main command", ) args = cmd_parser.parse_known_args()[0] PATH_TO_SETTINGS = Path.home() / Path(".tas.json") def get_default_settings(): return { "namespaces": [ { "name": "default", "path": str(Path.home() / Path("Documents/tas_projects/")), } ], "templates": [ { "name": "default", "actions": [ {"type": "venv"}, {"type": "dir", "path": "py"}, {"type": "dir", "path": "py/src"}, {"type": "dir", "path": "sql"}, {"type": "dir", "path": "resources"}, {"type": "file", "path": "README.md"}, {"type": "requirements", "packages": ["jupyter"]}, {"type": "file_link", "url": ""} ], } ], "projects": [], } def load_settings(): if not PATH_TO_SETTINGS.exists(): return get_default_settings() with open(PATH_TO_SETTINGS) as f: return json.load(f) def save_settings(): with open(PATH_TO_SETTINGS, "w+") as f: json.dump(settings, f, ensure_ascii=False, indent=4) def lookup_in_list_of_dicts(l, name, return_index=False): for i, val in enumerate(l): if val["name"] == name: return val if not return_index else (i, val) return None if not return_index else (None, None) def get_proj(args, should_exist, ns_path): proj_name = f"{args.namespace}.{args.name}" proj_path = Path(ns_path) / Path(args.name) exists = lookup_in_list_of_dicts(settings["projects"], proj_name) if exists and not should_exist: raise Exception("Project already exists!") elif not exists and should_exist: raise Exception("Project not found!") return exists if exists else {"name": proj_name, "path": proj_path} def get_args(cmd): # TODO: create allowed combinations of args if cmd == "set": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("namespace", type=str, help="Namespace") args_parser.add_argument("path", type=str, help="PosixPath") elif cmd == "del": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("name", type=str, help="Name of an object") args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("type", type=str, choices=["n", "p"], default="p") elif cmd == "list": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument( "type", type=str, choices=["n", "t", "p", "a"], default="p" ) elif cmd == "new": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument("name", type=str, help="Name") args_parser.add_argument( "-template", "-t", type=str, default="default", help="Template" ) args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("-path", "-p", type=str, help="PosixPath") elif cmd == "run": args_parser = argparse.ArgumentParser(parents=[cmd_parser]) args_parser.add_argument( "-namespace", "-ns", type=str, default="default", help="Namespace" ) args_parser.add_argument("name", type=str, help="Project name") return args_parser.parse_args() def interactive_y_n(question): while True: try: reply = str(input(question + " (y/n): ")).lower().strip() return strtobool(reply) except ValueError as e: pprint.pprint("Please enter yes or no!") pass settings = load_settings() if __name__ == "__main__": extra_args = get_args(args.cmd) if args.cmd == "set": # TODO: make it interactive? ns_id, ns = lookup_in_list_of_dicts( settings["namespaces"], extra_args.namespace, return_index=True ) if ns_id != None: settings["namespaces"][ns_id] = {**ns, "path": extra_args.path} else: settings["namespaces"].append( {"name": extra_args.namespace, "path": extra_args.path} ) save_settings() elif args.cmd == "del": # TODO: interactive and delete projects if extra_args.type == "n": target = "namespaces" name = args.name elif extra_args.type == "p": target = "projects" ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, True, ns["path"]) name = proj["name"] target_id, ns = lookup_in_list_of_dicts( settings[target], name, return_index=True ) if target_id is None: raise Exception("No such name!") del settings[target][target_id] save_settings() elif args.cmd == "list": if extra_args.type == "n": pprint.pprint(settings["namespaces"]) elif extra_args.type == "p": pprint.pprint(settings["projects"]) elif extra_args.type == "t": pprint.pprint(settings["templates"]) elif extra_args.type == "a": pprint.pprint(settings) elif args.cmd == "new": ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, False, ns["path"]) template = lookup_in_list_of_dicts(settings["templates"], extra_args.template) if proj["path"].exists(): if not interactive_y_n("Path already exists. Should we proceed?"): exit() else: proj["path"].mkdir(parents=True) for action in template["actions"]: if action["type"] == "dir": (proj["path"] / Path(action["path"])).mkdir( parents=False, exist_ok=True ) elif action["type"] == "file": filepath = proj["path"] / Path(action["path"]) filepath.touch() elif action["type"] == "requirements": os.chdir(proj["path"]) subprocess.call( [ "python", "-m", "venv", "--system-site-packages", str(proj["path"] / Path("env")), ] ) if action["packages"]: subprocess.call( ["./env/bin/python", "-m", "pip", "install"] + action["packages"] ) filepath = proj["path"] / Path("requirements.txt") with filepath.open("w+") as f: f.write("\n".join(action["packages"])) settings["projects"].append({"name": proj["name"], "path": str(proj["path"])}) save_settings() elif args.cmd == "run": ns = lookup_in_list_of_dicts(settings["namespaces"], extra_args.namespace) proj = get_proj(extra_args, True, ns["path"]) os.chdir(Path(proj["path"])) child = subprocess.Popen( ["./env/bin/python", "-m", "jupyter", "notebook", "--log-level=0"] ) children_pid.append(child.pid) time.sleep(2) while not interactive_y_n("Would you like to end?"): continue

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projects/tests/test_migrations.py

18F/projects

9

103310

from unittest import SkipTest from django.apps import apps from django.test import TransactionTestCase from django.db.migrations.executor import MigrationExecutor from django.db import connection from django.conf import settings from test_without_migrations.management.commands.test import DisableMigrations class MigrationTestCase(TransactionTestCase): # https://www.caktusgroup.com/blog/2016/02/02/writing-unit-tests-django-migrations/ @property def app(self): return apps.get_containing_app_config(type(self).__module__).name migrate_from = None migrate_to = None def setUp(self): if isinstance(settings.MIGRATION_MODULES, DisableMigrations): raise SkipTest('migrations are disabled') assert self.migrate_from and self.migrate_to, \ ("TestCase '{}' must define migrate_from and " "migrate_to properties".format(type(self).__name__)) self.migrate_from = [(self.app, self.migrate_from)] self.migrate_to = [(self.app, self.migrate_to)] executor = MigrationExecutor(connection) old_apps = executor.loader.project_state(self.migrate_from).apps # Reverse to the original migration executor.migrate(self.migrate_from) self.setUpBeforeMigration(old_apps) # This wasn't part of the original code from the blog post, but # was mentioned as a required workaround in the comments. executor = MigrationExecutor(connection) # Run the migration to test executor.migrate(self.migrate_to) self.apps = executor.loader.project_state(self.migrate_to).apps def setUpBeforeMigration(self, apps): pass class TestPopulateIsBillable(MigrationTestCase): migrate_from = '0012_add_is_billable' migrate_to = '0013_populate_is_billable' BILLABLE = 0 NON_BILLABLE = 1 def setUpBeforeMigration(self, apps): Project = apps.get_model('projects', 'Project') self.billable_id = Project.objects.create( billable=self.BILLABLE ).id self.non_billable_id = Project.objects.create( billable=self.NON_BILLABLE ).id def test_migration_works(self): Project = self.apps.get_model('projects', 'Project') self.assertTrue( Project.objects.get(id=self.billable_id).is_billable ) self.assertFalse( Project.objects.get(id=self.non_billable_id).is_billable, )

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firmwire/vendor/mtk/mtkdb/parse_mdb.py

j4s0n/FirmWire

0

172381

<reponame>j4s0n/FirmWire<filename>firmwire/vendor/mtk/mtkdb/parse_mdb.py ## Copyright (c) 2022, Team FirmWire ## SPDX-License-Identifier: BSD-3-Clause import struct import lzma import logging log = logging.getLogger(__name__) def reads32(f): x = f.read(4) return struct.unpack("<i", x)[0] def read32(f): x = f.read(4) return struct.unpack("<I", x)[0] def read16(f): x = f.read(2) return struct.unpack("<H", x)[0] def read8(f): x = f.read(1) return struct.unpack("<B", x)[0] def readCATD(f): magic = f.read(4) assert magic == b"CATD" idk1 = read32(f) idk2 = read32(f) magic = f.read(4) assert magic == b"HEAD" idk3 = read32(f) entrycount = read32(f) entries = [] for n in range(entrycount): idke1 = read32(f) entryoffset = read32(f) entrysize = read32(f) entries.append((idke1, entryoffset, entrysize)) log.debug(idke1, hex(entryoffset), hex(entrysize)) entries2 = [] for idke1, entryoffset, entrysize in entries: assert entrysize >= 16 f.seek(entryoffset) magic = f.read(4) assert magic == b"DATA" idkee1 = read32(f) offset = read32(f) size = read32(f) if entrysize < 20: uncompsize = size # a41..? else: uncompsize = read32(f) remainder = f.read(entrysize - 20) # log.debug(idke1, hex(size), hex(uncompsize), remainder.encode('hex')) log.debug(idke1, hex(size), hex(uncompsize)) entries2.append((idkee1, offset, remainder, size, uncompsize)) segments = [] for idkee1, offset, remainder, size, uncompsize in entries2: f.seek(offset) log.debug("%x (uncomp %x) bytes @ %x" % (size, uncompsize, offset)) s = f.read(16) log.debug(s.hex()) # if size != uncompsize: if size != uncompsize and s[:4] != b"CATD": # FIXME f.seek(offset) props = read8(f) dict_size = read32(f) lc = props % 9 props = int(props / 9) pb = int(props / 5) lp = props % 5 filters = [ { "id": lzma.FILTER_LZMA1, "dict_size": dict_size, "lc": lc, "lp": lp, "pb": pb, } ] decomp = lzma.decompress( f.read(size - 5), format=lzma.FORMAT_RAW, filters=filters ) segments += [decomp] else: f.seek(offset) data = f.read(size) segments += [data] return segments

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Constants.py

micv-dev/DeepKubeGPUCluster

2

18419

DEFAULT_KUBE_VERSION=1.14 KUBE_VERSION="kubeVersion" USER_ID="userId" DEFAULT_USER_ID=1 CLUSTER_NAME="clusterName" CLUSTER_MASTER_IP="masterHostIP" CLUSTER_WORKER_IP_LIST="workerIPList" FRAMEWORK_TYPE= "frameworkType" FRAMEWORK_VERSION="frameworkVersion" FRAMEWORK_RESOURCES="frameworkResources" FRAMEWORK_VOLUME_SIZE= "storageVolumeSizegb" FRAMEWORK_ASSIGN_DPU_TYPE= "dpuType" FRAMEWORK_ASSIGN_DPU_COUNT= "count" FRAMEWORK_INSTANCE_COUNT="instanceCount" FRAMEWORK_SPEC="spec" FRAMEWORK_IMAGE_NAME="imageName" FRAMEWORK_DPU_ID="dpuId" FRAMEWORK_DPU_COUNT="count" CLUSTER_ID="clusterId" FRAMEWORK_DEFAULT_PVC="/home/user/" DEFAULT_FRAMEWORK_TYPE="POLYAXON" DEFAULT_FRAMEWORK_VERSION="0.4.4" POLYAXON_TEMPLATE="templates/polyaxon_config" POLYAXON_CONFIG_FILE="/home/user/polyaxonConfig.yaml" POLYAXON_DEFAULT_NAMESPACE="polyaxon" TENSORFLOW_TEMPLATE="templates/tensorflow-gpu" DEFAULT_PATH="/home/user/" ##########Cluster Info#################### POD_IP="podIp" POD_STATUS="podStatus" POD_HOST_IP="hostIp" ##########End Of Cluster Info#################### PVC_MAX_ITERATIONS=50 SLEEP_TIME=5 GLUSTER_DEFAULT_MOUNT_PATH="/volume" CONTAINER_VOLUME_PREFIX="volume" MAX_RETRY_FOR_CLUSTER_FORM=10 ##############Cluster Related ####################33 CLUSTER_NODE_READY_COUNT=60 CLUSTER_NODE_READY_SLEEP=6 CLUSTER_NODE_NAME_PREFIX="worker" NO_OF_GPUS_IN_GK210_K80=2 POLYAXON_NODE_PORT_RANGE_START=30000 POLYAXON_NODE_PORT_RANGE_END=32767 DEFAULT_CIDR="10.244.0.0/16" GFS_STORAGE_CLASS="glusterfs" GFS_STORAGE_REPLICATION="replicate:2" HEKETI_REST_URL="http://10.138.0.2:8080" DEFAULT_VOLUME_MOUNT_PATH="/volume" GLUSTER_DEFAULT_REP_FACTOR=2 POLYAXON_DEFAULT_HTTP_PORT=80 POLYAXON_DEFAULT_WS_PORT=1337 SUCCESS_MESSAGE_STATUS="SUCCESS" ERROR_MESSAGE_STATUS="SUCCESS" ROLE="role" IP_ADDRESS="ipAddress" INTERNAL_IP_ADDRESS="internalIpAddress" ADD_NODE_USER_ID="hostUserId" ADD_NODE_PASSWORD="password" ####Polyaxon GetClusterInfo### QUOTA_NAME="quotaName" QUOTA_USED="used" QUOTA_LIMIT="limit" DEFAULT_QUOTA="default" VOLUME_NAME="volumeName" MOUNT_PATH_IN_POD="volumePodMountPath" VOLUME_TOTAL_SIZE="totalSize" VOLUME_FREE="free" NVIDIA_GPU_RESOURCE_NAME="requests.nvidia.com/gpu" EXECUTOR="executor" MASTER_IP="masterIP" GPU_COUNT="gpuCount" NAME="name" KUBE_CLUSTER_INFO="kubeClusterInfo" ML_CLUSTER_INFO="mlClusterInfo" POLYAXON_DEFAULT_USER_ID="root" POLYAXON_DEFAULT_PASSWORD="<PASSWORD>" POLYAXON_USER_ID="polyaxonUserId" POLYAXON_PASSWORD="<PASSWORD>" DEFAULT_DATASET_VOLUME_NAME="vol_f37253d9f0f35868f8e3a1d63e5b1915" DEFAULT_DATASET_MOUNT_PATH="/home/user/dataset" DEFAULT_CLUSTER_VOLUME_MOUNT_PATH="/home/user/volume" DEFAULT_GLUSTER_SERVER="10.138.0.2" DEFAULT_DATASET_VOLUME_SIZE="10Gi" CLUSTER_VOLUME_MOUNT_PATH="volumeHostMountPath" DATASET_VOLUME_MOUNT_POINT="dataSetVolumemountPointOnHost" DATASET_VOLUME_MOUNT_PATH_IN_POD_REST= "volumeDataSetPodMountPoint" DATASET_VOLUME_MOUNT_PATH_IN_POD="/dataset" DYNAMIC_GLUSTERFS_ENDPOINT_STARTS_WITH="glusterfs-dynamic-"

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currency/__init__.py

p4l1ly/currency

0

40280

# -*- coding: utf-8 -*- from .fetcher import from_all

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packaging/create_msi.py

physimals/quantiphyse

9

137225

""" Create an MSI package using the WIX toolset We adopt the rule of 'one file per component' as suggested although this requires thousands of components. Generation of GUIDs is accomplished by using the Python UUID library to generate the ID based on a hash of the file path. This should ensure that the GUIDs are specific to the file path (as required) and also reproducible (as required). The same technique is used to generate the product, upgrade GUID, using fixed notional paths for reproducibility """ import os, sys import uuid import shutil from six import StringIO MSI_SUBDIR = "msi" # Path to WIX toolset - update as required WIXDIR = "c:\Program Files (x86)/WiX Toolset v3.11/bin/" # Main template for our WXS file - content is added using the Python # string formatting placeholders WXS_TEMPLATE = """ <Wix xmlns="http://schemas.microsoft.com/wix/2006/wi">   <Product Id="*" UpgradeCode="%(upgrade_guid)s" Name="Quantiphyse" Version="%(version_str)s" Manufacturer="ibme-qubic" Language="1033"> <Package Id="*" InstallerVersion="200" Compressed="yes" Comments="Windows Installer Package" Platform="x64"/> <Media Id="1" Cabinet="product.cab" EmbedCab="yes"/> <MajorUpgrade AllowDowngrades="no" DowngradeErrorMessage="Cannot downgrade to lower version - remove old version first" AllowSameVersionUpgrades="no"/> <Directory Id="TARGETDIR" Name="SourceDir">  <Component Id="RegKeys" Guid="%(regkeys_guid)s" Win64="yes"> <RegistryKey Root='HKLM' Key='Software\[Manufacturer]\[ProductName]'> <RegistryValue Type='string' Name='InstallDir' Value='[INSTALLDIR1]' KeyPath='yes'/> <RegistryValue Type='string' Name='PluginDir' Value='[INSTALLDIR1]packages\plugins'/> </RegistryKey> </Component>  <Directory Id="ProgramMenuFolder" Name="Programs"> <Directory Id="ProgramMenuDir" Name="Quantiphyse"> <Component Id="ProgramMenuDir" Guid="%(menu_guid)s" Win64="yes"> <RemoveFolder Id='ProgramMenuDir' On='uninstall' /> <RegistryValue Root='HKCU' Key='Software\[Manufacturer]\[ProductName]' Type='string' Value='' KeyPath='yes'/> </Component> </Directory> </Directory>  <Directory Id="ProgramFiles64Folder"> %(dist_files)s </Directory> </Directory>  <Feature Id="Complete" Level="1"> %(features)s <ComponentRef Id="ProgramMenuDir"/> <ComponentRef Id="RegKeys"/> </Feature>  <Property Id="WIXUI_INSTALLDIR" Value="INSTALLDIR" /> <UIRef Id="WixUI_Minimal" /> <UIRef Id="WixUI_ErrorProgressText" /> <WixVariable Id="WixUIBannerBmp" Value="packaging/images/banner.bmp" /> <WixVariable Id="WixUIDialogBmp" Value="packaging/images/dialog.bmp" /> <WixVariable Id="WixUILicenseRtf" Value="packaging/licence.rtf"/> <Icon Id="main_icon.ico" SourceFile="quantiphyse/icons/main_icon.ico" /> <Property Id="ARPPRODUCTICON" Value="main_icon.ico" /> </Product> </Wix>""" # Minimal RTF template used to turn the license text into RTF RTF_TEMPLATE = """{\\rtf {\\fonttbl {\\f0 Courier;}} \\f0\\fs20 %s }""" def get_guid(path): """ Return a GUID which is reproducibly tied to a file path """ return uuid.uuid5(uuid.NAMESPACE_DNS, 'quantiphyse.org/' + os.path.normpath(path)) def add_files_in_dir(distdir, pkgdir, nfile, ndir, output, indent): """ Add file componenents from a directory, recursively adding from subdirs """ output.write('%s<Directory Id="INSTALLDIR%i" Name="%s">\n' % (indent, ndir, os.path.basename(pkgdir))) ndir += 1 for dirName, subdirList, fileList in os.walk(os.path.join(distdir, pkgdir)): for fname in fileList: srcpath = os.path.join(distdir, pkgdir, fname) # Generate GUID based on destination path relative to install location destpath = os.path.join(pkgdir, fname) guid = get_guid(destpath) # Write component XML output.write('%s <Component Id="Component%i" Guid="%s" Win64="yes">\n' % (indent, nfile, str(guid))) if fname == "quantiphyse.exe": output.write('%s <File Id="File%i" Source="%s" KeyPath="yes">\n' % (indent, nfile, srcpath)) output.write('%s <Shortcut Id="startmenu_qp" Directory="ProgramMenuDir" Name="Quantiphyse"\n' % indent) output.write('%s WorkingDirectory="INSTALLDIR" Icon="main_icon.ico" Advertise="yes"/>\n' % indent) output.write('%s </File>\n' % indent) else: output.write('%s <File Id="File%i" Source="%s" KeyPath="yes"/>\n' % (indent, nfile, srcpath)) output.write('%s </Component>\n' % indent) nfile += 1 for child in subdirList: # Deal with subdirs recursively nfile, ndir = add_files_in_dir(distdir, os.path.join(pkgdir, child), nfile, ndir, output, indent + " ") # os.walk is recursive by default but we do not want this so break out after first listing break output.write('%s</Directory>\n' % indent) return nfile, ndir def create_wxs(distdir, version_str, wxs_fname): """ Create the WXS file for WIX toolset to create the MSI """ formatting_values = { "version_str" : version_str.replace("-", "."), "product_guid" : get_guid('quantiphyse/product'), "upgrade_guid" : get_guid('quantiphyse/upgrade'), "menu_guid" : get_guid('quantiphyse/menu'), "regkeys_guid" : get_guid('quantiphyse/regkeys'), } output = StringIO() nfile, ndir = add_files_in_dir(distdir, "quantiphyse", 1, 1, output, " " * 5) formatting_values["dist_files"] = output.getvalue() output = StringIO() for n in range(nfile-1): output.write(' <ComponentRef Id="Component%i"/>\n' % (n+1)) formatting_values["features"] = output.getvalue() output = open(wxs_fname, 'w') output.write(WXS_TEMPLATE % formatting_values) output.close() def convert_licence(txt_fname, rtf_fname): f = open(txt_fname, "r") txt = "\\line ".join(f.readlines()) f.close() f = open(rtf_fname, "w") f.write(RTF_TEMPLATE % txt) f.close() def create_msi(distdir, pkgdir, version_str, sysname, version_str_display=None): """ Create the MSI itself using WIX toolset """ if version_str_display == None: version_str_display = version_str qpdir = os.path.join(distdir, os.pardir) convert_licence(os.path.join(qpdir, "LICENSE"), os.path.join(pkgdir, "licence.rtf")) msidir = os.path.join(pkgdir, MSI_SUBDIR) shutil.rmtree(msidir, ignore_errors=True) os.makedirs(msidir) wxs_fname = os.path.join(msidir, "quantiphyse.wxs") obj_fname = os.path.join(msidir, "quantiphyse.wixobj") msi_fname = os.path.join(msidir, "quantiphyse-%s.msi" % version_str_display) create_wxs(distdir, version_str, wxs_fname) os.system('"%s/candle.exe" %s -out %s >%s/msi.out 2>&1' % (WIXDIR, wxs_fname, obj_fname, msidir)) os.system('"%s/light.exe" %s -out %s -ext WixUIExtension >>%s/msi.out 2>&1' % (WIXDIR, obj_fname, msi_fname, msidir)) shutil.move(msi_fname, distdir) if __name__ == "__main__": # Get absolute paths to the packaging dir and the root Quantiphyse dir pkgdir = os.path.abspath(os.path.dirname(__file__)) qpdir = os.path.abspath(os.path.join(pkgdir, os.pardir)) sys.path.append(qpdir) import update_version wxs_fname = os.path.join(pkgdir, "quantiphyse.wxs") create_msi(os.path.join(qpdir, "dist"), pkgdir, update_version.update_version()[1], "win32")

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lecturegen_old.py

ucsb-cs-course-repos/tools

0

163170

#!/usr/bin/env python3 import argparse import pytest import datetime import dateutil from dateutil.parser import parse import os legal_days_of_week="MTWRF" def mkdir_p(newdir): """works the way a good mkdir should :) - already exists, silently complete - regular file in the way, raise an exception - parent directory(ies) does not exist, make them as well Source: http://code.activestate.com/recipes/82465-a-friendly-mkdir/ Note: os.makedirs() already makes all directories in the path but raises an exception if directory already exists. """ if os.path.isdir(newdir): pass elif os.path.isfile(newdir): raise OSError("a file with the same name as the desired " \ "dir, '%s', already exists." % newdir) else: head, tail = os.path.split(newdir) if head and not os.path.isdir(head): mkdir_p(head) #print "_mkdir %s" % repr(newdir) if tail: os.mkdir(newdir) def validate_days_of_week(days_of_week): for c in days_of_week: if c not in legal_days_of_week: raise ValueError("days_of_week should contain only chars from" + legal_days_of_week) def validate_date(date): result = dateutil.parser.parse(date) return result def validate_start_date(date): result = validate_date(date) sunday = 6 # see: https://docs.python.org/2/library/datetime.html day_of_week = result.weekday() if day_of_week != sunday: raise ValueError("Start Date should be a Sunday") return result def add_weeks(start_datetime,weeks): """ Return a datetime that is start_datetime plus weeks into the future Example: start_datetime represents 2019-03-31, weeks is 0 => 2019-03-31 start_datetime represents 2019-03-31, weeks is 1 => 2019-04-07 start_datetime represents 2019-03-31, weeks is 2 => 2019-04-14 """ days_ahead = weeks * 7 final_datetime = n_days_ahead(start_datetime, 7*weeks) return final_datetime def n_days_ahead(start_datetime, days): """ Return a datetime that is start_datetime plus days into the future """ delta = datetime.timedelta(days = days) return start_datetime + delta def days_for_this_week(start_datetime, dates): """ Return a tuple of len(dates) datetimes, one for each lecture day start_datetime is the first lecture day of the week, the rest are calculated by addings days forward according to dates Warning: Does not account for holidays (see days_without_holidays) """ days_this_week = [] for d in dates: day_num = day_to_num(d) + 1 #Plus 1 so Monday is offset 1 from Sunday days_this_week.append(n_days_ahead(start_datetime, day_num)) return days_this_week def days_without_holidays(days_of_week, holiday_list): """ Given a tuple for the two lecture days of the week, returns a list of valid dates, removing any that clash with holidays """ sanitized_holidays = [] for h in holiday_list: sanitized_holidays.append(parse(h)) sanitized_dates = [] for day in days_of_week: if day not in sanitized_holidays: sanitized_dates.append(day) return sanitized_dates def day_to_num(day): if day == "M": return 0 elif day == "T": return 1 elif day == "W": return 2 elif day == "R": return 3 elif day == "F": return 4 else: raise ValueError("day_to_num should contain only chars from" + legal_days_of_week) def find_first_lect_datetime(start_datetime, days_of_week): """ Note: No longer using this function In the case where start_datetime is not the first lecture date, this function returns the first lecture's date """ first_day = days_of_week[0] dayNum = day_to_num(first_day) first_lect = start_datetime while first_lect.weekday() != dayNum: first_lect = n_days_ahead(first_lect, 1) return first_lect def make_date_list(start_date, weeks, days_of_week, holiday_list): """ return list of date strings in yyyy-mm-dd format Example: TODO shouldn't the 3 below be 2? As this is for 2 weeks? make_date_list("2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) => ["2019-04-01","2019-04-03","2019-04-10"] """ validate_days_of_week(days_of_week) start_datetime = validate_start_date(start_date) final_datetimes = [] for i in range(weeks): start_of_week_datetime = add_weeks(start_datetime,i) days_this_week_unsanitized = days_for_this_week(start_of_week_datetime, days_of_week) days_this_week_sanitized = days_without_holidays(days_this_week_unsanitized, holiday_list) final_datetimes.append(days_this_week_sanitized) return final_datetimes def lecture_gen(path, start_date, weeks, days_of_week, holiday_list): """ Creates a _lectures directory in the given path with premade lecture stubs according to the other fields: start date, number of weeks, days of the week that the lecture is on, and a list of holidays that lectures can not be held on. """ #Create path: directory_path = os.path.join(path, "_lectures") try: mkdir_p(directory_path) except OSError: print ("Creation of the directory %s failed" % directory_path) return else: print ("Successfully created the directory %s" % directory_path) #create valid dates listing: valid_dates = make_date_list(start_date, weeks, days_of_week, holiday_list) lecture_num = 0 for dates_by_week in valid_dates: for date in dates_by_week: lecture_num += 1 #first lecture num will be 1 filename = "lecture" + str(lecture_num) f = open(os.path.join(directory_path, filename), "w+") f.write("---\n") f.write("num: " + '"lect' + str(lecture_num) + '"\n') f.write("lecture_date: " + str(date.date()) + "\n") f.write("desc: " + '\n') f.write("ready: " + "false\n") f.write("pdfurl: " + "\n") f.write("---\n") f.close() if __name__=="__main__": #lecture_gen(os.getcwd(), "2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) print("valid dates 1") valid_dates = make_date_list("2019-03-31",2,"MW",["2019-04-08","2019-04-09"]) print(valid_dates) print("valid dates 2") valid_dates2 = make_date_list("2019-03-31",2,"MWF",["2019-04-08","2019-04-09"]) print(valid_dates2) print("valid dates 3") valid_dates3 = make_date_list("2019-03-31",2,"TWR",["2019-04-08","2019-04-09"]) print(valid_dates3)

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mailer/settings.py

mvpoland/django-mailer

0

128645

<reponame>mvpoland/django-mailer from django.conf import settings """ Add here dictionary of extra headers pushed forward to django's EmailMultiAlternatives and EmailMessage. Example: to activate click and open action for e-mails sent by Mandrillapp you'll need to define this as follows: MAIL_EXTRA_HEADERS = {'X-MC-Track': 'opens,clicks'} """ MAILER_EXTRA_HEADERS = getattr(settings, "MAILER_EXTRA_HEADERS", None)

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dito/highgui.py

dhaase-de/dito

0

189847

import abc import copy import cv2 import dito.visual class Slider(abc.ABC): def __init__(self, window_name, name, initial_raw_value, max_raw_value): assert max_raw_value > 0 assert 0 <= initial_raw_value <= max_raw_value self.window_name = window_name if self.window_name is None: self.window_name = dito.visual.DEFAULT_WINDOW_NAME self.name = name self.initial_raw_value = initial_raw_value self.max_raw_value = max_raw_value self.create_trackbar() self.changed = True def callback(self, raw_value): self.changed = True self.custom_callback() def custom_callback(self): pass def create_trackbar(self): cv2.namedWindow(winname=self.window_name) cv2.createTrackbar(self.name, self.window_name, self.initial_raw_value, self.max_raw_value, self.callback) def get_raw_value(self): self.changed = False return cv2.getTrackbarPos(trackbarname=self.name, winname=self.window_name) def set_raw_value(self, raw_value): if raw_value < 0: raw_value = 0 elif raw_value > self.max_raw_value: raw_value = self.max_raw_value cv2.setTrackbarPos(trackbarname=self.name, winname=self.window_name, pos=raw_value) def reset(self): self.set_raw_value(raw_value=self.initial_raw_value) @abc.abstractmethod def raw_from_value(self, value): pass @abc.abstractmethod def value_from_raw(self, raw_value): pass def get_value(self): raw_value = self.get_raw_value() return self.value_from_raw(raw_value=raw_value) def set_value(self, value): raw_value = self.raw_from_value(value=value) self.set_raw_value(raw_value=raw_value) class ChoiceSlider(Slider): def __init__(self, window_name, name, choices, initial_choice=None): self.choices = copy.deepcopy(choices) super().__init__( name=name, window_name=window_name, initial_raw_value=0 if initial_choice is None else self.raw_from_value(value=initial_choice), max_raw_value=len(self.choices) - 1, ) def raw_from_value(self, value): return self.choices.index(value) def value_from_raw(self, raw_value): return self.choices[raw_value] class BoolSlider(Slider): def __init__(self, window_name, name, initial_value=False): super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=initial_value), max_raw_value=1, ) def raw_from_value(self, value): return 1 if value else 0 def value_from_raw(self, raw_value): return raw_value > 0 class IntegerSlider(Slider): def __init__(self, window_name, name, min_value, max_value, initial_value=None): self.min_value = min_value self.max_value = max_value super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=self.resolve_initial_value(initial_value=initial_value)), max_raw_value=self.max_value - self.min_value, ) def resolve_initial_value(self, initial_value): if isinstance(initial_value, int): return initial_value if initial_value is None: return self.min_value if initial_value == "min": return self.min_value if initial_value == "max": return self.max_value if initial_value == "mean": return (self.max_value - self.min_value) // 2 + self.min_value raise RuntimeError("Invalid initial value '{}'".format(initial_value)) def raw_from_value(self, value): return value - self.min_value def value_from_raw(self, raw_value): return self.min_value + raw_value class FloatSlider(Slider): def __init__(self, window_name, name, min_value, max_value, value_count=101, initial_value=None): self.min_value = min_value self.max_value = max_value self.value_count = value_count super().__init__( name=name, window_name=window_name, initial_raw_value=self.raw_from_value(value=self.resolve_initial_value(initial_value=initial_value)), max_raw_value=self.value_count - 1, ) def resolve_initial_value(self, initial_value): if isinstance(initial_value, float): return initial_value if initial_value is None: return self.min_value if initial_value == "min": return self.min_value if initial_value == "max": return self.max_value if initial_value == "mean": return (self.max_value - self.min_value) * 0.5 + self.min_value raise RuntimeError("Invalid initial value '{}'".format(initial_value)) def raw_from_value(self, value): # int is required for the case that `value` is a NumPy float return int(round((value - self.min_value) / (self.max_value - self.min_value) * (self.value_count - 1))) def value_from_raw(self, raw_value): return raw_value / (self.value_count - 1) * (self.max_value - self.min_value) + self.min_value

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tests/plugins/test_brittv.py

fuglede/streamlink

0

38153

<gh_stars>0 import unittest from streamlink.plugins.brittv import BritTV class TestPluginBritTV(unittest.TestCase): def test_can_handle_url(self): should_match = [ 'http://brittv.co.uk/watch/?channel=1', ] for url in should_match: self.assertTrue(BritTV.can_handle_url(url)) def test_can_handle_url_negative(self): should_not_match = [ 'https://example.com/index.html', ] for url in should_not_match: self.assertFalse(BritTV.can_handle_url(url))

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ponyexpress/models/__init__.py

TelekomCloud/pony-express

0

66895

from ponyexpress.models.repository import Repository from ponyexpress.models.repo_history import RepoHistory from ponyexpress.models.package import Package from ponyexpress.models.package_history import PackageHistory from ponyexpress.models.node import Node

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krogon/maybe.py

enamrik/krogon

1

8606

from typing import Callable, TypeVar, Union, Tuple from krogon.infix import Infix A = TypeVar('A') B = TypeVar('B') E = TypeVar('E') Maybe = Union[Tuple['just', A], Tuple['nothing']] def just(value=None): return "just", value def nothing(): return "nothing", None def from_value(value) -> Maybe[B]: return _cast_to_maybe(value) def from_value_or_default(value, default) -> Maybe[B]: return from_maybe( _cast_to_maybe(value), dict(if_just=lambda x: just(x), if_nothing=lambda: _cast_to_maybe(default))) @Infix def then(maybe: Maybe[A], func: Callable[[A], Maybe[B]]) -> Maybe[B]: if maybe[0] == "just": return _cast_to_maybe(func(maybe[1])) elif maybe[0] == "nothing": return maybe @Infix def catch_nothing(maybe: Maybe[A], func: Callable[[A], Maybe[B]]) -> Maybe[B]: if maybe[0] == "nothing": return _cast_to_maybe(func()) elif maybe[0] == "just": return maybe @Infix def map(maybe: Maybe[A], mapper: Callable[[A], B]) -> Maybe[B]: if maybe[0] == "just": return just(mapper(maybe[1])) elif maybe[0] == "nothing": return maybe @Infix def value_or_default(maybe: Maybe[A], default_value: B): return maybe | from_maybe | (dict(if_just=lambda x: x, if_nothing=lambda: default_value)) @Infix def from_maybe(maybe: Maybe[A], dict_args: dict) -> B: if_just: Callable = dict_args['if_just'] if_nothing: Callable = dict_args['if_nothing'] if maybe[0] == "just" and if_just is not None: return if_just(maybe[1]) elif maybe[0] == "nothing" and if_nothing is not None: return if_nothing() else: raise Exception('Invalid Maybe: {}, {}'.format(maybe, dict_args)) def _cast_to_maybe(result): if result is None: return nothing() if isinstance(result, tuple) and len(result) == 2: maybe_type, value = result if maybe_type == "just" or maybe_type == "nothing": return result return just(result)

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crontab_module/crons/update_predicted_location_crontab.py

openmaker-eu/watchtower

2

181067

<reponame>openmaker-eu/watchtower<gh_stars>1-10 import sys from decouple import config sys.path.insert(0, config("ROOT_DIR")) from predict_location.update_field_db import update_field_db as up_db database_names = ["audience_test", "events"] field_names = ["location", "place"] for ind in range(len(database_names)): up_db(database_names[ind], field_names[ind])

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aiovault/client.py

johnnoone/aiovault

1

31299

from . import v1 from .request import Request from .util import task, extract_id class Vault(v1.SysEndpoint): def __init__(self, addr, token=None, cert=None, verify=True): token = extract_id(token) self.req_handler = Request(addr, 'v1', token=token, cert=cert, verify=verify) @property def audit(self): return v1.AuditEndpoint(self.req_handler) @property def auth(self): return v1.AuthEndpoint(self.req_handler) @property def lease(self): return v1.LeaseEndpoint(self.req_handler) @property def policy(self): return v1.PolicyEndpoint(self.req_handler) @property def raw(self): return v1.RawEndpoint(self.req_handler) @property def seal(self): return v1.SealEndpoint(self.req_handler) @property def secret(self): return v1.SecretEndpoint(self.req_handler) @task def login(self, *args, **kwargs): return self.auth.login(*args, **kwargs) @task def read(self, path, **kwargs): method = kwargs.pop('method', 'GET') response = yield from self.req_handler(method, path, **kwargs) return response @task def write(self, path, **kwargs): method = kwargs.pop('method', 'POST') response = yield from self.req_handler(method, path, **kwargs) return response @task def delete(self, path, **kwargs): method = kwargs.pop('method', 'DELETE') response = yield from self.req_handler(method, path, **kwargs) return response def __repr__(self): return '<Vault(addr=%r)>' % self.req_handler.addr

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6.py

rowanG077/automated_reasoning

0

102177

<reponame>rowanG077/automated_reasoning from z3 import * from copy import deepcopy import sys num_stores = 1 num_villages = 4 route_costs_list = [ [-1, 15, -1, 15, -1], [15, -1, 17, 12, -1], [-1, 17, -1, 10, 20], [15, 12, 10, -1, 20], [-1, -1, 20, 20, -1], ] assignment_b = False capacities = [ 260 if assignment_b else 250, 110, 160, 110, 160, ] num_eval = 14 if assignment_b else 32 route_costs = Array('routes', IntSort(), ArraySort(IntSort(), IntSort())) truck_pos = [Int(f"truck_pos_{i}") for i in range(num_eval)] truck_store = [Int(f"truck_store_{i}") for i in range(num_eval)] village_store = [[Int(f"vilage_store_{chr(ord('A') + v)}_{i}") for v in range(num_villages)] for i in range(num_eval)] if assignment_b: world_hunger_save = [[Bool(f"world_hunger_{n1}_{n2}") for n2 in range(n1 + 1, num_eval)] for n1 in range(num_eval)] def print_solution(model): cycle_arrows = [" " for i in range(num_eval)] if assignment_b: for n1 in range(num_eval): for n2 in range(n1 + 1, num_eval): if is_true(model.eval(world_hunger_save[n1][n2 - n1 - 1])): cycle_arrows[n1] = "-->" cycle_arrows[n2] = "-->" print(" cycle, truck pos, truck storage, A, B, C, D") for n in range(num_eval): truck_p = model[truck_pos[n]].as_long() truck_storage = model[truck_store[n]].as_long() truck_cap = capacities[0] a = model[village_store[n][0]].as_long() a_cap = capacities[1] b = model[village_store[n][1]].as_long() b_cap = capacities[2] c = model[village_store[n][2]].as_long() c_cap = capacities[3] d = model[village_store[n][3]].as_long() d_cap = capacities[4] assert(a <= a_cap) assert(b <= b_cap) assert(c <= c_cap) assert(d <= d_cap) assert(truck_storage <= truck_cap) if n > 0: cost = model.eval(route_costs[truck_pos[n-1]][truck_pos[n]]).as_long() prev_truck_storage = model[truck_store[n - 1]].as_long() assert(cost != -1) prev_a = model[village_store[n - 1][0]].as_long() prev_b = model[village_store[n - 1][1]].as_long() prev_c = model[village_store[n - 1][2]].as_long() prev_d = model[village_store[n - 1][3]].as_long() assert(cost <= prev_a) assert(cost <= prev_b) assert(cost <= prev_c) assert(cost <= prev_d) unloaded = [ a - (prev_a - cost), b - (prev_b - cost), c - (prev_c - cost), d - (prev_d - cost) ] unloaded = [x for x in unloaded if x != 0] assert(len(unloaded) <= 1) if truck_p == 0: unloaded = prev_truck_storage - capacities[0] elif len(unloaded) == 1: unloaded = unloaded[0] else: unloaded = 0 assert(truck_storage - prev_truck_storage == -unloaded) print(f"{cycle_arrows[n]}{n:5}, {truck_p}, {truck_storage:03}/{truck_cap:03}, {a:03}/{a_cap:03}, {b:03}/{b_cap:03}, {c:03}/{c_cap:03}, {d:03}/{d_cap:03}") s = Solver() # load routes into Z3 Array for y in range(num_stores + num_villages): for x in range(num_stores + num_villages): s.add(route_costs[y][x] == route_costs_list[y][x]) # set initial conditions s.add(truck_pos[0] == 0) s.add(truck_store[0] == capacities[0]) for v in range(num_villages): s.add(village_store[0][v] == 80) # Run bounded model for n in range(num_eval - 1): curr_loc = truck_pos[n] next_loc = truck_pos[n + 1] curr_truck_store = truck_store[n] next_truck_store = truck_store[n + 1] cost = route_costs[curr_loc][next_loc] # ensure we take a route that exists s.add(And(next_loc >= 0, next_loc < num_stores + num_villages, cost >= 0)) unload = [] # unload a negative amount to fill up capacity for i in range(num_stores): unload.append(If(next_loc == i, curr_truck_store - capacities[i], 0)) for j in range(num_villages): store_curr = village_store[n][j] store_next = village_store[n + 1][j] # Ensure we don't go through 0 when traveling # and ensure we don't store more then possible s.add(store_curr - cost >= 0) # Ensure we only unload at the current location unloaded = store_next - (store_curr - cost) s.add(If( next_loc == (num_stores + j), And(unloaded >= 0, unloaded <= curr_truck_store), unloaded == 0 )) unload.append(unloaded) # set next store s.add(store_next <= capacities[num_stores + j]) s.add(store_next == (store_curr - cost) + unloaded) # Remove capacity from truck s.add(next_truck_store == curr_truck_store - sum(unload)) # exercise 6b # check if a storage state is encountered that is strictly # better then a previous state. # if that happens we have proven we can just always keep # using that path and we have solved world hunger if assignment_b: ors = [] for n1 in range(num_eval): for n2 in range(n1 + 1, num_eval): ands = [] ands.append(truck_pos[n1] == truck_pos[n2]) ands.append(truck_store[n2] >= truck_store[n1]) for j in range(num_villages): ands.append(village_store[n2][j] >= village_store[n1][j]) world_hunger_save[n1][n2 - n1 - 1] = And(*ands) ors.append(world_hunger_save[n1][n2 - n1 - 1]) s.add(Or(*ors)) res = s.check() if res == unsat: print(f"unsat") else: print(f"SAT") print_solution(s.model())

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src/devel/___blocks/___block_base.py

jakub-vesely/hugo

0

163488

# Copyright (c) 2022 <NAME> # This software is published under MIT license. Full text of the license is available at https://opensource.org/licenses/MIT from ___basal.___logging import Logging from ___blocks.___block_types import BlockTypes import machine import time from micropython import const _power_save_command = const(0xf6) _get_module_version_command = const(0xf7) _change_i2c_address_command = const(0xfe) _i2c_block_type_id_base = const(0xFA) class PowerSaveLevel: NoPowerSave = 0 # powersave is off LightPowerSave = 1 # subsystems that are not needed are turned off DeepPowerSave = 2 # all subsystems are turned off class BlockBase: i2c = machine.I2C(0, scl=machine.Pin(22), sda=machine.Pin(21), freq=100000) def __init__(self, block_type: int, address: int): self.type_id = block_type.id self.address = address if address else block_type.id #default block i2c address is equal to its block type self.logging = Logging(block_type.name) self.block_version = self._get_block_version() self.block_type_valid = False self.power_save_level = PowerSaveLevel.NoPowerSave self._tiny_write_base_id(_power_save_command, self.power_save_level.to_bytes(1, 'big'), True) #wake up block functionality if not self.block_version: self.logging.warning("module with address 0x%x is not available", self.address) elif self.block_version[0] != self.type_id: self.logging.error("unexpected block type. expected: %d, returned: %d", self.type_id, self.block_version[0]) else: self.block_type_valid = True def _raw_tiny_write(self, type_id: int, command: int, data=None, silent=False): try: payload = type_id.to_bytes(1, 'big') + command.to_bytes(1, 'big') if data: payload += data #self.logging.info(("write", payload)) self.i2c.writeto(self.address, payload) except OSError: if not silent: self.logging.error("tiny-block with address 0x%02X is unavailable for writing", self.address) def _check_type(self, type_id): return type_id in (_i2c_block_type_id_base, self.type_id) and (_i2c_block_type_id_base or self.block_type_valid) def __tiny_write_common(self, type_id: int, command: int, data=None, silent=False): """ writes data to tiny_block via I2C @param type_id: block type id @param command: one byte command @param data: specify input data for entered command """ if self._check_type(type_id): self._raw_tiny_write(type_id, command, data, silent) else: self.logging.error("invalid block type - writing interupted") def _tiny_write_base_id(self, command: int, data=None, silent=False): self.__tiny_write_common(_i2c_block_type_id_base, command, data, silent) def _tiny_write(self, command: int, data=None, silent=False): if not self.is_available(): return self.__tiny_write_common(self.type_id, command, data, silent) def __tiny_read_common(self, type_id: int, command: int, in_data: bytes=None, expected_length: int=0, silent=False): """ reads data form tiny_block via I2C @param type_id: block type id @param command: one byte command @param in_data: specify input data for entered command @param expected_length: if defined will be read entered number of bytes. If None is expected length as a first byte @return provided bytes. If size is first byte is not included to output data """ if self._check_type(type_id): self._raw_tiny_write(type_id, command, in_data, silent) try: data = self.i2c.readfrom(self.address, expected_length, True) return data except OSError: if not silent: self.logging.error("tiny-block with address 0x%02X is unavailable for reading", self.address) return None else: self.logging.error("invalid block type - reading interupted") return None def _tiny_read_base_id(self, command: int, in_data: bytes=None, expected_length: int=0, silent=False): return self.__tiny_read_common(_i2c_block_type_id_base, command, in_data, expected_length, silent) def _tiny_read(self, command: int, in_data: bytes=None, expected_length: int=0): if not self.is_available(): return None return self.__tiny_read_common(self.type_id, command, in_data, expected_length) def change_block_address(self, new_address): self._tiny_write_base_id(_change_i2c_address_command, new_address.to_bytes(1, 'big')) self.address = new_address time.sleep(0.1) #wait to the change is performed and stopped def _get_block_version(self): """ returns block_type, pcb version, adjustment_version """ data = self._tiny_read_base_id(_get_module_version_command, None, 3, silent=True) if not data: return None return (data[0], data[1], data[2]) def is_available(self): return self.block_type_valid #available and valid block version def power_save(self, level:PowerSaveLevel) -> None: self.power_save_level = level self._tiny_write_base_id(_power_save_command, level.to_bytes(1, 'big'))

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python/src/year2020/day22.py

Farbfetzen/Advent_of_Code

4

192002

<reponame>Farbfetzen/Advent_of_Code # https://adventofcode.com/2020/day/22 from collections import deque from copy import deepcopy from itertools import islice from src.util.types import Data, Solution def prepare_data(data: str) -> list[deque[int]]: return [deque([int(card) for card in deck.splitlines()[1:]]) for deck in data.split("\n\n")] def calculate_score(cards): return sum(i * v for i, v in enumerate(reversed(cards), start=1)) def part_1(decks): decks = deepcopy(decks) while True: p0 = decks[0].popleft() p1 = decks[1].popleft() if p0 > p1: decks[0].extend((p0, p1)) if len(decks[1]) == 0: return calculate_score(decks[0]) else: decks[1].extend((p1, p0)) if len(decks[0]) == 0: return calculate_score(decks[1]) def part_2(decks, return_index=False): cache = set() winner_game = None while winner_game is None: d = (tuple(decks[0]), tuple(decks[1])) if d in cache: winner_game = 0 # player 1 (= index 0) wins break cache.add(d) p0 = decks[0].popleft() p1 = decks[1].popleft() if p0 <= len(decks[0]) and p1 <= len(decks[1]): new_deck_p0 = deque(islice(decks[0], 0, p0)) new_deck_p1 = deque(islice(decks[1], 0, p1)) winner_round = part_2([new_deck_p0, new_deck_p1], True) elif p0 > p1: winner_round = 0 else: winner_round = 1 if winner_round == 0: decks[0].extend((p0, p1)) if len(decks[1]) == 0: winner_game = 0 else: decks[1].extend((p1, p0)) if len(decks[0]) == 0: winner_game = 1 if return_index: return winner_game else: return calculate_score(decks[winner_game]) def solve(data: Data) -> Solution: solution = Solution() sample_data = prepare_data(data.samples[0]) solution.samples_part_1.append(part_1(sample_data)) solution.samples_part_2.append(part_2(sample_data)) challenge_data = prepare_data(data.input) solution.part_1 = part_1(challenge_data) solution.part_2 = part_2(challenge_data) return solution

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superset/views/extract_db_info.py

charvigupta/apachesuperset_ed

0

174282

<gh_stars>0 import sqlite3 ## path to .db connection = sqlite3.connect("/home/charvi/.superset/superset.db") def sql_table_fetch(con): datasource_dict = {} database_dict = {} cursorObj = con.cursor() cursorObj.execute('SELECT * FROM tables') rows = cursorObj.fetchall() for row in rows: db_val = str(list(row)[6]) param = list(row)[-5:-4][0].split(".") db_key = param[0][1:-1] ds_key = param[-1].split("](id:")[0][1:] ds_value = param[-1].split("](id:")[1][:-1] database_dict[db_key] = db_val datasource_dict[ds_key] = ds_value return datasource_dict, database_dict datasource_dict, database_dict = sql_table_fetch(connection)

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cinder/tests/unit/scheduler/test_capacity_weigher.py

helenwalsh/cinder

571

64668

# Copyright 2011-2012 OpenStack Foundation # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """Tests For Capacity Weigher.""" from datetime import datetime from unittest import mock import ddt from cinder.common import constants from cinder import context from cinder.scheduler import weights from cinder.tests.unit.scheduler import fakes from cinder.tests.unit import test from cinder.volume import volume_utils @ddt.ddt class CapacityWeigherTestCase(test.TestCase): def setUp(self): super(CapacityWeigherTestCase, self).setUp() self.host_manager = fakes.FakeHostManager() self.weight_handler = weights.OrderedHostWeightHandler( 'cinder.scheduler.weights') def _get_weighed_hosts(self, hosts, weight_properties=None): if weight_properties is None: weight_properties = {'size': 1} return self.weight_handler.get_weighed_objects( [weights.capacity.CapacityWeigher], hosts, weight_properties) @mock.patch('cinder.db.sqlalchemy.api.service_get_all') def _get_all_backends(self, _mock_service_get_all, disabled=False): ctxt = context.get_admin_context() fakes.mock_host_manager_db_calls(_mock_service_get_all, disabled=disabled) backend_states = self.host_manager.get_all_backend_states(ctxt) _mock_service_get_all.assert_called_once_with( ctxt, None, # backend_match_level topic=constants.VOLUME_TOPIC, frozen=False, disabled=disabled) return backend_states # If thin and thin_provisioning_support are True, # use the following formula: # free = (total * host_state.max_over_subscription_ratio # - host_state.provisioned_capacity_gb # - math.floor(total * reserved)) # Otherwise, use the following formula: # free = free_space - math.floor(total * reserved) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host1'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host2'}, {'volume_type': {}, 'winner': 'host2'}, {'volume_type': None, 'winner': 'host2'}, ) @ddt.unpack def test_default_of_spreading_first(self, volume_type, winner): backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=1024-math.floor(1024*0.1)=922 # Norm=0.837837837838 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=2048*1.5-1748-math.floor(2048*0.1)=1120 # Norm=1.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=256-512*0=256 # Norm=0.292383292383 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=2048*1.0-2047-math.floor(2048*0.05)=-101 # Norm=0.0 # host5: free_capacity_gb=unknown free=-1 # Norm=0.0819000819001 # so, host2 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties)[0] self.assertEqual(1.0, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host4'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host4'}, {'volume_type': {}, 'winner': 'host4'}, {'volume_type': None, 'winner': 'host4'}, ) @ddt.unpack def test_capacity_weight_multiplier1(self, volume_type, winner): self.flags(capacity_weight_multiplier=-1.0) backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=-(1024-math.floor(1024*0.1))=-922 # Norm=-0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=-(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=-(256-512*0)=-256 # Norm=--0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=-(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # host5: free_capacity_gb=unknown free=-float('inf') # Norm=-1.0 # so, host4 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties) weighed_host = weighed_host[0] self.assertEqual(0.0, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) @ddt.data( {'volume_type': {'extra_specs': {'provisioning:type': 'thin'}}, 'winner': 'host2'}, {'volume_type': {'extra_specs': {'provisioning:type': 'thick'}}, 'winner': 'host1'}, {'volume_type': {'extra_specs': {}}, 'winner': 'host2'}, {'volume_type': {}, 'winner': 'host2'}, {'volume_type': None, 'winner': 'host2'}, ) @ddt.unpack def test_capacity_weight_multiplier2(self, volume_type, winner): self.flags(capacity_weight_multiplier=2.0) backend_info_list = self._get_all_backends() # Results for the 1st test # {'provisioning:type': 'thin'}: # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))*2=1844 # Norm=1.67567567568 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))*2=2240 # Norm=2.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)*2=512 # Norm=0.584766584767 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))*2=-202 # Norm=0.0 # host5: free_capacity_gb=unknown free=-2 # Norm=0.1638001638 # so, host2 should win: weight_properties = { 'size': 1, 'volume_type': volume_type, } weighed_host = self._get_weighed_hosts( backend_info_list, weight_properties=weight_properties)[0] self.assertEqual(1.0 * 2, weighed_host.weight) self.assertEqual(winner, volume_utils.extract_host(weighed_host.obj.host)) def test_capacity_weight_no_unknown_or_infinite(self): self.flags(capacity_weight_multiplier=-1.0) del self.host_manager.service_states['host5'] backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))=-922 # Norm=-0.837837837838 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-1.0 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)=-256 # Norm=-0.292383292383 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host2 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host2', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_free_unknown(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 3000, 'free_capacity_gb': 'unknown', 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # host5: free_capacity_gb=unknown free=3000 # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_cap_unknown(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 'unknown', 'free_capacity_gb': 3000, 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # host5: free_capacity_gb=3000 free=unknown # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_free_infinite(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 3000, 'free_capacity_gb': 'infinite', 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # host5: free_capacity_gb=infinite free=3000 # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host)) def test_capacity_weight_cap_infinite(self): self.flags(capacity_weight_multiplier=-1.0) self.host_manager.service_states['host5'] = { 'total_capacity_gb': 'infinite', 'free_capacity_gb': 3000, 'allocated_capacity_gb': 1548, 'provisioned_capacity_gb': 1548, 'max_over_subscription_ratio': 1.0, 'thin_provisioning_support': True, 'thick_provisioning_support': False, 'reserved_percentage': 5, 'timestamp': datetime.utcnow()} backend_info_list = self._get_all_backends() # host1: thin_provisioning_support = False # free_capacity_gb=1024, # free=(1024-math.floor(1024*0.1))=-922 # Norm= -0.00829542413701 # host2: thin_provisioning_support = True # free_capacity_gb=300, # free=(2048*1.5-1748-math.floor(2048*0.1))=-1120 # Norm=-0.00990099009901 # host3: thin_provisioning_support = False # free_capacity_gb=512, free=(256-512*0)=-256 # Norm=-0.002894884083 # host4: thin_provisioning_support = True # free_capacity_gb=200, # free=(2048*1.0-2047-math.floor(2048*0.05))=101 # Norm=0.0 # host5: free_capacity_gb=3000 free=infinite # Norm=-1.0 # so, host4 should win: weighed_hosts = self._get_weighed_hosts(backend_info_list) best_host = weighed_hosts[0] self.assertEqual(0.0, best_host.weight) self.assertEqual('host4', volume_utils.extract_host(best_host.obj.host)) # and host5 is the worst: worst_host = weighed_hosts[-1] self.assertEqual(-1.0, worst_host.weight) self.assertEqual('host5', volume_utils.extract_host(worst_host.obj.host))

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29947, 29947, 29946, 29900, 29947, 29941, 13, 4706, 396, 3495, 29946, 29901, 16835, 29918, 771, 4924, 292, 29918, 5924, 353, 5852, 13, 4706, 396, 4706, 3889, 29918, 5030, 5946, 29918, 26300, 29922, 29906, 29900, 29900, 29892, 13, 4706, 396, 4706, 3889, 7607, 29906, 29900, 29946, 29947, 29930, 29896, 29889, 29900, 29899, 29906, 29900, 29946, 29955, 29899, 755, 29889, 14939, 29898, 29906, 29900, 29946, 29947, 29930, 29900, 29889, 29900, 29945, 876, 29922, 29896, 29900, 29896, 13, 4706, 396, 4706, 5655, 29922, 29900, 29889, 29900, 13, 4706, 396, 3495, 29945, 29901, 3889, 29918, 5030, 5946, 29918, 26300, 29922, 29941, 29900, 29900, 29900, 3889, 29922, 262, 18925, 13, 4706, 396, 4706, 5655, 10457, 29896, 29889, 29900, 13, 13, 4706, 396, 577, 29892, 3495, 29946, 881, 5401, 29901, 13, 4706, 591, 25398, 29918, 23525, 353, 1583, 3032, 657, 29918, 705, 25398, 29918, 23525, 29898, 27852, 29918, 3888, 29918, 1761, 29897, 13, 4706, 1900, 29918, 3069, 353, 591, 25398, 29918, 23525, 29961, 29900, 29962, 13, 4706, 1583, 29889, 9294, 9843, 29898, 29900, 29889, 29900, 29892, 1900, 29918, 3069, 29889, 7915, 29897, 13, 4706, 1583, 29889, 9294, 9843, 877, 3069, 29946, 742, 13, 462, 308, 7977, 29918, 13239, 29889, 21111, 29918, 3069, 29898, 13318, 29918, 3069, 29889, 5415, 29889, 3069, 876, 13, 4706, 396, 322, 3495, 29945, 338, 278, 17322, 29901, 13, 4706, 17322, 29918, 3069, 353, 591, 25398, 29918, 23525, 14352, 29896, 29962, 13, 4706, 1583, 29889, 9294, 9843, 6278, 29896, 29889, 29900, 29892, 17322, 29918, 3069, 29889, 7915, 29897, 13, 4706, 1583, 29889, 9294, 9843, 877, 3069, 29945, 742, 13, 462, 308, 7977, 29918, 13239, 29889, 21111, 29918, 3069, 29898, 13762, 303, 29918, 3069, 29889, 5415, 29889, 3069, 876, 13, 2 ]

method_of_moments/__init__.py

AlbertFarkhutdinov/method_of_moments

0

59454

<reponame>AlbertFarkhutdinov/method_of_moments """ This package allows you to work with probability distributions with a specified mean values and variances. """ from .continuous import Beta, GenNBD, Norm from .discrete import Bernoulli, GPD, HGD, NBD, Poisson, QGD, ZiNBD

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Lista_Simplesmente_Encadeada/Lista_Encadeada/OO/controlador_contas.py

BeatrizSilva-Dev/Algoritmos-e-Estruturas-de-Dados

0

125941

from OO import bd_contas, menu def iniciar(): print('ACESSO CAIXA ELETRONICO') agencia = input('DIGITE AGENCIA') num_conta = input('DIGITE A CONTA') conta = bd_contas.buscar_contas(agencia, num_conta) if conta is not None: while True: menu.caixa_eletronico() op = input('Digite a opção') if op == '0': print('SAINDO CAIXA ELETRÔNICO') return elif op == '1': valor = float(input('DIGITE O VALOR DE SAQUE')) if (conta.sacar(valor)): print('SUCESSO!!!') else: print('SALDO INDISPONÍVEL') elif op == '2': valor = float(input('DIGITE O VALOR DE SAQUE')) if (conta.depositar(valor)): print('SUCESSO!!!') else: print('DEPOSITO INVÁLIDO') elif op == '3': agencia = input('DIGITE AGENCIA - DESTINATÁRIO') num_conta = input('DIGITE A CONTA - DESTINATÁRIO') contas_desti = bd_contas.buscar_contas(agencia, num_conta) if contas_desti is not None: valor = float(input('DIGITE O VALOR DE TRANSFERENCIA')) if conta.transferir(valor, contas_desti): print('TRANSFERENCIA COM SUCESSO') else: print('VALOR INDISPONÍVEL""') else: print('CONTA DESTINATÁRIO NÃO EXISTE') elif op == '4': print(conta.get_saldo()) else: print('Opção Inválida') else: print('CONTA NÃO EXISTE')

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analysis/FlatfieldCalibration.py

Borlaff/EuclidVisibleInstrument

5

155900

""" Flat Field Calibration ====================== This simple script can be used to study the number of flat fields required to meet the VIS calibration requirements. The following requirements related to the flat field calibration has been taken from GDPRD. R-GDP-CAL-054: The contribution of the residuals of VIS flat-field correction to the error on the determination of each ellipticity component of the local PSF shall not exceed 3x10-5 (one sigma). R-GDP-CAL-064: The contribution of the residuals of VIS flat-field correction to the relative error on the determination of the local PSF R2 shall not exceed 1x10-4 (one sigma). .. Note:: The amount of cosmic rays in the simulated input images might be too low, because the exposure was set to 10 seconds and cosmic rays were calculated based on this. However, in reality the readout takes about 80 seconds. Thus, the last row is effected by cosmic a lot more than by assuming a single 10 second exposure. :requires: PyFITS :requires: NumPy :requires: SciPy :requires: matplotlib :requires: VISsim-Python :version: 0.97 :author: <NAME> :contact: <EMAIL> """ import matplotlib matplotlib.rc('text', usetex=True) matplotlib.rcParams['font.size'] = 17 matplotlib.rc('xtick', labelsize=14) matplotlib.rc('axes', linewidth=1.1) matplotlib.rcParams['legend.fontsize'] = 11 matplotlib.rcParams['legend.handlelength'] = 3 matplotlib.rcParams['xtick.major.size'] = 5 matplotlib.rcParams['ytick.major.size'] = 5 import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm import pyfits as pf import numpy as np import datetime, cPickle, glob, os, sys from scipy.ndimage.interpolation import zoom from scipy import interpolate from analysis import shape from support import logger as lg from support import surfaceFitting as sf from support import files as fileIO def generateResidualFlatField(files='Q0*flatfield*.fits', combine=77, lampfile='data/VIScalibrationUnitflux.fits', reference='data/VISFlatField1percent.fits', gain=3.5, plots=False, debug=False): """ Generate a median combined flat field residual from given input files. Randomly draws a given number (kw combine) of files from the file list identified using the files kw. Median combine all files before the lamp profile given by lampfile kw is being divided out. This will produce a derived flat field. This flat can be compared against the reference that was used to produce the initial data to derive a residual flat that describes the error in the flat field that was derived. :param files: wildcard flagged name identifier for the FITS files to be used for generating a flat :type files: str :param combine: number of files to median combine :type combine: int :param lampfile: name of the calibration unit flux profile FITS file :type lampfile: str :param reference: name of the reference pixel-to-pixel flat field FITS file :type reference: str :param gain: gain factor [e/ADU] :type gain: float :param plots: whether or not to generate plots :type plots: boolean :param debug: whether or not to produce output FITS files :type debug: boolean .. Warning:: Remember to use an appropriate lamp and reference files so that the error in the derived flat field can be correctly calculated. :return: residual flat field (difference between the generated flat and the reference) :rtype: ndarray """ #find all FITS files files = glob.glob(files) #choose randomly the files that should be combined if combine < len(files): ids = np.random.random_integers(0, len(files)-1, combine) files = np.asarray(files)[ids] #load data and scale to electrons data = fileIO.readFITSDataExcludeScanRegions(files) data *= gain #check that the sizes match and median combine if len(set(x.shape for x in data)) > 1: sys.exit('ERROR -- files are not the same shape, cannot median combine!') else: medianCombined = np.median(data, axis=0) #fit surface to the median and normalize it out #m = sf.polyfit2d(xx.ravel(), yy.ravel(), median.ravel(), order=order) # Evaluate it on a rectangular grid #fitted = sf.polyval2d(xx, yy, m) #load the lamp profile that went in and divide the combined image with the profile lamp = pf.getdata(lampfile) pixvar = medianCombined.astype(np.float64).copy() / lamp #load the true reference p-flat and calculate the error in the derived flat field (i.e. residual) real = pf.getdata(reference).astype(np.float64) res = np.abs(real - pixvar) / (real*pixvar) + 1. #old: maybe incorrect? #res = np.abs(pixvar - real) + 1. if debug: print np.mean(res), np.min(res), np.max(res), np.std(res) if not os.path.exists('debug'): os.makedirs('debug') fileIO.writeFITS(medianCombined, 'debug/medianFlat.fits') fileIO.writeFITS(pixvar, 'debug/derivedFlat.fits') fileIO.writeFITS(res, 'debug/residualFlat.fits') if plots: if not os.path.exists('plots'): os.makedirs('plots') #generate a mesh grid fo plotting ysize, xsize = medianCombined.shape xx, yy = np.meshgrid(np.linspace(0, xsize, xsize), np.linspace(0, ysize, ysize)) fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, medianCombined, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlabel('Counts [electrons]') ax.set_zlim(8.9e4, 1.05e5) plt.savefig('plots/MedianFlat.png') plt.close() im = plt.imshow(medianCombined, origin='lower', vmin=8.9e4, vmax=1.05e5) c1 = plt.colorbar(im) c1.set_label('Counts [electrons]') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/Mediand2D.png') plt.close() fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, pixvar, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlim(0.95, 1.05) ax.set_zlabel('Counts [electrons]') plt.savefig('plots/PixelFlat.png') plt.close() im = plt.imshow(pixvar, origin='lower', vmin=0.95, vmax=1.05) c1 = plt.colorbar(im) c1.set_label('Counts [electrons]') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/PixelFlat2D.png') plt.close() fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(xx, yy, res, rstride=100, cstride=100, alpha=0.6, cmap=cm.jet) ax.set_xlabel('X [pixels]') ax.set_ylabel('Y [pixels]') ax.set_zlim(0.95, 1.05) ax.set_zlabel('Residual Flat Field') plt.savefig('plots/ResidualFlatField.png') plt.close() im = plt.imshow(res, origin='lower', vmin=0.95, vmax=1.05) c1 = plt.colorbar(im) c1.set_label('Residual Flat Field') plt.xlabel('X [pixels]') plt.ylabel('Y [pixels]') plt.savefig('plots/ResidualFlatField2D.png') plt.close() return res def testFlatCalibration(log, flats, surfaces=10, file='data/psf1x.fits', psfs=5000, sigma=0.75, iterations=7, weighting=True, plot=False, debug=False): """ Derive the PSF ellipticities for a given number of random surfaces with random PSF positions and a given number of flat fields median combined. This function is to derive the the actual values so that the knowledge (variance) can be studied. """ #read in PSF and rescale to avoid rounding or truncation errors data = pf.getdata(file) data /= np.max(data) data *= 300. #SNR about 10 for star... #derive reference values settings = dict(sigma=sigma, iterations=iterations, weighted=weighting) sh = shape.shapeMeasurement(data.copy(), log, **settings) reference = sh.measureRefinedEllipticity() #random positions for the PSFs, these positions are the lower corners #assume that this is done on quadrant level thus the xmax and ymax are 2065 and 2047, respectively xpositions = np.random.random_integers(0, 2047 - data.shape[1], psfs) ypositions = np.random.random_integers(0, 2065 - data.shape[0], psfs) out = {} #number of biases to median combine for a in flats: print 'Number of Flats to combine: %i / %i' % (a, flats[-1]) #data storage de1 = [] de2 = [] de = [] R2 = [] dR2 = [] e1 = [] e2 = [] e = [] for b in xrange(surfaces): print 'Random Realisations: %i / %i' % (b+1, surfaces) residual = generateResidualFlatField(combine=a, plots=plot, debug=debug) print 'Average residual = %e' % (np.mean(residual) - 1.) # generate 2D plot if b == 0 and plot: im = plt.imshow(residual, extent=(0, 2066, 2048, 0)) plt.scatter(xpositions + (data.shape[1]/2), ypositions + (data.shape[0]/2), color='white') c1 = plt.colorbar(im) c1.set_label('Residual Flat Field') plt.xlim(0, 2066) plt.ylim(0, 2048) plt.xlabel('Y [pixels]') plt.ylabel('X [pixels]') plt.savefig('residualFlat2D%i.png' % a) plt.close() #loop over the PSFs for xpos, ypos in zip(xpositions, ypositions): tmp = data.copy() #get the underlying residual surface and multiple with the PSF small = residual[ypos:ypos+data.shape[0], xpos:xpos+data.shape[1]].copy() #small += 1. small *= tmp #small *= tmp # depends on the residual geenration #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(small.copy(), log, **settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) de1.append(results['e1'] - reference['e1']) de2.append(results['e2'] - reference['e2']) de.append(results['ellipticity'] - reference['ellipticity']) dR2.append(results['R2'] - reference['R2']) out[a+1] = [e1, e2, e, R2, de1, de2, de, dR2] return out, reference def plotNumberOfFrames(results, reqe=3e-5, reqr2=1e-4, shift=0.1, outdir='results', timeStamp=False): """ Creates a simple plot to combine and show the results. :param res: results to be plotted [results dictionary, reference values] :type res: list :param reqe: the requirement for ellipticity [default=3e-5] :type reqe: float :param reqr2: the requirement for size R2 [default=1e-4] :type reqr2: float :param shift: the amount to shift the e2 results on the abscissa (for clarity) :type shift: float :param outdir: output directory to which the plots will be saved to :type outdir: str :param timeStamp: whether or not to include a time stamp to the output image :type timeStamp: bool :return: None """ if not os.path.exists(outdir): os.makedirs(outdir) #rename ref = results[1] res = results[0] print '\nSigma results:' txt = '%s' % datetime.datetime.isoformat(datetime.datetime.now()) fig = plt.figure() plt.title(r'VIS Flat Field Calibration: $\sigma(e)$') ax = fig.add_subplot(111) maxx = 0 frames = [] values = [] #loop over the number of frames combined for key in res: e1 = np.asarray(res[key][0]) e2 = np.asarray(res[key][1]) e = np.asarray(res[key][2]) std1 = np.std(e1) std2 = np.std(e2) std = np.std(e) frames.append(key) values.append(std) ax.scatter(key-shift, std, c='m', marker='*') ax.scatter(key, std1, c='b', marker='o') ax.scatter(key, std2, c='y', marker='s') if key > maxx: maxx = key print key, std, std1, std2 #label ax.scatter(key-shift, std, c='m', marker='*', label=r'$\sigma (e)$') ax.scatter(key, std1, c='b', marker='o', label=r'$\sigma (e_{1})$') ax.scatter(key, std2, c='y', marker='s', label=r'$\sigma (e_{2})$') #sort and interpolate values = np.asarray(values) frames = np.asarray(frames) srt = np.argsort(frames) x = np.arange(frames.min(), frames.max()+1) f = interpolate.interp1d(frames[srt], values[srt], kind='cubic') vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=20) try: msk = vals < reqe minn = np.min(x[msk]) plt.text(np.mean(frames), 8e-6, r'Flats Required $\raise-.5ex\hbox{$\buildrel>\over\sim$}$ %i' % np.ceil(minn), ha='center', va='center', fontsize=11) except: pass ax.fill_between(np.arange(maxx+10), np.ones(maxx+10)*reqe, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=reqe, c='g', ls='--', label='Requirement') plt.text(1, 0.9*reqe, '%.1e' % reqe, ha='left', va='top', fontsize=11) ax.set_yscale('log') ax.set_ylim(5e-6, 1e-4) ax.set_xlim(0, maxx+1) ax.set_xlabel('Number of Flat Fields Median Combined') ax.set_ylabel(r'$\sigma (e_{i})\ , \ \ \ i \in [1,2]$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=2.0, ncol=2) plt.savefig(outdir+'/FlatCalibrationsigmaE.pdf') plt.close() #same for R2s fig = plt.figure() plt.title(r'VIS Flat Field Calibration: $\frac{\sigma (R^{2})}{R_{ref}^{2}}$') ax = fig.add_subplot(111) ax.axhline(y=0, c='k', ls=':') maxx = 0 frames = [] values = [] #loop over the number of frames combined for key in res: dR2 = np.asarray(res[key][3]) #std = np.std(dR2) / ref['R2'] std = np.std(dR2) / np.mean(dR2) frames.append(key) values.append(std) print key, std ax.scatter(key, std, c='b', marker='s', s=35, zorder=10) if key > maxx: maxx = key #for the legend ax.scatter(key, std, c='b', marker='s', label=r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') #sort and interpolate values = np.asarray(values) frames = np.asarray(frames) srt = np.argsort(frames) x = np.arange(frames.min(), frames.max()) f = interpolate.interp1d(frames[srt], values[srt], kind='cubic') vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) try: msk = vals < reqr2 minn = np.min(x[msk]) plt.text(np.mean(frames), 2e-5, r'Flats Required $\raise-.5ex\hbox{$\buildrel>\over\sim$}$ %i' % np.ceil(minn), fontsize=11, ha='center', va='center') except: pass #show the requirement ax.fill_between(np.arange(maxx+10), np.ones(maxx+10)*reqr2, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=reqr2, c='g', ls='--', label='Requirement') plt.text(1, 0.9*reqr2, '%.1e' % reqr2, ha='left', va='top', fontsize=11) ax.set_yscale('log') ax.set_ylim(5e-6, 1e-3) ax.set_xlim(0, maxx+1) ax.set_xlabel('Number of Flat Fields Median Combined') ax.set_ylabel(r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8 ) plt.savefig(outdir+'/FlatCalibrationSigmaR2.pdf') plt.close() print '\nDelta results:' #loop over the number of frames combined for key in res: fig = plt.figure() ax = fig.add_subplot(111) plt.title(r'VIS Flat Field Calibration (%i exposures): $\delta e$' % key) de1 = np.asarray(res[key][4]) de2 = np.asarray(res[key][5]) de = np.asarray(res[key][6]) avg1 = np.mean(de1)**2 avg2 = np.mean(de2)**2 avg = np.mean(de)**2 #write down the values print key, avg, avg1, avg2 plt.text(0.08, 0.9, r'$\left< \delta e_{1} \right>^{2} = %e$' %avg1, fontsize=10, transform=ax.transAxes) plt.text(0.08, 0.85, r'$\left< \delta e_{2}\right>^{2} = %e$' %avg2, fontsize=10, transform=ax.transAxes) plt.text(0.08, 0.8, r'$\left< \delta | \bar{e} |\right>^{2} = %e$' %avg, fontsize=10, transform=ax.transAxes) ax.hist(de, bins=15, color='y', alpha=0.2, label=r'$\delta | \bar{e} |$', normed=True, log=True) ax.hist(de1, bins=15, color='b', alpha=0.5, label=r'$\delta e_{1}$', normed=True, log=True) ax.hist(de2, bins=15, color='g', alpha=0.3, label=r'$\delta e_{2}$', normed=True, log=True) ax.axvline(x=0, ls=':', c='k') ax.set_ylabel('Probability Density') ax.set_xlabel(r'$\delta e_{i}\ , \ \ \ i \in [1,2]$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=2.0, ncol=2) plt.savefig(outdir+'/FlatCalibrationEDelta%i.pdf' % key) plt.close() #same for R2s for key in res: fig = plt.figure() plt.title(r'VIS Flat Field Calibration (%i exposures): $\frac{\delta R^{2}}{R_{ref}^{2}}$' % key) ax = fig.add_subplot(111) dR2 = np.asarray(res[key][7]) avg = np.mean(dR2/ref['R2'])**2 ax.hist(dR2, bins=15, color='y', label=r'$\frac{\delta R^{2}}{R_{ref}^{2}}$', normed=True, log=True) print key, avg plt.text(0.1, 0.9, r'$\left<\frac{\delta R^{2}}{R^{2}_{ref}}\right>^{2} = %e$' %avg, fontsize=10, transform=ax.transAxes) ax.axvline(x=0, ls=':', c='k') ax.set_ylabel('Probability Density') ax.set_xlabel(r'$\frac{\delta R^{2}}{R_{ref}^{2}}$') if timeStamp: plt.text(0.83, 1.12, txt, ha='left', va='top', fontsize=9, transform=ax.transAxes, alpha=0.2) plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8) plt.savefig(outdir+'/FlatCalibrationDeltaSize%i.pdf' % key) plt.close() def findTolerableError(log, file='data/psf4x.fits', oversample=4.0, psfs=10000, iterations=7, sigma=0.75): """ Calculate ellipticity and size for PSFs of different scaling when there is a residual pixel-to-pixel variations. """ #read in PSF and renormalize it data = pf.getdata(file) data /= np.max(data) #PSF scalings for the peak pixel, in electrons scales = np.random.random_integers(1e2, 2e5, psfs) #set the scale for shape measurement settings = dict(sampling=1.0/oversample, itereations=iterations, sigma=sigma) #residual from a perfect no pixel-to-pixel non-uniformity residuals = np.logspace(-7, -1.6, 9)[::-1] #largest first tot = residuals.size res = {} for i, residual in enumerate(residuals): print'%i / %i' % (i+1, tot) R2 = [] e1 = [] e2 = [] e = [] #loop over the PSFs for scale in scales: #random residual pixel-to-pixel variations if oversample < 1.1: residualSurface = np.random.normal(loc=1.0, scale=residual, size=data.shape) elif oversample == 4.0: tmp = np.random.normal(loc=1.0, scale=residual, size=(170, 170)) residualSurface = zoom(tmp, 4.013, order=0) else: sys.exit('ERROR when trying to generate a blocky pixel-to-pixel non-uniformity map...') #make a copy of the PSF and scale it with the given scaling #and then multiply with a residual pixel-to-pixel variation tmp = data.copy() * scale * residualSurface #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(tmp.copy(), log, **settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) out = dict(e1=np.asarray(e1), e2=np.asarray(e2), e=np.asarray(e), R2=np.asarray(R2)) res[residual] = out return res def plotTolerableErrorR2(res, output, req=1e-4): fig = plt.figure() plt.title(r'VIS Flat Fielding') ax = fig.add_subplot(111) #loop over the number of bias frames combined vals = [] for key in res.keys(): dR2 = res[key]['R2'] normed = np.std(dR2) / np.mean(dR2) ax.scatter(key, normed, c='m', marker='*', s=35) vals.append(normed) print key, normed #for the legend ax.scatter(key, normed, c='m', marker='*', label=r'$\frac{\sigma(R^{2})}{R_{ref}^{2}}$') #show the requirement ks = np.asarray(res.keys()) ran = np.linspace(ks.min() * 0.99, ks.max() * 1.01) ax.fill_between(ran, np.ones(ran.size) * req, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=req, c='g', ls='--', label='Requirement') #find the crossing srt = np.argsort(ks) values = np.asarray(vals) f = interpolate.interp1d(ks[srt], values[srt], kind='cubic') x = np.logspace(np.log10(ks.min()), np.log10(ks.max()), 100) vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) msk = vals < req maxn = np.max(x[msk]) plt.text(1e-5, 2e-5, r'Error must be $\leq %.2e$ per cent' % (maxn*100), fontsize=11, ha='center', va='center') ax.set_yscale('log') ax.set_xscale('log') ax.set_ylim(1e-7, 1e-2) ax.set_xlim(ks.min() * 0.99, ks.max() * 1.01) ax.set_xlabel('Error in the Flat Field Map') ax.set_ylabel(r'$\frac{\sigma (R^{2})}{R_{ref}^{2}}$') plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8, loc='upper left') plt.savefig(output) plt.close() def plotTolerableErrorE(res, output, req=3e-5): fig = plt.figure() plt.title(r'VIS Flat Fielding') ax = fig.add_subplot(111) #loop over the number of bias frames combined vals = [] for key in res.keys(): e1 = np.std(res[key]['e1']) e2 = np.std(res[key]['e']) e = np.std(res[key]['e']) vals.append(e) ax.scatter(key, e1, c='m', marker='*', s=35) ax.scatter(key, e2, c='y', marker='s', s=35) ax.scatter(key, e, c='r', marker='o', s=35) print key, e, e1, e2 #for the legend ax.scatter(key, e1, c='m', marker='*', label=r'$\sigma(e_{1})$') ax.scatter(key, e2, c='y', marker='s', label=r'$\sigma(e_{2})$') ax.scatter(key, e, c='r', marker='o', label=r'$\sigma(e)$') #show the requirement ks = np.asarray(res.keys()) ran = np.linspace(ks.min() * 0.99, ks.max() * 1.01) ax.fill_between(ran, np.ones(ran.size) * req, 1.0, facecolor='red', alpha=0.08) ax.axhline(y=req, c='g', ls='--', label='Requirement') #find the crossing srt = np.argsort(ks) values = np.asarray(vals) f = interpolate.interp1d(ks[srt], values[srt], kind='cubic') x = np.logspace(np.log10(ks.min()), np.log10(ks.max()), 100) vals = f(x) ax.plot(x, vals, ':', c='0.2', zorder=10) msk = vals < req maxn = np.max(x[msk]) plt.text(1e-5, 2e-5, r'Error for $e$ must be $\leq %.2e$ per cent' % (maxn*100), fontsize=11, ha='center', va='center') ax.set_yscale('log') ax.set_xscale('log') ax.set_ylim(1e-7, 1e-2) ax.set_xlim(ks.min() * 0.99, ks.max() * 1.01) ax.set_xlabel('Error in the Flat Field Map') ax.set_ylabel(r'$\sigma (e_{i})\ , \ \ \ i \in [1,2]$') plt.legend(shadow=True, fancybox=True, numpoints=1, scatterpoints=1, markerscale=1.8, loc='upper left') plt.savefig(output) plt.close() def testNoFlatfieldingEffects(log, file='data/psf1x.fits', oversample=1.0, psfs=500): """ Calculate ellipticity and size variance and error in case of no pixel-to-pixel flat field correction. """ #read in PSF and renormalize it data = pf.getdata(file) data /= np.max(data) data *= 1e5 #derive reference values settings = dict(sampling=1.0/oversample) sh = shape.shapeMeasurement(data.copy(), log, **settings) reference = sh.measureRefinedEllipticity() print reference #residual residual = pf.getdata('data/VISFlatField2percent.fits') #'data/VISFlatField1percent.fits' if oversample == 4.0: residual = zoom(zoom(residual, 2, order=0), 2, order=0) elif oversample == 1.0: pass else: print 'ERROR--cannot do arbitrary oversampling...' #random positions for the PSFs, these positions are the lower corners xpositions = np.random.random_integers(0, residual.shape[1] - data.shape[1], psfs) ypositions = np.random.random_integers(0, residual.shape[0] - data.shape[0], psfs) #data storage out = {} de1 = [] de2 = [] de = [] R2 = [] dR2 = [] e1 = [] e2 = [] e = [] rnd = 1 tot = xpositions.size #loop over the PSFs for xpos, ypos in zip(xpositions, ypositions): print'%i / %i' % (rnd, tot) rnd += 1 #make a copy of the PSF tmp = data.copy() #get the underlying residual surface ond multiple the PSF with the surface small = residual[ypos:ypos+data.shape[0], xpos:xpos+data.shape[1]].copy() small *= tmp #measure e and R2 from the postage stamp image sh = shape.shapeMeasurement(small.copy(), log, **settings) results = sh.measureRefinedEllipticity() #save values e1.append(results['e1']) e2.append(results['e2']) e.append(results['ellipticity']) R2.append(results['R2']) de1.append(results['e1'] - reference['e1']) de2.append(results['e2'] - reference['e2']) de.append(results['ellipticity'] - reference['ellipticity']) dR2.append(results['R2'] - reference['R2']) out[1] = [e1, e2, e, R2, de1, de2, de, dR2] return out, reference if __name__ == '__main__': run = True debug = False plots = True error = False #start the script log = lg.setUpLogger('flatfieldCalibration.log') log.info('Testing flat fielding calibration...') if error: res = findTolerableError(log) fileIO.cPickleDumpDictionary(res, 'errors/residuals.pk') res = cPickle.load(open('errors/residuals.pk')) plotTolerableErrorE(res, output='errors/FlatFieldingTolerableErrorE.pdf') plotTolerableErrorR2(res, output='errors/FlatFieldingTolerableErrorR2.pdf') if run: results = testFlatCalibration(log, flats=np.arange(5, 100, 9)) fileIO.cPickleDumpDictionary(results, 'flatfieldResults.pk') if debug: #calculate RMS on image with x frames combined together combined = generateResidualFlatField(combine=30, plots=True, debug=True) print np.std(combined), np.std(combined[500:561, 500:561]), np.std(combined[300:361, 300:361]) results = testNoFlatfieldingEffects(log, oversample=4.0, file='data/psf4x.fits', psfs=400) if plots: if not run: results = cPickle.load(open('flatfieldResults.pk')) plotNumberOfFrames(results) log.info('Run finished...\n\n\n')

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tests/test_rqscheduler.py

dymaxionlabs/nb_workflows

4

96104

<reponame>dymaxionlabs/nb_workflows from labfunctions.conf.server_settings import settings from labfunctions.control_plane import rqscheduler def test_rqscheduler_run(mocker): mocker.patch( "labfunctions.control_plane.rqscheduler.Scheduler.run", return_value=None ) rqscheduler.run(settings.RQ_REDIS, 5, "INFO")

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getch.py

salt-die/Snippets

3

153122

<filename>getch.py import sys from io import BytesIO if sys.platform.startswith('linux'): import fcntl import os import termios import tty def getch(block=True): fd = sys.stdin.fileno() settings = termios.tcgetattr(fd) flags = fcntl.fcntl(fd, fcntl.F_GETFL) try: tty.setraw(fd) if not block: fcntl.fcntl(fd, fcntl.F_SETFL, flags | os.O_NONBLOCK) return sys.stdin.buffer.read(1) finally: fcntl.fcntl(fd, fcntl.F_SETFL, flags) termios.tcsetattr(fd, termios.TCSADRAIN, settings) elif sys.platform == 'win32': import msvcrt def getch(block=True): if not block and not msvcrt.kbhit(): return b'' return msvcrt.getch() else: try: # Try for Mac import Carbon Carbon.Evt # Not in *nix except (ModuleNotFoundError, AttributeError) as e: raise OSError(f'getch not implemented for {sys.platform}') from e def getch(block=True): # I haven't tested this. if not block and Carbon.Evt.EventAvail(0x0008)[0] == 0: # 0x0008 is the keyDownMask return b'' return bytes(chr(Carbon.Evt.GetNextEvent(0x0008)[1][1] & 0x000000FF), 'utf8') def flush(): with BytesIO() as r: while c := getch(block=False): r.write(c) return r.getvalue()

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purpleair_connector/main.py

tetradsensors/gcp-functions

0

118590

from google.cloud import bigquery, storage import json import pandas as pd import time import requests import os import datetime import geojson import numpy as np from matplotlib.path import Path from time import sleep import yaml UPDATE_MINS = 60 gs_client = storage.Client() env = None _area_params = None # Download the project environment variables # env = yaml.load( # gs_client.get_bucket(os.getenv('gs_bucket')).get_blob(os.getenv('config')).download_as_string(), # Loader=yaml.SafeLoader) def getProjectConfigFile(): if not hasattr(getProjectConfigFile, "updateTime"): getProjectConfigFile.updateTime = 0 if time.time() - getProjectConfigFile.updateTime > (UPDATE_MINS*60): getProjectConfigFile.env = yaml.load(gs_client.get_bucket(os.environ['gs_bucket']).get_blob(os.environ['config']).download_as_string(), Loader=yaml.SafeLoader) getProjectConfigFile.updateTime = time.time() return getProjectConfigFile.env def getAreaParams(): if not hasattr(getAreaParams, "updateTime"): getAreaParams.updateTime = 0 if time.time() - getAreaParams.updateTime > (UPDATE_MINS*60): bucket = env['storage']['server_bucket']['name'] area_params_json = env['storage']['server_bucket']['files']['area_params'] getAreaParams.params = json.loads( gs_client.get_bucket(bucket).get_blob(area_params_json).download_as_string()) getAreaParams.updateTime = time.time() getAreaParams.params = buildAreaModelsFromJson(getAreaParams.params) return getAreaParams.params def loadBoundingBox(bbox_info): if bbox_info is None: return None rows = [row for row in bbox_info] bounding_box_vertices = [(index, float(row['Latitude']), float(row['Longitude'])) for row, index in zip(rows, range(len(rows)))] return bounding_box_vertices def buildAreaModelsFromJson(json_data): area_models = {} for key in json_data: this_model = {} this_model['name'] = json_data[key]['Name'] this_model['timezone'] = json_data[key]['Timezone'] this_model['idstring'] = json_data[key]['ID String'] this_model['elevationfile'] = json_data[key]['Elevation File'] this_model['note'] = json_data[key]['Note'] # this_model['elevationinterpolator'] = buildAreaElevationInterpolator(json_data[key]['Elevation File']) this_model['elevationinterpolator'] = None this_model['boundingbox'] = loadBoundingBox(json_data[key]['Boundingbox']) # this_model['correctionfactors'] = loadCorrectionFactors(json_data[key]['Correction Factors'],json_data[key]['Timezone']) # this_model['lengthscales'] = loadLengthScales(json_data[key]['Length Scales'], json_data[key]['Timezone']) if 'Source table map' in json_data[key]: this_model['sourcetablemap'] = json_data[key]['Source table map'] # else: # this_model['sourcetablemap'] = None area_models[key] = this_model return area_models # Information for all the regions # _area_params = buildAreaModelsFromJson( # json.loads( # gs_client.get_bucket(env['storage']['server_bucket']['name'] # ).get_blob(env['storage']['server_bucket']['files']['area_params'] # ).download_as_string())) def getAreaModelBounds(area_model): print(area_model.keys()) if area_model['boundingbox'] is None: return None area_bounds = area_model['boundingbox'] bounds = { 'lat_hi': area_bounds[0][1], 'lon_hi': area_bounds[1][2], 'lat_lo': area_bounds[2][1], 'lon_lo': area_bounds[3][2] } if bounds['lat_hi'] <= bounds['lat_lo'] or bounds['lon_hi'] < bounds['lon_lo']: return None else: return bounds def isQueryInBoundingBox(bounding_box_vertices, query_lat, query_lon): verts = [(0, 0)] * len(bounding_box_vertices) for elem in bounding_box_vertices: verts[elem[0]] = (elem[2], elem[1]) # Add first vertex to end of verts so that the path closes properly verts.append(verts[0]) codes = [Path.MOVETO] codes += [Path.LINETO] * (len(verts) - 2) codes += [Path.CLOSEPOLY] boundingBox = Path(verts, codes) return boundingBox.contains_point((query_lon, query_lat)) def getAreaModelByLocation(area_models, lat=0.0, lon=0.0, string=None): if string is None: for key in area_models: if (isQueryInBoundingBox(area_models[key]['boundingbox'], lat, lon)): print(f'Using area_model for {key}') return area_models[key] else: try: return area_models[string] except: print("Got bad request for area by string: " + str(string)) print("Query location "+str(lat)+ "," + str(lon) + " not in any known model area") return None def applyRegionalLabelsToDataFrame(regions_dict, df, null_value=np.nan, trim=False): df['Label'] = null_value for region_name, region_info in regions_dict.items(): bbox = getAreaModelBounds(region_info) if bbox is None: continue df.loc[ (df['Lat'] >= bbox['lat_lo']) & (df['Lat'] <= bbox['lat_hi']) & (df['Lon'] >= bbox['lon_lo']) & (df['Lon'] <= bbox['lon_hi']), 'Label' ] = region_info['name'] print(f"For region {region_name}, applied labels to {len(df[df['Label'] == region_info['name']])} rows") print(f"Regional labels applied to {len(df[~df['Label'].isnull()])} out of {len(df)} rows. ({int(100 * (len(df[~df['Label'].isnull()]) / len(df)))})") if trim: x = len(df) df = df.dropna(subset=['Label']) print(f"Dropped {x - len(df)} unlabeled rows.") return df def chunk_list(ls, chunk_size=10000): ''' BigQuery only allows inserts <=10,000 rows ''' for i in range(0, len(ls), chunk_size): yield ls[i: i + chunk_size] def setPMSModels(df, col_name): pms_models = ['PMS1003', 'PMS3003', 'PMS5003', 'PMS7003'] for model in pms_models: df.loc[df['Type'].str.contains(model), col_name] = model return df def setChildFromParent(df, pairings, col_name): df.loc[pairings.index, col_name] = df.loc[pairings, col_name].values return df def getParentChildPairing(df): ''' Purple Air devices have two PM sensors inside. Data is reported for both sensors seperately, but one sensor is considered the "parent" and one is the "child". The child has lots of missing information, like DEVICE_LOCATIONTYPE, Flag, Type. So we create this Series to link parents and children, then later use this Series to fill in missing data for the children with data from their parents. Beware: sometimes we find orphans - rows with a non-null ParentID, but no corresponding row with an ID equal to the value of that ParentID. ''' # Get the rows where ParentID is not Null (ParentID values are the IDs of the parent sensors) pairings = df['ParentID'].loc[~df['ParentID'].isnull()].astype(int) # Eliminate orphans (sorry orphans) pairings = pairings[pairings.isin(df.index)] return pairings def main(data, context): # with open('area_params.json') as json_file: # json_temp = json.load(json_file) # _area_models = buildAreaModelsFromJson(json_temp) global _area_params, env env = getProjectConfigFile() _area_params = getAreaParams() response = None try: response = json.loads(requests.get('https://www.purpleair.com/json?a').text) results = response['results'] except Exception as e: print('Could not download data. Exception: ', str(e), response) try: print('trying again after 15 seconds') sleep(20) response = json.loads(requests.get('https://www.purpleair.com/json?a').text) results = response['results'] except: print('Could not download data (take 2). Exception: ', str(e), response) return # Convert JSON response to a Pandas DataFrame df = pd.DataFrame(results) print(f'rows: {len(df)}') if df.empty: return # Trim off old data df['LastSeen'] = pd.to_datetime(df['LastSeen'], unit='s', utc=True) # Remove all datapoints older than 6 minutes. Run every 5 minutes, so give 1 minute overlap df = df[df['LastSeen'] > (pd.Timestamp.utcnow() - pd.Timedelta(6, unit='minutes'))] # Following Series operations depend on having an index df = df.set_index('ID') # Get Series with index = child ID and 'ParentID' = Parent ID pairing = getParentChildPairing(df) # Set DEVICE_LOCATIONTYPE child to DEVICE_LOCATIONTYPE parent df = setChildFromParent(df, pairing, 'DEVICE_LOCATIONTYPE') # Set flag of child sensor to flag of parent sensor df = setChildFromParent(df, pairing, 'Flag') # Set the 'Type' string of child to that of parent df = setChildFromParent(df, pairing, 'Type') # Use 'Flag', 'A_H', 'Hidden' to filter out bad data # 'Flag': Data flagged for unusually high readings # 'A_H': true if the sensor output has been downgraded or marked for attention due to suspected hardware issues # 'Hidden': Hide from public view on map: true/false df = df.fillna({ 'A_H': False, 'Flag': False, 'Hidden': False }) # Convert JSON 'true'/'false' strings into bools df = df.replace({'true': True, 'false': False}) # Change types df = df.astype({ 'A_H': bool, 'Flag': bool, 'Hidden': bool, 'PM2_5Value': float, 'temp_f': float, 'LastSeen': str, }) # If any of these are true, remove the row df['Flag'] = df['Flag'] | df['A_H'] | df['Hidden'] # Remove rows df = df[df['DEVICE_LOCATIONTYPE'] == 'outside'] # Remove sensors not outside df = df[df['Flag'] != 1] # Remove sensors with Flag, A_H, or Hidden flags df = df.dropna(subset=['Lat', 'Lon']) # Remove sensors with no lat/lon info # Apply regional labels ('slc_ut', 'chatt_tn', etc.) df = applyRegionalLabelsToDataFrame(_area_params, df, trim=True) # Create the GPS column df['GPS'] = df.apply(lambda x: geojson.dumps(geojson.Point((x['Lon'], x['Lat']))), axis=1) # Move bad PM data out of cleaned column df['PM2_5_Raw'] = df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'PM2_5Value'] df['Flags'] = 0 df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'Flags'] |= 2 df.loc[df['PM2_5Value'] >= float(env['pm_threshold']), 'PM2_5Value'] = np.nan # Convert temperature F to C df['temp_f'] = (df['temp_f'] - 32) * (5. / 9) # clean up PMS 'Type' names df = setPMSModels(df, col_name='PMSModel') # Reduce DataFrame to desired columns df = df.reset_index() cols_to_keep = ['LastSeen', 'ID', 'GPS', 'PM2_5Value', 'PM2_5_Raw', 'Flags', 'PMSModel', 'humidity', 'temp_f', 'pressure', 'Label'] df = df.loc[:, df.columns.isin(cols_to_keep)] # Append 'PP' to device id's df['ID'] = 'PP' + df['ID'].astype(str) # Add 'Source' = 'PurpleAir' df['Source'] = 'PurpleAir' # Finally, convert NaN to None df = df.replace({np.nan: None}) # Rename columns df = df.rename({ 'LastSeen': 'Timestamp', 'ID': 'DeviceID', 'PM2_5Value': 'PM2_5', 'humidity': 'Humidity', 'temp_f': 'Temperature', 'pressure': 'Pressure' }, axis='columns') # Convert dataframe to list of dicts data = df.to_dict('records') # Create unique row_ids to avoid duplicates when inserting overlapping data row_ids = pd.util.hash_pandas_object(df[['Timestamp', 'DeviceID']]).values.astype(str) bq_client = bigquery.Client() target_table = bq_client.dataset(env['bigquery']['tbl_telemetry']['ds_name']).table(env['bigquery']['tbl_telemetry']['tbl_name']) # Maximum upload size for BigQuery API is 10,000 rows, so we have to upload the data in chunks for i, (data_chunk, rows_chunk) in enumerate(zip(chunk_list(data, chunk_size=10000), chunk_list(row_ids, chunk_size=10000))): print(f'Sending chunk {i + 1}...') errors = bq_client.insert_rows_json( table=target_table, json_rows=data_chunk, row_ids=rows_chunk ) if errors: print(errors) else: print(f"Inserted {len(rows_chunk)} rows") if __name__ == '__main__': # This only runs locally import os os.environ['gs_bucket'] = "tetrad-resources" os.environ['config'] = "tetrad_config.yaml" main('data', 'context')

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examples/gradient_damagex.py

TTitscher/fenics-constitutive

0

69247

""" Implicit gradient-enhanced damage model in dolfinx ================================================== For the theory and the constitutive model, please refer to the dolfin version :ref:`gdm-label`. Here, you see the "quadrature" approach working in dolfinx without the need of `LocalProject`. """ from gdm_constitutive import * from gdm_analytic import PeerlingsAnalytic import dolfinx as df from petsc4py import PETSc from mpi4py import MPI import ufl import basix import matplotlib.pyplot as plt class GDMProblemX: def __init__(self, mesh, mat, deg=2, q_deg=4, fd_np=None): self.mesh, self.mat= mesh, mat Ed = ufl.VectorElement("CG", mesh.ufl_cell(), degree=deg) Ee = ufl.FiniteElement("CG", mesh.ufl_cell(), degree=deg) self.V = df.fem.FunctionSpace(mesh, (Ed * Ee)) self.Vd, self.Ve = self.V.sub(0), self.V.sub(1) self.u = df.fem.Function(self.V) q = "Quadrature" cell = mesh.ufl_cell() voigt = 3 QF = ufl.FiniteElement(q, cell, q_deg, quad_scheme="default") QV = ufl.VectorElement(q, cell, q_deg, quad_scheme="default", dim=voigt) QT = ufl.TensorElement( q, cell, q_deg, quad_scheme="default", shape=(voigt, voigt) ) VQF, VQV, VQT = [df.fem.FunctionSpace(mesh, Q) for Q in [QF, QV, QT]] self.q_sigma = df.fem.Function(VQV) self.q_e = df.fem.Function(VQF) self.q_eeq = df.fem.Function(VQF) self.q_dsigma_deps = df.fem.Function(VQT) self.q_dsigma_de = df.fem.Function(VQV) self.q_deeq_deps = df.fem.Function(VQV) # define functions dd, de = ufl.TrialFunctions(self.V) d_, e_ = ufl.TestFunctions(self.V) self.d, self.e = ufl.split(self.u) # define form self.metadata = {"quadrature_degree": q_deg, "quadrature_scheme": "default"} self.dxm = ufl.dx(metadata=self.metadata) # prepare strain evaluation eps = mat.eps map_c = mesh.topology.index_map(mesh.topology.dim) num_cells = map_c.size_local + map_c.num_ghosts self.cells = np.arange(0, num_cells, dtype=np.int32) basix_celltype = getattr(basix.CellType, mesh.topology.cell_type.name) self.q_points, wts = basix.make_quadrature(basix_celltype, q_deg) self.strain_expr = df.fem.Expression(eps(self.d), self.q_points) self.e_expr = df.fem.Expression(self.e, self.q_points) self.evaluate_constitutive_law() self.bcs = None if fd_np is None: fd_np = lambda x: 1.0 Vfd = df.fem.FunctionSpace(mesh, ("DG", 0)) fd = df.fem.Function(Vfd) fd.x.array[:] = fd_np(Vfd.tabulate_dof_coordinates()) R = fd * ufl.inner(eps(d_), self.q_sigma) * self.dxm R += e_ * (self.e - self.q_eeq) * self.dxm R += ufl.dot(ufl.grad(e_), mat.l ** 2 * ufl.grad(self.e)) * self.dxm dR = fd * ufl.inner(eps(d_), self.q_dsigma_deps * eps(dd)) * self.dxm dR += fd * ufl.inner(eps(d_), self.q_dsigma_de * de) * self.dxm dR += e_ * (de - ufl.dot(self.q_deeq_deps, eps(dd))) * self.dxm dR += ufl.dot(ufl.grad(e_), mat.l ** 2 * ufl.grad(de)) * self.dxm self.R, self.dR = df.fem.form(R), df.fem.form(dR) self.solver = None def evaluate_constitutive_law(self): with df.common.Timer("compute strains"): strain = self.strain_expr.eval(self.cells) e = self.e_expr.eval(self.cells) with df.common.Timer("evaluate constitutive law"): self.mat.evaluate(strain.flatten(), e.flatten()) with df.common.Timer("assign q space"): self.q_sigma.x.array[:] = self.mat.sigma.flat self.q_dsigma_deps.x.array[:] = self.mat.dsigma_deps.flat self.q_dsigma_de.x.array[:] = self.mat.dsigma_de.flat self.q_eeq.x.array[:] = self.mat.eeq.flat self.q_deeq_deps.x.array[:] = self.mat.deeq.flat def update(self): e = self.e_expr.eval(self.cells) self.mat.update(e.flatten()) def form(self, x: PETSc.Vec): """This function is called before the residual or Jacobian is computed. This is usually used to update ghost values. Parameters ---------- x The vector containing the latest solution """ x.ghostUpdate(addv=PETSc.InsertMode.INSERT, mode=PETSc.ScatterMode.FORWARD) x.copy(self.u.vector) self.u.vector.ghostUpdate( addv=PETSc.InsertMode.INSERT, mode=PETSc.ScatterMode.FORWARD ) self.evaluate_constitutive_law() def J(self, x: PETSc.Vec, A: PETSc.Mat, P=None): """Assemble the Jacobian matrix.""" A.zeroEntries() df.fem.petsc.assemble_matrix(A, self.dR, bcs=self.bcs) A.assemble() def F(self, x: PETSc.Vec, b: PETSc.Vec): """Assemble the residual F into the vector b.""" # Reset the residual vector with b.localForm() as b_local: b_local.set(0.0) df.fem.petsc.assemble_vector(b, self.R) df.fem.apply_lifting(b, [self.dR], bcs=[self.bcs], x0=[x], scale=-1.0) b.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE) df.fem.set_bc(b, self.bcs, x, -1.0) def solve(self): if self.solver is None: self.a = self.dR self.L = self.R self.solver = df.nls.petsc.NewtonSolver(MPI.COMM_WORLD, self) self.solver.atol = 1.e-8 return self.solver.solve(self.u) def plane_at(x): """ """ def boundary(c): return np.isclose(c[0, :], x) return boundary def gdm_error(n_elements): """ ... evaluated in 2D """ e = PeerlingsAnalytic() mesh = df.mesh.create_rectangle( MPI.COMM_WORLD, [[0, 0], [e.L / 2.0, 1]], [n_elements, 1], df.mesh.CellType.quadrilateral, ) mat = GDMPlaneStrain(E=e.E, nu=0.0, ft=e.E * e.kappa0, l=e.l, dmg=damage_perfect) def area(coords): A = np.full(len(coords), 10.0) A[coords[:, 0] < e.W / 2.0] *= 1.0 - e.alpha return A problem = GDMProblemX(mesh, mat, fd_np=area) V = problem.Vd # space of displacements to apply the BCs b_facets_l = df.mesh.locate_entities_boundary(mesh, 1, plane_at(0.0)) b_facets_r = df.mesh.locate_entities_boundary(mesh, 1, plane_at(e.L / 2.0)) b_dofs_lx = df.fem.locate_dofs_topological(V.sub(0), 1, b_facets_l) b_dofs_ly = df.fem.locate_dofs_topological(V.sub(1), 1, b_facets_l) b_dofs_rx = df.fem.locate_dofs_topological(V.sub(0), 1, b_facets_r) u_bc = df.fem.Constant(mesh, 0.0) problem.bcs = [ df.fem.dirichletbc(PETSc.ScalarType(0), b_dofs_lx, V.sub(0)), df.fem.dirichletbc(PETSc.ScalarType(0), b_dofs_ly, V.sub(1)), df.fem.dirichletbc(u_bc, b_dofs_rx, V.sub(0)), ] for t in np.linspace(0.0, 1.0, 11): u_bc.value = t * e.deltaL / 2.0 iterations, converged = problem.solve() assert converged problem.update() # Honestly, I have not idea (yet) how to properly/easily compute the # errornorm to the analytic solution. Thus, we extract the dof # coordinates x to compute analytic dof values. e_fem = problem.u.sub(1).collapse() xs = e_fem.function_space.tabulate_dof_coordinates()[:, 0] e_exact = [e.e(x) for x in xs] return np.linalg.norm(e_fem.x.array - e_exact) def convergence_test(): ns = [50, 100, 200, 400] errors = [] for n in ns: error = gdm_error(n) print(f"Error to analytic solution with {n} elements is {error}.") errors.append(error) ps = [] for i in range(len(ns) - 1): p = np.log(errors[i] - errors[i + 1]) / np.log(1.0 / ns[i] - 1.0 / ns[i + 1]) ps.append(p) import matplotlib.pyplot as plt plt.figure(figsize=(6, 3)) plt.loglog(ns, errors, "-ko") plt.xlabel("# elements") plt.ylabel("error") plt.tight_layout() plt.savefig("gdm_convergencex.png") plt.show() if __name__ == "__main__": convergence_test()

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draft/migrations/0001_initial.py

zffgithub/genshin-bp

0

57951

# Generated by Django 3.0.4 on 2020-04-17 23:13 from django.db import migrations, models import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Champion', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('lane', models.CharField(default='', help_text='한글로 입력해주세요. ex)上单/中路', max_length=20, verbose_name='라인')), ('keyword', models.CharField(default='', help_text='"/" 로 구분해주세요. ex)가렌/garen', max_length=255, verbose_name='검색어')), ('no', models.CharField(default='', max_length=3, verbose_name='角色번호')), ('name', models.CharField(default='', help_text='한글로 입력해주세요. ex)가렌', max_length=20, verbose_name='角色명')), ], options={ 'verbose_name': '角色', 'verbose_name_plural': '角色', }, ), migrations.CreateModel( name='Draft', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('match_name', models.CharField(max_length=255, verbose_name='매치 이름')), ('red_team_name', models.CharField(max_length=255, verbose_name='红队名称')), ('blue_team_name', models.CharField(max_length=255, verbose_name='蓝队名称')), ('password', models.CharField(max_length=255, verbose_name='패스워드')), ('banpick', models.CharField(blank=True, max_length=255, verbose_name='禁选Data')), ('timer', models.DateTimeField(blank=True, null=True, verbose_name='시작')), ('date', models.DateTimeField(default=django.utils.timezone.now, verbose_name='일시')), ], options={ 'verbose_name': '禁选', 'verbose_name_plural': '禁选', }, ), ]

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src/compat_func.py

rangell/icff

0

68351

<gh_stars>0 import copy import numpy as np from sparse_dot_mkl import dot_product_mkl from utils import MIN_FLOAT from IPython import embed #def raw_overlap(node, constraint, num_points): def raw_overlap(raw_reps, stacked_constraints, num_points): extreme_raw_reps = copy.deepcopy(raw_reps).astype(float) extreme_raw_reps *= np.inf extreme_constraints = copy.deepcopy(stacked_constraints).astype(float) extreme_constraints.data *= np.inf compat_mx = dot_product_mkl( extreme_raw_reps, extreme_constraints.T, dense=True ) incompat_mx = ((compat_mx == -np.inf) | np.isnan(compat_mx)) pos_overlap_scores = dot_product_mkl( raw_reps.astype(float), stacked_constraints.T, dense=True ) pos_overlap_scores = np.array(pos_overlap_scores) pos_overlap_mask = (pos_overlap_scores > 0) pos_feat_totals = np.array(np.sum(stacked_constraints > 0, axis=1).T) overlap_scores = pos_overlap_scores / pos_feat_totals overlap_scores *= pos_overlap_mask overlap_scores[overlap_scores == 1] = num_points overlap_scores[incompat_mx] = -np.inf return np.asarray(overlap_scores) def transformed_overlap(node, constraint): # FIXME: this won't work assert False rep = node.transformed_rep pair_product = rep * constraint if np.array_equal(rep, np.ones_like(rep) * -np.inf) \ or not np.all(pair_product >= 0): return MIN_FLOAT else: score = np.sum(pair_product > 0) / np.sum(constraint != 0) return score if score < 1 else num_points * score

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exercicios_basico/ex007.py

montalvas/python

0

186271

<gh_stars>0 # Informe duas notas e sem seguida mostre sua média. n1 = float(input('Informe a primeira nota: ')) n2 = float(input('Informe a segunda nota: ')) print("As notas do aluno foram {} e {}, logo sua média será {:.2f}".format(n1, n2, (n1 + n2)/2))

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src/python/utility/shared.py

andyjost/Sprite

1

119842

<filename>src/python/utility/shared.py from copy import copy import collections, six, sys class Shared(object): ''' Manages an object with copy-on-write semantics. To access the contained object for reading or writing, use the ``read`` and ``write`` methods, resp. If the object has multiple references, then writing will trigger a copy. ''' def __init__(self, ty, obj=None): self.ty = ty if obj is None: self.obj = ty() assert self.unique else: self.obj = obj def __copy__(self): return Shared(self.ty, self.obj) # sharing copy @property def read(self): return self.obj @property def write(self): if not self.unique: self.obj = self.ty(self.obj) # copy for write assert self.unique return self.obj @property def refcnt(self): return sys.getrefcount(self.obj) - 1 @property def unique(self): return self.refcnt == 1 def __str__(self): return str(self.read) def __repr__(self): return str(self) return 'Shared(refcnt=%s, %s)' % (self.refcnt, self.obj) # Read-only container methods, for convenience. def __contains__(self, key): return key in self.obj def __len__(self): return len(self.obj) def __getitem__(self, key): return self.obj[key] def __iter__(self): return iter(self.obj) class DefaultDict(collections.defaultdict): '''Like defaultdict but recursively copies values.''' def __copy__(self): return DefaultDict(self.default_factory, {k: copy(v) for k,v in six.iteritems(self)}) copy = __copy__ def compose(typefunction, ty): ''' Composes a type function and type. The type function is a type, such as Shared or DefaultDict, that takes another type as its only argument. The returned object has object-copy semantics. ''' def factory(obj=None): if obj is None: return typefunction(ty) else: return copy(obj) return factory

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scraper.py

noswald/PatentScraper1.0

2

119063

from pyvirtualdisplay import Display from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.common.exceptions import WebDriverException from selenium.common.exceptions import TimeoutException from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.common.by import By from selenium.webdriver.common.keys import Keys import time from datetime import datetime from lxml import html from lxml import etree from io import StringIO from fake_useragent import UserAgent import pandas as pd import numpy as np dateFormat = '%Y-%m-% %H:%M:%S' fileDate = '%Y%m%d%H%M' filePath = '/home/noswald/Documents/PersonalScraper/' chromeDriverPath = '/home/noswald/Documents/PersonalScraper/chromedriver' searchValue = 'wallet' searchPage = 'http://patft.uspto.gov/netahtml/PTO/search-adv.htm' queryID = 'mytextarea' searchButtonValue = 'Search' yrsDropDownValue = 'PTXT' display = Display(visible=0,size=(800,600)) display.start() #add tor dependency and logic PROXY = 'socks5://127.0.0.1:9050' chrome_options = webdriver.ChromeOptions() chrome_options.add_argument('--proxy-server=%s' % PROXY) #add useragent ua = UserAgent() userAgent = ua.random print("My user agent is: " + userAgent) chrome_options.add_argument('user-agent=%s' % userAgent) #start browser browser = webdriver.Chrome(chrome_options = chrome_options, executable_path = chromeDriverPath) browser.get(searchPage) inputElement = browser.find_element_by_id(queryID) inputElement.send_keys(searchValue) time.sleep(2) inputElement.submit() html_source = browser.page_source curDT = datetime.now() datepulled = curDT t = curDT.strftime('%Y%m%d%H%M') #uncomment if writing html file to directory #f = open(filePath+'test1_' + t + '.html','w') #f.write(html_source) #f.close() tree = html.parse(StringIO(html_source)) #added logic to pull correct end range (1-length of initial number of rows in table) endRow = len(tree.xpath('//table[1]//tr'))-1 patentRank = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[1]//text()')[0] for x in range(2,endRow)] patentNumber = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[2]//text()')[0] for x in range(2,endRow)] patentTitle = [tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]//text()')[0] for x in range(2,endRow)] patentLink = ['http://patft.uspto.gov' + tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]/a/@href')[0] for x in range(2,endRow)] #loop over next page while len(tree.xpath("//form[@name='srchForm']//input[starts-with(@name,'NextList')]"))>0: inputElement = browser.find_element_by_xpath("//form[@name='srchForm']//input[starts-with(@name,'NextList')]") time.sleep(2) inputElement.click() #try clicking button #add logic to pull new rank, number, title, and link and then append to existing data columns html_source = browser.page_source curDT = datetime.now() datepulled = curDT #uncomment if writing html file to directory #f = open(filePath+'test1_' + t + '.html','w') #f.write(html_source) #f.close() tree = html.parse(StringIO(html_source)) endRow = len(tree.xpath('//table[1]//tr'))-1 patentRank += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[1]//text()')[0] for x in range(2,endRow)] patentNumber += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[2]//text()')[0] for x in range(2,endRow)] patentTitle += [tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]//text()')[0] for x in range(2,endRow)] patentLink += ['http://patft.uspto.gov' + tree.xpath('//table[1]//tr[' + str(x) + ']/td[4]/a/@href')[0] for x in range(2,endRow)] time.sleep(2) #keep re-creating dictionary and csv file with current data patentDict = {'Rank':patentRank, 'PatentNumber':patentNumber, 'PatentTitle':patentTitle, 'PatentLink':patentLink} patentFrame = pd.DataFrame.from_dict(patentDict) patentFrame.to_csv(filePath+searchValue+'_'+t+'.txt',sep='\t') browser.quit() display.stop() #create full Dictionary after all pages have been extracted patentDict = {'Rank':patentRank, 'PatentNumber':patentNumber, 'PatentTitle':patentTitle, 'PatentLink':patentLink} patentFrame = pd.DataFrame.from_dict(patentDict) patentFrame.to_csv(filePath+searchValue+'_'+t+'.txt',sep='\t') print("Finished Scraping")

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test/lib/testMap.py

animator/titus2

18

194093

#!/usr/bin/env python # Copyright (C) 2014 Open Data ("Open Data" refers to # one or more of the following companies: Open Data Partners LLC, # Open Data Research LLC, or Open Data Capital LLC.) # # This file is part of Hadrian. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest from titus.genpy import PFAEngine from titus.errors import * class TestLib1Map(unittest.TestCase): def testGetLength(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: int action: - {map.len: [input]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), 5) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: int action: - {map.len: [input]} ''') self.assertEqual(engine.action({}), 0) def testGetKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: string} action: - {map.keys: [input]} ''') self.assertEqual(set(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})), set(["a", "b", "c", "d", "e"])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: string} action: - {map.keys: [input]} ''') self.assertEqual(engine.action({}), []) def testGetValues(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.values: [input]} ''') self.assertEqual(set(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})), set([1, 2, 3, 4, 5])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.values: [input]} ''') self.assertEqual(engine.action({}), []) def testCheckContainsKey(self): engine, = PFAEngine.fromYaml(''' input: string output: boolean action: map.containsKey: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertTrue(engine.action("a")) self.assertFalse(engine.action("z")) engine, = PFAEngine.fromYaml(''' input: string output: boolean action: map.containsKey: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - params: [{x: string}] ret: boolean do: {"==": [x, input]} ''') self.assertTrue(engine.action("a")) self.assertFalse(engine.action("z")) def testCheckContainsKey(self): engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.containsValue: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertTrue(engine.action(1)) self.assertFalse(engine.action(9)) engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.containsValue: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - params: [{x: int}] ret: boolean do: {"==": [x, input]} ''') self.assertTrue(engine.action(1)) self.assertFalse(engine.action(9)) def testAddKeyValuePairs(self): engine, = PFAEngine.fromYaml(''' input: string output: {type: map, values: int} action: map.add: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input - 999 ''') self.assertEqual(engine.action("a"), {"a": 999, "b": 2, "c": 3, "d": 4, "e": 5}) self.assertEqual(engine.action("z"), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "z": 999}) engine, = PFAEngine.fromYaml(''' input: int output: {type: map, values: int} action: map.add: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - input ''') self.assertEqual(engine.action(1), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4}) self.assertEqual(engine.action(999), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4, "zg8=": 999}) def testRemoveKeys(self): engine, = PFAEngine.fromYaml(''' input: string output: {type: map, values: int} action: map.remove: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action("a"), {"b": 2, "c": 3, "d": 4, "e": 5}) self.assertEqual(engine.action("z"), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) def testKeepOnlyCertainKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.only: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {"b": 2, "c": 3, "e": 5}) self.assertEqual(engine.action(["b", "c", "e", "z"]), {"b": 2, "c": 3, "e": 5}) self.assertEqual(engine.action([]), {}) engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.only: - {value: {}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {}) self.assertEqual(engine.action([]), {}) def testEliminateOnlyCertainKeys(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.except: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {"a": 1, "d": 4}) self.assertEqual(engine.action(["b", "c", "e", "z"]), {"a": 1, "d": 4}) self.assertEqual(engine.action([]), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) engine, = PFAEngine.fromYaml(''' input: {type: array, items: string} output: {type: map, values: int} action: map.except: - {value: {}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action(["b", "c", "e"]), {}) self.assertEqual(engine.action([]), {}) def testUpdateWithAnOverlay(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.update: - {value: {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}, type: {type: map, values: int}} - input ''') self.assertEqual(engine.action({"b": 102, "c": 103, "z": 999}), {"a": 1, "b": 102, "c": 103, "d": 4, "e": 5, "z": 999}) def testSplit(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: {type: map, values: int}} action: map.split: input ''') self.assertEqual(sorted(engine.action({"a": 1, "b": 2, "c": 3}), key=lambda x: list(x.keys())[0]), sorted([{"a": 1}, {"b": 2}, {"c": 3}], key=lambda x: list(x.keys())[0])) def testJoin(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: {type: map, values: int}} output: {type: map, values: int} action: map.join: input ''') self.assertEqual(sorted(engine.action([{"a": 1}, {"b": 2}, {"c": 3}])), sorted({"a": 1, "b": 2, "c": 3})) def testNumericalArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmax: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}]} ''')[0].action(None), "2") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmin: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}]} ''')[0].action(None), "1") def testObjectArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmax: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - {map.argmin: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}]} ''')[0].action(None), "4") def testUserDefinedArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argmaxLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argmaxLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "1") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argminLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "4") self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: string action: - map.argminLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), "4") def testFindTop3NumericalArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argmaxN: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}, 3]} ''')[0].action(None), ["2", "6", "4"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argminN: [{value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}}, 3]} ''')[0].action(None), ["1", "5", "3"]) def testFindTop3ObjectArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argmaxN: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}, 3]} ''')[0].action(None), ["1", "2", "5"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - {map.argminN: [{value: {"0": "one", "1": "two", "2": "three", "3": "four", "4": "five", "5": "six", "6": "seven"}, type: {type: map, values: string}}, 3]} ''')[0].action(None), ["4", "3", "0"]) def testFindTop3UserDefinedArgmaxArgmin(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argmaxNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["1", "5", "3"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argmaxNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["1", "5", "3"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argminNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - {fcn: u.mylt} fcns: mylt: params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["4", "0", "6"]) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: array, items: string} action: - map.argminNLT: - {value: {"0": 5.5, "1": 2.2, "2": 7.7, "3": 4.4, "4": 6.6, "5": 2.2, "6": 7.6}, type: {type: map, values: double}} - 3 - params: [{a: double}, {b: double}] ret: boolean do: {"<": [{m.abs: {"-": [a, 6.2]}}, {m.abs: {"-": [b, 6.2]}}]} ''')[0].action(None), ["4", "0", "6"]) def testToSet(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: {type: map, values: int} action: - {map.toset: [input]} ''') self.assertEqual(engine.action([1, 2, 3, 4, 5]), {"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4}) def testFromSet(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: array, items: int} action: - {map.fromset: [input]} ''') self.assertEqual(set(engine.action({"BA==": 2, "Ag==": 1, "Bg==": 3, "Cg==": 5, "CA==": 4})), set([1, 2, 3, 4, 5])) engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: array, items: string} action: - {map.fromset: [input]} ''') self.assertEqual(set(engine.action({"BA==": "two", "Ag==": "one", "Bg==": "three", "Cg==": "five", "CA==": "four"})), set(["one", "two", "three", "four", "five"])) def testIn(self): engine, = PFAEngine.fromYaml(''' input: int output: boolean action: map.in: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - input ''') self.assertTrue(engine.action(2)) self.assertFalse(engine.action(0)) def testUnion(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.union: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3, 4, 5, 6, 7, 8])) def testIntersection(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.intersection: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([4, 5])) def testDiff(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.diff: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3])) def testSymDiff(self): engine, = PFAEngine.fromYaml(''' input: "null" output: {type: array, items: int} action: map.fromset: map.symdiff: - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} - {map.toset: {value: [4, 5, 6, 7, 8], type: {type: array, items: int}}} ''') self.assertEqual(set(engine.action(None)), set([1, 2, 3, 6, 7, 8])) def testSubset(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: boolean action: map.subset: - {map.toset: input} - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} ''') self.assertTrue(engine.action([1, 2, 3])) self.assertFalse(engine.action([1, 2, 3, 999])) self.assertFalse(engine.action([888, 999])) def testDisjoint(self): engine, = PFAEngine.fromYaml(''' input: {type: array, items: int} output: boolean action: map.disjoint: - {map.toset: input} - {map.toset: {value: [1, 2, 3, 4, 5], type: {type: array, items: int}}} ''') self.assertFalse(engine.action([1, 2, 3])) self.assertFalse(engine.action([1, 2, 3, 999])) self.assertTrue(engine.action([888, 999])) def testMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: map, values: int} action: map.map: - input - params: [{x: string}] ret: int do: {parse.int: [x, 10]} ''') self.assertEqual(engine.action({"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}) def testMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: string} output: {type: map, values: int} action: map.mapWithKey: - input - params: [{key: string}, {value: string}] ret: int do: if: {">": [key, {string: "c"}]} then: {+: [{parse.int: [value, 10]}, 1000]} else: {parse.int: [value, 10]} ''') self.assertEqual(engine.action({"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}), {"a": 1, "b": 2, "c": 3, "d": 1004, "e": 1005}) def testFilter(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filter: - input - params: [{x: int}] ret: boolean do: {"<": [x, 3]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1, "b": 2}) def testFilterWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterWithKey: - input - params: [{key: string}, {value: int}] ret: boolean do: {"&&": [{"<": [value, 3]}, {"==": [key, {string: "a"}]}]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1}) def testFilterMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterMap: - input - params: [{value: int}] ret: [int, "null"] do: if: {"==": [{"%": [value, 2]}, 0]} then: {"+": [value, 1000]} else: null ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"b": 1002, "d": 1004}) def testFilterMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.filterMapWithKey: - input - params: [{key: string}, {value: int}] ret: [int, "null"] do: if: {"&&": [{"==": [{"%": [value, 2]}, 0]}, {"==": [key, {string: "b"}]}]} then: {"+": [value, 1000]} else: null ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"b": 1002}) def testFlatMap(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.flatMap: - input - params: [{value: int}] ret: {type: map, values: int} do: if: {">": [value, 2]} then: - let: {out: {value: {}, type: {type: map, values: int}}} - set: out: map.add: - out - {s.int: value} - value - set: out: map.add: - out - {s.concat: [{s.int: value}, {s.int: value}]} - value - out else: {value: {}, type: {type: map, values: int}} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"3": 3, "4": 4, "5": 5, "33": 3, "44": 4, "55": 5}) def testFlatMapWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: {type: map, values: int} action: map.flatMapWithKey: - input - params: [{key: string}, {value: int}] ret: {type: map, values: int} do: map.add: - map.add: - {value: {}, type: {type: map, values: int}} - key - value - {s.concat: [key, key]} - {+: [100, value]} ''') self.assertEqual(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5}), {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "aa": 101, "bb": 102, "cc": 103, "dd": 104, "ee": 105}) def testZipMap(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - params: [{a: string}, {b: int}] ret: string do: {s.concat: [a, {s.int: b}]} ''')[0].action(None), {"0": "x101", "1": "y102", "2": "z103"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - params: [{a: string}, {b: int}, {c: string}] ret: string do: {s.concat: [{s.concat: [a, {s.int: b}]}, c]} ''')[0].action(None), {"0": "x101a", "1": "y102b", "2": "z103c"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmap: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - {value: {"0": true, "1": false, "2": true}, type: {type: map, values: boolean}} - params: [{a: string}, {b: int}, {c: string}, {d: boolean}] ret: string do: {s.concat: [{s.concat: [{s.concat: [a, {s.int: b}]}, c]}, {if: d, then: {string: "-up"}, else: {string: "-down"}}]} ''')[0].action(None), {"0": "x101a-up", "1": "y102b-down", "2": "z103c-up"}) def testZipMapWithKey(self): self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - params: [{k: string}, {a: string}, {b: int}] ret: string do: {s.concat: [{s.concat: [k, a]}, {s.int: b}]} ''')[0].action(None), {"0": "0x101", "1": "1y102", "2": "2z103"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - params: [{k: string}, {a: string}, {b: int}, {c: string}] ret: string do: {s.concat: [{s.concat: [{s.concat: [k, a]}, {s.int: b}]}, c]} ''')[0].action(None), {"0": "0x101a", "1": "1y102b", "2": "2z103c"}) self.assertEqual(PFAEngine.fromYaml(''' input: "null" output: {type: map, values: string} action: map.zipmapWithKey: - {value: {"0": "x", "1": "y", "2": "z"}, type: {type: map, values: string}} - {value: {"0": 101, "1": 102, "2": 103}, type: {type: map, values: int}} - {value: {"0": "a", "1": "b", "2": "c"}, type: {type: map, values: string}} - {value: {"0": true, "1": false, "2": true}, type: {type: map, values: boolean}} - params: [{k: string}, {a: string}, {b: int}, {c: string}, {d: boolean}] ret: string do: {s.concat: [{s.concat: [{s.concat: [{s.concat: [k, a]}, {s.int: b}]}, c]}, {if: d, then: {string: "-up"}, else: {string: "-down"}}]} ''')[0].action(None), {"0": "0x101a-up", "1": "1y102b-down", "2": "2z103c-up"}) def testCorresponds(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: boolean action: map.corresponds: - input - {value: {"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}, type: {type: map, values: string}} - params: [{x: int}, {y: string}] ret: boolean do: {"==": [x, {parse.int: [y, 10]}]} ''') self.assertTrue(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertFalse(engine.action({"a": 111, "b": 2, "c": 3, "d": 4, "e": 5})) def testCorrespondsWithKey(self): engine, = PFAEngine.fromYaml(''' input: {type: map, values: int} output: boolean action: map.correspondsWithKey: - input - {value: {"a": "1", "b": "2", "c": "3", "d": "4", "e": "5"}, type: {type: map, values: string}} - params: [{k: string}, {x: int}, {y: string}] ret: boolean do: if: {"==": [k, {string: "a"}]} then: true else: {"==": [x, {parse.int: [y, 10]}]} ''') self.assertTrue(engine.action({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertTrue(engine.action({"a": 111, "b": 2, "c": 3, "d": 4, "e": 5})) self.assertFalse(engine.action({"a": 1, "b": 222, "c": 3, "d": 4, "e": 5}))

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