Datasets:
paulo037
/
starcoder

Dataset card Data Studio Files Community
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checkov/gitlab/runner.py
pmalkki/checkov
1
158875
from checkov.common.output.report import CheckType from checkov.gitlab.dal import Gitlab from checkov.json_doc.runner import Runner as JsonRunner from checkov.runner_filter import RunnerFilter class Runner(JsonRunner): check_type = CheckType.GITLAB_CONFIGURATION def __init__(self): self.gitlab = Gitlab() super().__init__() def run(self, root_folder=None, external_checks_dir=None, files=None, runner_filter=RunnerFilter(), collect_skip_comments=True): self.prepare_data() report = super().run(root_folder=self.gitlab.gitlab_conf_dir_path, external_checks_dir=external_checks_dir, files=files, runner_filter=runner_filter, collect_skip_comments=collect_skip_comments) JsonRunner._change_files_path_to_relative(report) return report def prepare_data(self): self.gitlab.persist_all_confs() def require_external_checks(self): # default json runner require only external checks. Gitlab runner brings build in checks return False def import_registry(self): from checkov.gitlab.registry import registry return registry
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qymel/core/__init__.py
hal1932/QyMEL
6
16039
<reponame>hal1932/QyMEL # coding: utf-8 from .force_reload import * from .scopes import *
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app.py
ballmaK/StockPool_V2
0
1614390
<filename>app.py # -*- coding: utf-8 -*- #!/usr/bin/python import re import os import sys import time import random import httplib import json import datetime import traceback import threadpool import Queue from math import ceil from optparse import OptionParser,OptionGroup DATADIR="data/historys" DATEHIS="data/date-historys" PH=50 PL=-15 STOCKINFO={} # 获取所有交易日 def __getFullDate(yearStart,yearEnd): for year in range(yearStart,yearEnd+1): year = str(year) startdate = year+'0101' enddate = year+'1231' timestam = time.time() url = "q.stock.sohu.com" path = "/hisHq?code=zs_000001&start=%s&end=%s&stat=1&order=D&period=d&callback=historySerchHandler&rt=jsonp&r=%s" % (startdate, enddate, timestam) content = __httpGetContent(url, path) print content datelist = [date[0].replace('-','') for date in json.loads(content[len('historySerchHandler('):-2].replace('%',''), encoding="GBK")[0]['hq']] if not os.path.exists(DATEHIS): os.mkdir(DATEHIS) fd = open(os.path.join(DATEHIS,year), 'w+') fd.write(json.dumps(datelist)) fd.close() def __getTurnOver(code, year): timestam = time.time() dateStart = year+'0101' dateEnd = year +'1231' url = "q.stock.sohu.com" path = "/hisHq?code=cn_%s&start=%s&end=%s&stat=1&order=D&period=d&callback=historySerchHandler&rt=jsonp&r=%s" % (code, dateStart, dateEnd, timestam) content = __httpGetContent(url, path) # print content try: jsonp = json.loads(content[len('historySerchHandler('):-2].replace('%',''), encoding="GBK") stockinfo = jsonp[0]['hq'] except: stockinfo = [] datedict = {} for date in stockinfo: datedict[date[0].replace('-','')] = date[9] if not stockinfo: datedict[dateStart] = 0 return datedict def getShangHaiInfo(year): timestam = time.time() dateStart = year+'0101' dateEnd = year +'1231' url = "q.stock.sohu.com" path = "/hisHq?code=zs_000001&start=%s&end=%s&stat=1&order=D&period=d&callback=historySerchHandler&rt=jsonp&r=%s" % (dateStart, dateEnd, timestam) content = __httpGetContent(url, path) try: jsonp = json.loads(content[len('historySerchHandler('):-2].replace('%',''), encoding="GBK") stockinfo = jsonp[0]['hq'] except: stockinfo = [] sh = {} for info in stockinfo: shStock = {} date = info[0]#.replace('-','') shStock['date'] = date shStock['start'] = float(info[1]) shStock['end'] = float(info[2]) shStock['low'] = float(info[5]) shStock['high'] = float(info[6]) shStock['volume'] = int(ceil(float(info[7]))) shStock['total'] = int(ceil(float(info[8]))) sh[date]=shStock return sh def getShangHaiBR(stock): stock_date = stock.keys() stocklist = [(k,stock[k]) for k in sorted(stock_date, reverse=True)] sorted_stock_date = [s[0] for s in stocklist] for date in stock_date: if date: try: index = sorted_stock_date.index(date) except: delist = True index = 0 else: index = 0 stockdayslist = stocklist[index:index+20] #print stocklist20 h, l, a = __getHLIn(stockdayslist) BR = a/(h/l) stock[date]['BR'] = BR now_price = stocklist[index][1]['end'] if index >= 1: day1 = stocklist[index-1][1]['end'] #1日后收盘价 day1_p = round((day1 - now_price)/now_price, 3) * 100 #1日后涨跌幅 if index >= 3: day3 = stocklist[index-3][1]['end'] #3日后收盘价 day3_p = round((day3 - now_price)/now_price, 3) * 100 #3日后涨跌幅 if index >= 5: day5 = stocklist[index-5][1]['end'] #5日后收盘价 day5_p = round((day5 - now_price)/now_price, 3) * 100 #5日后涨跌幅 stock[date]['1d'] = day1_p stock[date]['3d'] = day3_p stock[date]['5d'] = day5_p stock[date]['price'] = now_price #print "%-8s %-15s %8s %8s %8s" % ('DATE', 'BR-20', '1-DAYS', '3-DAYS', '5-DAYS') #print "%s,%s,%s,%s,%s,%s" % ('DATE', 'BR-20', 'PRICE', '1-DAYS', '3-DAYS', '5-DAYS') total = b = 0 for s in sorted_stock_date: #print "%-8s %-15.2f %8.2f %8.2f %8.2f" % (stock[s]['date'],stock[s]['BR'],stock[s]['1d'],stock[s]['3d'],stock[s]['5d']) aa = stock[s]['BR']/stock[s]['total'] #if aa <= 0.72: # total += 1 # print "%s,%.2f,%d,%.2f,%d,%.2f" % (stock[s]['date'],stock[s]['BR'],stock[s]['price'],stock[s]['1d'],stock[s]['total'],stock[s]['BR']/stock[s]['total']) # if stock[s]['1d'] <= 0: # b += 1 print "%s,%.2f,%d,%.2f,%d,%.2f" % (stock[s]['date'],stock[s]['BR'],stock[s]['price'],stock[s]['1d'],stock[s]['total'],stock[s]['BR']/stock[s]['total']) #print "TOTAL: %s, BINGO: %s" % (total, b) #return stock def __convert_inner(stock, todict, stock_dict={}): stock_day = stock.split(',') if all(stock_day): date = stock_day[0] #日期 start = float(stock_day[1]) #开盘价格 high = float(stock_day[2]) #最高价格 low = float(stock_day[3]) #最低价格 end = float(stock_day[4]) #收盘价格 volume = int(ceil(float(stock_day[5]))) #成交量 total = int(ceil(float(stock_day[6]))) #成交额 try: to = float(todict[date]) except: to = 0.0 #print stock, date, to stock_dict[date] = { "date": date, 'start': start, 'high': high, 'low': low, 'end': end, 'volume': volume, 'total': total, 'to': to } return stock_dict def __convert_day(content, todict): stock_list = content.split('=')[1].split('|') stock_dict = {} for stock in stock_list: if stock and stock.strip(): __convert_inner(stock, todict, stock_dict) #print stock_dict return stock_dict def __httpGetContent(url,path): conn = httplib.HTTPConnection(url,timeout=60) conn.request("GET", path) response = conn.getresponse() if response.status == 200: content = response.read() else: content = None return content def __getHLIn(stocklist): high_list = [] low_list = [] money = 0 for stock in stocklist: info = stock[1] high_list.append(info['high']) low_list.append(info['low']) #计算每10亿股相对成交额 #if info['to'] != 0: # rate = info['volume']/info['to'] / 1000000000 money += info['total']#/rate return sorted(high_list)[-1], sorted(low_list)[0], money/20 def updateStockDayHistory(code, market, year='2015', type='b'): """ http://qd.10jqka.com.cn/api.php?p=stock_day&info=k_sz_000005&year=2012,2013&fq= sz:深证 sh:上海 b向后复权 q向前复权 return dict """ if needUpdate(market, code, year, type): url = "qd.10jqka.com.cn" path = "/api.php?p=stock_day&info=k_%s_%s&year=%s&fq=%s" % (market, code, year, type) todict = __getTurnOver(code, year) try: content = __httpGetContent(url, path) except: content = None print code, ": Request failed ..." if content: #print code, ": Request success ..." stock_dict = __convert_day(content,todict) try: updateSingleLocalHistory(market, code, year, type, stock_dict) except Exception, e: #print traceback.print_exc(e) pass return stock_dict else: # print '< ' + market + code + ' > need not to update ..' pass def __getLocalStockInfo(code, market, year, type): code = market+code try: if code and year and type: fd = open(os.path.join(DATADIR,code, year, type, '%s' % code),'r') content = fd.read() fd.close() else: fd = None except Exception, e: #print traceback.print_exc(e) #if fd: # fd.close() return return json.loads(content) def __getMemeryStockInfo(code, market, year, type): global STOCKINFO stockcode = market+code if stockcode in STOCKINFO: return STOCKINFO[stockcode] else: codeMemInfo = __getLocalStockInfo(code, market, year, type) STOCKINFO[stockcode] = codeMemInfo return codeMemInfo def needUpdate (market, code, year, type): code = market+code need = False if not os.path.exists(os.path.join(DATADIR,code)): need = True if not os.path.exists(os.path.join(DATADIR,code, year)): need = True if not os.path.exists(os.path.join(DATADIR,code, year, type)): need = True # print os.path.join(DATADIR,code), os.path.join(DATADIR,code, year), os.path.join(DATADIR,code, year, type) return need def updateSingleLocalHistory(market, code, year, type, stock_dict): code = market+code print 'update <', code, '> info ..' if os.path.exists(os.path.join(DATADIR,code)): if os.path.exists(os.path.join(DATADIR,code, year)): if os.path.exists(os.path.join(DATADIR,code, year, type)): fd = open(os.path.join(DATADIR,code, year, type, '%s' % code), 'w+') fd.write(json.dumps(stock_dict)) fd.close() else: os.mkdir(os.path.join(DATADIR,code, year, type)) fd = open(os.path.join(DATADIR,code, year, type, '%s' % code), 'w+') fd.write(json.dumps(stock_dict)) fd.close() else: os.mkdir(os.path.join(DATADIR,code, year)) os.mkdir(os.path.join(DATADIR,code, year, type)) fd = open(os.path.join(DATADIR,code, year, type, '%s' % code), 'w+') fd.write(json.dumps(stock_dict)) fd.close() else: os.mkdir(os.path.join(DATADIR,code)) os.mkdir(os.path.join(DATADIR,code, year)) os.mkdir(os.path.join(DATADIR,code, year, type)) fd = open(os.path.join(DATADIR,code, year, type, '%s' % code), 'w+') fd.write(json.dumps(stock_dict)) fd.close() def isTradeDay(date): year = date[:4] fd = open(os.path.join(DATEHIS,year),'r') datelist = json.loads(fd.read()) fd.close() try: index = datelist.index(date) except Exception,e: return False return True def getNextDate(date,code=''): year = date[:4] fd = open(os.path.join(DATEHIS,year),'r') datelist = json.loads(fd.read()) fd.close() #print datelist if datelist.index(date) >= 1: return datelist[datelist.index(date)-1] else: return datelist[0] def getLastDate(date,code=''): year = date[:4] month = date[4:6] day = date[6:] if code: codeDateList = sorted(__getLocalStockInfo(code[2:], code[:2], year, type='b').keys(), reverse=True) delta = 1 while 1: try: index = codeDateList.index(date) break #return codeDateList[index+1] except: newDate = datetime.datetime(int(year), int(month),int(day)) - datetime.timedelta(delta) year, month, day = str(newDate.year), '%02d' % newDate.month , '%02d' % newDate.day date = year+month+day #return codeDateList[0] return codeDateList[index+1] else: fd = open(os.path.join(DATEHIS,year),'r') datelist = json.loads(fd.read()) fd.close() delta = 1 while 1: try: index = datelist.index(date) break except: print "Date is not deal day, choose one before it" #delta += 1 newDate = datetime.datetime(int(year), int(month),int(day)) - datetime.timedelta(delta) year, month, day = str(newDate.year), '%02d' % newDate.month , '%02d' % newDate.day date = year+month+day if index >= 1: return datelist[index+1] else: return datelist[0] def getBR(stockCode,date="",days=20): code, market = stockCode[2:], stockCode[:2] #print code, market #stock = getStockDayHistory(code, market, year="2015", type="b") year = date[:4] stock = __getMemeryStockInfo(code, market, year, type="b") day1 = day3 = day5 = 'NaN' day1_p = day3_p = day5_p = 'NaN' now_volume = 'NaN' flow_volume = 0 flow_money = 0 delist = False if stock: stock_date = stock.keys() stocklist = [(k,stock[k]) for k in sorted(stock_date, reverse=True)] sorted_stock_date = [s[0] for s in stocklist] if date: try: index = sorted_stock_date.index(date) except: delist = True index = 0 else: index = 0 #print "date: ",sorted_stock_date[index] stockdayslist = stocklist[index:index+days] #print stocklist20 h, l, a = __getHLIn(stockdayslist) BR = a/(h/l) stList = getSTStock() now_price = stocklist[index][1]['end'] #当日收盘价 now_volume = stocklist[index][1]['volume'] turnover = stocklist[index][1]['to'] if turnover == 0: flow_volume = 0 else: flow_volume = now_volume / turnover * 100 / 100000000 flow_money = flow_volume * now_price if now_volume <= 1000000 or delist or stockCode[2:] in stList: #当天交易量小于10000手 BR = 99999999999999999 if index >= 1: day1 = stocklist[index-1][1]['end'] #1日后收盘价 day1_p = round((day1 - now_price)/now_price, 3) * 100 #1日后涨跌幅 if index >= 3: day3 = stocklist[index-3][1]['end'] #3日后收盘价 day3_p = round((day3 - now_price)/now_price, 3) * 100 #3日后涨跌幅 if index >= 5: day5 = stocklist[index-5][1]['end'] #5日后收盘价 day5_p = round((day5 - now_price)/now_price, 3) * 100 #5日后涨跌幅 return stockCode,BR,day1_p,day3_p,day5_p,now_volume,delist,flow_volume, flow_money #return BR,day1,day3,day5 else: return stockCode,99999999999999999,day1_p,day3_p,day5_p,now_volume,delist,flow_volume,flow_money def getStockCode(): fdHA = open('data/HA.data','r') fdSA = open('data/SA.data','r') fdZX = open('data/ZX.data','r') fdCY = open('data/CY.data','r') HA = fdHA.read().split() SA = fdSA.read().split() ZX = fdZX.read().split() CY = fdCY.read().split() allStock = HA+SA+ZX+CY allStockDict = {} for stock in allStock: k,v = stock.split(',') allStockDict[k] = v return allStockDict def getSTStock(): fdST = open('data/ST.data','r') ST = fdST.read().split() stDict = {} for st in ST: k,v = st.split(',') stDict[k] = v return stDict def getResult(request, br_info): global sorted_s sorted_s.append(br_info) def updateLocalHistory(year, type): ''' year@string: 2015 type@string: b=后复权;q=前复权 ''' allStockDict = getStockCode() stock_data = allStockDict.keys() q_size = len(stock_data) pool = threadpool.ThreadPool(10, q_size=q_size, resq_size=q_size) data = [([stock[2:], stock[:2], year, type],{}) for stock in stock_data] requests = threadpool.makeRequests(updateStockDayHistory, data) [pool.putRequest(req) for req in requests] pool.wait() def getBest(date="",length=50, days=20, printOut=False, filter=0.01): ''' date@string: 20150729 length@int: days@int: avg day ''' #a = time.time() global sorted_s sorted_s = [] allStockDict = getStockCode() stock_data = allStockDict.keys() q_size = len(stock_data) pool = threadpool.ThreadPool(1, q_size=q_size, resq_size=q_size) data = [([stock],{"date": date,"days": days}) for stock in stock_data] requests = threadpool.makeRequests(getBR, data, getResult) [pool.putRequest(req, False) for req in requests] pool.wait() #print len(sorted_s) best50 = sorted(sorted_s, key=lambda sorted_s:sorted_s[1])#[:50] stList = getSTStock().keys() length = length best = [] #print "DATE: %s" % date if printOut: print "==================================== TRADE DATE: %s ====================================" % date print "%-10s %-20s\t%-20s %-20s %-20s %-20s %-20s %-10s" % ("CODE","股票名字","BR-%s" % days,"1DAY_P","3DAY_P","5DAY_P","VOL","DELIST") for b in best50: if length > 0: if not filter: if printOut: print "%-10s %-20s\t%-20.2f %-20s %-20s %-20s %-20s %-10s %10.2f %10.2f" % (b[0],allStockDict[b[0]],b[1],str(b[2]),str(b[3]),str(b[4]), b[5], b[6],b[7], b[8] ) length -= 1 best.append(b[0]) else: if b[7] >= float(filter): length -= 1 if printOut: print "%-10s %-20s\t%-20.2f %-20s %-20s %-20s %-20s %-10s %10.2f %10.2f" % (b[0],allStockDict[b[0]],b[1],str(b[2]),str(b[3]),str(b[4]), b[5], b[6],b[7], b[8] ) best.append(b[0]) else: #print 'GET BEST TAKE: %s' % (time.time() - a) return best def getFullCode(code): ''' return@string: sz002891/sh600061 etc. ''' if code.find('sz') < 0 or code.find('sh') < 0: if code.find('60') == 0: code = 'sh' + code else: code = 'sz' + code return code def getStockBR(stockCode, year='2015', type='b'): ''' stockCode@string: full code year@string: year type@string: b=后复权;q=前复权 return@int: ''' code, market = stockCode[2:], stockCode[:2] stockinfo = __getMemeryStockInfo(code, market, year, type) dateBRList = [(tuple([info]) + getBR(stockCode,info)) for info in stockinfo] s_date = sorted(dateBRList, key=lambda dateBRList:dateBRList[0]) print "%-10s %-10s %-20s %-20s %-20s %-20s %-20s %-10s" % ("DATE","CODE","BR","1DAY_P","3DAY_P","5DAY_P","VOL","DELIST") for b in s_date: print "%-10s %-10s %-20s %-20s %-20s %-20s %-20s %-10s" % (b[0],b[1],str(b[2]),str(b[3]),str(b[4]), b[5], b[6], b[7] ) def updateStockCodeList(): url = "quote.eastmoney.com" path = "/stocklist.html" content = __httpGetContent(url, path) p_sh = 'sh\d+' p_sz = 'sz\d+' p_st = "ST(.+)\((\d+)" all = re.findall(p_sh, content) + re.findall(p_sz, content) HA = [] SA = [] ZX = [] ST = [] CY = [] ST = [ t[1]+',*ST'+t[0].decode('GBK').encode('utf-8')+'\n' for t in re.findall(p_st, content)] #print ST #print content.decode('GBK') #print all for code in all: p_cn = '">(.+)\(' + code[2:] try: codeCN = re.findall(p_cn, content)[0].decode('GBK').encode('utf-8') except Exception, e: codeCN = 'NONAME' # print code, codeCN if code[2:].find('60') == 0: HA.append(code+','+codeCN+'\n') if code[2:].find('000') == 0: SA.append(code+','+codeCN+'\n') if code[2:].find('002') == 0: ZX.append(code+','+codeCN+'\n') if code[2:].find('300') == 0: CY.append(code+','+codeCN+'\n') # print CY fdHA = open('data/HA.data', 'w+') fdSA = open('data/SA.data', 'w+') fdZX = open('data/ZX.data', 'w+') fdST = open('data/ST.data', 'w+') fdCY = open('data/CY.data', 'w+') fdHA.writelines(HA) fdSA.writelines(SA) fdZX.writelines(ZX) fdST.writelines(ST) fdCY.writelines(CY) fdHA.close() fdSA.close() fdST.close() fdZX.close() fdCY.close() #print content def makeDeal(s_date, e_date, filter, codeinfo=[], rest_money=1000000, stockpick=10): ''' s_date@string: start date e_date@string: end date codeinfo@list: [('002063', 27.78, 300), ('002150', 21.78, 200), ('600604', 18.21, 250)]; 数量单位：(股票代码,买入价格,手数))] rest_money@int: 1000000 ''' a = time.time() if not codeinfo: #还未购买股票 #根据上一个交易日BR，在前20随机得出5支股票 suspension = False while not isTradeDay(s_date): s_date = getLastDate(s_date) #s_date = getLastDate(s_date) #lastDate = getLastDate(s_date) allStock = getBest(s_date,length=5000,days=20) bestlist = allStock[:20] codelist = [] while len(codelist) < stockpick: index = random.randint(0, 19) if bestlist[index] not in codelist: codelist.append(bestlist[index]) #codelist = [bestlist[random.randint(0,19)] for i in range(0,stockpick)] #infodict@dict: {codefull_0:stockyear_0, codefull_1:stockyear_1} infodict = {} #print codelist for bestcode in codelist: infodict.update({bestcode:__getMemeryStockInfo(bestcode[2:], bestcode[:2], s_date[:4], type='b')}) #股票交易 rest_total = 0 #print 'TRADE DATE: ',s_date newCodeInfo = [] print "==================================== TRADE DATE: %s ====================================" % s_date print "<<OP>> : %-10s %-6s %-6s %-6s %-6s %-6s %-6s %6s%% %8s" % ('CODE','BUY','SELL','NOW', 'DEALT', 'SUSPEN', 'RANGE', 'P/L', 'MONEY') for code in codelist: codeinfoyear = infodict[code] codeinfoday = codeinfoyear[s_date] range = allStock.index(code) buy = codeinfoday['start'] #开盘价买入 avgMoney = int(rest_money / stockpick) #每支买入金钱 buyNumber = int(avgMoney/buy/100) #每支买入数量 avgRestMoney = avgMoney - buy*buyNumber*100 #每支剩余金钱 nextDate = getNextDate(s_date) #获取下一个交易日天日期 rest_total += avgRestMoney print "-> BUY : %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6s%% %8s" % (code,buy,0,buy, buyNumber, suspension, range, 0,'-'+str(int(buy*buyNumber*100))) newCodeInfo.append((code, buy, buyNumber)) print ">>TOTAL: %-10s %-6s %-6s %-6s %-6s %-6s %-6s %6.2f%% %8s" % ('-','-','-','-', '-', '-', '-', 0 , 1000000) print 'TAKE ',int(time.time()) - a, ' seconds' makeDeal(nextDate, e_date, filter, newCodeInfo, rest_total, stockpick) else: print "==================================== TRADE DATE: %s ====================================" % s_date print "<<OP>> : %-10s %-6s %-6s %-6s %-6s %-6s %-6s %6s%% %8s" % ('CODE','BUY','SELL','NOW', 'DEALT', 'SUSPEN', 'RANGE', 'P/L', 'MONEY') #计算股票市值 infodict = {} totalValue = 0 lastDate = getLastDate(s_date) allStock = getBest(lastDate,length=5000,days=20) #print lastDate, allStock bestlist= allStock[:20] codelist = [_code[0] for _code in codeinfo] for bestcode in codelist: infodict.update({bestcode:__getMemeryStockInfo(bestcode[2:], bestcode[:2], s_date[:4], type='b')}) newCodeInfo = [] #newCodeInfo@list: [('002063', 27.78, 300), ('002150', 21.78, 200), ('600604', 18.21, 250)]; 数量单位：(股票代码,买入价格,手数))] for info in codeinfo: suspension = False code, buy, oBuyNumber = info #print allStock range = allStock.index(code) codeinfoyear = infodict[code] codeinfoday = None start_date = s_date while not codeinfoday: try: codeinfoday = codeinfoyear[start_date] break except Exception,e: #print traceback.print_exc(e) codeinfoday = None suspension = True start_date = getLastDate(start_date, code) #print start_date, code #判断是否换股 if not suspension: #未停牌 #卖出条件：1.BR不在前20；2.盈利超过35% #判断盈利率 oldPrice = codeinfo[codelist.index(code)][1] newPrice = codeinfoyear[s_date]['start'] percent = (newPrice/oldPrice - 1) * 100 #判断BR if code not in bestlist: #从前20挑出一支没有买过的新股 #print code,' out of 20' tmpList = [_code[0] for _code in codelist] while 1: new = int(random.randint(0,19)) #新股不在codeinfo中且当日没有停牌 if bestlist[new] not in codelist: newStock = bestlist[new] newcodeinfoyear = __getMemeryStockInfo(newStock[2:], newStock[:2], s_date[:4], type='b') if s_date in newcodeinfoyear.keys(): newRange = bestlist.index(newStock) break #print codeinfoyear[s_date] sell = newPrice print "<- SELL: %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8s" % (code,oldPrice, sell,0,oBuyNumber, suspension, range, percent,'+'+str(int(sell*oBuyNumber*100))) #print sell, oBuyNumber, rest_money oIndex=codelist.index(code) codelist.remove(code) codelist.insert(oIndex, newStock) aTotalValue = sell * oBuyNumber * 100 + rest_money #print sell, oBuyNumber, rest_money, aTotalValue totalValue += aTotalValue buy = newcodeinfoyear[s_date]['start'] #以开盘价购买 buyNumber = int(aTotalValue/buy/100) #计算股票数量 rest_money = aTotalValue - buy*buyNumber*100 #重新计算剩余金钱 #print buy, buyNumber, rest_money print "-> BUY : %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8s" % (newStock,buy, 0,buy,buyNumber, suspension, newRange, 0,'-'+str(int(buy*buyNumber*100))) newCodeInfo.append((newStock, buy, buyNumber)) continue if percent >= PH or percent <= PL: #盈利大于50%或者亏损大于15%，换股 #print 'Percent: ',newPrice/oldPrice tmpList = [_code[0] for _code in codelist] while 1: new = int(random.randint(0,19)) if bestlist[new] not in codelist: newStock = bestlist[new] newcodeinfoyear = __getMemeryStockInfo(newStock[2:], newStock[:2], s_date[:4], type='b') if s_date in newcodeinfoyear.keys(): newRange = bestlist.index(newStock) break #print codeinfoyear[s_date] sell = newPrice print "<- SELL: %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8s" % (code,oldPrice,sell,0,oBuyNumber, suspension, range, percent,'+'+str(int(sell*oBuyNumber*100))) #print sell, oBuyNumber, rest_money oIndex=codelist.index(code) codelist.remove(code) codelist.insert(oIndex, newStock) aTotalValue = sell * oBuyNumber * 100 + rest_money totalValue += aTotalValue newcodeinfoyear = __getMemeryStockInfo(newStock[2:], newStock[:2], s_date[:4], type='b') buy = newcodeinfoyear[s_date]['start'] #以开盘价购买 buyNumber = int(aTotalValue/buy/100) #计算股票数量 rest_money = aTotalValue - buy*buyNumber*100 #重新计算剩余金钱 print "-> BUY : %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8s" % (newStock,buy,0,buy, buyNumber, suspension, range, percent,'-'+str(int(buy*buyNumber*100))) newCodeInfo.append((newStock, buy, buyNumber)) continue if percent > PL and percent < PH and code in bestlist: oPrice = codeinfoday['start'] aTotalValue = oPrice * oBuyNumber * 100 totalValue += aTotalValue print "-* HOLD: %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8d" % (code,oldPrice,0,oPrice,oBuyNumber, suspension, range, percent,oPrice*oBuyNumber*100) newCodeInfo.append((code, oldPrice, oBuyNumber)) continue else: #停牌,不换股 oldPrice = codeinfo[codelist.index(code)][1] lastDate = getLastDate(s_date, code) newPrice = codeinfoyear[lastDate]['end'] #停牌当天收盘价 #newPrice = codeinfoyear[s_date]['start'] percent = (newPrice/oldPrice - 1) * 100 oPrice = codeinfoday['end'] aTotalValue = oPrice * oBuyNumber * 100 totalValue += aTotalValue print "-* HOLD: %-10s %-6.2f %-6.2f %-6.2f %-6d %-6s %-6s %6.2f%% %8d" % (code,oldPrice,0,newPrice,oBuyNumber, suspension, range, percent,oPrice*oBuyNumber*100) newCodeInfo.append((code, oldPrice, oBuyNumber)) #else: # totalValue = rest_money + totalValue print ">>TOTAL: %-10s %-6s %-6s %-6s %-6s %-6s %-6s %6.2f%% %8s" % ('-','-','-','-', '-', '-', '-', ((totalValue+rest_money)/1000000 - 1)*100 , int(totalValue+rest_money)) #print "STOCK INFO: %s" % newCodeInfo #print "STOCK VALUE: %s" % totalValue #print "REST MONEY: %s" % rest_money #print type(s_date.encode(sys.getdefaultencoding())), type(e_date) #print s_date.encode(sys.getdefaultencoding()), e_date if s_date!=e_date: print 'TAKE ',int(time.time()) - a, ' seconds' return makeDeal(getNextDate(s_date),e_date, filter, newCodeInfo,rest_money,stockpick) else: print "FINALLY VALUE: %s" % totalValue return True def getRange(stocklist, date='', length=20, days=20): ''' stocklist: ['002063','002150', '600604'] return: [('002063', 1374), ('002150', 2), ('600604', 'NaN')] ''' bestlist = [stock for stock in getBest(date, length, days)] range = [] for stock in stocklist: try: #print getFullCode(stock) index = bestlist.index(getFullCode(stock)) except: index = 'NaN' range.append((stock,index)) else: return range def setupParser(): usage = "usage: %prog [options] arg" parser = OptionParser(usage=usage) parser.add_option("-F", "--flow-filter", action="store", type="string", dest="filter", help="Filtrate by capital stock in circulation.", default='0.01') parser.add_option("-P", "--print-out", action="store_true", dest="aPrint", help="Decide if to print out result.", default=False) parser.add_option("-D", "--selected-date", action="store",type="string", dest="sDate", help="Selected date of picking.", default='') parser.add_option("-t", "--top-X", action="store",type="int", dest="topX", help="Picking stock from topX.", default=20) updateGroup = OptionGroup(parser, "Update Options","These options update all local data.") updateGroup.add_option("-d", "--update-date", action="store_true", dest="update_date", help="Update all date from 1999.", default=False) updateGroup.add_option("-l", "--update-local", action="store_true", dest="update_local", help="Update local stock info of specified year.", default=False) updateGroup.add_option("-s", "--update-stock", action="store", dest="update_stock", help="Update stock list, from given year(2010 later).", default='') parser.add_option_group(updateGroup) makeDealGroup = OptionGroup(parser, "Make Deal Options","These options simulate deals. \ e.g: python app.py -f 20100105 -e 20101231 -m 1000000 -n 10") makeDealGroup.add_option("-f", "--start-date", action="store",type="string", dest="sDate", help="Starting date of simulation.", default='') makeDealGroup.add_option("-e", "--end-date", action="store",type="string", dest="eDate", help="Ending date of simulation.", default='') makeDealGroup.add_option("-m", "--start-money", action="store",type="int", dest="sMoney", help="Get range by specified stocks number.", default=1000000) makeDealGroup.add_option("-p", "--pick-policy", action="store",type="int", dest="policy", help="Policy of stock picking: \ 0: random in pick number; \ 1: static top 10.", default=0) makeDealGroup.add_option("-n", "--pick-number", action="store",type="int", dest="pNumber", help="Number of stocks for random picking.", default=5) parser.add_option_group(makeDealGroup) getBestGroup = OptionGroup(parser, "Pick Best Stocks","These options pick out best stocks by specified args. \ e.g: python app.py -D 20100231 -P [-t 20] [-a 20] [-F 5]") getBestGroup.add_option("-a", "--average-day", action="store",type="int", dest="aDays", help="BR's average day.", default=20) getRangeGroup = OptionGroup(parser, "Get Stock Range","These options get range of stocks by given args. \ e.g: python app.py -D 20100231 [-t 20] [-a 20] [-F 5]") getRangeGroup.add_option("-r", "--get-range", action="store",type="string", dest="sList", help="Get one or multi stocks range. \ e.g.: 000651,000731.", default='') parser.add_option_group(getRangeGroup) parser.add_option_group(getBestGroup) return parser if __name__ == "__main__": #l = ['2015','2014','2013','2012','2011','2010'] #for year in l: #sh = getShangHaiInfo('2015') # sh = getShangHaiInfo(year) # getShangHaiBR(sh) #sh = getShangHaiInfo('2015') #getShangHaiBR(sh) sorted_s = [] parser = setupParser() (options, args) = parser.parse_args() if options.update_date: print 'Update full date list ...' __getFullDate(2010,2018) print 'Complete ...' print 'Update stock list ...' updateStockCodeList() print 'Complete ...' if options.update_local: print 'Update ST stocks ...' getSTStock() print 'Complete ...' if options.update_stock: try: year = int(options.update_stock) except Exception,e: parser.error('%s is not a year' % options.update_stock) print 'Update stocks from %s to now ...' % options.update_stock for i in range(int(year),year+1): print 'Update %s\'s stocks info ...' % i updateLocalHistory(str(i),'b') else: print 'Complete ...' if options.sDate and options.topX and options.aDays: try: date, topX, aDays,filter= options.sDate, options.topX, options.aDays, options.filter except Exception,e: parser.error("Not enough args.") try: filter = float(options.filter) except Exception,e: parser.error('%s is not a float.' % options.filter) getBest(date,length=topX,days=aDays,printOut=options.aPrint,filter=filter) #else: # parser.error("Not enough args.") if options.sDate and options.eDate and options.sMoney and options.pNumber: sDate, eDate, filter, sMoney, pNumber = options.sDate, options.eDate, options.filter, options.sMoney, options.pNumber makeDeal(sDate, eDate, filter, [], sMoney, pNumber) if options.sList and options.sDate: sDate, sList = options.sDate,options.sList try: l = sList.split(',') except: parser.error('Split stock with ",".' % options.filter) print getRange(l,date=sDate, length=options.topX) #print __getFullDate(1999,2015) #getStockBR('sz000739') #getSTStock() #best = getBest("20150730",length=20,days=20,printOut=True) #stocklist = ['000736','002735','002323','603006','002679','000025','603268','002680','603009'] #print getRange(stocklist,date='20150730', length=20) #print best #makeDeal('20150715','20150730', [], 1000000, 5) #money = makeDeal("20150720", "20150724", 1000000, stockpick=2) #updateLocalHistory('2015','b') #updateStockCodeList()
[ 1, 529, 9507, 29958, 932, 29889, 2272, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 29937, 14708, 4855, 29914, 2109, 29914, 4691, 13, 5215, 337, 13, 5215, 2897, 13, 5215, 10876, 13, 5215, 931, 13, 5215, 4036, 13, 5215, 1732, 1982, 13, 5215, 4390, 13, 5215, 12865, 13, 5215, 9637, 1627, 13, 5215, 3244, 10109, 13, 5215, 5462, 434, 13, 13, 3166, 5844, 1053, 2257, 309, 13, 3166, 3523, 5510, 1053, 10831, 11726, 29892, 8375, 4782, 13, 13, 25832, 3035, 8193, 543, 1272, 29914, 18434, 29879, 29908, 13, 6248, 29950, 3235, 543, 1272, 29914, 1256, 29899, 18434, 29879, 29908, 13, 19689, 29922, 29945, 29900, 13, 7390, 10457, 29896, 29945, 13, 1254, 29949, 7077, 11690, 3790, 29913, 13, 13, 29937, 29871, 31024, 30683, 30744, 30417, 31398, 233, 155, 150, 30325, 13, 1753, 4770, 657, 13658, 2539, 29898, 6360, 4763, 29892, 6360, 5044, 1125, 13, 1678, 363, 1629, 297, 3464, 29898, 6360, 4763, 29892, 6360, 5044, 29974, 29896, 1125, 13, 4706, 1629, 353, 851, 29898, 6360, 29897, 13, 4706, 1369, 1256, 353, 1629, 23097, 29900, 29896, 29900, 29896, 29915, 13, 4706, 1095, 1256, 353, 1629, 23097, 29896, 29906, 29941, 29896, 29915, 13, 4706, 5335, 342, 314, 353, 931, 29889, 2230, 580, 13, 4706, 3142, 353, 376, 29939, 29889, 17712, 29889, 578, 6905, 29889, 510, 29908, 13, 4706, 2224, 353, 5591, 22880, 29950, 29939, 29973, 401, 29922, 22381, 29918, 29900, 29900, 29900, 29900, 29900, 29896, 29987, 2962, 16328, 29879, 29987, 355, 16328, 29879, 29987, 6112, 29922, 29896, 29987, 2098, 29922, 29928, 29987, 19145, 29922, 29881, 29987, 14035, 29922, 18434, 1748, 305, 4598, 29987, 2273, 29922, 3126, 29886, 29987, 29878, 16328, 29879, 29908, 1273, 313, 2962, 1256, 29892, 1095, 1256, 29892, 5335, 342, 314, 29897, 13, 4706, 2793, 353, 4770, 1124, 2577, 3916, 29898, 2271, 29892, 2224, 29897, 13, 4706, 1596, 2793, 13, 4706, 1418, 295, 391, 353, 518, 1256, 29961, 29900, 1822, 6506, 877, 29899, 3788, 1495, 363, 2635, 297, 4390, 29889, 18132, 29898, 3051, 29961, 2435, 877, 18434, 1748, 305, 4598, 877, 1125, 29899, 29906, 1822, 6506, 877, 29995, 3788, 5477, 8025, 543, 7210, 29968, 1159, 29961, 29900, 22322, 29882, 29939, 2033, 29962, 13, 4706, 565, 451, 2897, 29889, 2084, 29889, 9933, 29898, 6248, 29950, 3235, 1125, 13, 9651, 2897, 29889, 11256, 3972, 29898, 6248, 29950, 3235, 29897, 13, 4706, 285, 29881, 353, 1722, 29898, 359, 29889, 2084, 29889, 7122, 29898, 6248, 29950, 3235, 29892, 6360, 511, 525, 29893, 29974, 1495, 13, 4706, 285, 29881, 29889, 3539, 29898, 3126, 29889, 29881, 17204, 29898, 4130, 295, 391, 876, 13, 4706, 285, 29881, 29889, 5358, 580, 13, 13, 1753, 4770, 657, 27407, 3563, 29898, 401, 29892, 1629, 1125, 268, 13, 1678, 5335, 342, 314, 353, 931, 29889, 2230, 580, 13, 1678, 2635, 4763, 353, 1629, 23097, 29900, 29896, 29900, 29896, 29915, 13, 1678, 2635, 5044, 353, 1629, 718, 29915, 29896, 29906, 29941, 29896, 29915, 13, 1678, 3142, 353, 376, 29939, 29889, 17712, 29889, 578, 6905, 29889, 510, 29908, 13, 1678, 2224, 353, 5591, 22880, 29950, 29939, 29973, 401, 29922, 18038, 29918, 29995, 29879, 29987, 2962, 16328, 29879, 29987, 355, 16328, 29879, 29987, 6112, 29922, 29896, 29987, 2098, 29922, 29928, 29987, 19145, 29922, 29881, 29987, 14035, 29922, 18434, 1748, 305, 4598, 29987, 2273, 29922, 3126, 29886, 29987, 29878, 16328, 29879, 29908, 1273, 313, 401, 29892, 2635, 4763, 29892, 2635, 5044, 29892, 5335, 342, 314, 29897, 13, 1678, 2793, 353, 4770, 1124, 2577, 3916, 29898, 2271, 29892, 2224, 29897, 13, 1678, 396, 1596, 2793, 13, 1678, 1018, 29901, 13, 4706, 4390, 29886, 353, 4390, 29889, 18132, 29898, 3051, 29961, 2435, 877, 18434, 1748, 305, 4598, 877, 1125, 29899, 29906, 1822, 6506, 877, 29995, 3788, 5477, 8025, 543, 7210, 29968, 1159, 13, 4706, 10961, 3888, 353, 4390, 29886, 29961, 29900, 22322, 29882, 29939, 2033, 13, 1678, 5174, 29901, 13, 4706, 10961, 3888, 353, 5159, 13, 268, 13, 1678, 29797, 919, 353, 6571, 13, 1678, 363, 2635, 297, 10961, 3888, 29901, 13, 4706, 29797, 919, 29961, 1256, 29961, 29900, 1822, 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tests/mod_todo_tests.py
rockyhandsm2k/website
0
79188
from tests.app_tests import BaseTestCase from app.mod_todo.models import * from flask import url_for import datetime TODO = 'Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ille enim occurrentia nescio quae comminiscebatur; Sin tantum modo ad indicia veteris memoriae cognoscenda, curiosorum. Duo Reges: constructio interrete. Tollenda est atque extrahenda radicitus. Atque ego: Scis me, inquam, istud idem sentire, Piso, sed a te opportune facta mentio est.' TODO2 = 'Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ille enim occurrentia nescio quae comminiscebatur; Sin tantum modo' CATEGORY = 'Category' PRIORITY = 'Priority' DO_BEFORE = datetime.date(2020, 12, 12) class TestTodo(BaseTestCase): @classmethod def setUpClass(cls): cls.disable_login = True super().setUpClass() cls.url = url_for('adminpanel.configure_module', bp_name='todo') TodoCategory.create(category=CATEGORY) TodoPriority.create(name=PRIORITY, priority=0) def create_todo_item(self, todo, category_id, priority_id, do_before): return self.client.post(url_for('todo.index'), data=dict( todo=todo, category=category_id, priority=priority_id, do_before=do_before, create='Create' )) def delete_todo_items(self, todo_ids): return self.client.get(url_for('todo.index', delete=','.join([str(x) for x in todo_ids]))) def complete_todo_items(self, todo_ids): return self.client.get(url_for('todo.index', complete=','.join([str(x) for x in todo_ids]))) def test_create_todo_item(self): # Test adding an item self.create_todo_item(TODO, 1, 1, DO_BEFORE) todo_item = Todo.query.filter_by(todo=TODO).first() self.assertIsInstance(todo_item, Todo) self.assertEquals(todo_item.category_id, 1) self.assertEquals(todo_item.priority_id, 1) self.assertEquals(todo_item.do_before.date(), DO_BEFORE) # Test that adding an empty item fails self.create_todo_item('', 1, 1, DO_BEFORE) todo_item = Todo.query.filter_by(todo='').first() self.assertIsNone(todo_item) def test_delete_todo_item(self): # Test deleting a single item self.create_todo_item(TODO, 1, 1, DO_BEFORE) self.delete_todo_items([1]) todo = Todo.query.filter_by(id=1).first() self.assertIsNone(todo) # Test deleting multiple items self.create_todo_item(TODO, 1, 1, DO_BEFORE) self.create_todo_item(TODO2, 1, 1, DO_BEFORE) self.delete_todo_items([2, 3]) todo = Todo.query.filter(Todo.id.in_([2, 3])).all() self.assertEquals(todo, []) def test_complete_todo_item(self): # Test completing a single item self.create_todo_item(TODO, 1, 1, DO_BEFORE) self.complete_todo_items([1]) todo = Todo.query.filter_by(id=1).first() timedelta = datetime.datetime.now() - todo.completed_on self.assertLess(timedelta, datetime.timedelta(seconds=0.1)) # Test trying to complete the same item again doesn't change the closed on time. old_completed_on = todo.completed_on self.complete_todo_items([1]) todo = Todo.query.filter_by(id=1).first() self.assertEquals(old_completed_on, todo.completed_on) # Test completing multiple items self.create_todo_item(TODO, 1, 1, DO_BEFORE) self.create_todo_item(TODO2, 1, 1, DO_BEFORE) self.complete_todo_items([2, 3]) todo = Todo.query.filter(Todo.id.in_([2, 3])).all() for item in todo: self.assertIsNotNone(item.completed_on)
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research/width_control.py
HewJhong/1st_Day_Hack
1
106987
import streamlit as st def select_block_container_style(): """Add selection section for setting setting the max-width and padding of the main block container""" st.sidebar.header("Block Container Style") max_width_100_percent = st.sidebar.checkbox("Max-width: 100%?", False) if not max_width_100_percent: max_width = st.sidebar.slider("Select max-width in px", 100, 2000, 1200, 100) else: max_width = 1200 dark_theme = st.sidebar.checkbox("Dark Theme?", False) padding_top = st.sidebar.number_input("Select padding top in rem", 0, 200, 5, 1) padding_right = st.sidebar.number_input("Select padding right in rem", 0, 200, 1, 1) padding_left = st.sidebar.number_input("Select padding left in rem", 0, 200, 1, 1) padding_bottom = st.sidebar.number_input( "Select padding bottom in rem", 0, 200, 10, 1 ) if dark_theme: BACKGROUND_COLOR = "rgb(17,17,17)" COLOR = "#fff" else: BACKGROUND_COLOR = "rgb(255,255,255)" COLOR = "#000" _set_block_container_style( BACKGROUND_COLOR, COLOR, max_width, max_width_100_percent, padding_top, padding_right, padding_left, padding_bottom, ) def _set_block_container_style( bg_color: str, color: str, max_width: int = 1000, max_width_100_percent: bool = False, padding_top: int = 5, padding_right: int = 1, padding_left: int = 1, padding_bottom: int = 10, ): if max_width_100_percent: max_width_str = f"max-width: 100%;" else: max_width_str = f"max-width: {max_width}px;" st.markdown( f""" <style> .reportview-container .main .block-container{{ {max_width_str} padding-top: {padding_top}rem; padding-right: {padding_right}rem; padding-left: {padding_left}rem; padding-bottom: {padding_bottom}rem; }} .reportview-container .main {{ color: {color}; background-color: {bg_color}; }} </style> """, unsafe_allow_html=True, )
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Part5/varargs3.py
BaiMoHan/LearningPython_ING_202002
0
111934
<reponame>BaiMoHan/LearningPython_ING_202002 #!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2020/2/14 14:58 # @Author : Baimohan/PH # @Site : https://github.com/BaiMoHan # @File : varargs3.py # @Software: PyCharm def test(x, y, z=3, *books, **scores): # **代表收集关键字参数 print(x, y, z) print(books) # 收集参数保存的是元组 print(scores) # 对于关键字参数保存的是字典形式 if __name__ == '__main__': test(1, 2, 3, 'fluent phthon', 'first python', Chinese=89, Math=36) test(1, 2, Chinese=88, Englishi=88)
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Python3-world2/ex068.py
samirsaravia/Python_101
0
38161
<filename>Python3-world2/ex068.py import random title = 'par ou ímpar'.upper() print('~~' * 10) print(f'\033[7;30m{title:^20}\033[m') print('~~' * 10) # poi = par ou impar # vop = vitoria ou perda poi = vop = '' cont = 0 while True: cont += 1 escolha_numero = int(input('Digite um número: ')) escolha_parinpar = str(input('Par ou Impar[P/I]: ')).strip().upper()[0] en = escolha_numero epi = escolha_parinpar # npc = numero do pc npc = random.randint(1, 100) soma = npc + en if soma % 2 == 0: poi = 'par' else: poi = 'ímpar' if soma % 2 == 0 and epi in 'Pp' or soma % 2 != 0 and epi in 'Ii': vop = '\033[1;32mganhou\033[m' else: vop = '\033[1;31mperdeu\033[m' break print(f'O numero escolhido pelo pc foi : {npc}') print(f'A soma foi: \033[1;33m{soma}\033[m') print(f'Você {vop}, deu \033[1;33m{poi}\033[m') print('---' * 10) print(f'O numero escolhido pelo pc foi : {npc}') print(f'A soma foi: \033[1;33m{soma}\033[m') if cont > 1: print(f'Depois de {cont - 1} vezes seguidas, ', end='') print(f'Você {vop}, deu \033[1;33m{poi}')
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pedantic/decorators/fn_deco_pedantic.py
LostInDarkMath/Pedantic-python-decorators
15
109204
from functools import wraps from typing import Any, Optional from pedantic.type_checking_logic.check_docstring import _check_docstring from pedantic.constants import ReturnType, F from pedantic.models.decorated_function import DecoratedFunction from pedantic.models.function_call import FunctionCall from pedantic.env_var_logic import is_enabled def pedantic(func: Optional[F] = None, require_docstring: bool = False) -> F: """ A PedanticException is raised if one of the following happened: - The decorated function is called with positional arguments. - The function has no type annotation for their return type or one or more parameters do not have type annotations. - A type annotation is incorrect. - A type annotation misses type arguments, e.g. typing.List instead of typing.List[int]. - The documented arguments do not match the argument list or their type annotations. Example: >>> @pedantic ... def my_function(a: int, b: float, c: str) -> bool: ... return float(a) == b and str(b) == c >>> my_function(a=42.0, b=14.0, c='hi') Traceback (most recent call last): ... pedantic.exceptions.PedanticTypeCheckException: In function my_function: Type hint is incorrect: Argument a=42.0 of type <class 'float'> does not match expected type <class 'int'>. >>> my_function(a=42, b=None, c='hi') Traceback (most recent call last): ... pedantic.exceptions.PedanticTypeCheckException: In function my_function: Type hint is incorrect: Argument b=None of type <class 'NoneType'> does not match expected type <class 'float'>. >>> my_function(a=42, b=42, c='hi') Traceback (most recent call last): ... pedantic.exceptions.PedanticTypeCheckException: In function my_function: Type hint is incorrect: Argument b=42 of type <class 'int'> does not match expected type <class 'float'>. >>> my_function(5, 4.0, 'hi') Traceback (most recent call last): ... pedantic.exceptions.PedanticCallWithArgsException: In function my_function: Use kwargs when you call function my_function. Args: (5, 4.0, 'hi') """ def decorator(f: F) -> F: if not is_enabled(): return f decorated_func = DecoratedFunction(func=f) if require_docstring or len(decorated_func.docstring.params) > 0: _check_docstring(decorated_func=decorated_func) @wraps(f) def wrapper(*args: Any, **kwargs: Any) -> ReturnType: call = FunctionCall(func=decorated_func, args=args, kwargs=kwargs) call.assert_uses_kwargs() return call.check_types() async def async_wrapper(*args: Any, **kwargs: Any) -> ReturnType: call = FunctionCall(func=decorated_func, args=args, kwargs=kwargs) call.assert_uses_kwargs() return await call.async_check_types() if decorated_func.is_coroutine: return async_wrapper else: return wrapper return decorator if func is None else decorator(f=func) def pedantic_require_docstring(func: Optional[F] = None) -> F: """Shortcut for @pedantic(require_docstring=True) """ return pedantic(func=func, require_docstring=True) if __name__ == "__main__": import doctest doctest.testmod(verbose=False, optionflags=doctest.ELLIPSIS)
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dp/combination_sum.py
Ratione/Python-Algroithms
0
186262
<reponame>Ratione/Python-Algroithms Given an integer array with all positive numbers and no duplicates, find the number of possible combinations that add up to a positive integer target. Example: nums = [1, 2, 3] target = 4 The possible combination ways are: (1, 1, 1, 1) (1, 1, 2) (1, 2, 1) (1, 3) (2, 1, 1) (2, 2) (3, 1) Note that different sequences are counted as different combinations. Therefore the output is 7. Follow up: What if negative numbers are allowed in the given array? How does it change the problem? What limitation we need to add to the question to allow negative numbers? private int[] dp; public int combinationSum4(int[] nums, int target) { dp = new int[target + 1]; Arrays.fill(dp, -1); dp[0] = 1; return helper(nums, target); } private int helper(int[] nums, int target) { if (dp[target] != -1) { return dp[target]; } int res = 0; for (int i = 0; i < nums.length; i++) { if (target >= nums[i]) { res += helper(nums, target - nums[i]); } } dp[target] = res; return res; } EDIT: The above solution is top-down. How about a bottom-up one? public int combinationSum4(int[] nums, int target) { int[] comb = new int[target + 1]; comb[0] = 1; for (int i = 1; i < comb.length; i++) { for (int j = 0; j < nums.length; j++) { if (i - nums[j] >= 0) { comb[i] += comb[i - nums[j]]; } } } return comb[target]; }
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run_evaluation.py
XiaoSanGit/wda_tracker
24
62152
<filename>run_evaluation.py<gh_stars>10-100 import sys def append_to_pythonpath(paths): for path in paths: sys.path.append(path) append_to_pythonpath(['/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/clustering', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/detectors/mmdetection', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/trackers/iou_tracker', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/evaluation/py_motmetrics', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/feature_extractors/reid-strong-baseline', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/clustering', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/detectors/mmdetection', '/home/koehlp/Dokumente/JTA-MTMCT-Mod/deep_sort_mc/feature_extractors/ABD_Net']) import argparse import mmcv import logging from utils.logger import setup_logger import os import json from evaluation.multicam_evaluation import splitted_multi_cam_evaluation from evaluation.motmetrics_evaluation import splitted_single_cam_evaluation class Run_clustering: def __init__(self,args): self.cfg = mmcv.Config.fromfile(args.config).root self.cfg.config_basename = os.path.basename(args.config).replace(".py", "") config_run_path = os.path.join(self.cfg.config_run_path, self.cfg.config_basename) setattr(self.cfg, "config_run_path", config_run_path) os.makedirs(config_run_path,exist_ok=True) self.logger = setup_logger("clustering_logger", self.cfg.config_run_path, 0) self.logger.info(json.dumps(self.cfg, sort_keys=True, indent=4)) def run(self): if self.cfg.evaluate_multi_cam: multi_cam_eval_results_folder = os.path.join(self.cfg.config_run_path,"multi_cam_evaluation") self.logger.info("Started multi cam evaluation") splitted_multi_cam_evaluation(dataset_folder=self.cfg.dataset_folder , track_results_folder=self.cfg.track_results_folder , results_output_folder=multi_cam_eval_results_folder , cam_ids=self.cfg.cam_ids , working_dir=self.cfg.working_dir , n_parts=self.cfg.n_parts ) self.logger.info("Finished multi cam evaluation") if self.cfg.evaluate_single_cam: single_cam_eval_results_folder = os.path.join(self.cfg.config_run_path,"single_cam_evaluation") self.logger.info("Started single cam evaluation") splitted_single_cam_evaluation(dataset_folder=self.cfg.dataset_folder , track_results_folder=self.cfg.track_results_folder , results_output_folder=single_cam_eval_results_folder , cam_ids=self.cfg.cam_ids , working_dir=self.cfg.working_dir , n_parts=self.cfg.n_parts ) self.logger.info("Finished single cam evaluation") def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--config", type=str) return parser.parse_args() if __name__=="__main__": args = parse_args() run_clustering = Run_clustering(args) run_clustering.run()
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src/list_screen/__init__.py
JeremyMoeglich/Python-Cmd-Screen
0
184488
from .main import Screen
[ 1, 515, 869, 3396, 1053, 22666, 2 ]
crowdbotics_test/animal/serializers/dog.py
marslan390/DjangoModelInheritance
0
160065
from .animal import AnimalSerializer from crowdbotics_test.animal.models import Dog class DogSerializer(AnimalSerializer): def create(self, validated_data): return Dog.objects.create(**validated_data) def update(self, instance, validated_data): instance.name = validated_data.get('name', instance.name) instance.birthday = validated_data.get('birthday', instance.birthday) instance.save() return instance
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bitey/cpu/flag/flag_json_decoder.py
jgerrish/bitey
0
197405
from dataclasses import dataclass import json from json import JSONDecoder from typing import ClassVar from bitey.cpu.flag.flag import Flag, Flags from bitey.cpu.flag.carry_flag import CarryFlag from bitey.cpu.flag.decimal_flag import DecimalFlag from bitey.cpu.flag.negative_flag import NegativeFlag from bitey.cpu.flag.zero_flag import ZeroFlag @dataclass class FlagJSONDecoder(JSONDecoder): """ Decode a flag definition in JSON format """ flag_map: ClassVar[dict[str, Flag]] = { "C": CarryFlag, "N": NegativeFlag, "Z": ZeroFlag, "D": DecimalFlag, } def decode(self, json_doc): """ Decode a flag definition in JSON format json_doc should be a parsed JSON structure """ if ( ("short_name" in json_doc) and ("name" in json_doc) and ("bit_field_pos" in json_doc) and ("status" in json_doc) ): status = False if json_doc["status"] == 0: status = False elif json_doc["status"] == 1: status = True short_name = json_doc["short_name"] if "options" in json_doc: options = json_doc["options"] else: options = None # Create a specific class if it exists if short_name in FlagJSONDecoder.flag_map: flag_class = FlagJSONDecoder.flag_map[short_name] return flag_class( short_name, json_doc["name"], json_doc["bit_field_pos"], status, options, ) return Flag( short_name, json_doc["name"], json_doc["bit_field_pos"], status, options, ) else: # Return None if the flag JSON object is missing fields or invalid return None class FlagsJSONDecoder(JSONDecoder): """ Decode a list of flag definitions in JSON format """ def decode(self, json_doc): parsed_json = json.loads(json_doc) return self.decode_parsed(parsed_json) def decode_parsed(self, parsed_json): flag_list = [] rjd = FlagJSONDecoder() for flag in parsed_json: f = rjd.decode(flag) # Only append the flag if all fields are present and the JSON # is valid for the flag if f: flag_list.append(f) # TODO: Some things should be initialized to certain values # Make sure setting the flags byte to zero on start is ok return Flags(flag_list, None)
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tests/test_game_map.py
brittleshinpass/mossbread
1
15127
import pytest from array import array from game_map import GameMap from tests.conftest import get_relative_path sample_map_data = tuple( reversed( ( array("I", (0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0)), array("I", (0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0)), array("I", (1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1)), array("I", (1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1)), array("I", (1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)), array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)), array("I", (1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1)), array("I", (0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0)), array("I", (0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0)), ) ) ) def test_game_map_from_file(sample_game_map, sample_tiles): assert sample_game_map.map_data == sample_map_data assert sample_game_map.width == 21 assert sample_game_map.height == 21 assert sample_game_map.tile_data == sample_tiles # Assert map is read right-up assert sample_game_map.get(16, 2) == 0 assert sample_game_map.get(16, 18) == 1 def test_game_map_get_out_of_bounds(sample_game_map): with pytest.raises(AssertionError): sample_game_map.get(-1, 0) sample_game_map.get(0, -1) sample_game_map.get(-1, -1) sample_game_map.get(21, 0) sample_game_map.get(0, 21) sample_game_map.get(21, 21) def test_game_map_load_mapfile_nonrectangular(): with pytest.raises(AssertionError): GameMap.load_mapfile(get_relative_path("fixtures/map_nonrectangular.csv")) def test_game_map_traversable(sample_game_map): assert sample_game_map.traversable(2, 2) assert not sample_game_map.traversable(1, 1) assert sample_game_map.traversable(16, 2) assert not sample_game_map.traversable(16, 18)
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evernotebot/bot/storage.py
AuroraDysis/evernote-telegram-bot
1
14550
import json import sqlite3 import typing from typing import Optional, Dict from copy import deepcopy from contextlib import suppress from bson.objectid import ObjectId from pymongo import MongoClient from pymongo.errors import ConfigurationError class MongoStorageException(Exception): pass class Mongo: def __init__(self, connection_string, *, collection=None, db_name=None): if collection is None: raise MongoStorageException('`collection` is required') self._driver = MongoClient(connection_string) with suppress(ConfigurationError): db = self._driver.get_database(db_name) if db is None: raise MongoStorageException( 'You have to specify database name ' 'either in connection string or as `db_name` parameter') self._collection = db.get_collection(collection) def create(self, data: dict, auto_generate_id=False): data = deepcopy(data) if "id" in data: data["_id"] = data["id"] del data["id"] elif not auto_generate_id: raise MongoStorageException("`id` required") object_id = self._collection.insert_one(data).inserted_id if isinstance(object_id, ObjectId): object_id = str(object_id) return object_id def get(self, object_id, fail_if_not_exists=False): query = object_id if isinstance(object_id, dict) else {"_id": object_id} data = self._collection.find_one(query) if fail_if_not_exists and not data: raise MongoStorageException(f"Object not found. Query: {query}") if data: data["id"] = data["_id"] del data["_id"] return data def get_all(self, query): for document in self._collection.find(query): document["id"] = document["_id"] del document["_id"] yield document def save(self, data: dict): object_id = data.get("id") if object_id: data["_id"] = object_id del data["id"] query = {"_id": object_id} result = self._collection.update_one(query, {"$set": data}) if result.matched_count == 0: raise MongoStorageException(f"Object `{object_id}` not found") data["id"] = object_id else: object_id = str(self._collection.insert_one(data).inserted_id) if isinstance(object_id, ObjectId): object_id = str(object_id) data["id"] = object_id return object_id def delete(self, object_id, check_deleted_count=True): result = self._collection.delete_one({"_id": object_id}) if check_deleted_count and result.deleted_count != 1: raise MongoStorageException(f"Object `{object_id}` not found") def close(self): self._driver.close() class Sqlite: def __init__(self, dirpath: str, *, collection: str = None, db_name: str = None) -> None: db_filepath = f'{dirpath}/{db_name}' self._connection = sqlite3.connect(db_filepath) self._table_name = collection self.__execute_sql( f'CREATE TABLE IF NOT EXISTS {collection}' '(id INTEGER PRIMARY KEY AUTOINCREMENT, data TEXT)' ) def __execute_sql(self, sql: str, *args) -> sqlite3.Cursor: sql = sql.strip().upper() cursor = self._connection.execute(sql, args) if not sql.startswith('SELECT'): self._connection.commit() return cursor def create(self, data: dict, auto_generate_id: bool = False) -> int: table = self._table_name if auto_generate_id: if 'id' in data: del data['id'] sql = f'INSERT INTO {table}(data) VALUES(?)' cursor = self.__execute_sql(sql, json.dumps(data)) else: object_id = data['id'] if object_id <= 0: raise Exception(f'Invalid id `{object_id}`. Id must be >= 0') cursor = self.__execute_sql(f'INSERT INTO {table}(id, data) VALUES(?, ?)', object_id, json.dumps(data)) return cursor.lastrowid def get(self, object_id: int, fail_if_not_exists: bool = False) -> Dict: query = object_id if isinstance(object_id, dict) else {'id': object_id} objects = self.get_all(query) result = list(objects) if fail_if_not_exists and not result: raise Exception(f'Object not found. Query: {query}') return result and result[0] def get_all(self, query: Optional[Dict] = None) -> typing.Generator: if query is None: query = {} table = self._table_name args = tuple() if 'id' in query: sql = f'SELECT id, data FROM {table} WHERE id=?' args = (query['id'],) else: sql = f'SELECT id, data FROM {table}' cursor = self.__execute_sql(sql, *args) objects = cursor.fetchall() if not objects: return tuple() for object_id, json_data in objects: data = json.loads(json_data) data['id'] = object_id if self._check_query(data, query): yield data def _check_query(self, document: dict, query: dict) -> bool: matched = True for k, query_value in query.items(): key_value = document for name in k.split('.'): key_value = key_value.get(name) if isinstance(key_value, dict) else None if key_value is None: break if isinstance(query_value, dict): matched = self._check_query(key_value, query_value) else: matched = key_value == query_value if not matched: return False return matched def save(self, data: dict) -> int: object_id = data['id'] if not object_id: object_id = self.create(data, auto_generate_id=True) else: table = self._table_name sql = f'UPDATE {table} SET data=? WHERE id=?' cursor = self.__execute_sql(sql, json.dumps(data), object_id) if cursor.rowcount == 0: raise Exception(f'Object `{object_id}` not found') return object_id def delete(self, object_id: int, check_deleted_count: bool = True) -> None: table = self._table_name sql = f'DELETE FROM {table} WHERE id=?' cursor = self.__execute_sql(sql, object_id) if check_deleted_count and cursor.rowcount != 1: raise Exception(f'Object `{object_id}` not found') def close(self) -> None: self._connection.commit() self._connection.close()
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hubspot/crm/products/api/__init__.py
fakepop/hubspot-api-python
117
43727
<reponame>fakepop/hubspot-api-python from __future__ import absolute_import # flake8: noqa # import apis into api package from hubspot.crm.products.api.associations_api import AssociationsApi from hubspot.crm.products.api.basic_api import BasicApi from hubspot.crm.products.api.batch_api import BatchApi from hubspot.crm.products.api.search_api import SearchApi
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yoon/stage1_kernel.py
yoon28/realsr-noise-injection
17
6379
<reponame>yoon28/realsr-noise-injection import os, sys import numpy as np import cv2 import random import torch from configs import Config from kernelGAN import KernelGAN from data import DataGenerator from learner import Learner import tqdm DATA_LOC = "/mnt/data/NTIRE2020/realSR/track2" # "/mnt/data/NTIRE2020/realSR/track1" DATA_X = "DPEDiphone-tr-x" # "Corrupted-tr-x" DATA_Y = "DPEDiphone-tr-y" # "Corrupted-tr-y" DATA_VAL = "DPEDiphone-va" # "Corrupted-va-x" def config_kernelGAN(afile): img_folder = os.path.dirname(afile) img_file = os.path.basename(afile) out_dir = "yoon/kernels/track2" params = ["--input_image_path", afile, "--output_dir_path", out_dir, "--noise_scale", str(1.0), "--X4"] conf = Config().parse(params) conf.input2 = None return conf def estimate_kernel(img_file): conf = config_kernelGAN(img_file) kgan = KernelGAN(conf) learner = Learner() data = DataGenerator(conf, kgan) for iteration in tqdm.tqdm(range(conf.max_iters), ncols=70): [g_in, d_in, _] = data.__getitem__(iteration) kgan.train(g_in, d_in) learner.update(iteration, kgan) kgan.finish() if __name__ == "__main__": seed_num = 0 torch.manual_seed(seed_num) torch.cuda.manual_seed(seed_num) torch.cuda.manual_seed_all(seed_num) torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False np.random.seed(seed_num) random.seed(seed_num) # exit(0) data = {"X":[os.path.join(DATA_LOC, DATA_X, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_X)) if f[-4:] == ".png"], "Y":[os.path.join(DATA_LOC, DATA_Y, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_Y)) if f[-4:] == ".png"], "val":[os.path.join(DATA_LOC, DATA_VAL, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_VAL)) if f[-4:] == ".png"]} Kernels = [] Noises = [] for f in data["X"]: estimate_kernel(f) print("fin.")
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code/doubanUtils.py
verazuo/douban_crawler
1
7143
<gh_stars>1-10 import requests import re from bs4 import BeautifulSoup def nextPageLink(sess,soup,page,head=""): NextPage=soup.find(class_='next').link.get('href') req=sess.get(head + NextPage) print(f'第{page}页：',req.status_code) return BeautifulSoup(req.text,'html.parser')
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flask_application/script.py
fmarella/dalie-flask
8
1601425
<reponame>fmarella/dalie-flask from flask.ext.script import Command from flask_application.populate import populate_data from flask_application.models import db, User, Role class ResetDB(Command): """Drops all tables and recreates them""" def run(self, **kwargs): for m in [User, Role]: m.drop() class PopulateDB(Command): """Fills in predefined data into DB""" def run(self, **kwargs): populate_data()
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mat2py/core/specgraph.py
mat2py/mat2py
0
181999
# type: ignore __all__ = [ "meshc", "barh", "trisurf", "compass", "isonormals", "plotutils", "ezcontour", "streamslice", "scatter", "rgb2ind", "usev6plotapi", "quiver", "streamline", "triplot", "tetramesh", "rose", "patch", "comet", "voronoi", "contourslice", "histogram", "errorbar", "reducepatch", "ezgraph3", "interpstreamspeed", "shrinkfaces", "ezplot3", "ezpolar", "curl", "stream3", "contour", "contours", "coneplot", "rotate", "isosurface", "pie3", "specgraphhelper", "stem", "frame2im", "comet3", "ezmeshc", "contourf", "fplot", "quiver3", "isocolors", "soundview", "ellipsoid", "parseplotapi", "streamtube", "changeseriestype", "makebars", "bar3h", "image", "trimesh", "clabel", "fill", "spinmap", "plotmatrix", "ezsurf", "divergence", "ind2rgb", "pareto", "isocaps", "moviein", "pie", "contourc", "feather", "hgline2lineseries", "ezcontourf", "stairs", "surfc", "im2java", "ezplot", "im2frame", "colstyle", "movieview", "contour3", "rgbplot", "surf2patch", "dither", "contrast", "waterfall", "cylinder", "bar", "slice", "histogram2", "streamribbon", "pcolor", "ribbon", "isplotchild", "sphere", "reducevolume", "ezsurfc", "imagesc", "subvolume", "streamparticles", "volumebounds", "plotchild", "area", "meshz", "imageview", "stem3", "scatter3", "ezmesh", "plotdoneevent", "stream2", "vissuite", "bar3", "smooth3", ] def meshc(*args): raise NotImplementedError("meshc") def barh(*args): raise NotImplementedError("barh") def trisurf(*args): raise NotImplementedError("trisurf") def compass(*args): raise NotImplementedError("compass") def isonormals(*args): raise NotImplementedError("isonormals") def plotutils(*args): raise NotImplementedError("plotutils") def ezcontour(*args): raise NotImplementedError("ezcontour") def streamslice(*args): raise NotImplementedError("streamslice") def scatter(*args): raise NotImplementedError("scatter") def rgb2ind(*args): raise NotImplementedError("rgb2ind") def usev6plotapi(*args): raise NotImplementedError("usev6plotapi") def quiver(*args): raise NotImplementedError("quiver") def streamline(*args): raise NotImplementedError("streamline") def triplot(*args): raise NotImplementedError("triplot") def tetramesh(*args): raise NotImplementedError("tetramesh") def rose(*args): raise NotImplementedError("rose") def patch(*args): raise NotImplementedError("patch") def comet(*args): raise NotImplementedError("comet") def voronoi(*args): raise NotImplementedError("voronoi") def contourslice(*args): raise NotImplementedError("contourslice") def histogram(*args): raise NotImplementedError("histogram") def errorbar(*args): raise NotImplementedError("errorbar") def reducepatch(*args): raise NotImplementedError("reducepatch") def ezgraph3(*args): raise NotImplementedError("ezgraph3") def interpstreamspeed(*args): raise NotImplementedError("interpstreamspeed") def shrinkfaces(*args): raise NotImplementedError("shrinkfaces") def ezplot3(*args): raise NotImplementedError("ezplot3") def ezpolar(*args): raise NotImplementedError("ezpolar") def curl(*args): raise NotImplementedError("curl") def stream3(*args): raise NotImplementedError("stream3") def contour(*args): raise NotImplementedError("contour") def contours(*args): raise NotImplementedError("contours") def coneplot(*args): raise NotImplementedError("coneplot") def rotate(*args): raise NotImplementedError("rotate") def isosurface(*args): raise NotImplementedError("isosurface") def pie3(*args): raise NotImplementedError("pie3") def specgraphhelper(*args): raise NotImplementedError("specgraphhelper") def stem(*args): raise NotImplementedError("stem") def frame2im(*args): raise NotImplementedError("frame2im") def comet3(*args): raise NotImplementedError("comet3") def ezmeshc(*args): raise NotImplementedError("ezmeshc") def contourf(*args): raise NotImplementedError("contourf") def fplot(*args): raise NotImplementedError("fplot") def quiver3(*args): raise NotImplementedError("quiver3") def isocolors(*args): raise NotImplementedError("isocolors") def soundview(*args): raise NotImplementedError("soundview") def ellipsoid(*args): raise NotImplementedError("ellipsoid") def parseplotapi(*args): raise NotImplementedError("parseplotapi") def streamtube(*args): raise NotImplementedError("streamtube") def changeseriestype(*args): raise NotImplementedError("changeseriestype") def makebars(*args): raise NotImplementedError("makebars") def bar3h(*args): raise NotImplementedError("bar3h") def image(*args): raise NotImplementedError("image") def trimesh(*args): raise NotImplementedError("trimesh") def clabel(*args): raise NotImplementedError("clabel") def fill(*args): raise NotImplementedError("fill") def spinmap(*args): raise NotImplementedError("spinmap") def plotmatrix(*args): raise NotImplementedError("plotmatrix") def ezsurf(*args): raise NotImplementedError("ezsurf") def divergence(*args): raise NotImplementedError("divergence") def ind2rgb(*args): raise NotImplementedError("ind2rgb") def pareto(*args): raise NotImplementedError("pareto") def isocaps(*args): raise NotImplementedError("isocaps") def moviein(*args): raise NotImplementedError("moviein") def pie(*args): raise NotImplementedError("pie") def contourc(*args): raise NotImplementedError("contourc") def feather(*args): raise NotImplementedError("feather") def hgline2lineseries(*args): raise NotImplementedError("hgline2lineseries") def ezcontourf(*args): raise NotImplementedError("ezcontourf") def stairs(*args): raise NotImplementedError("stairs") def surfc(*args): raise NotImplementedError("surfc") def im2java(*args): raise NotImplementedError("im2java") def ezplot(*args): raise NotImplementedError("ezplot") def im2frame(*args): raise NotImplementedError("im2frame") def colstyle(*args): raise NotImplementedError("colstyle") def movieview(*args): raise NotImplementedError("movieview") def contour3(*args): raise NotImplementedError("contour3") def rgbplot(*args): raise NotImplementedError("rgbplot") def surf2patch(*args): raise NotImplementedError("surf2patch") def dither(*args): raise NotImplementedError("dither") def contrast(*args): raise NotImplementedError("contrast") def waterfall(*args): raise NotImplementedError("waterfall") def cylinder(*args): raise NotImplementedError("cylinder") def bar(*args): raise NotImplementedError("bar") def slice(*args): raise NotImplementedError("slice") def histogram2(*args): raise NotImplementedError("histogram2") def streamribbon(*args): raise NotImplementedError("streamribbon") def pcolor(*args): raise NotImplementedError("pcolor") def ribbon(*args): raise NotImplementedError("ribbon") def isplotchild(*args): raise NotImplementedError("isplotchild") def sphere(*args): raise NotImplementedError("sphere") def reducevolume(*args): raise NotImplementedError("reducevolume") def ezsurfc(*args): raise NotImplementedError("ezsurfc") def imagesc(*args): raise NotImplementedError("imagesc") def subvolume(*args): raise NotImplementedError("subvolume") def streamparticles(*args): raise NotImplementedError("streamparticles") def volumebounds(*args): raise NotImplementedError("volumebounds") def plotchild(*args): raise NotImplementedError("plotchild") def area(*args): raise NotImplementedError("area") def meshz(*args): raise NotImplementedError("meshz") def imageview(*args): raise NotImplementedError("imageview") def stem3(*args): raise NotImplementedError("stem3") def scatter3(*args): raise NotImplementedError("scatter3") def ezmesh(*args): raise NotImplementedError("ezmesh") def plotdoneevent(*args): raise NotImplementedError("plotdoneevent") def stream2(*args): raise NotImplementedError("stream2") def vissuite(*args): raise NotImplementedError("vissuite") def bar3(*args): raise NotImplementedError("bar3") def smooth3(*args): raise NotImplementedError("smooth3")
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tests/test_req_vars.py
fast01/falcon-python
1
74446
import datetime import six import testtools import ddt import falcon from falcon.request import Request import falcon.testing as testing @ddt.ddt class TestReqVars(testing.TestBase): def before(self): self.qs = 'marker=deadbeef&limit=10' self.headers = { 'Content-Type': 'text/plain', 'Content-Length': '4829', 'Authorization': '' } self.app = '/test' self.path = '/hello' self.relative_uri = self.path + '?' + self.qs self.req = Request(testing.create_environ( app=self.app, port=8080, path='/hello', query_string=self.qs, headers=self.headers)) self.req_noqs = Request(testing.create_environ( app=self.app, path='/hello', headers=self.headers)) def test_missing_qs(self): env = testing.create_environ() if 'QUERY_STRING' in env: del env['QUERY_STRING'] # Should not cause an exception when Request is instantiated Request(env) def test_empty(self): self.assertIs(self.req.auth, None) def test_host(self): self.assertEqual(self.req.host, testing.DEFAULT_HOST) def test_subdomain(self): req = Request(testing.create_environ( host='com', path='/hello', headers=self.headers)) self.assertIs(req.subdomain, None) req = Request(testing.create_environ( host='example.com', path='/hello', headers=self.headers)) self.assertEqual(req.subdomain, 'example') req = Request(testing.create_environ( host='highwire.example.com', path='/hello', headers=self.headers)) self.assertEqual(req.subdomain, 'highwire') req = Request(testing.create_environ( host='lb01.dfw01.example.com', port=8080, path='/hello', headers=self.headers)) self.assertEqual(req.subdomain, 'lb01') # NOTE(kgriffs): Behavior for IP addresses is undefined, # so just make sure it doesn't blow up. req = Request(testing.create_environ( host='127.0.0.1', path='/hello', headers=self.headers)) self.assertEqual(type(req.subdomain), str) # NOTE(kgriffs): Test fallback to SERVER_NAME by using # HTTP 1.0, which will cause .create_environ to not set # HTTP_HOST. req = Request(testing.create_environ( protocol='HTTP/1.0', host='example.com', path='/hello', headers=self.headers)) self.assertEqual(req.subdomain, 'example') def test_reconstruct_url(self): req = self.req scheme = req.protocol host = req.get_header('host') app = req.app path = req.path query_string = req.query_string expected_uri = ''.join([scheme, '://', host, app, path, '?', query_string]) self.assertEqual(expected_uri, req.uri) @testtools.skipUnless(six.PY3, 'Test only applies to Python 3') def test_nonlatin_path(self): cyrillic_path = u'/hello_\u043f\u0440\u0438\u0432\u0435\u0442' cyrillic_path_decoded = cyrillic_path.encode('utf-8').decode('latin1') req = Request(testing.create_environ( host='com', path=cyrillic_path_decoded, headers=self.headers)) self.assertEqual(req.path, cyrillic_path) def test_uri(self): uri = ('http://' + testing.DEFAULT_HOST + ':8080' + self.app + self.relative_uri) self.assertEqual(self.req.url, uri) # NOTE(kgriffs): Call twice to check caching works self.assertEqual(self.req.uri, uri) self.assertEqual(self.req.uri, uri) uri_noqs = ('http://' + testing.DEFAULT_HOST + self.app + self.path) self.assertEqual(self.req_noqs.uri, uri_noqs) def test_uri_https(self): # ======================================================= # Default port, implicit # ======================================================= req = Request(testing.create_environ( path='/hello', scheme='https')) uri = ('https://' + testing.DEFAULT_HOST + '/hello') self.assertEqual(req.uri, uri) # ======================================================= # Default port, explicit # ======================================================= req = Request(testing.create_environ( path='/hello', scheme='https', port=443)) uri = ('https://' + testing.DEFAULT_HOST + '/hello') self.assertEqual(req.uri, uri) # ======================================================= # Non-default port # ======================================================= req = Request(testing.create_environ( path='/hello', scheme='https', port=22)) uri = ('https://' + testing.DEFAULT_HOST + ':22/hello') self.assertEqual(req.uri, uri) def test_uri_http_1_0(self): # ======================================================= # HTTP, 80 # ======================================================= req = Request(testing.create_environ( protocol='HTTP/1.0', app=self.app, port=80, path='/hello', query_string=self.qs, headers=self.headers)) uri = ('http://' + testing.DEFAULT_HOST + self.app + self.relative_uri) self.assertEqual(req.uri, uri) # ======================================================= # HTTP, 80 # ======================================================= req = Request(testing.create_environ( protocol='HTTP/1.0', app=self.app, port=8080, path='/hello', query_string=self.qs, headers=self.headers)) uri = ('http://' + testing.DEFAULT_HOST + ':8080' + self.app + self.relative_uri) self.assertEqual(req.uri, uri) # ======================================================= # HTTP, 80 # ======================================================= req = Request(testing.create_environ( protocol='HTTP/1.0', scheme='https', app=self.app, port=443, path='/hello', query_string=self.qs, headers=self.headers)) uri = ('https://' + testing.DEFAULT_HOST + self.app + self.relative_uri) self.assertEqual(req.uri, uri) # ======================================================= # HTTP, 80 # ======================================================= req = Request(testing.create_environ( protocol='HTTP/1.0', scheme='https', app=self.app, port=22, path='/hello', query_string=self.qs, headers=self.headers)) uri = ('https://' + testing.DEFAULT_HOST + ':22' + self.app + self.relative_uri) self.assertEqual(req.uri, uri) def test_relative_uri(self): self.assertEqual(self.req.relative_uri, self.app + self.relative_uri) self.assertEqual( self.req_noqs.relative_uri, self.app + self.path) req_noapp = Request(testing.create_environ( path='/hello', query_string=self.qs, headers=self.headers)) self.assertEqual(req_noapp.relative_uri, self.relative_uri) req_noapp = Request(testing.create_environ( path='/hello/', query_string=self.qs, headers=self.headers)) # NOTE(kgriffs): Call twice to check caching works self.assertEqual(req_noapp.relative_uri, self.relative_uri) self.assertEqual(req_noapp.relative_uri, self.relative_uri) def test_client_accepts(self): headers = {'Accept': 'application/xml'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('application/xml')) headers = {'Accept': '*/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('application/xml')) self.assertTrue(req.client_accepts('application/json')) self.assertTrue(req.client_accepts('application/x-msgpack')) headers = {'Accept': 'application/x-msgpack'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts('application/xml')) self.assertFalse(req.client_accepts('application/json')) self.assertTrue(req.client_accepts('application/x-msgpack')) headers = {} # NOTE(kgriffs): Equivalent to '*/*' per RFC req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('application/xml')) headers = {'Accept': 'application/json'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts('application/xml')) headers = {'Accept': 'application/x-msgpack'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('application/x-msgpack')) headers = {'Accept': 'application/xm'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts('application/xml')) headers = {'Accept': 'application/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('application/json')) self.assertTrue(req.client_accepts('application/xml')) self.assertTrue(req.client_accepts('application/x-msgpack')) headers = {'Accept': 'text/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('text/plain')) self.assertTrue(req.client_accepts('text/csv')) self.assertFalse(req.client_accepts('application/xhtml+xml')) headers = {'Accept': 'text/*, application/xhtml+xml; q=0.0'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('text/plain')) self.assertTrue(req.client_accepts('text/csv')) self.assertTrue(req.client_accepts('application/xhtml+xml')) headers = {'Accept': 'text/*; q=0.1, application/xhtml+xml; q=0.5'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('text/plain')) headers = {'Accept': 'text/*, application/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('text/plain')) self.assertTrue(req.client_accepts('application/xml')) self.assertTrue(req.client_accepts('application/json')) self.assertTrue(req.client_accepts('application/x-msgpack')) headers = {'Accept': 'text/*,application/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts('text/plain')) self.assertTrue(req.client_accepts('application/xml')) self.assertTrue(req.client_accepts('application/json')) self.assertTrue(req.client_accepts('application/x-msgpack')) def test_client_accepts_bogus(self): headers = {'Accept': '~'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts('text/plain')) self.assertFalse(req.client_accepts('application/json')) def test_client_accepts_props(self): headers = {'Accept': 'application/xml'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts_xml) self.assertFalse(req.client_accepts_json) self.assertFalse(req.client_accepts_msgpack) headers = {'Accept': 'application/*'} req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts_xml) self.assertTrue(req.client_accepts_json) self.assertTrue(req.client_accepts_msgpack) headers = {'Accept': 'application/json'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts_xml) self.assertTrue(req.client_accepts_json) self.assertFalse(req.client_accepts_msgpack) headers = {'Accept': 'application/x-msgpack'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts_xml) self.assertFalse(req.client_accepts_json) self.assertTrue(req.client_accepts_msgpack) headers = {'Accept': 'application/msgpack'} req = Request(testing.create_environ(headers=headers)) self.assertFalse(req.client_accepts_xml) self.assertFalse(req.client_accepts_json) self.assertTrue(req.client_accepts_msgpack) headers = { 'Accept': 'application/json,application/xml,application/x-msgpack' } req = Request(testing.create_environ(headers=headers)) self.assertTrue(req.client_accepts_xml) self.assertTrue(req.client_accepts_json) self.assertTrue(req.client_accepts_msgpack) def test_client_prefers(self): headers = {'Accept': 'application/xml'} req = Request(testing.create_environ(headers=headers)) preferred_type = req.client_prefers(['application/xml']) self.assertEqual(preferred_type, 'application/xml') headers = {'Accept': '*/*'} preferred_type = req.client_prefers(('application/xml', 'application/json')) # NOTE(kgriffs): If client doesn't care, "preferr" the first one self.assertEqual(preferred_type, 'application/xml') headers = {'Accept': 'text/*; q=0.1, application/xhtml+xml; q=0.5'} req = Request(testing.create_environ(headers=headers)) preferred_type = req.client_prefers(['application/xhtml+xml']) self.assertEqual(preferred_type, 'application/xhtml+xml') headers = {'Accept': '3p12845j;;;asfd;'} req = Request(testing.create_environ(headers=headers)) preferred_type = req.client_prefers(['application/xhtml+xml']) self.assertEqual(preferred_type, None) def test_range(self): headers = {'Range': 'bytes=10-'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (10, -1)) headers = {'Range': 'bytes=10-20'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (10, 20)) headers = {'Range': 'bytes=-10240'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (-10240, -1)) headers = {'Range': 'bytes=0-2'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (0, 2)) headers = {'Range': ''} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPInvalidHeader, lambda: req.range) req = Request(testing.create_environ()) self.assertIs(req.range, None) def test_range_unit(self): headers = {'Range': 'bytes=10-'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (10, -1)) self.assertEqual(req.range_unit, 'bytes') headers = {'Range': 'items=10-'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.range, (10, -1)) self.assertEqual(req.range_unit, 'items') headers = {'Range': ''} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPInvalidHeader, lambda: req.range_unit) req = Request(testing.create_environ()) self.assertIs(req.range_unit, None) def test_range_invalid(self): headers = {'Range': 'bytes=10240'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=-'} expected_desc = ('The value provided for the Range header is ' 'invalid. The range offsets are missing.') self._test_error_details(headers, 'range', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) headers = {'Range': 'bytes=--'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=-3-'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=-3-4'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=3-3-4'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=3-3-'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=3-3- '} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=fizbit'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=a-'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=a-3'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=-b'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=3-b'} req = Request(testing.create_environ(headers=headers)) self.assertRaises(falcon.HTTPBadRequest, lambda: req.range) headers = {'Range': 'bytes=x-y'} expected_desc = ('The value provided for the Range header is ' 'invalid. It must be a range formatted ' 'according to RFC 7233.') self._test_error_details(headers, 'range', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) headers = {'Range': 'bytes=0-0,-1'} expected_desc = ('The value provided for the Range ' 'header is invalid. The value must be a ' 'continuous range.') self._test_error_details(headers, 'range', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) headers = {'Range': '10-'} expected_desc = ("The value provided for the Range " "header is invalid. The value must be " "prefixed with a range unit, e.g. 'bytes='") self._test_error_details(headers, 'range', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) def test_missing_attribute_header(self): req = Request(testing.create_environ()) self.assertEqual(req.range, None) req = Request(testing.create_environ()) self.assertEqual(req.content_length, None) def test_content_length(self): headers = {'content-length': '5656'} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.content_length, 5656) headers = {'content-length': ''} req = Request(testing.create_environ(headers=headers)) self.assertEqual(req.content_length, None) def test_bogus_content_length_nan(self): headers = {'content-length': 'fuzzy-bunnies'} expected_desc = ('The value provided for the ' 'Content-Length header is invalid. The value ' 'of the header must be a number.') self._test_error_details(headers, 'content_length', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) def test_bogus_content_length_neg(self): headers = {'content-length': '-1'} expected_desc = ('The value provided for the Content-Length ' 'header is invalid. The value of the header ' 'must be a positive number.') self._test_error_details(headers, 'content_length', falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc) @ddt.data(('Date', 'date'), ('If-Modified-since', 'if_modified_since'), ('If-Unmodified-since', 'if_unmodified_since'), ) @ddt.unpack def test_date(self, header, attr): date = datetime.datetime(2013, 4, 4, 5, 19, 18) date_str = 'Thu, 04 Apr 2013 05:19:18 GMT' self._test_header_expected_value(header, date_str, attr, date) @ddt.data(('Date', 'date'), ('If-Modified-Since', 'if_modified_since'), ('If-Unmodified-Since', 'if_unmodified_since'), ) @ddt.unpack def test_date_invalid(self, header, attr): # Date formats don't conform to RFC 1123 headers = {header: 'Thu, 04 Apr 2013'} expected_desc = ('The value provided for the {0} ' 'header is invalid. It must be formatted ' 'according to RFC 7231, Section 7.1.1.1') self._test_error_details(headers, attr, falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc.format(header)) headers = {header: ''} self._test_error_details(headers, attr, falcon.HTTPInvalidHeader, 'Invalid header value', expected_desc.format(header)) @ddt.data('date', 'if_modified_since', 'if_unmodified_since') def test_date_missing(self, attr): req = Request(testing.create_environ()) self.assertIs(getattr(req, attr), None) def test_attribute_headers(self): hash = 'fa0d1a60ef6616bb28038515c8ea4cb2' auth = 'HMAC_SHA1 c590afa9bb59191ffab30f223791e82d3fd3e3af' agent = 'testing/1.0.1' default_agent = 'curl/7.24.0 (x86_64-apple-darwin12.0)' self._test_attribute_header('Accept', 'x-falcon', 'accept', default='*/*') self._test_attribute_header('Authorization', auth, 'auth') self._test_attribute_header('Content-Type', 'text/plain', 'content_type') self._test_attribute_header('Expect', '100-continue', 'expect') self._test_attribute_header('If-Match', hash, 'if_match') self._test_attribute_header('If-None-Match', hash, 'if_none_match') self._test_attribute_header('If-Range', hash, 'if_range') self._test_attribute_header('User-Agent', agent, 'user_agent', default=default_agent) def test_method(self): self.assertEqual(self.req.method, 'GET') self.req = Request(testing.create_environ(path='', method='HEAD')) self.assertEqual(self.req.method, 'HEAD') def test_empty_path(self): self.req = Request(testing.create_environ(path='')) self.assertEqual(self.req.path, '/') def test_content_type_method(self): self.assertEqual(self.req.get_header('content-type'), 'text/plain') def test_content_length_method(self): self.assertEqual(self.req.get_header('content-length'), '4829') # ------------------------------------------------------------------------- # Helpers # ------------------------------------------------------------------------- def _test_attribute_header(self, name, value, attr, default=None): headers = {name: value} req = Request(testing.create_environ(headers=headers)) self.assertEqual(getattr(req, attr), value) req = Request(testing.create_environ()) self.assertEqual(getattr(req, attr), default) def _test_header_expected_value(self, name, value, attr, expected_value): headers = {name: value} req = Request(testing.create_environ(headers=headers)) self.assertEqual(getattr(req, attr), expected_value) def _test_error_details(self, headers, attr_name, error_type, title, description): req = Request(testing.create_environ(headers=headers)) try: getattr(req, attr_name) self.fail('{0} not raised'.format(error_type.__name__)) except error_type as ex: self.assertEqual(ex.title, title) self.assertEqual(ex.description, description)
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oop/data-hiding.py
sinhdev/python-demo
0
58222
<reponame>sinhdev/python-demo<gh_stars>0 #!/usr/bin/python class JustCounter: __secret_count = 0 def count(self): self.__secret_count += 1 print(self.__secret_count) counter = JustCounter() counter.count() counter.count() # can't access print(counter.__secret_count)
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users/views.py
Slawomir-Kwiatkowski/auto-maniac
3
1600297
from django.shortcuts import render, redirect from django.contrib.auth.forms import UserCreationForm, PasswordChangeForm from django.contrib.auth import login, authenticate, update_session_auth_hash from django.views.generic import CreateView from django.contrib import messages from django.contrib.auth.mixins import LoginRequiredMixin class RegisterUser(CreateView): form_class = UserCreationForm def get(self, request, *args, **kwargs): return render(request, 'users/register-user.html', {'form': UserCreationForm()}) def post(self, request, *args, **kwargs): form = UserCreationForm(request.POST) if form.is_valid(): form.save() username = form.cleaned_data.get('username') password = form.cleaned_data.get('<PASSWORD>') user = authenticate(username=username, password=password) login(request, user) messages.success(request, f'Welcome, {username}!') return redirect('cars') return render(request, 'users/register-user.html', {'form': form}) class ChangePassword(LoginRequiredMixin, CreateView): form_class = PasswordChangeForm def get(self, request, *args, **kwargs): form = PasswordChangeForm(request.user) return render(request, 'users/change-password.html', {'form': form}) def post(self, request, *args, **kwargs): form = PasswordChangeForm(request.user, request.POST) if form.is_valid(): user = form.save() update_session_auth_hash(request, user) messages.success(request, 'Password changed!') return redirect('cars') return render(request, 'users/change-password.html', {'form': form})
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atcoder/abc/abc135_b.py
knuu/competitive-programming
1
125127
N = int(input()) A = [int(x) for x in input().split()] for i in range(N): for j in range(i, N): A[i], A[j] = A[j], A[i] if sorted(A) == A: print("YES") quit() A[i], A[j] = A[j], A[i] print("NO")
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app/actions/campaigns.py
appliedbloc/cm-data-service
0
116611
<filename>app/actions/campaigns.py<gh_stars>0 from sqlalchemy.orm import Session from sqlalchemy import update from fastapi.encoders import jsonable_encoder import models, schemas def get_campaign(db: Session, campaign_id: int): return db.query(models.Campaign).filter(models.Campaign.id == campaign_id).first() def get_campaign_by_recipient(db: Session, recipient: str): return db.query(models.Campaign).filter(models.Campaign.recipient == recipient).first() def get_campaigns(db: Session, skip: int = 0, limit: int = 10): return db.query(models.Campaign).offset(skip).limit(limit).all() def create_campaign(db: Session, campaign: schemas.CampaignCreate): db_campaign = models.Campaign(**campaign.dict()) db.add(db_campaign) db.commit() db.refresh(db_campaign) return db_campaign def update_campaign(db: Session, db_campaign: models.Campaign, campaign: schemas.CampaignUpdate): campaign_in = campaign.dict(exclude_unset=True) obj_data = jsonable_encoder(db_campaign) for field in obj_data: if field in campaign_in: setattr(db_campaign, field, campaign_in[field]) db.add(db_campaign) db.commit() db.refresh(db_campaign) return db_campaign
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test_vs_model_DEMs.py
drewleonard42/CoronaTemps
1
34608
<reponame>drewleonard42/CoronaTemps # -*- coding: utf-8 -*- """ Script to produce synthetic AIA data based on arbitrary model DEMs and test the results of the tempmap code against the model. Created on Mon Jul 28 16:34:28 2014 @author: <NAME> """ import numpy as np from matplotlib import use, rc use('agg') rc('savefig', bbox='tight', pad_inches=0.5) import matplotlib.pyplot as plt from matplotlib import patches import sunpy from sunpy.map import Map from temperature import TemperatureMap from utils import gaussian, load_temp_responses from os import path, makedirs import subprocess32 as subp from itertools import product from skimage import measure from sys import argv # Decide whether to assess single-parameter or full-Gaussian method n_pars = int(argv[1]) # Define which wavelength to use for EM estimation with 1-parameter TMaps emwlen = str(argv[2]) # Define CoronaTemps home folder and output folder CThome = path.join(path.expanduser('~'), 'CoronaTemps') outdir = path.join(CThome, 'validation', '{}pars'.format(n_pars)) tmap_script = path.join(CThome, 'create_tempmap.py') if not path.exists(outdir): makedirs(outdir) # Define parameter ranges #temps = np.arange(4.6, 7.405, 0.01)#0.005) temps = np.arange(5.6, 7.005, 0.01) widths = np.array([0.01, 0.1, 0.5])#np.arange(0.01, 0.605, 0.005) # Just copying Aschwanden's range here #heights = 10 ** np.arange(18, 37, 0.1)#0.05) heights = 10 ** np.arange(20, 35, 0.1) #print heights n_temps = len(temps) n_widths = len(widths) n_heights = len(heights) parvals = np.array([i for i in product(temps, widths, heights)]) #print parvals.shape n_vals = n_temps * n_widths * n_heights #print n_temps, n_widths, n_heights, n_vals, n_vals * 6 # Create model DEMs and synthetic emission emission = np.zeros((6, n_temps, n_widths, n_heights)) #print emission.shape logt = np.arange(0, 15.05, 0.05) resp = load_temp_responses() delta_t = logt[1] - logt[0] for p, params in enumerate(parvals): dem = gaussian(logt, *params) f = resp * dem t = np.where(temps == params[0])[0][0] w = np.where(widths == params[1])[0][0] h = np.where(heights == params[2])[0][0] emission[:, t, w, h] = np.sum(f, axis=1) * delta_t #emission = emission / emission[2, :, :, :] #print '----', emission[2, :, :, :].min(), emission[2, :, :, :].max() # Load AIA response functions resp = load_temp_responses() # Load unnessecary map for its metadata voidmap = Map(sunpy.AIA_171_IMAGE) mapmeta = voidmap.meta #rect = patches.Rectangle([25.0, 5.6], 1.0, 1.0, color='black', fill=True, clip_on=False) # Run synthetic data through 1param tempmap method for w, wid in enumerate(widths):#heights): print '\nWidth:', wid fig = plt.figure(figsize=(30, 12)) for wl, wlength in enumerate(['94', '131', '171', '193', '211', '335']): #emiss = Map(emission[wl, :, :, w], mapmeta) emiss = Map(emission[wl, :, w, :].copy(), mapmeta) emiss.cmap = sunpy.cm.get_cmap('sdoaia{}'.format(wlength)) emiss.meta['naxis1'] = emiss.shape[1] emiss.meta['naxis2'] = emiss.shape[0] #emiss.meta['cdelt1'] = widths[1] - widths[0] emiss.meta['cdelt1'] = heights[1] - heights[0] #np.log10(heights[1]) - np.log10(heights[0]) emiss.meta['cdelt2'] = temps[1] - temps[0] #emiss.meta['crval1'] = widths[0] emiss.meta['crval1'] = heights[0] #np.log10(heights[0]) emiss.meta['crval2'] = temps[0] emiss.meta['crpix1'] = 0.5 emiss.meta['crpix2'] = 0.5 if wlength == '94': wlength = '094' fits_dir = path.join(CThome, 'data', 'synthetic', wlength) if not path.exists(fits_dir): makedirs(fits_dir) emiss.save(path.join(fits_dir, 'model.fits'), clobber=True) #print '----', emission[2, :, :, :].min(), emission[2, :, :, :].max() #print '------', emission[2, :, w, :].min(), emission[2, :, w, :].max() emiss.data /= emission[2, :, w, :] #print '--------', emiss.min(), emiss.max() ax = fig.add_subplot(1, 6, wl+1) emiss.plot(aspect='auto', vmin=emiss.min(), vmax=emiss.max()) plt.title('{}'.format(wlength)) plt.xlabel('Input EM') plt.ylabel('Input log(T)') plt.colorbar() #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') #plt.savefig(path.join(outdir, 'model_emission_h={}'.format(np.log10(wid)).replace('.', '_'))) plt.savefig(path.join(outdir, 'model_emission_w={}'.format(wid).replace('.', '_'))) plt.close() #images = [Map(emission[i, :, :, w], mapmeta) for i in range(6)] images = [Map(emission[i, :, w, :], mapmeta) for i in range(6)] if n_pars == 3: cmdargs = "mpiexec -n 10 python {} model {} {} {} {} {} {}".format( tmap_script, n_pars, path.join(CThome, 'data'), None, None, True, True).split() else: cmdargs = "python {} model {} {} {} {} {} {}".format( tmap_script, n_pars, path.join(CThome, 'data'), None, None, True, True).split() status = subp.call(cmdargs) newmap = TemperatureMap(fname=path.join(CThome, 'temporary.fits')) subp.call(["rm", path.join(CThome, 'temporary.fits')]) data, meta = newmap.data, newmap.meta fitsmap = Map(np.log10(newmap.goodness_of_fit), newmap.meta.copy()) #print fitsmap.max() newmap.data = data print '-------------MINMAX:-------------'#, newmap.min(), newmap.max(), newmap.shape, #print newmap.data[newmap.data == 0].shape, '----------\n' print 'GoF', fitsmap.min(), fitsmap.mean(), fitsmap.max() print 'T_out', newmap.min(), newmap.mean(), newmap.max() #truetemp = np.array(list(temps)*n_widths).reshape((n_widths, n_temps)).T truetemp = np.array(list(temps)*n_heights).reshape((n_heights, n_temps)).T #print truetemp.shape, data.shape diff = Map((abs(truetemp - data) / truetemp) * 100, newmap.meta.copy()) print 'T_diff', diff.min(), diff.mean(), diff.max() if n_pars == 3: wdata = Map(newmap.dem_width, newmap.meta.copy()) truew = np.ones(shape=(n_temps, n_heights)) * wid #print 'truew', truew.min(), truew.mean(), truew.max() diffw = Map((abs(truew - wdata.data) / truew) * 100, newmap.meta.copy()) print 'w_out', wdata.min(), wdata.mean(), wdata.max() print 'w_diff', diffw.min(), diffw.mean(), diffw.max() #print wid, newmap.xrange, newmap.yrange, newmap.scale #print wid, diff.xrange, diff.yrange, diff.scale fig = plt.figure(figsize=(24, 12)) fig.add_subplot(1, 3, 1) newmap.plot(cmap='coolwarm', vmin=5.6, vmax=7.0, aspect='auto') plt.colorbar() plt.title('Solution log(T)', fontsize=28) plt.ylabel('Input log(T)', fontsize=24) plt.xlabel('Input EM', fontsize=24)#width', fontsize=24) #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') ax = fig.add_subplot(1, 3, 2) #print 'diff', diff.min(), diff.max() #print np.nanmin(diff.data), np.nanmax(diff.data) diff.plot(cmap='RdYlGn_r', aspect='auto')#, vmin=diff.min(), vmax=diff.max()) plt.colorbar() plt.title('Difference from input (%)', fontsize=28) plt.xlabel('Input EM', fontsize=24) #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') ax = fig.add_subplot(1, 3, 3) #print 'fits', fitsmap.min(), fitsmap.max() #print np.nanmin(fitsmap.data), np.nanmax(fitsmap.data) fitsmap.plot(cmap='cubehelix', aspect='auto')#, # vmin=np.nanmin(fitsmap.data)-(2.0*(np.nanstd(fitsmap.data))), # vmax=np.nanmax(fitsmap.data)+(2.0*(np.nanstd(fitsmap.data)))) plt.colorbar() plt.title('log(Goodness-of-fit)', fontsize=28) plt.xlabel('Input EM', fontsize=24) #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') #plt.savefig(path.join(outdir, 'tempsolutions_em={}'.format(np.log10(wid)).replace('.', '_'))) plt.savefig(path.join(outdir, 'tempsolutions_wid={:.3f}'.format(wid).replace('.', '_'))) plt.close() if n_pars == 3: emdata = Map(newmap.emission_measure, newmap.meta.copy()) else: if emwlen == 'three': total = np.zeros(newmap.shape) for w in ['171', '193', '211']: emdata = newmap.calculate_em(w, model=True) total += emdata.data emdata.data = total/3.0 elif emwlen == 'all': total = np.zeros(newmap.shape) for w in ['94', '131', '171', '193', '211', '335']: emdata = newmap.calculate_em(w, model=True) total += emdata.data emdata.data = total/6.0 else: emdata = newmap.calculate_em(emwlen, model=True) trueem = np.array(list(heights)*n_temps).reshape(n_temps, n_heights) diffem = Map((abs(trueem - emdata.data) / trueem) * 100, newmap.meta.copy()) #print wid, emdata.xrange, emdata.yrange, emdata.scale #print wid, diffem.xrange, diffem.yrange, diffem.scale #print wid, fitsmap.xrange, fitsmap.yrange, fitsmap.scale fig = plt.figure(figsize=(24, 12)) ax = fig.add_subplot(1, 3, 1) print 'em_out', emdata.min(), emdata.mean(), emdata.max() print 'em_diff', diffem.min(), diffem.mean(), diffem.max() #print np.nanmin(emdata.data), np.nanmax(emdata.data) emdata.plot(cmap='coolwarm', aspect='auto', vmin=emdata.min(), vmax=emdata.max()) # vmin=np.log10(heights[0]), vmax=np.log10(heights[-1])) contours = measure.find_contours(emdata.data, heights[0]) for contour in contours: contour[:, 0] *= emdata.scale['y'] contour[:, 1] *= emdata.scale['x'] contour[:, 0] += emdata.yrange[0] contour[:, 1] += emdata.xrange[0] plt.plot(contour[:, 1], contour[:, 0], color='blue') plt.xlim(*emdata.xrange) plt.ylim(*emdata.yrange) contours = measure.find_contours(emdata.data, heights[-1]) for contour in contours: contour[:, 0] *= emdata.scale['y'] contour[:, 1] *= emdata.scale['x'] contour[:, 0] += emdata.yrange[0] contour[:, 1] += emdata.xrange[0] plt.plot(contour[:, 1], contour[:, 0], color='black') plt.xlim(*emdata.xrange) plt.ylim(*emdata.yrange) if n_pars == 3: plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('Solution EM', fontsize=28) plt.ylabel('Input log(T)', fontsize=24) plt.xlabel('Input EM', fontsize=24)#width', fontsize=24) ax = fig.add_subplot(1, 3, 2) #print 'diffem', diffem.min(), diffem.max() #print np.nanmin(diffem.data), np.nanmax(diffem.data) diffem.plot(cmap='RdYlGn_r', aspect='auto', # vmin=0, vmax=50) vmin=diffem.min(), vmax=diffem.max()) #fig.gca().add_artist(rect) if n_pars == 3: plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('Difference from input (%)', fontsize=28) plt.xlabel('Input EM', fontsize=24) ax = fig.add_subplot(1, 3, 3) fitsmap.plot(cmap='cubehelix', aspect='auto') if n_pars == 3: plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('log(Goodness-of-fit)', fontsize=28) plt.xlabel('Input EM', fontsize=24) if n_pars == 3: plt.savefig(path.join(outdir, 'emsolutions_wid={:.3f}'.format(wid).replace('.', '_'))) else: plt.savefig(path.join(outdir, 'emsolutions_wid={:.3f}_wlen={}'.format(wid, emwlen).replace('.', '_'))) plt.close() if n_pars == 3: #print wid, wdata.xrange, wdata.yrange, wdata.scale #print wid, diffw.xrange, diffw.yrange, diffw.scale fig = plt.figure(figsize=(24, 12)) ax = fig.add_subplot(1, 3, 1) wdata.plot(cmap='coolwarm', vmin=widths[0], vmax=widths[-1], aspect='auto') #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('Solution width', fontsize=28) plt.ylabel('Input log(T)', fontsize=24) plt.xlabel('Input EM', fontsize=24)#width', fontsize=24) ax = fig.add_subplot(1, 3, 2) #print 'diffw', diffw.min(), diffw.max() #print np.nanmin(diffw.data), np.nanmax(diffw.data) diffw.plot(cmap='RdYlGn_r', vmin=diffw.min(), vmax=diffw.max(), aspect='auto') #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('Difference from input (%)', fontsize=28) plt.xlabel('Input EM', fontsize=24) ax = fig.add_subplot(1, 3, 3) fitsmap.plot(cmap='cubehelix', aspect='auto') #fig.gca().add_artist(rect) plt.axvline(20.0, color='white') plt.axvline(35.0, color='white') plt.axhline(5.6, color='white') plt.axhline(7.0, color='white') plt.colorbar() plt.title('log(Goodness-of-fit)', fontsize=28) plt.xlabel('Input EM', fontsize=24) plt.savefig(path.join(outdir, 'widsolutions_wid={:.3f}'.format(wid).replace('.', '_'))) plt.close() """w = np.where((widths > 0.097)*(widths < 0.103)) dataslice = data[:, w].reshape(len(temps)) diffslice = diff[:, w].reshape(len(temps)) fitslice = fits[:, w].reshape(len(temps)) fig = plt.figure(figsize=(16, 12)) plt.plot(temps, dataslice) plt.title('Solution log(T) at width=0.1', fontsize=28) plt.xlabel('Input log(T)', fontsize=24) plt.ylabel('Solution log(T)', fontsize=24) plt.savefig('/home/drew/Dropbox/euroscipy/dataslice') plt.close() fig = plt.figure(figsize=(16, 12)) plt.plot(temps, diffslice) plt.title('Difference from input at width=0.1', fontsize=28) plt.xlabel('Input log(T)', fontsize=24) plt.ylabel('Difference (%)', fontsize=24) plt.savefig('/home/drew/Dropbox/euroscipy/diffslice') plt.close() fig = plt.figure(figsize=(16, 12)) ax = fig.add_subplot(1, 1, 1) plt.plot(temps, np.log10(fitslice)) plt.title('Goodness-of-fit at width=0.1', fontsize=28) plt.xlabel('Input log(T)', fontsize=24) plt.ylabel('log(Goodness-of-fit)', fontsize=24) plt.savefig('/home/drew/Dropbox/euroscipy/fitslice') plt.close()""" # Run synthetic data throguh 3param tempmap method # Somehow display the results.
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get_block_data/relation.py
cyclone923/blocks-world
1
3997
class SceneRelation: def __init__(self): self.on_ground = set() self.on_block = {} self.clear = set() def print_relation(self): print(self.on_ground) print(self.on_block) print(self.clear)
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sigopt/cli/commands/run_base.py
emattia/sigopt-python
67
143137
import functools import click from ..arguments import commands_argument, run_file_option def run_command(f): @commands_argument @run_file_option @functools.wraps(f) def wrapper(*args, commands, run_file, **kwargs): if run_file: run_options = run_file.data else: run_options = {} if not commands: try: commands = run_options["run"] except KeyError as ke: raise click.UsageError( "Missing command: Please specify your run command via arguments or in the 'run' section of the run file." ) from ke return f(*args, command=commands, run_options=run_options, **kwargs) return wrapper
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gen_api/generate_cpp_api.py
jordenson/nakama-cpp
0
82955
#!/usr/bin/env python # # Copyright 2019 The Nakama Authors # # 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. # from __future__ import print_function import os import sys import subprocess import argparse import platform def getEnvVar(name): if name in os.environ: return os.environ[name] return '' parser = argparse.ArgumentParser(description='Nakama C++ API generator') parser.add_argument('-n', '--nakama', help='Nakama server sources') parser.add_argument('-g', '--gateway', help='grpc-gateway sources') args = parser.parse_args() def getArgOrEnvVar(env_var_name, arg_value): if arg_value: value = arg_value else: value = getEnvVar(env_var_name) if not value: print('Error: missing "' + env_var_name + '" env variable') sys.exit(-1) return value # https://github.com/heroiclabs/nakama NAKAMA = getArgOrEnvVar('NAKAMA', args.nakama) # https://github.com/grpc-ecosystem/grpc-gateway GRPC_GATEWAY = getArgOrEnvVar('GRPC_GATEWAY', args.gateway) def path(p): return os.path.normpath(p) def get_host_arch(): import platform bits, _ = platform.architecture() if bits == '64bit': arch = 'x64' elif bits == '32bit': arch = 'x86' else: arch = bits return arch NAKAMA_CPP = os.path.abspath('./..') GRPC = path(NAKAMA_CPP + '/third_party/grpc') GOOGLEAPIS = path(GRPC_GATEWAY + '/third_party/googleapis') PROTOBUF_SRC = path(GRPC + '/third_party/protobuf/src') OUT = os.path.abspath('cppout') is_windows = platform.system() == 'Windows' is_mac = platform.system() == 'Darwin' if is_windows: build_dir = NAKAMA_CPP + '/build/windows/build/v142_x86' elif is_mac: build_dir_debug = NAKAMA_CPP + '/build/mac/build/Debug' build_dir_release = NAKAMA_CPP + '/build/mac/build/Release' else: # linux arch = get_host_arch() build_dir_debug = NAKAMA_CPP + '/build/linux/build/Debug_' + arch build_dir_release = NAKAMA_CPP + '/build/linux/build/Release_' + arch def find_grpc_cpp_plugin(): if is_windows: grpc_cpp_plugin = path(build_dir + '/third_party/grpc/Debug/grpc_cpp_plugin.exe') if not os.path.exists(grpc_cpp_plugin): grpc_cpp_plugin = path(build_dir + '/third_party/grpc/Release/grpc_cpp_plugin.exe') else: grpc_cpp_plugin = path(build_dir_release + '/third_party/grpc/grpc_cpp_plugin') if not os.path.exists(grpc_cpp_plugin): grpc_cpp_plugin = path(build_dir_debug + '/third_party/grpc/grpc_cpp_plugin') if not os.path.exists(grpc_cpp_plugin): print('grpc_cpp_plugin not found') print('Please build for desktop OS first') sys.exit(-1) return grpc_cpp_plugin def find_protoc(): if is_windows: protoc = path(build_dir + '/third_party/grpc/third_party/protobuf/Debug/protoc.exe') if not os.path.exists(protoc): protoc = path(build_dir + '/third_party/grpc/third_party/protobuf/Release/protoc.exe') else: protoc = path(build_dir_release + '/third_party/grpc/third_party/protobuf/protoc') if not os.path.exists(protoc): protoc = path(build_dir_debug + '/third_party/grpc/third_party/protobuf/protoc') if not os.path.exists(protoc): print('protoc not found') print('Please build for desktop OS first') sys.exit(-1) return protoc def call(commands, shell=False): #print('call', str(commands)) res = subprocess.call(commands, shell=shell) if res != 0: sys.exit(-1) def check_required_folder(folder): if not os.path.exists(folder): print('ERROR: not exist', folder) sys.exit(-1) def makedirs(path): if not os.path.exists(path): os.makedirs(path) def mklink(link, target): if not os.path.exists(link): if is_windows: call(['mklink', link, target], shell=True) else: call(['ln', '-s', target, link], shell=False) GRPC_CPP_PLUGIN = find_grpc_cpp_plugin() PROTOC = find_protoc() check_required_folder(NAKAMA) check_required_folder(GRPC) check_required_folder(GRPC_GATEWAY) check_required_folder(GOOGLEAPIS) check_required_folder(GRPC_CPP_PLUGIN) check_required_folder(PROTOC) check_required_folder(PROTOBUF_SRC) CUR_DIR = os.path.abspath('.') makedirs(OUT) makedirs(path(OUT + '/google/api')) makedirs(path(OUT + '/google/rpc')) makedirs(path(CUR_DIR + '/github.com/heroiclabs/nakama-common/api')) makedirs(path(CUR_DIR + '/github.com/heroiclabs/nakama/apigrpc')) makedirs(path(CUR_DIR + '/github.com/heroiclabs/nakama-common/rtapi')) mklink(path(CUR_DIR + '/github.com/heroiclabs/nakama-common/api/api.proto'), path(NAKAMA + '/vendor/github.com/heroiclabs/nakama-common/api/api.proto')) mklink(path(CUR_DIR + '/github.com/heroiclabs/nakama/apigrpc/apigrpc.proto'), path(NAKAMA + '/apigrpc/apigrpc.proto')) mklink(path(CUR_DIR + '/github.com/heroiclabs/nakama-common/rtapi/realtime.proto'), path(NAKAMA + '/vendor/github.com/heroiclabs/nakama-common/rtapi/realtime.proto')) print('generating apigrpc') call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--grpc_out=' + OUT, '--plugin=protoc-gen-grpc=' + GRPC_CPP_PLUGIN, path('github.com/heroiclabs/nakama/apigrpc/apigrpc.proto')]) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + OUT, path('github.com/heroiclabs/nakama/apigrpc/apigrpc.proto')]) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + OUT, path('github.com/heroiclabs/nakama-common/api/api.proto')]) os.chdir(path(GOOGLEAPIS + '/google/rpc')) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + path(OUT + '/google/rpc'), 'status.proto']) os.chdir(path(GOOGLEAPIS + '/google/api')) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + path(OUT + '/google/api'), 'annotations.proto']) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + path(OUT + '/google/api'), 'http.proto']) os.chdir(CUR_DIR) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + OUT, path(GRPC_GATEWAY + '/protoc-gen-swagger/options/annotations.proto')]) call([PROTOC, '-I.', '-I' + GRPC_GATEWAY, '-I' + GOOGLEAPIS, '-I' + PROTOBUF_SRC, '--cpp_out=' + OUT, path(GRPC_GATEWAY + '/protoc-gen-swagger/options/openapiv2.proto')]) print('generating rtapi') call([PROTOC, '-I.', '-I' + PROTOBUF_SRC, '--cpp_out=' + OUT, path('github.com/heroiclabs/nakama-common/rtapi/realtime.proto')]) print('done.')
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1495, 2314, 13, 13, 359, 29889, 305, 3972, 29898, 2084, 29898, 17080, 29949, 29954, 1307, 8787, 29903, 718, 8207, 3608, 29914, 29878, 6739, 8785, 13, 13, 4804, 4197, 8618, 4986, 29907, 29892, 17411, 29902, 29889, 742, 17411, 29902, 29915, 718, 18016, 9026, 29918, 29954, 3040, 12982, 29979, 29892, 17411, 29902, 29915, 718, 21947, 29949, 29954, 1307, 8787, 29903, 29892, 17411, 29902, 29915, 718, 13756, 4986, 7838, 29943, 29918, 29903, 10363, 29892, 525, 489, 8223, 29918, 449, 2433, 718, 2224, 29898, 12015, 718, 8207, 3608, 29914, 29878, 6739, 5477, 525, 4882, 29889, 17529, 11287, 13, 13, 359, 29889, 305, 3972, 29898, 2084, 29898, 17080, 29949, 29954, 1307, 8787, 29903, 718, 8207, 3608, 29914, 2754, 8785, 13, 13, 4804, 4197, 8618, 4986, 29907, 29892, 17411, 29902, 29889, 742, 17411, 29902, 29915, 718, 18016, 9026, 29918, 29954, 3040, 12982, 29979, 29892, 17411, 29902, 29915, 718, 21947, 29949, 29954, 1307, 8787, 29903, 29892, 17411, 29902, 29915, 718, 13756, 4986, 7838, 29943, 29918, 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md.py
Tensai7/manga-dl
0
51190
<filename>md.py import argparse import os import urllib.request from urllib.error import HTTPError from urllib.request import urlopen from sys import exit import extra from parsers import Mangapanda, Mangasee opener = urllib.request.build_opener() opener.addheaders = [('User-Agent', 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/36.0.1941.0 Safari/537.36')] urllib.request.install_opener(opener) """ A Multi Site Manga Downloader. """ __author__ = "<NAME>" __copyright__ = "Copyright 2017" __credits__ = "<NAME>" __license__ = "MIT License, Tensai No License" __version__ = "4.0" __maintainer__ = "Sudarshan(Ashura)" __email__ = "<EMAIL>" __status__ = "Under Production" print("\n\tMangaDownloader\n Author: {}\n Copyright: {}\n Credits: {}\n License: {}\n Version: {}\n".format(__author__, __copyright__, __credits__, __license__, __version__)) ####################################################################################################################################################################### parser = argparse.ArgumentParser(description="Command Line Mode.") parser.add_argument("-u", "--url", help="Url of the manga to be downloaded.") parser.add_argument("-b", "--begin", help="The chapter number to begin from or list of space seperated chapter numbers.") parser.add_argument("-e", "--end", help="The chapter to end at." ) parser.add_argument("-z", "--zip", action="store_true", help="Enable if zipped chapters are needed.") parser.add_argument("-i", "--interactive", action="store_true", help="Enable if you want interactive Mode") parser.add_argument("-a", "--all", action="store_true", help="Download all the chapters") parser.add_argument("-A", "--Archive", action="store_true", help="Downloads All available chapters of the series, the cover Image and zips them") parser.add_argument("-s", "--site", help="Enter 1 for mangapanda.com, 2 for mangaseeonline.us .") parser.add_argument("-n", "--name", help="Enter the name of the manga series, use if you know the correct name. Else use -g option.") parser.add_argument("-g", "--guess", help="Name of manga to be guessed.") # parser.add_argument("-t", # "--test", # action='store_true', # help="Download a series as test under Archive mode.") args = parser.parse_args() if args.interactive is True: """ For Interactive Mode. """ args.url = None args.begin = None args.end = "int" args.zip = None if args.url is True: args.site = 0 if args.all is True: """ In All Chapters Downloading mode.""" args.begin = 1 args.end = None # None used to distinguish b/w interactive and all mode if args.Archive is True: """ For Archive Mode. """ args.all = True args.zip = True args.begin = 1 args.end = "Archive" if args.guess is not None: if args.site is None: args.site = ("Please input site!!!!\nUse -s option.") exit() url = extra.Guess(int(args.site), args.guess) res = "" try: response = urllib.request.urlopen(url).read().decode('utf-8') except HTTPError: # if our guess doesnt work match = extra.Search(int(args.site), args.guess) print("Press 'y' for yes, 'n' for no.\n") for m in match: print("Did you mean :\n{}".format(m)) res = input() if res is 'y': args.url = extra.Guess(int(args.site), m.lower()) matched = m if args.end is None: args.end = "GuessMode" # for clarification. break if res is not 'y': print("Could not find manga series.\n Please use -u / --url option.\n Off Out!") exit() print("The Selected series is >>> {} <<<".format(matched)) if type(args.site) is str and type(args.name) is str: # Guess the url of the manga series try: url = extra.Guess(int(args.site), args.name) # get the guessed url x = urlopen(url) # check if the url exists args.url = "Guessed" # so that interactive mode doesn't gets implemented except HTTPError: # if the url is wrong, go to interactive mode print("Guess didn't work, lets continue in interactive mode.") args.url = None url = "" total = 0 stop = "" if args.url is None: url = str(input("Enter the url of the manga.\n1)http://www.mangapanda.com/naruto : For " "mangapanda.com\n2)http://mangaseeonline.us/manga/naruto : For mangaseeonline.us \n")) elif args.url is "Guessed": pass else: url = args.url if url[-1] is "/": # Remove trailing "/" if found url = url[0:-1] if args.begin is None: start = int(input("Enter the chapter to start from.\n")) else: start = int(args.begin) if args.end is "int" or args.end is "GuessMode": # "int" : Interactive, None : all chapters stop = input("Enter the chapter to stop at.\n") try: stop = int(stop) if stop == 0: stop = None except (ValueError, TypeError) as e: stop = None elif args.end is None: stop = None zip_flag = "" # Initialize zip_flag if args.zip is None: # interactive mode is enabled response = input(("Do you want zip archives of each chapter? Input 'y' for Yes ; 'n' for No.\n")) if response is 'y': zip_flag = True elif response is 'n': zip_flag = False else: zip_flag = False elif args.zip is True: zip_flag = True site = extra.site(url, args.site) ##################################################################################################################################################### class InvalidSite(BaseException): # Invalid Site Exception pass class Error(BaseException): # Other Errors Exception pass ###################################################################################################################################################### ## Lets Start downloading if site is "Mangapanda" or args.site is 1: manga = Mangapanda.Mangapanda(url, start, stop) MangaName = manga.GetMangaName() MangaName = extra.Namer(MangaName) Site = 1 elif site is "Mangasee" or args.site is 2: manga = Mangasee.Mangasee(url, start, stop) MangaName = manga.GetMangaName() MangaName = extra.Namer(MangaName) print(MangaName) Site = 2 else: raise InvalidSite("Error Site Not Supported.\nSee help.txt for more.!!!") # The following logic was implemented due to non consistent naming of chapters by mangaseeonline.us if args.end is "Archive": # if -A is true, set stop = Total Chapters x = manga.TotalChapters() stop = len(x) else: x = manga.TotalChapters() # x = total chapters if Site is 1 and args.end is not "GuessMode": # To avoid confusion stop = args.end elif Site is 2 and args.end is not "GuessMode": if args.end is None: args.end = start int(args.end) stop = len(x[:args.end]) else: stop = int(args.end) # if -e is given stop = len(x[: int(args.end)]) #stop = 0 to args.end print("Total Chapters Available : [].".format(stop)) ################################################################################################################################################################# """ Main Logic For Downloading. """ if stop is None or start == stop: """ single chapter downloading mode """ cwd = os.getcwd() NewPath = os.path.join(cwd, str(MangaName)) extra.MakeDir(str(MangaName), NewPath) if args.Archive is True: # Archive mode. manga.GetCoverImage() # gets cover image under Archive Mode total = manga.TotalPgs(start) ChapterPath = os.path.join(NewPath, str(start)) # Creates a new path for chapter's folder extra.MakeDir(str(start), ChapterPath, NewPath) print("Chapter-{} is Starting!".format(start)) for number in range(1, total + 1): currentUrl = manga.CurrentUrl(start, number) imgSrc = manga.GetSrc(currentUrl) manga.imgGetter(imgSrc, number) print("Chapter-{} is Downloaded".format(start)) if zip_flag is True: # Zipping of chapters. os.chdir('..') extra.zip(str(start), ChapterPath) print("Chapter-{} is Zipped!".format(start)) extra.DeleteDir(ChapterPath) else: """ Multi chapter Mode """ # Making a New folder for MangaName cwd = os.getcwd() NewPath = os.path.join(cwd, str(MangaName)) print(NewPath) extra.MakeDir(str(MangaName), NewPath) if args.Archive is True: # Archive mode manga.GetCoverImage() # gets cover image under Archive Mode print("stop is {}".format(stop)) for i in range(start, int(stop) + 1): # i = Chapter Number(generally) if Site is 1: total = manga.TotalPgs(i) # mangapanda is consistent in naming, so i is not altered elif Site is 2: total = manga.TotalPgs(int(x[i - 1])) # mangaseeonline is non consistent, so i is changed x[i - 1] = i ChapterPath = os.path.join(NewPath, str(i)) # Creates a new path for chapter's folder extra.MakeDir(str(i), ChapterPath, NewPath) print("Chapter-{} is Starting!".format(i)) for number in range(1, total + 1): # number = page number currentUrl = manga.CurrentUrl(i, number) imgSrc = manga.GetSrc(currentUrl) manga.imgGetter(imgSrc, number) print("Chapter-{} is Downloaded".format(i)) if zip_flag is True: # zipping block os.chdir('..') extra.zip(str(i), ChapterPath) print("Chapter-{} is Zipped!".format(i)) extra.DeleteDir(ChapterPath) else: os.chdir('..') print("Download Complete!!!\n")
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src/UQpy/Distributions/baseclass/DistributionContinuous1D.py
marrov/UQpy
132
17858
import numpy as np import scipy.stats as stats from UQpy.Distributions.baseclass.Distribution import Distribution class DistributionContinuous1D(Distribution): """ Parent class for univariate continuous probability distributions. """ def __init__(self, **kwargs): super().__init__(**kwargs) @staticmethod def _check_x_dimension(x): """ Check the dimension of input x - must be an ndarray of shape (npoints,) or (npoints, 1) """ x = np.atleast_1d(x) if len(x.shape) > 2 or (len(x.shape) == 2 and x.shape[1] != 1): raise ValueError('Wrong dimension in x.') return x.reshape((-1,)) def _construct_from_scipy(self, scipy_name=stats.rv_continuous): self.cdf = lambda x: scipy_name.cdf(x=self._check_x_dimension(x), **self.params) self.pdf = lambda x: scipy_name.pdf(x=self._check_x_dimension(x), **self.params) self.log_pdf = lambda x: scipy_name.logpdf(x=self._check_x_dimension(x), **self.params) self.icdf = lambda x: scipy_name.ppf(q=self._check_x_dimension(x), **self.params) self.moments = lambda moments2return='mvsk': scipy_name.stats(moments=moments2return, **self.params) self.rvs = lambda nsamples=1, random_state=None: scipy_name.rvs( size=nsamples, random_state=random_state, **self.params).reshape((nsamples, 1)) def tmp_fit(dist, data): data = self._check_x_dimension(data) fixed_params = {} for key, value in dist.params.items(): if value is not None: fixed_params['f' + key] = value params_fitted = scipy_name.fit(data=data, **fixed_params) return dict(zip(dist.order_params, params_fitted)) self.fit = lambda data: tmp_fit(self, data)
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cwvae.py
juliuskunze/cwvae
0
1603508
<filename>cwvae.py import tensorflow.compat.v1 as tf import cnns from cells import * import tools class CWVAE: def __init__( self, levels, tmp_abs_factor, state_sizes, embed_size, cell_type, lr, min_stddev, mean_only_cell=False, reset_states=False, var_scope="CWVAE", ): self.cell_type = cell_type self._levels = levels self._state_size = state_sizes["stoch"] self._detstate_size = state_sizes["deter"] self._embed_size = embed_size self._var_scope = var_scope self.lr = lr self._min_stddev = min_stddev self._tmp_abs_factor = tmp_abs_factor self._reset_states = reset_states self.cells = [] for i_lvl in range(self._levels): if self.cell_type == "RSSMCell": assert ( self._detstate_size ), f"deter state size should be non-zero int, found {self._detstate_size}" cell = RSSMCell( self._state_size, self._detstate_size, self._embed_size, reset_states=self._reset_states, min_stddev=self._min_stddev, mean_only=mean_only_cell, var_scope="cell_" + str(i_lvl), ) else: raise ValueError(f"Cell type {self.cell_type} not supported") self.cells.append(cell) def hierarchical_unroll( self, inputs, actions=None, use_observations=None, initial_state=None ): """ Used to unroll a list of recurrent cells. Arguments: cells inputs : list of encoded observations Number of nodes at every level in 'inputs' is the exact number of nodes to be unrolled actions use_observations : bool or list[bool] initial_state : list of cell states """ if use_observations is None: use_observations = self._levels * [True] elif not isinstance(use_observations, list): use_observations = self._levels * [use_observations] if initial_state is None: initial_state = self._levels * [None] level_top = self._levels - 1 inputs_top = inputs[level_top] level = level_top # Feeding in zeros as context to the top level. context = tf.zeros( shape=tf.concat( [tf.shape(inputs_top)[0:2], [self.cells[-1].state_size["output"]]], -1 ) ) # Init reset_state: alternate zeros and ones, of the size of input[level=-2] if level_top >= 1: inputs_top_ = inputs[level_top - 1] temp_zeros = tf.zeros( tf.concat([tf.shape(inputs_top_)[:2], [tf.constant(1)]], -1) ) temp_ones = tf.ones_like(temp_zeros) _reset_state = tf.concat([temp_zeros, temp_ones], -1) _reset_state = tf.reshape(_reset_state, [tf.shape(_reset_state)[0], -1, 1]) _reset_state = tf.slice( _reset_state, [0, 0, 0], tf.concat([tf.shape(inputs_top_)[:2], [tf.constant(1)]], -1), ) else: _reset_state = tf.no_op() prior_list = [] # Stored bot to top. posterior_list = [] # Stored bot to top. last_state_all_levels = [] for level in range(level_top, -1, -1): obs_inputs = inputs[level] print(f"Input shape in CWVAE level {level}: {obs_inputs.shape}") if level == level_top: reset_state, reset_state_next = ( tf.ones(shape=tf.concat([tf.shape(obs_inputs)[0:2], [1]], -1)), _reset_state, ) else: reset_state, reset_state_next = ( reset_state, tf.tile(reset_state, [1, self._tmp_abs_factor, 1]), ) # Pruning reset_state, context from previous layer, to match the num of nodes reqd as in inputs[level] reset_state = tf.slice( reset_state, len(context.shape.as_list()) * [0], tf.concat([tf.shape(obs_inputs)[:2], [1]], -1), ) context = tf.slice( context, len(context.shape.as_list()) * [0], tf.concat([tf.shape(obs_inputs)[:2], context.shape.as_list()[2:]], -1), ) # Concatenating actions (if provided) to the context at the bottom-most level. if level == 0 and actions is not None: context = tf.concat([context, actions], axis=-1) # Dynamic unroll of RNN cell. initial = self.cells[level].zero_out_state(tf.shape(obs_inputs)[0]) if initial_state[level] is not None: initial["state"] = initial_state[level] (prior, posterior), posterior_last_step = tools.scan( self.cells[level], (obs_inputs, context, reset_state), use_observations[level], initial, ) last_state_all_levels.insert(0, posterior_last_step) context = posterior["output"] prior_list.insert(0, prior) posterior_list.insert(0, posterior) # Tiling context by a factor of tmp_abs_factor for use at the level below. if level != 0: context = tf.expand_dims(context, axis=2) context = tf.tile( context, [1, 1, self._tmp_abs_factor] + (len(context.shape.as_list()) - 3) * [1], ) context = tf.reshape( context, [tf.shape(context)[0], tf.reduce_prod(tf.shape(context)[1:3])] + context.shape.as_list()[3:], ) reset_state = reset_state_next output_bot_level = context return output_bot_level, last_state_all_levels, prior_list, posterior_list def open_loop_unroll(self, inputs, ctx_len, actions=None, use_observations=None): if use_observations is None: use_observations = self._levels * [True] ctx_len_backup = ctx_len pre_inputs = [] post_inputs = [] for lvl in range(self._levels): pre_inputs.append(inputs[lvl][:, :ctx_len, ...]) post_inputs.append(tf.zeros_like(inputs[lvl][:, ctx_len:, ...])) ctx_len = int(ctx_len / self._tmp_abs_factor) ctx_len = ctx_len_backup actions_pre = actions_post = None if actions is not None: actions_pre = actions[:, :ctx_len, :] actions_post = actions[:, ctx_len:, :] ( _, pre_last_state_all_levels, pre_priors, pre_posteriors, ) = self.hierarchical_unroll( pre_inputs, actions=actions_pre, use_observations=use_observations ) _, _, post_priors, _ = self.hierarchical_unroll( post_inputs, actions=actions_post, use_observations=self._levels * [False], initial_state=pre_last_state_all_levels, ) return pre_posteriors, pre_priors, post_priors def _gaussian_KLD(self, dist1, dist2): """ Computes KL(dist1 || dist2) Arguments: dist1 : dict containing 'mean' and 'stddev' for multivariate normal distributions shape of mean/stddev: (batch size, timesteps, [dim1, dim2, ...]) dist2 : (same as dist1) """ if len(dist1["mean"].shape[2:]) > 1: new_shape = tf.concat([tf.shape(dist1["mean"])[:2], [-1]], -1) dist1["mean"] = tf.reshape(dist1["mean"], new_shape) dist1["stddev"] = tf.reshape(dist1["stddev"], new_shape) dist2["mean"] = tf.reshape(dist2["mean"], new_shape) dist2["stddev"] = tf.reshape(dist2["stddev"], new_shape) mvn1 = tfd.MultivariateNormalDiag(loc=dist1["mean"], scale_diag=dist1["stddev"]) mvn2 = tfd.MultivariateNormalDiag(loc=dist2["mean"], scale_diag=dist2["stddev"]) return mvn1.kl_divergence(mvn2) def _log_prob_obs(self, samples, mean, stddev): """ Returns prob density of samples in the given distribution The last dim of the samples is the one taken sum over. """ if len(samples.shape[2:]) > 1: new_shape = tf.concat([tf.shape(samples)[:2], [-1]], -1) samples = tf.reshape(samples, new_shape) mean = tf.reshape(mean, new_shape) if isinstance(stddev, tf.Tensor): stddev = tf.reshape(stddev, new_shape) dist = tfd.Independent(tfd.Normal(mean, stddev), reinterpreted_batch_ndims=1) return dist.log_prob(samples) def _stop_grad_dist(self, dist): dist["mean"] = tf.stop_gradient(dist["mean"]) dist["stddev"] = tf.stop_gradient(dist["stddev"]) return dist def compute_losses( self, obs, obs_decoded, priors, posteriors, dec_stddev=0.1, kl_grad_post_perc=None, free_nats=None, beta=None, ): """ Computes ELBO. Arguments: obs : Placeholder Observed video obs_decoded : Tensor Decoded video priors : list[dict] each dict holds the priors at all timesteps for a particular level in the model posteriors : list[dict] each dict holds the posteriors at all timesteps for a particular level in the model """ nll_term = -self._log_prob_obs(obs, obs_decoded, dec_stddev) # shape: (B,T) nll_term = tf.reduce_mean(tf.reduce_sum(nll_term, axis=1), 0) assert len(nll_term.shape) == 0, nll_term.shape # Computing KLs between priors and posteriors self.kld_all_levels = [] kl_term = tf.constant(0.0) for i in range(self._levels): kld_level = self._gaussian_KLD(posteriors[i], priors[i]) if kl_grad_post_perc is None: kld_level_total = tf.reduce_mean(tf.reduce_sum(kld_level, axis=1)) else: # Scaling gradient between prior and posterior. kld_level_p = (1 - kl_grad_post_perc) * self._gaussian_KLD( self._stop_grad_dist(posteriors[i]), priors[i] ) # shape: (B,T) kld_level_q = kl_grad_post_perc * self._gaussian_KLD( posteriors[i], self._stop_grad_dist(priors[i]) ) # shape: (B,T) kld_level_total_p = tf.reduce_mean(tf.reduce_sum(kld_level_p, axis=1)) kld_level_total_q = tf.reduce_mean(tf.reduce_sum(kld_level_q, axis=1)) # Giving 1 free nat to the posterior. kld_level_total_q = tf.maximum(1.0, kld_level_total_q) kld_level_total = kld_level_total_p + kld_level_total_q if free_nats is None: if beta is None: kl_term += kld_level_total else: if isinstance(beta, list): kl_term += beta[i] * kld_level_total else: kl_term += beta * kld_level_total else: if beta is None: kl_term += tf.maximum(0.0, kld_level_total - free_nats) else: if isinstance(beta, list): kl_term += beta[i] * tf.maximum( 0.0, kld_level_total - free_nats ) else: kl_term += beta * tf.maximum(0.0, kld_level_total - free_nats) self.kld_all_levels.insert(i, kld_level) neg_elbo = nll_term + kl_term num_timesteps_obs = tf.cast(tf.shape(obs)[1], tf.float32) self.loss = neg_elbo / num_timesteps_obs self._kl_term = kl_term / num_timesteps_obs self._nll_term = nll_term / num_timesteps_obs return self.loss def build_model(cfg, open_loop=True): obs = tf.placeholder(tf.float32, [None, None, 64, 64, cfg.channels], name="obs") encoder = cnns.Encoder( cfg.levels, cfg.tmp_abs_factor, dense_layers=cfg.enc_dense_layers, embed_size=cfg.enc_dense_embed_size, channels_mult=cfg.channels_mult, ) decoder = cnns.Decoder(cfg.channels, channels_mult=cfg.channels_mult) obs_encoded = encoder(obs) model = CWVAE( cfg.levels, cfg.tmp_abs_factor, dict(stoch=cfg.cell_stoch_size, deter=cfg.cell_deter_size), cfg.cell_embed_size, cfg.cell_type, cfg.lr, cfg.cell_min_stddev, mean_only_cell=cfg.cell_mean_only, reset_states=cfg.cell_reset_state, ) outputs_bot, _, priors, posteriors = model.hierarchical_unroll(obs_encoded) obs_decoded = decoder(outputs_bot) loss = model.compute_losses( obs, obs_decoded, priors, posteriors, dec_stddev=cfg.dec_stddev, kl_grad_post_perc=cfg.kl_grad_post_perc, free_nats=cfg.free_nats, beta=cfg.beta, ) out = dict(training=dict(obs=obs, encoder=encoder, decoder=decoder, obs_encoded=obs_encoded, obs_decoded=obs_decoded, priors=priors, posteriors=posteriors, loss=loss), meta={"model": model}) if open_loop: posteriors_recon, priors_onestep, priors_multistep = model.open_loop_unroll( obs_encoded, cfg.open_loop_ctx, use_observations=cfg.use_obs ) obs_decoded_posterior_recon = decoder(posteriors_recon[0]["output"]) obs_decoded_prior_onestep = decoder(priors_onestep[0]["output"]) obs_decoded_prior_multistep = decoder(priors_multistep[0]["output"]) gt_multistep = obs[:, cfg.open_loop_ctx :, ...] out.update( dict(open_loop_obs_decoded=dict( posterior_recon=obs_decoded_posterior_recon, prior_onestep=obs_decoded_prior_onestep, prior_multistep=obs_decoded_prior_multistep, gt_multistep=gt_multistep)) ) return out
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app.py
varshithrajbasa/RetailBanking
0
70964
from flask import Flask, render_template, request,redirect, url_for,session from flask_mysqldb import MySQL app = Flask(__name__) app.secret_key = "<KEY>" app.config['MYSQL_HOST'] = 'localhost' app.config['MYSQL_USER'] = 'root' app.config['MYSQL_PASSWORD'] = '<PASSWORD>' app.config['MYSQL_DB'] = 'retailbanking' mysql = MySQL(app) @app.route('/', methods=['post', 'get']) def login(): message = '' if request.method == 'POST': username = request.form.get('uname') # access the data inside password = request.form.get('password') cur = mysql.connection.cursor() cur.execute('SELECT * FROM userstore WHERE login = %s AND password = %s', (username, password,)) results = cur.fetchall() if results: session['username'] = username return redirect(url_for('create_customer')) else: message = "Wrong username or password" mysql.connection.commit() cur.close() return render_template('login.html', message=message) @app.route('/create_customer', methods=['post', 'get']) def create_customer(): if session=={}: return redirect(url_for('login')) message="" if request.method == 'POST': ssn_id=int(request.form.get('ssn-id')) cust_id=int(request.form.get('cust-id')) cname=request.form.get('cname') c_age=int(request.form.get('cage')) address=request.form.get('address') city=request.form.get('secondlist') state=request.form.get('listBox') if(mysql): cursor= mysql.connection.cursor() #cursor.execute("select * from customer") cursor.execute('''INSERT INTO customer(ws_ssn, ws_cust_id, ws_name, ws_age, ws_adrs, city, state) values(%s, %s, %s, %s, %s, %s, %s)''',(ssn_id,cust_id,cname,c_age,address,city,state)) mysql.connection.commit() message="Done" else: message = "Error" return render_template('create_customer.html',message=message) @app.route('/view_customer') def users(): if session=={}: return redirect(url_for('login')) cur = mysql.connection.cursor() resultValue = cur.execute("SELECT * FROM customer") if resultValue > 0: userDetails = cur.fetchall() return render_template('view_customer.html',userDetails=userDetails) @app.route('/update_customer',methods=['post', 'get']) def update_customer(): if session=={}: return redirect(url_for('login')) id=int(request.form.get('id')) cur = mysql.connection.cursor() resultValue = cur.execute("select * from customer where ws_ssn = %s",(id,)) if resultValue > 0: userDetails = cur.fetchall() return render_template('update_customer.html',userDetails=userDetails) @app.route('/update',methods=['post', 'get']) def update(): if session=={}: return redirect(url_for('login')) id=int(request.form.get('id')) cname=request.form.get('cname') address=request.form.get('address') c_age=int(request.form.get('cage')) cur = mysql.connection.cursor() cur.execute('''UPDATE customer Set ws_age= %s ,ws_adrs= %s,ws_name= %s where ws_ssn= %s''',(c_age,address,cname,id)) mysql.connection.commit() return redirect(url_for('users')) @app.route('/view_customer2') def users1(): if session=={}: return redirect(url_for('login')) cur = mysql.connection.cursor() resultValue = cur.execute("SELECT * FROM customer") if resultValue > 0: userDetails = cur.fetchall() return render_template('view_customer2.html',userDetails=userDetails) @app.route('/delete_customer',methods=['post', 'get']) def delete_customer(): if session=={}: return redirect(url_for('login')) id=int(request.form.get('id')) cur = mysql.connection.cursor() resultValue = cur.execute("select * from customer where ws_ssn = %s",(id,)) if resultValue > 0: userDetails = cur.fetchall() return render_template('delete_customer.html',userDetails=userDetails) @app.route('/delete',methods=['post', 'get']) def delete(): if session=={}: return redirect(url_for('login')) id=int(request.form.get('id')) cur = mysql.connection.cursor() cur.execute('''delete from customer where ws_ssn= %s''',(id,)) mysql.connection.commit() return redirect(url_for('users')) #For accounts @app.route('/create_a') def create_a(): if session=={}: return redirect(url_for('login')) return render_template('create_account.html') @app.route('/create_account', methods=['post', 'get']) def create_account(): if session=={}: return redirect(url_for('login')) message="" id=int(request.form.get('cust-id')) a_type=request.form.get('account_type') print(a_type) balance=request.form.get('deposit_amount') today = date.today() cur = mysql.connection.cursor() cur.execute('''select * from customer where ws_cust_id= %s''',(id,)) result_value=cur.fetchall() if result_value: account_id=result_value[0][0] cur.execute('''INSERT INTO `retailbanking`.`account` (`ws_cust_id` ,`ws_acct_id` ,`ws_acct_type` ,`ws_acct_balance` ,`ws_acct_crdate` ) VALUES (%s, %s, %s, %s, %s)''',(id,account_id,a_type,balance,today,)) mysql.connection.commit() message="Account created" return render_template('create_account.html',message=message) @app.route('/delete_account') def delete_account(): if session=={}: return redirect(url_for('login')) cur = mysql.connection.cursor() resultValue = cur.execute("SELECT * FROM account") if resultValue > 0: userDetails = cur.fetchall() return render_template('delete_account.html',accountDetails=userDetails) @app.route('/delete_a', methods=['post', 'get']) def delete_a(): if session=={}: return redirect(url_for('login')) account_id=int(request.form.get('account_id')) account_type=request.form.get('account_type') cur = mysql.connection.cursor() cur.execute('''select * from account where ws_acct_type= %s && ws_acct_id= %s''',(account_type,account_id,)) result_value=cur.fetchall() print(result_value) if result_value: cur.execute('''delete from account where ws_acct_id= %s''',(account_id,)) mysql.connection.commit() return redirect(url_for('delete_account')) #For Cashier @app.route('/account_details') def account_details(): if session=={}: return redirect(url_for('login')) return render_template('account_details.html') @app.route('/account_details') def account_details(): if session=={}: return redirect(url_for('login')) cur = mysql.connection.cursor() resultValue = cur.execute("SELECT * FROM account") if resultValue > 0: userDetails = cur.fetchall() return render_template('account_holders.html',userDetails=userDetails) @app.route('/deposit_amount', methods=['post', 'get']) def deposit_amount(): if session=={}: return redirect(url_for('login')) id=request.form.get('id') print(id) cur = mysql.connection.cursor() resultValue = cur.execute("select * from account where ws_cust_id = %s",(id,)) if resultValue > 0: users = cur.fetchall() return render_template('deposit_money.html',user=users) @app.route('/deposit',methods=['post','get']) def deposit(): if session=={}: return redirect(url_for('login')) message="" id=int(request.form.get('id')) amount=int(request.form.get('deposit')) cur = mysql.connection.cursor() cur.execute("update account set ws_acct_balance=ws_acct_balance+cast(%s as decimal(16,2)) where ws_cust_id= %s",(amount,id,)) mysql.connection.commit() resultValue = cur.execute("select * from account where ws_cust_id = %s",(id,)) if resultValue > 0: userDetails = cur.fetchall() message="Amount deposited successfully" today = date.today() a_type=userDetails[0][2] balance=int(request.form.get('deposit')) cur.execute('''INSERT INTO `retailbanking`.`transactions` (`ws_cust_id` ,`ws_accnt_type` ,`ws_amt` ,`ws_trxn_date` ,`ws_src_typ` ,`ws_tgt_typ`)VALUES (%s, %s, %s, %s , %s , %s);''',(id,a_type,balance,today,a_type,a_type)) mysql.connection.commit() return render_template('deposit_money.html',user=userDetails,message=message) #for transfer @app.route("/transfer", methods=['post', 'get']) def transfer(): if session=={}: return redirect(url_for('login')) return render_template("transfer_money.html") @app.route("/transfer_amount", methods=['post', 'get']) def transfer_amount(): if session=={}: return redirect(url_for('login')) cust_id=int(request.form.get('id')) print(cust_id) tran_id=int(request.form.get('transfer_id')) amount=int(request.form.get('transfer')) cur = mysql.connection.cursor() result=cur.execute('''select * from account where ws_cust_id= %s''',(cust_id,)) cust=cur.fetchall() result1=cur.execute('''select * from account where ws_cust_id= %s''',(tran_id,)) trans=cur.fetchall() today = date.today() if result > 0: if result1 > 0: cust_after=cust[0][3]-amount print(trans) trans_after=trans[0][3]+amount cur.execute('''update account set ws_acct_balance=%s where ws_cust_id=%s''',(cust_after,cust_id,)) mysql.connection.commit() cur.execute('''update account set ws_acct_balance=%s where ws_cust_id=%s''',(trans_after,tran_id,)) mysql.connection.commit() type1=cust[0][2] cur.execute('''INSERT INTO `retailbanking`.`transactions` (`ws_cust_id` ,`ws_accnt_type` ,`ws_amt` ,`ws_trxn_date` ,`ws_src_typ` ,`ws_tgt_typ`)VALUES (%s, %s, %s, %s , %s , %s);''',(cust_id,type1,amount,today,type1,type1)) mysql.connection.commit() type2=trans[0][2] cur.execute('''INSERT INTO `retailbanking`.`transactions` (`ws_cust_id` ,`ws_accnt_type` ,`ws_amt` ,`ws_trxn_date` ,`ws_src_typ` ,`ws_tgt_typ`)VALUES (%s, %s, %s, %s , %s , %s);''',(tran_id,type2,amount,today,type2,type2)) mysql.connection.commit() message="Amount transfer completed successfully" return render_template('transfer_Details.html',message=message,cust=cust,trans=trans,cust_after=cust_after,trans_after=trans_after) else: message="Enter correct Target ID" else: message="Enter correct Customer ID" return render_template("transfer_money.html",message=message) #for logout @app.route('/logout',methods=['post','get']) def logout(): if session=={}: return redirect(url_for('login')) session.pop('username', None) print(session) return redirect(url_for('login')) #for customer search @app.route('/csearch',methods=['post','get']) def csearch(): return render_template('customer_search.html') @app.route('/customersearch',methods=['post','get']) def customersearch(): cust_id=request.form.get('cust-id') ssn_id=request.form.get('ssn-id') cur = mysql.connection.cursor() result=cur.execute('''select * from customer where ws_cust_id= %s or ws_ssn=%s''',(cust_id,ssn_id)) if result>0: sample=cur.fetchall() return render_template('customer_detail.html',sample=sample)
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test/sortByMostFrequent.py
rootadminWalker/SearchByObjects
0
161873
<filename>test/sortByMostFrequent.py #!/usr/bin/env python3 from os import path, listdir import cv2 as cv from operator import itemgetter from core.Detection import YOLOPreprocessWithTarget, YOLODetect, yoloIMG from core.basePaths import basePaths from core.settings import Settings from time import time # Initialize start time start = time() # Initialize variables yolo = YOLODetect( model_path=basePaths( '../models/yolov3_416.h5' ).joinBase(), anchors_path=basePaths( '../models/yolo_anchors.txt' ).joinBase(), classes_path=basePaths( '../models/coco_classes.txt' ).joinBase() ) target = 'cow' videos = basePaths( '../static/videos' ).joinBase() _targetCount = 0 _allCounts = {} # You can set how much themes will the program # Jump to predict. More themes jumped will resulting # In a faster program and fewer themes jumped will be Slow # # Total frames you wanna jump = total seconds * fps _jumpThemes = 500 # Start looping with all videos for video in listdir(videos): boxes = {} video_name = path.join(videos, video) # Read the video video = cv.VideoCapture(video_name) # Configure the settings settings = Settings(video) start_predict = 0 while True: ret, frame = video.read() if not ret: continue # We'll jump n themes before we predict # In this case, we jumped 100 themes if start_predict % _jumpThemes == 0: frame = yoloIMG(frame).preprocess_to() # Preprocess the frame into PIL format frame, box_count, predicted_classes = yolo.detect(frame) # Predict our frame frame = yoloIMG(frame).rollback() # Rollback our theme # Get duration in H:M:S format duration = settings.get_current_SEC() settings.format_to_HMS(duration) duration = settings.duration # Process our output with target counting result = YOLOPreprocessWithTarget( [predicted_classes, box_count], duration, target ).process_outputs() targetCount = result[duration]['target'] print(video_name + ":", duration, predicted_classes, box_count, targetCount, end='\r') _targetCount += targetCount start_predict += 1 # Check if we have to stop if settings.get_fps() * settings.get_current_SEC() == settings.get_frames_count(): break _allCounts[video_name] = _targetCount # Sort our targets from largest to smallest _allCounts = sorted(_allCounts.items(), key=itemgetter(1), reverse=True) _allCounts = dict((key, value) for key, value in _allCounts) print(_allCounts) # Initialize end time end = time() print("Program runtime: {}".format( round( end - start, 5 ) ))
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1642, 4830, 29898, 13, 1678, 4513, 29898, 13, 4706, 1095, 448, 1369, 29892, 29871, 29945, 13, 1678, 1723, 13, 876, 13, 2 ]
Find Minimum in Rotated Array.py
lisnb/leetcode
2
164703
<reponame>lisnb/leetcode #!/usr/bin/env python # -*- coding: utf-8 -*- # @Author: LiSnB # @Date: 2015-01-09 11:01:40 # @Last Modified by: LiSnB # @Last Modified time: 2015-01-09 11:21:54 # @Email: <EMAIL> """ # @comment here: """ class Solution: # @param num, a list of integer # @return an integer def findMin(self, num): print num if not len(num): return None l = len(num) if l<=2: return min(num) pivot = l/2 print pivot if num[0]<num[-1]: return num[0] if num[pivot]<num[pivot-1] and num[pivot]<num[pivot+1]: return num[pivot] # if num[0]<num[pivot-1] and num[pivot+1]<num[-1]: # return num[pivot] if num[pivot]<num[pivot+1] else num[pivot+1] else: if num[0]>num[pivot-1]: return self.findMin(num[0:pivot]) else: return self.findMin(num[pivot+1:]) if __name__ == '__main__': s=Solution() num = [3,3,3,3,3,3,4,4,4,4,4,4,6,6,6,6,6,6,6,6,1,1,1,1,2] num2 = [0,0,0] print s.findMin(num2)
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openstack_dashboard/test/integration_tests/steps.py
Mirantis/mos-horizon
9
26888
# 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 logging from openstack_dashboard.test.integration_tests.pages import loginpage from openstack_dashboard.test.integration_tests.regions import messages LOGGER = logging.getLogger(__name__) def login(test_case): test_case.login_pg = loginpage.LoginPage(test_case.driver, test_case.CONFIG) test_case.login_pg.go_to_login_page() test_case.create_demo_user() test_case.home_pg = test_case.login_pg.login(test_case.TEST_USER_NAME, test_case.TEST_PASSWORD) test_case.home_pg.change_project(test_case.HOME_PROJECT) test_case.assertTrue( test_case.home_pg.find_message_and_dismiss(messages.SUCCESS)) test_case.assertFalse( test_case.home_pg.find_message_and_dismiss(messages.ERROR)) yield if test_case.home_pg.is_logged_in: test_case.home_pg.log_out() else: LOGGER.warn("{!r} isn't logged in".format(test_case.TEST_USER_NAME))
[ 1, 396, 1678, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 366, 1122, 13, 29937, 1678, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 887, 1122, 4017, 13, 29937, 1678, 263, 3509, 310, 278, 19245, 472, 13, 29937, 13, 29937, 308, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 13, 29937, 1678, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 1678, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 399, 1806, 8187, 2692, 13, 29937, 1678, 399, 1718, 29934, 13566, 29059, 6323, 8707, 29928, 22122, 29903, 8079, 13764, 29979, 476, 22255, 29892, 2845, 4653, 470, 2411, 2957, 29889, 2823, 278, 13, 29937, 1678, 19245, 363, 278, 2702, 4086, 14765, 1076, 11239, 322, 27028, 13, 29937, 1678, 1090, 278, 19245, 29889, 13, 13, 5215, 12183, 13, 13, 3166, 1722, 1429, 29918, 14592, 3377, 29889, 1688, 29889, 27925, 29918, 21150, 29889, 12292, 1053, 6464, 3488, 13, 3166, 1722, 1429, 29918, 14592, 3377, 29889, 1688, 29889, 27925, 29918, 21150, 29889, 1727, 1080, 1053, 7191, 13, 13, 14480, 17070, 353, 12183, 29889, 657, 16363, 22168, 978, 1649, 29897, 13, 13, 13, 1753, 6464, 29898, 1688, 29918, 4878, 1125, 13, 1678, 1243, 29918, 4878, 29889, 7507, 29918, 4061, 353, 6464, 3488, 29889, 11049, 5074, 29898, 1688, 29918, 4878, 29889, 9465, 29892, 13, 462, 462, 632, 1243, 29918, 4878, 29889, 25903, 29897, 13, 1678, 1243, 29918, 4878, 29889, 7507, 29918, 4061, 29889, 1484, 29918, 517, 29918, 7507, 29918, 3488, 580, 13, 13, 1678, 1243, 29918, 4878, 29889, 3258, 29918, 17482, 29918, 1792, 580, 13, 13, 1678, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 353, 1243, 29918, 4878, 29889, 7507, 29918, 4061, 29889, 7507, 29898, 1688, 29918, 4878, 29889, 18267, 29918, 11889, 29918, 5813, 29892, 13, 462, 462, 462, 1243, 29918, 4878, 29889, 18267, 29918, 25711, 17013, 29897, 13, 1678, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 29889, 3167, 29918, 4836, 29898, 1688, 29918, 4878, 29889, 17353, 29918, 8618, 17637, 29897, 13, 1678, 1243, 29918, 4878, 29889, 9294, 5574, 29898, 13, 4706, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 29889, 2886, 29918, 4906, 29918, 392, 29918, 29881, 28303, 29898, 19158, 29889, 14605, 26925, 876, 13, 1678, 1243, 29918, 4878, 29889, 9294, 8824, 29898, 13, 4706, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 29889, 2886, 29918, 4906, 29918, 392, 29918, 29881, 28303, 29898, 19158, 29889, 11432, 876, 13, 13, 1678, 7709, 13, 13, 1678, 565, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 29889, 275, 29918, 1188, 3192, 29918, 262, 29901, 13, 4706, 1243, 29918, 4878, 29889, 5184, 29918, 4061, 29889, 1188, 29918, 449, 580, 13, 1678, 1683, 29901, 13, 4706, 25401, 17070, 29889, 25442, 703, 29912, 29991, 29878, 29913, 3508, 29915, 29873, 13817, 297, 1642, 4830, 29898, 1688, 29918, 4878, 29889, 18267, 29918, 11889, 29918, 5813, 876, 13, 2 ]
python_tamer/SpecificDoses.py
tch521/python-TAMER
0
110206
import pandas as pd import numpy as np import netCDF4 as nc from .subroutines import * class SpecificDoses(pd.DataFrame): """A class for specific dose estimates akin to dosimetry measurements High resolution data allows for personal and ambient dose estimation without the need for direct measurement. This class is structured like a table with a set of functions to add columns ultimately leading to dose estimates. Each row of this table represents a specific exposure instance, i.e. an individual at a specific location for a specific date and time with a specific exposure ratio. See Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) for more information on calculations appropriate for this class. Parameters ---------- src_filename_format : str Describes the filename of the netCDF files containing the UV data with 'yyyy' in place of the year. src_directory : str The directory where the data is stored. Must end with a slash. Notes ----- Presently, the class is inherited from a pandas.DataFrame which is somewhat restrictive and will likely be revised in a later update. For the time being, this means that the parameters cannot be set when initialising a `SpecificDoses` object, they must instead be adjusted after initialisation, like so:: ExistingExposureMapObject.src_directory = "/new/data/directory/" Example ------- In this example, we illustrate the process for calculating the doses in Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) from the spreadsheet supplied as supplementary data (https://www.mdpi.com/2073-4433/12/2/268/s1). Note that results will differ as the spreadsheet contains only local Swiss time and not UTC time. There are four important functions as part of this class, three for standardising and preparing the columns, and one for actually loading the data and performing the dose calculations. See below:: import python_tamer as pt import pandas as pd example = pt.SpecificDoses(pd.read_excel(r'atmosphere-12-00268-s001.xlsx', header=2,index_col=0,usecols="B:K")) example.src_directory = 'C:/enter_the_directory_of_your_dataset_here' example = example.standard_column_names() example = example.schedule_constant_exposure().ER_from_posture() example = example.calculate_specific_dose() """ # This property ensures that functions return the same subclass @property def _constructor(self): return SpecificDoses # This adds some useful metadata (self-explanatory) _metadata = ["src_filename_format","src_directory"] src_filename_format = 'UVery.AS_ch02.lonlat_yyyy01010000.nc' src_directory = 'C:/Data/UV/' # TODO: set up __init__ for these options # It feels like this should be declared with __init__ as well but idk def standard_column_names(self) : """Limited function to standardise column names When loading tables to use as the basis for a SpecificDoses table, some columns may have slightly names to what is expected. This function standardises the names but is very limited in terms of what it can recognise. The user is encourages to ensure the columns are correctly labelled themselves and not to rely on this function. Returns ------- SpecificDoses The table has its column names modified. """ legend_dict_reverse = {'Point' : ['Lieu de mesure'], 'Date' : ['Date'], 'Time_start' : ['Heure début','Start_time','Start time'], 'Time_end' : ['Heure fin','End_time','End time'], 'Measured_dose' : ['Exposition [MED]','Exposure'], 'Anatomic_zone' : ['Zone anatomique','Body part','Anatomic zone'], 'Posture' : ['Body posture'], 'Latitude' : ['lat'], 'Longitude' : ['lon','lng']} legend_dict = {keys: old_keys for old_keys, old_values in legend_dict_reverse.items() for keys in old_values} self = self.rename(columns=legend_dict) return self def schedule_constant_exposure(self) : """Generates exposure schedules given start and end times. This function generates exposure schedules based on simple continuous exposure, i.e. with a start time and an end time. The exposure schedule is a vector with length 24 with each entry representing the proportion of the corresponding hour of the day that the subject is exposed. Returns ------- python_tamer.SpecificDoses An exposure_schedule column is created and is appended to the input `SpecificDoses` object or, if that column already exists, it is overwritten. Notes ----- The input `SpecificDoses` object must contain the following columns: * ``Time_start`` * ``Time_end`` Example ------- In this example, we illustrate the process for calculating the doses in Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) from the spreadsheet supplied as supplementary data (https://www.mdpi.com/2073-4433/12/2/268/s1). Note that results will differ as the spreadsheet contains only local Swiss time and not UTC time. There are four important functions as part of this class, three for standardising and preparing the columns, and one for actually loading the data and performing the dose calculations. See below:: import python_tamer as pt import pandas as pd example = pt.SpecificDoses(pd.read_excel(r'atmosphere-12-00268-s001.xlsx', header=2,index_col=0,usecols="B:K")) example.src_directory = 'C:/enter_the_directory_of_your_dataset_here' example = example.standard_column_names() example = example.schedule_constant_exposure().ER_from_posture() example = example.calculate_specific_dose() """ def schedule_constant_exposure_iter(Start_time,End_time) : """Iterates through rows of a SpecificDoses table to generate schedules. This function is designed to be applied to each row in a datatable to generate an exposure schedule based on a start time and end time Parameters ---------- Start_time : datetime.time UTC time at which exposure period begins End_time : datetime.time UTC time at which exposure period end Returns ------- numpy.array 24 length vector of values between 0 and 1 indicating proportion of time exposed for that corresponding hour of the day. """ schedule = np.zeros(24) schedule[Start_time.hour:End_time.hour] = 1 # Modify start and end hours according to proportion of time exposed if Start_time.minute != 0 : schedule[Start_time.hour] = (1 - Start_time.minute/60) if End_time.minute != 0 : schedule[End_time.hour] = End_time.minute/60 return schedule # With that function defined, we need just one line to apply it to the whole table self["Schedule"] = self.apply(lambda x: schedule_constant_exposure_iter( x["Time_start"],x["Time_end"]),axis='columns') return self def ER_from_posture(self, Vis_table_path=None, Vis_table=None) : """ER_from_posture calculates Exposure Ratios for a given anatomic zone, posture, and date. This function calculates ER as a percentage between 0 and 100 based on information from an input table. The input table must contain certain columns at a minimum. Those are: Date, Anatomic_zone, and Posture. This function contains hard-coded synonyms for certain anatomical zones, e.g. 'Forehead" maps to "Face'. See Vernez et al., Journal of Exposure Science and Environmental Epidemiology (2015) 25, 113–118 (https://doi.org/10.1038/jes.2014.6) for further details on the model used for the calculation. Parameters ---------- Vis_table_path : str, optional The full path to an alternative table for the Vis parameter. Must be a csv file. Defaults to None. Vis_table : str, optional An alternative table for the Vis parameter. Defaults to None. Returns ------- SpecificDoses Returns input table appended with ER column Notes ----- The SpecificDoses table used must contain columns for Date, Anatomic_zone, and Posture. The Date column should contain DateTime entries. The Anatonic_zone column should contain one string per row describing the exposed body part. The Posture column should contain one string per row describing one of six accepted postures. Example ------- In this example, we illustrate the process for calculating the doses in Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) from the spreadsheet supplied as supplementary data (https://www.mdpi.com/2073-4433/12/2/268/s1). Note that results will differ as the spreadsheet contains only local Swiss time and not UTC time. There are four important functions as part of this class, three for standardising and preparing the columns, and one for actually loading the data and performing the dose calculations. See below:: import python_tamer as pt import pandas as pd example = pt.SpecificDoses(pd.read_excel(r'atmosphere-12-00268-s001.xlsx', header=2,index_col=0,usecols="B:K")) example.src_directory = 'C:/enter_the_directory_of_your_dataset_here' example = example.standard_column_names() example = example.schedule_constant_exposure().ER_from_posture() example = example.calculate_specific_dose() """ # This chunk of code checks if the default Vis table should be used or if the user enters some alternative table. if Vis_table is None and Vis_table_path is None : Vis_table = pd.DataFrame.from_records( columns=['Seated','Kneeling','Standing erect arms down','Standing erect arms up','Standing bowing'], index=['Face','Skull','Forearm','Upper arm','Neck','Top of shoulders','Belly','Upper back','Hand','Shoulder','Upper leg','Lower leg','Lower back'], data=[[53.7,28.7,46.6,44.9,19.2], [56.2,66.6,61.1,58.4,67.5], [62.3,56.5,49.4,53.1,62.1], [51.7,60.5,45.9,65.3,61.6], [58.3,84.3,67.6,65.2,81.6], [35.9,50.3,48.6,45.7,85.3], [58.1,45.1,50.3,49.6,15.2], [35.9,50.3,48.6,45.7,85.3], [59.2,58.8,42.4,55,58.5], [68,62,63,67.1,64], [65.4,45.4,50.9,51,43.5], [32.8,63.4,49.7,50.3,50], [44.9,51.6,56.6,53.4,86.9]]) # The 'standing moving' posture must be dealt with somehow... # Vis_table['Standing moving']= (Vis_table['Standing erect arms down'] + Vis_table['Standing bowing']) / 2 # TODO: add interpeter or force users to conform? Vis_table['Standing moving']= Vis_table['Standing erect arms down'] elif Vis_table is None : Vis_table = pd.read_csv(Vis_table_path) # Below is a dictionary describing a range of synonyms for the anatomical zones defined in the Vis table. Anatomic_zone_synonyms_reverse = { 'Forearm' : ['wrist', 'Left extern radial', 'Right extern radial', 'Left wrist: radius head', 'Right wrist: radius head', 'Left wrist', 'Right wrist'], 'Face' : ['Forehead'], 'Upper back' : ['Right trapezoid', 'Left trapezoid', 'trapezius'], 'Belly' : ['Chest'], 'Shoulder' : ['Left deltoid', 'Right deltoid', 'Left shoulder', 'Right shoulder'], 'Upper arm' : ['Left elbow', 'Right elbow', 'Left biceps', 'Right biceps'], 'Upper leg' : ['Left thigh', 'Right thigh', 'Left knee', 'Right knee'], 'Lower back' : ['Low back'] } # The dictionary is reversed so that the multiple synonyms can be mapped to the few correct terms for the Vis table. Anatomic_zone_synonyms = {keys: old_keys for old_keys, old_values in Anatomic_zone_synonyms_reverse.items() for keys in old_values} self = self.replace({'Anatomic_zone' : Anatomic_zone_synonyms}) # With the correct anatomic zone names established, we can lookup the Vis values from the table # TODO: lookup is being depreciated, must replace with something new Vis = Vis_table.lookup(self['Anatomic_zone'],self['Posture']) # Next we must calculate the minimal Solar Zenith Angle for the given date mSZA = min_solar_zenith_angle(self.Date,self.Latitude) # With the Vis value and the SZA, we can calculate the ER according to the Vernez model self.loc[:,'ER'] = ER_Vernez_model_equation(Vis,mSZA) / 100 return self def calculate_specific_dose(self) : """Calculates doses according to exposure schedule, ER, date, and location. This function takes the SpecificDoseEstimationTable and calculates the specific ambient and personal doses according to the exposure schedule and ER. There are a few key steps to this function. First it reads the Date column to determine which years of data must be loaded. It then iterates through each year, loading only the necessary dates. It applies the exposure schedule and the ER to calculate the ambient and personal doses. Returns ------- SpecificDoses The input table is appended with a Ambient_dose and Personal_dose column. Notes ----- The input SpecificDoses object must include Date, Schedule, ER, Latitude, and Longitude columns. Consult Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) for more information on how this function can be used in the context of mimicking UV dosimetry measurements. Example ------- In this example, we illustrate the process for calculating the doses in Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) from the spreadsheet supplied as supplementary data (https://www.mdpi.com/2073-4433/12/2/268/s1). Note that results will differ as the spreadsheet contains only local Swiss time and not UTC time. There are four important functions as part of this class, three for standardising and preparing the columns, and one for actually loading the data and performing the dose calculations. See below:: import python_tamer as pt import pandas as pd example = pt.SpecificDoses(pd.read_excel(r'atmosphere-12-00268-s001.xlsx', header=2,index_col=0,usecols="B:K")) example.src_directory = 'C:/enter_the_directory_of_your_dataset_here' example = example.standard_column_names() example = example.schedule_constant_exposure().ER_from_posture() example = example.calculate_specific_dose() """ # First step is find unique years to avoid loading unnecessary data years = pd.DatetimeIndex(self.Date).year unique_years = sorted(set(years)) self['Ambient_dose'] = np.nan self['Personal_dose'] = np.nan for year in unique_years : # Load netCDF file print("Processing year "+str(year)) dataset=nc.Dataset(self.src_directory+self.src_filename_format.replace('yyyy',str(year))) dataset.set_auto_mask(False) # This is important for nans to import correctly # Make temporary table for yearly subset temp_table = self[years == year].copy() # find all unique days in year to be loaded unique_days,unique_days_idx = np.unique(pd.DatetimeIndex(temp_table.Date).dayofyear, return_inverse=True) temp_table['unique_days_idx'] = unique_days_idx #pd.DatetimeIndex(nc.num2date(dataset.variables["time"][:],dataset.variables["time"].units,only_use_cftime_datetimes=False)) if dataset.dimensions['time'].size == 24 : # needed if just a single day time_subset = [True for i in range(dataset.dimensions['time'].size)] else : # Next we pull a subset from the netCDF file # declare false array with same length of time dimension from netCDF time_subset = [False for i in range(dataset.dimensions['time'].size)] # reshape false array to have first dimension 24 (hours in day) time_subset = assert_data_shape_24(time_subset) # set the appropriate days as true time_subset[:,unique_days-1] = True # flatten time_subset array back to one dimension time_subset = time_subset.flatten(order='F') data = assert_data_shape_24(dataset['UV_AS'][time_subset,:,:]) # TODO: improve comprehension of raw data units rather than assuming # convert lat lon into pixel coordinates # TODO: consider is necessary to load entire maps for just a few required pixels lat = dataset['lat'][:] lon = dataset['lon'][:] temp_table['pixel_lat'] = temp_table.apply(lambda x: find_nearest(lat,x['Latitude']),axis='columns') temp_table['pixel_lon'] = temp_table.apply(lambda x: find_nearest(lon,x['Longitude']),axis='columns') # calculate doses temp_table['Ambient_dose'] = temp_table.apply(lambda x: np.sum(data[:,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] * x['Schedule']),axis='columns') temp_table['Personal_dose'] = temp_table.apply(lambda x: np.sum(data[:,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] * (x['Schedule'] * x['ER'])),axis='columns') # extra step necessary to ensure correct assignment self.loc[temp_table.index,'Ambient_dose'] = temp_table['Ambient_dose'].values self.loc[temp_table.index,'Personal_dose'] = temp_table['Personal_dose'].values # TODO: improve units options here self['Ambient_dose'] = self['Ambient_dose']/40*3600/100 # SED self['Personal_dose'] = self['Personal_dose']/40*3600/100 # SED return self def analyse_variable(self, variable="UV_AS", statistic="Mean", src_filename_format=None, src_directory=None) : """Basic calculations for specific exposure instances This function is for calculating information other than ambient and personal doses that corresponds to specific exposure instances. Parameters ---------- variable : str, optional The name of the variable to be analysed. This informs what data should be pulled from the source netCDF files. This also informs the name of the column(s) that will be created by this function. Defaults to "UV_AS", i.e. the All-Sky UV data that is used in the calculate_specific_dose function. statistic : str or list, optional The statistic to be calculated, options include: mean, median, stdev, variance, min, max, weighted_mean, and sum. Not case sensitive. Can be a single string or a list of strings whereby multiple columns will be calculated. Defaults to "Mean". src_filename_format : str, optional Allows the user to select different source data. This may be useful in cases where the user wants to compare doses calculated with one dataset to (say) cloud cover from another dataset. Defaults to None, where the function uses the source files specified by the object's metadata. src_directory : str, optional Allows the user to select different source data. This may be useful in cases where the user wants to compare doses calculated with one dataset to (say) cloud cover from another dataset. Defaults to None, where the function uses the source files specified by the object's metadata. Returns ------- SpecificDoses The table is appended with new columns named [variable]_[statistic]. Example ------- In this example, we illustrate the process for calculating the doses in Harris et al. 2021 (https://doi.org/10.3390/atmos12020268) from the spreadsheet supplied as supplementary data (https://www.mdpi.com/2073-4433/12/2/268/s1). Note that results will differ as the spreadsheet contains only local Swiss time and not UTC time. Additionally, to demonstrate the analyse_variable function, we also calculate the weighted mean CMF assuming it to be an additional variable in the source data files. See below:: import python_tamer as pt import pandas as pd example = pt.SpecificDoses(pd.read_excel(r'atmosphere-12-00268-s001.xlsx', header=2,index_col=0,usecols="B:K")) example.src_directory = 'C:/enter_the_directory_of_your_dataset_here' example = example.standard_column_names() example = example.schedule_constant_exposure().ER_from_posture() example = example.calculate_specific_dose() example = example.analyse_variable(variable="CMF",statistic="weighted_mean") """ # users have option to load different files, otherwise defaults to metadata if src_filename_format is None : src_filename_format = self.src_filename_format if src_directory is None : src_directory = self.src_directory # First step is find unique years to avoid loading unnecessary data years = pd.DatetimeIndex(self.Date).year unique_years = sorted(set(years)) if isinstance(statistic,str) : self[variable+"_"+statistic] = np.nan # convert to list to simplify code later statistic = [statistic] elif isinstance(statistic,list) : for x in statistic : self[variable+"_"+x]=np.nan else : raise TypeError("statistic input must be str or list of str") for year in unique_years : # Load netCDF file print("Processing year "+str(year)) dataset=nc.Dataset(src_directory+src_filename_format.replace('yyyy',str(year))) dataset.set_auto_mask(False) # This is important for nans to import correctly # Make temporary table for yearly subset temp_table = self[years == year].copy() # find all unique days in year to be loaded unique_days,unique_days_idx = np.unique(pd.DatetimeIndex(temp_table.Date).dayofyear, return_inverse=True) temp_table['unique_days_idx'] = unique_days_idx #pd.DatetimeIndex(nc.num2date(dataset.variables["time"][:],dataset.variables["time"].units,only_use_cftime_datetimes=False)) if dataset.dimensions['time'].size == 24 : # needed if just a single day time_subset = [True for i in range(dataset.dimensions['time'].size)] else : # Next we pull a subset from the netCDF file # declare false array with same length of time dimension from netCDF time_subset = [False for i in range(dataset.dimensions['time'].size)] # reshape false array to have first dimension 24 (hours in day) time_subset = assert_data_shape_24(time_subset) # set the appropriate days as true time_subset[:,unique_days-1] = True # flatten time_subset array back to one dimension time_subset = time_subset.flatten(order='F') data = assert_data_shape_24(dataset[variable][time_subset,:,:]) # TODO: improve comprehension of raw data units rather than assuming # convert lat lon into pixel coordinates # TODO: consider is necessary to load entire maps for just a few required pixels lat = dataset['lat'][:] lon = dataset['lon'][:] temp_table['pixel_lat'] = temp_table.apply(lambda x: find_nearest(lat,x['Latitude']),axis='columns') temp_table['pixel_lon'] = temp_table.apply(lambda x: find_nearest(lon,x['Longitude']),axis='columns') # calculate for stat in statistic : # mean if stat.lower() in ["mean",'average','avg'] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.mean(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # median elif stat.lower() in ["median","med"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.median(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # stdev elif stat.lower() in ["std","sd","stdev"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.std(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # variance elif stat.lower() in ["var","variance"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.var(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # minimum elif stat.lower() in ["min",'minimum'] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.amin(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # maximum elif stat.lower() in ["max","maximum"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.amax(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # weighted mean elif stat.lower() in ["weighted_mean","weighted_average","mean_weighted","average_weighted","avg_weighted"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.average(data[:,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']],weights=x['Schedule']),axis='columns') # sum elif stat.lower() in ["sum","total"] : temp_table[variable+"_"+stat] = temp_table.apply(lambda x: np.sum(data[x['Schedule']!=0,x['unique_days_idx'],x['pixel_lat'],x['pixel_lon']] ),axis='columns') # extra step necessary to ensure correct assignment self.loc[temp_table.index,variable+"_"+stat] = temp_table[variable+"_"+stat].values return self
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fabfile.py
codersquid/richard-deploy
0
167972
<filename>fabfile.py """deployment scripts for researchcompendia with credit to scipy-2014 and researchcompendia fabric.py fab <deploy|provision>[:<git ref>] provision: provisions a box to run the site. is not idempotent. do not rerun. deploy: deploys a update to the site. if no git ref is provided, deploys HEAD. git ref: a git branch, hash, tag provision: provisions a new box. example usages: deploy new version of the site with an updated virtualenv. $ fab provision:1.1.1 WARNINGS This does not set up elasticsearch or the cron jobs for indexing and running the link checker. deploy has never been properly tested provision is no longer properly tested, Carl wanted an vagrant example and I don't have time to finish this today. It's a start for him to pick up, unless I get to it first. """ import string, random from os.path import join, dirname, abspath from fabric.api import run, task, env, cd, sudo, local from fabric.contrib.files import sed, append from fabtools import require, supervisor, postgres, files from fabtools.files import upload_template import fabtools from fabtools.vagrant import vagrant FAB_HOME = dirname(abspath(__file__)) TEMPLATE_DIR = join(FAB_HOME, 'templates') # shourt name - user, group, db name, supervised_process... SITE_NAME = "rt1" # public facing name (connonical? fqdn?) SERVER_NAME='richard.test1.nextdayvideo.com' try: from secrets import admins except: # you will need to run ./manage.py createsuperuser admins = [] SITE_CLONE_NAME = SITE_NAME SITE_DIR = join('/', 'srv', SITE_NAME) SITE_SETTINGS = { 'site_name': SITE_NAME, 'repo_dir': join(SITE_DIR, SITE_NAME), 'setup_args': '.[postgresql]', 'django_site_url': 'http://{0}'.format(SERVER_NAME), 'repo': 'https://github.com/willkg/richard.git', 'user': SITE_NAME, 'group': SITE_NAME, 'virtualenv': 'venv', 'supervised_process': SITE_NAME, 'settings_module': '{0}.richard.settings'.format(SITE_NAME) , 'wsgi_module': '{0}.richard.wsgi'.format(SITE_NAME), 'server_name': SERVER_NAME, 'nginx_site': SITE_NAME, 'gunicorn_port':'8001', 'admins':admins } env.disable_known_hosts = True env.hosts = ['root@'+SERVER_NAME] # env.hosts = [SERVER_NAME+':2222'] #env.hosts = ['127.0.0.1:2222'] #env.hosts = ['<EMAIL>'] @task def uname(): """call uname to check that we can do a simple command """ run('uname -a') @task def deploy(version_tag=None): """deploys a updated version of the site version_tag: a git tag, defaults to HEAD """ supervised_process = SITE_SETTINGS['supervised_process'] #dust() stop(supervised_process) update(commit=version_tag) setup() collectstatic() start(supervised_process) #undust() @task def stop(process_name): """stops supervisor process """ supervisor.stop_process(process_name) @task def start(process_name): """starts supervisor process """ supervisor.start_process(process_name) @task def update(commit='origin/master'): repo_dir = SITE_SETTINGS['repo_dir'] with cd(repo_dir): su('git fetch') su('git checkout %s' % commit) @task def migrate(app): """ run south migration on specified app """ with cd(SITE_SETTINGS['repo_dir']): vsu('./manage.py migrate %s' % app) @task def provision(commit='origin/master'): """Run only once to provision a new host. This is not idempotent. Only run once! """ install_packages() install_python_packages() lockdown_nginx() # lockdown_ssh() # locks you out if you don't have keys setup setup_database() setup_site_user() setup_site_root() provision_django() provision_django_settings() syncdb() create_superuser() collectstatic() setup_nginx_site() setup_supervisor() print("") print('handy debugging stuff:') print('127.0.0.1 localhost {server_name}'.format( **SITE_SETTINGS)) print('curl http://{server_name}:8081'.format( **SITE_SETTINGS)) # not the gunicorn_port. this is the port mapped to 80 by vagrant print('curl --head http://{server_name}:8081'.format( **SITE_SETTINGS)) print("sudo supervisorctl restart {0}".format(SITE_NAME)) print('cat {0}/logs/gunicorn.log'.format(SITE_DIR)) activate = join( SITE_DIR, SITE_SETTINGS['virtualenv'], 'bin', 'activate') print('cd {repo_dir}'.format(**SITE_SETTINGS)) print( 'sudo su {user} -c "source {activate} && ./manage.py shell"'.format(activate=activate, **SITE_SETTINGS)) def setup_nginx_site(): nginx_site = SITE_NAME static_dir = SITE_SETTINGS['repo_dir'] upload_template('nginx_site.conf', '/etc/nginx/sites-available/%s' % nginx_site, context={ 'server_name': SITE_SETTINGS['server_name'], 'gunicorn_port': SITE_SETTINGS['gunicorn_port'], 'path_to_static': join(static_dir, 'static'), 'site_dir': SITE_DIR, 'static_parent': '%s/' % static_dir, }, use_jinja=True, use_sudo=True, template_dir=TEMPLATE_DIR) require.nginx.enabled(nginx_site) def setup_supervisor(): supervised_process = SITE_SETTINGS['supervised_process'] bindir = join(SITE_DIR, 'bin') logdir = join(SITE_DIR, 'logs') upload_template('supervised_site.conf', '/etc/supervisor/conf.d/%s.conf' % supervised_process, context={ 'supervised_process': supervised_process, 'command': join(bindir, 'gunicorn.sh'), 'user': SITE_SETTINGS['user'], 'group': SITE_SETTINGS['group'], 'logfile': join(logdir, 'gunicorn.log'), 'site_dir': bindir, }, use_jinja=True, use_sudo=True, template_dir=TEMPLATE_DIR) supervisor.update_config() def lockdown_nginx(): # don't share nginx version in header and error pages sed('/etc/nginx/nginx.conf', '# server_tokens off;', 'server_tokens off;', use_sudo=True) sudo('service nginx restart') def lockdown_ssh(): sed('/etc/ssh/sshd_config', '^#PasswordAuthentication yes', 'PasswordAuthentication no', use_sudo=True) append('/etc/ssh/sshd_config', ['UseDNS no', 'PermitRootLogin no', 'DebianBanner no', 'TcpKeepAlive yes'], use_sudo=True) sudo('service ssh restart') def clone_site(): with cd(SITE_DIR): su('git clone -q %s %s' % (SITE_SETTINGS['repo'], SITE_CLONE_NAME)) with cd(join(SITE_DIR, SITE_CLONE_NAME)): su('touch __init__.py') # janky way to treat the SITE_CLONE_NAME like a module name def provision_django(): with cd(SITE_DIR): su('virtualenv {0}'.format(SITE_SETTINGS['virtualenv'])) clone_site() setup() @task def provision_django_settings(): settings_local = join(SITE_DIR, SITE_SETTINGS['repo_dir'], 'richard', 'settings_local.py') secret_key = ''.join(random.choice(string.ascii_letters + string.digits + '~@#%^&*-_') for x in range(64)) upload_template('settings_local.py', settings_local, context={ 'site_name': SITE_NAME, 'db_name': SITE_NAME, 'secret_key': secret_key, 'admins': SITE_SETTINGS['admins'], 'server_name': SITE_SETTINGS['server_name'], }, use_jinja=True, use_sudo=True, template_dir=TEMPLATE_DIR) sudo('chown {user}:{group} {file}'.format( file=settings_local, **SITE_SETTINGS )) def syncdb(): with cd(SITE_SETTINGS['repo_dir']): vsu('./manage.py syncdb --noinput --migrate') @task def create_superuser(): """ create admin user. richard uses Persona, which is tied to email. """ with cd(SITE_SETTINGS['repo_dir']): for user,email in SITE_SETTINGS['admins']: vsu('./manage.py createsuperuser --noinput --username {user} --email {email}'.format(user=user,email=email)) @task def setup(virtualenv='venv'): with cd(SITE_SETTINGS['repo_dir']): # TODO: figure out how to escape .[postgresql], I keep getting: invalid command name #vsu("python setup.py '%s'" % SITE_SETTINGS['setup_args'], virtualenv=virtualenv) vsu("python setup.py install", virtualenv=virtualenv) vsu("pip install gunicorn", virtualenv=virtualenv) vsu("pip install psycopg2", virtualenv=virtualenv) def setup_database(): user = SITE_SETTINGS['user'] require.postgres.server() # TODO: fabtools.require.postgres.user did not allow a user with no pw prompt? see if there is a better way if not postgres.user_exists(user): su('createuser -S -D -R -w %s' % user, 'postgres') if not postgres.database_exists(user): require.postgres.database(user, user, encoding='UTF8', locale='en_US.UTF-8') # TODO: change default port # port = 5432 # /etc/postgresql/9.1/main/postgresql.conf def setup_site_user(): user = SITE_SETTINGS['user'] if not fabtools.user.exists(user): sudo('useradd -s/bin/bash -d/home/%s -m %s' % (user, user)) def setup_site_root(): bindir = join(SITE_DIR, 'bin') user = SITE_SETTINGS['user'] sudo('mkdir -p %s' % SITE_DIR) sudo('chown %s:%s %s' % (user, user, SITE_DIR)) with cd(SITE_DIR): su('mkdir -p logs bin {0}'.format(SITE_SETTINGS['virtualenv'])) with cd(bindir): setup_gunicorn_script() sudo('chown -R %s:%s %s' % (user, user, SITE_DIR)) su('chmod +x gunicorn.sh') def setup_gunicorn_script(): bindir = join(SITE_DIR, 'bin') python_path = SITE_SETTINGS['repo_dir'] upload_template('gunicorn.sh', join(bindir, 'gunicorn.sh'), context={ 'settings_module': SITE_SETTINGS['settings_module'], 'path_to_virtualenv': join(SITE_DIR, SITE_SETTINGS['virtualenv']), 'user': SITE_SETTINGS['user'], 'group': SITE_SETTINGS['group'], 'site_dir': SITE_DIR, 'wsgi_module': SITE_SETTINGS['wsgi_module'], 'gunicorn_port': SITE_SETTINGS['gunicorn_port'], 'python_path': python_path, }, use_jinja=True, use_sudo=True, template_dir=TEMPLATE_DIR) def install_packages(): require.deb.uptodate_index(max_age={'hour': 1}) require.deb.packages([ 'python-software-properties', 'python-dev', 'build-essential', 'libxml2', 'libxslt-dev', 'git', 'nginx-extras', 'libxslt1-dev', 'supervisor', 'postgresql', 'postgresql-server-dev-9.1', # useful but not strictly required 'tig', 'vim', 'curl', 'tmux', 'htop', 'ack-grep', ]) def install_python_packages(): sudo('wget --quiet https://raw.github.com/pypa/pip/master/contrib/get-pip.py') sudo('python get-pip.py') # install global python packages require.python.packages([ 'virtualenvwrapper', 'setproctitle', 'wheel', ], use_sudo=True) def su(cmd, user=None): if user is None: user = SITE_SETTINGS['user'] sudo("su %s -c '%s'" % (user, cmd)) def vsu(cmd, virtualenv='venv', user=None): if user is None: user = SITE_SETTINGS['user'] activate = join(SITE_DIR, virtualenv, 'bin', 'activate') sudo("su {0} -c 'source {1}; {2}'".format(user, activate, cmd)) def collectstatic(): with cd(SITE_SETTINGS['repo_dir']): vsu('./manage.py collectstatic --noinput') def randomstring(n): return ''.join(random.choice(string.ascii_letters + string.digits + '~@#%^&*-_') for x in range(n))
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spec/__init__.py
deep-spin/spec-blackboxnlp
2
26623
<gh_stars>1-10 """ SpEC ~~~~~~~~~~~~~~~~~~~ Sparsity, Explainability, and Communication :copyright: (c) 2019 by <NAME> :licence: MIT, see LICENSE for more details """ # Generate your own AsciiArt at: # patorjk.com/software/taag/#f=Calvin%20S&t=SpEC __banner__ = """ _____ _____ _____ | __|___| __| | |__ | . | __| --| |_____| _|_____|_____| |_| """ __prog__ = "spec" __title__ = 'SpEC' __summary__ = 'Sparsity, Explainability, and Communication' __uri__ = 'https://github.com/mtreviso/spec' __version__ = '0.0.1' __author__ = '<NAME> and <NAME>' __email__ = '<EMAIL>' __license__ = 'MIT' __copyright__ = 'Copyright 2019 Marcos Treviso'
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httpd.py
bshah2016/web-processing
250
70335
#!/usr/bin/env python PORT = 9914 SERVER = '127.0.0.1' import SimpleHTTPServer import BaseHTTPServer import SocketServer Handler = SimpleHTTPServer.SimpleHTTPRequestHandler class Server(SocketServer.ThreadingMixIn, BaseHTTPServer.HTTPServer): pass httpd = Server((SERVER, PORT), Handler) print "Web Server listening on http://%s:%s/ (stop with ctrl+c)..." % (SERVER, PORT) try: httpd.serve_forever() except KeyboardInterrupt: print "Going down..."
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scripts/junction_tree/generate_vocab.py
rtriangle/moses
2
164523
<reponame>rtriangle/moses<gh_stars>1-10 import argparse import rdkit import torch import tqdm from moses.junction_tree.datautils import JTreeVocab from moses.junction_tree.jtnn.mol_tree import MolTree from moses.script_utils import read_smiles_csv lg = rdkit.RDLogger.logger() lg.setLevel(rdkit.RDLogger.CRITICAL) def main(config): data = read_smiles_csv(config.train_load) clusters = set() for smiles in tqdm.tqdm(data): mol = MolTree(smiles) for c in mol.nodes: clusters.add(c.smiles) vocab = JTreeVocab(sorted(list(clusters))) torch.save(vocab, config.vocab_save) def get_parser(): parser = argparse.ArgumentParser() parser.add_argument("--train_load", type=str, required=True, help='Input data in csv format to train') parser.add_argument('--vocab_save', type=str, default='vocab.pt', help='Where to save the vocab') return parser if __name__ == '__main__': parser = get_parser() config = parser.parse_known_args()[0] main(config)
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tests/providers/apache/hive/transfers/test_s3_to_hive.py
gtossou/airflow
2
197823
<gh_stars>1-10 # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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 bz2 import errno import filecmp import logging import shutil import unittest from collections import OrderedDict from gzip import GzipFile from itertools import product from tempfile import NamedTemporaryFile, mkdtemp from unittest import mock from airflow.exceptions import AirflowException from airflow.providers.apache.hive.transfers.s3_to_hive import S3ToHiveOperator try: import boto3 from moto import mock_s3 except ImportError: mock_s3 = None class TestS3ToHiveTransfer(unittest.TestCase): def setUp(self): self.file_names = {} self.task_id = 'S3ToHiveTransferTest' self.s3_key = 'S32hive_test_file' self.field_dict = OrderedDict([('Sno', 'BIGINT'), ('Some,Text', 'STRING')]) self.hive_table = 'S32hive_test_table' self.delimiter = '\t' self.create = True self.recreate = True self.partition = {'ds': 'STRING'} self.headers = True self.check_headers = True self.wildcard_match = False self.input_compressed = False self.kwargs = { 'task_id': self.task_id, 's3_key': self.s3_key, 'field_dict': self.field_dict, 'hive_table': self.hive_table, 'delimiter': self.delimiter, 'create': self.create, 'recreate': self.recreate, 'partition': self.partition, 'headers': self.headers, 'check_headers': self.check_headers, 'wildcard_match': self.wildcard_match, 'input_compressed': self.input_compressed, } try: header = b"Sno\tSome,Text \n" line1 = b"1\tAirflow Test\n" line2 = b"2\tS32HiveTransfer\n" self.tmp_dir = mkdtemp(prefix='test_tmps32hive_') # create sample txt, gz and bz2 with and without headers with NamedTemporaryFile(mode='wb+', dir=self.tmp_dir, delete=False) as f_txt_h: self._set_fn(f_txt_h.name, '.txt', True) f_txt_h.writelines([header, line1, line2]) fn_gz = self._get_fn('.txt', True) + ".gz" with GzipFile(filename=fn_gz, mode="wb") as f_gz_h: self._set_fn(fn_gz, '.gz', True) f_gz_h.writelines([header, line1, line2]) fn_gz_upper = self._get_fn('.txt', True) + ".GZ" with GzipFile(filename=fn_gz_upper, mode="wb") as f_gz_upper_h: self._set_fn(fn_gz_upper, '.GZ', True) f_gz_upper_h.writelines([header, line1, line2]) fn_bz2 = self._get_fn('.txt', True) + '.bz2' with bz2.BZ2File(filename=fn_bz2, mode="wb") as f_bz2_h: self._set_fn(fn_bz2, '.bz2', True) f_bz2_h.writelines([header, line1, line2]) # create sample txt, bz and bz2 without header with NamedTemporaryFile(mode='wb+', dir=self.tmp_dir, delete=False) as f_txt_nh: self._set_fn(f_txt_nh.name, '.txt', False) f_txt_nh.writelines([line1, line2]) fn_gz = self._get_fn('.txt', False) + ".gz" with GzipFile(filename=fn_gz, mode="wb") as f_gz_nh: self._set_fn(fn_gz, '.gz', False) f_gz_nh.writelines([line1, line2]) fn_gz_upper = self._get_fn('.txt', False) + ".GZ" with GzipFile(filename=fn_gz_upper, mode="wb") as f_gz_upper_nh: self._set_fn(fn_gz_upper, '.GZ', False) f_gz_upper_nh.writelines([line1, line2]) fn_bz2 = self._get_fn('.txt', False) + '.bz2' with bz2.BZ2File(filename=fn_bz2, mode="wb") as f_bz2_nh: self._set_fn(fn_bz2, '.bz2', False) f_bz2_nh.writelines([line1, line2]) # Base Exception so it catches Keyboard Interrupt except BaseException as e: logging.error(e) self.tearDown() def tearDown(self): try: shutil.rmtree(self.tmp_dir) except OSError as e: # ENOENT - no such file or directory if e.errno != errno.ENOENT: raise e # Helper method to create a dictionary of file names and # file types (file extension and header) def _set_fn(self, fn, ext, header): key = self._get_key(ext, header) self.file_names[key] = fn # Helper method to fetch a file of a # certain format (file extension and header) def _get_fn(self, ext, header): key = self._get_key(ext, header) return self.file_names[key] @staticmethod def _get_key(ext, header): key = ext + "_" + ('h' if header else 'nh') return key @staticmethod def _check_file_equality(fn_1, fn_2, ext): # gz files contain mtime and filename in the header that # causes filecmp to return False even if contents are identical # Hence decompress to test for equality if ext.lower() == '.gz': with GzipFile(fn_1, 'rb') as f_1, NamedTemporaryFile(mode='wb') as f_txt_1: with GzipFile(fn_2, 'rb') as f_2, NamedTemporaryFile(mode='wb') as f_txt_2: shutil.copyfileobj(f_1, f_txt_1) shutil.copyfileobj(f_2, f_txt_2) f_txt_1.flush() f_txt_2.flush() return filecmp.cmp(f_txt_1.name, f_txt_2.name, shallow=False) else: return filecmp.cmp(fn_1, fn_2, shallow=False) def test_bad_parameters(self): self.kwargs['check_headers'] = True self.kwargs['headers'] = False self.assertRaisesRegex(AirflowException, "To check_headers.*", S3ToHiveOperator, **self.kwargs) def test__get_top_row_as_list(self): self.kwargs['delimiter'] = '\t' fn_txt = self._get_fn('.txt', True) header_list = S3ToHiveOperator(**self.kwargs)._get_top_row_as_list(fn_txt) self.assertEqual( header_list, ['Sno', 'Some,Text'], msg="Top row from file doesnt matched expected value" ) self.kwargs['delimiter'] = ',' header_list = S3ToHiveOperator(**self.kwargs)._get_top_row_as_list(fn_txt) self.assertEqual( header_list, ['Sno\tSome', 'Text'], msg="Top row from file doesnt matched expected value" ) def test__match_headers(self): self.kwargs['field_dict'] = OrderedDict([('Sno', 'BIGINT'), ('Some,Text', 'STRING')]) self.assertTrue( S3ToHiveOperator(**self.kwargs)._match_headers(['Sno', 'Some,Text']), msg="Header row doesnt match expected value", ) # Testing with different column order self.assertFalse( S3ToHiveOperator(**self.kwargs)._match_headers(['Some,Text', 'Sno']), msg="Header row doesnt match expected value", ) # Testing with extra column in header self.assertFalse( S3ToHiveOperator(**self.kwargs)._match_headers(['Sno', 'Some,Text', 'ExtraColumn']), msg="Header row doesnt match expected value", ) def test__delete_top_row_and_compress(self): s32hive = S3ToHiveOperator(**self.kwargs) # Testing gz file type fn_txt = self._get_fn('.txt', True) gz_txt_nh = s32hive._delete_top_row_and_compress(fn_txt, '.gz', self.tmp_dir) fn_gz = self._get_fn('.gz', False) self.assertTrue( self._check_file_equality(gz_txt_nh, fn_gz, '.gz'), msg="gz Compressed file not as expected" ) # Testing bz2 file type bz2_txt_nh = s32hive._delete_top_row_and_compress(fn_txt, '.bz2', self.tmp_dir) fn_bz2 = self._get_fn('.bz2', False) self.assertTrue( self._check_file_equality(bz2_txt_nh, fn_bz2, '.bz2'), msg="bz2 Compressed file not as expected" ) @unittest.skipIf(mock is None, 'mock package not present') @unittest.skipIf(mock_s3 is None, 'moto package not present') @mock.patch('airflow.providers.apache.hive.transfers.s3_to_hive.HiveCliHook') @mock_s3 def test_execute(self, mock_hiveclihook): conn = boto3.client('s3') conn.create_bucket(Bucket='bucket') # Testing txt, zip, bz2 files with and without header row for (ext, has_header) in product(['.txt', '.gz', '.bz2', '.GZ'], [True, False]): self.kwargs['headers'] = has_header self.kwargs['check_headers'] = has_header logging.info("Testing %s format %s header", ext, 'with' if has_header else 'without') self.kwargs['input_compressed'] = ext.lower() != '.txt' self.kwargs['s3_key'] = 's3://bucket/' + self.s3_key + ext ip_fn = self._get_fn(ext, self.kwargs['headers']) op_fn = self._get_fn(ext, False) # Upload the file into the Mocked S3 bucket conn.upload_file(ip_fn, 'bucket', self.s3_key + ext) # file parameter to HiveCliHook.load_file is compared # against expected file output mock_hiveclihook().load_file.side_effect = lambda *args, **kwargs: self.assertTrue( self._check_file_equality(args[0], op_fn, ext), msg='{0} output file not as expected'.format(ext), ) # Execute S3ToHiveTransfer s32hive = S3ToHiveOperator(**self.kwargs) s32hive.execute(None) @unittest.skipIf(mock is None, 'mock package not present') @unittest.skipIf(mock_s3 is None, 'moto package not present') @mock.patch('airflow.providers.apache.hive.transfers.s3_to_hive.HiveCliHook') @mock_s3 def test_execute_with_select_expression(self, mock_hiveclihook): conn = boto3.client('s3') conn.create_bucket(Bucket='bucket') select_expression = "SELECT * FROM S3Object s" bucket = 'bucket' # Only testing S3ToHiveTransfer calls S3Hook.select_key with # the right parameters and its execute method succeeds here, # since Moto doesn't support select_object_content as of 1.3.2. for (ext, has_header) in product(['.txt', '.gz', '.GZ'], [True, False]): input_compressed = ext.lower() != '.txt' key = self.s3_key + ext self.kwargs['check_headers'] = False self.kwargs['headers'] = has_header self.kwargs['input_compressed'] = input_compressed self.kwargs['select_expression'] = select_expression self.kwargs['s3_key'] = 's3://{0}/{1}'.format(bucket, key) ip_fn = self._get_fn(ext, has_header) # Upload the file into the Mocked S3 bucket conn.upload_file(ip_fn, bucket, key) input_serialization = {'CSV': {'FieldDelimiter': self.delimiter}} if input_compressed: input_serialization['CompressionType'] = 'GZIP' if has_header: input_serialization['CSV']['FileHeaderInfo'] = 'USE' # Confirm that select_key was called with the right params with mock.patch( 'airflow.providers.amazon.aws.hooks.s3.S3Hook.select_key', return_value="" ) as mock_select_key: # Execute S3ToHiveTransfer s32hive = S3ToHiveOperator(**self.kwargs) s32hive.execute(None) mock_select_key.assert_called_once_with( bucket_name=bucket, key=key, expression=select_expression, input_serialization=input_serialization, )
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Weltantschauung/__init__.py
area42/Weltanschauung-
0
23286
from .Weltantschauung import Weltantschauung
[ 1, 515, 869, 29956, 2152, 424, 29172, 686, 1053, 7633, 424, 29172, 686, 13, 2 ]
python算法/3.3如何从顶部开始逐层打印二叉树结点数据.py
RobinYaoWenbin/Python-CommonCode
12
77879
# -*- coding: utf-8 -*- """ Created on Mon Dec 23 14:31:43 2019 @author: wenbin """ """ 给定一棵二叉树,要求逐层打印二叉树结点的数据,例如有如下二叉树: 1 2 3 4 5 6 7 对这棵二叉树层序遍历的结果为1,2,3,4,5,6,7; """ from collections import deque class BiTNode: # the node of the binary tree def __init__(self , data = None): self.Data = data self.Lchild = None self.Rchild = None def GenerateTree(): # generate the tree for the case research Root = BiTNode(data = 1) Root.Lchild = BiTNode(data = 2) ; Root.Rchild = BiTNode(data = 3) Root.Lchild.Lchild = BiTNode(data = 4) ; Root.Lchild.Rchild = BiTNode(data = 5) Root.Rchild.Lchild = BiTNode(data = 6) ; Root.Rchild.Rchild = BiTNode(data = 7) return Root def PrintMidOrder(Root): # print the binary tree by the middle order if Root == None: return if Root.Lchild != None: PrintMidOrder(Root.Lchild) print(Root.Data , " " , end = "") if Root.Rchild != None: PrintMidOrder(Root.Rchild) def TraversalbyLayer(Root): # traversal the tree by layer, 1st layer, 2nd layer````,时间复杂夫O(n),空间复杂度O(n) queue = deque() # new a queue queue.append(Root) print("Traversal the binary tree in the order by layer!") while len(queue) != 0: tempnode = queue.popleft() print(tempnode.Data , " " , end = "") if tempnode.Lchild != None: queue.append(tempnode.Lchild) if tempnode.Rchild != None: queue.append(tempnode.Rchild) def PrintAtLevel(root , level): # travelsal the tree by layer. 空间复杂度是O(1)，以时间换取空间 if root == None or level < 0 : # 空树或是要求打印出负的层数,返回0 return elif level == 0: print(root.Data , " " , end = "") # 打印出这一层的数据 return else: PrintAtLevel(root.Lchild , level - 1) PrintAtLevel(root.Rchild , level - 1) if __name__ == "__main__": Root = GenerateTree() print("The generating tree in the middel order is : ") PrintMidOrder(Root) print("") TraversalbyLayer(Root) print("") print("Another method : ") for i in range(3): PrintAtLevel(Root , i)
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applications/FluidDynamicsApplication/tests/embedded_couette_flow_test.py
lkusch/Kratos
778
1617996
# Import kratos core and applications import KratosMultiphysics import KratosMultiphysics.KratosUnittest as KratosUnittest import KratosMultiphysics.kratos_utilities as KratosUtilities from KratosMultiphysics.FluidDynamicsApplication.fluid_dynamics_analysis import FluidDynamicsAnalysis class EmbeddedCouetteTestFluidDynamicsAnalysis(FluidDynamicsAnalysis): def __init__(self, model, parameters, slip_interface, distance): super().__init__(model, parameters) self.distance = distance self.slip_interface = slip_interface def ModifyAfterSolverInitialize(self): super().ModifyAfterSolverInitialize() # Set up distance field in the DISTANCE nodal variable computing_model_part = self._GetSolver().GetComputingModelPart() domain_size = computing_model_part.ProcessInfo[KratosMultiphysics.DOMAIN_SIZE] if domain_size == 2: for node in computing_model_part.Nodes: distance = node.Y-self.distance node.SetSolutionStepValue(KratosMultiphysics.DISTANCE, 0, distance) elif domain_size == 3: for node in computing_model_part.Nodes: distance = node.Z-self.distance node.SetSolutionStepValue(KratosMultiphysics.DISTANCE, 0, distance) else: raise Exception("DOMAIN_SIZE has not been set in the ProcessInfo container.") # Set the ELEMENTAL_DISTANCES value # This is required for the discontinuous elements tests n_nodes = len(computing_model_part.Elements[1].GetNodes()) n_edges = computing_model_part.Elements[1].GetGeometry().EdgesNumber() elem_edge_dist = KratosMultiphysics.Vector(n_edges, -1.0) for element in computing_model_part.Elements: elem_dist = KratosMultiphysics.Vector(n_nodes) elem_nodes = element.GetNodes() for i_node in range(n_nodes): elem_dist[i_node] = elem_nodes[i_node].GetSolutionStepValue(KratosMultiphysics.DISTANCE) element.SetValue(KratosMultiphysics.ELEMENTAL_DISTANCES, elem_dist) element.SetValue(KratosMultiphysics.ELEMENTAL_EDGE_DISTANCES, elem_edge_dist) # Set up the initial velocity condition if self.slip_interface: init_v = KratosMultiphysics.Vector([1.0,0.0,0.0]) for node in computing_model_part.Nodes: if node.GetSolutionStepValue(KratosMultiphysics.DISTANCE) > 0.0: node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, init_v) else: for node in computing_model_part.Nodes: dist = node.GetSolutionStepValue(KratosMultiphysics.DISTANCE) if dist > 0.0: init_v = KratosMultiphysics.Vector([dist,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, init_v) def ApplyBoundaryConditions(self): super().ApplyBoundaryConditions() # Set velocity boundary condition main_model_part = self._GetSolver().GetComputingModelPart().GetRootModelPart() if self.slip_interface: for node in main_model_part.GetSubModelPart("Inlet").Nodes: if node.GetSolutionStepValue(KratosMultiphysics.DISTANCE) > 0.0: aux_vel = KratosMultiphysics.Vector([1.0,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, aux_vel) node.Fix(KratosMultiphysics.VELOCITY_X) node.Fix(KratosMultiphysics.VELOCITY_Y) node.Fix(KratosMultiphysics.VELOCITY_Z) else: aux_vel = KratosMultiphysics.Vector([0.0,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, aux_vel) else: for node in main_model_part.GetSubModelPart("Inlet").Nodes: dist = node.GetSolutionStepValue(KratosMultiphysics.DISTANCE) if (dist > 0.0): aux_vel = KratosMultiphysics.Vector([dist,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, aux_vel) node.Fix(KratosMultiphysics.VELOCITY_X) node.Fix(KratosMultiphysics.VELOCITY_Y) node.Fix(KratosMultiphysics.VELOCITY_Z) else: aux_vel = KratosMultiphysics.Vector([0.0,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, aux_vel) # Set and fix the top boundary velocity for node in main_model_part.GetSubModelPart("Top").Nodes: dist = node.GetSolutionStepValue(KratosMultiphysics.DISTANCE) aux_vel = KratosMultiphysics.Vector([dist,0.0,0.0]) node.SetSolutionStepValue(KratosMultiphysics.VELOCITY, aux_vel) node.Fix(KratosMultiphysics.VELOCITY_X) node.Fix(KratosMultiphysics.VELOCITY_Y) node.Fix(KratosMultiphysics.VELOCITY_Z) @KratosUnittest.skipIfApplicationsNotAvailable("LinearSolversApplication") class EmbeddedCouetteFlowTest(KratosUnittest.TestCase): # Continuous level set 2D tests def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokes2D(self): self.distance = 0.25 self.slip_flag = False self.settings_filename = "ProjectParameters2D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes", "is_slip": false, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokes2DSlip(self): self.distance = 0.25 self.slip_flag = True self.settings_filename = "ProjectParameters2D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes", "is_slip": true, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() # Continuous level set 3D tests def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokes3D(self): self.distance = 0.25 self.slip_flag = False self.settings_filename = "ProjectParameters3D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes", "is_slip": false, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokes3DSlip(self): self.distance = 0.25 self.slip_flag = True self.settings_filename = "ProjectParameters3D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes", "is_slip": true, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() # Discontinuous level set tests def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokesDiscontinuous2D(self): self.distance = 0.25 self.slip_flag = False self.settings_filename = "ProjectParameters2D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes_discontinuous", "is_slip": true, "slip_length": 1.0e8, "penalty_coefficient": 0.1, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() def testEmbeddedCouetteFlowEmbeddedWeaklyCompressibleNavierStokesDiscontinuous3D(self): self.distance = 0.25 self.slip_flag = True self.settings_filename = "ProjectParameters3D.json" self.formulation_settings = KratosMultiphysics.Parameters("""{ "element_type": "embedded_weakly_compressible_navier_stokes_discontinuous", "is_slip": true, "slip_length": 1.0e8, "penalty_coefficient": 0.1, "dynamic_tau": 1.0 }""") self._ReadAndCustomizeTestSettings() self._RunEmbeddedCouetteFlowTest() def setUp(self): self.print_output = False self.check_tolerance = 1.0e-6 self.check_relative_tolerance = 1.0e-8 self.print_reference_values = False self.work_folder = "embedded_couette_flow_test" def _RunEmbeddedCouetteFlowTest(self): # Create the test simulation with KratosUnittest.WorkFolderScope(self.work_folder,__file__): self.model = KratosMultiphysics.Model() simulation = EmbeddedCouetteTestFluidDynamicsAnalysis(self.model, self.parameters, self.slip_flag, self.distance) simulation.Run() def tearDown(self): with KratosUnittest.WorkFolderScope(self.work_folder, __file__): KratosUtilities.DeleteFileIfExisting('{0}.time'.format(self.parameters["solver_settings"]["model_import_settings"]["input_filename"].GetString())) def _ReadAndCustomizeTestSettings(self): # Read the simulation settings with KratosUnittest.WorkFolderScope(self.work_folder,__file__): with open(self.settings_filename,'r') as parameter_file: self.parameters = KratosMultiphysics.Parameters(parameter_file.read()) # Customize simulation settings self.parameters["solver_settings"]["formulation"] = self.formulation_settings # If required, add the output process to the test settings if self.print_output: self._AddOutput() # If required, add the reference values output process to the test settings if self.print_reference_values: self._AddReferenceValuesOutput() else: self._AddReferenceValuesCheck() def _AddOutput(self): gid_output_settings = KratosMultiphysics.Parameters("""{ "python_module" : "gid_output_process", "kratos_module" : "KratosMultiphysics", "process_name" : "GiDOutputProcess", "help" : "This process writes postprocessing files for GiD", "Parameters" : { "model_part_name" : "MainModelPart.fluid_computational_model_part", "output_name" : "embedded_couette_flow_test", "postprocess_parameters" : { "result_file_configuration" : { "gidpost_flags" : { "GiDPostMode" : "GiD_PostBinary", "WriteDeformedMeshFlag" : "WriteDeformed", "WriteConditionsFlag" : "WriteConditions", "MultiFileFlag" : "SingleFile" }, "file_label" : "time", "output_control_type" : "step", "output_interval" : 1, "body_output" : true, "node_output" : false, "skin_output" : false, "plane_output" : [], "nodal_results" : ["DISTANCE","VELOCITY","PRESSURE"], "gauss_point_results" : [], "nodal_nonhistorical_results" : [] }, "point_data_configuration" : [] } } }""") domain_size = self.parameters["solver_settings"]["domain_size"].GetInt() output_name = gid_output_settings["Parameters"]["output_name"].GetString() output_name += "_{0}_{1}d".format(self.formulation_settings["element_type"].GetString(), domain_size) if self.slip_flag: output_name += "_slip" gid_output_settings["Parameters"]["output_name"].SetString(output_name) self.parameters["output_processes"]["gid_output"].Append(gid_output_settings) def _AddReferenceValuesOutput(self): json_output_settings = KratosMultiphysics.Parameters("""{ "python_module" : "json_output_process", "kratos_module" : "KratosMultiphysics", "process_name" : "JsonOutputProcess", "Parameters" : { "output_variables" : ["VELOCITY","PRESSURE"], "output_file_name" : "reference_embedded_couette_flow_test", "model_part_name" : "MainModelPart.Parts_Fluid", "time_frequency" : 0.1 } }""") domain_size = self.parameters["solver_settings"]["domain_size"].GetInt() output_file_name = json_output_settings["Parameters"]["output_file_name"].GetString() output_file_name += "_{0}_{1}d".format(self.formulation_settings["element_type"].GetString(), domain_size) if self.slip_flag: output_file_name += "_slip" json_output_settings["Parameters"]["output_file_name"].SetString(output_file_name) self.parameters["processes"]["json_check_process_list"].Append(json_output_settings) def _AddReferenceValuesCheck(self): json_check_settings = KratosMultiphysics.Parameters("""{ "python_module" : "from_json_check_result_process", "kratos_module" : "KratosMultiphysics", "process_name" : "FromJsonCheckResultProcess", "Parameters" : { "check_variables" : ["VELOCITY_X","VELOCITY_Y","PRESSURE"], "input_file_name" : "reference_embedded_couette_flow_test", "model_part_name" : "MainModelPart.Parts_Fluid", "tolerance" : 0.0, "relative_tolerance" : 0.0, "time_frequency" : 0.1 } }""") domain_size = self.parameters["solver_settings"]["domain_size"].GetInt() input_file_name = json_check_settings["Parameters"]["input_file_name"].GetString() input_file_name += "_{0}_{1}d".format(self.formulation_settings["element_type"].GetString(), domain_size) if self.slip_flag: input_file_name += "_slip" json_check_settings["Parameters"]["input_file_name"].SetString(input_file_name) json_check_settings["Parameters"]["tolerance"].SetDouble(self.check_tolerance) json_check_settings["Parameters"]["relative_tolerance"].SetDouble(self.check_relative_tolerance) self.parameters["processes"]["json_check_process_list"].Append(json_check_settings) if __name__ == '__main__': KratosUnittest.main()
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test.py
xiaohuaibaoguigui/EllSeg
1
3001
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os import sys import tqdm import torch import pickle import resource import numpy as np import matplotlib.pyplot as plt from args import parse_args from modelSummary import model_dict from pytorchtools import load_from_file from torch.utils.data import DataLoader from helperfunctions import mypause, stackall_Dict from loss import get_seg2ptLoss from utils import get_nparams, get_predictions from utils import getSeg_metrics, getPoint_metric, generateImageGrid, unnormPts sys.path.append(os.path.abspath(os.path.join(os.getcwd(), os.pardir))) rlimit = resource.getrlimit(resource.RLIMIT_NOFILE) resource.setrlimit(resource.RLIMIT_NOFILE, (2048*10, rlimit[1])) #%% if __name__ == '__main__': args = parse_args() device=torch.device("cuda") torch.cuda.manual_seed(12) if torch.cuda.device_count() > 1: print('Moving to a multiGPU setup.') args.useMultiGPU = True else: args.useMultiGPU = False torch.backends.cudnn.deterministic=False if args.model not in model_dict: print("Model not found.") print("valid models are: {}".format(list(model_dict.keys()))) exit(1) LOGDIR = os.path.join(os.getcwd(), 'logs', args.model, args.expname) path2model = os.path.join(LOGDIR, 'weights') path2checkpoint = os.path.join(LOGDIR, 'checkpoints') path2writer = os.path.join(LOGDIR, 'TB.lock') path2op = os.path.join(os.getcwd(), 'op', str(args.curObj)) os.makedirs(LOGDIR, exist_ok=True) os.makedirs(path2model, exist_ok=True) os.makedirs(path2checkpoint, exist_ok=True) os.makedirs(path2writer, exist_ok=True) os.makedirs(path2op, exist_ok=True) model = model_dict[args.model] netDict = load_from_file([args.loadfile, os.path.join(path2checkpoint, 'checkpoint.pt')]) startEp = netDict['epoch'] if 'epoch' in netDict.keys() else 0 if 'state_dict' in netDict.keys(): model.load_state_dict(netDict['state_dict']) print('Parameters: {}'.format(get_nparams(model))) model = model if not args.useMultiGPU else torch.nn.DataParallel(model) model = model.to(device).to(args.prec) f = open(os.path.join('curObjects', 'baseline', 'cond_'+str(args.curObj)+'.pkl'), 'rb') _, _, testObj = pickle.load(f) testObj.path2data = os.path.join(args.path2data, 'Datasets', 'All') testObj.augFlag = False testloader = DataLoader(testObj, batch_size=args.batchsize, shuffle=False, num_workers=args.workers, drop_last=False) if args.disp: fig, axs = plt.subplots(nrows=1, ncols=1) #%% accLoss = 0.0 imCounter = 0 ious = [] dists_pupil_latent = [] dists_pupil_seg = [] dists_iris_latent = [] dists_iris_seg = [] model.eval() opDict = {'id':[], 'archNum': [], 'archName': [], 'code': [], 'scores':{'iou':[], 'lat_dst':[], 'seg_dst':[]}, 'pred':{'pup_latent_c':[], 'pup_seg_c':[], 'iri_latent_c':[], 'iri_seg_c':[], 'mask':[]}, 'gt':{'pup_c':[], 'mask':[]}} with torch.no_grad(): for bt, batchdata in enumerate(tqdm.tqdm(testloader)): img, labels, spatialWeights, distMap, pupil_center, iris_center, elNorm, cond, imInfo = batchdata out_tup = model(img.to(device).to(args.prec), labels.to(device).long(), pupil_center.to(device).to(args.prec), elNorm.to(device).to(args.prec), spatialWeights.to(device).to(args.prec), distMap.to(device).to(args.prec), cond.to(device).to(args.prec), imInfo[:, 2].to(device).to(torch.long), 0.5) output, elOut, latent, loss = out_tup latent_pupil_center = elOut[:, 0:2].detach().cpu().numpy() latent_iris_center = elOut[:, 5:7].detach().cpu().numpy() _, seg_pupil_center = get_seg2ptLoss(output[:, 2, ...].cpu(), pupil_center, temperature=4) _, seg_iris_center = get_seg2ptLoss(-output[:, 0, ...].cpu(), iris_center, temperature=4) loss = loss if args.useMultiGPU else loss.mean() accLoss += loss.detach().cpu().item() predict = get_predictions(output) iou, iou_bySample = getSeg_metrics(labels.numpy(), predict.numpy(), cond[:, 1].numpy())[1:] latent_pupil_dist, latent_pupil_dist_bySample = getPoint_metric(pupil_center.numpy(), latent_pupil_center, cond[:,0].numpy(), img.shape[2:], True) # Unnormalizes the points seg_pupil_dist, seg_pupil_dist_bySample = getPoint_metric(pupil_center.numpy(), seg_pupil_center, cond[:,1].numpy(), img.shape[2:], True) # Unnormalizes the points latent_iris_dist, latent_iris_dist_bySample = getPoint_metric(iris_center.numpy(), latent_iris_center, cond[:,1].numpy(), img.shape[2:], True) # Unnormalizes the points seg_iris_dist, seg_iris_dist_bySample = getPoint_metric(iris_center.numpy(), seg_iris_center, cond[:,1].numpy(), img.shape[2:], True) # Unnormalizes the points dists_pupil_latent.append(latent_pupil_dist) dists_iris_latent.append(latent_iris_dist) dists_pupil_seg.append(seg_pupil_dist) dists_iris_seg.append(seg_iris_dist) ious.append(iou) pup_latent_c = unnormPts(latent_pupil_center, img.shape[2:]) pup_seg_c = unnormPts(seg_pupil_center, img.shape[2:]) iri_latent_c = unnormPts(latent_iris_center, img.shape[2:]) iri_seg_c = unnormPts(seg_iris_center, img.shape[2:]) dispI = generateImageGrid(img.numpy().squeeze(), predict.numpy(), elOut.detach().cpu().numpy().reshape(-1, 2, 5), pup_seg_c, cond.numpy(), override=True, heatmaps=False) for i in range(0, img.shape[0]): archNum = testObj.imList[imCounter, 1] opDict['id'].append(testObj.imList[imCounter, 0]) opDict['code'].append(latent[i,...].detach().cpu().numpy()) opDict['archNum'].append(archNum) opDict['archName'].append(testObj.arch[archNum]) opDict['pred']['pup_latent_c'].append(pup_latent_c[i, :]) opDict['pred']['pup_seg_c'].append(pup_seg_c[i, :]) opDict['pred']['iri_latent_c'].append(iri_latent_c[i, :]) opDict['pred']['iri_seg_c'].append(iri_seg_c[i, :]) if args.test_save_op_masks: opDict['pred']['mask'].append(predict[i,...].numpy().astype(np.uint8)) opDict['scores']['iou'].append(iou_bySample[i, ...]) opDict['scores']['lat_dst'].append(latent_pupil_dist_bySample[i, ...]) opDict['scores']['seg_dst'].append(seg_pupil_dist_bySample[i, ...]) opDict['gt']['pup_c'].append(pupil_center[i,...].numpy()) if args.test_save_op_masks: opDict['gt']['mask'].append(labels[i,...].numpy().astype(np.uint8)) imCounter+=1 if args.disp: if bt == 0: h_im = plt.imshow(dispI.permute(1, 2, 0)) plt.pause(0.01) else: h_im.set_data(dispI.permute(1, 2, 0)) mypause(0.01) opDict = stackall_Dict(opDict) ious = np.stack(ious, axis=0) ious = np.nanmean(ious, axis=0) print('mIoU: {}. IoUs: {}'.format(np.mean(ious), ious)) print('Latent space PUPIL dist. Med: {}, STD: {}'.format(np.nanmedian(dists_pupil_latent), np.nanstd(dists_pupil_latent))) print('Segmentation PUPIL dist. Med: {}, STD: {}'.format(np.nanmedian(dists_pupil_seg), np.nanstd(dists_pupil_seg))) print('Latent space IRIS dist. Med: {}, STD: {}'.format(np.nanmedian(dists_iris_latent), np.nanstd(dists_iris_latent))) print('Segmentation IRIS dist. Med: {}, STD: {}'.format(np.nanmedian(dists_iris_seg), np.nanstd(dists_iris_seg))) print('--- Saving output directory ---') f = open(os.path.join(path2op, 'opDict.pkl'), 'wb') pickle.dump(opDict, f) f.close()
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pipeline/tests/engine/core/data/test_api.py
wkma/bk-sops
2
12162
# -*- coding: utf-8 -*- """ Tencent is pleased to support the open source community by making 蓝鲸智云PaaS平台社区版 (BlueKing PaaS Community Edition) available. Copyright (C) 2017-2021 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://opensource.org/licenses/MIT 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 sys from django.test import TestCase from django.utils.module_loading import import_string from pipeline.tests.mock import * # noqa from pipeline.tests.mock_settings import * # noqa class EngineDataAPITestCase(TestCase): @classmethod def setUpClass(cls): cls.mock_settings = MagicMock() cls.settings_patch = patch(ENGINE_DATA_API_SETTINGS, cls.mock_settings) cls.import_backend_patch = patch(ENGINE_DATA_API_IMPORT_BACKEND, MagicMock()) cls.settings_patch.start() cls.import_backend_patch.start() cls.api = import_string("pipeline.engine.core.data.api") cls.write_methods = ["set_object", "del_object", "expire_cache"] cls.read_methods = ["get_object", "cache_for"] cls.method_params = { "set_object": ["key", "obj"], "del_object": ["key"], "expire_cache": ["key", "obj", "expires"], "cache_for": ["key"], "get_object": ["key"], } @classmethod def tearDownClass(cls): cls.settings_patch.stop() cls.import_backend_patch.stop() def setUp(self): self.backend = MagicMock() self.candidate_backend = MagicMock() self.mock_settings.PIPELINE_DATA_BACKEND_AUTO_EXPIRE = False def test_write__without_candidate(self): for method in self.write_methods: with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, None): getattr(self.api, method)(*self.method_params[method]) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_not_called() sys.stdout.write( "{} pass test_write__without_candidate test\n".format(method) ) def test_write__without_candiate_raise_err(self): for method in self.write_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, None): self.assertRaises( Exception, getattr(self.api, method), *self.method_params[method] ) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_not_called() sys.stdout.write( "{} pass test_write__without_candiate_raise_err test\n".format(method) ) def test_write__with_candidate(self): for method in self.write_methods: with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): getattr(self.api, method)(*self.method_params[method]) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write("{} pass test_write__with_candidate test\n".format(method)) def test_write__with_candidate_main_raise_err(self): for method in self.write_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): getattr(self.api, method)(*self.method_params[method]) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_write__with_candidate_main_raise_err test\n".format( method ) ) def test_write__with_candidate_raise_err(self): for method in self.write_methods: setattr(self.candidate_backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): getattr(self.api, method)(*self.method_params[method]) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_write__with_candidate_raise_err test\n".format(method) ) def test_write__with_candidate_both_raise_err(self): for method in self.write_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) setattr(self.candidate_backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): self.assertRaises( Exception, getattr(self.api, method), *self.method_params[method] ) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_write__with_candidate_both_raise_err test\n".format( method ) ) def test_write__with_auto_expire(self): self.mock_settings.PIPELINE_DATA_BACKEND_AUTO_EXPIRE = True self.mock_settings.PIPELINE_DATA_BACKEND_AUTO_EXPIRE_SECONDS = 30 for method in self.write_methods: with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): getattr(self.api, method)(*self.method_params[method]) if method == "set_object": getattr(self.backend, "expire_cache").assert_called_once_with( *self.method_params[method], expires=30 ) self.backend.expire_cache.reset_mock() else: getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_write__with_candidate_both_raise_err test\n".format( method ) ) def test_read__without_candidate(self): for method in self.read_methods: with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, None): data = getattr(self.api, method)(*self.method_params[method]) self.assertIsNotNone(data) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_not_called() sys.stdout.write( "{} pass test_read__without_candidate test\n".format(method) ) def test_read__without_candidate_raise_err(self): for method in self.read_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, None): self.assertRaises( Exception, getattr(self.api, method), *self.method_params[method] ) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_not_called() sys.stdout.write( "{} pass test_read__without_candidate_raise_err test\n".format(method) ) def test_read__with_candidate_not_use(self): for method in self.read_methods: with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): data = getattr(self.api, method)(*self.method_params[method]) self.assertIsNotNone(data) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_not_called() sys.stdout.write( "{} pass test_read__with_candidate_not_use test\n".format(method) ) def test_read__with_candidate_use(self): for method in self.read_methods: setattr(self.backend, method, MagicMock(return_value=None)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): data = getattr(self.api, method)(*self.method_params[method]) self.assertIsNotNone(data) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_read__with_candidate_use test\n".format(method) ) def test_read__with_candidate_err(self): for method in self.read_methods: setattr(self.backend, method, MagicMock(return_value=None)) setattr(self.candidate_backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): data = getattr(self.api, method)(*self.method_params[method]) self.assertIsNone(data) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_read__with_candidate_err test\n".format(method) ) def test_read__with_candidate_main_raise_err(self): for method in self.read_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): data = getattr(self.api, method)(*self.method_params[method]) self.assertIsNotNone(data) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_read__with_candidate_main_raise_err test\n".format(method) ) def test_read__with_candidate_both_raise_err(self): for method in self.read_methods: setattr(self.backend, method, MagicMock(side_effect=Exception)) setattr(self.candidate_backend, method, MagicMock(side_effect=Exception)) with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): self.assertRaises( Exception, getattr(self.api, method), *self.method_params[method] ) getattr(self.backend, method).assert_called_once_with( *self.method_params[method] ) getattr(self.candidate_backend, method).assert_called_once_with( *self.method_params[method] ) sys.stdout.write( "{} pass test_read__with_candidate_both_raise_err test\n".format(method) ) def test_set_schedule_data(self): with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): self.api.set_schedule_data("key", "data") self.backend.set_object.assert_called_once_with( "key_schedule_parent_data", "data" ) self.candidate_backend.set_object.assert_called_once_with( "key_schedule_parent_data", "data" ) def test_delete_parent_data(self): with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): self.api.delete_parent_data("key") self.backend.del_object.assert_called_once_with( "key_schedule_parent_data" ) self.candidate_backend.del_object.assert_called_once_with( "key_schedule_parent_data" ) def test_get_schedule_parent_data(self): with patch(ENGINE_DATA_API_BACKEND, self.backend): with patch(ENGINE_DATA_API_CANDIDATE_BACKEND, self.candidate_backend): data = self.api.get_schedule_parent_data("key") self.assertIsNotNone(data) self.backend.get_object.assert_called_once_with( "key_schedule_parent_data" ) self.candidate_backend.get_object.assert_not_called()
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5746, 2227, 1525, 29918, 1660, 6007, 8452, 353, 29871, 29941, 29900, 13, 13, 4706, 363, 1158, 297, 1583, 29889, 3539, 29918, 23515, 29901, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 565, 1158, 1275, 376, 842, 29918, 3318, 1115, 13, 462, 4706, 679, 5552, 29898, 1311, 29889, 27852, 29892, 376, 4548, 533, 29918, 8173, 2564, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 9651, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 1402, 1518, 2658, 29922, 29941, 29900, 13, 462, 4706, 1723, 13, 462, 4706, 1583, 29889, 27852, 29889, 4548, 533, 29918, 8173, 29889, 12071, 29918, 17640, 580, 13, 462, 1678, 1683, 29901, 13, 462, 4706, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 9651, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 4706, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 3539, 1649, 2541, 29918, 29883, 5380, 403, 29918, 20313, 29918, 22692, 29918, 3127, 1243, 29905, 29876, 1642, 4830, 29898, 13, 462, 1678, 1158, 13, 18884, 1723, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 14037, 29918, 29883, 5380, 403, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 6213, 1125, 13, 462, 1678, 848, 353, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 1583, 29889, 9294, 3624, 3664, 8516, 29898, 1272, 29897, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 1333, 29918, 13998, 580, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 14037, 29918, 29883, 5380, 403, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 14037, 29918, 29883, 5380, 403, 29918, 22692, 29918, 3127, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 731, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2975, 29918, 15987, 29922, 2451, 876, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 6213, 1125, 13, 462, 1678, 1583, 29889, 9294, 29934, 1759, 267, 29898, 13, 462, 4706, 8960, 29892, 13, 462, 4706, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 511, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 1333, 29918, 13998, 580, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 14037, 29918, 29883, 5380, 403, 29918, 22692, 29918, 3127, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 1333, 29918, 1509, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 848, 353, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 1583, 29889, 9294, 3624, 3664, 8516, 29898, 1272, 29897, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 1333, 29918, 13998, 580, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 1333, 29918, 1509, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 1509, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 731, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2457, 29918, 1767, 29922, 8516, 876, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 848, 353, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 1583, 29889, 9294, 3624, 3664, 8516, 29898, 1272, 29897, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 1509, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 3127, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 731, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2457, 29918, 1767, 29922, 8516, 876, 13, 9651, 731, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2975, 29918, 15987, 29922, 2451, 876, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 848, 353, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 1583, 29889, 9294, 3624, 8516, 29898, 1272, 29897, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 3127, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 3396, 29918, 22692, 29918, 3127, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 731, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2975, 29918, 15987, 29922, 2451, 876, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 848, 353, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 5033, 29930, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 2314, 13, 462, 1678, 1583, 29889, 9294, 3624, 3664, 8516, 29898, 1272, 29897, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 3396, 29918, 22692, 29918, 3127, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 20313, 29918, 22692, 29918, 3127, 29898, 1311, 1125, 13, 4706, 363, 1158, 297, 1583, 29889, 949, 29918, 23515, 29901, 13, 13, 9651, 731, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2975, 29918, 15987, 29922, 2451, 876, 13, 9651, 731, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 29892, 26494, 18680, 29898, 2975, 29918, 15987, 29922, 2451, 876, 13, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 18884, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 462, 1678, 1583, 29889, 9294, 29934, 1759, 267, 29898, 13, 462, 4706, 8960, 29892, 13, 462, 4706, 679, 5552, 29898, 1311, 29889, 2754, 29892, 1158, 511, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 462, 1678, 679, 5552, 29898, 1311, 29889, 29883, 5380, 403, 29918, 27852, 29892, 1158, 467, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 4706, 334, 1311, 29889, 5696, 29918, 7529, 29961, 5696, 29962, 13, 462, 1678, 1723, 13, 13, 9651, 10876, 29889, 25393, 29889, 3539, 29898, 13, 18884, 376, 8875, 1209, 1243, 29918, 949, 1649, 2541, 29918, 29883, 5380, 403, 29918, 20313, 29918, 22692, 29918, 3127, 1243, 29905, 29876, 1642, 4830, 29898, 5696, 29897, 13, 9651, 1723, 13, 13, 1678, 822, 1243, 29918, 842, 29918, 816, 11272, 29918, 1272, 29898, 1311, 1125, 13, 4706, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 18884, 1583, 29889, 2754, 29889, 842, 29918, 816, 11272, 29918, 1272, 703, 1989, 613, 376, 1272, 1159, 13, 18884, 1583, 29889, 27852, 29889, 842, 29918, 3318, 29889, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 1678, 376, 1989, 29918, 816, 11272, 29918, 3560, 29918, 1272, 613, 376, 1272, 29908, 13, 18884, 1723, 13, 18884, 1583, 29889, 29883, 5380, 403, 29918, 27852, 29889, 842, 29918, 3318, 29889, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 1678, 376, 1989, 29918, 816, 11272, 29918, 3560, 29918, 1272, 613, 376, 1272, 29908, 13, 18884, 1723, 13, 13, 1678, 822, 1243, 29918, 8143, 29918, 3560, 29918, 1272, 29898, 1311, 1125, 13, 4706, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 18884, 1583, 29889, 2754, 29889, 8143, 29918, 3560, 29918, 1272, 703, 1989, 1159, 13, 18884, 1583, 29889, 27852, 29889, 6144, 29918, 3318, 29889, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 1678, 376, 1989, 29918, 816, 11272, 29918, 3560, 29918, 1272, 29908, 13, 18884, 1723, 13, 18884, 1583, 29889, 29883, 5380, 403, 29918, 27852, 29889, 6144, 29918, 3318, 29889, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 1678, 376, 1989, 29918, 816, 11272, 29918, 3560, 29918, 1272, 29908, 13, 18884, 1723, 13, 13, 1678, 822, 1243, 29918, 657, 29918, 816, 11272, 29918, 3560, 29918, 1272, 29898, 1311, 1125, 13, 4706, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 27852, 1125, 13, 9651, 411, 13261, 29898, 1430, 29954, 8895, 29918, 14573, 29918, 8787, 29918, 29907, 9468, 1367, 3040, 29918, 29933, 11375, 11794, 29892, 1583, 29889, 29883, 5380, 403, 29918, 27852, 1125, 13, 18884, 848, 353, 1583, 29889, 2754, 29889, 657, 29918, 816, 11272, 29918, 3560, 29918, 1272, 703, 1989, 1159, 13, 18884, 1583, 29889, 9294, 3624, 3664, 8516, 29898, 1272, 29897, 13, 18884, 1583, 29889, 27852, 29889, 657, 29918, 3318, 29889, 9294, 29918, 13998, 29918, 10646, 29918, 2541, 29898, 13, 462, 1678, 376, 1989, 29918, 816, 11272, 29918, 3560, 29918, 1272, 29908, 13, 18884, 1723, 13, 18884, 1583, 29889, 29883, 5380, 403, 29918, 27852, 29889, 657, 29918, 3318, 29889, 9294, 29918, 1333, 29918, 13998, 580, 13, 2 ]
setup.py
NogaOs/wit
0
168076
<reponame>NogaOs/wit from setuptools import find_packages, setup setup( name='Swit', packages=find_packages(where='Swit'), package_dir={"": "Swit"}, include_package_data=True, version='0.2', license='MIT', description='Swit is a basic open-source implementation of Git, meant for experimenting and studying Git\'s concepts and core design.', author='<NAME>', author_email='<EMAIL>', url='https://github.com/NogaOs/Swit', download_url='https://github.com/NogaOs/Swit/archive/refs/tags/v0.2.tar.gz', keywords=['git', 'version control', 'source control'], install_requires=[ 'wheel', 'loguru', 'networkx', 'matplotlib', ], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Topic :: Software Development :: Build Tools', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', ], entry_points={ 'console_scripts': ['Swit=Swit.Switter:main'], }, )
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wb/main/enumerates.py
openvinotoolkit/workbench
23
82499
""" OpenVINO DL Workbench Enumerates classes Copyright (c) 2020 Intel Corporation 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 enum from typing import Tuple, Optional class JobTypesEnum(enum.Enum): profiling_type = 'ProfilingJob' single_inference_type = 'SingleInferenceJob' int8calibration_type = 'Int8CalibrationJob' # Accuracy create_accuracy_scripts_type = 'CreateAccuracyScriptsJob' create_accuracy_bundle_type = 'CreateAccuracyBundleJob' accuracy_type = 'AccuracyJob' remote_accuracy_type = 'RemoteAccuracyJob' # Per tensor report create_per_tensor_scripts_type = 'CreatePerTensorScriptsJob' create_per_tensor_bundle_type = 'CreatePerTensorBundleJob' per_tensor_report_type = 'PerTensorReportJob' remote_per_tensor_report_type = 'RemotePerTensorReportJob' # Parent Accuracy Analysis create_annotate_dataset_scripts_type = 'CreateAnnotateDatasetScriptsJob' create_annotate_dataset_bundle_type = 'CreateAnnotateDatasetBundleJob' annotate_dataset = 'AnnotateDatasetJob' remote_annotate_dataset = 'RemoteAnnotateDatasetJob' extract_dataset_type = 'ExtractDatasetJob' extract_text_dataset_type = 'ExtractTextDatasetJob' wait_upload_dataset_type = 'WaitDatasetUploadJob' recognize_dataset_type = 'RecognizeDatasetJob' convert_dataset_type = 'ConvertDatasetJob' validate_dataset_type = 'ValidateDatasetJob' validate_text_dataset_type = 'ValidateTextDatasetJob' generate_dataset_type = 'DatasetGeneratorJob' augment_dataset_type = 'DatasetAugmentationJob' analyze_model_input_shape_type = 'AnalyzeModelInputShapeJob' wait_upload_model_type = 'WaitModelUploadJob' model_analyzer_type = 'ModelAnalyzerJob' model_optimizer_type = 'ModelOptimizerJob' model_optimizer_scan_type = 'ModelOptimizerScanJob' convert_keras_type = 'ConvertKerasJob' omz_model_download_type = 'OMZModelDownloadJob' omz_model_convert_type = 'OMZModelConvertJob' omz_model_move_type = 'OMZModelMoveJob' download_model_type = 'DownloadModelJob' deployment_manager_type = 'DeploymentManagerJob' export_project_type = 'ExportProjectJob' download_log_type = 'DownloadLogJob' export_project_report = 'ProjectReportExportJob' export_inference_report = 'InferenceReportExportJob' create_profiling_scripts_type = 'CreateProfilingScriptsJob' wait_upload_tokenizer_type = 'WaitTokenizerUploadJob' validate_tokenizer_type = 'ValidateTokenizerJob' # huggingface import_huggingface_model_type = 'ImportHuggingfaceModelJob' # Remote profiling create_profiling_bundle_type = 'CreateProfilingBundleJob' remote_profiling_type = 'RemoteProfilingJob' remote_int8_calibration_type = 'RemoteInt8CalibrationJob' # Remote INT8 calibration create_int8_calibration_scripts_type = 'CreateInt8CalibrationScriptsJob' create_int8_calibration_bundle_type = 'CreateInt8CalibrationBundleJob' create_setup_bundle_type = 'CreateSetupBundleJob' upload_artifact_to_target_type = 'UploadArtifactToTargetJob' setup_target_type = 'SetupTargetJob' get_devices_type = 'GetDevicesJob' get_system_resources_type = 'GetSystemResourcesJob' # DevCloud trigger_dev_cloud_job = 'TriggerDevCloudJob' handle_dev_cloud_profiling_sockets_job = 'HandleDevCloudProfilingSocketsJob' handle_dev_cloud_int8_calibration_sockets_job = 'HandleDevCloudInt8CalibrationJob' handle_dev_cloud_accuracy_sockets_job = 'HandleDevCloudAccuracyJob' handle_dev_cloud_dataset_annotation_sockets_job = 'HandleDevCloudDatasetAnnotationJob' handle_dev_cloud_per_tensor_sockets_job = 'HandleDevCloudPerTensorJob' parse_dev_cloud_profiling_result_job = 'ParseDevCloudProfilingResultJob' parse_dev_cloud_int8_calibration_result_job = 'ParseDevCloudInt8CalibrationResultJob' parse_dev_cloud_accuracy_result_job = 'ParseDevCloudAccuracyResultJob' parse_dev_cloud_dataset_annotation_result_job = 'ParseDevCloudDatasetAnnotationResultJob' parse_dev_cloud_per_tensor_result_job = 'ParseDevCloudPerTensorResultJob' # Accuracy visualization inference_test_image_job = 'InferenceTestImageJob' # Environment setup_environment_job = 'SetupEnvironmentJob' # Reshape Model reshape_model = 'ReshapeModelJob' create_reshape_model_scripts_job = 'CreateReshapeModelScriptsJob' # Apply model layout apply_model_layout = 'ApplyModelLayoutJob' # Deprecated winograd_tune_type = 'WinogradTuneJob' class StatusEnum(enum.Enum): queued = 'queued' running = 'running' ready = 'ready' error = 'error' cancelled = 'cancelled' archived = 'archived' warning = 'warning' class ModelDomainEnum(enum.Enum): CV = 'CV' NLP = 'NLP' class ThroughputUnitNameEnum(enum.Enum): FPS = 'FPS' SPS = 'SPS' class TaskMethodEnum(enum.Enum): classificator = 'classificator' generic = 'generic' ssd = 'ssd' tiny_yolo_v2 = 'tiny_yolo_v2' yolo_v2 = 'yolo_v2' yolo_v3 = 'yolo_v3' yolo_v4 = 'yolo_v4' tiny_yolo_v3_v4 = 'tiny_yolo_v3_v4' mask_rcnn = 'mask_rcnn' segmentation = 'segmentation' inpainting = 'inpainting' style_transfer = 'style_transfer' super_resolution = 'super_resolution' face_recognition = 'face_recognition' landmark_detection = 'landmark_detection' custom = 'custom' @classmethod def has_value(cls, value: str) -> bool: return any(value == item.value for item in cls) class AnnotationConverterEnum(enum.Enum): common_semantic_segmentation = 'common_semantic_segmentation' custom = 'REQUIRED' imagenet = 'imagenet' inpainting = 'inpainting' lfw = 'lfw' mscoco_detection = 'mscoco_detection' mscoco_mask_rcnn = 'mscoco_mask_rcnn' style_transfer = 'style_transfer' super_resolution = 'super_resolution' super_resolution_dir_based = 'super_resolution_dir_based' vgg_face = 'vgg_face' voc_detection = 'voc_detection' voc_segmentation = 'voc_segmentation' wider = 'wider' open_images_detection = 'open_images_detection' image_processing = 'image_processing' class YoloAnchorMasksEnum(enum.Enum): yolo_v3 = [[6, 7, 8], [3, 4, 5], [0, 1, 2]] yolo_v4 = [[0, 1, 2], [3, 4, 5], [6, 7, 8]] tiny_yolo_v3_v4 = [[3, 4, 5], [1, 2, 3]] class OptimizationTypesEnum(enum.Enum): inference = JobTypesEnum.profiling_type.value int8calibration = JobTypesEnum.int8calibration_type.value # Deprecated winograd_tune = JobTypesEnum.winograd_tune_type.value class SupportedFrameworksEnum(enum.Enum): openvino = 'openvino' caffe = 'caffe' caffe2 = 'caffe2' mxnet = 'mxnet' onnx = 'onnx' pytorch = 'pytorch' tf = 'tf' tf2 = 'tf2' tf2_keras = 'tf2_keras' @classmethod def get_name(cls, key: str) -> Optional[str]: _frameworks_names = { cls.openvino.value: 'OpenVINO IR', cls.caffe.value: 'Caffe', cls.caffe2.value: 'Caffe2', cls.mxnet.value: 'MXNet', cls.onnx.value: 'ONNX', cls.pytorch.value: 'PyTorch', cls.tf.value: 'TensorFlow', cls.tf2.value: 'TensorFlow 2.0', cls.tf2_keras.value: 'TensorFlow 2.0 Keras', } return _frameworks_names.get(key) class TF2FilesKeysEnum(enum.Enum): keras = 'kerasModel' saved_model_dir = 'savedModelDir' class ConfigFileNames(enum.Enum): tf_pipeline_config = 'pipeline.config' transformations_config = 'transformations_config.json' class ModelPrecisionEnum(enum.Enum): fp32 = 'FP32' fp16 = 'FP16' i8 = 'INT8' i1 = 'INT1' mixed = 'MIXED' unknown = 'UNKNOWN' class ModelColorChannelsEnum(enum.Enum): RGB = 'RGB' BGR = 'BGR' Grayscale = 'Grayscale' @staticmethod def values() -> set: return set(item.value for item in ModelColorChannelsEnum) class ArtifactTypesEnum(enum.Enum): model = 'model' project = 'project' project_report = 'project_report' inference_report = 'inference_report' deployment_package = 'deployment_package' bundle_package = 'bundle_package' log = 'log' job_bundle = 'job_bundle' remote_job_result = 'remote_job_result' class QuantizationAlgorithmEnum(enum.Enum): default = 'DefaultQuantization' accuracy_aware = 'AccuracyAwareQuantization' class QuantizationAlgorithmPresetEnum(enum.Enum): performance = 'performance' mixed = 'mixed' class ModelSourceEnum(enum.Enum): omz = 'omz' original = 'original' ir = 'ir' huggingface = 'huggingface' class TargetOSEnum(enum.Enum): ubuntu18 = 'ubuntu18' ubuntu20 = 'ubuntu20' windows = 'windows' mac = 'mac' class DeploymentTargetEnum(enum.Enum): cpu = 'CPU' gpu = 'GPU' myriad = 'VPU' hddl = 'HDDL' opencv = 'opencv' python36 = 'python3.6' python37 = 'python3.7' python38 = 'python3.8' @staticmethod def values() -> set: return set(item.value for item in DeploymentTargetEnum) @staticmethod def create(value: str) -> 'DeploymentTargetEnum': return DeploymentTargetEnum.myriad if DeploymentTargetEnum.is_myriad(value) else DeploymentTargetEnum(value) @staticmethod def get_python_targets() -> Tuple[str, ...]: python_targets = (DeploymentTargetEnum.python36, DeploymentTargetEnum.python37, DeploymentTargetEnum.python38) return tuple(python_target.value for python_target in python_targets) @staticmethod def is_myriad(device_name: str) -> bool: return device_name == 'MYRIAD' class DeploymentPackageSizesEnum(enum.Enum): ie = 24 cpu = 31.2 gpu = 16.09 myriad = 1.8 hddl = 4.8 python = 24 install_script = 0.0032 gpu_drivers = 0.012 myriad_drivers = 0.0013 @staticmethod def json(): return { 'IE_COMMON': DeploymentPackageSizesEnum.ie.value, 'TARGETS': { 'CPU': DeploymentPackageSizesEnum.cpu.value, 'GPU': DeploymentPackageSizesEnum.gpu.value, 'MYRIAD': DeploymentPackageSizesEnum.myriad.value, 'HDDL': DeploymentPackageSizesEnum.hddl.value, }, 'DRIVERS': { 'CPU': 0, 'GPU': DeploymentPackageSizesEnum.gpu_drivers.value, 'MYRIAD': DeploymentPackageSizesEnum.myriad_drivers.value, 'HDDL': 0, }, 'PYTHON': DeploymentPackageSizesEnum.python.value, 'INSTALL_SCRIPT': DeploymentPackageSizesEnum.install_script.value } STATUS_PRIORITY = { StatusEnum.queued: 0, StatusEnum.ready: 1, StatusEnum.running: 2, StatusEnum.cancelled: 3, StatusEnum.error: 4 } class DeviceTypeEnum(enum.Enum): CPU = 'CPU' GPU = 'GPU' MYRIAD = 'MYRIAD' HDDL = 'HDDL' @staticmethod def is_supported(device: str) -> bool: return device in DeviceTypeEnum.values() or DeviceTypeEnum.is_myriad(device) or DeviceTypeEnum.is_gpu(device) @staticmethod def values() -> set: return set(item.value for item in DeviceTypeEnum) @staticmethod def is_myriad(device_name: str) -> bool: return DeviceTypeEnum.MYRIAD.value in device_name @staticmethod def is_gpu(device_name: str) -> bool: return DeviceTypeEnum.GPU.value in device_name @staticmethod def is_hddl(device_name: str) -> bool: return DeviceTypeEnum.HDDL.value == device_name @staticmethod def is_vpu(device_name: str) -> bool: return DeviceTypeEnum.is_myriad(device_name) or DeviceTypeEnum.is_hddl(device_name) @staticmethod def get_device(device: str) -> str: if DeviceTypeEnum.is_myriad(device): return DeviceTypeEnum.MYRIAD.value if DeviceTypeEnum.is_gpu(device): return DeviceTypeEnum.GPU.value return device class TargetTypeEnum(enum.Enum): local = 'local' remote = 'remote' dev_cloud = 'dev_cloud' class TargetStatusEnum(enum.Enum): available = 'available' configuring = 'configuring' connecting = 'connecting' configuration_failure = 'configuration_failure' connection_failure = 'connection_failure' not_configured = 'not_configured' busy = 'busy' class PipelineTypeEnum(enum.Enum): remote_profiling = 'remote_profiling' local_profiling = 'local_profiling' dev_cloud_profiling = 'dev_cloud_profiling' local_int8_calibration = 'local_int8_calibration' remote_int8_calibration = 'remote_int8_calibration' dev_cloud_int8_calibration = 'dev_cloud_int8_calibration' create_profiling_bundle = 'create_profiling_bundle' download_log = 'download_log' download_model = 'download_model' deployment_manager = 'deployment_manager' export_project = 'export_project' setup = 'setup' ping = 'ping' inference_test_image = 'inference_test_image' upload_dataset = 'upload_dataset' upload_model = 'upload_model' upload_tokenizer = 'upload_tokenizer' download_omz_model = 'download_omz_model' export_project_report = 'export_project_report' export_inference_report = 'export_inference_report' local_accuracy = 'local_accuracy' remote_accuracy = 'remote_accuracy' dev_cloud_accuracy = 'dev_cloud_accuracy' local_per_tensor_report = 'local_per_tensor_report' remote_per_tensor_report = 'remote_per_tensor_report' dev_cloud_per_tensor_report = 'dev_cloud_per_tensor_report' local_predictions_relative_accuracy_report = 'local_predictions_relative_accuracy_report' remote_predictions_relative_accuracy_report = 'remote_predictions_relative_accuracy_report' dev_cloud_predictions_relative_accuracy_report = 'dev_cloud_predictions_relative_accuracy_report' configure_model = 'configure_model' class PipelineStageEnum(enum.Enum): accuracy = 'accuracy' # Setup Pipeline stages preparing_setup_assets = 'preparing_setup_assets' uploading_setup_assets = 'uploading_setup_assets' configuring_environment = 'configuring_environment' # Ping Pipeline stages collecting_available_devices = 'collecting_available_devices' collecting_system_information = 'collecting_system_information' # Remote Profile Pipeline stages preparing_profiling_assets = 'preparing_profiling_assets' preparing_int8_calibration_assets = 'preparing_int8_calibration_assets' preparing_accuracy_assets = 'preparing_accuracy_assets' profiling = 'profiling' getting_remote_job_result = 'getting_remote_job_result' # Download Log stage download_log = 'download_log' # Int8 calibration int8_calibration = 'int8_calibration' remote_int8_calibration = 'remote_int8_calibration' # Dataset augment_dataset = 'augment_dataset' convert_dataset = 'convert_dataset' extract_dataset = 'extract_dataset' extract_text_dataset = 'extract_text_dataset' recognize_dataset = 'recognize_dataset' validate_dataset = 'validate_dataset' validate_text_dataset = 'validate_text_dataset' wait_dataset_upload = 'wait_dataset_upload' # Export Report stages export_project_report = 'export_project_report' export_inference_report = 'export_inference_report' # Tokenizer wait_tokenizer_upload = 'wait_tokenizer_upload' validate_tokenizer = 'validate_tokenizer' # Model wait_model_upload = 'wait_model_upload' model_analyzer = 'model_analyzer' model_optimizer_scan = 'model_optimizer_scan' convert_keras_model = 'convert_keras_model' convert_model = 'convert_model' setup_environment = 'setup_environment' # Huggingface import_huggingface_model = 'import_huggingface_model', # Model Downloader download_omz_model = 'download_omz_model' convert_omz_model = 'convert_omz_model' move_omz_model = 'move_omz_model' inference_test_image = 'inference_test_image' export_project = 'export_project' preparing_reshape_model_assets = 'preparing_reshape_model_assets' reshape_model = 'reshape_model' apply_model_layout = 'apply_model_layout' class DevCloudRemoteJobTypeEnum(enum.Enum): profiling = 'profiling' calibration = 'calibration' accuracy = 'accuracy' class DevCloudAPIVersionEnum(enum.Enum): v1 = 'v1' v2 = 'v2' class BenchmarkAppReportTypesEnum(enum.Enum): no_counters = 'no_counters' average_counters = 'average_counters' class SocketNamespacesEnum(enum.Enum): accuracy = '/accuracy' feed = '/feed' database = '/database' deployment = '/deployment' download = '/download' profiling = '/profiling' inference = '/inference' optimization = '/optimization' upload = '/upload' log = '/log' remote_target = '/remote_target' create_profiling_bundle = '/create_profiling_bundle' create_int8_calibration_bundle = '/create_int8_calibration_bundle' export_project_report = '/export_project_report' export_inference_report = '/export_inference_report' export_project = '/export_project' configure_model = '/configure_model' class SocketEventsEnum(enum.Enum): connect = 'connect' accuracy = 'accuracy' dump = 'dump' events = 'events' deployment = 'deployment' download = 'download' profiling = 'profiling' int8 = 'int8' dataset = 'dataset' model = 'model' tokenizer = 'tokenizer' setup_target = 'setup_target' ping_target = 'ping_target' create_profiling_bundle = 'create_profiling_bundle' create_int8_calibration_bundle = 'create_int8_calibration_bundle' inference_test_image = 'inference_test_image' configure_model = 'configure_model' class SSHAuthStatusCodeEnum(enum.Enum): SSH_AUTH_ERROR = 7001 INCORRECT_USERNAME = 7002 TIMEOUT = 7003 INCORRECT_HOSTNAME_PORT = 7004 INCORRECT_KEY = 7005 INCORRECT_KEY_CONTENT = 7006 INCORRECT_KEY_NAME = 7007 class SSHAuthStatusMessagesEnum(enum.Enum): SSH_AUTH_ERROR = 'ssh_auth_error' INCORRECT_USERNAME = 'incorrect_username' TIMEOUT = 'timeout' INCORRECT_HOSTNAME_PORT = 'incorrect_hostname_port' INCORRECT_KEY = 'incorrect_key' INCORRECT_KEY_CONTENT = 'incorrect_key_content' INCORRECT_KEY_NAME = 'incorrect_key_name' class RemoteSetupStatusMessagesEnum(enum.Enum): NO_PYTHON = 'no_python' PYTHON_VERSION_ERROR = 'python_version_error' OS_VERSION_ERROR = 'os_version_error' NO_INTERNET_CONNECTION = 'no_internet_connection' PIP_VERSION_ERROR = 'pip_version_error' NO_ROOT_WARNING = 'no_root_warning' NO_SUDO_WARNING = 'no_sudo_warning' class RemoteSetupStatusCodeEnum(enum.Enum): PYTHON_VERSION_ERROR = 8001 OS_VERSION_ERROR = 8002 NO_INTERNET_CONNECTION = 8003 PIP_VERSION_ERROR = 8004 NO_PYTHON = 8005 class ModelAnalyzerErrorMessagesEnum(enum.Enum): DEPRECATED_IR_VERSION = 'deprecated_ir_version' class CPUPlatformTypeEnum(enum.Enum): celeron = 'celeron' atom = 'atom' pentium = 'pentium' core = 'core' xeon = 'xeon' not_recognized = 'not_recognized' @classmethod def _missing_(cls, unused_value: str) -> 'CPUPlatformTypeEnum': return CPUPlatformTypeEnum.not_recognized class AcceptableFileSizesMb(enum.Enum): MODEL = 4500 DATASET = 10000 TOKENIZER = 5000 SSH_KEY = 1 class CeleryTaskSupportedSignal(enum.Enum): SIGTERM = 'SIGTERM' SIGKILL = 'SIGKILL' SIGHUP = 'SIGHUP' class TestInferVisualizationTypesEnum(enum.Enum): explain = 'explain' ref_visualization = 'ref_visualization' default = 'default' class AccuracyReportTypeEnum(enum.Enum): parent_model_per_tensor = 'parent_model_per_tensor' parent_model_predictions = 'parent_model_predictions' dataset_annotations = 'dataset_annotations' class CSVDatasetSeparatorEnum(enum.Enum): tab = '\t' comma = ',' semicolon = ';' colon = ':' pipe = '|' class ModelShapeTypeEnum(enum.Enum): static = 'static' dynamic = 'dynamic' class DatumaroModesEnum(enum.Enum): convert = 'convert' detect_format = 'detect-format' class TokenizerTypeEnum(enum.Enum): wordpiece = 'wordpiece' BPE = 'BPE' class OpenVINOWheelsEnum(enum.Enum): ov_runtime_wheel = 'ov_runtime_wheel' ov_dev_wheel = 'ov_dev_wheel' class LayoutDimValuesEnum(enum.Enum): N = 'N' C = 'C' H = 'H' W = 'W' D = 'D' S = 'S' OTHER = '?'
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src/szz/map_bugs2snapshot/get_sha_pairs_from_deleted_linums.py
dSar-UVA/repoMiner
9
97437
import pandas, sys data_dir = sys.argv[1] + '/' project_name = sys.argv[2] deleted_lines_filename = data_dir + 'lines_deleted_in_bf_shas/' + project_name + '.buggylines' df = pandas.read_csv(deleted_lines_filename) df = df[['bf_sha', 'bi_sha']] grouped = df.groupby(['bf_sha', 'bi_sha']) index = [gp_keys[0] for gp_keys in grouped.groups.values()] unique_df = df.reindex(index) result_filename = data_dir + 'lines_deleted_in_bf_shas/' + project_name + '.pairs' unique_df.to_csv(result_filename, columns=['bf_sha', 'bi_sha'], index=False)
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sdk/python/pulumi_azure/ad/service_principal_password.py
Frassle/pulumi-azure
0
121342
# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import pulumi import pulumi.runtime from .. import utilities, tables class ServicePrincipalPassword(pulumi.CustomResource): """ Manages a Password associated with a Service Principal within Azure Active Directory. -> **NOTE:** If you're authenticating using a Service Principal then it must have permissions to both `Read and write all applications` and `Sign in and read user profile` within the `Windows Azure Active Directory` API. """ def __init__(__self__, __name__, __opts__=None, end_date=None, key_id=None, service_principal_id=None, start_date=None, value=None): """Create a ServicePrincipalPassword resource with the given unique name, props, and options.""" if not __name__: raise TypeError('Missing resource name argument (for URN creation)') if not isinstance(__name__, str): raise TypeError('Expected resource name to be a string') if __opts__ and not isinstance(__opts__, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') __props__ = dict() if not end_date: raise TypeError('Missing required property end_date') __props__['end_date'] = end_date __props__['key_id'] = key_id if not service_principal_id: raise TypeError('Missing required property service_principal_id') __props__['service_principal_id'] = service_principal_id __props__['start_date'] = start_date if not value: raise TypeError('Missing required property value') __props__['value'] = value super(ServicePrincipalPassword, __self__).__init__( 'azure:ad/servicePrincipalPassword:ServicePrincipalPassword', __name__, __props__, __opts__) def translate_output_property(self, prop): return tables._CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return tables._SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop
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subjects/code_only/CodeOnly.py
ytyaru/Python.pylangstudy.Subjects.Template.201705221143
0
1604123
<reponame>ytyaru/Python.pylangstudy.Subjects.Template.201705221143 #!python3 #encoding: utf-8 import HtmlWrapper import HeaderNavi #import Breadcrumbs #import MetaNavi import NextPrevNavi class HeaderNavi(object): def __init__(self): nav_head = HeaderNavi.HeaderNavi(directional_icon_type='FontAwesome') nav_next = NextPrevNavi.NextPrevNavi() def CreateHtml(self): return self.__CreateHeaderNavi() + '\n\n' + self.__CreateNextPrevNavi()
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main.py
tmespe/linkedin_adder
0
197614
import os import time from dotenv import load_dotenv from selenium import webdriver from selenium.common.exceptions import NoSuchElementException, ElementClickInterceptedException load_dotenv() driver = webdriver.Firefox() LOGIN_URL = "https://www.linkedin.com/login?fromSignIn=true&trk=guest_homepage-basic_nav-header-signin" user_name = os.getenv("USER_NAME") password = <PASSWORD>("PASSWORD") def sign_in(user_name=user_name, password=password): """ Logs in to linkedin with username and password from arguments using selenium :param user_name: Linkedin username :param password: Linkedin password :return: None """ driver.get(LOGIN_URL) username_field = driver.find_element_by_xpath('//*[@id="username"]') username_field.send_keys(user_name) password_field = driver.find_element_by_xpath('//*[@id="password"]') password_field.send_keys(password) sign_in_button = driver.find_element_by_xpath('/html/body/div/main/div[3]/div[1]/form/div[3]/button') sign_in_button.click() def connect(): """ Opens a linkedin page using selenium and checks if connect button is clickable. If the button is clickable an invitation to connect is sent. If the button is not present and clickable prints message that person is most likely added. :return: None """ name_xpath = "/html/body/div[7]/div[3]/div/div/div/div/div[3]/div/div/main/div/section[1]/div[2]/div[2]/div/div[1]/h1" try: # Set Xpath paths for name, connect button and send button pop-up name = driver.find_element_by_xpath(name_xpath) connect_xpath = '//*[@data-control-name="connect"]' send_xpath = "/html/body/div[3]/div/div/div[3]/button[2]/span" # Waits for page to load connect_button = driver.find_element_by_xpath(connect_xpath) time.sleep(1) connect_button.click() time.sleep(1) send_button = driver.find_element_by_xpath(send_xpath) send_button.click() print(f"Successfully connected with {name.text}") except (NoSuchElementException, ElementClickInterceptedException) as e: name = driver.find_element_by_xpath(name_xpath) print(f"{name.text} is probably already added or error occurred. See following debug {e}") def main(): with open("linkedin_urls.txt", "r") as linkedin_urls: urls = linkedin_urls.read().splitlines() sign_in() for url in urls: driver.get(url) connect() time.sleep(1) main()
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nova/tests/servicegroup/test_zk_driver.py
vmthunder/nova
7
8838
# Copyright (c) AT&T 2012-2013 <NAME> <<EMAIL>> # Copyright 2012 IBM Corp. # # 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. """Test the ZooKeeper driver for servicegroup. You need to install ZooKeeper locally and related dependencies to run the test. It's unclear how to install python-zookeeper lib in venv so you might have to run the test without it. To set up in Ubuntu 12.04: $ sudo apt-get install zookeeper zookeeperd python-zookeeper $ sudo pip install evzookeeper $ nosetests nova.tests.servicegroup.test_zk_driver """ import eventlet from nova import servicegroup from nova import test class ZKServiceGroupTestCase(test.NoDBTestCase): def setUp(self): super(ZKServiceGroupTestCase, self).setUp() servicegroup.API._driver = None from nova.servicegroup.drivers import zk self.flags(servicegroup_driver='zk') self.flags(address='localhost:2181', group="zookeeper") try: zk.ZooKeeperDriver() except ImportError: self.skipTest("Unable to test due to lack of ZooKeeper") def test_join_leave(self): self.servicegroup_api = servicegroup.API() service_id = {'topic': 'unittest', 'host': 'serviceA'} self.servicegroup_api.join(service_id['host'], service_id['topic']) self.assertTrue(self.servicegroup_api.service_is_up(service_id)) self.servicegroup_api.leave(service_id['host'], service_id['topic']) # make sure zookeeper is updated and watcher is triggered eventlet.sleep(1) self.assertFalse(self.servicegroup_api.service_is_up(service_id)) def test_stop(self): self.servicegroup_api = servicegroup.API() service_id = {'topic': 'unittest', 'host': 'serviceA'} pulse = self.servicegroup_api.join(service_id['host'], service_id['topic'], None) self.assertTrue(self.servicegroup_api.service_is_up(service_id)) pulse.stop() eventlet.sleep(1) self.assertFalse(self.servicegroup_api.service_is_up(service_id))
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src/status_node.py
Faust-Wang/vswarm
21
1498
#!/usr/bin/env python3 from __future__ import absolute_import, division, print_function import curses import sys from collections import deque from datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c: 0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ == '__main__': main()
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packages/submodopt/submodopt/__init__.py
toruurakawa/DiPS
75
57882
<filename>packages/submodopt/submodopt/__init__.py<gh_stars>10-100 """submodopt - A package for maximizing submodular functions""" __version__ = '0.1.0' __author__ = '<NAME> <<EMAIL>>' __all__ = []
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tests/mysensors-display.py
paulino/home-assistant-text-display
0
193729
""" Testing "gatewayserial.ino" at examples folder Dep: - https://github.com/theolind/pymysensors - pip3 install pymysensors) Raw commands using mysensors serial API (https://www.mysensors.org/download/serial_api_20) DISPLAY_OFF: 0;1;1;0;47;10 DISPLAY_ON: 0;1;1;0;47;11 CURSOR_OFF: 0;1;1;0;47;20 """ import mysensors.mysensors as mysensors import time import sys SERIAL_PORT="/dev/ttyUSB0" DISPLAY_CLEAR = '30' DISPLAY_ON = '11' DISPLAY_OFF = '10' BACKLIGHT = '1' # + 1 byte (1 .. 8) CURSOR_ON = '21' CURSOR_OFF = '20' BLINK_CURSOR_ON = '40' BLINK_CURSOR_OFF = '41' def event_callback(msg): """Callback for mysensors updates.""" print('MSG | '\ ' NodeId: {} | ChildId: {} | Type:{}'.format( msg.node_id,msg.child_id,msg.type) ) GATEWAY = mysensors.SerialGateway( port = SERIAL_PORT, baud = 115200, event_callback = event_callback, protocol_version='2.2') GATEWAY.start() # To set sensor 1, child 1, sub-type V_LIGHT (= 2), with value 1. print("Wait for gateway ...") time.sleep(2) print("Sensors detected: {}".format(len(GATEWAY.sensors))) is_sensor = GATEWAY.is_sensor(0,1) # Check if there is a sensor print('Check for a valid sensor at node 0 child 1: {}'.format(is_sensor)) ### Start Test print("Clear Screen ...") GATEWAY.set_child_value(0, 1, 47, DISPLAY_CLEAR) time.sleep(2) print("Display OFF ...") GATEWAY.set_child_value(0, 1, 47, DISPLAY_OFF) time.sleep(2) print("Display ON ...") GATEWAY.set_child_value(0, 1, 47, DISPLAY_ON) time.sleep(2) print("Set BACKLIGHT 0 ...") GATEWAY.set_child_value(0, 1, 47, BACKLIGHT + '0') time.sleep(2) print("Set BACKLIGHT 1 ...") GATEWAY.set_child_value(0, 1, 47, BACKLIGHT + '1') time.sleep(2) print("Set BACKLIGHT 5 ...") GATEWAY.set_child_value(0, 1, 47, BACKLIGHT + '5') time.sleep(2) col = 0 counter = 0 while True: time.sleep(1) counter = counter + 1 print("Set CURSOR_OFF ") GATEWAY.set_child_value(0, 1, 47, CURSOR_OFF) GATEWAY.set_child_value(0, 1, 47, BLINK_CURSOR_OFF) time.sleep(2) print("Send Hello at row 0 col 0") GATEWAY.set_child_value(0, 1, 47, "AAHello at line 1") print("Send text to row 1 col 1") GATEWAY.set_child_value(0, 1, 47, "BBRow 2") print("Send counter to row 2 col 10") GATEWAY.set_child_value(0, 1, 47, "KCCount:{}".format(counter)) print("Moving text") text = chr(ord('A') + col) + 'D <move> ' GATEWAY.set_child_value(0, 1, 47, text) time.sleep(2) print("Set CURSOR_ON ") GATEWAY.set_child_value(0, 1, 47, CURSOR_ON) if col < 10: col = col +1 else: col = 0 time.sleep(5) # Wait before clear screen @BUG print("Clear screen") GATEWAY.set_child_value(0, 1, 47, DISPLAY_CLEAR)
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2 ]
flask_api_server/api_server.py
gdcrocx/CiscoDevNetHackathonToronto
0
101283
from flask import Flask, render_template, request, redirect, url_for from bson import ObjectId from pymongo import MongoClient import os app = Flask(__name__) title = "Paste-Wise" heading = "Paste-Wise Dashboard" mongoClient = MongoClient("mongodb://10.4.64.209:27017") # host uri dbObject = mongoClient.webex_teams # Select the database dbCollection = dbObject.paste_log # Select the collection name def redirect_url(): return request.args.get('next') or \ request.referrer or \ url_for('index') @app.route("/") def allLogs(): logItem = dbCollection.find() return render_template('index.html', mode="get", logs=logItem, t=title, h=heading) @app.route("/<string:log_id>", methods=['GET']) def getLog(log_id): logItem = dbCollection.find({"_id": ObjectId(log_id) }) return render_template('index.html', mode="get", logs=logItem, t=title, h=heading) @app.route("/<string:log_id>", methods=['DELETE']) def deleteLog(log_id): logItem = dbCollection.find_one_and_delete({"_id": ObjectId(log_id) }) return render_template('index.html', mode="delete", logs=logItem, t=title, h=heading) # @app.route('/todo/api/v1.0/tasks/<int:task_id>', methods=['DELETE']) # def delete_task(task_id): # task = [task for task in tasks if task['id'] == task_id] # if len(task) == 0: # abort(404) # tasks.remove(task[0]) # return jsonify({'result': True}) if __name__ == "__main__": app.run(host= '0.0.0.0', port=3010)
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hello_app/migrations/0002_auto_20160321_0846.py
Lessica/StatusHub
0
148663
<reponame>Lessica/StatusHub # -*- coding: utf-8 -*- # Generated by Django 1.9.2 on 2016-03-21 08:46 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('hello_app', '0001_initial'), ] operations = [ migrations.RenameField( model_name='resphostmodel', old_name='expected_method', new_name='match_method', ), migrations.RemoveField( model_name='resphostmodel', name='expected_contents', ), migrations.AddField( model_name='resphostmodel', name='expected_body', field=models.TextField(blank=True), ), migrations.AddField( model_name='resphostmodel', name='expected_headers', field=models.TextField(blank=True), ), ]
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create_sp_model.py
pwldj/nls
0
99910
<reponame>pwldj/nls import sentencepiece as spm import os dir = 'raw_data' files = os.listdir(dir) files = ','.join([dir+'/'+x for x in files]) spm.SentencePieceTrainer.train(input='raw_data/0_wiki_en.txt', model_prefix='30k_spm', vocab_size=32000, input_sentence_size=3000000, shuffle_input_sentence=True, unk_piece='[UNK]', pad_piece='[PAD]', user_defined_symbols=['[CLS]', '[SEP]', '[MASK]'])
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threads/migrations/0002_auto_20170909_1106.py
GunnerJnr/we_are_social_project
4
125461
# -*- coding: utf-8 -*- # Generated by Django 1.11.4 on 2017-09-09 10:06 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('threads', '0001_initial'), ] operations = [ migrations.RenameField( model_name='thread', old_name='Subject', new_name='subject', ), ]
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resize_lfw.py
corganhejijun/frontal-face-trans
0
93623
from src.resize_for_train import getTrainImg DATA_SET = "datasets/lfw_trans" OUT_DIR = "datasets/lfw_resize_for_train_128" MARGIN_FILE = "datasets/lfw_resize_margin_128.txt" IMAGE_SIZE = 128 getTrainImg(DATA_SET, IMAGE_SIZE, OUT_DIR, MARGIN_FILE)
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demos/DPSRGAN/dpsrmodels/basicblock.py
hduba/MDF
1
30650
from collections import OrderedDict import torch import torch.nn as nn import torch.nn.functional as F from torch.nn import Module ''' # =================================== # Advanced nn.Sequential # reform nn.Sequentials and nn.Modules # to a single nn.Sequential # =================================== ''' def sequential(*args): if len(args) == 1: if isinstance(args[0], OrderedDict): raise NotImplementedError('sequential does not support OrderedDict input.') return args[0] # No sequential is needed. modules = [] for module in args: if isinstance(module, nn.Sequential): for submodule in module.children(): modules.append(submodule) elif isinstance(module, nn.Module): modules.append(module) return nn.Sequential(*modules) ''' # =================================== # Useful blocks # -------------------------------- # conv (+ normaliation + relu) # concat # sum # resblock (ResBlock) # resdenseblock (ResidualDenseBlock_5C) # resinresdenseblock (RRDB) # =================================== ''' # ------------------------------------------------------- # return nn.Sequantial of (Conv + BN + ReLU) # ------------------------------------------------------- def conv(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CBR'): L = [] for t in mode: if t == 'C': L.append(nn.Conv2d(in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias)) elif t == 'T': L.append(nn.ConvTranspose2d(in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias)) elif t == 'B': L.append(nn.BatchNorm2d(out_channels, momentum=0.9, eps=1e-04, affine=True)) elif t == 'I': L.append(nn.InstanceNorm2d(out_channels, affine=True)) elif t == 'R': L.append(nn.ReLU(inplace=True)) elif t == 'r': L.append(nn.ReLU(inplace=False)) elif t == 'L': L.append(nn.LeakyReLU(negative_slope=1e-1, inplace=True)) elif t == 'l': L.append(nn.LeakyReLU(negative_slope=1e-1, inplace=False)) elif t == '2': L.append(nn.PixelShuffle(upscale_factor=2)) elif t == '3': L.append(nn.PixelShuffle(upscale_factor=3)) elif t == '4': L.append(nn.PixelShuffle(upscale_factor=4)) elif t == 'U': L.append(nn.Upsample(scale_factor=2, mode='nearest')) elif t == 'u': L.append(nn.Upsample(scale_factor=3, mode='nearest')) elif t == 'M': L.append(nn.MaxPool2d(kernel_size=kernel_size, stride=stride, padding=0)) elif t == 'A': L.append(nn.AvgPool2d(kernel_size=kernel_size, stride=stride, padding=0)) else: raise NotImplementedError('Undefined type: '.format(t)) return sequential(*L) class MeanShift(nn.Conv2d): def __init__(self, rgb_range=255, rgb_mean=(0.4488, 0.4371, 0.4040), rgb_std=(1.0, 1.0, 1.0), sign=-1): super(MeanShift, self).__init__(3, 3, kernel_size=1) std = torch.Tensor(rgb_std) self.weight.data = torch.eye(3).view(3, 3, 1, 1) / std.view(3, 1, 1, 1) self.bias.data = sign * rgb_range * torch.Tensor(rgb_mean) / std for p in self.parameters(): p.requires_grad = False # ------------------------------------------------------- # Concat the output of a submodule to its input # ------------------------------------------------------- class ConcatBlock(nn.Module): def __init__(self, submodule): super(ConcatBlock, self).__init__() self.sub = submodule def forward(self, x): output = torch.cat((x, self.sub(x)), dim=1) return output def __repr__(self): return self.sub.__repr__() + 'concat' # ------------------------------------------------------- # Elementwise sum the output of a submodule to its input # ------------------------------------------------------- class ShortcutBlock(nn.Module): def __init__(self, submodule): super(ShortcutBlock, self).__init__() self.sub = submodule def forward(self, x): output = x + self.sub(x) return output def __repr__(self): tmpstr = 'Identity + \n|' modstr = self.sub.__repr__().replace('\n', '\n|') tmpstr = tmpstr + modstr return tmpstr # ------------------------------------------------------- # Res Block: x + conv(relu(conv(x))) # ------------------------------------------------------- class ResBlock(nn.Module): def __init__(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC'): super(ResBlock, self).__init__() assert in_channels == out_channels, 'Only support in_channels==out_channels.' if mode[0] in ['R','L']: mode = mode[0].lower() + mode[1:] self.res = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode) def forward(self, x): res = self.res(x) return x + res # ------------------------------------------------------- # Channel Attention (CA) Layer # ------------------------------------------------------- class CALayer(nn.Module): def __init__(self, channel=64, reduction=16): super(CALayer, self).__init__() self.avg_pool = nn.AdaptiveAvgPool2d(1) self.conv_fc = nn.Sequential( nn.Conv2d(channel, channel // reduction, 1, padding=0, bias=True), nn.ReLU(inplace=True), nn.Conv2d(channel // reduction, channel, 1, padding=0, bias=True), nn.Sigmoid() ) def forward(self, x): y = self.avg_pool(x) y = self.conv_fc(y) return x * y # ------------------------------------------------------- # Residual Channel Attention Block (RCAB) # ------------------------------------------------------- class RCABlock(nn.Module): def __init__(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC', reduction=16): super(RCABlock, self).__init__() assert in_channels == out_channels, 'Only support in_channels==out_channels.' if mode[0] in ['R','L']: mode = mode[0].lower() + mode[1:] self.res = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode) self.ca = CALayer(out_channels, reduction) def forward(self, x): res = self.res(x) res = self.ca(res) return res + x # ------------------------------------------------------- # Residual Channel Attention Group (RG) # ------------------------------------------------------- class RCAGroup(nn.Module): def __init__(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC', reduction=16, nb=12): super(RCAGroup, self).__init__() assert in_channels == out_channels, 'Only support in_channels==out_channels.' if mode[0] in ['R','L']: mode = mode[0].lower() + mode[1:] RG = [RCABlock(in_channels, out_channels, kernel_size, stride, padding, bias, mode, reduction) for _ in range(nb)] RG.append(conv(out_channels, out_channels, mode='C')) self.rg = nn.Sequential(*RG) # self.rg = ShortcutBlock(nn.Sequential(*RG)) def forward(self, x): res = self.rg(x) return res + x # ------------------------------------------------------- # Residual Dense Block # style: 5 convs # ------------------------------------------------------- class ResidualDenseBlock_5C(nn.Module): def __init__(self, nc=64, gc=32, kernel_size=3, stride=1, padding=1, bias=True, mode='CR'): super(ResidualDenseBlock_5C, self).__init__() # gc: growth channel self.conv1 = conv(nc, gc, kernel_size, stride, padding, bias, mode) self.conv2 = conv(nc+gc, gc, kernel_size, stride, padding, bias, mode) self.conv3 = conv(nc+2*gc, gc, kernel_size, stride, padding, bias, mode) self.conv4 = conv(nc+3*gc, gc, kernel_size, stride, padding, bias, mode) self.conv5 = conv(nc+4*gc, nc, kernel_size, stride, padding, bias, mode[:-1]) def forward(self, x): x1 = self.conv1(x) x2 = self.conv2(torch.cat((x, x1), 1)) x3 = self.conv3(torch.cat((x, x1, x2), 1)) x4 = self.conv4(torch.cat((x, x1, x2, x3), 1)) x5 = self.conv5(torch.cat((x, x1, x2, x3, x4), 1)) return x5.mul_(0.2) + x # ------------------------------------------------------- # Residual in Residual Dense Block # 3x5c # ------------------------------------------------------- class RRDB(nn.Module): def __init__(self, nc=64, gc=32, kernel_size=3, stride=1, padding=1, bias=True, mode='CR'): super(RRDB, self).__init__() self.RDB1 = ResidualDenseBlock_5C(nc, gc, kernel_size, stride, padding, bias, mode) self.RDB2 = ResidualDenseBlock_5C(nc, gc, kernel_size, stride, padding, bias, mode) self.RDB3 = ResidualDenseBlock_5C(nc, gc, kernel_size, stride, padding, bias, mode) def forward(self, x): out = self.RDB1(x) out = self.RDB2(out) out = self.RDB3(out) return out.mul_(0.2) + x ''' # ====================== # Upsampler # ====================== ''' # ------------------------------------------------------- # conv + subp + relu # ------------------------------------------------------- def upsample_pixelshuffle(in_channels=64, out_channels=3, kernel_size=3, stride=1, padding=1, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3', '4'], 'mode examples: 2, 2R, 2BR, 3, ..., 4BR.' up1 = conv(in_channels, out_channels * (int(mode[0]) ** 2), kernel_size, stride, padding, bias, mode='C'+mode) return up1 # ------------------------------------------------------- # nearest_upsample + conv + relu # ------------------------------------------------------- def upsample_upconv(in_channels=64, out_channels=3, kernel_size=3, stride=1, padding=1, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3'], 'mode examples: 2, 2R, 2BR, 3, ..., 3BR.' if mode[0] == '2': uc = 'UC' elif mode[0] == '3': uc = 'uC' mode = mode.replace(mode[0], uc) up1 = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode=mode) return up1 # ------------------------------------------------------- # convTranspose + relu # ------------------------------------------------------- def upsample_convtranspose(in_channels=64, out_channels=3, kernel_size=2, stride=2, padding=0, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3', '4'], 'mode examples: 2, 2R, 2BR, 3, ..., 4BR.' kernel_size = int(mode[0]) stride = int(mode[0]) mode = mode.replace(mode[0], 'T') up1 = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode) return up1 ''' # ====================== # Downsampler # ====================== ''' # ------------------------------------------------------- # strideconv + relu # ------------------------------------------------------- def downsample_strideconv(in_channels=64, out_channels=64, kernel_size=2, stride=2, padding=0, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3', '4'], 'mode examples: 2, 2R, 2BR, 3, ..., 4BR.' kernel_size = int(mode[0]) stride = int(mode[0]) mode = mode.replace(mode[0], 'C') down1 = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode) return down1 # ------------------------------------------------------- # maxpooling + conv + relu # ------------------------------------------------------- def downsample_maxpool(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=0, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3'], 'mode examples: 2, 2R, 2BR, 3, ..., 3BR.' kernel_size_pool = int(mode[0]) stride_pool = int(mode[0]) mode = mode.replace(mode[0], 'MC') pool = conv(kernel_size=kernel_size_pool, stride=stride_pool, mode=mode[0]) pool_tail = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode=mode[1:]) return sequential(pool, pool_tail) # ------------------------------------------------------- # averagepooling + conv + relu # ------------------------------------------------------- def downsample_avgpool(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='2R'): assert len(mode)<4 and mode[0] in ['2', '3'], 'mode examples: 2, 2R, 2BR, 3, ..., 3BR.' kernel_size_pool = int(mode[0]) stride_pool = int(mode[0]) mode = mode.replace(mode[0], 'AC') pool = conv(kernel_size=kernel_size_pool, stride=stride_pool, mode=mode[0]) pool_tail = conv(in_channels, out_channels, kernel_size, stride, padding, bias, mode=mode[1:]) return sequential(pool, pool_tail)
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448, 2683, 2683, 2683, 22158, 13, 29937, 6588, 10109, 292, 718, 7602, 718, 1104, 29884, 13, 29937, 448, 2683, 2683, 2683, 22158, 13, 1753, 1623, 11249, 29918, 485, 29887, 10109, 29898, 262, 29918, 305, 12629, 29922, 29953, 29946, 29892, 714, 29918, 305, 12629, 29922, 29953, 29946, 29892, 8466, 29918, 2311, 29922, 29941, 29892, 380, 2426, 29922, 29896, 29892, 7164, 29922, 29896, 29892, 24003, 29922, 5574, 29892, 4464, 2433, 29906, 29934, 29374, 13, 1678, 4974, 7431, 29898, 8513, 29897, 29966, 29946, 322, 4464, 29961, 29900, 29962, 297, 6024, 29906, 742, 525, 29941, 7464, 525, 8513, 6455, 29901, 29871, 29906, 29892, 29871, 29906, 29934, 29892, 29871, 29906, 15176, 29892, 29871, 29941, 29892, 2023, 29892, 29871, 29941, 15176, 6169, 13, 1678, 8466, 29918, 2311, 29918, 10109, 353, 938, 29898, 8513, 29961, 29900, 2314, 13, 1678, 380, 2426, 29918, 10109, 353, 938, 29898, 8513, 29961, 29900, 2314, 13, 1678, 4464, 353, 4464, 29889, 6506, 29898, 8513, 29961, 29900, 1402, 525, 2477, 1495, 13, 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bot/utils/dma_api.py
webhp/discord-moderator-wumpus
0
186214
<reponame>webhp/discord-moderator-wumpus<gh_stars>0 import functools import re import textwrap import aiohttp from bs4 import BeautifulSoup from loguru import logger from bot.constants import DMA_API_URL, DMA_TITLE_REGEX def get_api(): def wrapper(func): @functools.wraps(func) async def wrapped(search): try: async with aiohttp.ClientSession() as sess: response = await sess.get(DMA_API_URL) response.raise_for_status() data = await response.json() articles = data["articles"] articles_parse = [] for item in articles: if re.search(DMA_TITLE_REGEX, item["name"]): article = {} # Article number, name = item["name"].split(": ") article["series"] = number[0] article["category"] = number[1] article["digit"] = number[2] article["name"] = name soup = BeautifulSoup(item["body"], "html.parser") placeholder = ( f"... [continue reading](https://dis.gd/dma{number})" ) article["text"] = textwrap.shorten( soup.p.text, 800, placeholder=placeholder ) articles_parse.append(article) except Exception: logger.exception("Error fetching information from DMA") return await func(search, articles_parse) return wrapped return wrapper @get_api() async def get_article(number, articles): return [ item for item in articles if item["series"] == str(number)[0] and item["category"] == str(number)[1] and item["digit"] == str(number)[2] ] @get_api() async def get_series(series, articles): return [item for item in articles if item["series"] == str(series)] @get_api() async def get_category(category, articles): return [item for item in articles if item["category"] == str(category)] @get_api() async def search_term(term, articles): return [ item for item in articles if term.lower() in item["text"].lower() or term.lower() in item["name"].lower() ]
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trio/_core/tests/test_multierror.py
JefffHofffman/trio
4
14733
<gh_stars>1-10 import logging import pytest from traceback import extract_tb, print_exception, format_exception, _cause_message import sys import os import re from pathlib import Path import subprocess from .tutil import slow from .._multierror import MultiError, concat_tb from ..._core import open_nursery class NotHashableException(Exception): code = None def __init__(self, code): super().__init__() self.code = code def __eq__(self, other): if not isinstance(other, NotHashableException): return False return self.code == other.code async def raise_nothashable(code): raise NotHashableException(code) def raiser1(): raiser1_2() def raiser1_2(): raiser1_3() def raiser1_3(): raise ValueError("raiser1_string") def raiser2(): raiser2_2() def raiser2_2(): raise KeyError("raiser2_string") def raiser3(): raise NameError def get_exc(raiser): try: raiser() except Exception as exc: return exc def get_tb(raiser): return get_exc(raiser).__traceback__ def einfo(exc): return (type(exc), exc, exc.__traceback__) def test_concat_tb(): tb1 = get_tb(raiser1) tb2 = get_tb(raiser2) # These return a list of (filename, lineno, fn name, text) tuples # https://docs.python.org/3/library/traceback.html#traceback.extract_tb entries1 = extract_tb(tb1) entries2 = extract_tb(tb2) tb12 = concat_tb(tb1, tb2) assert extract_tb(tb12) == entries1 + entries2 tb21 = concat_tb(tb2, tb1) assert extract_tb(tb21) == entries2 + entries1 # Check degenerate cases assert extract_tb(concat_tb(None, tb1)) == entries1 assert extract_tb(concat_tb(tb1, None)) == entries1 assert concat_tb(None, None) is None # Make sure the original tracebacks didn't get mutated by mistake assert extract_tb(get_tb(raiser1)) == entries1 assert extract_tb(get_tb(raiser2)) == entries2 def test_MultiError(): exc1 = get_exc(raiser1) exc2 = get_exc(raiser2) assert MultiError([exc1]) is exc1 m = MultiError([exc1, exc2]) assert m.exceptions == [exc1, exc2] assert "ValueError" in str(m) assert "ValueError" in repr(m) with pytest.raises(TypeError): MultiError(object()) with pytest.raises(TypeError): MultiError([KeyError(), ValueError]) def test_MultiErrorOfSingleMultiError(): # For MultiError([MultiError]), ensure there is no bad recursion by the # constructor where __init__ is called if __new__ returns a bare MultiError. exceptions = [KeyError(), ValueError()] a = MultiError(exceptions) b = MultiError([a]) assert b == a assert b.exceptions == exceptions async def test_MultiErrorNotHashable(): exc1 = NotHashableException(42) exc2 = NotHashableException(4242) exc3 = ValueError() assert exc1 != exc2 assert exc1 != exc3 with pytest.raises(MultiError): async with open_nursery() as nursery: nursery.start_soon(raise_nothashable, 42) nursery.start_soon(raise_nothashable, 4242) def test_MultiError_filter_NotHashable(): excs = MultiError([NotHashableException(42), ValueError()]) def handle_ValueError(exc): if isinstance(exc, ValueError): return None else: return exc filtered_excs = MultiError.filter(handle_ValueError, excs) assert isinstance(filtered_excs, NotHashableException) def test_traceback_recursion(): exc1 = RuntimeError() exc2 = KeyError() exc3 = NotHashableException(42) # Note how this creates a loop, where exc1 refers to exc1 # This could trigger an infinite recursion; the 'seen' set is supposed to prevent # this. exc1.__cause__ = MultiError([exc1, exc2, exc3]) # python traceback.TracebackException < 3.6.4 does not support unhashable exceptions # and raises a TypeError exception if sys.version_info < (3, 6, 4): with pytest.raises(TypeError): format_exception(*einfo(exc1)) else: format_exception(*einfo(exc1)) def make_tree(): # Returns an object like: # MultiError([ # MultiError([ # ValueError, # KeyError, # ]), # NameError, # ]) # where all exceptions except the root have a non-trivial traceback. exc1 = get_exc(raiser1) exc2 = get_exc(raiser2) exc3 = get_exc(raiser3) # Give m12 a non-trivial traceback try: raise MultiError([exc1, exc2]) except BaseException as m12: return MultiError([m12, exc3]) def assert_tree_eq(m1, m2): if m1 is None or m2 is None: assert m1 is m2 return assert type(m1) is type(m2) assert extract_tb(m1.__traceback__) == extract_tb(m2.__traceback__) assert_tree_eq(m1.__cause__, m2.__cause__) assert_tree_eq(m1.__context__, m2.__context__) if isinstance(m1, MultiError): assert len(m1.exceptions) == len(m2.exceptions) for e1, e2 in zip(m1.exceptions, m2.exceptions): assert_tree_eq(e1, e2) def test_MultiError_filter(): def null_handler(exc): return exc m = make_tree() assert_tree_eq(m, m) assert MultiError.filter(null_handler, m) is m assert_tree_eq(m, make_tree()) # Make sure we don't pick up any detritus if run in a context where # implicit exception chaining would like to kick in m = make_tree() try: raise ValueError except ValueError: assert MultiError.filter(null_handler, m) is m assert_tree_eq(m, make_tree()) def simple_filter(exc): if isinstance(exc, ValueError): return None if isinstance(exc, KeyError): return RuntimeError() return exc new_m = MultiError.filter(simple_filter, make_tree()) assert isinstance(new_m, MultiError) assert len(new_m.exceptions) == 2 # was: [[ValueError, KeyError], NameError] # ValueError disappeared & KeyError became RuntimeError, so now: assert isinstance(new_m.exceptions[0], RuntimeError) assert isinstance(new_m.exceptions[1], NameError) # implicit chaining: assert isinstance(new_m.exceptions[0].__context__, KeyError) # also, the traceback on the KeyError incorporates what used to be the # traceback on its parent MultiError orig = make_tree() # make sure we have the right path assert isinstance(orig.exceptions[0].exceptions[1], KeyError) # get original traceback summary orig_extracted = ( extract_tb(orig.__traceback__) + extract_tb(orig.exceptions[0].__traceback__) + extract_tb(orig.exceptions[0].exceptions[1].__traceback__) ) def p(exc): print_exception(type(exc), exc, exc.__traceback__) p(orig) p(orig.exceptions[0]) p(orig.exceptions[0].exceptions[1]) p(new_m.exceptions[0].__context__) # compare to the new path assert new_m.__traceback__ is None new_extracted = extract_tb(new_m.exceptions[0].__context__.__traceback__) assert orig_extracted == new_extracted # check preserving partial tree def filter_NameError(exc): if isinstance(exc, NameError): return None return exc m = make_tree() new_m = MultiError.filter(filter_NameError, m) # with the NameError gone, the other branch gets promoted assert new_m is m.exceptions[0] # check fully handling everything def filter_all(exc): return None assert MultiError.filter(filter_all, make_tree()) is None def test_MultiError_catch(): # No exception to catch def noop(_): pass # pragma: no cover with MultiError.catch(noop): pass # Simple pass-through of all exceptions m = make_tree() with pytest.raises(MultiError) as excinfo: with MultiError.catch(lambda exc: exc): raise m assert excinfo.value is m # Should be unchanged, except that we added a traceback frame by raising # it here assert m.__traceback__ is not None assert m.__traceback__.tb_frame.f_code.co_name == "test_MultiError_catch" assert m.__traceback__.tb_next is None m.__traceback__ = None assert_tree_eq(m, make_tree()) # Swallows everything with MultiError.catch(lambda _: None): raise make_tree() def simple_filter(exc): if isinstance(exc, ValueError): return None if isinstance(exc, KeyError): return RuntimeError() return exc with pytest.raises(MultiError) as excinfo: with MultiError.catch(simple_filter): raise make_tree() new_m = excinfo.value assert isinstance(new_m, MultiError) assert len(new_m.exceptions) == 2 # was: [[ValueError, KeyError], NameError] # ValueError disappeared & KeyError became RuntimeError, so now: assert isinstance(new_m.exceptions[0], RuntimeError) assert isinstance(new_m.exceptions[1], NameError) # Make sure that Python did not successfully attach the old MultiError to # our new MultiError's __context__ assert not new_m.__suppress_context__ assert new_m.__context__ is None # check preservation of __cause__ and __context__ v = ValueError() v.__cause__ = KeyError() with pytest.raises(ValueError) as excinfo: with MultiError.catch(lambda exc: exc): raise v assert isinstance(excinfo.value.__cause__, KeyError) v = ValueError() context = KeyError() v.__context__ = context with pytest.raises(ValueError) as excinfo: with MultiError.catch(lambda exc: exc): raise v assert excinfo.value.__context__ is context assert not excinfo.value.__suppress_context__ for suppress_context in [True, False]: v = ValueError() context = KeyError() v.__context__ = context v.__suppress_context__ = suppress_context distractor = RuntimeError() with pytest.raises(ValueError) as excinfo: def catch_RuntimeError(exc): if isinstance(exc, RuntimeError): return None else: return exc with MultiError.catch(catch_RuntimeError): raise MultiError([v, distractor]) assert excinfo.value.__context__ is context assert excinfo.value.__suppress_context__ == suppress_context def assert_match_in_seq(pattern_list, string): offset = 0 print("looking for pattern matches...") for pattern in pattern_list: print("checking pattern:", pattern) reobj = re.compile(pattern) match = reobj.search(string, offset) assert match is not None offset = match.end() def test_assert_match_in_seq(): assert_match_in_seq(["a", "b"], "xx a xx b xx") assert_match_in_seq(["b", "a"], "xx b xx a xx") with pytest.raises(AssertionError): assert_match_in_seq(["a", "b"], "xx b xx a xx") def test_format_exception(): exc = get_exc(raiser1) formatted = "".join(format_exception(*einfo(exc))) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" not in formatted assert "in raiser2_2" not in formatted assert "direct cause" not in formatted assert "During handling" not in formatted exc = get_exc(raiser1) exc.__cause__ = get_exc(raiser2) formatted = "".join(format_exception(*einfo(exc))) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" in formatted assert "in raiser2_2" in formatted assert "direct cause" in formatted assert "During handling" not in formatted # ensure cause included assert _cause_message in formatted exc = get_exc(raiser1) exc.__context__ = get_exc(raiser2) formatted = "".join(format_exception(*einfo(exc))) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" in formatted assert "in raiser2_2" in formatted assert "direct cause" not in formatted assert "During handling" in formatted exc.__suppress_context__ = True formatted = "".join(format_exception(*einfo(exc))) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" not in formatted assert "in raiser2_2" not in formatted assert "direct cause" not in formatted assert "During handling" not in formatted # chain=False exc = get_exc(raiser1) exc.__context__ = get_exc(raiser2) formatted = "".join(format_exception(*einfo(exc), chain=False)) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" not in formatted assert "in raiser2_2" not in formatted assert "direct cause" not in formatted assert "During handling" not in formatted # limit exc = get_exc(raiser1) exc.__context__ = get_exc(raiser2) # get_exc adds a frame that counts against the limit, so limit=2 means we # get 1 deep into the raiser stack formatted = "".join(format_exception(*einfo(exc), limit=2)) print(formatted) assert "raiser1_string" in formatted assert "in raiser1" in formatted assert "in raiser1_2" not in formatted assert "raiser2_string" in formatted assert "in raiser2" in formatted assert "in raiser2_2" not in formatted exc = get_exc(raiser1) exc.__context__ = get_exc(raiser2) formatted = "".join(format_exception(*einfo(exc), limit=1)) print(formatted) assert "raiser1_string" in formatted assert "in raiser1" not in formatted assert "raiser2_string" in formatted assert "in raiser2" not in formatted # handles loops exc = get_exc(raiser1) exc.__cause__ = exc formatted = "".join(format_exception(*einfo(exc))) assert "raiser1_string" in formatted assert "in raiser1_3" in formatted assert "raiser2_string" not in formatted assert "in raiser2_2" not in formatted # ensure duplicate exception is not included as cause assert _cause_message not in formatted # MultiError formatted = "".join(format_exception(*einfo(make_tree()))) print(formatted) assert_match_in_seq( [ # Outer exception is MultiError r"MultiError:", # First embedded exception is the embedded MultiError r"\nDetails of embedded exception 1", # Which has a single stack frame from make_tree raising it r"in make_tree", # Then it has two embedded exceptions r" Details of embedded exception 1", r"in raiser1_2", # for some reason ValueError has no quotes r"ValueError: raiser1_string", r" Details of embedded exception 2", r"in raiser2_2", # But KeyError does have quotes r"KeyError: 'raiser2_string'", # And finally the NameError, which is a sibling of the embedded # MultiError r"\nDetails of embedded exception 2:", r"in raiser3", r"NameError", ], formatted ) # Prints duplicate exceptions in sub-exceptions exc1 = get_exc(raiser1) def raise1_raiser1(): try: raise exc1 except: raise ValueError("foo") def raise2_raiser1(): try: raise exc1 except: raise KeyError("bar") exc2 = get_exc(raise1_raiser1) exc3 = get_exc(raise2_raiser1) try: raise MultiError([exc2, exc3]) except MultiError as e: exc = e formatted = "".join(format_exception(*einfo(exc))) print(formatted) assert_match_in_seq( [ r"Traceback", # Outer exception is MultiError r"MultiError:", # First embedded exception is the embedded ValueError with cause of raiser1 r"\nDetails of embedded exception 1", # Print details of exc1 r" Traceback", r"in get_exc", r"in raiser1", r"ValueError: raiser1_string", # Print details of exc2 r"\n During handling of the above exception, another exception occurred:", r" Traceback", r"in get_exc", r"in raise1_raiser1", r" ValueError: foo", # Second embedded exception is the embedded KeyError with cause of raiser1 r"\nDetails of embedded exception 2", # Print details of exc1 again r" Traceback", r"in get_exc", r"in raiser1", r"ValueError: raiser1_string", # Print details of exc3 r"\n During handling of the above exception, another exception occurred:", r" Traceback", r"in get_exc", r"in raise2_raiser1", r" KeyError: 'bar'", ], formatted ) def test_logging(caplog): exc1 = get_exc(raiser1) exc2 = get_exc(raiser2) m = MultiError([exc1, exc2]) message = "test test test" try: raise m except MultiError as exc: logging.getLogger().exception(message) # Join lines together formatted = "".join( format_exception(type(exc), exc, exc.__traceback__) ) assert message in caplog.text assert formatted in caplog.text def run_script(name, use_ipython=False): import trio trio_path = Path(trio.__file__).parent.parent script_path = Path(__file__).parent / "test_multierror_scripts" / name env = dict(os.environ) print("parent PYTHONPATH:", env.get("PYTHONPATH")) if "PYTHONPATH" in env: # pragma: no cover pp = env["PYTHONPATH"].split(os.pathsep) else: pp = [] pp.insert(0, str(trio_path)) pp.insert(0, str(script_path.parent)) env["PYTHONPATH"] = os.pathsep.join(pp) print("subprocess PYTHONPATH:", env.get("PYTHONPATH")) if use_ipython: lines = [script_path.open().read(), "exit()"] cmd = [ sys.executable, "-u", "-m", "IPython", # no startup files "--quick", "--TerminalIPythonApp.code_to_run=" + '\n'.join(lines), ] else: cmd = [sys.executable, "-u", str(script_path)] print("running:", cmd) completed = subprocess.run( cmd, env=env, stdout=subprocess.PIPE, stderr=subprocess.STDOUT ) print("process output:") print(completed.stdout.decode("utf-8")) return completed def check_simple_excepthook(completed): assert_match_in_seq( [ "in <module>", "MultiError", "Details of embedded exception 1", "in exc1_fn", "ValueError", "Details of embedded exception 2", "in exc2_fn", "KeyError", ], completed.stdout.decode("utf-8") ) def test_simple_excepthook(): completed = run_script("simple_excepthook.py") check_simple_excepthook(completed) def test_custom_excepthook(): # Check that user-defined excepthooks aren't overridden completed = run_script("custom_excepthook.py") assert_match_in_seq( [ # The warning "RuntimeWarning", "already have a custom", # The message printed by the custom hook, proving we didn't # override it "custom running!", # The MultiError "MultiError:", ], completed.stdout.decode("utf-8") ) # This warning is triggered by ipython 7.5.0 on python 3.8 import warnings warnings.filterwarnings( "ignore", message=".*\"@coroutine\" decorator is deprecated", category=DeprecationWarning, module="IPython.*" ) try: import IPython except ImportError: # pragma: no cover have_ipython = False else: have_ipython = True need_ipython = pytest.mark.skipif(not have_ipython, reason="need IPython") @slow @need_ipython def test_ipython_exc_handler(): completed = run_script("simple_excepthook.py", use_ipython=True) check_simple_excepthook(completed) @slow @need_ipython def test_ipython_imported_but_unused(): completed = run_script("simple_excepthook_IPython.py") check_simple_excepthook(completed) @slow @need_ipython def test_ipython_custom_exc_handler(): # Check we get a nice warning (but only one!) if the user is using IPython # and already has some other set_custom_exc handler installed. completed = run_script("ipython_custom_exc.py", use_ipython=True) assert_match_in_seq( [ # The warning "RuntimeWarning", "IPython detected", "skip installing Trio", # The MultiError "MultiError", "ValueError", "KeyError", ], completed.stdout.decode("utf-8") ) # Make sure our other warning doesn't show up assert "custom sys.excepthook" not in completed.stdout.decode("utf-8")
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jw/custom_ml.py
JoonSeongLee/dss7-coupon
0
179331
<filename>jw/custom_ml.py import warnings warnings.simplefilter(action='ignore', category=FutureWarning) import numpy as np import scipy as sp import pandas as pd import statsmodels.api as sm import statsmodels.formula.api as smf import statsmodels.stats.api as sms import sklearn as sk import matplotlib as mpl import matplotlib.pylab as plt import matplotlib.font_manager as fm from mpl_toolkits.mplot3d import Axes3D import seaborn as sns sns.set() sns.set_style("whitegrid") sns.set_color_codes() # Model from sklearn.linear_model import LogisticRegression from sklearn.linear_model import Perceptron from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis from sklearn.discriminant_analysis import LinearDiscriminantAnalysis from sklearn import svm from sklearn.naive_bayes import GaussianNB from sklearn.naive_bayes import BernoulliNB from sklearn.naive_bayes import MultinomialNB # preprocss with etc from sklearn.model_selection import train_test_split from sklearn.metrics import * from sklearn.preprocessing import label_binarize from sklearn.multiclass import OneVsRestClassifier from scipy import interp def df_to_nparray(): return 0 def cls_conf(X, y, model, test_ratio=0.5): ''' a, b = cls_conf(X,y,GaussianNB(),0.5) a, b = cls_conf(X,y,QuadraticDiscriminantAnalysis(store_covariance=True),0.5) a, b = cls_conf(X,y,LinearDiscriminantAnalysis(n_components=3, solver="svd", store_covariance=True),0.5) a, b = cls_conf(X,y,LogisticRegression(), 0.5) a, b = cls_conf(X,y,SVC(gamma=0.0026, C=10), 0.5) ''' X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_ratio, random_state=0) model = model.fit(X_train, y_train) y_pred = model.predict(X_test) return confusion_matrix(y_test, y_pred), classification_report(y_test, y_pred) def bin_roc(X,y,model,test_ratio=0.5): X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_ratio, random_state=0) classifier = model.fit(X_train, y_train) fpr, tpr, threshold = roc_curve(y_test, classifier.decision_function(X_test)) plt.figure(figsize=(10, 10)) lw = 2 plt.plot(fpr, tpr, label = 'auc area = {}'.format(auc(fpr,tpr))) plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--') plt.xlim([-0.1, 1.0]) plt.ylim([0.0, 1.05]) plt.xlabel('False Positive Rate',fontsize=20) plt.ylabel('True Positive Rate',fontsize=20) plt.title('ROC',fontsize=20) plt.legend(loc='lower right',fontsize=20) plt.show() def multi_roc(X, y, model, test_ratio=0.5): y = label_binarize(y, classes=np.unique(y)) n_classes = y.shape[1] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_ratio, random_state=0) ovr = OneVsRestClassifier(model) y_score = ovr.fit(X_train, y_train).predict_proba(X_test) fpr = dict() tpr = dict() roc_auc = dict() for i in range(n_classes): fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i]) roc_auc[i] = auc(fpr[i], tpr[i]) fpr["micro"], tpr["micro"], _ = roc_curve(y_test.ravel(), y_score.ravel()) roc_auc["micro"] = auc(fpr["micro"], tpr["micro"]) plt.figure(figsize=(10, 10)) lw = 2 for i in range(n_classes): plt.plot(fpr[i], tpr[i], lw=lw, label='class {} (auc area = {})'.format(i, roc_auc[i])) plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--') plt.xlim([-0.1, 1.0]) plt.ylim([0.0, 1.05]) plt.xlabel('False Positive Rate',fontsize=20) plt.ylabel('True Positive Rate',fontsize=20) plt.title('ROC',fontsize=20) plt.legend(loc='lower right',fontsize=20) plt.show()
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examples/PyGame/reaching_osc.py
Andrew-Luo1/ABR_Control_Prosthetic
0
1609792
""" Running the threelink arm with the pygame display. The arm will move the end-effector to the target, which can be moved by clicking on the background. """ import numpy as np from abr_control.arms import threejoint as arm # from abr_control.arms import twojoint as arm from abr_control.interfaces import PyGame from abr_control.controllers import OSC, Damping, RestingConfig # initialize our robot config robot_config = arm.Config(use_cython=True) # create our arm simulation arm_sim = arm.ArmSim(robot_config) # damp the movements of the arm damping = Damping(robot_config, kv=10) # keep the arm near a default configuration resting_config = RestingConfig( robot_config, kp=50, kv=np.sqrt(50), rest_angles=[np.pi/4, np.pi/4, None]) # create an operational space controller ctrlr = OSC(robot_config, kp=20, use_C=True, null_controllers=[damping]) def on_click(self, mouse_x, mouse_y): self.target[0] = self.mouse_x self.target[1] = self.mouse_y # create our interface interface = PyGame(robot_config, arm_sim, dt=.001, on_click=on_click) interface.connect() # create a target feedback = interface.get_feedback() target_xyz = robot_config.Tx('EE', feedback['q']) interface.set_target(target_xyz) # set up lists for tracking data ee_path = [] target_path = [] try: # run ctrl.generate once to load all functions zeros = np.zeros(robot_config.N_JOINTS) ctrlr.generate(q=zeros, dq=zeros, target_pos=np.zeros(3)) robot_config.R('EE', q=zeros) print('\nSimulation starting...\n') print('\nClick to move the target.\n') count = 0 while 1: # get arm feedback feedback = interface.get_feedback() hand_xyz = robot_config.Tx('EE', feedback['q']) # generate an operational space control signal u = ctrlr.generate( q=feedback['q'], dq=feedback['dq'], target_pos=target_xyz, target_vel=np.zeros(3)) new_target = interface.get_mousexy() if new_target is not None: target_xyz[0:2] = new_target interface.set_target(target_xyz) # apply the control signal, step the sim forward interface.send_forces( u, update_display=True if count % 50 == 0 else False) # track data ee_path.append(np.copy(hand_xyz)) target_path.append(np.copy(target_xyz)) count += 1 finally: # stop and reset the simulation interface.disconnect() print('Simulation terminated...')
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]
dspback/main.py
czcnhub/dsp
1
177128
import uvicorn as uvicorn from fastapi import FastAPI, Request, Response from fastapi.staticfiles import StaticFiles from starlette.middleware.sessions import SessionMiddleware from dspback.config import get_settings from dspback.database.models import SessionLocal from dspback.routers import authentication, repository_authorization, submissions, metadata_class app = FastAPI() app.add_middleware(SessionMiddleware, secret_key=get_settings().session_secret_key) app.mount("/api/schema", StaticFiles(directory="dspback/schemas"), name="schemas") app.include_router(authentication.router, prefix="/api", tags=["api"]) app.include_router(repository_authorization.router, prefix="/api", tags=["api"]) app.include_router(submissions.router, prefix="/api", tags=["api"]) app.include_router(metadata_class.router, prefix="/api", tags=["api"]) @app.middleware("http") async def db_session_middleware(request: Request, call_next): response = Response("Internal server error", status_code=500) try: request.state.db = SessionLocal() response = await call_next(request) finally: request.state.db.close() return response if __name__ == "__main__": uvicorn.run(app, host="0.0.0.0", port=5002)
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module/bio/queue/demux.py
moonwatcher/tubo
0
105200
<reponame>moonwatcher/tubo<filename>module/bio/queue/demux.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- import io import logging from ontology import Ontology from material import Resource from command import Command from queue import Job, Task, Scanner from queue import ResourceTask from error import * class DemuxJob(Job): def __init__(self, queue, node): Job.__init__(self, queue, node) self.log = logging.getLogger('Bio') def load(self): Job.load(self) scanner = Scanner(self.env, self.ontology) if scanner.ignored: self.node['ignored'].extend(scanner.ignored) if scanner.results: count = 0 if self.action == 'demux': # every lane is demultiplxed by a separate task # we break the fastq files into tasks by flowcell/lane breakdown = {} for location in scanner.results: if 'flowcell id' in location and 'lane number' in location: if location['flowcell id'] not in breakdown: breakdown[location['flowcell id']] = {} if location['lane number'] not in breakdown[location['flowcell id']]: breakdown[location['flowcell id']][location['lane number']] = [] breakdown[location['flowcell id']][location['lane number']].append(location) for flowcell in breakdown.values(): for lane in flowcell.values(): self.push(DemuxTask(self, self.ontology, lane)) count += 1 elif self.action == 'merge': # merge all files from different lanes but with the same nibble number breakdown = {} for location in scanner.results: if 'flowcell id' in location and 'nibble number' in location: if location['flowcell id'] not in breakdown: breakdown[location['flowcell id']] = {} if location['nibble number'] not in breakdown[location['flowcell id']]: breakdown[location['flowcell id']][location['nibble number']] = [] breakdown[location['flowcell id']][location['nibble number']].append(location) for flowcell_id, flowcell in breakdown.items(): for nibble_number in flowcell.keys(): flowcell[nibble_number] = sorted(flowcell[nibble_number], key=lambda x: x['lane number']) pattern = [':'.join([ str(x['lane number']) for x in nibble ]) for nibble in flowcell.values()] if len(set(pattern)) > 1: self.abort('not all lanes have the same number of nibbles in flowcell {}'.format(flowcell_id)) else: for nibble in flowcell.values(): self.push(MergeTask(self, self.ontology, nibble)) count += 1 elif self.action == 'filter': for location in scanner.results: self.push(FilterTask(self, self.ontology, location)) count += 1 self.log.debug('%d %s tasks queued in job %s', count, self.action, self.uuid) class DemuxTask(Task): def __init__(self, job, ontology, locations): Task.__init__(self, job, ontology) self.log = logging.getLogger('Bio') self.locations = locations self.resources = [] self.flowcell = None self.lane = None self.template = None self.node['origins'] = [] def load(self): Task.load(self) def fetch_flowcell_resource(resource): # Locate an ihrf, inrf or imrf resource we can use to get meatadata about the flowcell flowcell = None asset = self.env.resolver.resolve(resource.location['flowcell asset uri'], None, self.context) if asset is not None: for reference in asset['body']['references']: if reference['genealogy']['media kind'] == 50 \ and (reference['genealogy']['kind'] in [ 'ihrf', 'imrf', 'inrf' ]): flowcell = self.env.resolver.resolve(reference['canonical'], None, self.context) if flowcell is not None: break return flowcell # Since all resources are assumed to come from the same flowcell # pick a representing resource. representing = None if self.valid: for location in self.locations: resource = Resource.create(self.env, location, self.context) if resource is not None: self.node['origins'].append(location) self.resources.append(resource) else: self.abort('resource location is invalid:\n{}'.format(self.env.to_json(location))) if self.resources: representing = self.resources[0] else: self.abort('need at least one resource to demultiplex') if self.valid: self.flowcell = fetch_flowcell_resource(representing) if self.flowcell is None: self.abort('no suitable flowcell resource found to infer pheniqs output layout') if self.valid: if 'knowledge uri' in representing.location: if representing.knowledge: self.lane = representing.knowledge if 'pools' not in self.lane['body']: self.abort('no pools are associated with lane {}'.format(representing.location['home uri'])) else: self.abort('was unable to resolve {}'.format(representing.location['knowledge uri'])) else: self.abort('insufficient information to resolve lane from\n{}'.format(self.env.to_json(representing.location))) if self.valid: self.template = Ontology.clone(representing.location) for e in [ 'nibble number', ]: del self.template[e] self.template['media kind'] = 53 def unload(self): if self.resources: if self.valid: for resource in self.resources: resource.unload() else: del self.node['origins'] Task.unload(self) def last_fragment(self, command): return len(command.ontology['pheniqs fragment']) - 1 def write_configuration_file(self, command): def encode_pheniqs_config(ontology): node = {} for prototype in ontology.namespace.element.values(): if prototype.key in ontology: value = ontology[prototype.key] if value is not None and 'config' in prototype.node: name = prototype.node['config'] if prototype.type == 'object': if prototype.plural and value: node[name] = [ encode_pheniqs_config(e) for e in value ] else: node[name] = encode_pheniqs_config(value) elif not prototype.plural or value: node[name] = value return node node = encode_pheniqs_config(command.ontology) with io.open(command.ontology['pheniqs configuration path'], 'wb') as w: w.write(self.env.to_json(node).encode('utf8')) def reverse_complement(self, nucleotide): complement = self.env.enumeration['iupac nucleic acid notation'].element reversed = ''.join([ complement[n].node['reverse'] for n in nucleotide ][::-1]) return reversed def configure(self, pheniqs): if self.valid: for term in [ 'pheniqs barcode', 'pheniqs fragment', 'pheniqs input', 'pheniqs library', 'pheniqs output', 'pheniqs sequence' ]: if term not in pheniqs.ontology: pheniqs.ontology[term] = [] if not pheniqs.ontology['pheniqs library']: if 'nibbles' in self.flowcell['body']['flowcell'] and self.flowcell['body']['flowcell']['nibbles']: # append a new fragment spanning the entire nibble for each non index nibble # than add a library output contaning just that fragment for nibble in self.flowcell['body']['flowcell']['nibbles']: if not nibble['index nibble']: pheniqs.ontology['pheniqs fragment'].append('{}:0:'.format(nibble['nibble number'] - 1)) pheniqs.ontology['pheniqs library'].append(str(self.last_fragment(pheniqs))) if not pheniqs.ontology['pheniqs library']: self.abort('could not find any non index nibbles to write') # Add all task resources as pheniqs inputs if self.valid: for input in self.resources: pheniqs.ontology['pheniqs input'].append(input.path) if self.valid: for pool in self.lane['body']['pools']: if 'pool barcodes' in pool: pool['pool barcodes'].sort(key=lambda i: i['barcode index']) if 'samples' in pool: for sample in pool['samples']: if 'library' in sample: library = sample['library'] if library['barcodes']: for index,barcode in enumerate(library['barcodes']): nucleotide = barcode['barcode sequence'] # reverse complement the barcode if needed if ('pool barcodes' in pool and \ index < len(pool['pool barcodes']) and \ 'barcode reverse complement' in pool['pool barcodes'][index] and \ pool['pool barcodes'][index]['barcode reverse complement']): reversed = self.reverse_complement(nucleotide) self.log.debug('reverse complementing %s to %s', nucleotide, reversed) nucleotide = reversed pheniqs.ontology['pheniqs sequence'].append(nucleotide) # infer an output product for each nibble for index in range(len(pheniqs.ontology['pheniqs library'])): if self.valid: o = Ontology.clone(self.template) o.overlay(library.project('ns/service/genealogy')) o.overlay(sample.project('ns/service/genealogy')) o['nibble number'] = index + 1 product = self.produce(o) pheniqs.ontology['pheniqs output'].append(product.path) else: self.log.warning('ignoring library %s with missing barcodes', library['home uri']) else: self.log.warning('ignoring sample %s with missing library ', sample['home uri']) def validate(self, pheniqs): if self.valid: pattern = { 'barcode':{} } for pool in self.lane['body']['pools']: if 'samples' in pool: for sample in pool['samples']: if 'library' in sample: library = sample['library'] if library['barcodes']: for index,barcode in enumerate(library['barcodes']): if index not in pattern['barcode']: pattern['barcode'][index] = [] pattern['barcode'][index].append( '{}:{}:{}'.format( barcode['barcode nibble'] - 1, barcode['barcode cycle offset'] - 1, barcode['barcode length'] ) ) # verify all barcodes in each collection have an identical pattern for index,collection in pattern['barcode'].items(): if len(set(collection)) == 1: pheniqs.ontology['pheniqs fragment'].append(collection[0]) pheniqs.ontology['pheniqs barcode'].append(str(self.last_fragment(pheniqs))) else: self.abort('barcodes in set {} are heterogeneous: {}'.format(index, ', '.join(collection))) if self.valid: if pheniqs.ontology['pheniqs output']: for path in pheniqs.ontology['pheniqs output']: try: self.env.prepare_to_write_to_path(path, self.ontology['overwrite']) except (NoOverwriteError, PermissionDeniedError) as e: self.abort(str(e)) break else: self.abort('no libraries to demultiplex') def pheniqs_demux(self): pheniqs = Command('pheniqs demux', self.context) if pheniqs.valid: try: self.env.prepare_to_write_to_path(pheniqs.ontology['pheniqs configuration path'], self.ontology['overwrite']) except (NoOverwriteError, PermissionDeniedError) as e: self.abort(str(e)) else: self.configure(pheniqs) self.validate(pheniqs) if self.valid: try: self.write_configuration_file(pheniqs) except OSError as error: self.abort('writing pheniqs configuration file to {} failed'.format(pheniqs.ontology['pheniqs configuration path'])) self.log.error(str(error)) else: self.log.info('using pheniqs configuration %s', pheniqs.ontology['pheniqs configuration path']) pheniqs.execute() else: self.abort('command {} is invalid'.format(pheniqs.name)) class FilterTask(ResourceTask): def __init__(self, job, ontology, location): ResourceTask.__init__(self, job, ontology, location) self.log = logging.getLogger('Bio') def pheniqs_filter(self): product = self.produce(self.resource.origin) if self.resource.local and product.local: try: self.env.prepare_to_write_to_path(product.path, self.ontology['overwrite']) except (NoOverwriteError, PermissionDeniedError) as e: self.abort(str(e)) else: pheniqs = Command('pheniqs filter', self.context) if pheniqs.valid: pheniqs.ontology['pheniqs input'].append(self.resource.qualified_path) pheniqs.ontology['pheniqs output'].append(product.path) self.log.debug('pheniqs filter {} --> {}'.format(self.resource.qualified_path, product.qualified_path)) pheniqs.execute() else: self.abort('command {} is invalid'.format(rsync.name)) else: self.abort('filter can only be done locally') class MergeTask(Task): def __init__(self, job, ontology, locations): Task.__init__(self, job, ontology) self.log = logging.getLogger('Bio') self.locations = locations self.resources = [] self.node['origins'] = [] def load(self): Task.load(self) if self.valid: for location in self.locations: resource = Resource.create(self.env, location, self.context) if resource is not None: self.node['origins'].append(location) self.resources.append(resource) else: self.abort('resource location is invalid:\n{}'.format(self.env.to_json(location))) def unload(self): if self.resources: if self.valid: for resource in self.resources: resource.unload() else: del self.node['origins'] Task.unload(self) def merge_fastq(self): origin = Ontology.clone(self.resources[0].origin) origin['media kind'] = 50 product = self.produce(origin) if product.local: try: self.env.prepare_to_write_to_path(product.path, self.ontology['overwrite']) except (NoOverwriteError, PermissionDeniedError) as e: self.abort(str(e)) else: if not self.simulated: with io.open(product.path, 'wb') as o: for resource in self.resources: with io.open(resource.path, 'rb') as i: o.write(i.read()) else: self.log.info( 'merge {} --> {}'.format( ' + '.join([resource.path for resource in self.resources]), product.path ) ) else: self.abort('merge can only be done locally')
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zshoes/api/auth.py
andresgz/zshoes
0
140341
from django.utils.translation import ugettext_lazy as _ from django.contrib.auth import get_user_model from rest_framework.authentication import BasicAuthentication from rest_framework.exceptions import AuthenticationFailed class AuthenticationBasic(BasicAuthentication): def authenticate_credentials(self, userid, password): """ Authenticate the userid and password against username and password. """ User = get_user_model() user = User() if userid == 'my_user' and password == '<PASSWORD>': return (user, None) else: raise AuthenticationFailed( _('Invalid username/password.'))
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dataloader.py
cviaai/TMJ-segment
6
159873
import numpy as np np.random.seed(0) import torch torch.manual_seed(0) from torch.utils.data import Dataset, DataLoader, ConcatDataset, RandomSampler import torchvision import imageio import importlib import random import glob import os import transforms_3d class patch_DS(Dataset): """Implementation of torch.utils.data.Dataset for set of .tiff files, which iterates over the raw and label datasets patch by patch with a given stride. """ def __init__(self, root_dcm, root_mask, phase, transformer_config, patient_ids, patch_shape, stride_shape, patch_builder_cls, voi_shape, precrop, seed_fn=None): """ Args: root_dcm: path to directory containing raw data. root_mask: path to directory containing label data. phase: 'train' for training, 'val' for validation, 'test' for testing; data augmentation is performed only during the 'train' phase. transformer_config: dictionary of transformations and parameters for data augmentation. patient_ids: set of patients' ids for dataset during the phase. patch_shape: the shape of the patch DxHxW. stride_shape: the shape of the stride DxHxW. slice_builder_cls: defines how to sample patches from the image. voi_shape: shape of each image DxHxW. precrop: necessity of precroppping. """ self.root_dcm = root_dcm self.root_mask = root_mask assert phase in ['train', 'val', 'test'] self.phase = phase self.transformer_config = transformer_config self.patient_ids = patient_ids self.patch_shape = patch_shape self.stride_shape = stride_shape self.patch_builder_cls = patch_builder_cls self.voi_shape = voi_shape self.precrop = precrop self.seed_fn = seed_fn self.to_tensor_transform = torchvision.transforms.ToTensor() self.filenames_dcm = [] self.filenames_mask = [] self.raws = [] self.labels = [] for i in patient_ids: filenames_img = glob.glob(os.path.join(root_dcm+str(i), '*.tiff')) filenames_img.sort() filenames_m = [x.replace('dicom','mask') for x in filenames_img] self.filenames_dcm.append(filenames_img) self.filenames_mask.append(filenames_m) depth = len(filenames_img) if self.precrop: z1 = (depth-self.voi_shape[2])//2 z2 = z1+self.voi_shape[2] else: z1 = 0 z2 = depth # read raw scan raw_img = np.zeros(self.voi_shape, dtype='uint8') # create zero image for fn in filenames_img[z1:z2]: img = imageio.imread(fn) if self.precrop: img = self._center_crop(img,self.voi_shape[:2]) raw_img[:, :, filenames_img[z1:z2].index(fn)] = img self.raws.append(raw_img) # read mask for scan label_img = np.zeros(self.voi_shape, dtype='uint8') # create zero mask for fn in filenames_m[z1:z2]: m = imageio.imread(fn) if self.precrop: m = self._center_crop(m,self.voi_shape[:2]) label_img[:, :, filenames_m[z1:z2].index(fn)] = m self.labels.append(label_img) self.raws = np.array(self.raws) self.labels = np.array(self.labels) min_value, max_value, mean, std = self._calculate_stats(self.raws) print (f'Input stats: min={min_value}, max={max_value}, mean={mean}, std={std}') self.transformer = transforms_3d.get_transformer(self.transformer_config, min_value=min_value, max_value=max_value, mean=mean, std=std, phase=self.phase) self.raw_transform = self.transformer.raw_transform() self.label_transform = self.transformer.label_transform() patch_builder = patch_builder_cls(self.raws, self.labels, patch_shape, stride_shape) self.raw_patches = patch_builder.raw_patches self.label_patches= patch_builder.label_patches self.len = len(self.raw_patches) def _set_seed(self, seed): random.seed(seed) torch.manual_seed(seed) if self.seed_fn: self.seed_fn(seed) @staticmethod def _calculate_stats(inputs): return np.min(inputs), np.max(inputs), np.mean(inputs), np.std(inputs) def __getitem__(self, index): raw_idx = self.raw_patches[index] label_idx = self.label_patches[index] image = self.raws[raw_idx] image = image.reshape(self.patch_shape) mask = self.labels[label_idx] mask = mask.reshape(self.patch_shape) seed = random.randint(0, 2**32) self._set_seed(seed) image = self.raw_transform(image) image = self.to_tensor_transform(image) self._set_seed(seed) mask = self.label_transform(mask) mask = self.to_tensor_transform(mask) return image, mask def _center_crop(self, img, roi_shape): y_size, x_size = roi_shape y1 = (img.shape[0]-y_size)//2 x1 = (img.shape[1]-x_size)//2 return img[y1:y1+y_size, x1:x1+x_size] def __len__(self): return self.len class PatchBuilder: """Sample patches from the image.""" def __init__(self, raw_dataset, label_dataset, patch_shape, stride_shape): """ Args: raw_dataset: array of raw data. label_dataset: array of label data. patch_shape: the shape of the patch DxHxW. stride_shape: the shape of the stride DxHxW. """ self._raw_patches = self._build_patches(raw_dataset, patch_shape, stride_shape) if label_dataset is None: self._label_patches = None else: self._label_patches = self._build_patches(label_dataset, patch_shape, stride_shape) @property def raw_patches(self): return self._raw_patches @property def label_patches(self): return self._label_patches @staticmethod def _build_patches(dataset, patch_shape, stride_shape): """Iterate over a given dataset patch-by-patch with a given stride and builds an array of slice positions. Args: dataset: array of label data. patch_shape: the shape of the patch DxHxW. stride_shape: the shape of the stride DxHxW. Returns: list of slices [(slice, slice, slice, slice), ...] """ slices = [] assert len(dataset.shape) == 4, 'Supports only 4D (NxDxHxW)' num_patients, i_z, i_y, i_x = dataset.shape k_z, k_y, k_x = patch_shape s_z, s_y, s_x = stride_shape for p in range(num_patients): z_steps = PatchBuilder._gen_indices(i_z, k_z, s_z) for z in z_steps: y_steps = PatchBuilder._gen_indices(i_y, k_y, s_y) for y in y_steps: x_steps = PatchBuilder._gen_indices(i_x, k_x, s_x) for x in x_steps: slice_idx = ( slice(z, z + k_z), slice(y, y + k_y), slice(x, x + k_x) ) slice_idx = (slice(p, p+1),) + slice_idx # patient id slices.append(slice_idx) return slices @staticmethod def _gen_indices(i, k, s): """ Args: i (int): image size. k (int): patch size. s (int): stride size. Returns: generator of slides start positions """ assert i >= k, 'Sample size should be bigger than the patch size' for j in range(0, i - k + 1, s): yield j if (j + k < i)&(i!=s): yield i - k def _get_patch_builder_cls(class_name): m = importlib.import_module('dataloader') clazz = getattr(m, class_name) return clazz def get_train_loaders(config): """Return dictionary containing the training and validation loaders (torch.utils.data.DataLoader). Args: config: a top level configuration object containing the 'loaders' key. Returns: dict {'train': <train_loader>, 'val': <val_loader>}: dictionary containing the training and validation loaders. """ assert 'loaders' in config, 'Could not find data loaders configuration' loaders_config = config['loaders'] print ('Creating training and validation set loaders...') # get train and validation files objects = loaders_config['objects'] assert isinstance(objects, list) voi_shape = loaders_config['voi_shape'] dicom_path = loaders_config['dicom_path'] mask_path = loaders_config['mask_path'] train_ids = tuple(loaders_config['train_patient_ids']) train_patch = tuple(loaders_config['train_patch']) train_stride = tuple(loaders_config['train_stride']) val_ids = tuple(loaders_config['val_patient_ids']) val_patch = tuple(loaders_config['val_patch']) val_stride = tuple(loaders_config['val_stride']) transformer_config = loaders_config['transformer'] precrop = loaders_config['precrop'] # get train slice_builder_cls train_patch_builder_str = loaders_config.get('train_patch_builder', 'PatchBuilder') print (f'Train s builder class: {train_patch_builder_str}') train_patch_builder_cls = _get_patch_builder_cls(train_patch_builder_str) train_datasets = [] for obj in objects: root_dcm = dicom_path+'_'+obj+ '/' root_mask = mask_path+'_'+obj+ '/' try: print (f'Loading training set from: {root_dcm}...') train_dataset = patch_DS(root_dcm, root_mask, 'train', transformer_config, train_ids, train_patch, train_stride, train_patch_builder_cls, voi_shape,precrop, seed_fn=None) train_datasets.append(train_dataset) except Exception: print (f'Skipping training set: {root_dcm}') # get val slice_builder_cls val_patch_builder_str = loaders_config.get('val_patch_builder', 'PatchBuilder') print (f'Val patch builder class: {val_patch_builder_str}') val_patch_builder_cls = _get_patch_builder_cls(val_patch_builder_str) val_datasets = [] for obj in objects: root_dcm = dicom_path+'_'+obj+ '/' root_mask = mask_path+'_'+obj+ '/' try: print (f'Loading val set from: {root_dcm}...') val_dataset = patch_DS(root_dcm, root_mask, 'val', transformer_config, val_ids, val_patch, val_stride, val_patch_builder_cls, voi_shape, precrop, seed_fn=None) val_datasets.append(val_dataset) except Exception: print(f'Skipping val set: {root_dcm}') num_workers = loaders_config.get('num_workers', 1) print (f'Number of workers for train/val dataloader: {num_workers}') batch_size = loaders_config.get('batch_size', 1) print (f'Batch size for train/val loader: {batch_size}') train_dataset_size = loaders_config.get('train_dataset_size', 1) train_rand_sampler = RandomSampler(ConcatDataset(train_datasets), replacement=True, num_samples=train_dataset_size) return {'train': DataLoader(ConcatDataset(train_datasets), batch_size=batch_size, shuffle=False, sampler=train_rand_sampler, num_workers=num_workers), 'val': DataLoader(ConcatDataset(val_datasets), batch_size=batch_size, shuffle=False, num_workers=num_workers) }
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src/code/static_network/globals.py
dvaruas/minority_recommendations
0
43774
<gh_stars>0 import os PARAMETERS_PATH = os.path.join(os.path.dirname(__file__), os.pardir, "common", "parameters.ini") STATIC_DATA_PATH = os.path.join(os.path.dirname(__file__), os.pardir, os.pardir, os.pardir, "data", "synthetic", "static")
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base/base_trainer.py
yhung119/show-and-tell-image-captioning
10
145888
import os import math import shutil import torch from utils import ensure_dir, Early_stopping class BaseTrainer: """ Base class for all trainer. Note: Modify if you need to change logging style, checkpoint naming, or something else. """ def __init__(self, model, loss, vocab, optimizer, epochs, save_dir, save_freq, eval_freq, resume, verbosity, id, dataset, identifier='', logger=None): self.model = model self.loss = loss self.optimizer = optimizer self.epochs = epochs self.min_loss = math.inf self.vocab = vocab self.save_dir = save_dir self.save_freq = save_freq self.verbosity = verbosity self.identifier = identifier self.logger = logger self.start_epoch = 1 self.dataset = dataset self.id = id self.eval_freq = eval_freq ensure_dir(save_dir) if resume: self._resume_checkpoint(resume) self.early_stop = Early_stopping(patience=3) def train(self): for epoch in range(self.start_epoch, self.epochs+1): result = self._train_epoch(epoch) # if self.logger: # log = {'epoch': epoch} # for key, value in result.items(): # if key == 'metrics': # for i, metric in enumerate(self.metrics): # log[metric.__name__] = result['metrics'][i] # elif key == 'val_metrics': # for i, metric in enumerate(self.metrics): # log['val_'+metric.__name__] = result['val_metrics'][i] # else: # log[key] = value # self.logger.add_entry(log) # if self.verbosity >= 1: # print(log) if epoch % self.save_freq == 0: self._save_checkpoint(epoch, result['loss']) self.early_stop.update(result["coco_stat"]["Bleu_4"]) if self.early_stop.stop(): break def _train_epoch(self, epoch): raise NotImplementedError def _valid_epoch(self, epoch): raise NotImplementedError def _save_checkpoint(self, epoch, loss): if loss < self.min_loss: self.min_loss = loss arch = type(self.model).__name__ state = { 'epoch': epoch, 'logger': self.logger, 'arch': arch, 'state_dict': self.model.state_dict(), 'optimizer': self.optimizer.state_dict(), 'min_loss': self.min_loss, } id_filename = str(self.id) + '_/' id_file_path = self.save_dir + '/' + id_filename + 'checkpoints/' ensure_dir(id_file_path) filename = os.path.join(id_file_path, self.identifier + 'checkpoint_epoch{:02d}_loss_{:.5f}.pth.tar'.format(epoch, loss)) print("Saving checkpoint: {} ...".format(filename)) torch.save(state, filename) if loss == self.min_loss: shutil.copyfile(filename, os.path.join(self.save_dir, 'model_best.pth.tar')) def _resume_checkpoint(self, resume_path): print("Loading checkpoint: {} ...".format(resume_path)) checkpoint = torch.load(resume_path) self.start_epoch = checkpoint['epoch'] + 1 self.min_loss = checkpoint['min_loss'] self.model.load_state_dict(checkpoint['state_dict']) self.optimizer.load_state_dict(checkpoint['optimizer']) self.logger = checkpoint['logger'] print("Checkpoint '{}' (epoch {}) loaded".format(resume_path, self.start_epoch))
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code/testbed/pde1/FemPde1.py
nicolai-schwartze/Masterthesis
1
3954
# -*- coding: utf-8 -*- """ Created on Mon Apr 13 14:57:32 2020 @author: Nicolai """ import sys import os importpath = os.path.dirname(os.path.realpath(__file__)) + "/../" sys.path.append(importpath) from FemPdeBase import FemPdeBase import numpy as np # import from ngsolve import ngsolve as ngs from netgen.geom2d import unit_square import time import psutil import gc class FemPde1(FemPdeBase): """ **Implementation of PDE1 of the testbed:** .. math:: - \Delta u(\mathbf{x}) = -2^{40}y^{10}(1-y)^{10}[90x^8(1-x)^{10} - 200x^9(1-x)^9 + 90x^{10}(1-x)^8] -2^{40}x^{10}(1-x)^{10}[90y^8(1-y)^{10} - 200y^9(1-y)^9 + 90y^{10}(1-y)^8] \Omega: \mathbf{x} \in [0,1] u(\mathbf{x})|_{\partial \Omega} = 0 **with the solution:** .. math:: u(\mathbf{x}) = 2^{40}x^{10}(1-x)^{10}y^{10}(1-y)^{10} Attributes ---------- max_nodf: int the maximum number of degrees of freedom that can be created in the adaptive mesh refinement, standard value is 50000 Methods ------- solve() solves the pde by calling ngsolve, provides: static condensation, adaptive mesh refinement, parallelisation (where possible), sets the internal variables for evaluating the exact solution and calculating the distance between exact and approx solution also sets execution time and memory consumption Examples -------- >>> import numpy as np >>> fempde2 = FemPde2(True) >>> pos = np.array([0.5, 0.5]) >>> fempde2.exact(pos) >>> x -> numpy.ndarray with shape (2,) _mesh -> ngs.comp.Mesh _ngs_ex -> ngs.fem.CoefficientFunction -> try to call solve() first >>> fempde2.solve() >>> fempde2.exact(pos) 1.0 >>> fempde2.approx(pos) 0.999998924259486 >>> fempde2.normL2() 5.853102150391562e-07 >>> fempde2.exec_time 3.830256175994873 >>> fempde2.mem_consumption 76705792 """ def __init__(self, show_gui, max_ndof=50000): super().__init__(show_gui) # init protected self._pde_string = "-laplacian(u(x)) = -(2^40*y^10*(1-y)^10*(90*x^8*(1-x)^10 - 200*x^9*(1-x)^9 + 90*x^10*(1-x)^8)) -(2^40*x^10*(1-x)^10*(90*y^8*(1-y)^10 - 200*y^9*(1-y)^9 + 90*y^10*(1-y)^8))" self._ngs_ex = (2**(4*10))*(ngs.x**10)*((1-ngs.x)**10)*(ngs.y**10)*((1-ngs.y)**10) # init public self.max_ndof = max_ndof def solve(self): # disable garbage collector # --------------------------------------------------------------------# gc.disable() while(gc.isenabled()): time.sleep(0.1) # --------------------------------------------------------------------# # measure how much memory is used until here process = psutil.Process() memstart = process.memory_info().vms # starts timer tstart = time.time() if self.show_gui: import netgen.gui # create mesh with initial size 0.1 self._mesh = ngs.Mesh(unit_square.GenerateMesh(maxh=0.1)) #create finite element space self._fes = ngs.H1(self._mesh, order=2, dirichlet=".*", autoupdate=True) # test and trail function u = self._fes.TrialFunction() v = self._fes.TestFunction() # create bilinear form and enable static condensation self._a = ngs.BilinearForm(self._fes, condense=True) self._a += ngs.grad(u)*ngs.grad(v)*ngs.dx # creat linear functional and apply RHS self._f = ngs.LinearForm(self._fes) self._f += ( \ -(2**40*ngs.y**10*(1-ngs.y)**10*(90*ngs.x**8*(1-ngs.x)**10 - 200*ngs.x**9*(1-ngs.x)**9 + 90*ngs.x**10*(1-ngs.x)**8)) \ -(2**40*ngs.x**10*(1-ngs.x)**10*(90*ngs.y**8*(1-ngs.y)**10 - 200*ngs.y**9*(1-ngs.y)**9 + 90*ngs.y**10*(1-ngs.y)**8)) )*v*ngs.dx # preconditioner: multigrid - what prerequisits must the problem have? self._c = ngs.Preconditioner(self._a,"multigrid") # create grid function that holds the solution and set the boundary to 0 self._gfu = ngs.GridFunction(self._fes, autoupdate=True) # solution self._g = 0.0 self._gfu.Set(self._g, definedon=self._mesh.Boundaries(".*")) # draw grid function in gui if self.show_gui: ngs.Draw(self._gfu) # create Hcurl space for flux calculation and estimate error self._space_flux = ngs.HDiv(self._mesh, order=2, autoupdate=True) self._gf_flux = ngs.GridFunction(self._space_flux, "flux", autoupdate=True) # TaskManager starts threads that (standard thread nr is numer of cores) with ngs.TaskManager(): # this is the adaptive loop while self._fes.ndof < self.max_ndof: self._solveStep() self._estimateError() self._mesh.Refine() # since the adaptive loop stopped with a mesh refinement, the gfu must be # calculated one last time self._solveStep() if self.show_gui: ngs.Draw(self._gfu) # set measured exectution time self._exec_time = time.time() - tstart # set measured used memory memstop = process.memory_info().vms - memstart self._mem_consumption = memstop # enable garbage collector # --------------------------------------------------------------------# gc.enable() gc.collect() # --------------------------------------------------------------------# if __name__ == "__main__": fempde1 = FemPde1(True) print(fempde1.pde_string) try: fempde1.exact(np.array([0.5,0.5])) except: print("Î error message above") try: fempde1.approx(np.array([0.5,0.5])) except: print("Î error message above") fempde1.solve() print("-------------------------------------") print("exact(0.5, 0.5) = {}".format(fempde1.exact(np.array([0.5,0.5])))) print("approx(0.5, 0.5) = {}".format(fempde1.approx(np.array([0.5,0.5])))) print("L2 norm to the real solution {}".format(fempde1.normL2())) print("solving took {} sec".format(fempde1.exec_time)) print("solving uses {} Mb".format(fempde1.mem_consumption/1000000)) from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from matplotlib import cm fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x = y = np.arange(0, 1.01, 0.01) X, Y = np.meshgrid(x, y) zs0 = np.array([fempde1.exact(\ np.array([x,y])) for x,y in zip(np.ravel(X), np.ravel(Y))]) Z = zs0.reshape(X.shape) ax.plot_surface(X, Y, Z, cmap=cm.gnuplot) fig.tight_layout() ax.set_xlabel("X0") ax.set_ylabel("X1") ax.set_zlabel("f(X0, X1)") plt.show() fig.savefig("sol_pde_1.pdf", bbox_inches='tight') fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x = y = np.arange(0, 1.01, 0.01) X, Y = np.meshgrid(x, y) zs0 = np.array([fempde1.approx(\ np.array([x,y])) for x,y in zip(np.ravel(X), np.ravel(Y))]) Z = zs0.reshape(X.shape) ax.plot_surface(X, Y, Z, cmap=cm.gnuplot) ax.set_xlabel("X0") ax.set_ylabel("X1") ax.set_zlabel("f(X0,X1)") plt.show()
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lightflow_rest/__main__.py
AustralianSynchrotron/lightflow-rest
0
42389
<reponame>AustralianSynchrotron/lightflow-rest def main(args): """ Main entry point for the extension. """ from lightflow_rest.service import app app.run() if __name__ == '__main__': import sys main(sys.argv[1:])
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library/azure_rm_sqlvirtualnetworkrule.py
wray/azure_modules
0
109749
<filename>library/azure_rm_sqlvirtualnetworkrule.py #!/usr/bin/python # # Copyright (c) 2018, <NAME> # # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import absolute_import, division, print_function __metaclass__ = type ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ['preview'], 'supported_by': 'community'} DOCUMENTATION = ''' --- module: azure_rm_sqlvirtualnetworkrule version_added: "2.7" short_description: Manage SQL Virtual Network Rules description: - Add/Delete Virtual network Rule. options: resource_group: description: - The name of the resource group that contains the resource. You can obtain this value from the Azure Resource Manager API or the portal. required: True server_name: description: - The name of the sql server. required: True name: description: - The name of the firewall rule. required: True subnet_name: description: - The name of the subnet required: True state: description: - Assert the state of the VNet rule. Use 'present' to add a rule and 'absent' to delete it. default: present choices: - absent - present extends_documentation_fragment: - azure author: - "<NAME> (@wray)" ''' EXAMPLES = ''' - name: Create (or update) Virutal Network Rule azure_rm_sqlvirtualnetworkrule: resource_group: vnrulecrudtest-17 server_name: vnrulecrudtest-6234 name: vnrulecrudtest-5332 subnet_name: vnrulecrudtest-333 ''' RETURN = ''' id: description: - Resource ID. returned: always type: str sample: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/vnrulecrudtest-17/providers/Microsoft.Sql/servers/firewallrulecrudtest-6234 5/firewallRules/firewallrulecrudtest-5332" ''' import time from ansible.module_utils.azure_rm_common import AzureRMModuleBase try: from msrestazure.azure_exceptions import CloudError from msrestazure.azure_operation import AzureOperationPoller from msrest.polling import LROPoller from azure.mgmt.sql import SqlManagementClient from msrest.serialization import Model except ImportError: # This is handled in azure_rm_common pass class Actions: NoAction, Create, Delete = range(3) class AzureRMVirtualNetworkRules(AzureRMModuleBase): """Configuration class for an Azure RM Firewall Rule resource""" def __init__(self): self.module_arg_spec = dict( resource_group=dict( type='str', required=True ), server_name=dict( type='str', required=True ), name=dict( type='str', required=True ), subnet_name=dict( type='str', required=True ), state=dict( type='str', default='present', choices=['present', 'absent'] ) ) self.resource_group = None self.server_name = None self.name = None self.virtual_network = None self.subnet_name = None self.results = dict(changed=False) self.state = None self.to_do = Actions.NoAction super(AzureRMVirtualNetworkRules, self).__init__(derived_arg_spec=self.module_arg_spec, supports_check_mode=True, supports_tags=False) def exec_module(self, **kwargs): """Main module execution method""" for key in list(self.module_arg_spec.keys()): if hasattr(self, key): setattr(self, key, kwargs[key]) old_response = self.get_virtualnetworkrule() response = None if not old_response: self.log("Virtual Network Rule instance doesn't exist") if self.state == 'absent': self.log("Old Rule didn't exist") else: self.to_do = Actions.Create else: self.log("Virtual Network Rule instance already exists") if self.state == 'absent': self.to_do = Actions.Delete elif self.state == 'present': self.log("Virtual Network Rule will remain") if self.to_do == Actions.Create: self.log("Need to Create the Virtual Network Rule instance") if self.check_mode: self.results['changed'] = True return self.results response = self.create_virtualnetworkrule() if not old_response: self.results['changed'] = True else: self.results['changed'] = old_response.__ne__(response) self.log("Creation done") elif self.to_do == Actions.Delete: self.log("Virtual Network Rule instance to be deleted") self.results['changed'] = True if self.check_mode: return self.results self.delete_virtualnetworkrule() # make sure instance is actually deleted, for some Azure resources, instance is hanging around # for some time after deletion -- this should be really fixed in Azure while self.get_virtualnetworkrule(): time.sleep(20) else: self.log("Virtual Network Rule instance unchanged") self.results['changed'] = False response = old_response if response: self.results["id"] = response["id"] return self.results def create_virtualnetworkrule(self): ''' Creates or updates Virtual Network Rule with the specified configuration. :return: deserialized Network Rule instance state dictionary ''' self.log("Creating the Virtual Network Rule instance {0}".format(self.name)) try: response = self.sql_client.virtual_network_rules.create_or_update(resource_group_name=self.resource_group, server_name=self.server_name, virtual_network_rule_name=self.name, virtual_network_subnet_id=self.subnet_name) if isinstance(response, AzureOperationPoller): response = self.get_poller_result(response) except CloudError as exc: self.log('Error attempting to create the Firewall Rule instance.') self.fail("Error creating the Firewall Rule instance: {0}".format(str(exc))) return response.as_dict() def delete_virtualnetworkrule(self): ''' Deletes specified Firewall Rule instance in the specified subscription and resource group. :return: True ''' self.log("Deleting the Firewall Rule instance {0}".format(self.name)) try: response = self.sql_client.virtual_network_rules.delete(resource_group_name=self.resource_group, server_name=self.server_name, virtual_network_rule_name=self.name) except CloudError as e: self.log('Error attempting to delete the Firewall Rule instance.') self.fail("Error deleting the Firewall Rule instance: {0}".format(str(e))) return True def get_virtualnetworkrule(self): ''' Gets the properties of the specified Virtual Network Rule. :return: deserialized Virtual Network Rule instance state dictionary ''' self.log("Checking if the Virtual network Rule instance {0} is present".format(self.name)) found = False try: response = self.sql_client.virtual_network_rules.get(resource_group_name=self.resource_group, server_name=self.server_name, virtual_network_rule_name=self.name) found = True self.log("Response : {0}".format(response)) self.log("Virtual Network Rule instance : {0} found".format(response.name)) except CloudError as e: self.log('Did not find the Virtual Network Rule instance.') if found is True: return response.as_dict() return False def main(): """Main execution""" AzureRMVirtualNetworkRules() if __name__ == '__main__': main()
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neighborapp/models.py
Maureen-1998DEV/watch_Hood
0
25766
from django.db import models from django.contrib.auth.models import User from cloudinary.models import CloudinaryField # Create your models here. class Neighborhood(models.Model): name = models.CharField(max_length = 50) location = models.ForeignKey('Location',on_delete = models.CASCADE,null = True) admin = models.ForeignKey(User,on_delete = models.CASCADE) occupants = models.IntegerField(null=True) def __str__(self): return self.name def create_neighborhood(self): self.save() def delete_neighborhood(self): self.delete() @classmethod def find_neighborhood(cls,neigborhood_id): neighborhood = cls.objects.get(id = neigborhood_id) return neighborhood def update_neighborhood(self): self.save() def update_occupants(self): self.occupants += 1 self.save() class UserProfile(models.Model): user = models.ForeignKey(User,on_delete = models.CASCADE,related_name = 'profile') first_name = models.CharField(max_length = 50,null=True) last_name = models.CharField(max_length = 50,null=True) bio = models.TextField(null=True) neighborhood = models.ForeignKey(Neighborhood,on_delete = models.CASCADE,null=True) email = models.EmailField(max_length = 60,null=True) profile_pic = CloudinaryField('profile/') pub_date = models.DateTimeField(auto_now_add=True) def __str__(self): return self.user.username class Business(models.Model): name = models.CharField(max_length = 60) user = models.ForeignKey(User,on_delete = models.CASCADE,related_name = 'business_user') description = models.CharField(max_length = 150,null=True) neighborhood = models.ForeignKey(Neighborhood,on_delete = models.CASCADE,related_name = 'business_neighbourhood') category = models.ForeignKey('Category',on_delete = models.CASCADE,null=True) email = models.EmailField(max_length = 60) def __str__(self): return self.name def create_business(self): self.save() def delete_business(self): self.delete() @classmethod def find_business(cls,business_id): business = Business.objects.get(id = business_id) return business def update_business(self): self.save() class Post(models.Model): title = models.CharField(max_length = 50) content = models.TextField() user = models.ForeignKey(User,on_delete = models.CASCADE) neighborhood = models.ForeignKey(Neighborhood,on_delete = models.CASCADE) type = models.CharField(max_length = 50,null=True) pub_date = models.DateTimeField(auto_now_add=True,null=True) def __str__(self): return self.title class Comment(models.Model): comment = models.CharField(max_length = 300) posted_on = models.DateTimeField(auto_now=True) user = models.ForeignKey(User, on_delete=models.CASCADE) def save_comment(self): self.save() def delete_comment(self): self.delete() class Location(models.Model): name = models.CharField(max_length = 40) def __str__(self): return self.name class Category(models.Model): name = models.CharField(max_length = 40) def __str__(self): return self.name
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assignment-section-05/classification_model/__init__.py
RostekA/deploying-machine-learning-models
1
154920
import logging from classification_model.config.core import PACKAGE_ROOT, config # It is strongly advised that you do not add any handlers other than # NullHandler to your library’s loggers. This is because the configuration # of handlers is the prerogative of the application developer who uses your # library. The application developer knows their target audience and what # handlers are most appropriate for their application: if you add handlers # ‘under the hood’, you might well interfere with their ability to carry out # unit tests and deliver logs which suit their requirements. # https://docs.python.org/3/howto/logging.html#configuring-logging-for-a-library logging.getLogger(config.app_config.package_name).addHandler(logging.NullHandler()) with open(PACKAGE_ROOT / "VERSION") as version_file: __version__ = version_file.read().strip()
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yt_dlp/extractor/zingmp3.py
mrBliss/yt-dlp
80
72605
# coding: utf-8 from __future__ import unicode_literals from .common import InfoExtractor from ..utils import ( int_or_none, ) class ZingMp3BaseIE(InfoExtractor): _VALID_URL_TMPL = r'https?://(?:mp3\.zing|zingmp3)\.vn/(?:%s)/[^/]+/(?P<id>\w+)\.html' _GEO_COUNTRIES = ['VN'] def _extract_item(self, item, fatal): item_id = item['id'] title = item.get('name') or item['title'] formats = [] for k, v in (item.get('source') or {}).items(): if not v: continue if k in ('mp4', 'hls'): for res, video_url in v.items(): if not video_url: continue if k == 'hls': formats.extend(self._extract_m3u8_formats( video_url, item_id, 'mp4', 'm3u8_native', m3u8_id=k, fatal=False)) elif k == 'mp4': formats.append({ 'format_id': 'mp4-' + res, 'url': video_url, 'height': int_or_none(self._search_regex( r'^(\d+)p', res, 'resolution', default=None)), }) else: formats.append({ 'ext': 'mp3', 'format_id': k, 'tbr': int_or_none(k), 'url': self._proto_relative_url(v), 'vcodec': 'none', }) if not formats: if not fatal: return msg = item['msg'] if msg == 'Sorry, this content is not available in your country.': self.raise_geo_restricted(countries=self._GEO_COUNTRIES, metadata_available=True) self.raise_no_formats(msg, expected=True) self._sort_formats(formats) subtitles = None lyric = item.get('lyric') if lyric: subtitles = { 'origin': [{ 'url': lyric, }], } album = item.get('album') or {} return { 'id': item_id, 'title': title, 'formats': formats, 'thumbnail': item.get('thumbnail'), 'subtitles': subtitles, 'duration': int_or_none(item.get('duration')), 'track': title, 'artist': item.get('artists_names'), 'album': album.get('name') or album.get('title'), 'album_artist': album.get('artists_names'), } def _real_extract(self, url): page_id = self._match_id(url) webpage = self._download_webpage( url.replace('://zingmp3.vn/', '://mp3.zing.vn/'), page_id, query={'play_song': 1}) data_path = self._search_regex( r'data-xml="([^"]+)', webpage, 'data path') return self._process_data(self._download_json( 'https://mp3.zing.vn/xhr' + data_path, page_id)['data']) class ZingMp3IE(ZingMp3BaseIE): _VALID_URL = ZingMp3BaseIE._VALID_URL_TMPL % 'bai-hat|video-clip' _TESTS = [{ 'url': 'http://mp3.zing.vn/bai-hat/Xa-Mai-Xa-Bao-Thy/ZWZB9WAB.html', 'md5': 'ead7ae13693b3205cbc89536a077daed', 'info_dict': { 'id': 'ZWZB9WAB', 'title': 'Xa Mãi Xa', 'ext': 'mp3', 'thumbnail': r're:^https?://.+\.jpg', 'subtitles': { 'origin': [{ 'ext': 'lrc', }] }, 'duration': 255, 'track': 'Xa Mãi Xa', 'artist': 'Bảo Thy', 'album': 'Special Album', 'album_artist': 'Bảo Thy', }, }, { 'url': 'https://mp3.zing.vn/video-clip/Suong-Hoa-Dua-Loi-K-ICM-RYO/ZO8ZF7C7.html', 'md5': 'e9c972b693aa88301ef981c8151c4343', 'info_dict': { 'id': 'ZO8ZF7C7', 'title': 'Sương Hoa Đưa Lối', 'ext': 'mp4', 'thumbnail': r're:^https?://.+\.jpg', 'duration': 207, 'track': 'Sương Hoa Đưa Lối', 'artist': 'K-ICM, RYO', }, }, { 'url': 'https://zingmp3.vn/bai-hat/Xa-Mai-Xa-Bao-Thy/ZWZB9WAB.html', 'only_matching': True, }] IE_NAME = 'zingmp3' IE_DESC = 'mp3.zing.vn' def _process_data(self, data): return self._extract_item(data, True) class ZingMp3AlbumIE(ZingMp3BaseIE): _VALID_URL = ZingMp3BaseIE._VALID_URL_TMPL % 'album|playlist' _TESTS = [{ 'url': 'http://mp3.zing.vn/album/Lau-Dai-Tinh-Ai-Bang-Kieu-Minh-Tuyet/ZWZBWDAF.html', 'info_dict': { '_type': 'playlist', 'id': 'ZWZBWDAF', 'title': 'Lâu Đài Tình Ái', }, 'playlist_count': 10, }, { 'url': 'http://mp3.zing.vn/playlist/Duong-Hong-Loan-apollobee/IWCAACCB.html', 'only_matching': True, }, { 'url': 'https://zingmp3.vn/album/Lau-Dai-Tinh-Ai-Bang-Kieu-Minh-Tuyet/ZWZBWDAF.html', 'only_matching': True, }] IE_NAME = 'zingmp3:album' def _process_data(self, data): def entries(): for item in (data.get('items') or []): entry = self._extract_item(item, False) if entry: yield entry info = data.get('info') or {} return self.playlist_result( entries(), info.get('id'), info.get('name') or info.get('title'))
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backend-example.py
MOSAIC-LoPoW/oss7-thingsboard-backend-example
5
84318
<gh_stars>1-10 #!/usr/bin/env python from __future__ import print_function import argparse import socket import subprocess from datetime import datetime import jsonpickle import serial import time import paho.mqtt.client as mqtt import signal import struct from d7a.alp.command import Command from d7a.alp.operations.responses import ReturnFileData from d7a.system_files.system_file_ids import SystemFileIds from d7a.system_files.system_files import SystemFiles from modem.modem import Modem import time from pprint import pprint from tb_api_client import swagger_client from tb_api_client.swagger_client import ApiClient, Configuration from tb_api_client.swagger_client.rest import ApiException class BackendExample: def __init__(self): argparser = argparse.ArgumentParser() argparser.add_argument("-v", "--verbose", help="verbose", default=False, action="store_true") argparser.add_argument("-b", "--broker", help="mqtt broker hostname", default="localhost") argparser.add_argument("-u", "--url", help="URL of the thingsboard server", default="http://localhost:8080") argparser.add_argument("-t", "--token", help="token to access the thingsboard API", required=True) self.mq = None self.connected_to_mqtt = False self.config = argparser.parse_args() self.connect_to_mqtt() api_client_config = Configuration() api_client_config.host = self.config.url api_client_config.api_key['X-Authorization'] = self.config.token api_client_config.api_key_prefix['X-Authorization'] = 'Bearer' api_client = ApiClient(api_client_config) self.device_controller_api = swagger_client.DeviceControllerApi(api_client=api_client) self.device_api_controller_api =swagger_client.DeviceApiControllerApi(api_client=api_client) def connect_to_mqtt(self): self.connected_to_mqtt = False self.mq = mqtt.Client("", True, None, mqtt.MQTTv31) self.mq.on_connect = self.on_mqtt_connect self.mq.on_message = self.on_mqtt_message self.mq.connect(self.config.broker, 1883, 60) self.mq.loop_start() while not self.connected_to_mqtt: pass # busy wait until connected print("Connected to MQTT broker on {}".format( self.config.broker, )) def on_mqtt_connect(self, client, config, flags, rc): self.mq.subscribe("/tb") self.connected_to_mqtt = True def on_mqtt_message(self, client, config, msg): # msg contains already parsed command in ALP in JSON print("ALP Command received from TB: {}".format(msg.payload)) try: obj = jsonpickle.json.loads(msg.payload) except: print("Payload not valid JSON, skipping") # TODO issue with TB rule filter, to be fixed return gateway = obj["deviceId"] cmd = jsonpickle.decode(jsonpickle.json.dumps(obj["alp"])) node_id = gateway # overwritten below with remote node ID when received over D7 interface # get remote node id (when this is received over D7 interface) if cmd.interface_status != None and cmd.interface_status.operand.interface_id == 0xd7: node_id = '{:x}'.format(cmd.interface_status.operand.interface_status.addressee.id) # look for returned file data which we can parse, in this example file 64 my_sensor_value = 0 for action in cmd.actions: if type(action.operation) is ReturnFileData and action.operand.offset.id == 64: my_sensor_value = struct.unpack("L", bytearray(action.operand.data))[0] # parse binary payload (adapt to your needs) print("node {} sensor value {}".format(node_id, my_sensor_value)) # save the parsed sensor data as an attribute to the device, using the TB API try: # first get the deviceId mapped to the device name response = self.device_controller_api.get_tenant_device_using_get(device_name=str(node_id)) device_id = response.id.id # next, get the access token of the device response = self.device_controller_api.get_device_credentials_by_device_id_using_get(device_id=device_id) device_access_token = response.credentials_id # finally, store the sensor attribute on the node in TB response = self.device_api_controller_api.post_telemetry_using_post( device_token=device_access_token, json={ "my_sensor": my_sensor_value } ) print("Updated my_sensor attribute for node {}".format(node_id)) except ApiException as e: print("Exception when calling API: %s\n" % e) def __del__(self): try: self.mq.loop_stop() self.mq.disconnect() except: pass def run(self): print("Started") keep_running = True while keep_running: try: signal.pause() except KeyboardInterrupt: print("received KeyboardInterrupt... stopping processing") keep_running = False if __name__ == "__main__": BackendExample().run()
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lwc/views.py
codingforentrepreneurs/launch-with-code
64
42341
<reponame>codingforentrepreneurs/launch-with-code from django.shortcuts import render def testhome(request): context = {} template = "donotuse.html" return render(request, template, context) # def home2(request): # context = {} # template = "home2.html" # return render(request, template, context)
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cassiopeia/datastores/riotapi/match.py
artemigkh/cassiopeia
1
8266
from time import time from typing import Type, TypeVar, MutableMapping, Any, Iterable, Generator, Union import arrow import datetime import math from datapipelines import DataSource, PipelineContext, Query, NotFoundError, validate_query from .common import RiotAPIService, APINotFoundError from ...data import Platform, Season, Queue, SEASON_IDS, QUEUE_IDS from ...dto.match import MatchDto, MatchListDto, TimelineDto from ..uniquekeys import convert_region_to_platform T = TypeVar("T") def _get_current_time(query: MutableMapping[str, Any], context: PipelineContext = None) -> int: return int(time()) * 1000 class MatchAPI(RiotAPIService): @DataSource.dispatch def get(self, type: Type[T], query: MutableMapping[str, Any], context: PipelineContext = None) -> T: pass @DataSource.dispatch def get_many(self, type: Type[T], query: MutableMapping[str, Any], context: PipelineContext = None) -> Iterable[T]: pass _validate_get_match_query = Query. \ has("id").as_(int).also. \ has("platform").as_(Platform) @get.register(MatchDto) @validate_query(_validate_get_match_query, convert_region_to_platform) def get_match(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> MatchDto: url = "https://{platform}.api.riotgames.com/lol/match/v4/matches/{id}".format(platform=query["platform"].value.lower(), id=query["id"]) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "matches/id") data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["gameId"] = query["id"] data["region"] = query["platform"].region.value for p in data["participantIdentities"]: aid = p.get("player", {}).get("currentAccountId", None) if aid == 0: p["player"]["bot"] = True return MatchDto(data) _validate_get_many_match_query = Query. \ has("ids").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(MatchDto) @validate_query(_validate_get_many_match_query, convert_region_to_platform) def get_many_match(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[MatchDto, None, None]: def generator(): for id in query["ids"]: url = "https://{platform}.api.riotgames.com/lol/match/v4/matches/{id}".format(platform=query["platform"].value.lower(), id=id) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "matches/id") data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error for participant in data["participants"]: participant.setdefault("runes", []) for p in data["participantIdentities"]: aid = p.get("player", {}).get("currentAccountId", None) if aid == 0: p["player"]["bot"] = True data["gameId"] = id data["region"] = query["platform"].region.value yield MatchDto(data) return generator() _validate_get_match_list_query = Query. \ has("accountId").as_(str).also. \ has("platform").as_(Platform).also. \ has("beginTime").as_(int).also. \ can_have("endTime").as_(int).also. \ has("beginIndex").as_(int).also. \ has("maxNumberOfMatches").as_(float).also. \ can_have("seasons").as_(Iterable).also. \ can_have("champion.ids").as_(Iterable).also. \ can_have("queues").as_(Iterable) @get.register(MatchListDto) @validate_query(_validate_get_match_list_query, convert_region_to_platform) def get_match_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> MatchListDto: params = {} riot_index_interval = 100 riot_date_interval = datetime.timedelta(days=7) begin_time = query["beginTime"] # type: arrow.Arrow end_time = query.get("endTime", arrow.now()) # type: arrow.Arrow if isinstance(begin_time, int): begin_time = arrow.get(begin_time / 1000) if isinstance(end_time, int): end_time = arrow.get(end_time / 1000) def determine_calling_method(begin_time, end_time) -> str: """Returns either "by_date" or "by_index".""" matches_per_date_interval = 10 # This is an assumption seconds_per_day = (60 * 60 * 24) riot_date_interval_in_days = riot_date_interval.total_seconds() / seconds_per_day # in units of days npulls_by_date = (end_time - begin_time).total_seconds() / seconds_per_day / riot_date_interval_in_days npulls_by_index = (arrow.now() - begin_time).total_seconds() / seconds_per_day / riot_date_interval_in_days * matches_per_date_interval / riot_index_interval if math.ceil(npulls_by_date) < math.ceil(npulls_by_index): by = "by_date" else: by = "by_index" return by calling_method = determine_calling_method(begin_time, end_time) if calling_method == "by_date": params["beginTime"] = begin_time.timestamp * 1000 if "endTime" in query: params["endTime"] = min((begin_time + riot_date_interval).timestamp * 1000, query["endTime"]) else: params["endTime"] = (begin_time + riot_date_interval).timestamp * 1000 else: params["beginIndex"] = query["beginIndex"] params["endIndex"] = query["beginIndex"] + min(riot_index_interval, query["maxNumberOfMatches"]) params["endIndex"] = int(params["endIndex"]) if "seasons" in query: seasons = {Season(season) for season in query["seasons"]} params["season"] = {SEASON_IDS[season] for season in seasons} else: seasons = set() if "champion.ids" in query: champions = query["champion.ids"] params["champion"] = champions else: champions = set() if "queues" in query: queues = {Queue(queue) for queue in query["queues"]} params["queue"] = {QUEUE_IDS[queue] for queue in queues} else: queues = set() url = "https://{platform}.api.riotgames.com/lol/match/v4/matchlists/by-account/{accountId}".format(platform=query["platform"].value.lower(), accountId=query["accountId"]) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "matchlists/by-account/accountId") data = self._get(url, params, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError: data = {"matches": []} data["accountId"] = query["accountId"] data["region"] = query["platform"].region.value data["season"] = seasons data["champion"] = champions data["queue"] = queues if calling_method == "by_index": data["beginIndex"] = params["beginIndex"] data["endIndex"] = params["endIndex"] data["maxNumberOfMatches"] = query["maxNumberOfMatches"] else: data["beginTime"] = params["beginTime"] data["endTime"] = params["endTime"] for match in data["matches"]: match["accountId"] = query["accountId"] match["region"] = Platform(match["platformId"]).region.value return MatchListDto(data) _validate_get_many_match_list_query = Query. \ has("accountIds").as_(Iterable).also. \ has("platform").as_(Platform).also. \ can_have("beginTime").as_(int).also. \ can_have("endTime").as_(int).also. \ can_have("beginIndex").as_(int).also. \ can_have("endIndex").as_(int).also. \ can_have("seasons").as_(Iterable).also. \ can_have("champion.ids").as_(Iterable).also. \ can_have("queues").as_(Iterable) @get_many.register(MatchListDto) @validate_query(_validate_get_many_match_list_query, convert_region_to_platform) def get_many_match_list(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[MatchListDto, None, None]: params = {} if "beginIndex" in query: params["beginIndex"] = query["beginIndex"] if "endIndex" in query: params["endIndex"] = query["endIndex"] if "seasons" in query: seasons = {Season(season) for season in query["seasons"]} params["season"] = {SEASON_IDS[season] for season in seasons} else: seasons = set() if "champion.ids" in query: params["champion"] = {query["champion.ids"]} if "queues" in query: queues = {Queue(queue) for queue in query["queues"]} params["queue"] = {QUEUE_IDS[queue] for queue in queues} else: queues = set() def generator(): for id in query["accountIds"]: url = "https://{platform}.api.riotgames.com/lol/match/v4/matchlists/by-account/{accountId}".format(platform=query["platform"].value.lower(), accountId=id) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "matchlists/by-account/accountId") data = self._get(url, params, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["accountId"] = id data["region"] = query["platform"].region.value if "beginIndex" in query: data["beginIndex"] = query["beginIndex"] if "endIndex" in query: data["endIndex"] = query["endIndex"] if "seasons" in query: data["seasons"] = seasons if "champion.ids" in query: data["champion"] = params["champion"] if "queues" in query: params["queue"] = queues yield MatchListDto(data) return generator() _validate_get_timeline_query = Query. \ has("id").as_(int).also. \ has("platform").as_(Platform) @get.register(TimelineDto) @validate_query(_validate_get_timeline_query, convert_region_to_platform) def get_match_timeline(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> TimelineDto: url = "https://{platform}.api.riotgames.com/lol/match/v4/timelines/by-match/{id}".format(platform=query["platform"].value.lower(), id=query["id"]) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "timelines/by-match/id") data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["matchId"] = query["id"] data["region"] = query["platform"].region.value return TimelineDto(data) _validate_get_many_timeline_query = Query. \ has("ids").as_(Iterable).also. \ has("platform").as_(Platform) @get_many.register(TimelineDto) @validate_query(_validate_get_many_timeline_query, convert_region_to_platform) def get_many_match_timeline(self, query: MutableMapping[str, Any], context: PipelineContext = None) -> Generator[TimelineDto, None, None]: def generator(): for id in query["ids"]: url = "https://{platform}.api.riotgames.com/lol/match/v4/timelines/by-match/{id}".format(platform=query["platform"].value.lower(), id=id) try: app_limiter, method_limiter = self._get_rate_limiter(query["platform"], "timelines/by-match/id") data = self._get(url, {}, app_limiter=app_limiter, method_limiter=method_limiter) except APINotFoundError as error: raise NotFoundError(str(error)) from error data["matchId"] = id data["region"] = query["platform"].region.value yield TimelineDto(data) return generator()
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queue_services/events-listener/tests/integration/test_worker_queue.py
karthik-aot/sbc-auth
11
109679
<reponame>karthik-aot/sbc-auth # Copyright © 2019 Province of British Columbia # # 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. """Test Suite to ensure the worker routines are working as expected.""" import pytest from auth_api.models import Org as OrgModel from entity_queue_common.service_utils import subscribe_to_queue from tests.integration import factory_org_model from .utils import helper_add_event_to_queue @pytest.mark.asyncio async def test_events_listener_queue(app, session, stan_server, event_loop, client_id, events_stan, future): """Assert that events can be retrieved and decoded from the Queue.""" # Call back for the subscription from events_listener.worker import cb_subscription_handler # vars org_id = '1' status = 'lock' events_subject = 'test_subject' events_queue = 'test_queue' events_durable_name = 'test_durable' # Create a Credit Card Payment # register the handler to test it await subscribe_to_queue(events_stan, events_subject, events_queue, events_durable_name, cb_subscription_handler) # add an event to queue await helper_add_event_to_queue(events_stan, events_subject, org_id=org_id, action=status) assert True @pytest.mark.asyncio async def test_update_internal_payment(app, session, stan_server, event_loop, client_id, events_stan, future): """Assert that the update internal payment records works.""" # Call back for the subscription from events_listener.worker import cb_subscription_handler events_subject = 'test_subject' events_queue = 'test_queue' events_durable_name = 'test_durable' org = factory_org_model() id = org.id # register the handler to test it await subscribe_to_queue(events_stan, events_subject, events_queue, events_durable_name, cb_subscription_handler) # add an event to queue await helper_add_event_to_queue(events_stan, events_subject, org_id=org.id, action='lock') # Get the internal account and invoice and assert that the identifier is new identifier new_org = OrgModel.find_by_org_id(id) assert new_org.status_code == 'NSF_SUSPENDED'
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PIVX-Discord-master/bot.py
Sieres/PIVX-Discord-Master
1
198646
<filename>PIVX-Discord-master/bot.py import discord from discord.ext import commands from utils import output, parsing, checks, mysql_module import os, traceback config = parsing.parse_json('config.json') Mysql = mysql_module.Mysql() bot = commands.Bot(command_prefix="!", description=config["description"]) #command_prefix=commands.when_mentioned try: os.remove("log.txt") except FileNotFoundError: pass startup_extensions = os.listdir("./cogs") if "__pycache__" in startup_extensions: startup_extensions.remove("__pycache__") startup_extensions = [ext.replace('.py', '') for ext in startup_extensions] loaded_extensions = [] @bot.event async def on_ready(): output.info("Loading {} extension(s)...".format(len(startup_extensions))) for extension in startup_extensions: try: bot.load_extension("cogs.{}".format(extension.replace(".py", ""))) loaded_extensions.append(extension) except Exception as e: exc = '{}: {}'.format(type(e).__name__, e) output.error('Failed to load extension {}\n\t->{}'.format(extension, exc)) output.success('Successfully loaded the following extension(s); {}'.format(loaded_extensions)) async def send_cmd_help(ctx): if ctx.invoked_subcommand: pages = bot.formatter.format_help_for(ctx, ctx.invoked_subcommand) for page in pages: em = discord.Embed(title="Missing args :x:", description=page.strip("```").replace('<', '[').replace('>', ']'), color=discord.Color.red()) await bot.send_message(ctx.message.channel, embed=em) else: pages = bot.formatter.format_help_for(ctx, ctx.command) for page in pages: em = discord.Embed(title="Missing args :x:", description=page.strip("```").replace('<', '[').replace('>', ']'), color=discord.Color.red()) await bot.send_message(ctx.message.channel, embed=em) @bot.command(pass_context=True) @commands.check(checks.is_owner) async def shutdown(ctx): """Shut down the bot""" author = str(ctx.message.author) try: await bot.say("Shutting down...") await bot.logout() bot.loop.stop() output.info('{} has shut down the bot...'.format(author)) except Exception as e: exc = '{}: {}'.format(type(e).__name__, e) output.error('{} has attempted to shut down the bot, but the following ' 'exception occurred;\n\t->{}'.format(author, exc)) @bot.command(pass_context=True) @commands.check(checks.is_owner) async def load(ctx, module: str): """Load a cog located in /cogs""" author = str(ctx.message.author) module = module.strip() try: bot.load_extension("cogs.{}".format(module)) output.info('{} loaded module: {}'.format(author, module)) loaded_extensions.append(module) await bot.say("Successfully loaded {}.py".format(module)) except Exception as e: exc = '{}: {}'.format(type(e).__name__, e) output.error('{} attempted to load module \'{}\' but the following ' 'exception occured;\n\t->{}'.format(author, module, exc)) await bot.say('Failed to load extension {}\n\t->{}'.format(module, exc)) @bot.command(pass_context=True) @commands.check(checks.is_owner) async def unload(ctx, module: str): """Unload any loaded cog""" author = str(ctx.message.author) module = module.strip() try: bot.unload_extension("cogs.{}".format(module)) output.info('{} unloaded module: {}'.format(author, module)) startup_extensions.remove(module) await bot.say("Successfully unloaded {}.py".format(module)) except Exception as e: exc = '{}: {}'.format(type(e).__name__, e) await bot.say('Failed to load extension {}\n\t->{}'.format(module, exc)) @bot.command() @commands.check(checks.is_owner) async def loaded(): """List loaded cogs""" string = "" for cog in loaded_extensions: string += str(cog) + "\n" await bot.say('Currently loaded extensions:\n```{}```'.format(string)) @bot.command(pass_context=True) @commands.check(checks.is_owner) async def restart(ctx): """Restart the bot""" author = str(ctx.message.author) try: await bot.say("Restarting...") await bot.logout() bot.loop.stop() output.info('{} has restarted the bot...'.format(author)) os.system('sh restart.sh') except Exception as e: exc = '{}: {}'.format(type(e).__name__, e) output.error('{} has attempted to restart the bot, but the following ' 'exception occurred;\n\t->{}'.format(author, exc)) @bot.event async def on_server_join(server): output.info("Added to {0}".format(server.name)) Mysql.add_server(server) for channel in server.channels: Mysql.add_channel(channel) await bot.say(server.default_channel, "Hey {0}, {1} seems nice. To set me up run {2}configure otherwise I will work in all channels".format( server.owner.mention, server.name, config["prefix"])) @bot.event async def on_server_leave(server): Mysql.remove_server(server) output.info("Removed from {0}".format(server.name)) @bot.event async def on_channel_create(channel): Mysql.add_channel(channel) channelString = str(channel) if channelString.startswith("Direct Message"): output.info(channelString) else: output.info("Channel {0} added to {1}".format(channel.name, channel.server.name)) @bot.event async def on_channel_delete(channel): Mysql.remove_channel(channel) output.info("Channel {0} deleted from {1}".format(channel.name, channel.server.name)) @bot.event async def on_command_error(error, ctx): channel = ctx.message.channel if isinstance(error, commands.MissingRequiredArgument): await send_cmd_help(ctx) elif isinstance(error, commands.BadArgument): await send_cmd_help(ctx) elif isinstance(error, commands.CommandInvokeError): output.error("Exception in command '{}', {}".format(ctx.command.qualified_name, error.original)) oneliner = "Error in command '{}' - {}: {}\nIf this issue persists, Please report it in the support server.".format( ctx.command.qualified_name, type(error.original).__name__, str(error.original)) await ctx.bot.send_message(channel, oneliner) bot.run(config["discord"]["token"]) bot.loop.close()
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cwf2neo/tests/__init__.py
sintax1/cwf2neo
1
27170
<gh_stars>1-10 import sys # NOQA import os current_path = os.path.dirname(os.path.abspath(__file__)) sys.path.insert(0, current_path + '/../')
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common/web_client.py
newsettle/ns4_chatbot
51
26504
# -*- coding=utf-8 -*- import urllib2 import json import logger import traceback def send(apiUrl,data,method=None): logger.debug("调用内部系统[%s],data[%r]",apiUrl,data) try: data_json = json.dumps(data) headers = {'Content-Type': 'application/json'} # 设置数据为json格式，很重要 request = urllib2.Request(url=apiUrl, headers=headers, data=data_json) if method is not None: request.get_method = method response = urllib2.urlopen(request) result = {'code':response.getcode(),'content':response.read()} logger.debug("调用[%s]返回结果:%r",apiUrl,result) return result except Exception as e: #traceback.print_stack() logger.exception(e,"调用内部系统[%s],data[%r],发生错误[%r]", apiUrl, data,e) return None if __name__ == "__main__": logger.init_4_debug()
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tests/test_write.py
Aquaveo/gsshapyorm
0
116438
<reponame>Aquaveo/gsshapyorm """ ******************************************************************************** * Name: Write Tests * Author: <NAME> * Created On: May 16, 2013 * Copyright: (c) Brigham Young University 2013 * License: BSD 2-Clause ******************************************************************************** """ import uuid import os from unittest import TestCase, main from gsshapyorm.orm.file_io import MapTableFile, ProjectFileEventManager, PrecipFile, ChannelInputFile, \ StormPipeNetworkFile, HmetFile, NwsrfsFile, OrographicGageFile, GridPipeFile, GridStreamFile, TimeSeriesFile, \ OutputLocationFile, RasterMapFile, ProjectionFile, ReplaceParamFile, ReplaceValFile, LinkNodeDatasetFile, IndexMap from gsshapyorm.orm import ProjectFile from gsshapyorm.lib import db_tools as dbt class TestWriteMethods(TestCase): def setUp(self): # Find db directory path here = os.path.abspath(os.path.dirname(__file__)) self.dbName = '%s.db' % uuid.uuid4() self.db_path = os.path.join(here, 'db', 'standard.db') # Create Test DB sqlalchemy_url = dbt.init_sqlite_db(self.db_path) # Define workspace self.readDirectory = os.path.join(here, 'standard') self.writeDirectory = os.path.join(here, 'out') self.original = 'standard' self.name = 'standard' self.dir_list = ('run_2014_to_2017', 'run_2014_to_2017_2', 'run_2015_to_2017', 'run_2015_to_2017_1', 'run_2016_to_2017') for subdir in self.dir_list: try: os.mkdir(os.path.join(self.readDirectory, subdir)) except OSError: pass # Create DB Sessions session_maker = dbt.get_sessionmaker(sqlalchemy_url) readSession = session_maker() # Instantiate GSSHAPY ProjectFile object prjR = ProjectFile() # Invoke read project method prjR.readProject(directory=self.readDirectory, projectFileName='standard.prj', session=readSession) readSession.close() # create write session self.writeSession = session_maker() def tearDown(self): self.writeSession.close() self._delete_extra_dirs() # Remove temp database dbt.del_sqlite_db(self.db_path) # Clear out directory fileList = os.listdir(self.writeDirectory) for afile in fileList: if afile != ".gitignore": path = os.path.join(self.writeDirectory, afile) try: os.remove(path) except OSError: pass def test_project_file_write(self): """ Test ProjectFile write method """ # Query and invoke write method self._query_n_write(ProjectFile) # Test self._compare_files(self.original, self.name, 'prj') def test_channel_input_write(self): """ Test ChannelInputFile write method """ # Query and invoke write method self._query_n_write(ChannelInputFile) # Test self._compare_files(self.original, self.name, 'cif') def test_map_table_file_write(self): """ Test MapTableFile write method """ # Query and invoke write method self._query_n_write(MapTableFile) # Test self._compare_files(self.original, self.name, 'cmt') def test_precip_file_write(self): """ Test PrecipFile write method """ # Query and invoke write method self._query_n_write(PrecipFile) # Test self._compare_files(self.original, self.name, 'gag') def test_grid_pipe_file_write(self): """ Test GridPipeFile write method """ # Query and invoke write method self._query_n_write(GridPipeFile) # Test self._compare_files(self.original, self.name, 'gpi') def test_grid_stream_file_write(self): """ Test GridStreamFile write method """ # Query and invoke write method self._query_n_write(GridStreamFile) # Test self._compare_files(self.original, self.name, 'gst') def test_hmet_file_write(self): """ Test HmetFile write method """ # Query and invoke write method self._query_n_write_filename(HmetFile, 'hmet_wes.hmt') # Test self._compare_files('hmet_wes', 'hmet_wes', 'hmt') def test_output_location_file_write(self): """ Test OutputLocationFile write method """ # Query and invoke write method self._query_n_write_multiple(OutputLocationFile, 'ihl') # Test self._compare_files(self.original, self.name, 'ihl') def test_link_node_dataset_file_write(self): """ Test LinkNodeDatasetFile write method """ # Query and invoke write method self._query_n_write_multiple(LinkNodeDatasetFile, 'cdp') # Test self._compare_files(self.original, self.name, 'cdp') def test_raster_map_file_write(self): """ Test RasterMapFile write method """ # Query and invoke write method self._query_n_write_multiple(RasterMapFile, 'msk') # Test self._compare_files(self.original, self.name, 'msk') def test_projection_file_write(self): """ Test ProjectionFile write method """ # Query and invoke write method self._query_n_write(ProjectionFile) # Test self._compare_files('standard_prj', 'standard_prj', 'pro') def test_replace_param_file_write(self): """ Test ReplaceParamFile write method """ # Query and invoke write method self._query_n_write_filename(ReplaceParamFile, 'replace_param.txt') # Test self._compare_files('replace_param', 'replace_param', 'txt') def test_replace_val_file_write(self): """ Test ReplaceValFile write method """ # Query and invoke write method self._query_n_write_filename(ReplaceValFile, 'replace_val.txt') # Test self._compare_files('replace_val', 'replace_val', 'txt') def test_nwsrfs_file_write(self): """ Test NwsrfsFile write method """ # Query and invoke write method self._query_n_write_filename(NwsrfsFile, 'nwsrfs_elev.txt') # Test self._compare_files('nwsrfs_elev', 'nwsrfs_elev', 'txt') def test_oro_gage_file_write(self): """ Test OrographicGageFile write method """ # Query and invoke write method self._query_n_write_filename(OrographicGageFile, 'oro_gages.txt') # Test self._compare_files('oro_gages', 'oro_gages', 'txt') def test_evt_yml_file_write(self): """ Test ProjectFileEventManager write method """ # Query and invoke write method self._query_n_write_filename(ProjectFileEventManager, 'testyml.yml') # Test self._compare_files('testyml', 'testyml', 'yml') def test_evt_yml_file_add_write(self): """ Test ProjectFileEventManager add_event write method """ # Retrieve ProjectFileEventManager from database prjEvtMng = self.writeSession.query(ProjectFileEventManager).one() a = prjEvtMng.add_event(name="event3", subfolder="run_2015_to_2017", session=self.writeSession) assert a.name == "event3" assert a.subfolder == "run_2015_to_2017_2" a1 = prjEvtMng.add_event(name="event3", subfolder="run_2015_to_2017", session=self.writeSession) assert a1.name == "event3" assert a1.subfolder == "run_2015_to_2017_3" b = prjEvtMng.generate_event(session=self.writeSession) assert b.name == "event_1" assert b.subfolder == "event_1" b1 = prjEvtMng.generate_event(session=self.writeSession) assert b1.name == "event_2" assert b1.subfolder == "event_2" c = prjEvtMng.add_event(name="event2", subfolder="run_2014_to_2017", session=self.writeSession) assert c.name == "event2" assert c.subfolder == "run_2014_to_2017_3" c1 = prjEvtMng.add_event(name="event2", subfolder="run_2014_to_2017", session=self.writeSession) assert c1.name == "event2" assert c1.subfolder == "run_2014_to_2017_4" # Query and invoke write method self._query_n_write_filename(ProjectFileEventManager, 'testyml2.yml') # Test self._compare_files('testyml2', 'testyml2', 'yml') def test_storm_pipe_network_file_write(self): """ Test StormPipeNetworkFile write method """ # Query and invoke write method self._query_n_write(StormPipeNetworkFile) # Test self._compare_files(self.original, self.name, 'spn') def test_time_series_file_write(self): """ Test TimeSeriesFile write method """ # Query and invoke write method self._query_n_write_multiple(TimeSeriesFile, 'ohl') # Test self._compare_files(self.original, self.name, 'ohl') def test_index_map_write(self): """ Test IndexMap write method """ # Retrieve file from database idx = self.writeSession.query(IndexMap).\ filter(IndexMap.filename == 'Soil.idx').\ one() # Invoke write method idx.write(session=self.writeSession, directory=self.writeDirectory, name='soil_new_name') # Test self._compare_files('Soil', 'soil_new_name', 'idx') def test_project_file_write_all(self): """ Test ProjectFile write all method """ # Retrieve ProjectFile from database projectFile = self.writeSession.query(ProjectFile).one() # Invoke write all method projectFile.writeProject(session=self.writeSession, directory=self.writeDirectory, name='standard') # Compare all files self._compare_directories(self.readDirectory, self.writeDirectory) def test_project_file_write_input(self): """ Test ProjecFile write input method """ # Retrieve ProjectFile from database projectFile = self.writeSession.query(ProjectFile).one() # Invoke write input method projectFile.writeInput(session=self.writeSession, directory=self.writeDirectory, name='standard') # Compare all files self._compare_directories(self.readDirectory, self.writeDirectory) def test_project_file_write_output(self): """ Test ProjectFile write output method """ # Retrieve ProjectFile from database projectFile = self.writeSession.query(ProjectFile).one() # Invoke write output method projectFile.writeOutput(session=self.writeSession, directory=self.writeDirectory, name='standard') # Compare all files self._compare_directories(self.readDirectory, self.writeDirectory) def _query_n_write(self, fileIO): """ Query database and write file method """ # Retrieve file from database instance = self.writeSession.query(fileIO).one() # Invoke write method instance.write(session=self.writeSession, directory=self.writeDirectory, name=self.name) def _query_n_write_filename(self, fileIO, filename): """ Query database and write file method """ # Retrieve file from database instance = self.writeSession.query(fileIO).one() # Invoke write method instance.write(session=self.writeSession, directory=self.writeDirectory, name=filename) def _query_n_write_multiple(self, fileIO, ext): """ Query database and write file method for fileIO object that could have multiple extensions """ # Retrieve file from database instance = self.writeSession.query(fileIO).\ filter(fileIO.fileExtension == ext).\ one() # Invoke write method instance.write(session=self.writeSession, directory=self.writeDirectory, name=self.name) def _compare_files(self, original, new, ext): """ Compare the contents of two files """ if ext == 'cmt': original = '{0}_compare'.format(original) filenameO = '%s.%s' % (original, ext) filePathO = os.path.join(self.readDirectory, filenameO) filenameN = '%s.%s' % (new, ext) filePathN = os.path.join(self.writeDirectory, filenameN) with open(filePathO) as fileO: contentsO = fileO.read() linesO = contentsO.strip().split() with open(filePathN) as fileN: contentsN = fileN.read() linesN = contentsN.strip().split() self.assertEqual(linesO, linesN) def _compare_directories(self, dir1, dir2): """ Compare the contents of the files of two directories """ self._delete_extra_dirs() fileList2 = os.listdir(dir2) for afile in fileList2: if not os.path.basename(afile).startswith("."): name = afile.split('.')[0] ext = afile.split('.')[1] # Compare files with same name self._compare_files(name, name, ext) def _list_compare(self, listone, listtwo): for one, two in zip(listone, listtwo): self.assertEqual(one, two) def _delete_extra_dirs(self): for subdir in self.dir_list: try: os.rmdir(os.path.join(self.readDirectory, subdir)) except OSError: pass if __name__ == '__main__': main()
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image_extractor.py
IstoVisio/script_image_extractor
0
21160
import os import sys import syglass as sy from syglass import pyglass import numpy as np import tifffile import subprocess def extract(projectPath): project = sy.get_project(projectPath) head, tail = os.path.split(projectPath) # Get a dictionary showing the number of blocks in each level #codebreak() resolution_map = project.get_resolution_map() # Calculate the index of the highest resolution level max_resolution_level = len(resolution_map) - 1 # Determine the number of blocks in this level block_count = resolution_map[max_resolution_level] # get size of project total_size = project.get_size(max_resolution_level) xsize = total_size[1] ysize = total_size[2] zslices = total_size[0] dimensions = np.asarray([1,xsize, ysize]) offset = np.asarray([0,0,0]) os.chdir(os.path.dirname(projectPath)) for slice in range(zslices): s = str(slice).zfill(5) offset[0] = slice block = project.get_custom_block(0, max_resolution_level, offset, dimensions) data = block.data print(s + ".tiff") tifffile.imwrite(tail + "_" + s + ".tiff", data) subprocess.run(['explorer', head]) def main(): print("Image Extractor, by <NAME>") print("Attempts to extract the original data volume from a syGlass project") print("and write it to a series of TIFF files") print("---------------------------------------") print("Usage: Highlight a project and use the Script Launcher in syGlass.") print("---------------------------------------") print(sys.argv) for syGlassProjectPath in sys.argv: print("Extracting project from: " + syGlassProjectPath) extract(syGlassProjectPath) if __name__== "__main__": main()
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src/TMscore_test.py
h3nnn4n/TMscore.py
2
190954
<filename>src/TMscore_test.py import pytest from TMscore import TMscore def test_init(): tmscore = TMscore("./TMscore") assert tmscore is not None def test_init_no_args(): tmscore = TMscore() assert tmscore is not None def test_init_wrong_path(): with pytest.raises(FileNotFoundError): TMscore('this path is bananas') def test_call(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") data = tmscore.get_all() assert data['gdt_ha'] == (0.2772, (0.1304, 0.1957, 0.2609, 0.5217)) assert data['gdt_ts'] == (0.4402, (0.1957, 0.2609, 0.5217, 0.7826)) assert data['maxsub'] == 0.3286 assert data['tm_score'] == 0.2875 assert data['rmsd'] == 6.709 def test_get_rmsd(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_rmsd() == 6.709 def test_get_tm_score(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_tm_score() == 0.2875 def test_get_gdt_ts(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_gdt_ts() == 0.4402 def test_get_gdt_ts_info(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_gdt_ts_info() == (0.4402, (0.1957, 0.2609, 0.5217, 0.7826)) def test_get_gdt_ha(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_gdt_ha() == 0.2772 def test_get_gdt_ha_info(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_gdt_ha_info() == (0.2772, (0.1304, 0.1957, 0.2609, 0.5217)) def test_get_maxsub(): tmscore = TMscore("./TMscore") tmscore("../proteins/1crn.pdb", "../proteins/best.pdb") assert tmscore.get_maxsub() == 0.3286
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src/apytizer/utils/__init__.py
seanssullivan/apytizer
1
1614662
<filename>src/apytizer/utils/__init__.py # -*- coding: utf-8 -*- # pylint: skip-file from .generate_key import generate_key from .merge import merge
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lists_carousels/urls.py
snoop2head/exercise_curation_django
3
122663
<gh_stars>1-10 from django.urls import path from . import views # making separate urls.py for rooms app_name = "lists_carousels" # receiving "localhost/rooms/110230" to use it as primary key for database urlpatterns = []
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forms/TranslationForm.py
greshniksv/PBDatabaseGenerator
0
198923
<reponame>greshniksv/PBDatabaseGenerator from .TranslationFormUi import Ui_TranslationForm from PyQt5 import QtWidgets from PyQt5.QtGui import QStandardItemModel, QStandardItem from PyQt5.QtWidgets import QFileDialog from PyQt5.QtWidgets import QMessageBox from pydantic import ValidationError from models.TranslationModel import TranslationModel from .MetadataForm import MetadataWidget from .TranslationFormUi import Ui_TranslationForm class TranslationForm(QtWidgets.QMainWindow, Ui_TranslationForm): def __init__(self, parent): # Это здесь нужно для доступа к переменным, методам # и т.д. в файле design.py super().__init__() self.parent_form = parent self.setupUi(self) self.translation_model = None self.model = QStandardItemModel() self.tvMetadata.setModel(self.model) self.model.setHorizontalHeaderLabels(["Name", "Value", "Type", "Row Type"]) self.tvMetadata.setColumnWidth(0, 200) self.tvMetadata.setColumnWidth(1, 290) self.tvMetadata.setColumnWidth(2, 290) self.tvMetadata.setColumnWidth(3, 100) # this column should be read-only self.btnAddMetodata.clicked.connect(self.add_metadata) self.btnRemoveMetodata.clicked.connect(self.remove_metadata) self.btnSave.clicked.connect(self.save) self.btnBrowseFile.clicked.connect(self.open_file_names_dialog) self.setFixedSize(self.width(), self.height()-20) def apply_model(self): model = self.translation_model self.txbLangId.setText(model.language) self.txbDraftBy.setText(model.draft_by) self.txbSlug.setText(model.slug) self.txbPermalink.setText(model.permalink) self.txbCreatedBy.setText(model.created_by) self.txbAllowedChildren.setText(model.allowed_children) self.txbTitle.setText(model.title) self.txbIsPublished.setText(model.is_published) self.txbFile.setText(model.file) # Clear while self.model.rowCount() > 0: self.model.removeRow(0) for item in model.metadata: self.model.appendRow( [ QStandardItem(item['name']), QStandardItem(item['value']), QStandardItem(item['type']), QStandardItem('MetaData') ]) for item in model.content_data: self.model.appendRow( [ QStandardItem(item['name']), QStandardItem(item['value']), QStandardItem(item['type']), QStandardItem('ContentData') ]) def open_file_names_dialog(self): options = QFileDialog.Options() options |= QFileDialog.DontUseNativeDialog files, _ = QFileDialog.getOpenFileNames(self, "QFileDialog.getOpenFileNames()", "", "All Files (*);;", options=options) if len(files) > 0: self.txbFile.setText(files[0]) def save(self): try: metadata = [] content_data = [] row_count = self.model.rowCount() for row in range(row_count): name = self.model.data(self.model.index(row, 0)) value = self.model.data(self.model.index(row, 1)) value_type = self.model.data(self.model.index(row, 2)) row_type = self.model.data(self.model.index(row, 3)) if row_type == "ContentData": content_data.append({'name': name, 'value': value, 'type': value_type}) if row_type == "MetaData": metadata.append({'name': name, 'value': value, 'type': value_type}) self.translation_model = TranslationModel( language=self.txbLangId.text(), draft_by=self.txbDraftBy.text(), slug=self.txbSlug.text(), permalink=self.txbPermalink.text(), created_by=self.txbCreatedBy.text(), allowed_children=self.txbAllowedChildren.text(), title=self.txbTitle.text(), is_published=self.txbIsPublished.text(), file=self.txbFile.text(), metadata=metadata, content_data=content_data ) self.parent_form.set_translation(self.translation_model) except ValidationError as e: error_acquire = True QMessageBox.about(self, 'Error message', '{}'.format(e)) except BaseException as err: error_acquire = True QMessageBox.about(self, 'Error message', 'An exception occurred: {}'.format(err)) self.close() def remove_metadata(self): indexes = self.tvMetadata.selectedIndexes() for index in indexes: self.model.removeRow(index.row()) def add_metadata(self): try: dialog = MetadataWidget() result = dialog.exec_() if result == 1: data = dialog.return_data() self.model.appendRow( [ QStandardItem(data['name']), QStandardItem(data['value']), QStandardItem(data['type']), QStandardItem(data['row_type']) ]) except BaseException as err: QMessageBox.about(self, 'PyQt5 message', 'An exception occurred: {}'.format(err))
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src/client/pydaos/raw/conversion.py
gczsjdy/daos
1
8558
#!/usr/bin/python """ (C) Copyright 2018 Intel Corporation. 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. GOVERNMENT LICENSE RIGHTS-OPEN SOURCE SOFTWARE The Government's rights to use, modify, reproduce, release, perform, display, or disclose this software are subject to the terms of the Apache License as provided in Contract No. B609815. Any reproduction of computer software, computer software documentation, or portions thereof marked with this legend must also reproduce the markings. """ import ctypes import uuid def c_uuid_to_str(uuid): """ utility function to convert a C uuid into a standard string format """ uuid_str = '{:02X}{:02X}{:02X}{:02X}-{:02X}{:02X}-{:02X}{:02X}-{:02X}'\ '{:02X}-{:02X}{:02X}{:02X}{:02X}{:02X}{:02X}'.format( uuid[0], uuid[1], uuid[2], uuid[3], uuid[4], uuid[5], uuid[6], uuid[7], uuid[8], uuid[9], uuid[10], uuid[11], uuid[12], uuid[13], uuid[14], uuid[15]) return uuid_str def c_uuid(p_uuid, c_uuid): """ utility function to create a UUID in C format from a python UUID """ hexstr = p_uuid.hex for i in range(0, 31, 2): c_uuid[int(i/2)] = int(hexstr[i:i+2], 16) def str_to_c_uuid(uuidstr): """ utility function to convert string format uuid to a C uuid """ uuidstr2 = '{' + uuidstr + '}' puuid = uuid.UUID(uuidstr2) cuuid = (ctypes.c_ubyte * 16)() c_uuid(puuid, cuuid) return cuuid
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utils/pvacapi/controllers/database.py
mrichters/pVACtools
96
24591
import os import re import csv import sys import json import yaml import time import socket import connexion import postgresql as psql from flask import current_app from urllib.parse import urlencode from hashlib import md5 from bokeh.embed import server_document from .processes import fetch_process, is_running, process_info from .utils import column_filter float_pattern = re.compile(r'^\d*\.\d+$') int_pattern = re.compile(r'^-?\d+$') NA_pattern = re.compile(r'^NA$') queryfilters = re.compile(r'(.+)(<=?|>=?|!=|==)(.+)') def init_column_mapping(row, schema): """Generate initial estimates of column data types""" defs = {column_filter(col): 'text' for col in row} # Apply predefined table schema defs.update({k: v for (k, v) in schema.items() if k in defs}) for (col, val) in row.items(): col = column_filter(col) if col not in schema: if int_pattern.match(val): try: int(val) print("Assigning int to", col, "based on", val) defs[col] = 'integer' except ValueError: print("ERROR: Int mismatch:", val) elif float_pattern.match(val): try: float(val) print("Assigning float to", col, "based on", val) defs[col] = 'decimal' except ValueError: print("ERROR: Float mismatch:", val) mapping = {} for (col, val) in defs.items(): if 'int' in val: mapping[col] = int elif val == 'decimal': mapping[col] = float else: mapping[col] = str return (mapping, defs) def column_mapping(row, mapping, schema): """Apply filtering to the current row. Detect if column data types need to be changed""" output = {} changes = {} for (col, val) in row.items(): col = column_filter(col) if val == None or NA_pattern.match(str(val)): output[col] = None continue if col not in schema and mapping[col] == str: if int_pattern.match(val): try: int(val) print("Assigning int to", col, "based on", val) mapping[col] = int changes[col] = int except ValueError: print("ERROR: Int mismatch:", val) elif float_pattern.match(val): try: float(val) print("Assigning float to", col, "based on", val) mapping[col] = float changes[col] = float except ValueError: print("ERROR: Float mismatch:", val) try: output[col] = mapping[col](val) except ValueError: output[col] = None return (mapping, output, changes) def old_file_read(db, CREATE_TABLE, tablekey, column_names, reader, mapping): with db.xact(): db.execute(CREATE_TABLE) # table marked for insertion during original attempt, so don't need to here # prepare the insertion query insert = db.prepare("INSERT INTO %s (%s) VALUES (%s)" % ( tablekey, ','.join(column_names), ','.join('$%d' % i for (_, i) in zip( column_names, range(1, sys.maxsize) )) )) update = "ALTER TABLE %s " % tablekey for row in reader: # process each row # We format the data in the row and update column data types, if # necessary (mapping, formatted, changes) = column_mapping(row, mapping, current_app.config['schema']) if len(changes): #Generate a query to alter the table schema, if any changes are required alter_cols = [] for (k, v) in changes.items(): # if there were any changes to the data type, update the table # since we only ever update a text column to int/decimal, then # it's okay to nullify the data typ = '' if v == int: typ = 'bigint' if k in {'start', 'stop'} else 'integer' elif v == float: typ = 'decimal' alter_cols.append( "ALTER COLUMN %s SET DATA TYPE %s USING %s::%s" % ( k, typ, k, typ ) ) # Re-generate the insert statement since the data types changed print("Alter:", update + ','.join(alter_cols)) db.execute(update + ','.join(alter_cols)) insert = db.prepare("INSERT INTO %s (%s) VALUES (%s)" % ( tablekey, ','.join(column_names), ','.join('$%d' % i for (_, i) in zip( column_names, range(1, sys.maxsize) )) )) # insert the row insert(*[formatted[column] for column in column_names]) def table_transaction(file_permissions, db, CREATE_TABLE, tablekey, all_tablecolumns, raw_reader, column_names, mapping): with db.xact(): db.execute(CREATE_TABLE) db.prepare("LOCK TABLE %s IN ACCESS EXCLUSIVE MODE" % (tablekey)) copy_query = "COPY %s (%s) FROM '%s' WITH FREEZE NULL 'NA' DELIMITER E'\t' CSV HEADER" % (tablekey, all_tablecolumns, raw_reader.name) #copy_query may result in psql.exceptions.InsufficientPrivilegeError when run; workaround attempted below if file_permissions: #mark the table for deletion when the server shuts down #don't need to mark table for deletion during second attempt if 'db-clean' not in current_app.config: current_app.config['db-clean'] = [tablekey] else: current_app.config['db-clean'].append(tablekey) #attempt file copy db.execute(copy_query) else: import subprocess filedest = "/tmp/"+os.path.basename(raw_reader.name) subprocess.run(["mktemp", filedest], stdout=subprocess.DEVNULL) subprocess.run(["cp", raw_reader.name, filedest]) subprocess.run(["chmod", "666", filedest]) copy_query = "COPY %s (%s) FROM '%s' WITH FREEZE NULL 'NA' DELIMITER E'\t' CSV HEADER" % (tablekey, all_tablecolumns, filedest) try: db.execute(copy_query) print("...Success") finally: subprocess.run(["rm", filedest]) col_val_query = "SELECT " for col_name in column_names: col_val_query += "(select %s from %s where %s is not null limit 1), "%(col_name, tablekey, col_name) col_val_query = col_val_query[:-2] col_values = db.prepare(col_val_query) values = col_values()[0] update = "ALTER TABLE %s " % tablekey row = dict(zip(col_values.column_names, values)) (mapping, formatted, changes) = column_mapping(row, mapping, current_app.config['schema']) if len(changes): #Generate a query to alter the table schema, if any changes are required alter_cols = [] for (k, v) in changes.items(): # if there were any changes to the data type, update the table # since we only ever update a text column to int/decimal, then # it's okay to nullify the data typ = '' if v == int: typ = 'bigint' if k in {'start', 'stop'} else 'integer' elif v == float: typ = 'decimal' alter_cols.append( "ALTER COLUMN %s SET DATA TYPE %s USING %s::%s" % ( k, typ, k, typ ) ) print("Alter:", update + ','.join(alter_cols)) db.execute(update + ','.join(alter_cols)) def create_table(parentID, fileID, data, tablekey, db): # Open a reader to cache the file in the database if parentID != -1: process = fetch_process(parentID, data, current_app.config['storage']['children']) if not process[0]: return ( { "code": 400, "message": "The requested process (%d) does not exist" % parentID, "fields": "parentID" }, 400 ) if is_running(process): return ( { "code": 400, "message": "The requested process (%d) is still running" % parentID, "fields": "parentID" }, 400 ) if str(fileID) not in process[0]['files']: return ( { "code": 400, "message": "The requested fileID (%s) does not exist for this process (%d)" % (fileID, parentID), "fields": "fileID" }, 400 ) raw_reader = open(process[0]['files'][fileID]['fullname']) else: if str(fileID) not in data['visualize']: return ( { "code": 400, "message": "The requested fileID (%s) does not exist in the visualize" % fileID, "fields": "fileID" }, 400 ) raw_reader = open(data['visualize'][str(fileID)]['fullname']) if not raw_reader.name.endswith('.tsv'): ext = os.path.splitext(raw_reader.name)[1].lower() if len(ext) and ext[0] == '.': ext = ext[1:] return serve_as(raw_reader, ext) reader = csv.DictReader(raw_reader, delimiter='\t') tmp_reader = open(raw_reader.name) tmp = csv.DictReader(tmp_reader, delimiter='\t') try: init = next(tmp) except StopIteration: return [] tmp_reader.close() # Get an initial estimate of column datatypes from the first row (mapping, column_names) = init_column_mapping(init, current_app.config['schema']) tablecolumns = "\n".join( # use the estimated types to create the table "%s %s," % (colname, column_names[colname]) for colname in column_names )[:-1] CREATE_TABLE = "CREATE TABLE %s (\ rowid SERIAL PRIMARY KEY NOT NULL,\ %s\ )" % (tablekey, tablecolumns) all_tablecolumns = ', '.join(column_filter(col) for col in reader.fieldnames) try: table_transaction(True, db, CREATE_TABLE, tablekey, all_tablecolumns, raw_reader, column_names, mapping) except psql.exceptions.UniqueError: #If another transaction already created specified table, pass pass except psql.exceptions.InsufficientPrivilegeError as e: #can occur when postgres user unable to open file due to permissions; specifically for travis-ci tests #check if resulting from postgres user permissions if e.args[0].startswith("must be superuser"): print("WARNING: Postgres user is not a super user; visualization time may be slow") old_file_read(db, CREATE_TABLE, tablekey, column_names, reader, mapping) #use inefficient file-read-to-db method else: #attempt to resolve by copying file to /tmp/, changing its permissions, and accessing it there try: print("InsufficientPrivilegeError raised in accessing file.\nAttempting workaround...") table_transaction(False, db, CREATE_TABLE, tablekey, all_tablecolumns, raw_reader, column_names, mapping) except psql.exceptions.InsufficientPrivilegeError: print("Postgres could not access file. Check to make sure that both the " "file and your current postgres user has the appropriate permissions.") raise raw_reader.close() def filterfile(parentID, fileID, count, page, filters, sort, direction): """Gets the file ID belonging to the parent.\ For result files, the parentID is the process ID that spawned them.\ For visualize files, the parentID is -1""" data = current_app.config['storage']['loader']() # first, generate the key tablekey = "data_%s_%s" % ( (parentID if parentID >= 0 else 'visualize'), fileID ) # check if the table exists: db = psql.open("localhost/pvacseq") fileID = str(fileID) with db.xact(): query = db.prepare("SELECT 1 FROM information_schema.tables WHERE table_name = $1") response = query(tablekey) if not len(response): # table does not exist table_errors = create_table(parentID, fileID, data, tablekey, db) if table_errors != None: return table_errors #with db.synchronizer: # test_query = db.prepare("SELECT 1 FROM information_schema.tables WHERE table_name = $1") # test_response = query(tablekey) with db.xact(): typequery = db.prepare( "SELECT column_name, data_type FROM information_schema.columns WHERE table_name = $1" ) column_defs = typequery(tablekey) column_maps = {} for (col, typ) in column_defs: if 'int' in typ: column_maps[col] = int elif typ == 'numeric'or typ == 'decimal': column_maps[col] = float else: column_maps[col] = str formatted_filters = [] for i in range(len(filters)): f = filters[i].strip() if not len(f): continue result = queryfilters.match(f) if not result: return ({ "code": 400, "message": "Encountered an invalid filter (%s)" % f, "fields": "filters" }, 400) colname = column_filter(result.group(1)) if colname not in column_maps: return ({ "code": 400, "message": "Unknown column name %s" % result.group(1), "fields": "filters" }, 400) op = result.group(2) typ = column_maps[colname] val = None try: val = column_maps[colname]( result.group(3) ) except ValueError: return ({ "code": 400, "message": "Value %s cannot be formatted to match the type of column %s (%s)" % ( result.group(3), result.group(1), typ ) }, 400) if typ == str and (op in {'==', '!='}): formatted_filters.append( json.dumps(colname) + (' not ' if '!' in op else ' ') + "LIKE '%s'" % ( json.dumps(val)[1:-1] ) ) else: # type is numerical op = op.replace('==', '=') formatted_filters.append( '%s %s %s' % ( json.dumps(colname), op, json.dumps(val) ) ) raw_query = "SELECT %s FROM %s" % ( ','.join([k[0] for k in column_defs]), tablekey ) if len(formatted_filters): raw_query += " WHERE " + " AND ".join(formatted_filters) if sort: if column_filter(sort) not in column_maps: return ({ 'code': 400, 'message': 'Invalid column name %s' % sort, 'fields': 'sort' }, 400) raw_query += " ORDER BY %s" % (column_filter(sort)) if direction: raw_query += " " + direction if count: raw_query += " LIMIT %d" % count if page: raw_query += " OFFSET %d" % (page * count) print("Query:", raw_query) import decimal with db.xact('SERIALIZABLE', 'READ ONLY DEFERRABLE'): query = db.prepare(raw_query) decimalizer = lambda x: (float(x) if type(x) == decimal.Decimal else x) result = [ { colname: decimalizer(value) for (colname, value) in zip( [k[0] for k in column_defs], [val for val in row] ) } for row in query.rows() ] db.close() return result def fileschema(parentID, fileID): data = current_app.config['storage']['loader']() tablekey = "data_%s_%s" % ( (parentID if parentID >= 0 else 'visualize'), fileID ) # check if the table exists: db = psql.open("localhost/pvacseq") with db.xact(): query = db.prepare("SELECT 1 FROM information_schema.tables WHERE table_name = $1") if not len(query(tablekey)): # table does not exist return ({ 'code': 400, 'message': "The requested file has not been loaded into the Postgres database", 'fields': "fileID" }, 400) typequery = db.prepare("SELECT column_name, data_type FROM information_schema.columns WHERE table_name = $1") result = { key: val for (key, val) in typequery(tablekey) } db.close() return result def serve_as(reader, filetype): if filetype == 'json': return { 'filetype':'json', 'content':json.load(reader) } elif filetype == 'yaml' or filetype == 'yml': return { 'filetype':'yaml', 'content':yaml.load(reader.read()) } elif filetype == 'log': return { 'filetype':'log', 'content':[line.rstrip() for line in reader.readlines()] } else: return { 'filetype':'raw', 'content':reader.read() } def visualize(parentID, fileID): vis = visualize_script(parentID, fileID) return '<html><head></head><body>%s</body></html'%(vis if type(vis)!=tuple else vis[0]) def visualize_script(parentID, fileID): """Return an HTML document containing the requested table visualization""" from .files import results_getcols data = current_app.config['storage']['loader']() #first call filterfile to load the table if it's not loaded already result = filterfile(parentID, fileID, 1, 0, '', 'rowid', 'ASC') if type(result) != list: return ( { 'code':400, 'message':json.dumps(result), 'fields':'unknown', }, 400 ) if len(result) == 0 or type(result) == dict: return ( 'Results file contains no data - cannot visualize' ) cols = results_getcols(parentID, fileID) if type(cols) != dict: return ( { 'code':400, 'message':json.dumps(cols), 'fields':'unknown' }, 400 ) proc_data = process_info(parentID) if type(proc_data)==dict and 'parameters' in proc_data and 'sample_name' in proc_data['parameters']: sample = proc_data['parameters']['sample_name'] elif parentID == -1: sample = data['visualize'][str(fileID)]['display_name'].rsplit(".", 1)[0] else: sample = 'Unknown Sample' if current_app.PROXY_IP_ADDRESS is not None: IP = current_app.PROXY_IP_ADDRESS else: IP = current_app.IP_ADDRESS return ( server_document( url="http://" + IP + ":5006/visualizations", arguments={ 'target-process': parentID, 'target-file': fileID, 'cols': json.dumps(cols), 'samplename': sample } ) )
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Loan-Approval-Analysis/code.py
pavanmakineni/ga-learner-dsb-repo
0
133787
<reponame>pavanmakineni/ga-learner-dsb-repo # -------------- # Import packages import numpy as np import pandas as pd from scipy.stats import mode # code starts here bank=pd.read_csv(path,sep=',',header='infer') #print(bank) categorical_var = bank.select_dtypes(include = 'object') #print(categorical_var) numerical_var = bank.select_dtypes(include = 'number') print(numerical_var) # code ends here # -------------- # code starts here import pandas as pd print(bank.columns) banks = bank.drop(columns = 'Loan_ID') print(banks.columns) print(banks.isnull().sum()) bank_mode1 = banks.mode() print(bank_mode1) bank_mode = banks.mode().iloc[0] print(bank_mode) banks.fillna(bank_mode, inplace=True) print(banks.isnull().sum()) #code ends here # -------------- # Code starts here import pandas as pd avg_loan_amount = pd.pivot_table(banks,index=['Gender','Married','Self_Employed'],values='LoanAmount',aggfunc='mean') print(avg_loan_amount) print(type(avg_loan_amount)) # code ends here # -------------- # code starts here import pandas as pd loan_status = 614 loan_approved_se = banks[(banks['Self_Employed'] == 'Yes') & (banks['Loan_Status'] == 'Y')] #print(loan_approved_se) print(type(loan_approved_se)) loan_approved_nse = banks[(banks['Self_Employed'] == 'No') & (banks['Loan_Status'] == 'Y')] #print(loan_approved_nse) print(type(loan_approved_nse)) print(loan_approved_se.count()) print(loan_approved_se.count().iloc[0]) percentage_se = (loan_approved_se.count().iloc[0]/loan_status) * 100 print(percentage_se) percentage_nse = (loan_approved_nse.count().iloc[0]/loan_status) * 100 print(percentage_nse) # code ends here # -------------- # code starts here import pandas as pd print(banks.columns) def convert_to_year(months): return int(months)/12 loan_term = banks['Loan_Amount_Term'].apply(lambda x:convert_to_year(x)) #print(loan_term) print(type(loan_term)) print(banks.columns) big_loan_term1 = loan_term[loan_term >= 25].count() print(big_loan_term1) print(type(big_loan_term1)) big_loan_term = len(loan_term[loan_term >= 25]) print(big_loan_term) print(type(big_loan_term)) # code ends here # -------------- # code starts here import pandas as pd loan_groupby = banks.groupby('Loan_Status') print(loan_groupby) loan_groupby = loan_groupby['ApplicantIncome','Credit_History'] print(loan_groupby) mean_values = loan_groupby.apply(np.mean) print(mean_values) # code ends here
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Documentation_generator/ivml_documentation_from_file.py
jegentile/IVML
8
51504
__author__ = 'jgentile' class IVMLDocumentationFromFile: def __init__(self,file_name): self.__file_name = file_name self.__file = open(file_name) print ' Document generator looking at ',file_name self.__ivml_object_documentation = '\0' self.__type = '' self.__ivml_non_required_attributes = {} self.__ivml_required_attributes = {} self.__svg_attributes = {} self.__events = {} self.__name = "" self.__description = "" def change_from_camel_case(self,string): str = string for i in range(65,91): str = str.replace(chr(i),'-'+chr(i+32)) return str def parse(self): on_line = 0 for line in self.__file: #check to see if the first line annotates an IVML object if on_line ==0: stripped_line = line.replace(' ','').replace('\t','').rstrip() array = stripped_line.split(':') #if the first line in the JavaScript file is not annotated for the documentaion, return if not array[0] == '//@defining' or not len(array) ==3: print " WARNING: First line of",self.__file_name," file does not have proper annotation. Skipping." return print array if array[1] == 'ivml.chart': self.__type = 'chart' if array[1] == 'ivml.visualElement': self.__type = 'visual_element' if array[1] == 'ivml.group': self.__type = 'group' print 'Name: ', array[2]," --- type:",self.__type self.__name = self.change_from_camel_case( array[2]) if on_line > 0 and self.__type: if '//@' in line: struct = 0 offset = 1 if '//@i' in line: struct = self.__ivml_non_required_attributes if '//@ir' in line: struct = self.__ivml_required_attributes offset = 2 if '//@s' in line: struct = self.__svg_attributes if '//@e' in line: struct = self.__events if '//@description' in line: self.__description = line.split('//@description')[1].rstrip() if not struct == 0: attribute = line.strip().replace(' ','').replace('\t','').split(':')[0] struct[self.change_from_camel_case(attribute)] = line.split('//@')[len(line.split('//@'))-1][offset:].strip().rstrip().replace('#','\#').replace('_','\_') on_line+=1 ''' print 'ivml',self.__ivml_attributes print 'svg',self.__svg_attributes print 'events',self.__events ''' def get_type(self): if self.__type: return self.__type def get_ivml_required_attributes(self): return self.__ivml_required_attributes def get_ivml_non_required_attributes(self): return self.__ivml_non_required_attributes def get_svg_attributes(self): return self.__svg_attributes def get_event_attributes(self): return self.__events def get_name(self): return self.__name def get_description(self): return self.__description
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bot_python/pwm_test.py
WillWagnerIV/gis_bot
1
179294
<reponame>WillWagnerIV/gis_bot import time from adafruit_servokit import ServoKit # Set channels to the number of servo channels on your kit. # 8 for FeatherWing, 16 for Shield/HAT/Bonnet. kit = ServoKit(channels=8) kit.servo[0].angle = 180 kit.continuous_servo[1].throttle = 1 time.sleep(1) kit.continuous_servo[1].throttle = -1 time.sleep(1) kit.servo[0].angle = 0 kit.continuous_servo[1].throttle = 0
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Level/__init__.py
PyRectangle/GreyRectangle
3
18786
from Level.Render import Render from Level.Data import Data from Constants import * import os class Level: def __init__(self, folder, main): self.main = main self.name = folder self.folder = LEVEL_PATH + "/" + folder self.dataFiles = [] files = os.listdir(self.folder) for file in files: if file[0:4] == "data": self.dataFiles.append(file) self.render = Render(self, main) self.data = Data(self) def rename(self, name): self.name = name folder = LEVEL_PATH + "/" + name os.rename(self.folder, folder) self.folder = folder self.main.levelSelection.levelGuiHandler.updateText() def openSection(self, number): self.close() self.data = Data(self, number) def save(self): self.data.save() for region in self.data.regions: if region.loaded: region.save() region.save() def close(self): self.data.close() del self.data
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example/declarative/custom_form.py
wilsaj/flask-admin-old
2
106274
import sys from flask import Flask, redirect from flask.ext import admin from flask.ext.admin.datastore.sqlalchemy import SQLAlchemyDatastore from sqlalchemy import create_engine from sqlalchemy.orm import scoped_session, sessionmaker from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Boolean, Column, Integer, Text, String, Float, Time from sqlalchemy.orm import synonym from werkzeug import check_password_hash, generate_password_hash from wtforms import Form, validators from wtforms.fields import BooleanField, TextField, PasswordField Base = declarative_base() class User(Base): __tablename__ = 'user' id = Column(Integer, primary_key=True) username = Column(String(80), unique=True) _password_hash = Column('password', String(80), nullable=False) is_active = Column(Boolean, default=True) def __init__(self, username="", password="", is_active=True): self.username = username self.password = password self.is_active = is_active def check_password(self, password): return check_password_hash(self.pw_hash, password) @property def password(self): return self._password_hash @password.setter def password(self, password): self._password_hash = generate_password_hash(password) password = synonym('_password_hash', descriptor=password) def __repr__(self): return self.username __mapper_args__ = { 'order_by': username } class UserForm(Form): """ Form for creating or editting User object (via the admin). Define any handling of fields here. This form class also has precedence when rendering forms to a webpage, so the model-generated fields will come after it. """ username = TextField(u'User name', [validators.required(), validators.length(max=80)]) password = PasswordField('<PASSWORD>', [validators.optional(), validators.equal_to('confirm_password')]) confirm_password = PasswordField() is_active = BooleanField(default=True) def create_app(database_uri='sqlite://'): app = Flask(__name__) app.config['SECRET_KEY'] = 'not secure' engine = create_engine(database_uri, convert_unicode=True) db_session = scoped_session(sessionmaker( autocommit=False, autoflush=False, bind=engine)) datastore = SQLAlchemyDatastore( (User,), db_session, model_forms={'User': UserForm}) admin_blueprint = admin.create_admin_blueprint( datastore) app.register_blueprint(admin_blueprint, url_prefix='/admin') Base.metadata.create_all(bind=engine) @app.route('/') def go_to_admin(): return redirect('/admin') return app if __name__ == '__main__': app = create_app('sqlite:///simple.db') app.run(debug=True)
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src/ml_analysis.py
UBC-MDS/DMC_Portuguese
0
144125
<gh_stars>0 # author: <NAME> # date: 2020-01-24 '''This script does ML analysis by training multiple models, doing hyperparameter tuning and reporting the results in a csv file. Usage: ml_analysis.py --train_csv=<train_csv> --test_csv=<test_csv> --output_csv=<output_csv> --output_png=<output_png> ml_analysis.py --test_csv=<test_csv> --output_csv=<output_csv> ml_analysis.py --train_csv=<train_csv> --output_csv=<output_csv> ml_analysis.py --train_csv=<train_csv> --test_csv=<test_csv> ml_analysis.py --train_csv=<train_csv> ml_analysis.py --test_csv=<test_csv> ml_analysis.py --output_csv=<output_csv> ml_analysis.py Options: --train_csv=<train_csv> csv path for training [Default: ./data/clean/bank_train.csv]. --test_csv=<test_csv> csv path for testing [Default: ./data/clean/bank_test.csv]. --output_csv=<output_csv> csv path for outputting the result of training and hyperparameter tuning. [Default: ./reports/training_report.csv] --output_png=<output_png> png path for outputting the result of figure containing all trainings [Default: ./reports/training_report.png] ''' import pandas as pd import numpy as np from sklearn.linear_model import LogisticRegression from sklearn.svm import SVC from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import classification_report from sklearn.metrics import confusion_matrix, f1_score from sklearn.model_selection import GridSearchCV from sklearn.model_selection import train_test_split from tqdm import tqdm import lightgbm as lgb from docopt import docopt from itertools import accumulate import os import altair as alt import selenium import matplotlib.pyplot as plt from matplotlib.colors import ListedColormap os.environ["PYTHONWARNINGS"] = "ignore::UserWarning" np.random.RandomState(42) np.random.seed(2020) def check_filepath(save_dir): """ Checks if all subfolders of save_dir exist or not. If not, creates Parameters ---------- save_dir: str containing the path where the files hould be saved Returns: None Usage ----- check_filepath('./unknown_dir') """ for subdir in accumulate(save_dir.split('/'), lambda x, y: os.path.join(x, y)): if not os.path.exists(subdir): os.mkdir(subdir) print(f"Directory {subdir} Created ") def train_lgb(X_train, y_train, X_test, y_test, epochs = 1000, early_stopping = 100): """ Function that handles the training process of Lightgbm. Parameters ---------- X_train: 2D numpy.ndarray containing predictors for training y_train: 1D numpy.ndarray containing response for training X_test: 2D numpy.ndarray containing predictors for testing y_test: 1D numpy.ndarray containing response for testing epochs: positive integer specifying number of weak learners in the model Default: 1000 early_stopping: represents number of epochs that is required to pass without model improvement to stop the training earlier. Default: 100 Returns ------- tuple: (model, parameters, Train F1 score, Test F1 score, Test accuracy, confusion_matrix) Examples -------- >>>train_lgb(X_train, y_train, X_test, y_test) (<lightgbm.basic.Booster at 0x7fd9f06b3470>, {'learning_rate': 0.01, 'lambda_l2': 0.5}, 0.6242424242424243, 0.3972602739726027, 0.9027624309392265) """ # Defining custom f1 score for LightGBM model def lgb_f1_score(y_hat, data): y_true = data.get_label() y_hat = np.round(y_hat) # scikits f1 doesn't like probabilities return 'f1', f1_score(y_true, y_hat), True # Defining validation set X_train, X_valid, y_train, y_valid = train_test_split(X_train, y_train, test_size=0.2) # Creating dataset objects for LightGBM lgb_train = lgb.Dataset(X_train, label=y_train) lgb_valid = lgb.Dataset(X_valid, label=y_valid) # For all possible parameters see https://lightgbm.readthedocs.io/en/latest/Parameters.html params = { "learning_rate" : 0.1, "lambda_l1": 0.5, "max_depth": 64, "num_leaves": 32, "bagging_fraction" : 0.9, "bagging_freq": 3, "bagging_seed": 42, "seed": 42 } # Training model model = lgb.train(params, lgb_train, valid_sets=[lgb_train, lgb_valid], feval = lgb_f1_score, num_boost_round=epochs, early_stopping_rounds=early_stopping, verbose_eval=False) # Getting train F1 score lgb_train_preds = np.round(model.predict(X_train)) train_f1 = f1_score(y_train, lgb_train_preds) # Getting test F1 score lgb_test_preds = np.round(model.predict(X_test)) test_f1 = f1_score(y_test, lgb_test_preds) # Getting test accuracy test_acc = sum(lgb_test_preds == y_test)/len(y_test) # Getting confusion matrix cm = confusion_matrix(y_test, lgb_test_preds) # Returning whatever is important return model, params, train_f1, test_f1, test_acc, [train_f1], [test_f1], cm def hyperparameter_tuning_and_report(classifier, parameters, X, y, X_test=None, y_test=None, scoring='f1'): """ Tunes hyperparameters of given model from the list of parameters. Uses GridSearchCV to find best hyperparameter. Optionally can calculate F1 score and accuracy of test set. Scoring function can be changed that GridSearchCV is using. Default scoring function is F1. Parameters ---------- X: 2D numpy.ndarray containing predictors for training y: 1D numpy.ndarray containing response for training X_test: 2D numpy.ndarray containing predictors for testing. If None, test scores will not be computed. Default: None y_test: 1D numpy.ndarray containing response for testing. If None, test scores will not be computed. Default: None scoring: Scoring function used in GridSearchCV. Default is 'f1'. For all possibilities, please check documentation of GridSearchCV. Returns ------- tuple: (best model, best parameters, Train F1 score, Test F1 score, Test accuracy, Mean Train scores, Mean Test scores, confusion_matrices) Examples -------- >>>hyperparameter_tuning_and_report(LogisticRegression(), {'penalty': ['l1', 'l2'], 'C': [0.1, 1, 10]}, X_train, y_train, X_test, y_test) (LogisticRegression(C=10, class_weight=None, dual=False, fit_intercept=True, intercept_scaling=1, l1_ratio=None, max_iter=100, multi_class='auto', n_jobs=None, penalty='l2', random_state=None, solver='lbfgs', tol=0.0001, verbose=0, warm_start=False), {'C': 10, 'penalty': 'l2'}, 0.43209194041441296, 0.3776223776223776, 0.901657458563536, array([ nan, 0.37217253, nan, 0.44838868, nan, 0.45292401]), array([ nan, 0.34413357, nan, 0.42585911, nan, 0.43209194])) """ # Find the best model try: grid_search = GridSearchCV(classifier, parameters, n_jobs=-1, scoring=scoring, return_train_score=True) grid_search.fit(X, y) except ValueError: pass test_f1 = None test_accuracy = None y_train_pred = grid_search.predict(X) train_report = classification_report(y, y_train_pred, output_dict=True) # Test best model on test set and produce classification report if X_test is not None and y_test is not None: y_test_pred = grid_search.predict(X_test) report = classification_report(y_test, y_test_pred, output_dict=True) test_f1 = report['1.0']['f1-score'], test_accuracy = report['accuracy'], cm = confusion_matrix(y_test, y_test_pred) # Return whatever is important return (grid_search.best_estimator_, grid_search.best_params_, train_report['1.0']['f1-score'], test_f1, test_accuracy, grid_search.cv_results_['mean_train_score'], grid_search.cv_results_['mean_test_score'], cm) def save_confusion_matrix(model_names, cms, save_path): """ Creates and saves confusion matrix figures containing all models mentioned in the input arrays. Parameters ---------- model_names: array containing names of the models tested csm: confusion matrices the models trained save_path: str showing the filepath, where the figure should be saved Returns ------- None """ fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(16, 10)) (ax1, ax2), (ax3, ax4) = axes cols = ListedColormap([[1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1]]) im1 = ax1.matshow(cms[0], cmap=cols) im2 = ax2.matshow(cms[1], cmap=cols) im3 = ax3.matshow(cms[2], cmap=cols) im4 = ax4.matshow(cms[3], cmap=cols) ax = (ax1, ax2, ax3, ax4) for i, model_name in enumerate(model_names): for y in range(cms[i].shape[0]): for x in range(cms[i].shape[1]): ax[i].text(x, y, f'{cms[i][y, x]}', horizontalalignment='center', verticalalignment='center', fontdict = {'size': 16, 'weight': 'bold'} ) ax[i].set_xticklabels(['', 'Predicted 0', 'Predicted 1']) ax[i].set_yticklabels(['', 'Actual 0', 'Actual 1']) ax[i].title.set_text(f'Confusion matrix of {model_name}') # for y in range(a.shape[0]): # for x in range(a.shape[1]): # ax2.text(x, y, '%.4f' % a[y, x], # horizontalalignment='center', # verticalalignment='center', # ) # # for y in range(a.shape[0]): # for x in range(a.shape[1]): # ax3.text(x, y, '%.4f' % a[y, x], # horizontalalignment='center', # verticalalignment='center', # ) # for y in range(a.shape[0]): # for x in range(a.shape[1]): # ax4.text(x, y, '%.4f' % a[y, x], # horizontalalignment='center', # verticalalignment='center', # ) # model_name = 'aa' # # ax1.title.set_text(f'confusion matrix of {model_name}') # ax2.title.set_text(f'confusion matrix of {model_name}') # ax3.title.set_text(f'confusion matrix of {model_name}') # ax4.title.set_text(f'confusion matrix of {model_name}') check_filepath(save_path.rsplit('/', 1)[0]) fig.savefig(save_path) def generate_csv_and_figure_reports(arr, csv_filepath, figure_filepath): """ Generates csv report from the results obtained from hyperparameter tuning. Given the array of results of hyperparameter_tuning_and_report for different models, generates csv file and saves in the given path. Parameters ---------- arr: 1D array containing a tuple returned from hyperparameter_tuning_and_report or train_lgb() function. csv_filepath: str containing path where the report should be saved. figure_filepath: str containing path where the figure report should be saved. Should have extension .png Returns ------- None Notes: Please be sure that arr is array of tuples. """ names = [] best_params = [] train_f1s = [] test_f1s = [] test_accuracies = [] train_score_results = [] test_score_results = [] score_res_names = [] cms = [] # Gathering names of the models and other information for model in tqdm(arr): names.append(model[0].__class__.__name__) best_params.append(model[1]) train_f1s.append(model[2]) test_f1s.append(model[3]) test_accuracies.append(model[4]) cms.append(model[7].astype(int)) if model[0].__class__.__name__ != 'Booster': train_score_results.extend(model[5]) test_score_results.extend(model[6]) score_res_names.extend([model[0].__class__.__name__]*len(model[5])) # Creating dataframe from the results csv_report = pd.DataFrame({'Model name': names, 'Best parameters': best_params, 'Train F1': train_f1s, 'Test F1': test_f1s, 'Test accuracies': test_accuracies, 'Confusion matrix': cms}) # Creating dataframe from the results for figure generation figure_report = pd.DataFrame({'models': score_res_names, 'train_scores': train_score_results, 'test_scores': test_score_results}) # Check for existance of a filepath check_filepath(csv_filepath.rsplit('/', 1)[0]) check_filepath(figure_filepath.rsplit('/', 1)[0]) # Saving the report csv_report.to_csv(csv_filepath) # Saving figure alt.Chart(figure_report).mark_circle(size=100).encode( x = alt.X('test_scores', axis = alt.Axis(title='Cross-Val Test F1 score'), scale = alt.Scale(domain = (0., 1.))), y = alt.Y('train_scores', axis = alt.Axis(title='Cross-Val Train F1 score'), scale = alt.Scale(domain=(0., 1.))), color = 'models').properties( title = 'Train and Test scores of all methods tested').\ configure_axis( labelFontSize=15, titleFontSize=15 ).\ configure_legend(labelFontSize = 15, titleFontSize=15).\ configure_title(fontSize=20).\ save(figure_filepath) # Saving confusion matrix save_confusion_matrix(names, cms, './reports/confusion_matrix.png') def read_data_and_split(train_csv_path = '../data/clean/bank_train.csv', test_csv_path = '../data/clean/bank_test.csv'): """ Reads the data from the given paths and returns predictors and response variables separately for train and test sets Parameters ---------- train_csv_path: str containing the path of train csv. Default: '../data/clean/bank_train.csv' test_csv_path: str containing the path of test csv. Default: '../data/clean/bank_test.csv' Returns ------- tuple: (X_train, y_train, X_test, y_test) """ try: train_ds = pd.read_csv(train_csv_path) test_ds = pd.read_csv(test_csv_path) except (FileNotFoundError) as e: print('Please check train and test filepaths') raise(e) try: X_train, y_train = train_ds.drop('y_yes', axis=1), train_ds['y_yes'] X_test, y_test = test_ds.drop('y_yes', axis=1), test_ds['y_yes'] except KeyError: print('Corrupted csv files. Please check the columns') raise KeyError return X_train, y_train, X_test, y_test def main(train_csv, test_csv, output_csv, output_png): try: X_train, y_train, X_test, y_test = read_data_and_split(train_csv, test_csv) except: return # Define models that should be passed to hyperparameter tuning models = [LogisticRegression(class_weight = 'balanced', random_state=42), SVC(class_weight = 'balanced', random_state=42), RandomForestClassifier(class_weight = 'balanced', random_state=42) ] # Define parameters that should be tested for each of the models. # Note: Be sure that indices of models and its parameters correspond. # Note2: Each model should have some valid dictionalry associated with it. parameters = [ [{'solver': ['saga', 'liblinear'], 'penalty': ['l1', 'l2'], 'C': [0.01, 0.1, 1, 10]}, {'solver': ['lbfgs', 'newton-cg', 'sag'], 'penalty': ['l2'], 'C': [0.01, 0.1, 1, 10]}], [{'C': [0.01, 0.1, 1, 10], 'kernel': ['rbf']}, {'C': [0.01, 0.1, 1, 10], 'kernel': ['poly'], 'degree': [2, 3, 4]}], {'n_estimators': [25, 50, 75], 'max_depth': [None, 16, 32], 'criterion': ['gini', 'entropy']} ] if len(models) != len(parameters): print('Check models and corresponding parameters. Each model should have a dictionary of parameters to test.') return # Performing hyperparameter tuning and getting reports of each of the models # defined above all_results = [] for model_id, model in enumerate(tqdm(models)): model_params = parameters[model_id] res = hyperparameter_tuning_and_report(model, model_params, X_train, y_train, X_test, y_test) all_results.append(res) # Training LightGBM model and appending results to other results lgb_model_res = train_lgb(X_train, y_train, X_test, y_test) all_results.append(lgb_model_res) # Generating and saving model results generate_csv_and_figure_reports(all_results, output_csv, output_png) if __name__ == '__main__': opt = docopt(__doc__) main(opt["--train_csv"], opt["--test_csv"], opt["--output_csv"], opt["--output_png"])
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