Reset23/the-stack-v2-processed · Datasets at Hugging Face

72e86ba0148bbe1b9d9f1b565316ff71b35a5b3d

0e1e643e864bcb96cf06f14f4cb559b034e114d0

/Exps_7_v3/doc3d/W_w_Mgt_to_Cx_Cy_focus_Z_ok/Sob_k15_s001_EroM/pyr_Tcrop255_pad60_jit15/pyr_2s/L3/step10_a.py

f0aef80d3b5947a605591d698c2bed71ebb8c14f

[]

no_license

KongBOy/kong_model2

33a94a9d2be5b0f28f9d479b3744e1d0e0ebd307

1af20b168ffccf0d5293a393a40a9fa9519410b2

refs/heads/master

2022-10-14T03:09:22.543998

2022-10-06T11:33:42

242,080,692

3

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10,323

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############################################################################################################################################################################################################# ############################################################################################################################################################################################################# ### 把 kong_model2 加入 sys.path import os code_exe_path = os.path.realpath(__file__) ### 目前執行 step10_b.py 的 path code_exe_path_element = code_exe_path.split("\\") ### 把 path 切分等等要找出 kong_model 在第幾層 code_dir = "\\".join(code_exe_path_element[:-1]) kong_layer = code_exe_path_element.index("kong_model2") ### 找出 kong_model2 在第幾層 kong_model2_dir = "\\".join(code_exe_path_element[:kong_layer + 1]) ### 定位出 kong_model2 的 dir import sys ### 把 kong_model2 加入 sys.path sys.path.append(kong_model2_dir) sys.path.append(code_dir) # print(__file__.split("\\")[-1]) # print(" code_exe_path:", code_exe_path) # print(" code_exe_path_element:", code_exe_path_element) # print(" code_dir:", code_dir) # print(" kong_layer:", kong_layer) # print(" kong_model2_dir:", kong_model2_dir) ############################################################################################################################################################################################################# kong_to_py_layer = len(code_exe_path_element) - 1 - kong_layer ### 中間 -1 是為了長度轉index # print(" kong_to_py_layer:", kong_to_py_layer) if (kong_to_py_layer == 0): template_dir = "" elif(kong_to_py_layer == 2): template_dir = code_exe_path_element[kong_layer + 1][0:] ### [7:] 是為了去掉 step1x_，後來覺得好像改有意義的名字不去掉也行所以改 0 elif(kong_to_py_layer == 3): template_dir = code_exe_path_element[kong_layer + 1][0:] + "/" + code_exe_path_element[kong_layer + 2][0:] ### [5:] 是為了去掉 mask_ ，前面的 mask_ 是為了python 的 module 不能數字開頭，隨便加的這樣子，後來覺得自動排的順序也可以接受，所以改0 elif(kong_to_py_layer > 3): template_dir = code_exe_path_element[kong_layer + 1][0:] + "/" + code_exe_path_element[kong_layer + 2][0:] + "/" + "/".join(code_exe_path_element[kong_layer + 3: -1]) # print(" template_dir:", template_dir) ### 舉例： template_dir: 7_mask_unet/5_os_book_and_paper_have_dtd_hdr_mix_bg_tv_s04_mae ############################################################################################################################################################################################################# exp_dir = template_dir ############################################################################################################################################################################################################# from step06_a_datas_obj import * from step09_2side_L3 import * from step10_a2_loss_info_obj import * from step10_b2_exp_builder import Exp_builder rm_paths = [path for path in sys.path if code_dir in path] for rm_path in rm_paths: sys.path.remove(rm_path) rm_moduless = [module for module in sys.modules if "step09" in module] for rm_module in rm_moduless: del sys.modules[rm_module] ############################################################################################################################################################################################################# ''' exp_dir 是決定 result_dir 的 "上一層"資料夾名字喔！ exp_dir要巢狀也沒問題～比如：exp_dir = "6_mask_unet/自己命的名字"，那 result_dir 就都在： 6_mask_unet/自己命的名字/result_a 6_mask_unet/自己命的名字/result_b 6_mask_unet/自己命的名字/... ''' use_db_obj = type8_blender_kong_doc3d_in_W_and_I_gt_F use_loss_obj = [G_sobel_k15_erose_M_loss_info_builder.set_loss_target("UNet_Cx").copy(), G_sobel_k15_erose_M_loss_info_builder.set_loss_target("UNet_Cy").copy()] ### z, y, x 順序是看 step07_b_0b_Multi_UNet 來對應的喔 ############################################################# ### 為了resul_analyze畫空白的圖，建一個empty的 Exp_builder empty = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_1__2side_1, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_1__2side_1.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="為了resul_analyze畫空白的圖，建一個empty的 Exp_builder") ############################################################# ch032_1side_1__2side_1 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_1__2side_1, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_1__2side_1.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_2__2side_1 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_2__2side_1, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_2__2side_1.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_2__2side_2 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_2__2side_2, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_2__2side_2.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_3__2side_1 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_3__2side_1, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_3__2side_1.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_3__2side_2 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_3__2side_2, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_3__2side_2.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_3__2side_3 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_3__2side_3, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_3__2side_3.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_4__2side_1 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_4__2side_1, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_4__2side_1.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_4__2side_2 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_4__2side_2, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_4__2side_2.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_4__2side_3 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_4__2side_3, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_4__2side_3.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ch032_1side_4__2side_4 = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_1side_4__2side_4, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_1side_4__2side_4.kong_model.model_describe) .set_train_args(epochs= 1) .set_train_iter_args(it_see_fq=900, it_save_fq=900 * 2, it_down_step="half", it_down_fq=900) .set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ############################################################# if(__name__ == "__main__"): print("build exps cost time:", time.time() - start_time) if len(sys.argv) < 2: ############################################################################################################ ### 直接按 F5 或打 python step10_b1_exp_obj_load_and_train_and_test.py，後面沒有接東西喔！才不會跑到下面給 step10_b_subprocss.py 用的程式碼~~~ ch032_1side_1__2side_1.build().run() # print('no argument') sys.exit() ### 以下是給 step10_b_subprocess.py 用的，相當於cmd打 python step10_b1_exp_obj_load_and_train_and_test.py 某個exp.build().run() eval(sys.argv[1])

[ "[email protected]" ]

[email protected]

278703b3e7899ad71128c9b1bcfa67f9a6245b9f

306de77289d118f819c9ded4807a91268b7cc58b

/models/resnet_prm/resnet_PRM15.py

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[]

no_license

ma-xu/NANet

67252d8e3108f16049b9ebdb5a8c4a473b117874

5c894ebf05fed54a437e1b9b2d5dfc7a947f0775

refs/heads/master

2022-03-28T01:59:11.409632

2020-01-23T04:41:28

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import torch.nn as nn import torch.utils.model_zoo as model_zoo from torch.nn.parameter import Parameter import torch import torch.nn.functional as F from torch.nn import init from torch.autograd import Variable from collections import OrderedDict import math import time """ Actually the SGE + maxvalue """ __all__ = ['prm15_resnet18','prm15_resnet34','prm15_resnet50','prm15_resnet101','prm15_resnet152'] """ group is the number of selected points. """ class PRMLayer(nn.Module): def __init__(self,groups=64,mode='dotproduct'): super(PRMLayer, self).__init__() self.mode = mode self.groups = groups self.max_pool = nn.AdaptiveMaxPool2d(1,return_indices=True) self.weight = Parameter(torch.zeros(1,self.groups,1,1)) self.bias = Parameter(torch.ones(1,self.groups,1,1)) self.sig = nn.Sigmoid() self.gap = nn.AdaptiveAvgPool2d(1) def forward(self, x): b,c,h,w = x.size() # Similarity function query_value, _ = self.get_key_position(x, self.groups) # shape [b*num,2,1,1] query_value = query_value.view(b*self.groups,-1,1,1) x_value = x.view(b*self.groups,-1,h,w) similarity = self.get_similarity(x_value, query_value, mode=self.mode) similarity = similarity.view(b,self.groups,h,w) context = similarity.view(b, self.groups, -1) context = context - context.mean(dim=2, keepdim=True) std = context.std(dim=2, keepdim=True) + 1e-5 context = (context/std).view(b,self.groups,h,w) # affine function context = context * self.weight + self.bias context = context.view(b*self.groups,1,h,w)\ .expand(b*self.groups, c//self.groups, h, w).reshape(b,c,h,w) value = x*self.sig(context) return value def get_key_position(self, key,groups): b,c,h,w = key.size() value = key.view(b*groups,c//groups,h,w) sumvalue = value.sum(dim=1,keepdim=True) maxvalue,maxposition = self.max_pool(sumvalue) t_position = torch.cat((maxposition//w,maxposition % w),dim=1) t_value = value[torch.arange(b*groups),:,t_position[:,0,0,0],t_position[:,1,0,0]] t_value = t_value.view(b, c, 1, 1) t_mean = self.gap(key) return t_value+t_mean, t_position def get_similarity(self,query, key_value, mode='dotproduct'): if mode == 'dotproduct': similarity = torch.matmul(key_value.permute(0, 2, 1), query) elif mode == 'l1norm': similarity = -(abs(query - key_value)).sum(dim=1) elif mode == 'gaussian': # Gaussian Similarity (No recommanded, too sensitive to noise) similarity = torch.exp(torch.matmul(key_value.permute(0, 2, 1), query)) similarity[similarity == float("Inf")] = 0 similarity[similarity <= 1e-9] = 1e-9 else: similarity = torch.matmul(key_value.permute(0, 2, 1), query) return similarity def conv3x3(in_planes, out_planes, stride=1): """3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False) def conv1x1(in_planes, out_planes, stride=1): """1x1 convolution""" return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False) class BasicBlock(nn.Module): expansion = 1 def __init__(self, inplanes, planes, stride=1, downsample=None): super(BasicBlock, self).__init__() self.conv1 = conv3x3(inplanes, planes, stride) self.bn1 = nn.BatchNorm2d(planes) self.relu = nn.ReLU(inplace=True) self.conv2 = conv3x3(planes, planes) self.bn2 = nn.BatchNorm2d(planes) self.downsample = downsample self.stride = stride self.prm = PRMLayer() def forward(self, x): identity = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) out = self.prm(out) if self.downsample is not None: identity = self.downsample(x) out += identity out = self.relu(out) return out class Bottleneck(nn.Module): expansion = 4 def __init__(self, inplanes, planes, stride=1, downsample=None): super(Bottleneck, self).__init__() self.conv1 = conv1x1(inplanes, planes) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = conv3x3(planes, planes, stride) self.bn2 = nn.BatchNorm2d(planes) self.conv3 = conv1x1(planes, planes * self.expansion) self.bn3 = nn.BatchNorm2d(planes * self.expansion) self.prm = PRMLayer() self.relu = nn.ReLU(inplace=True) self.downsample = downsample self.stride = stride def forward(self, x): identity = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) out = self.relu(out) out = self.conv3(out) out = self.bn3(out) out = self.prm(out) if self.downsample is not None: identity = self.downsample(x) out += identity out = self.relu(out) return out class ResNet(nn.Module): def __init__(self, block, layers, num_classes=1000, zero_init_residual=False): super(ResNet, self).__init__() self.inplanes = 64 self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False) self.bn1 = nn.BatchNorm2d(64) self.relu = nn.ReLU(inplace=True) self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) self.layer1 = self._make_layer(block, 64, layers[0]) self.layer2 = self._make_layer(block, 128, layers[1], stride=2) self.layer3 = self._make_layer(block, 256, layers[2], stride=2) self.layer4 = self._make_layer(block, 512, layers[3], stride=2) self.avgpool = nn.AdaptiveAvgPool2d((1, 1)) self.fc = nn.Linear(512 * block.expansion, num_classes) for m in self.modules(): if isinstance(m, nn.Conv2d): nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu') elif isinstance(m, nn.BatchNorm2d): nn.init.constant_(m.weight, 1) nn.init.constant_(m.bias, 0) # Zero-initialize the last BN in each residual branch, # so that the residual branch starts with zeros, and each residual block behaves like an identity. # This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677 if zero_init_residual: for m in self.modules(): if isinstance(m, Bottleneck): nn.init.constant_(m.bn3.weight, 0) elif isinstance(m, BasicBlock): nn.init.constant_(m.bn2.weight, 0) def _make_layer(self, block, planes, blocks, stride=1): downsample = None if stride != 1 or self.inplanes != planes * block.expansion: downsample = nn.Sequential( conv1x1(self.inplanes, planes * block.expansion, stride), nn.BatchNorm2d(planes * block.expansion), ) layers = [] layers.append(block(self.inplanes, planes, stride, downsample)) self.inplanes = planes * block.expansion for _ in range(1, blocks): layers.append(block(self.inplanes, planes)) return nn.Sequential(*layers) def forward(self, x): x = self.conv1(x) x = self.bn1(x) x = self.relu(x) x = self.maxpool(x) x = self.layer1(x) x = self.layer2(x) x = self.layer3(x) x = self.layer4(x) x = self.avgpool(x) x = x.view(x.size(0), -1) x = self.fc(x) return x def prm15_resnet18(pretrained=False, **kwargs): """Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNet(BasicBlock, [2, 2, 2, 2], **kwargs) return model def prm15_resnet34(pretrained=False, **kwargs): """Constructs a ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNet(BasicBlock, [3, 4, 6, 3], **kwargs) return model def prm15_resnet50(pretrained=False, **kwargs): """Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNet(Bottleneck, [3, 4, 6, 3], **kwargs) return model def prm15_resnet101(pretrained=False, **kwargs): """Constructs a ResNet-101 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNet(Bottleneck, [3, 4, 23, 3], **kwargs) return model def prm15_resnet152(pretrained=False, **kwargs): """Constructs a ResNet-152 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNet(Bottleneck, [3, 8, 36, 3], **kwargs) return model def demo(): st = time.perf_counter() for i in range(1): net = prm15_resnet50(num_classes=1000) y = net(torch.randn(2, 3, 224,224)) print(i) print("CPU time: {}".format(time.perf_counter() - st)) def demo2(): st = time.perf_counter() for i in range(1): net = prm15_resnet50(num_classes=1000).cuda() y = net(torch.randn(2, 3, 224,224).cuda()) print(i) # print("Allocated: {}".format(torch.cuda.memory_allocated())) print("GPU time: {}".format(time.perf_counter() - st)) # demo() # demo2()

[ "[email protected]" ]

[email protected]

be04c205e071f2ef645ebbaa5a3f066e0a5d660e

0d834835098f86c153367956cb2513377c91074c

/basic/html_table/table.py

d9fa2816db8db4c537b7c2ddd956d17b2a82d654

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no_license

klandon94/flask_fundamentals

a63c2c6b5567627203299a685db5f73a8d749051

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refs/heads/master

2020-03-21T06:14:53.013649

2018-06-21T18:20:36

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from flask import Flask,render_template as render app = Flask(__name__) @app.route('/') def table(): users = ( {'first_name': 'LeBron','last_name':'James'}, {'first_name': 'Kobe','last_name':'Bryant'}, {'first_name': 'Michael','last_name':'Jordan'}, {'first_name': 'Tim','last_name':'Duncan'} ) return render('table.html', data=users) if __name__ == "__main__": app.run(debug=True)

[ "[email protected]" ]

[email protected]

dcec49309b9d2263807ea94a99e6251ff33b8e55

7b55cfc4ffa7678e4c7b8f2312831ebbd549e54f

/proj1/tests/other-tests/oskis-angels_tests/regexperts_tests/correct/expr_mod.py

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[]

no_license

czchen1/cs164-projects

0d330efef85421e611a436b165428ba0ddfb3512

a04cafbcaafd32e518227dacf89a6d7837bf9f57

refs/heads/master

2020-03-27T04:03:31.727524

2018-08-23T21:43:46

145,909,148

0

null

UTF-8

Python

false

46

py

print 2 % 2 print 1 % 2 % 4 print ((1 % (2)))

[ "[email protected]" ]

[email protected]

95bec86aa8cf1ceab3c433e3060644fb568c10d4

e25b2bed99e7bec09a5ecdc2baee33c90b1d5fcf

/day1/chapter3/string-method.py

27c2ccb534327e0c08b62b890b74bd2ccdd2853b

[]

no_license

alabiansolution/python-wknd1902

6d579be040a130c54850396490961493e7eb3663

cb492085a522681a447bcb3668a30c851dec1247

refs/heads/master

2020-06-08T11:46:33.514204

2019-06-22T12:02:11

193,223,190

0

null

UTF-8

Python

false

74

py

name = ' Benedict ' remove_space = name.strip() print(len(remove_space))

[ "[email protected]" ]

[email protected]

616ac500554e2c805a0e873d7f50ac2c6131a9dd

1ea0e2b4f064ba0de45a73c527ee89a36771e8fc

/src/sentry/web/frontend/project_plugins.py

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[ "BSD-2-Clause" ]

permissive

atlassian/sentry

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refs/heads/master

2023-08-27T15:45:47.699173

2017-09-18T22:14:55

103,999,066

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BSD-3-Clause

2023-04-01T07:49:37

2017-09-18T22:38:18

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Python

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from __future__ import absolute_import from django.contrib import messages from django.utils.translation import ugettext_lazy as _ from sentry.plugins import plugins from sentry.web.frontend.base import ProjectView class ProjectPluginsView(ProjectView): required_scope = 'project:write' def handle(self, request, organization, team, project): if request.POST: enabled = set(request.POST.getlist('plugin')) for plugin in plugins.configurable_for_project(project, version=None): if plugin.slug in enabled: plugin.enable(project) else: plugin.disable(project) messages.add_message( request, messages.SUCCESS, _('Your settings were saved successfully.') ) return self.redirect(request.path) context = { 'page': 'plugins', } return self.respond('sentry/projects/plugins/list.html', context)

[ "[email protected]" ]

[email protected]

b27aa8ef9e31b0a9620b8601e53177fa99afc77b

0354d8e29fcbb65a06525bcac1f55fd08288b6e0

/clients/python-flask/generated/swagger_server/models/extension_class_impllinks.py

43b79fcdb2ef700ae5858714220dd95fce07aa70

[ "MIT" ]

permissive

zhiwei55/swaggy-jenkins

cdc52956a40e947067415cec8d2da1425b3d7670

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refs/heads/master

2020-03-06T20:38:53.012467

2018-02-19T01:53:33

2018-02-19T01:54:30

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# coding: utf-8 from __future__ import absolute_import from swagger_server.models.link import Link from .base_model_ import Model from datetime import date, datetime from typing import List, Dict from ..util import deserialize_model class ExtensionClassImpllinks(Model): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ def __init__(self, _self: Link=None, _class: str=None): """ ExtensionClassImpllinks - a model defined in Swagger :param _self: The _self of this ExtensionClassImpllinks. :type _self: Link :param _class: The _class of this ExtensionClassImpllinks. :type _class: str """ self.swagger_types = { '_self': Link, '_class': str } self.attribute_map = { '_self': 'self', '_class': '_class' } self.__self = _self self.__class = _class @classmethod def from_dict(cls, dikt) -> 'ExtensionClassImpllinks': """ Returns the dict as a model :param dikt: A dict. :type: dict :return: The ExtensionClassImpllinks of this ExtensionClassImpllinks. :rtype: ExtensionClassImpllinks """ return deserialize_model(dikt, cls) @property def _self(self) -> Link: """ Gets the _self of this ExtensionClassImpllinks. :return: The _self of this ExtensionClassImpllinks. :rtype: Link """ return self.__self @_self.setter def _self(self, _self: Link): """ Sets the _self of this ExtensionClassImpllinks. :param _self: The _self of this ExtensionClassImpllinks. :type _self: Link """ self.__self = _self @property def _class(self) -> str: """ Gets the _class of this ExtensionClassImpllinks. :return: The _class of this ExtensionClassImpllinks. :rtype: str """ return self.__class @_class.setter def _class(self, _class: str): """ Sets the _class of this ExtensionClassImpllinks. :param _class: The _class of this ExtensionClassImpllinks. :type _class: str """ self.__class = _class

[ "[email protected]" ]

[email protected]

d445f3dfb6f9d07858e859c69bbd06685a4c2ee4

13faa0d553ed6c6a57791db3dfdb2a0580a1695b

/CodeChef/Practice/Beginner/LONGSEQ.py

54638200608b86934ba675bf7674e2b4f9055ec4

[]

no_license

kautsiitd/Competitive_Programming

ba968a4764ba7b5f2531d03fb9c53dc1621c2d44

a0d8ae16646d73c346d9ce334e5b5b09bff67f67

refs/heads/master

2021-01-17T13:29:52.407558

2017-10-01T09:58:23

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0

null

2017-05-20T17:27:18

2016-05-23T15:56:55

HTML

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py

for _ in range(input()): a = raw_input() if a.count('0') == 1 or a.count('1') == 1: print "Yes" else: print "No"

[ "[email protected]" ]

[email protected]

4c36bb6674d30229ecd48b9147a7917e4d314c33

b7cb542ba2a0b00472aedda3a47a42f34ed01feb

/blogApp/admin.py

d6cd851510d7f6c427df2426cb543fe1f321f30b

[]

no_license

sajibuzzaman/Django_Rest_Framework

1c2f5bc00ef5d4b380cc94d60c66a77bdf69a955

c83cce921ad41f82c7ac960000ae1c0e2e2c5604

refs/heads/master

2023-04-04T14:30:28.609151

2021-04-20T11:58:10

359,554,892

0

null

UTF-8

Python

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702

py

from django.contrib import admin from .models import Blog, CommentBlog class CommentBlogInline(admin.TabularInline): model = CommentBlog extra = 0 readonly_fields = ['blog','user', 'comment', 'ip'] class BlogAdmin(admin.ModelAdmin): list_display = ['title', 'date_posted', 'image_tag'] list_filter = ['date_posted'] inlines = [CommentBlogInline] list_per_page = 10 class CommentBlogAdmin(admin.ModelAdmin): readonly_fields = ['blog','user', 'comment', 'ip'] list_display = ['blog', 'status', 'created_at', 'updated_at', 'user'] list_filter = ['status', 'created_at'] list_per_page = 10 # Register your models here. admin.site.register(Blog, BlogAdmin)

[ "[email protected]" ]

[email protected]

a6d97883d813063e9e64c30383d463c3795377ed

d66993b0383ee7a97c9d5fe761269a3cb8e67e22

/Ejercicios/EjercicioAños.py

437838d33b904ab1f6d4be9893aad03aede04c48

[]

no_license

rramosaveros/CursoPythonCisco

09828e3d8190490c0dc30861ae241f5222e108d6

1508e67873adfcf31b8c78d3f5cb2a0572dfeb1c

refs/heads/master

2023-06-27T12:07:52.652780

2021-08-01T14:19:19

391,647,026

0

null

UTF-8

Python

false

309

py

año = int(input("Introduzca un año:")) # if año <= 1580: print("No dentro del período del calendario gregoriano") elif (año%4) != 0: print("Año común") elif (año % 100) != 0: print("Año bisiesto") elif (año % 400) != 0: print("Año común") else: print("Año bisiesto") #

[ "[email protected]" ]

[email protected]

fe6407849dc00e3827ad92b25a8bd7a7c6f4a31c

314a687b50622e0377f9829b824b046a18f2421d

/passbook/core/admin.py

6e91b20800ee5bc367aef45818f109c11b0acf21

[ "MIT" ]

permissive

fossabot/passbook

a4d13b31bb831adb6392d434cfde3080b7fc797e

cba17f6659404445ac3025f11657d89368cc8b4f

refs/heads/master

2021-02-14T23:35:52.249963

2020-03-04T08:22:04

244,845,185

0

MIT

2020-03-04T08:21:59

null

UTF-8

Python

false

120

py

"""passbook core model admin""" from passbook.lib.admin import admin_autoregister admin_autoregister("passbook_core")

[ "[email protected]" ]

[email protected]

9ae571f70426fb357555e597a1796b30b120411c

9df2fb0bc59ab44f026b0a2f5ef50c72b2fb2ceb

/sdk/compute/azure-mgmt-compute/azure/mgmt/compute/v2019_04_01/aio/operations/_operations.py

523f0e7792ab8919d6a9be76ddbebb382332f883

[ "MIT", "LGPL-2.1-or-later", "LicenseRef-scancode-generic-cla" ]

permissive

openapi-env-test/azure-sdk-for-python

b334a2b65eeabcf9b7673879a621abb9be43b0f6

f61090e96094cfd4f43650be1a53425736bd8985

refs/heads/main

2023-08-30T14:22:14.300080

2023-06-08T02:53:04

222,384,897

1

0

MIT

2023-09-08T08:38:48

2019-11-18T07:09:24

Python

UTF-8

Python

false

6,073

py

# pylint: disable=too-many-lines # coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar import urllib.parse from azure.core.async_paging import AsyncItemPaged, AsyncList from azure.core.exceptions import ( ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, ResourceNotModifiedError, map_error, ) from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse from azure.core.rest import HttpRequest from azure.core.tracing.decorator import distributed_trace from azure.core.utils import case_insensitive_dict from azure.mgmt.core.exceptions import ARMErrorFormat from ... import models as _models from ..._vendor import _convert_request from ...operations._operations import build_resource_skus_list_request T = TypeVar("T") ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] class ResourceSkusOperations: """ .. warning:: **DO NOT** instantiate this class directly. Instead, you should access the following operations through :class:`~azure.mgmt.compute.v2019_04_01.aio.ComputeManagementClient`'s :attr:`resource_skus` attribute. """ models = _models def __init__(self, *args, **kwargs) -> None: input_args = list(args) self._client = input_args.pop(0) if input_args else kwargs.pop("client") self._config = input_args.pop(0) if input_args else kwargs.pop("config") self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer") self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer") @distributed_trace def list(self, *, filter: Optional[str] = None, **kwargs: Any) -> AsyncIterable["_models.ResourceSku"]: """Gets the list of Microsoft.Compute SKUs available for your Subscription. :keyword filter: The filter to apply on the operation. Only **location** filter is supported currently. Default value is None. :paramtype filter: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either ResourceSku or the result of cls(response) :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.compute.v2019_04_01.models.ResourceSku] :raises ~azure.core.exceptions.HttpResponseError: """ _headers = kwargs.pop("headers", {}) or {} _params = case_insensitive_dict(kwargs.pop("params", {}) or {}) api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2019-04-01")) cls: ClsType[_models.ResourceSkusResult] = kwargs.pop("cls", None) error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 304: ResourceNotModifiedError, } error_map.update(kwargs.pop("error_map", {}) or {}) def prepare_request(next_link=None): if not next_link: request = build_resource_skus_list_request( subscription_id=self._config.subscription_id, filter=filter, api_version=api_version, template_url=self.list.metadata["url"], headers=_headers, params=_params, ) request = _convert_request(request) request.url = self._client.format_url(request.url) else: # make call to next link with the client's api-version _parsed_next_link = urllib.parse.urlparse(next_link) _next_request_params = case_insensitive_dict( { key: [urllib.parse.quote(v) for v in value] for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() } ) _next_request_params["api-version"] = self._config.api_version request = HttpRequest( "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params ) request = _convert_request(request) request.url = self._client.format_url(request.url) request.method = "GET" return request async def extract_data(pipeline_response): deserialized = self._deserialize("ResourceSkusResult", pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) # type: ignore return deserialized.next_link or None, AsyncList(list_of_elem) async def get_next(next_link=None): request = prepare_request(next_link) _stream = False pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access request, stream=_stream, **kwargs ) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return AsyncItemPaged(get_next, extract_data) list.metadata = {"url": "/subscriptions/{subscriptionId}/providers/Microsoft.Compute/skus"}

[ "[email protected]" ]

[email protected]

f44e8f2bbb168252f1c63bf3eaa369e9b9bca476

ded1edb8ed387f9d1989334b8dd3ee397b36bf8b

/djangorest/api/views.py

317904089ccab3c785a6d5359f3be0fc1b499057

[]

no_license

elevenmunki/django_api

c790dfe6c8ab1d8da9454a9fc17d3bb339a7d39c

3a16214f18d015d4ce21f42a473f9d69274aab80

refs/heads/master

2021-07-12T02:51:30.513141

2017-09-30T01:16:21

null

0

null

UTF-8

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false

636

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.shortcuts import render from rest_framework import generics from .serializers import BucketlistSerializer from .models import Bucketlist #ListCreateAPIView is a generic view which provides GET (list all) and POST method handler class CreateView(generics.ListCreateAPIView): """This class defines the create behavior of our rest api.""" queryset = Bucketlist.objects.all() serializer_class = BucketlistSerializer def perform_create(self, serializer): """Save the post data when creating a new bucketlist.""" serializer.save()

[ "[email protected]" ]

[email protected]

d07a9c45cb065bb11701d18947cbb54a96100d40

e3742e43ea3ca59016406d3c4308c21fad07d3d5

/Basics/Shanbey/P30_章节回顾_2018世界杯各队进球数.py

3fdd8891e6dc9a305211d850685b3a222863e75c

[]

no_license

yangyang0126/PythonLearning

e499c59ce04e884c3614c6a8c6a5b219234dce6c

4a8ec4386ecb7609abb56c533131e4c283b628ec

refs/heads/master

2020-08-10T18:15:18.720145

2020-05-24T02:29:19

214,393,778

3

2

null

UTF-8

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''' 下方变量 goal_record 是2018年俄罗斯世界杯64场球赛的比分（不包含淘汰赛点球大战）创建字典 wc_2018_goal，记录32支球队的各自进球数。 ''' goal_record = """Russia 5–0 Saudi Arabia; Egypt 0–1 Uruguay; Russia 3–1 Egypt; Uruguay 1–0 Saudi Arabia; Uruguay 3–0 Russia; Saudi Arabia 2–1 Egypt; Morocco 0–1 Iran; Portugal 3–3 Spain; Portugal 1–0 Morocco; Iran 0–1 Spain; Iran 1–1 Portugal; Spain 2–2 Morocco; France 2–1 Australia; Peru 0–1 Denmark; Denmark 1–1 Australia; France 1–0 Peru; Denmark 0–0 France; Australia 0–2 Peru; Argentina 1–1 Iceland; Croatia 2–0 Nigeria; Argentina 0–3 Croatia; Nigeria 2–0 Iceland; Nigeria 1–2 Argentina; Iceland 1–2 Croatia; Costa Rica 0–1 Serbia; Brazil 1–1 Switzerland; Brazil 2–0 Costa Rica; Serbia 1–2 Switzerland; Serbia 0–2 Brazil; Switzerland 2–2 Costa Rica; Germany 0–1 Mexico; Sweden 1–0 South Korea; South Korea 1–2 Mexico; Germany 2–1 Sweden; South Korea 2–0 Germany; Mexico 0–3 Sweden; Belgium 3–0 Panama; Tunisia 1–2 England; Belgium 5–2 Tunisia; England 6–1 Panama; England 0–1 Belgium; Panama 1–2 Tunisia; Colombia 1–2 Japan; Poland 1–2 Senegal; Japan 2–2 Senegal; Poland 0–3 Colombia; Japan 0–1 Poland; Senegal 0–1 Colombia; France 4–3 Argentina; Uruguay 2–1 Portugal; Spain 1–1 Russia; Croatia 1–1 Denmark; Brazil 2–0 Mexico; Belgium 3–2 Japan; Sweden 1–0 Switzerland; Colombia 1–1 England; Uruguay 0–2 France; Brazil 1–2 Belgium; Sweden 0–2 England; Russia 2–2 Croatia; France 1–0 Belgium; Croatia 2–1 England; Belgium 2–0 England; France 4–2 Croatia""" team_goal = [] for match in goal_record.split(";\n"): for team in match.split("–"): team_goal.append(team) wc_2018_goal = {} for num in range(len(team_goal)): if num % 2 == 0: wc_2018_goal[team_goal[num][:-2]] = 0 else: wc_2018_goal[team_goal[num][2:]] = 0 for num in range(len(team_goal)): if num % 2 == 0: wc_2018_goal[team_goal[num][:-2]] += int(team_goal[num][-1]) else: wc_2018_goal[team_goal[num][2:]] += int(team_goal[num][0]) for key,value in wc_2018_goal.items(): print(key,value)

[ "[email protected]" ]

[email protected]

50b8d4da6ad76e44d8f29598f31da8e0096c0e67

a397ac42dab5e68342a412a0b00cbcf401663d13

/multithreadingTest.py

5a334e82563ae69481bcbf69394dba9799268153

[]

no_license

declanoller/rpi_camera1

b2fdc2798e3c44980a0d09ac1414a65e06ddc821

5dff10b9745b660d21a23dd4a9d42be34d1340b1

refs/heads/master

2020-03-21T09:58:25.576696

2018-08-07T22:13:14

138,427,312

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UTF-8

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py

from multiprocessing import Pool, Value import datetime from time import sleep import os def processFile(fName): dtString = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S") print("Processed file "+fName+" at time "+dtString+"\n") def fileMonitor(dir): print("entering filemonitor") processedFiles = [] files = os.listdir(dir) nFiles = len(files) print("there are {} files in the directory.".format(nFiles)) while True: sleep(.5) files = os.listdir(dir) if len(files)>nFiles: print("new files found") nFiles = len(files) print("this many files now:",nFiles) [processFile(file) for file in files if file not in processedFiles] [processedFiles.append(file) for file in files if file not in processedFiles] def fileSaver(path): print("entering filesaver") while True: sleep(3) dtString = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S") fName = path+"/"+dtString+".txt" print("created new file "+fName+" at time "+dtString+"\n") f = open(fName,'w') f.write("created new file "+fName+" at time "+dtString+"\n") f.close() if len(os.sys.argv)>1: dir = os.sys.argv[1] print(dir) print(len(dir)) print(len((str(dir),))) pool = Pool(processes=2) p1 = pool.apply_async(fileMonitor,args=(dir,)) p2 = pool.apply_async(fileSaver,args=(dir,)) print(p1.get(timeout=30)) print(p2.get(timeout=30))

[ "[email protected]" ]

[email protected]

bcf1792361959fe827e7c081b4078be6ae08174b

6580ba5d135c4f33f1a0996953ba2a65f7458a14

/applications/ji178/models/fdutilities0color.py

91fd463eb0f338b25751b6a4ed0885b19f611149

[ "LicenseRef-scancode-public-domain", "MIT" ]

permissive

ali96343/facew2p

02b038d3853691264a49de3409de21c8a33544b8

a3881b149045e9caac344402c8fc4e62edadb42f

refs/heads/master

2021-06-10T17:52:22.200508

2021-05-10T23:11:30

185,795,614

7

0

null

UTF-8

Python

false

6,439

py

# # table for controller: utilities_color # from gluon.contrib.populate import populate db.define_table('dutilities0color', Field('f0', label='key', writable = True , length= 1000), Field('f1', 'text', label='data string', length= 1000), Field('f2', 'text', label='save data string', length= 1000, default='' ), ) # if not db(db.dutilities0color.id ).count(): db.dutilities0color.insert( f0= 'sp247', f1= '(247)Dashboard') db.dutilities0color.insert( f0= 'sp248', f1= '(248)Components') db.dutilities0color.insert( f0= 'hf249', f1= '(249)Custom Components:') db.dutilities0color.insert( f0= 'aa251', f1= '(251)Buttons') db.dutilities0color.insert( f0= 'aa253', f1= '(253)Cards') db.dutilities0color.insert( f0= 'sp254', f1= '(254)Utilities') db.dutilities0color.insert( f0= 'hf255', f1= '(255)Custom Utilities:') db.dutilities0color.insert( f0= 'aa257', f1= '(257)Colors') db.dutilities0color.insert( f0= 'aa259', f1= '(259)Borders') db.dutilities0color.insert( f0= 'aa261', f1= '(261)Animations') db.dutilities0color.insert( f0= 'aa263', f1= '(263)Other') db.dutilities0color.insert( f0= 'sp264', f1= '(264)Pages') db.dutilities0color.insert( f0= 'hf265', f1= '(265)Login Screens:') db.dutilities0color.insert( f0= 'aa267', f1= '(267)Login') db.dutilities0color.insert( f0= 'aa269', f1= '(269)Register') db.dutilities0color.insert( f0= 'aa271', f1= '(271)Forgot Password') db.dutilities0color.insert( f0= 'hf272', f1= '(272)Other Pages:') db.dutilities0color.insert( f0= 'aa274', f1= '(274)404 Page') db.dutilities0color.insert( f0= 'aa276', f1= '(276)Blank Page') db.dutilities0color.insert( f0= 'sp278', f1= '(278)Charts') db.dutilities0color.insert( f0= 'sp280', f1= '(280)Tables') db.dutilities0color.insert( f0= 'pb281', f1= '(281)Search for...') db.dutilities0color.insert( f0= 'pb282', f1= '(282)Search for...') db.dutilities0color.insert( f0= 'sx283', f1= '(283)3+') db.dutilities0color.insert( f0= 'di284', f1= '(284)December 12, 2019') db.dutilities0color.insert( f0= 'sx285', f1= '(285)A new monthly report is ready to download!') db.dutilities0color.insert( f0= 'di286', f1= '(286)December 7, 2019') db.dutilities0color.insert( f0= 'di287', f1= '(287)December 2, 2019') db.dutilities0color.insert( f0= 'aa288', f1= '(288)Show All Alerts') db.dutilities0color.insert( f0= 'di289', f1= '(289)Hi there! I am wondering if you can help me with a problem I ve been having.') db.dutilities0color.insert( f0= 'di290', f1= '(290)Emily Fowler 58m') db.dutilities0color.insert( f0= 'di291', f1= '(291)I have the photos that you ordered last month, how would you like them sent to you?') db.dutilities0color.insert( f0= 'di292', f1= '(292)Jae Chun 1d') db.dutilities0color.insert( f0= 'di293', f1= '(293)Last month s report looks great, I am very happy with the progress so far, keep up the good work!') db.dutilities0color.insert( f0= 'di294', f1= '(294)Morgan Alvarez 2d') db.dutilities0color.insert( f0= 'di295', f1= '(295)Am I a good boy? The reason I ask is because someone told me that people say this to all dogs, even if they aren t good...') db.dutilities0color.insert( f0= 'di296', f1= '(296)Chicken the Dog 2w') db.dutilities0color.insert( f0= 'aa297', f1= '(297)Read More Messages') db.dutilities0color.insert( f0= 'sx298', f1= '(298)Valerie Luna') db.dutilities0color.insert( f0= 'ha299', f1= '(299)Color Utilities') db.dutilities0color.insert( f0= 'pc300', f1= '(300)page. The custom utilities below were created to extend this theme past the default utility classes built into Bootstrap s framework.') db.dutilities0color.insert( f0= 'aa301', f1= '(301)Bootstrap Documentation') db.dutilities0color.insert( f0= 'hf302', f1= '(302)Custom Text Color Utilities') db.dutilities0color.insert( f0= 'pc303', f1= '(303).text-gray-100') db.dutilities0color.insert( f0= 'pc304', f1= '(304).text-gray-200') db.dutilities0color.insert( f0= 'pc305', f1= '(305).text-gray-300') db.dutilities0color.insert( f0= 'pc306', f1= '(306).text-gray-400') db.dutilities0color.insert( f0= 'pc307', f1= '(307).text-gray-500') db.dutilities0color.insert( f0= 'pc308', f1= '(308).text-gray-600') db.dutilities0color.insert( f0= 'pc309', f1= '(309).text-gray-700') db.dutilities0color.insert( f0= 'pc310', f1= '(310).text-gray-800') db.dutilities0color.insert( f0= 'pc311', f1= '(311).text-gray-900') db.dutilities0color.insert( f0= 'hf312', f1= '(312)Custom Font Size Utilities') db.dutilities0color.insert( f0= 'pc313', f1= '(313).text-xs') db.dutilities0color.insert( f0= 'pc314', f1= '(314).text-lg') db.dutilities0color.insert( f0= 'hf315', f1= '(315)Custom Background Gradient Utilities') db.dutilities0color.insert( f0= 'di316', f1= '(316).bg-gradient-primary') db.dutilities0color.insert( f0= 'di317', f1= '(317).bg-gradient-success') db.dutilities0color.insert( f0= 'di318', f1= '(318).bg-gradient-info') db.dutilities0color.insert( f0= 'di319', f1= '(319).bg-gradient-warning') db.dutilities0color.insert( f0= 'di320', f1= '(320).bg-gradient-danger') db.dutilities0color.insert( f0= 'hf321', f1= '(321)Custom Grayscale Background Utilities') db.dutilities0color.insert( f0= 'di322', f1= '(322).bg-gray-100') db.dutilities0color.insert( f0= 'di323', f1= '(323).bg-gray-200') db.dutilities0color.insert( f0= 'di324', f1= '(324).bg-gray-300') db.dutilities0color.insert( f0= 'di325', f1= '(325).bg-gray-400') db.dutilities0color.insert( f0= 'di326', f1= '(326).bg-gray-500') db.dutilities0color.insert( f0= 'di327', f1= '(327).bg-gray-600') db.dutilities0color.insert( f0= 'di328', f1= '(328).bg-gray-700') db.dutilities0color.insert( f0= 'di329', f1= '(329).bg-gray-800') db.dutilities0color.insert( f0= 'di330', f1= '(330).bg-gray-900') db.dutilities0color.insert( f0= 'sp331', f1= '(331)Copyright © Your Website 2019') db.dutilities0color.insert( f0= 'he332', f1= '(332)Ready to Leave?') db.dutilities0color.insert( f0= 'sx333', f1= '(333)') db.dutilities0color.insert( f0= 'di334', f1= '(334)Select Logout below if you are ready to end your current session.') db.dutilities0color.insert( f0= 'bu335', f1= '(335)Cancel') db.dutilities0color.insert( f0= 'aa337', f1= '(337)Logout') db.commit() #

[ "[email protected]" ]

[email protected]

7805ee413e99196317a0afddff32012074eee45c

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/cadash/utils.py

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# -*- coding: utf-8 -*- """Helper utilities and decorators.""" import os import logging import logging.config import platform import re import sys import yaml from flask import current_app from flask import flash from flask import redirect from flask import request from flask import url_for from flask_login import current_user from functools import wraps import requests from requests.auth import HTTPBasicAuth from cadash import __version__ from cadash.user.models import BaseUser def flash_errors(form, category='warning'): """Flash all errors for a form.""" for field, errors in form.errors.items(): for error in errors: flash('{0} - {1}'.format(getattr(form, field).label.text, error), category) # from http://victorlin.me/posts/2012/08/26/good-logging-practice-in-python def setup_logging( app, default_level=logging.INFO): """ set up logging config. :param: app: application obj; relevant app.config['LOG_CONFIG'] which is the full path to the yaml file with configs for logs :param: default_level: log level for basic config, default=INFO """ if os.path.exists(app.config['LOG_CONFIG']): with open(app.config['LOG_CONFIG'], 'rt') as f: config = yaml.load(f.read()) logging.config.dictConfig(config) else: logging.basicConfig(level=default_level) def clean_name(name): """ clean `name` from non_alpha. replaces non-alpha with underscores '_' and set the string to lower case """ return re.sub('[^0-9a-zA-Z]+', '_', name.strip()).lower() def pull_data(url, creds=None): """ get text file from `url`. reads a text file from given url if basic auth needed, pass args creds['user'] and creds['pwd'] """ headers = { 'User-Agent': default_useragent(), 'Accept-Encoding': 'gzip, deflate', 'Accept': 'text/html, text/*' } au = None if creds is not None: if 'user' in creds and 'pwd' in creds: au = HTTPBasicAuth(creds['user'], creds['pwd']) headers.update({'X-REQUESTED-AUTH': 'Basic'}) try: response = requests.get(url, headers=headers, auth=au) except requests.HTTPError as e: logger = logging.getLogger(__name__) logger.warning('data from url(%s) is unavailable. Error: %s' % (url, e)) return None else: return response.text def default_useragent(): """Return a string representing the default user agent.""" _implementation = platform.python_implementation() if _implementation == 'CPython': _implementation_version = platform.python_version() elif _implementation == 'PyPy': _implementation_version = '%s.%s.%s' % (sys.pypy_version_info.major, sys.pypy_version_info.minor, sys.pypy_version_info.micro) if sys.pypy_version_info.releaselevel != 'final': _implementation_version = ''.join( [_implementation_version, sys.pypy_version_info.releaselevel]) elif _implementation == 'Jython': _implementation_version = platform.python_version() # Complete Guess elif _implementation == 'IronPython': _implementation_version = platform.python_version() # Complete Guess else: _implementation_version = 'Unknown' try: p_system = platform.system() p_release = platform.release() except IOError: p_system = 'Unknown' p_release = 'Unknown' return ' '.join([ '%s/%s' % (__name__, __version__), '%s/%s' % (_implementation, _implementation_version), '%s/%s' % (p_system, p_release)]) def fetch_ldap_user(usr, pwd, cli): """fetch user in ldap, and the groups user belongs to. returns a BaseUser object or None if not authenticated or unknown """ if cli.is_authenticated(usr, pwd): u = BaseUser(usr) groups = cli.fetch_groups(usr) u.place_in_groups(groups) return u else: return None def is_authorized_by_groups(user, groups): """return True if `user` in any group of list `groups`.""" for g in groups: if user.is_in_group(g): return True return False def requires_roles(*roles): def wrapper(f): @wraps(f) def wrapped(*args, **kwargs): if not current_app.config.get('LOGIN_DISABLED'): if not is_authorized_by_groups(current_user, *roles): flash('You need to login, or do not have credentials to access this page', 'info') return redirect(url_for('public.home', next=request.url)) return f(*args, **kwargs) return wrapped return wrapper

[ "[email protected]" ]

[email protected]

4bb2be4d6fdbddbaf576d3a9d74969ce33b1a2ce

f44aa93f92f2ddfa0e3ed6595c0b77c3ab14dde1

/v7_Modular_events/runner.py

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[]

no_license

michaeljpitcher/Lung-Network-Model

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8f23dc1c2002bdabc0f8ec5bd5078d64628adcb5

refs/heads/master

2020-06-23T05:17:07.357279

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__author__ = "Michael J. Pitcher" from Models.TB.TBModel3 import TBModel3 from Models.TB.TBClasses import * from Models.TB.TBEventProbabilityKeys import * params = {} params[P_REPLICATION_BACTERIA_FAST] = 0.1 params[P_REPLICATION_BACTERIA_SLOW] = 0.01 params[P_TRANSLOCATE_BRONCHUS_BACTERIA_FAST] = 0.0 params[P_TRANSLOCATE_BRONCHUS_BACTERIA_SLOW] = 0.0 params[P_CHANGE_BACTERIA_FAST_TO_SLOW] = 0.0 params[P_CHANGE_BACTERIA_SLOW_TO_FAST] = 0.0 params[P_INGEST_AND_DESTROY_MACROPHAGE_FAST] = 0.0 params[P_INGEST_AND_DESTROY_MACROPHAGE_SLOW] = 0.0 params[P_RECRUITMENT_BPS_MACROPHAGE] = 0.0 params[P_RECRUITMENT_LYMPH_MACROPHAGE] = 0.0 params[P_DEATH_MACROPHAGE] = 0.0 model = TBModel3(params) loads_f = {1: 10} loads_s = {2: 5} loads_m = {3: 10} model.load(loads_f, loads_s, loads_m) import cProfile p = cProfile.Profile() p.enable() model.run(75) p.disable() p.print_stats('cumtime') # model.display_network([BACTERIA_FAST, BACTERIA_SLOW, MACROPHAGE])

[ "[email protected]" ]

[email protected]

b7a9408ba9cddb579b33e13dd708ac9ca84475dd

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/qa/rpc-tests/maxuploadtarget.py

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#!/usr/bin/env python2 # # Distributed under the MIT/X11 software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. # from test_framework.mininode import * from test_framework.test_framework import BitcoinTestFramework from test_framework.util import * import time ''' Test behavior of -maxuploadtarget. * Verify that getdata requests for old blocks (>1week) are dropped if uploadtarget has been reached. * Verify that getdata requests for recent blocks are respecteved even if uploadtarget has been reached. * Verify that the upload counters are reset after 24 hours. ''' # TestNode: bare-bones "peer". Used mostly as a conduit for a test to sending # p2p messages to a node, generating the messages in the main testing logic. class TestNode(NodeConnCB): def __init__(self): NodeConnCB.__init__(self) self.connection = None self.ping_counter = 1 self.last_pong = msg_pong() self.block_receive_map = {} def add_connection(self, conn): self.connection = conn self.peer_disconnected = False def on_inv(self, conn, message): pass # Track the last getdata message we receive (used in the test) def on_getdata(self, conn, message): self.last_getdata = message def on_block(self, conn, message): message.block.calc_sha256() try: self.block_receive_map[message.block.sha256] += 1 except KeyError as e: self.block_receive_map[message.block.sha256] = 1 # Spin until verack message is received from the node. # We use this to signal that our test can begin. This # is called from the testing thread, so it needs to acquire # the global lock. def wait_for_verack(self): def veracked(): return self.verack_received return wait_until(veracked, timeout=10) def wait_for_disconnect(self): def disconnected(): return self.peer_disconnected return wait_until(disconnected, timeout=10) # Wrapper for the NodeConn's send_message function def send_message(self, message): self.connection.send_message(message) def on_pong(self, conn, message): self.last_pong = message def on_close(self, conn): self.peer_disconnected = True # Sync up with the node after delivery of a block def sync_with_ping(self, timeout=30): def received_pong(): return (self.last_pong.nonce == self.ping_counter) self.connection.send_message(msg_ping(nonce=self.ping_counter)) success = wait_until(received_pong, timeout) self.ping_counter += 1 return success class MaxUploadTest(BitcoinTestFramework): def __init__(self): self.utxo = [] self.txouts = gen_return_txouts() def add_options(self, parser): parser.add_option("--testbinary", dest="testbinary", default=os.getenv("USDED", "usdecoind"), help="usdecoind binary to test") def setup_chain(self): initialize_chain_clean(self.options.tmpdir, 2) def setup_network(self): # Start a node with maxuploadtarget of 200 MB (/24h) self.nodes = [] self.nodes.append(start_node(0, self.options.tmpdir, ["-debug", "-maxuploadtarget=200", "-blockmaxsize=999000"])) def mine_full_block(self, node, address): # Want to create a full block # We'll generate a 66k transaction below, and 14 of them is close to the 1MB block limit for j in xrange(14): if len(self.utxo) < 14: self.utxo = node.listunspent() inputs=[] outputs = {} t = self.utxo.pop() inputs.append({ "txid" : t["txid"], "vout" : t["vout"]}) remchange = t["amount"] - Decimal("0.001000") outputs[address]=remchange # Create a basic transaction that will send change back to ourself after account for a fee # And then insert the 128 generated transaction outs in the middle rawtx[92] is where the # # of txouts is stored and is the only thing we overwrite from the original transaction rawtx = node.createrawtransaction(inputs, outputs) newtx = rawtx[0:92] newtx = newtx + self.txouts newtx = newtx + rawtx[94:] # Appears to be ever so slightly faster to sign with SIGHASH_NONE signresult = node.signrawtransaction(newtx,None,None,"NONE") txid = node.sendrawtransaction(signresult["hex"], True) # Mine a full sized block which will be these transactions we just created node.generate(1) def run_test(self): # Before we connect anything, we first set the time on the node # to be in the past, otherwise things break because the CNode # time counters can't be reset backward after initialization old_time = int(time.time() - 2*60*60*24*7) self.nodes[0].setmocktime(old_time) # Generate some old blocks self.nodes[0].generate(130) # test_nodes[0] will only request old blocks # test_nodes[1] will only request new blocks # test_nodes[2] will test resetting the counters test_nodes = [] connections = [] for i in xrange(3): test_nodes.append(TestNode()) connections.append(NodeConn('127.0.0.1', p2p_port(0), self.nodes[0], test_nodes[i])) test_nodes[i].add_connection(connections[i]) NetworkThread().start() # Start up network handling in another thread [x.wait_for_verack() for x in test_nodes] # Test logic begins here # Now mine a big block self.mine_full_block(self.nodes[0], self.nodes[0].getnewaddress()) # Store the hash; we'll request this later big_old_block = self.nodes[0].getbestblockhash() old_block_size = self.nodes[0].getblock(big_old_block, True)['size'] big_old_block = int(big_old_block, 16) # Advance to two days ago self.nodes[0].setmocktime(int(time.time()) - 2*60*60*24) # Mine one more block, so that the prior block looks old self.mine_full_block(self.nodes[0], self.nodes[0].getnewaddress()) # We'll be requesting this new block too big_new_block = self.nodes[0].getbestblockhash() new_block_size = self.nodes[0].getblock(big_new_block)['size'] big_new_block = int(big_new_block, 16) # test_nodes[0] will test what happens if we just keep requesting the # the same big old block too many times (expect: disconnect) getdata_request = msg_getdata() getdata_request.inv.append(CInv(2, big_old_block)) max_bytes_per_day = 200*1024*1024 daily_buffer = 144 * MAX_BLOCK_SIZE max_bytes_available = max_bytes_per_day - daily_buffer success_count = max_bytes_available // old_block_size # 144MB will be reserved for relaying new blocks, so expect this to # succeed for ~70 tries. for i in xrange(success_count): test_nodes[0].send_message(getdata_request) test_nodes[0].sync_with_ping() assert_equal(test_nodes[0].block_receive_map[big_old_block], i+1) assert_equal(len(self.nodes[0].getpeerinfo()), 3) # At most a couple more tries should succeed (depending on how long # the test has been running so far). for i in xrange(3): test_nodes[0].send_message(getdata_request) test_nodes[0].wait_for_disconnect() assert_equal(len(self.nodes[0].getpeerinfo()), 2) print "Peer 0 disconnected after downloading old block too many times" # Requesting the current block on test_nodes[1] should succeed indefinitely, # even when over the max upload target. # We'll try 200 times getdata_request.inv = [CInv(2, big_new_block)] for i in xrange(200): test_nodes[1].send_message(getdata_request) test_nodes[1].sync_with_ping() assert_equal(test_nodes[1].block_receive_map[big_new_block], i+1) print "Peer 1 able to repeatedly download new block" # But if test_nodes[1] tries for an old block, it gets disconnected too. getdata_request.inv = [CInv(2, big_old_block)] test_nodes[1].send_message(getdata_request) test_nodes[1].wait_for_disconnect() assert_equal(len(self.nodes[0].getpeerinfo()), 1) print "Peer 1 disconnected after trying to download old block" print "Advancing system time on node to clear counters..." # If we advance the time by 24 hours, then the counters should reset, # and test_nodes[2] should be able to retrieve the old block. self.nodes[0].setmocktime(int(time.time())) test_nodes[2].sync_with_ping() test_nodes[2].send_message(getdata_request) test_nodes[2].sync_with_ping() assert_equal(test_nodes[2].block_receive_map[big_old_block], 1) print "Peer 2 able to download old block" [c.disconnect_node() for c in connections] #stop and start node 0 with 1MB maxuploadtarget, whitelist 127.0.0.1 print "Restarting nodes with -whitelist=127.0.0.1" stop_node(self.nodes[0], 0) self.nodes[0] = start_node(0, self.options.tmpdir, ["-debug", "-whitelist=127.0.0.1", "-maxuploadtarget=1", "-blockmaxsize=999000"]) #recreate/reconnect 3 test nodes test_nodes = [] connections = [] for i in xrange(3): test_nodes.append(TestNode()) connections.append(NodeConn('127.0.0.1', p2p_port(0), self.nodes[0], test_nodes[i])) test_nodes[i].add_connection(connections[i]) NetworkThread().start() # Start up network handling in another thread [x.wait_for_verack() for x in test_nodes] #retrieve 20 blocks which should be enough to break the 1MB limit getdata_request.inv = [CInv(2, big_new_block)] for i in xrange(20): test_nodes[1].send_message(getdata_request) test_nodes[1].sync_with_ping() assert_equal(test_nodes[1].block_receive_map[big_new_block], i+1) getdata_request.inv = [CInv(2, big_old_block)] test_nodes[1].send_message(getdata_request) test_nodes[1].wait_for_disconnect() assert_equal(len(self.nodes[0].getpeerinfo()), 3) #node is still connected because of the whitelist print "Peer 1 still connected after trying to download old block (whitelisted)" [c.disconnect_node() for c in connections] if __name__ == '__main__': MaxUploadTest().main()

[ "[email protected]" ]

[email protected]

a10f9c0aa132f6863b3adb1a46e00038ae728335

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/dnac_api_client/models/claim_device_request_config_list.py

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yijxiang/dnac-api-client

842d1da9e156820942656b8f34342d52c96d3c37

256d016e2df8fc1b3fdad6e28f441c6005b43b07

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# coding: utf-8 """ Cisco DNA Center Platform v. 1.2.x (EFT) REST API (EFT) # noqa: E501 OpenAPI spec version: 1.0.0 Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six class ClaimDeviceRequestConfigList(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'config_id': 'str', 'config_parameters': 'list[ClaimDeviceRequestConfigParameters]' } attribute_map = { 'config_id': 'configId', 'config_parameters': 'configParameters' } def __init__(self, config_id=None, config_parameters=None): # noqa: E501 """ClaimDeviceRequestConfigList - a model defined in OpenAPI""" # noqa: E501 self._config_id = None self._config_parameters = None self.discriminator = None if config_id is not None: self.config_id = config_id if config_parameters is not None: self.config_parameters = config_parameters @property def config_id(self): """Gets the config_id of this ClaimDeviceRequestConfigList. # noqa: E501 :return: The config_id of this ClaimDeviceRequestConfigList. # noqa: E501 :rtype: str """ return self._config_id @config_id.setter def config_id(self, config_id): """Sets the config_id of this ClaimDeviceRequestConfigList. :param config_id: The config_id of this ClaimDeviceRequestConfigList. # noqa: E501 :type: str """ self._config_id = config_id @property def config_parameters(self): """Gets the config_parameters of this ClaimDeviceRequestConfigList. # noqa: E501 :return: The config_parameters of this ClaimDeviceRequestConfigList. # noqa: E501 :rtype: list[ClaimDeviceRequestConfigParameters] """ return self._config_parameters @config_parameters.setter def config_parameters(self, config_parameters): """Sets the config_parameters of this ClaimDeviceRequestConfigList. :param config_parameters: The config_parameters of this ClaimDeviceRequestConfigList. # noqa: E501 :type: list[ClaimDeviceRequestConfigParameters] """ self._config_parameters = config_parameters def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, ClaimDeviceRequestConfigList): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "[email protected]" ]

[email protected]

b906a8ee56c5bdb20867a9f5ededa1379458b25e

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import numpy as np import matplotlib.colors as mcolors whitepoint_D65 = np.array([0.9642, 1, 0.8249]) A_xyz2rgb = np.array( [[3.240479, -1.537150, -0.498535], [-0.969256, 1.875992, 0.041556 ], [0.055648, -0.204043, 1.057311 ]]) A_rgb2xyz = np.linalg.inv(A_xyz2rgb) class RGBRangeError(Exception): pass def f(t): if t > (6./29)**3: return t**(1./3) else: return 1./3 * (29./6)**2 * t + 4./29 def f_inv(t): if t > 6./29: return t**3 else: return 3 * (6./29)**2 * (t - 4./29) def xyz2lab(xyz, whitepoint=whitepoint_D65): """ Convert from CIELAB to XYZ color coordinates. *Arguments* xyz: 3-tuple (or other list-like) *Returns* 3-tuple (L, a, b). """ X, Y, Z = xyz Xw, Yw, Zw = whitepoint L = 116. * f(Y/Yw) - 16 a = 500. * (f(X/Xw) - f(Y/Yw)) b = 200. * (f(Y/Yw) - f(Z/Zw)) return np.array([L, a, b], dtype=float) def lab2xyz(lab, whitepoint=whitepoint_D65): L, a, b = lab Xw, Yw, Zw = whitepoint Y = Yw * f_inv(1./116 * (L + 16)) X = Xw * f_inv(1./116 * (L + 16) + 0.002 * a) Z = Zw * f_inv(1./116 * (L + 16) - 0.005 * b) return X, Y, Z def rgb2xyz(rgb): rgb = np.asarray(rgb) return np.dot(A_rgb2xyz, rgb) def xyz2rgb(xyz, assert_valid=False, clip=False): xyz = np.asarray(xyz) rgb = np.dot(A_xyz2rgb, xyz) r, g, b = rgb if assert_valid and ((r < 0.0 or r > 1.0) or (g < 0.0 or g > 1.0) or (b < 0.0 or b > 1.0)): raise RGBRangeError() if clip: rgb = np.clip(rgb, 0., 1.) return rgb def rgb2lab(rgb, whitepoint=whitepoint_D65): return xyz2lab(rgb2xyz(rgb), whitepoint=whitepoint) def lab2rgb(lab, whitepoint=whitepoint_D65, assert_valid=False, clip=False): return xyz2rgb(lab2xyz(lab, whitepoint=whitepoint), assert_valid=assert_valid, clip=clip) def rgb2rgba(rgb): r, g, b = rgb return np.array([r, g, b, 1.]) def lab2rgba(lab, whitepoint=whitepoint_D65, assert_valid=False, clip=False): return rgb2rgba(lab2rgb(lab, whitepoint=whitepoint, assert_valid=assert_valid, clip=clip)) def linear_colormap(pt1, pt2, coordspace='RGB'): """ Define a perceptually linear colormap defined through a line in the CIELab [1] color space. The line is defined by its endpoints `pt1`, `pt2`. The argument `coordspace` can be either `RGB` (the default) or `lab` and specifies whether the coordinates of `pt1`, `pt2` are given in RGB or Lab coordinates. [1] http://dba.med.sc.edu/price/irf/Adobe_tg/models/cielab.html """ if coordspace == 'RGB': pt1 = np.array(rgb2lab(pt1)) pt2 = np.array(rgb2lab(pt2)) elif coordspace == 'Lab': pt1 = np.array(pt1) pt2 = np.array(pt2) else: raise ValueError("Argument 'coordspace' must be either 'RGB' " "or 'Lab'. Got: {}".format(coordspace)) tvals = np.linspace(0, 1, 256) path_vals = np.array([(1-t) * pt1 + t * pt2 for t in tvals]) cmap_vals = np.array([lab2rgb(pt) for pt in path_vals]) #print np.where(cmap_vals < 0) cmap = mcolors.ListedColormap(cmap_vals) return cmap

[ "[email protected]" ]

[email protected]

65ff0d2791ba3bee69abbe3799d327244d350005

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/flarestack/cosmo/rates/frb_rates.py

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[ "MIT" ]

permissive

icecube/flarestack

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refs/heads/master

2023-08-16T16:05:18.492306

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2023-09-13T00:17:44

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import logging from astropy import units as u from flarestack.cosmo.rates.sfr_rates import get_sfr_evolution local_frb_rates = { "bochenek_20": ( 7.23 * 10**7.0 / (u.Gpc**3 * u.yr), (7.23 - 6.13) * 10**7.0 / (u.Gpc**3 * u.yr), (7.23 + 8.78) * 10**7.0 / (u.Gpc**3 * u.yr), "https://arxiv.org/abs/2005.10828", ), } def get_local_frb_rate(rate_name=None, with_range=False): """Returns a local rate of Fast Radio Bursts (FBBs). :param rate_name: Name of local FRB rate to be used :param with_range: Boolean to return +/- one sigma range functions alongside central rate :return: Local rate """ if rate_name is None: logging.info("No rate specified. Assuming default rate.") rate_name = "bochenek_20" if rate_name not in local_frb_rates.keys(): raise Exception( f"Rate name '{rate_name}' not recognised. " f"The following rates are available: {local_frb_rates.keys()}" ) else: local_rate, lower_lim, upper_lim, ref = local_frb_rates[rate_name] logging.info(f"Loaded rate '{rate_name}' ({ref})") if with_range: if lower_lim is None: raise Exception( f"No one sigma rate range found for rate '{rate_name}'. " f"Use a different rate, or set 'with_range=False'." ) return ( local_rate.to("Mpc-3 yr-1"), lower_lim.to("Mpc-3 yr-1"), upper_lim.to("Mpc-3 yr-1"), ) else: return local_rate.to("Mpc-3 yr-1") def get_frb_rate(evolution_name=None, rate_name=None, with_range=False, **kwargs): """Returns a local rate of core-collapse supernovae (CCSNe) as a function of redshift. :param evolution_name: Name of Star Formation evolution to use :param rate_name: Name of local FRB rate to be used :param with_range: Boolean to return +/- one sigma range functions alongside central rate :return: Rate as a function of redshift """ normed_evolution = get_sfr_evolution(evolution_name=evolution_name, **kwargs) local_rate = get_local_frb_rate(rate_name=rate_name, with_range=with_range) if with_range: return ( lambda z: local_rate[0] * normed_evolution(z), lambda z: local_rate[1] * normed_evolution(z), lambda z: local_rate[2] * normed_evolution(z), ) else: return lambda z: local_rate * normed_evolution(z)

[ "[email protected]" ]

[email protected]

4d925c84db3c96226c9de413a722a8e09a7e2080

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/nemo/collections/nlp/models/language_modeling/bert_lm_model.py

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# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from typing import Dict, Optional import torch from omegaconf import DictConfig, OmegaConf from pytorch_lightning import Trainer from torch.utils.data import DataLoader from nemo.collections.common.losses import AggregatorLoss, CrossEntropyLoss, SmoothedCrossEntropyLoss from nemo.collections.common.metrics import Perplexity from nemo.collections.nlp.data.language_modeling.lm_bert_dataset import ( BertPretrainingDataset, BertPretrainingPreprocessedDataloader, ) from nemo.collections.nlp.modules.common import BertPretrainingTokenClassifier, SequenceClassifier from nemo.collections.nlp.modules.common.lm_utils import get_lm_model from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer from nemo.core.classes.common import PretrainedModelInfo, typecheck from nemo.core.classes.modelPT import ModelPT from nemo.core.neural_types import NeuralType from nemo.utils import logging __all__ = ["BERTLMModel"] class BERTLMModel(ModelPT): """ BERT language model pretraining. """ @property def input_types(self) -> Optional[Dict[str, NeuralType]]: return self.bert_model.input_types @property def output_types(self) -> Optional[Dict[str, NeuralType]]: output_types_dict = {"mlm_log_probs": self.mlm_classifier.output_types["log_probs"]} if not self.only_mlm_loss: output_types_dict["nsp_logits"] = self.nsp_classifier.output_types["logits"] return output_types_dict def __init__(self, cfg: DictConfig, trainer: Trainer = None): vocab_file = None config_dict = None config_file = None if cfg.tokenizer is not None: if cfg.tokenizer.get('tokenizer_name') and cfg.tokenizer.get('tokenizer_model'): self._setup_tokenizer(cfg.tokenizer) if cfg.get('tokenizer.vocab_file'): vocab_file = self.register_artifact('tokenizer.vocab_file', cfg.tokenizer.vocab_file) else: self.tokenizer = None super().__init__(cfg=cfg, trainer=trainer) if cfg.get('language_model.config'): config_dict = OmegaConf.to_container(cfg.language_model.config) if cfg.get('language_model.config_file'): config_file = self.register_artifact('language_model.config_file', cfg.language_model.config_file) self.bert_model = get_lm_model( config_file=config_file, config_dict=config_dict, vocab_file=vocab_file, trainer=trainer, cfg=cfg, ) self.hidden_size = self.bert_model.config.hidden_size self.vocab_size = self.bert_model.config.vocab_size self.only_mlm_loss = cfg.only_mlm_loss self.mlm_classifier = BertPretrainingTokenClassifier( hidden_size=self.hidden_size, num_classes=self.vocab_size, num_layers=cfg.num_tok_classification_layers, activation="gelu", log_softmax=True, use_transformer_init=True, ) self.mlm_loss = SmoothedCrossEntropyLoss() if not self.only_mlm_loss: self.nsp_classifier = SequenceClassifier( hidden_size=self.hidden_size, num_classes=2, num_layers=cfg.num_seq_classification_layers, log_softmax=False, activation="tanh", use_transformer_init=True, ) self.nsp_loss = CrossEntropyLoss() self.agg_loss = AggregatorLoss(num_inputs=2) # # tie weights of MLM softmax layer and embedding layer of the encoder if ( self.mlm_classifier.mlp.last_linear_layer.weight.shape != self.bert_model.embeddings.word_embeddings.weight.shape ): raise ValueError("Final classification layer does not match embedding layer.") self.mlm_classifier.mlp.last_linear_layer.weight = self.bert_model.embeddings.word_embeddings.weight # create extra bias # setup to track metrics self.validation_perplexity = Perplexity() self.setup_optimization(cfg.optim) @typecheck() def forward(self, input_ids, attention_mask, token_type_ids): """ No special modification required for Lightning, define it as you normally would in the `nn.Module` in vanilla PyTorch. """ hidden_states = self.bert_model( input_ids=input_ids, token_type_ids=token_type_ids, attention_mask=attention_mask, ) if isinstance(hidden_states, tuple): hidden_states = hidden_states[0] mlm_log_probs = self.mlm_classifier(hidden_states=hidden_states) if self.only_mlm_loss: return (mlm_log_probs,) nsp_logits = self.nsp_classifier(hidden_states=hidden_states) return mlm_log_probs, nsp_logits def _compute_losses(self, mlm_log_probs, nsp_logits, output_ids, output_mask, labels): mlm_loss = self.mlm_loss(log_probs=mlm_log_probs, labels=output_ids, output_mask=output_mask) if self.only_mlm_loss: loss, nsp_loss = mlm_loss, None else: nsp_loss = self.nsp_loss(logits=nsp_logits, labels=labels) loss = self.agg_loss(loss_1=mlm_loss, loss_2=nsp_loss) return mlm_loss, nsp_loss, loss def _parse_forward_outputs(self, forward_outputs): if self.only_mlm_loss: return forward_outputs[0], None else: return forward_outputs def training_step(self, batch, batch_idx): """ Lightning calls this inside the training loop with the data from the training dataloader passed in as `batch`. """ input_ids, input_type_ids, input_mask, output_ids, output_mask, labels = batch forward_outputs = self.forward(input_ids=input_ids, token_type_ids=input_type_ids, attention_mask=input_mask) mlm_log_probs, nsp_logits = self._parse_forward_outputs(forward_outputs) _, _, loss = self._compute_losses(mlm_log_probs, nsp_logits, output_ids, output_mask, labels) lr = self._optimizer.param_groups[0]['lr'] self.log('train_loss', loss) self.log('lr', lr, prog_bar=True) return {"loss": loss, "lr": lr} def validation_step(self, batch, batch_idx): """ Lightning calls this inside the validation loop with the data from the validation dataloader passed in as `batch`. """ input_ids, input_type_ids, input_mask, output_ids, output_mask, labels = batch forward_outputs = self.forward(input_ids=input_ids, token_type_ids=input_type_ids, attention_mask=input_mask) mlm_log_probs, nsp_logits = self._parse_forward_outputs(forward_outputs) _, _, loss = self._compute_losses(mlm_log_probs, nsp_logits, output_ids, output_mask, labels) self.validation_perplexity(logits=mlm_log_probs) loss = {'val_loss': loss} self.validation_step_outputs.append(loss) return loss def on_validation_epoch_end(self): """Called at the end of validation to aggregate outputs. Args: outputs (list): The individual outputs of each validation step. Returns: dict: Validation loss and tensorboard logs. """ if self.validation_step_outputs: avg_loss = torch.stack([x['val_loss'] for x in self.validation_step_outputs]).mean() perplexity = self.validation_perplexity.compute() logging.info(f"evaluation perplexity {perplexity.cpu().item()}") self.log(f'val_loss', avg_loss) self.validation_step_outputs.clear() # free memory def setup_training_data(self, train_data_config: Optional[DictConfig]): self._train_dl = ( self._setup_preprocessed_dataloader(train_data_config) if self.tokenizer is None else self._setup_dataloader(train_data_config) ) def setup_validation_data(self, val_data_config: Optional[DictConfig]): self._validation_dl = ( self._setup_preprocessed_dataloader(val_data_config) if self.tokenizer is None else self._setup_dataloader(val_data_config) ) def setup_test_data(self, test_data_config: Optional[DictConfig]): pass def _setup_preprocessed_dataloader(self, cfg: Optional[DictConfig]): dataset = cfg.data_file max_predictions_per_seq = cfg.max_predictions_per_seq batch_size = cfg.batch_size if os.path.isdir(dataset): files = [os.path.join(dataset, f) for f in os.listdir(dataset) if os.path.isfile(os.path.join(dataset, f))] else: files = [dataset] files.sort() dl = BertPretrainingPreprocessedDataloader( data_files=files, max_predictions_per_seq=max_predictions_per_seq, batch_size=batch_size, ) return dl def _setup_tokenizer(self, cfg: DictConfig): tokenizer = get_tokenizer( tokenizer_name=cfg.tokenizer_name, tokenizer_model=cfg.tokenizer_model, special_tokens=OmegaConf.to_container(cfg.special_tokens) if cfg.special_tokens else None, vocab_file=cfg.vocab_file, ) self.tokenizer = tokenizer def _setup_dataloader(self, cfg: DictConfig): dataset = BertPretrainingDataset( tokenizer=self.tokenizer, data_file=cfg.data_file, max_seq_length=cfg.max_seq_length, mask_prob=cfg.mask_prob, short_seq_prob=cfg.short_seq_prob, ) dl = torch.utils.data.DataLoader( dataset=dataset, batch_size=cfg.batch_size, collate_fn=dataset.collate_fn, drop_last=cfg.get("drop_last", False), shuffle=cfg.shuffle, num_workers=cfg.get("num_workers", 0), ) return dl @classmethod def list_available_models(cls) -> Optional[PretrainedModelInfo]: """ This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud. Returns: List of available pre-trained models. """ result = [] result.append( PretrainedModelInfo( pretrained_model_name="bertbaseuncased", location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/bertbaseuncased/versions/1.0.0rc1/files/bertbaseuncased.nemo", description="The model was trained EN Wikipedia and BookCorpus on a sequence length of 512.", ) ) result.append( PretrainedModelInfo( pretrained_model_name="bertlargeuncased", location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/bertlargeuncased/versions/1.0.0rc1/files/bertlargeuncased.nemo", description="The model was trained EN Wikipedia and BookCorpus on a sequence length of 512.", ) ) return result

[ "[email protected]" ]

[email protected]

40924b52d9e6ae8604eac8a4ca7597da7cb408e8

d659f9b546e1622aec6ad10495363da1175f76b9

/venv/bin/pip3.6

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modcomlearning/advanced_web2

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b701a25092a8ae40187c3af00a837e654fefc52e

refs/heads/master

2023-01-07T21:09:06.930774

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310,833,862

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UTF-8

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#!/home/jose/PycharmProjects/Advanced_Web_Sat/venv/bin/python # EASY-INSTALL-ENTRY-SCRIPT: 'pip==10.0.1','console_scripts','pip3.6' __requires__ = 'pip==10.0.1' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('pip==10.0.1', 'console_scripts', 'pip3.6')() )

[ "[email protected]" ]

[email protected]

072fcea6ad0ec0fa0e0effea0d1e577a5e7bed48

4d99350a527a88110b7bdc7d6766fc32cf66f211

/OpenGLCffi/GLES1/EXT/OES/EGL_image.py

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[ "MIT" ]

permissive

cydenix/OpenGLCffi

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refs/heads/master

2021-01-11T07:31:10.591188

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from OpenGLCffi.GLES1 import params @params(api='gles1', prms=['target', 'image']) def glEGLImageTargetTexture2DOES(target, image): pass @params(api='gles1', prms=['target', 'image']) def glEGLImageTargetRenderbufferStorageOES(target, image): pass

[ "[email protected]" ]

[email protected]

21a3e92d50d50f8afb88ed7e4b8b1700ab8212da

0178e6a705ee8aa6bb0b0a8512bf5184a9d00ded

/Sungjin/String/5525.py

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[]

no_license

comojin1994/Algorithm_Study

0379d513abf30e3f55d6a013e90329bfdfa5adcc

965c97a9b858565c68ac029f852a1c2218369e0b

refs/heads/master

2021-08-08T14:55:15.220412

2021-07-06T11:54:33

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1

null

2020-05-14T14:06:46

2019-09-07T14:23:31

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UTF-8

Python

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py

import sys input = sys.stdin.readline if __name__ == '__main__': N = int(input()) M = int(input()) S = input().strip() P = 'I' + 'OI'*N start = False check = 0 cnt, result = 0, 0 for i, s in enumerate(S): if start: if s == 'O' and check == 1: check += 1 elif s == 'I' and check == 2: cnt += 1 else: if cnt >= N: result += cnt - N + 1 start = False check, cnt = 0, 0 if s == 'I': start = True; check = 1 if cnt >= N: result += cnt - N + 1 print(result) ''' 2 25 OOIOIIOIOIOIOIOIOIOIOOIOI 6 4 100 IIOIOIOIOIOIOOOOIOIOIOIOOIIOIOIOIOIOIOIIOIOIOIOOOIIOIOIOIOIOIOOOOIOIOIOIOIOIOOIIIIOIOIOIOIOIIOIOIOIO 11 '''

[ "[email protected]" ]

[email protected]

514e0990111b61362819faa91608463b1ba507e2

e1aac65877d20e8f93e63c8edf6dedd5137b562b

/testPydev/Integer_Roman.py

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[]

no_license

weezer/fun_scripts

67ccb6cc107c0bdd1b347d9cb1c0bdf934e1a331

38b8bd25d6db79044712779f95b26bf09ca0072a

refs/heads/master

2020-12-25T19:26:21.685571

2018-09-20T07:56:25

18,510,051

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null

UTF-8

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class Solution(object): def intToRoman(self, num): """ :type num: int :rtype: str """ roman_dict = {1: 'I', 4: 'IV', 5: 'V', 9: 'IX', 10: 'X', 40: 'XL', 50: 'L', 90: 'LC', 100: 'C', 400: 'CD', 500: 'D', 900: 'CM', 1000: 'M'} r_lst = [] digit = 1 while num > 0: a_lst = [] reminder = num % 10 reminder *= digit digit *= 10 num /= 10 if roman_dict.get(reminder) is not None: r_lst.insert(0, roman_dict.get(reminder)) else: for minus_num in sorted(roman_dict, reverse = True): if reminder == 0: break if minus_num > reminder: continue else: while reminder >= minus_num: a_lst.append(roman_dict[minus_num]) reminder -= minus_num r_lst.insert(0, ''.join(a_lst)) return ''.join(r_lst) if __name__ == "__main__": s = Solution() print s.intToRoman(3999)

[ "[email protected]" ]

[email protected]

0d51c3a3f4fe0075d723424ee07d4b36454dd438

6bfe6e6c24eeb281a266a2d3fdaac645e79a4a85

/admin/web/login_controller.py

9d8a11e94f35b293ab2b7fdd2183bdc7d0fc23cc

[]

no_license

itsumura-h/masonite_admin_install

606b5fe5f7043919fd955a48485e14d063116837

a8448eacdee0b4088b84ac2cac6d0fdec46dbe87

refs/heads/master

2020-05-31T01:17:21.094154

2019-06-30T07:11:13

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null

UTF-8

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import os, pickle, secrets from datetime import datetime from bcrypt import checkpw from masonite.auth import Sign from masonite.controllers import Controller from masonite.request import Request from config.auth import AUTH from config.admin import LOGIN_CONF from admin.web.LoginToken import LoginToken # try: # from app.models.LoginToken import LoginToken # except: # from app.LoginToken import LoginToken class LoginController(Controller): def store(self, request: Request): email = request.input('email') password = request.input('password') user = AUTH['model'].where('email', email).first() login = checkpw(bytes(password, 'utf-8'), bytes(user.password, 'utf-8')) if login: hash = LoginToken().login(int(user.id)) return {'login': True, 'token': hash, 'id': user.id, 'name': user.name} # Delete existing token # LoginToken.where('admin_user_id', user.id).delete() # hash = secrets.token_urlsafe() # login_token = LoginToken() # login_token.admin_user_id = user.id # login_token.token = hash # login_token.save() # return {'login': True, 'token': hash, 'id': user.id, 'name': user.name} else: return {'login': False} def destroy(self, request: Request): login_id = request.input('login_id') # LoginToken.where('admin_user_id', login_id).delete() LoginToken().logout(int(login_id)) return {}

[ "[email protected]" ]

[email protected]

25b3e881e120ecfab45a93c2d78f861cb64a3cc0

be1d3bbe87e42b3cc41238697129fc701380c43c

/web_speller/backend/web_speller/blinks/migrations/0001_initial.py

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[]

no_license

Borda/BCI-speller

051a6bd2a03f9be3e795f628decea39166946cbb

bf80f6c99f4258448199040d81d21f10ba1fd09d

refs/heads/master

2020-03-21T09:31:28.683073

2018-06-25T19:39:00

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6

0

null

UTF-8

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false

506

py

# Generated by Django 2.0.5 on 2018-06-23 20:20 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='BCIDevice', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('device_id', models.CharField(max_length=50, unique=True)), ], ), ]

[ "[email protected]" ]

[email protected]

b594bc5ed8b10f098540111dac731858955d269e

1d5b2b72d322dd154a8efb547290ad5abb1fd098

/work_dir/py_rpc/test1/client.py

cd739de1ff7000803d3cdcf24557c405ba6060ac

[]

no_license

hxzwd/drafts

6b593b50cae309c02495a8aff28719f7b636962d

478f4a4c399ab0c7c3f8f6e22d13131488716e4d

refs/heads/master

2020-04-28T01:42:58.998610

2019-05-05T17:49:48

174,868,171

0

null

UTF-8

Python

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128

py

import rpyc host_addr = "localhost" port = 18812 c = rpyc.connect(host_addr, port) c.root.func_test("TEST MESSAGE! HELLO")

[ "=" ]

=

d0340512030ca2327070536ffecf2d04a3c898bf

3c000380cbb7e8deb6abf9c6f3e29e8e89784830

/venv/Lib/site-packages/cobra/modelimpl/qos/class.py

b2ba681e647deb4419d81561ae32ce1cc0831a60

[]

no_license

bkhoward/aciDOM

91b0406f00da7aac413a81c8db2129b4bfc5497b

f2674456ecb19cf7299ef0c5a0887560b8b315d0

refs/heads/master

2023-03-27T23:37:02.836904

2021-03-26T22:07:54

351,855,399

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null

UTF-8

Python

false

8,833

py

# coding=UTF-8 # ********************************************************************** # Copyright (c) 2013-2020 Cisco Systems, Inc. All rights reserved # written by zen warriors, do not modify! # ********************************************************************** from cobra.mit.meta import ClassMeta from cobra.mit.meta import StatsClassMeta from cobra.mit.meta import CounterMeta from cobra.mit.meta import PropMeta from cobra.mit.meta import Category from cobra.mit.meta import SourceRelationMeta from cobra.mit.meta import NamedSourceRelationMeta from cobra.mit.meta import TargetRelationMeta from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory from cobra.model.category import MoCategory, PropCategory, CounterCategory from cobra.mit.mo import Mo # ################################################## class Class(Mo): """ The QoS classification traffic descriptor and specifications are used to categorize a packet within a specific group and making the packet accessible for QoS handling in the network. """ meta = ClassMeta("cobra.model.qos.Class") meta.moClassName = "qosClass" meta.rnFormat = "class-%(prio)s" meta.category = MoCategory.REGULAR meta.label = "QOS Class Policy" meta.writeAccessMask = 0x100100000000001 meta.readAccessMask = 0x100100000000001 meta.isDomainable = False meta.isReadOnly = False meta.isConfigurable = True meta.isDeletable = False meta.isContextRoot = False meta.childClasses.add("cobra.model.qos.Cong") meta.childClasses.add("cobra.model.tag.Tag") meta.childClasses.add("cobra.model.qos.RtResQoSPol") meta.childClasses.add("cobra.model.aaa.RbacAnnotation") meta.childClasses.add("cobra.model.fault.Delegate") meta.childClasses.add("cobra.model.qos.Sched") meta.childClasses.add("cobra.model.qos.Buffer") meta.childClasses.add("cobra.model.tag.Annotation") meta.childClasses.add("cobra.model.qos.Queue") meta.childClasses.add("cobra.model.qos.PfcPol") meta.childNamesAndRnPrefix.append(("cobra.model.tag.Annotation", "annotationKey-")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.RtResQoSPol", "rtresQoSPol")) meta.childNamesAndRnPrefix.append(("cobra.model.aaa.RbacAnnotation", "rbacDom-")) meta.childNamesAndRnPrefix.append(("cobra.model.tag.Tag", "tagKey-")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.PfcPol", "pfcpol-")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.Buffer", "buffer")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.Sched", "sched")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.Queue", "queue")) meta.childNamesAndRnPrefix.append(("cobra.model.qos.Cong", "cong")) meta.childNamesAndRnPrefix.append(("cobra.model.fault.Delegate", "fd-")) meta.parentClasses.add("cobra.model.qos.InstPol") meta.superClasses.add("cobra.model.naming.NamedObject") meta.superClasses.add("cobra.model.pol.Obj") meta.superClasses.add("cobra.model.pol.Def") meta.rnPrefixes = [ ('class-', True), ] prop = PropMeta("str", "admin", "admin", 261, PropCategory.REGULAR) prop.label = "Admin State" prop.isConfig = True prop.isAdmin = True prop.defaultValue = 1 prop.defaultValueStr = "enabled" prop._addConstant("disabled", "disabled", 2) prop._addConstant("enabled", "enabled", 1) meta.props.add("admin", prop) prop = PropMeta("str", "annotation", "annotation", 37277, PropCategory.REGULAR) prop.label = "Annotation. Suggested format orchestrator:value" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 128)] prop.regex = ['[a-zA-Z0-9_.:-]+'] meta.props.add("annotation", prop) prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("deleteAll", "deleteall", 16384) prop._addConstant("deleteNonPresent", "deletenonpresent", 8192) prop._addConstant("ignore", "ignore", 4096) meta.props.add("childAction", prop) prop = PropMeta("str", "descr", "descr", 5579, PropCategory.REGULAR) prop.label = "Description" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 128)] prop.regex = ['[a-zA-Z0-9\\!#$%()*,-./:;@ _{|}~?&+]+'] meta.props.add("descr", prop) prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN) prop.label = "None" prop.isDn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("dn", prop) prop = PropMeta("str", "extMngdBy", "extMngdBy", 39416, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "undefined" prop._addConstant("msc", "msc", 1) prop._addConstant("undefined", "undefined", 0) meta.props.add("extMngdBy", prop) prop = PropMeta("str", "lcOwn", "lcOwn", 9, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "local" prop._addConstant("implicit", "implicit", 4) prop._addConstant("local", "local", 0) prop._addConstant("policy", "policy", 1) prop._addConstant("replica", "replica", 2) prop._addConstant("resolveOnBehalf", "resolvedonbehalf", 3) meta.props.add("lcOwn", prop) prop = PropMeta("str", "modTs", "modTs", 7, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "never" prop._addConstant("never", "never", 0) meta.props.add("modTs", prop) prop = PropMeta("str", "mtu", "mtu", 262, PropCategory.REGULAR) prop.label = "MTU" prop.isConfig = True prop.isAdmin = True prop.range = [(1500, 9216)] prop.defaultValue = 9216 prop.defaultValueStr = "9216" meta.props.add("mtu", prop) prop = PropMeta("str", "name", "name", 4991, PropCategory.REGULAR) prop.label = "Name" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 64)] prop.regex = ['[a-zA-Z0-9_.:-]+'] meta.props.add("name", prop) prop = PropMeta("str", "nameAlias", "nameAlias", 28417, PropCategory.REGULAR) prop.label = "Name alias" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 63)] prop.regex = ['[a-zA-Z0-9_.-]+'] meta.props.add("nameAlias", prop) prop = PropMeta("str", "ownerKey", "ownerKey", 15230, PropCategory.REGULAR) prop.label = "None" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 128)] prop.regex = ['[a-zA-Z0-9\\!#$%()*,-./:;@ _{|}~?&+]+'] meta.props.add("ownerKey", prop) prop = PropMeta("str", "ownerTag", "ownerTag", 15231, PropCategory.REGULAR) prop.label = "None" prop.isConfig = True prop.isAdmin = True prop.range = [(0, 64)] prop.regex = ['[a-zA-Z0-9\\!#$%()*,-./:;@ _{|}~?&+]+'] meta.props.add("ownerTag", prop) prop = PropMeta("str", "prio", "prio", 263, PropCategory.REGULAR) prop.label = "None" prop.isConfig = True prop.isAdmin = True prop.isCreateOnly = True prop.isNaming = True prop.range = [(0, 9)] prop.defaultValue = 0 prop.defaultValueStr = "unspecified" prop._addConstant("level1", "level1", 3) prop._addConstant("level2", "level2", 2) prop._addConstant("level3", "level3-(default)", 1) prop._addConstant("level4", "level4", 9) prop._addConstant("level5", "level5", 8) prop._addConstant("level6", "level6", 7) prop._addConstant("unspecified", "unspecified", 0) meta.props.add("prio", prop) prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN) prop.label = "None" prop.isRn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("rn", prop) prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("created", "created", 2) prop._addConstant("deleted", "deleted", 8) prop._addConstant("modified", "modified", 4) meta.props.add("status", prop) prop = PropMeta("str", "uid", "uid", 8, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True meta.props.add("uid", prop) meta.namingProps.append(getattr(meta.props, "prio")) # Deployment Meta meta.deploymentQuery = True meta.deploymentType = "Ancestor" def __init__(self, parentMoOrDn, prio, markDirty=True, **creationProps): namingVals = [prio] Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps) # End of package file # ##################################################

[ "[email protected]" ]

[email protected]

929ef551e4a4ed39cde8a606b1b2829d341e61c9

942f0b081d2271978ffe20fbbfa8d687b57e5c02

/daily_coding_challenges/challenges/mapping_of_digits.py

53d0d8d458ffa10f31cc7f656983e1ff6e8da511

[]

no_license

simtb/coding-puzzles

99762322606bb505d82924d4d5843db1c04aafbd

9e1d53e35b2117240eb357d7930cdb8cfd891c8e

refs/heads/master

2021-04-12T15:46:40.181048

2021-02-28T23:47:36

249,089,264

0

null

UTF-8

Python

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549

py

""" This problem was asked by Yelp. Given a mapping of digits to letters (as in a phone number), and a digit string, return all possible letters the number could represent. You can assume each valid number in the mapping is a single digit. For example if {“2”: [“a”, “b”, “c”], 3: [“d”, “e”, “f”], …} then “23” should return [“ad”, “ae”, “af”, “bd”, “be”, “bf”, “cd”, “ce”, “cf"]. """ from typing import List def solution(map_of_digits: dict, digit: str) -> List[str]: pass

[ "[email protected]" ]

[email protected]

27eda92427ea2fac869b971a6c59e28db69c8522

42fdf741bf64ea2e63d1546bb08356286f994505

/test_00_vd2ota/rasp30_gen7.py

a401fa45a8e426a8acd4cd76f7a914f9ea38d766

[]

no_license

skim819/RASP_Workspace_sihwan

7e3cd403dc3965b8306ec203007490e3ea911e3b

0799e146586595577c8efa05c647b8cb92b962f4

refs/heads/master

2020-12-24T05:22:25.775823

2017-04-01T22:15:18

41,511,563

1

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1,184

py

self.dev_types =['fgota']*2 + ['ota_buf']*1 + ['ota']*1 + ['cap']*4+ ['nfet']*2 + ['pfet']*2 + ['tgate']*4 + ['mux4_1']*1 +['nmirror']*2+['ladder_blk']*1+ ['c4_blk']*1+['Nagating_blk']*1+['speech']*1+['gnd_out']*1+['vdd_out']*1+['in2in_x1']*1+['in2in_x6']*1+['volt_div']*1+['volt_div_fgota']*1+['integrator']*1+['integrator_nmirror']*1+['INFneuron']*1+['lpf']*1+['nfet_i2v']*1+['pfet_i2v']*1+['nmirror_w_bias']*1+['fgswc_nmirror_w_bias']*1+['i2v_pfet_gatefgota']*1+['mismatch_meas']*1+['mmap_local_swc']*1+['ramp_fe']*1+['sigma_delta_fe']*1+['hhneuron']*1+['ladder_filter']*1+ ['h_rect']*1+['dendiff']*1+['Algo_ADC']*1+['TIA_blk']*1+['ichar_nfet']*1+['bias_gen']*1+['vmm_senseamp1']*1+['vmm_senseamp2']*1+['tgate_so']*1+['vmm4x4_SR']*1+['vmm8x4_SR']*1+['SR4']*1+['vmm4x4_SR2']*1+['vmm4x4']*1+['sftreg']*1+['DAC_sftreg']*1 +['sftreg2']*1+['sftreg3']*1+['sftreg4']*1+['vmm8x4']*1+['vmm8inx8in']*1+['vmm8x4_in']*1+['vmm12x1']*1+['vmm12x1_wowta']*1+['Adaptive_receptor']*1+['ota_vmm']*1 +['nmirror_vmm']*2+['inv_mcab']*1+['Hyst_diff']*1+['Max_detect']*1+['Min_detect']*1+['wta_w_bias']*1+['hhn']*1+['fgswitch']*1+['common_drain']*1+['common_drain_nfet']*1+['hhn_debug']*1+['vd_2ota']*1

[ "ubuntu@ubuntu-VirtualBox.(none)" ]

ubuntu@ubuntu-VirtualBox.(none)

37248cd18c25736ef9d16caf5efea05432caf0ab

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/venv/bin/pip

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[]

no_license

BillSam/M_shop

401228536b57ff98d44f26b24fbd7b46122e4be5

ecb0fb686957193f749413ef4f3b87c4ea046e7d

refs/heads/main

2023-03-23T12:05:55.313453

2021-02-25T11:39:35

342,137,767

0

null

UTF-8

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256

#!/home/work/Documents/pythhon/M_shop/venv/bin/python # -*- coding: utf-8 -*- import re import sys from pip._internal.cli.main import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "[email protected]" ]

[email protected]

63f8277e6c153482a0737d7d7fc2be4065b35437

4926667354fa1f5c8a93336c4d6e2b9f6630836e

/1318.py

39050eeca9d4be13c770e32b2ee0404761fb2afa

[]

no_license

nascarsayan/lintcode

343b3f6e7071479f0299dd1dd1d8068cbd7a7d9e

4da24b9f5f182964a1bdf4beaa8afc17eb7a70f4

refs/heads/master

2021-07-13T12:31:45.883179

2020-07-20T02:27:53

185,825,565

0

null

UTF-8

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false

715

py

class Solution: """ @param nums: the given array @param k: the given k @param t: the given t @return: whether there are two distinct indices i and j in the array such that the absolute difference between nums[i] and nums[j] is at most t and the absolute difference between i and j is at most k. """ def containsNearbyAlmostDuplicate(self, nums, k, t): # Write your code here size = len(nums) bucket, wt = {}, t + 1 for i in range(size): bi = nums[i] // wt for bj in range(bi - 1, bi + 2): if bj in bucket and abs(bucket[bj] - nums[i]) <= t: return True bucket[bi] = nums[i] if i >= k: del bucket[nums[i - k] // wt] return False

[ "[email protected]" ]

[email protected]

ded03050bd48a80ff92b49a40d0a4295a2803b38

bb2add9ca1fdd3e33b2c28d494d497b62af121ae

/setup.py

e2be87663ddf37084b2e742b0b56e5633964c225

[ "MIT" ]

permissive

wegamekinglc/simpleutils

4a48b0eae783ad74e3c16454ea04fff88a6b7796

1e3c89f72347b94538267c6f66f87c2cabdb18dd

refs/heads/master

2021-07-26T01:09:27.582528

2020-03-17T02:19:28

90,547,150

0

1

null

2017-07-22T19:21:26

2017-05-07T16:44:07

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UTF-8

Python

false

357

py

import io from setuptools import setup from setuptools import find_packages setup( name='simpleutils', version='0.2.5', packages=find_packages(), url='', license='MIT', author='wegamekinglc', author_email='[email protected]', install_requires=io.open("requirements.txt", encoding='utf8').read(), description='' )

[ "[email protected]" ]

[email protected]

4c981b7947331d05e0ffc54bf6c0a5898cc085f0

7c2e677d931a8eb7d7cffc6d54713411abbe83e4

/AppBuilder9000/AppBuilder9000/ZPYLP0914/HikingApp/migrations/0003_auto_20200925_1746.py

b15a2782dcbe732ed55cad1047fa3495f381341d

[]

no_license

r3bunker/Python_Live_Project

19e367b3cf74c2279c287fcd3a8a44a27f24041a

d3e06150d7daea6326cc1a4155309d99e4ff6244

refs/heads/main

2023-06-12T23:01:50.440371

2021-06-16T20:21:03

344,883,966

1

0

null

UTF-8

Python

false

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py

# Generated by Django 2.2.5 on 2020-09-26 00:46 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('HikingApp', '0002_auto_20200923_2326'), ] operations = [ migrations.AlterField( model_name='hike_preferences', name='nick_name', field=models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to='HikingApp.create_happ_user'), ), ]

[ "[email protected]" ]

[email protected]

09fce38313a60fd7a92b0eb090a3706cabaa6808

62b7c6baaef93a603ecc4eb0c6a140e7b133b577

/data/modules/exploit/macos/stager/membrane_reverse_tcp/core/handler.py

e25ac93798adf8402e51e6d675d78b3a9bdf9870

[ "MIT" ]

permissive

sashka3076/ZetaSploit

eca5badfcb796c95aa2c8036b3814d5687a2f7b8

f5de0c10fb811f4b6f358412f6d848a7da8080fd

refs/heads/main

2023-03-03T04:43:06.137871

2021-02-05T18:37:18

336,480,949

1

0

MIT

2021-02-06T07:27:20

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#!/usr/bin/env python3 # # MIT License # # Copyright (c) 2020-2021 EntySec # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # from data.modules.exploit.macos.stager.membrane_reverse_tcp.core.terminator import terminator class handler: def __init__(self, client): self.client = client self.terminator = terminator() def sendterm(self): terminator = self.terminator.generate_terminator() self.client.send((terminator + '\x04').encode()) return terminator def send(self, buffer): if not isinstance(buffer, bytes): buffer = buffer.encode() self.client.send(buffer + '\x04'.encode()) def sendall(self, buffer): terminator = self.sendterm() if not isinstance(buffer, bytes): buffer = buffer.encode() self.client.send(buffer + '\x04'.encode()) return terminator def recvstr(self, char='\n'): result = self.recvall(char) return result def recvall(self, terminator): result = b'' while 1: data = self.client.recv(1024) if terminator.encode() in data: data = data.replace(terminator.encode(), b'') result += data break else: result += data return result def recvfile(self, terminator, input_file): output_file = open(input_file, "wb") while 1: data = self.client.recv(1024) if terminator.encode() in data: data = data.replace(terminator.encode(), b'') output_file.write(data) break else: output_file.write(data) output_file.close()

[ "[email protected]" ]

[email protected]

4a36aec0bb29c9ee7b1376c66f7e37711c95c169

a71fbf421c43fcb34fe7c8000eb807677821683c

/keras/keras06_RMSE.py

7d109b56293501423f78ec268a42c551f20160cf

[]

no_license

leekyunghun/bit_seoul

ccd96dca3774f259e04b8388e134d6183b974268

b76a3d5f83b77f5345d61cf3baa68aaefc25cd2a

refs/heads/master

2023-02-06T08:12:17.768076

2020-12-22T13:35:19

311,286,916

0

null

UTF-8

Python

false

1,854

py

import numpy as np #1. 데이터 # 선형회귀 예제 x_train = np.array([1,2,3,4,5,6,7,8,9,10]) y_train = np.array([1,2,3,4,5,6,7,8,9,10]) x_test = np.array([11,12,13,14,15]) y_test = np.array([11,12,13,14,15]) x_pred = np.array([16,17,18]) from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense #2.모델 구성 model = Sequential() # model이 Sequential이라고 선언 model.add(Dense(32, input_dim = 1)) # input_dim = 1 => input이 1차원 #model.add(Dense(32, input_dim = 1)) 값이 잘 나옴 model.add(Dense(16)) #model.add(Dense(16)) model.add(Dense(8)) #model.add(Dense(8)) model.add(Dense(1)) #model.add(Dense(1)) #3.컴파일, 훈련 model.compile(loss='mse', optimizer='adam', metrics=['mae']) # metrics = 평가방식 (훈련중에 연산한 내용을 보여주는역할) model.fit(x_train, y_train, epochs = 100, batch_size = 1) # model.fit => 모델을 훈련시킴 # model.fit(x_train, y_train, epochs = 100) # model.fit => 모델을 훈련시킴 #4.평가, 예측 # loss, acc = model.evaluate(x_test, y_test, batch_size = 1) loss = model.evaluate(x_test, y_test) # evaluate의 디폴트는 loss값 metrics에 추가한 값들이 evaluate 출력에 포함 print("loss : ", loss) # print("acc : ", acc) y_predict = model.predict(x_test) # 예측값 확인 print("결과물: \n :", y_predict) from sklearn.metrics import mean_squared_error def RMSE(y_test, y_predict): return np.sqrt(mean_squared_error(y_test, y_predict)) print("RMSE: ", RMSE(y_test, y_predict))

[ "[email protected]" ]

[email protected]

3f8c227967ee0fd61a7c3e634b1b36f2412658e8

54f352a242a8ad6ff5516703e91da61e08d9a9e6

/Source Codes/AtCoder/arc013/A/4657608.py

a1c4dd03b11eae7bc30d1cf841829c266962862f

[]

no_license

Kawser-nerd/CLCDSA

5cbd8a4c3f65173e4e8e0d7ed845574c4770c3eb

aee32551795763b54acb26856ab239370cac4e75

refs/heads/master

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N, M, L = map(int, input().split()) P, Q, R = map(int, input().split()) Res = max((N//P)*(M//Q)*(L//R), (N//Q)*(M//R)*(L//P), (N//R)*(M//P)*(L//Q)) Res2 = max((N//Q)*(M//P)*(L//R),(N//R)*(M//Q)*(L//P), (N//P)*(M//R)*(L//Q)) print(max(Res, Res2))

[ "[email protected]" ]

[email protected]

2d3e682e938895f55504dace0bc7ead4ed580d59

e13bccceb4c2fefbf8000f9b34195ab434cf1656

/devel/lib/python2.7/dist-packages/test_rosmaster/__init__.py

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no_license

QuiN-cy/vacuum-en-band

ab59b718f289ad4e8a1f29e96724250b00bd894d

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refs/heads/master

2023-06-01T12:13:38.664849

2021-06-11T15:42:42

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UTF-8

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false

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py

/home/student/rosws/devel/.private/test_rosmaster/lib/python2.7/dist-packages/test_rosmaster/__init__.py

[ "[email protected]" ]

[email protected]

3e50ccd03eaa5a52efbe94b7be2d3d9b816f48b6

7889f7f0532db6a7f81e6f8630e399c90438b2b9

/3.4.3/_downloads/83afb11a0261474b783405dd2737c8b4/marker_path.py

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[]

no_license

matplotlib/matplotlib.github.com

ef5d23a5bf77cb5af675f1a8273d641e410b2560

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refs/heads/main

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2023-08-30T15:59:50

2011-02-19T03:27:35

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UTF-8

Python

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979

py

""" =========== Marker Path =========== Using a `~.path.Path` as marker for a `~.axes.Axes.plot`. """ import matplotlib.pyplot as plt import matplotlib.path as mpath import numpy as np star = mpath.Path.unit_regular_star(6) circle = mpath.Path.unit_circle() # concatenate the circle with an internal cutout of the star verts = np.concatenate([circle.vertices, star.vertices[::-1, ...]]) codes = np.concatenate([circle.codes, star.codes]) cut_star = mpath.Path(verts, codes) plt.plot(np.arange(10)**2, '--r', marker=cut_star, markersize=15) plt.show() ############################################################################# # # .. admonition:: References # # The use of the following functions, methods, classes and modules is shown # in this example: # # - `matplotlib.path` # - `matplotlib.path.Path` # - `matplotlib.path.Path.unit_regular_star` # - `matplotlib.path.Path.unit_circle` # - `matplotlib.axes.Axes.plot` / `matplotlib.pyplot.plot`

[ "[email protected]" ]

[email protected]

a0b9d2e0e3821e46cb8e9cf4d8cc75a86df1e90d

b9cd1b9758e58f00335900fd120e1d47c23600ce

/tool/fastq_splitter.py

29e257c5b5b800ac68560c31136a434849f7e847

[ "Apache-2.0" ]

permissive

Multiscale-Genomics/mg-process-fastq

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refs/heads/master

2020-04-12T06:46:01.100270

2018-11-19T16:05:03

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2018-11-16T16:54:54

2016-07-27T15:29:25

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""" .. See the NOTICE file distributed with this work for additional information regarding copyright ownership. 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 from utils import logger try: if hasattr(sys, '_run_from_cmdl') is True: raise ImportError from pycompss.api.parameter import FILE_IN, FILE_OUT, IN, OUT from pycompss.api.task import task # from pycompss.api.api import compss_wait_on except ImportError: logger.warn("[Warning] Cannot import \"pycompss\" API packages.") logger.warn(" Using mock decorators.") from utils.dummy_pycompss import FILE_IN, FILE_OUT, IN, OUT # pylint: disable=ungrouped-imports from utils.dummy_pycompss import task # pylint: disable=ungrouped-imports # from utils.dummy_pycompss import compss_wait_on # pylint: disable=ungrouped-imports from basic_modules.tool import Tool from basic_modules.metadata import Metadata from tool.fastqreader import fastqreader from tool.common import common # ------------------------------------------------------------------------------ class fastq_splitter(Tool): # pylint: disable=invalid-name """ Script for splitting up FASTQ files into manageable chunks """ def __init__(self, configuration=None): """ Initialise the tool with its configuration. Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which are specific to each Tool. """ logger.info("FASTQ Splitter") Tool.__init__(self) if configuration is None: configuration = {} self.configuration.update(configuration) @task( in_file1=FILE_IN, tag=IN, out_file=FILE_OUT, files_out=OUT, returns=list) def single_splitter(self, in_file1, out_file, tag='tmp'): # pylint: disable=no-self-use """ Function to divide the FastQ files into separate sub files of 1000000 sequences so that the aligner can run in parallel. Parameters ---------- in_file1 : str Location of first FASTQ file tag : str DEFAULT = tmp Tag used to identify the files. Useful if this is getting run manually on a single machine multiple times to prevent collisions of file names Returns ------- Returns: Returns a list of the files that have been generated. Each sub list containing the two paired end files for that subset. paired_files : list List of lists of pair end files. Each sub list containing the two paired end files for that subset. """ fqr = fastqreader() fqr.openFastQ(in_file1) file_loc_1_tmp = fqr.createOutputFiles(tag) fastq_chunk_size = 1000000 if "fastq_chunk_size" in self.configuration: fastq_chunk_size = self.configuration["fastq_chunk_size"] record1 = fqr.next(1) count_r3 = 0 tmp_dir = os.path.split(file_loc_1_tmp)[0] files_out = [[os.path.split(file_loc_1_tmp)[1]]] while fqr.eof(1) is False: fqr.writeOutput(record1, 1) record1 = fqr.next(1) count_r3 += 1 if count_r3 % fastq_chunk_size == 0: file_loc_1_new = fqr.incrementOutputFiles() files_out.append([os.path.split(file_loc_1_new)[1]]) fqr.closeFastQ() fqr.closeOutputFiles() untar_idx = True if "no-untar" in self.configuration and self.configuration["no-untar"] is True: untar_idx = False if untar_idx is True: if os.path.isfile(out_file): os.remove(out_file) output_file_pregz = out_file.replace('.tar.gz', '.tar') common.tar_folder(tmp_dir, output_file_pregz) common.zip_file(output_file_pregz, 2) return files_out @task( in_file1=FILE_IN, in_file2=FILE_IN, tag=IN, out_file=FILE_OUT, files_out=OUT, returns=list) def paired_splitter(self, in_file1, in_file2, out_file, tag='tmp'): # pylint: disable=no-self-use,too-many-locals,too-many-statements """ Function to divide the paired-end FastQ files into separte sub files of 1000000 sequences so that the aligner can run in parallel. Parameters ---------- in_file1 : str Location of first paired end FASTQ file in_file2 : str Location of second paired end FASTQ file tag : str DEFAULT = tmp Tag used to identify the files. Useful if this is getting run manually on a single machine multiple times to prevent collisions of file names Returns ------- Returns: Returns a list of lists of the files that have been generated. Each sub list containing the two paired end files for that subset. paired_files : list List of lists of pair end files. Each sub list containing the two paired end files for that subset. """ fqr = fastqreader() fqr.openFastQ(in_file1, in_file2) file_loc_1_tmp, file_loc_2_tmp = fqr.createOutputFiles(tag) fastq_chunk_size = 1000000 if "fastq_chunk_size" in self.configuration: fastq_chunk_size = self.configuration["fastq_chunk_size"] record1 = fqr.next(1) record2 = fqr.next(2) count_r1 = 0 count_r2 = 0 count_r3 = 0 tmp_dir = os.path.split(file_loc_1_tmp)[0] files_out = [[ os.path.split(file_loc_1_tmp)[1], os.path.split(file_loc_2_tmp)[1] ]] while fqr.eof(1) is False and fqr.eof(2) is False: r1_id = record1["id"].split(" ") r2_id = record2["id"].split(" ") if r1_id[0] == r2_id[0]: fqr.writeOutput(record1, 1) fqr.writeOutput(record2, 2) record1 = fqr.next(1) record2 = fqr.next(2) count_r1 += 1 count_r2 += 1 count_r3 += 1 elif r1_id[0] < r2_id[0]: record1 = fqr.next(1) count_r1 += 1 else: record2 = fqr.next(2) count_r2 += 1 if count_r3 % fastq_chunk_size == 0: file_loc_1_new, file_loc_2_new = fqr.incrementOutputFiles() files_out.append([ os.path.split(file_loc_1_new)[1], os.path.split(file_loc_2_new)[1] ]) fqr.closeFastQ() fqr.closeOutputFiles() untar_idx = True if "no-untar" in self.configuration and self.configuration["no-untar"] is True: untar_idx = False if untar_idx is True: if os.path.isfile(out_file): os.remove(out_file) output_file_pregz = out_file.replace('.tar.gz', '.tar') common.tar_folder(tmp_dir, output_file_pregz) common.zip_file(output_file_pregz, 2) return files_out def run(self, input_files, input_metadata, output_files): """ The main function to run the splitting of FASTQ files (single or paired) so that they can aligned in a distributed manner Parameters ---------- input_files : dict List of input fastq file locations metadata : dict output_files : dict Returns ------- output_file : str Location of compressed (.tar.gz) of the split FASTQ files output_names : list List of file names in the compressed file """ sources = [input_files["fastq1"]] if "fastq2" in input_files: sources.append(input_files["fastq2"]) self.paired_splitter( input_files["fastq1"], input_files["fastq2"], output_files["output"] ) else: self.single_splitter( input_files["fastq1"], output_files["output"], ) # results = compss_wait_on(results) fastq_tar_meta = Metadata( data_type=input_metadata["fastq1"].data_type, file_type="TAR", file_path=output_files["output"], sources=sources, taxon_id=input_metadata["fastq1"].taxon_id, meta_data={ "tool": "fastq_splitter" } ) return ( {"output": output_files["output"]}, {"output": fastq_tar_meta} ) # ------------------------------------------------------------------------------

[ "[email protected]" ]

[email protected]

1c7c39467f29261840f0dd971bee8ef850b22534

b5eaeded2af4417603d6592f29c81c2426397153

/catatan/migrations/0002_auto_20201111_0927.py

cb4367a8a60122829cf0c2231a5d667dc6c68e2d

[]

no_license

giko99/sim-labsos

9871059115be511882c96be10b6baaa9874a86ae

1711607aa3cb087c1ec5efc2b337841eb0a1f33d

refs/heads/main

2023-01-10T06:38:17.209459

2020-11-12T10:04:40

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# Generated by Django 2.2 on 2020-11-11 02:27 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('catatan', '0001_initial'), ] operations = [ migrations.RenameField( model_name='catatan', old_name='selang', new_name='waktu_kegiatan', ), ]

[ "[email protected]" ]

[email protected]

31170f4214bbbc086ecde9b382a34789691bc3a7

78230ff4256b5cc7b99a5139968b41a3495f173e

/test/test_retryz.py

ac54a00fe91e212239e8e2edc9f5c00633a7bb80

[ "Apache-2.0" ]

permissive

jealous/retryz

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refs/heads/master

2023-06-01T05:49:31.566554

2017-05-21T14:48:45

2017-05-21T15:14:26

48,358,949

1

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2017-05-21T15:17:54

2015-12-21T08:03:37

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UTF-8

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py

# coding=utf-8 # Copyright (c) 2015 EMC Corporation. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import functools from unittest import TestCase from hamcrest import assert_that, instance_of, equal_to, raises, \ greater_than, less_than, contains_string from retryz import retry, RetryTimeoutError def _return_callback(ret): return 4 + ret < 7 def func_wait_callback(tried): if tried <= 6: ret = 0.01 else: ret = 1000 return ret class AnotherDemoClass(object): def __init__(self): self.a = 0 @classmethod def class_wait_callback(cls, tried): if tried <= 3: ret = 0.01 else: ret = 1000 return ret @staticmethod def static_wait_callback(tried): if tried <= 4: ret = 0.01 else: ret = 1000 return ret def other_method_wait_callback(self, tried): self.a += 1 if tried <= 2: ret = 0.01 else: ret = 1000 return ret class RetryDemo(object): def __init__(self): self._call_count = 0 @property def call_count(self): return self._call_count @retry(on_error=ValueError) def on_error(self): self._call_count += 1 if self.call_count <= 3: raise ValueError() else: return self.call_count @retry(on_error=lambda e: isinstance(e, (ValueError, TypeError))) def on_errors(self): self._call_count += 1 if self.call_count == 1: raise ValueError() elif self.call_count == 2: raise TypeError() else: raise AttributeError() @retry(on_error=lambda e: not isinstance(e, TypeError)) def unless_error(self): self._call_count += 1 if self.call_count <= 2: raise ValueError() else: raise TypeError() @retry(on_error=lambda e: not isinstance(e, (TypeError, AttributeError))) def unless_errors(self): self._call_count += 1 if self.call_count == 1: raise ValueError() elif self.call_count == 2: raise TypeError() else: raise AttributeError() def _error_callback(self, ex): assert_that(ex, instance_of(TypeError)) return self.call_count != 4 @retry(on_error=_error_callback) def error_callback(self): self._call_count += 1 raise TypeError() @retry(timeout=0.05, wait=lambda x: 0 if x < 5 else 100) def timeout(self): self._call_count += 1 return self.call_count @retry(timeout=lambda: 0.05, wait=lambda x: 0 if x < 6 else 100) def timeout_callback(self): self._call_count += 1 return self.call_count @retry(on_return=True) def on_return(self): self._call_count += 1 if self.call_count < 3: ret = True else: ret = False return ret @retry(on_return=lambda x: x in (1, 2, 3, 4, 5)) def on_returns(self): self._call_count += 1 return self.call_count @retry(on_return=lambda x: x != 4) def unless_return(self): self._call_count += 1 return self.call_count @retry(on_return=lambda x: x not in [3, 4]) def unless_returns(self): self._call_count += 1 return self.call_count @retry(on_return=_return_callback) def return_callback(self): self._call_count += 1 return self.call_count @retry(on_return=False, wait=0.01, limit=10) def practical_on_return(self): self._call_count += 1 return self._call_count == 6 @retry(on_return=False, wait=0.01, limit=10) def on_return_raise_error(self): self._call_count += 1 if self._call_count == 3: raise ValueError('error out') return self._call_count == 6 @retry(limit=3) def limit(self): self._call_count += 1 return self.call_count @retry(wait=0.1, timeout=0.3) def wait(self): self._call_count += 1 return self.call_count def _wait_callback(self, tried): if tried <= 2 or self.call_count <= 5: ret = 0.01 else: ret = 1000 return ret @retry(wait=_wait_callback, timeout=0.1) def wait_callback(self): self._call_count += 1 return self.call_count @retry(wait=AnotherDemoClass.class_wait_callback, timeout=0.1) def class_wait_callback(self): self._call_count += 1 return self.call_count @retry(wait=AnotherDemoClass.static_wait_callback, timeout=0.1) def static_wait_callback(self): self._call_count += 1 return self.call_count @retry(wait=func_wait_callback, timeout=0.1) def func_wait_callback(self): self._call_count += 1 return self.call_count @retry(wait=AnotherDemoClass().other_method_wait_callback, timeout=0.1) def other_method_wait_callback(self): self._call_count += 1 return self.call_count def _on_retry(self): self._call_count += 1 @retry(on_retry=_on_retry, limit=3) def on_retry(self): """ doc string for on retry :return: call count """ self._call_count += 1 return self.call_count @retry(limit=lambda: 3) def limit_callback(self): self._call_count += 1 return self.call_count @retry(on_error=ValueError) def unexpected_error(self): raise AttributeError('unexpected attribute error.') @retry(on_error=ValueError, wait=15, timeout=60 * 60 * 24 * 7) def same_function(self): self._call_count += 1 return self._call_count def call(self): self._call_count += 1 return self._call_count class RetryTest(TestCase): def test_on_error(self): demo = RetryDemo() demo.on_error() assert_that(demo.call_count, equal_to(4)) def test_on_errors_and_limit(self): demo = RetryDemo() assert_that(demo.on_errors, raises(AttributeError)) assert_that(demo.call_count, equal_to(3)) def test_unless_error(self): demo = RetryDemo() assert_that(demo.unless_error, raises(TypeError)) assert_that(demo.call_count, equal_to(3)) def test_unless_errors(self): demo = RetryDemo() assert_that(demo.unless_errors, raises(TypeError)) assert_that(demo.call_count, equal_to(2)) def test_error_callback(self): demo = RetryDemo() assert_that(demo.error_callback, raises(TypeError)) assert_that(demo.call_count, equal_to(4)) def test_timeout(self): demo = RetryDemo() assert_that(demo.timeout, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(5)) def test_timeout_callback(self): demo = RetryDemo() assert_that(demo.timeout_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(6)) def test_on_return(self): demo = RetryDemo() assert_that(demo.on_return(), equal_to(False)) assert_that(demo.call_count, equal_to(3)) def test_on_returns(self): demo = RetryDemo() assert_that(demo.on_returns(), equal_to(6)) def test_unless_return(self): demo = RetryDemo() assert_that(demo.unless_return(), equal_to(4)) def test_unless_returns(self): demo = RetryDemo() assert_that(demo.unless_returns(), equal_to(3)) def test_return_callback(self): demo = RetryDemo() assert_that(demo.return_callback(), equal_to(3)) def test_limit(self): demo = RetryDemo() assert_that(demo.limit(), equal_to(3)) def test_wait(self): demo = RetryDemo() assert_that(demo.wait, raises(RetryTimeoutError)) assert_that(demo.call_count, greater_than(2)) assert_that(demo.call_count, less_than(6)) def test_wait_callback(self): demo = RetryDemo() assert_that(demo.wait_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(6)) def test_func_wait_callback(self): demo = RetryDemo() assert_that(demo.func_wait_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(7)) def test_class_wait_callback(self): demo = RetryDemo() assert_that(demo.class_wait_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(4)) def test_static_wait_callback(self): demo = RetryDemo() assert_that(demo.static_wait_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(5)) def test_other_method_wait_callback(self): demo = RetryDemo() assert_that(demo.other_method_wait_callback, raises(RetryTimeoutError)) assert_that(demo.call_count, equal_to(3)) def test_on_retry(self): demo = RetryDemo() assert_that(demo.on_retry(), equal_to(5)) def test_limit_callback(self): demo = RetryDemo() assert_that(demo.limit_callback(), equal_to(3)) def test_unexpected_error(self): demo = RetryDemo() assert_that(demo.unexpected_error, raises(AttributeError, 'unexpected')) def test_functional_limit(self): demo = RetryDemo() assert_that(retry(demo.call, limit=3)(), equal_to(3)) def test_functional_on_return(self): demo = RetryDemo() assert_that(retry(demo.call, on_return=lambda x: x < 5)(), equal_to(5)) def test_partial_function_on_return(self): def lt(x, y): return x < y f = functools.partial(lt, y=5) demo = RetryDemo() assert_that(retry(demo.call, on_return=f)(), equal_to(5)) def test_function_wrap(self): demo = RetryDemo() assert_that(demo.on_retry.__doc__, contains_string('doc string for on retry')) def test_same_function_first_entry(self): demo = RetryDemo() assert_that(demo.same_function(), equal_to(1)) def test_same_function_second_entry(self): demo = RetryDemo() assert_that(demo.same_function(), equal_to(1)) def test_practical_on_return(self): demo = RetryDemo() demo.practical_on_return() assert_that(demo.call_count, equal_to(6)) def test_on_return_raise_error(self): def f(): demo = RetryDemo() demo.on_return_raise_error() assert_that(f, raises(ValueError)) def test_error_wait_type(self): def f(): @retry(wait='string') def g(): pass g() assert_that(f, raises(ValueError, 'should be a number or a callback')) def test_retry_retry_type(self): def f(): @retry(on_retry=123) def g(): pass g() assert_that(f, raises(ValueError, 'should be a function'))

[ "[email protected]" ]

[email protected]

c888771fa263c8e74bf9f393fcdbb8476f204704

36add5afc63ec09d63b8a877c29c17391938ee5c

/.history/process_tweet_20201113145341.py

c00da9bce7d529f27130fc4cb4ab2841dd6d41c6

[]

no_license

E-STAT/sentiment_api

e84eb04a9f21c7368ca20bdb97436ffea9f65f25

bd9ee0d78d9eac8b6448b96c2560611a64f7b79d

refs/heads/master

2023-01-12T13:06:14.654883

2020-11-20T11:30:22

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null

UTF-8

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py

import re REPLACE_BY_SPACE = re.compile('[/(){}\[\]\|,;&-_]') #punctuation to replace def preprocess_text(text): """ Function to preprocess text: removes links, punctuation, spaces, non-alpha words and stop_words Parameters ---------- text: str a string to be preprocessed Returns ------- text: str a preprocessed string """ self.text = text.lower() #lowercase self.text = re.sub(r"http\S+", "", text) #replace links with "" self.text = re.sub(r"\@\S+", "", text) #replace mentions with "" self.text = re.sub(r"#\S+", "", text) #replace hashtags with "" self.text = re.sub(r"won\'t", "would not", text) #deal with contractions self.text = re.sub(r"n\'t", " not", text) #deal with contractions self.text = REPLACE_BY_SPACE.sub(' ', text) #replace punctuation with space self.text = [word.strip() for word in text.split()] #strip space from words self.text = [word for word in text if len(word)>2] #removing words less than 2 characters self.text = [word for word in text if word!='amp'] #removing twitter amp self.text = ' '.join(text) return self.text test = preprocess_text("Hello, this is Ernest @OwojoriErnest. #EndSars") print(test)

[ "[email protected]" ]

[email protected]

b70eb58802e5dbe8a525a194f8c647b1713059b2

f98f4aaeca3ac841905e0cd8547bbf41944fe690

/编程语言/Python/Python编程从入门到实践/第一部分_基础知识/第11章_测试代码/11_1/test_cities.py

8a129dc96c26bbe02c29536932c7670c18d25732

[]

no_license

zhb339/book-learning

64f433b1ee1f66f3120828352df3b533be4cf9de

5273fc8d11b2d602484dbe95e55f1e931858382f

refs/heads/master

2020-03-29T10:48:22.771146

2018-11-07T13:46:53

149,823,496

0

null

UTF-8

Python

false

236

py

import unittest from city_functions import get_location class CityTest(unittest.TestCase): def test_city_country(self): location = get_location("hangzhou", "china") self.assertEqual(location, "hangzhou, china") unittest.main()

[ "[email protected]" ]

[email protected]

06c77303e95c817d8ebca414a1acfcf467f2abd7

2c6f77b281ee9c901a788b5617f26e73a3732762

/chapter7/insertionSort.py

130a3f6cf1f401844d03745fea0c27e898c779cd

[]

no_license

Boberkraft/Data-Structures-and-Algorithms-in-Python

5db8ff814f4e954aca6701fabcc70900fe7012ff

60a5ef54f9cffb4dcdd3fc494cfeeb662d570ae9

refs/heads/master

2021-01-20T06:05:29.552453

2018-10-28T19:06:55

89,841,233

2

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UTF-8

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py

from PositinalList import PositionalList def insertion_sort(l): if len(l) > 1: marker = L.first() while marker != l.last(): pivot = l.after(marker) value = pivot.element() if value > marker.element(): marker = pivot else: walk = marker while walk != l.first() and l.before(walk).element() > value: walk = l.before(walk) l.delete(pivot) l.add_before(walk, value)

[ "[email protected]" ]

[email protected]

d71b31be0ea0908049b6484535473a11033bc7ca

c11123ce1e86f8306dcc3bf5d017dbfa8bb1d515

/Easy/Pascal's Triangle.py

2d0b01d3d2e9680b1cc10cbe895915d5b9fe90ab

[]

no_license

uathena1991/Leetcode

7e606c68a51ed09e6e6a9fad327b24066e92d0c4

e807ae43a0a253deaa6c9ed1c592fa3a14a6cab8

refs/heads/master

2021-05-01T15:21:25.568729

2019-10-13T14:33:30

74,910,747

1

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UTF-8

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false

469

py

class Solution(object): def generate(self, numRows): """ :type numRows: int :rtype: List[List[int]] """ res = [[1]] if numRows == 0: return [] if numRows == 1: return [[1]] for n in range(1,numRows): res.append([1]*(n+1)) for j in range(1,n): res[n][j] = res[n-1][j] + res[n-1][j-1] return res a = Solution() print a.generate(7)

[ "[email protected]" ]

[email protected]

5ae8b4f10739b6e6002264dbdfb90ab5fb784055

5d8bbb53d3ca8d532a1d977906a0fdf2aed6d46f

/ecoke/tests/test_views.py

e5c5f9a24e15e40c94f1b298ae200f8f7687d2b1

[]

no_license

ErickMwazonga/e-Coke

da113d5cf2127b9947622008433057331c6a87f9

d72f6f2d5f6b5bb8d1a50c2fa6d22cf9a462874d

refs/heads/master

2021-01-20T07:16:00.763059

2018-03-20T12:25:43

101,509,271

0

null

UTF-8

Python

false

2,689

py

# from django.test import Client, TestCase # from django.urls import reverse # from django.contrib.auth import get_user_model # from django.utils import timezone # # from ecoke.models import Brand # # # def create_user(): # User = get_user_model() # user = User(username='john', email='[email protected]', is_active=True) # user.set_password('letmein') # user.save() # return user # # # class IndexTestCase(TestCase): # def setUp(self): # user = create_user() # # self.client = Client() # self.client.force_login(user) # # def test_correct_template_used(self): # url = reverse('ecoke:index') # res = self.client.get(url) # # self.assertTemplateUsed(res, 'ecoke/index.html') # self.assertIn('This is a e-Coke Application where you can collect data based on brands...', res.content) # # # class BrandTestCase(TestCase): # def setUp(self): # user = create_user() # # self.client = Client() # self.client.force_login(user) # # # def test_data_posted(self): # # url = reverse('ecoke:brand_create') # # data = { # # 'collector_name': 'Chepe', # # 'respondent_name': 'Chitalo', # # 'respondent_city': 'Matano Mane', # # 'favourite_drink': 'Fuze', # # 'date_of_collection': timezone.now().date() # # } # # res = self.client.post(url, data=data) # # self.assertEqual(Brand.objects.count(), 1) # # # # # # def test_data_update(self): # # data = { # # 'collector_name': 'Chepe', # # 'respondent_name': 'Chitalo', # # 'respondent_city': 'Matano Mane', # # 'favourite_drink': 'Fuze', # # 'date_of_collection': timezone.now().date() # # } # # brand = Brand.objects.create(**data) # # url = reverse('ecoke:brand_update', kwargs={'pk':brand.pk}) # # data['collector_name'] = 'Biro' # # res = self.client.post(url, data=data) # # # # self.assertEqual(Brand.objects.first().collector_name, 'Biro') # # def test_data_delete(self): # data = { # 'collector_name': 'Chepe', # 'respondent_name': 'Chitalo', # 'respondent_city': 'Matano Mane', # 'favourite_drink': 'Fuze', # 'date_of_collection': timezone.now().date() # } # brand = Brand.objects.create(**data) # self.assertEqual(Brand.objects.count(), 1) # # url = reverse('ecoke:brand_delete', kwargs={'pk':brand.pk}) # res = self.client.post(url) # # self.assertEqual(Brand.objects.count(), 0)

[ "[email protected]" ]

[email protected]

1c2b29364823e4d003628dd1a69238ac0f8c2f65

6fd26735b9dfd1d3487c1edfebf9e1e595196168

/2018/task05a.py

efc9e8f1ff974feab1583ece5da19fdb8705b276

[ "BSD-3-Clause" ]

permissive

Kwpolska/adventofcode

bc3b1224b5272aa8f3a5c4bef1d8aebe04dcc677

8e55ef7b31a63a39cc2f08b3f28e15c2e4720303

refs/heads/master

2021-01-10T16:48:38.816447

2019-12-03T20:46:07

47,507,587

5

0

null

UTF-8

Python

false

718

py

#!/usr/bin/env python3 import string with open("input/05.txt") as fh: file_data = fh.read().strip() def solve(data): while True: out = data[0] lout = data[0].lower() for c in data[1:]: lc = c.lower() if lout and lout[-1] == lc and out[-1] != c: out = out[:-1] lout = lout[:-1] else: out += c lout += lc if out == data: break data = out return len(data), data test_data = "dabAcCaCBAcCcaDA" test_output = solve(test_data) test_expected = (10, "dabCBAcaDA") print(test_output, test_expected) assert test_output == test_expected print(solve(file_data))

[ "[email protected]" ]

[email protected]

62ab1ea93818eed7b32b1dd371198993153edd61

a752920841038f1f84df06779ff041d6c1100697

/pypinyin/phrases_dict.pyi

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permissive

mozillazg/python-pinyin

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6a306a6ec0148502ae4e689a229340555ecb6333

refs/heads/master

2023-08-31T14:13:44.512972

2023-05-14T12:18:47

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2023-09-09T03:46:41

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Python

UTF-8

Python

false

94

pyi

from typing import Dict, List, Text phrases_dict = ... # type: Dict[Text, List[List[Text]]]

[ "[email protected]" ]

[email protected]

0dd8e37f694e893ca41f0e481521e1f666d2443f

89376db3a7febcbd9b87a96cfc9e4f3fcf23758d

/test/unit/backends/msbuild/test_syntax.py

fab57708a7d0feb25463863dd417f764c17adbac

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permissive

zokrezyl/bfg9000

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430dfa2bfd4863d30f4690ff22f7b62dc80387ba

refs/heads/master

2022-10-02T18:10:36.577322

2020-05-29T20:53:56

2020-05-29T20:54:47

null

0

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UTF-8

Python

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8,727

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from io import BytesIO from lxml import etree from lxml.builder import E from . import * from bfg9000.backends.msbuild.syntax import * from bfg9000.file_types import SourceFile from bfg9000.path import Path, Root from bfg9000.safe_str import jbos, literal, safe_string from bfg9000.tools.common import Command class my_safe_str(safe_string): pass class TestTextify(TestCase): def test_string(self): self.assertEqual(textify('foo'), 'foo') self.assertEqual(textify('foo', True), 'foo') self.assertEqual(textify('foo bar'), 'foo bar') self.assertEqual(textify('foo bar', True), '"foo bar"') def test_literal(self): self.assertEqual(textify(literal('foo bar')), 'foo bar') self.assertEqual(textify(literal('foo bar'), True), 'foo bar') def test_jbos(self): j = jbos('foo', literal('='), 'bar baz') self.assertEqual(textify(j), 'foo=bar baz') self.assertEqual(textify(j, True), 'foo="bar baz"') def test_path(self): p1 = Path('foo') p2 = Path('foo', Root.srcdir) self.assertEqual(textify(p1), r'$(OutDir)\foo') self.assertEqual(textify(p2), r'$(SourceDir)\foo') self.assertEqual(textify(p1, builddir=BuildDir.intermediate), r'$(IntDir)\foo') self.assertEqual(textify(p2, builddir=BuildDir.intermediate), r'$(SourceDir)\foo') self.assertEqual(textify(p1, builddir=BuildDir.solution), r'$(SolutionDir)\foo') self.assertEqual(textify(p2, builddir=BuildDir.solution), r'$(SourceDir)\foo') def test_file(self): class MockCreator: def __init__(self, msbuild_output=False): self.msbuild_output = msbuild_output src = SourceFile(Path('foo'), 'c++') self.assertEqual(textify(src), r'$(SolutionDir)\foo') src.creator = MockCreator() self.assertEqual(textify(src), r'$(IntDir)\foo') src.creator = MockCreator(True) self.assertEqual(textify(src), r'$(OutDir)\foo') def test_invalid(self): with self.assertRaises(TypeError): textify(my_safe_str()) class ProjectTest(TestCase): xmlns = 'http://schemas.microsoft.com/developer/msbuild/2003' def xpath(self, node, query): return node.xpath(query, namespaces={'x': self.xmlns}) def assertXPath(self, node, query, result): self.assertEqual(self.xpath(node, query), result) class TestVcxProject(ProjectTest): def test_write(self): proj = VcxProject(FakeEnv(), 'project', output_file=Path('output'), files=[{'name': SourceFile(Path('src.cpp'), 'c++'), 'options': {}}]) out = BytesIO() proj.write(out) tree = etree.fromstring(out.getvalue()) project = self.xpath(tree, '/x:Project')[0] self.assertXPath(project, './x:PropertyGroup/x:TargetPath/text()', [r'$(OutDir)\output']) self.assertXPath(project, './x:ItemGroup/x:ClCompile/@Include', [r'$(SolutionDir)\src.cpp']) def test_duplicate_basename(self): proj = VcxProject( FakeEnv(), 'project', output_file=Path('output'), files=[ {'name': SourceFile(Path('a/src.cpp'), 'c++'), 'options': {}}, {'name': SourceFile(Path('b/src.cpp'), 'c++'), 'options': {}}, ]) out = BytesIO() proj.write(out) tree = etree.fromstring(out.getvalue()) self.assertXPath(tree, 'x:ItemGroup/x:ClCompile/@Include', [ r'$(SolutionDir)\a\src.cpp', r'$(SolutionDir)\b\src.cpp' ]) self.assertXPath( tree, 'x:ItemGroup/x:ClCompile/x:ObjectFileName/text()', [r'$(IntDir)\a\src.obj', r'$(IntDir)\b\src.obj'] ) def test_compile_options(self): proj = VcxProject(FakeEnv(), 'project') root = E.Element() proj._write_compile_options(root, {}) self.assertXPath(root, './*', []) root = E.Element() proj._write_compile_options(root, { 'warnings': {'level': 'all', 'as_error': True} }) self.assertXPath(root, './WarningLevel/text()', ['EnableAllWarnings']) self.assertXPath(root, './TreatWarningAsError/text()', ['true']) root = E.Element() proj._write_compile_options(root, {'debug': 'pdb'}) self.assertXPath(root, './DebugInformationFormat/text()', ['ProgramDatabase']) root = E.Element() proj._write_compile_options(root, {'includes': ['foo', 'bar']}) self.assertXPath(root, './AdditionalIncludeDirectories/text()', ['foo;bar;%(AdditionalIncludeDirectories)']) root = E.Element() proj._write_compile_options(root, {'defines': ['foo', 'bar']}) self.assertXPath(root, './PreprocessorDefinitions/text()', ['foo;bar;%(PreprocessorDefinitions)']) root = E.Element() proj._write_compile_options(root, {'pch': {'create': 'foo'}}) self.assertXPath(root, './PrecompiledHeader/text()', ['Create']) self.assertXPath(root, './PrecompiledHeaderFile/text()', ['foo']) root = E.Element() proj._write_compile_options(root, {'pch': {'use': 'foo'}}) self.assertXPath(root, './PrecompiledHeader/text()', ['Use']) self.assertXPath(root, './PrecompiledHeaderFile/text()', ['foo']) root = E.Element() proj._write_compile_options(root, {'runtime': 'dynamic-debug'}) self.assertXPath(root, './RuntimeLibrary/text()', ['MultiThreadedDebugDLL']) root = E.Element() proj._write_compile_options(root, {'extra': ['foo', 'bar']}) self.assertXPath(root, './AdditionalOptions/text()', ['foo bar %(AdditionalOptions)']) def test_link_options(self): proj = VcxProject(FakeEnv(), 'project') root = E.Element() proj._write_link_options(root, {}) self.assertXPath(root, './OutputFile/text()', ['$(TargetPath)']) root = E.Element() proj._write_link_options(root, {'debug': True}) self.assertXPath(root, './GenerateDebugInformation/text()', ['true']) root = E.Element() proj._write_link_options(root, {'import_lib': 'foo'}) self.assertXPath(root, './ImportLibrary/text()', ['foo']) root = E.Element() proj._write_link_options(root, {'extra': ['foo', 'bar']}) self.assertXPath(root, './AdditionalOptions/text()', ['foo bar %(AdditionalOptions)']) root = E.Element() proj._write_link_options(root, {'libs': ['foo', 'bar']}) self.assertXPath(root, './AdditionalDependencies/text()', ['foo;bar;%(AdditionalDependencies)']) class TestNoopProject(ProjectTest): def test_write(self): proj = NoopProject(FakeEnv(), 'project') out = BytesIO() proj.write(out) tree = etree.fromstring(out.getvalue()) self.assertXPath(tree, '/x:Project/x:Target/@Name', ['Build']) class TestCommandProject(ProjectTest): def test_write(self): proj = CommandProject(FakeEnv(), 'project', commands=[ CommandProject.task('Exec', Command='echo foo') ]) out = BytesIO() proj.write(out) tree = etree.fromstring(out.getvalue()) build = self.xpath(tree, '/x:Project/x:Target[@Name="Build"]')[0] self.assertXPath(build, './x:MakeDir/@Directories', ['$(OutDir)']) self.assertXPath(build, './x:Exec/@Command', ['echo foo']) # Now try without makedir. proj = CommandProject(FakeEnv(), 'project', commands=[ CommandProject.task('Exec', Command='echo foo') ], makedir=False) out = BytesIO() proj.write(out) tree = etree.fromstring(out.getvalue()) build = self.xpath(tree, '/x:Project/x:Target[@Name="Build"]')[0] self.assertXPath(build, './x:MakeDir', []) self.assertXPath(build, './x:Exec/@Command', ['echo foo']) def test_convert_attr(self): self.assertEqual(CommandProject.convert_attr('foo'), 'foo') self.assertEqual(CommandProject.convert_attr(['foo', 'bar']), 'foo;bar') def test_convert_command(self): self.assertEqual(CommandProject.convert_command(['foo', 'bar']), 'foo bar') self.assertEqual(CommandProject.convert_command( [Command(None, 'rule', 'var', 'command'), 'bar'] ), 'command bar')

[ "[email protected]" ]

[email protected]

0863e527af5d732af536a3f43a250d44e42f5214

bc441bb06b8948288f110af63feda4e798f30225

/ops_automation_sdk/model/topology/view_pb2.pyi

574a1e0fb8757902dfdc5b3c1c4fdc934341eb51

[ "Apache-2.0" ]

permissive

easyopsapis/easyops-api-python

23204f8846a332c30f5f3ff627bf220940137b6b

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

refs/heads/master

2020-06-26T23:38:27.308803

2020-06-16T07:25:41

199,773,131

5

0

null

UTF-8

Python

false

7,314

pyi

# @generated by generate_proto_mypy_stubs.py. Do not edit! import sys from google.protobuf.descriptor import ( Descriptor as google___protobuf___descriptor___Descriptor, ) from google.protobuf.internal.containers import ( RepeatedCompositeFieldContainer as google___protobuf___internal___containers___RepeatedCompositeFieldContainer, RepeatedScalarFieldContainer as google___protobuf___internal___containers___RepeatedScalarFieldContainer, ) from google.protobuf.message import ( Message as google___protobuf___message___Message, ) from ops_automation_sdk.model.topology.area_pb2 import ( Area as ops_automation_sdk___model___topology___area_pb2___Area, ) from ops_automation_sdk.model.topology.link_pb2 import ( Link as ops_automation_sdk___model___topology___link_pb2___Link, ) from ops_automation_sdk.model.topology.node_pb2 import ( Node as ops_automation_sdk___model___topology___node_pb2___Node, ) from ops_automation_sdk.model.topology.note_pb2 import ( Note as ops_automation_sdk___model___topology___note_pb2___Note, ) from typing import ( Iterable as typing___Iterable, Optional as typing___Optional, Text as typing___Text, Union as typing___Union, ) from typing_extensions import ( Literal as typing_extensions___Literal, ) builtin___bool = bool builtin___bytes = bytes builtin___float = float builtin___int = int if sys.version_info < (3,): builtin___buffer = buffer builtin___unicode = unicode class View(google___protobuf___message___Message): DESCRIPTOR: google___protobuf___descriptor___Descriptor = ... class Diff(google___protobuf___message___Message): DESCRIPTOR: google___protobuf___descriptor___Descriptor = ... @property def addNodes(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___node_pb2___Node]: ... @property def removeNodes(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___node_pb2___Node]: ... @property def addLinks(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___link_pb2___Link]: ... @property def removeLinks(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___link_pb2___Link]: ... def __init__(self, *, addNodes : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___node_pb2___Node]] = None, removeNodes : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___node_pb2___Node]] = None, addLinks : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___link_pb2___Link]] = None, removeLinks : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___link_pb2___Link]] = None, ) -> None: ... if sys.version_info >= (3,): @classmethod def FromString(cls, s: builtin___bytes) -> View.Diff: ... else: @classmethod def FromString(cls, s: typing___Union[builtin___bytes, builtin___buffer, builtin___unicode]) -> View.Diff: ... def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def ClearField(self, field_name: typing_extensions___Literal[u"addLinks",b"addLinks",u"addNodes",b"addNodes",u"removeLinks",b"removeLinks",u"removeNodes",b"removeNodes"]) -> None: ... id = ... # type: typing___Text name = ... # type: typing___Text creator = ... # type: typing___Text modifier = ... # type: typing___Text readAuthorizers = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text] writeAuthorizers = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text] version = ... # type: typing___Text ctime = ... # type: builtin___int mtime = ... # type: builtin___int @property def rootNode(self) -> ops_automation_sdk___model___topology___node_pb2___Node: ... @property def nodes(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___node_pb2___Node]: ... @property def links(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___link_pb2___Link]: ... @property def areas(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___area_pb2___Area]: ... @property def notes(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[ops_automation_sdk___model___topology___note_pb2___Note]: ... @property def diff(self) -> View.Diff: ... def __init__(self, *, id : typing___Optional[typing___Text] = None, name : typing___Optional[typing___Text] = None, creator : typing___Optional[typing___Text] = None, modifier : typing___Optional[typing___Text] = None, readAuthorizers : typing___Optional[typing___Iterable[typing___Text]] = None, writeAuthorizers : typing___Optional[typing___Iterable[typing___Text]] = None, version : typing___Optional[typing___Text] = None, ctime : typing___Optional[builtin___int] = None, mtime : typing___Optional[builtin___int] = None, rootNode : typing___Optional[ops_automation_sdk___model___topology___node_pb2___Node] = None, nodes : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___node_pb2___Node]] = None, links : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___link_pb2___Link]] = None, areas : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___area_pb2___Area]] = None, notes : typing___Optional[typing___Iterable[ops_automation_sdk___model___topology___note_pb2___Note]] = None, diff : typing___Optional[View.Diff] = None, ) -> None: ... if sys.version_info >= (3,): @classmethod def FromString(cls, s: builtin___bytes) -> View: ... else: @classmethod def FromString(cls, s: typing___Union[builtin___bytes, builtin___buffer, builtin___unicode]) -> View: ... def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def HasField(self, field_name: typing_extensions___Literal[u"diff",b"diff",u"rootNode",b"rootNode"]) -> builtin___bool: ... def ClearField(self, field_name: typing_extensions___Literal[u"areas",b"areas",u"creator",b"creator",u"ctime",b"ctime",u"diff",b"diff",u"id",b"id",u"links",b"links",u"modifier",b"modifier",u"mtime",b"mtime",u"name",b"name",u"nodes",b"nodes",u"notes",b"notes",u"readAuthorizers",b"readAuthorizers",u"rootNode",b"rootNode",u"version",b"version",u"writeAuthorizers",b"writeAuthorizers"]) -> None: ...

[ "[email protected]" ]

[email protected]

a52188f6b0918565c35293d5307352a232165999

daa8ed885ab8cac1d0c568bb01cb7c6426ae545a

/arithmetic.py

64238ac84292597ced56bf9c3f77eb27f706d7f0

[]

no_license

k8k/HBExercise02

f20cacc9761ab9d57be54416be0bc1a63967681d

de01b9a5466c662d823c1fbf16ff110684538d54

refs/heads/master

2021-01-19T06:18:35.253982

2014-10-02T01:03:33

null

0

null

UTF-8

Python

false

412

py

def add(num1, num2): return (num1 + num2) def subtract(num1, num2): return (num1 - num2) def multiply(num1, num2): return (num1 * num2) def divide(num1, num2): return (float(num1) / num2) def square(num1): return (num1 ** 2) def cube(num1): return (num1 ** 3) def power(num1, num2): return (num1 ** num2) print (num1 ** num2) def mod(num1, num2): return (num1 % num2)

[ "[email protected]" ]

[email protected]

a491e7f4fe918a165410005e4a2a8a193a1fdc41

6bc7062b2f99d0c54fd1bb74c1c312a2e3370e24

/crowdfunding/projects/migrations/0011_auto_20200823_1422.py

c685f8e23363ce08211f7cb85847cbf765624d1e

[]

no_license

marinkoellen/drf-proj

f2d1f539efb877df69d285bd2fe6d5e789709933

874549d68ab80a774988c83706bb7934e035de42

refs/heads/master

2022-12-25T16:53:52.187704

2020-10-03T03:54:06

289,620,536

0

null

UTF-8

Python

false

402

py

# Generated by Django 3.0.8 on 2020-08-23 06:22 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('projects', '0010_auto_20200823_1421'), ] operations = [ migrations.AlterField( model_name='project', name='date_created', field=models.DateTimeField(auto_now_add=True), ), ]

[ "[email protected]" ]

[email protected]

03b4d6ed65a5531775caf12fd19231937b5b77c8

5c0a253bf2fb83db01abc99097871c965f4cf565

/spark/crm/PROC_A_RPT_SUN_INFO_DETAIL.py

027630dff0344395b1cf1fef3a04b1f388a59356

[]

no_license

airuibel/python-1

3b16553ede9d069ec56efbb12a89a4de6917a447

94f387e2d406fab2128bcfffce6146da720b2ccc

refs/heads/master

2020-07-05T15:43:00.957221

2017-09-17T14:05:48

null

0

null

UTF-8

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#coding=UTF-8 from pyspark import SparkContext, SparkConf, SQLContext, Row, HiveContext from pyspark.sql.types import * from datetime import date, datetime, timedelta import sys, re, os st = datetime.now() conf = SparkConf().setAppName('PROC_A_RPT_SUN_INFO_DETAIL').setMaster(sys.argv[2]) sc = SparkContext(conf = conf) sc.setLogLevel('WARN') if len(sys.argv) > 5: if sys.argv[5] == "hive": sqlContext = HiveContext(sc) else: sqlContext = SQLContext(sc) hdfs = sys.argv[3] dbname = sys.argv[4] #处理需要使用的日期 etl_date = sys.argv[1] #etl日期 V_DT = etl_date #上一日日期 V_DT_LD = (date(int(etl_date[0:4]), int(etl_date[4:6]), int(etl_date[6:8])) + timedelta(-1)).strftime("%Y%m%d") #月初日期 V_DT_FMD = date(int(etl_date[0:4]), int(etl_date[4:6]), 1).strftime("%Y%m%d") #上月末日期 V_DT_LMD = (date(int(etl_date[0:4]), int(etl_date[4:6]), 1) + timedelta(-1)).strftime("%Y%m%d") #10位日期 V_DT10 = (date(int(etl_date[0:4]), int(etl_date[4:6]), int(etl_date[6:8]))).strftime("%Y-%m-%d") V_STEP = 0 #----------------------------------------------业务逻辑开始---------------------------------------------------------- #源表 OCRM_F_CI_SUN_BASEINFO = sqlContext.read.parquet(hdfs+'/OCRM_F_CI_SUN_BASEINFO/*') OCRM_F_CI_SUN_BASEINFO.registerTempTable("OCRM_F_CI_SUN_BASEINFO") OCRM_F_CI_SUN_BASE = sqlContext.read.parquet(hdfs+'/OCRM_F_CI_SUN_BASE/*') OCRM_F_CI_SUN_BASE.registerTempTable("OCRM_F_CI_SUN_BASE") OCRM_F_CUST_ELECTRICITY_COST = sqlContext.read.parquet(hdfs+'/OCRM_F_CUST_ELECTRICITY_COST/*') OCRM_F_CUST_ELECTRICITY_COST.registerTempTable("OCRM_F_CUST_ELECTRICITY_COST") OCRM_F_CUST_WATER_COST = sqlContext.read.parquet(hdfs+'/OCRM_F_CUST_WATER_COST/*') OCRM_F_CUST_WATER_COST.registerTempTable("OCRM_F_CUST_WATER_COST") OCRM_F_CI_CUSTOMER_TYPE = sqlContext.read.parquet(hdfs+'/OCRM_F_CI_CUSTOMER_TYPE/*') OCRM_F_CI_CUSTOMER_TYPE.registerTempTable("OCRM_F_CI_CUSTOMER_TYPE") OCRM_F_CI_PER_CUST_INFO = sqlContext.read.parquet(hdfs+'/OCRM_F_CI_PER_CUST_INFO/*') OCRM_F_CI_PER_CUST_INFO.registerTempTable("OCRM_F_CI_PER_CUST_INFO") ACRM_F_CI_ASSET_BUSI_PROTO = sqlContext.read.parquet(hdfs+'/ACRM_F_CI_ASSET_BUSI_PROTO/*') ACRM_F_CI_ASSET_BUSI_PROTO.registerTempTable("ACRM_F_CI_ASSET_BUSI_PROTO") #目标表： #RPT_SUN_INFO_DETAIL 增改表多个PY 属于第一个 #处理过程：先删除运算目录所有数据文件，然后复制BK目录前一天数据到运算目录，作为今天数据文件 ret = os.system("hdfs dfs -rm -r /"+dbname+"/RPT_SUN_INFO_DETAIL/*.parquet") ret = os.system("hdfs dfs -cp -f /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT_LD+".parquet /"+dbname+"/RPT_SUN_INFO_DETAIL/"+V_DT+".parquet") RPT_SUN_INFO_DETAIL = sqlContext.read.parquet(hdfs+'/RPT_SUN_INFO_DETAIL/*') RPT_SUN_INFO_DETAIL.registerTempTable("RPT_SUN_INFO_DETAIL") #任务[21] 001-01:: V_STEP = V_STEP + 1 #MERGE操作 sql=""" SELECT CASE WHEN T.VILLAGE IS NULL THEN concat(T.TOWN,T.GROUPID) WHEN T.TOWN IS NULL THEN concat(T.COUNTY,T.GROUPID) ELSE concat(T.VILLAGE,T.GROUPID) END AS ADDR, T.CUST_ID, CASE WHEN T.ISHOUSEHOST = '1' THEN T.CUST_NAME ELSE T7.CUST_NAME END AS CUST_NAME, T1.FAM_TOTASSET, T1.FAM_DEBT , T2.SUM_PRICE AS ELEC, T3.SUM_PRICE AS WATER, T.FR_ID, CONCAT(T4.VALUE,'县',T5.VALUE,'镇',T6.VALUE,'村',T.GROUPID,'组') ADDR_DESC FROM OCRM_F_CI_SUN_BASEINFO T LEFT JOIN OCRM_F_CI_SUN_BASE T1 ON T.CUST_ID = T1.CUST_ID AND T1.FR_ID = T.FR_ID LEFT JOIN OCRM_F_CUST_ELECTRICITY_COST T2 ON T1.CUST_ID = T2.CUST_ID AND T2.FR_ID = T1.FR_ID LEFT JOIN OCRM_F_CUST_WATER_COST T3 ON T1.CUST_ID = T3.CUST_ID AND T3.FR_ID = T1.FR_ID LEFT JOIN OCRM_F_CI_CUSTOMER_TYPE T4 ON T.COUNTY = T4.ID AND T4.FR_ID = T.FR_ID LEFT JOIN OCRM_F_CI_CUSTOMER_TYPE T5 ON T.TOWN = T5.ID AND T5.FR_ID = T.FR_ID LEFT JOIN OCRM_F_CI_CUSTOMER_TYPE T6 ON T.VILLAGE = T6.ID AND T6.FR_ID = T.FR_ID LEFT JOIN OCRM_F_CI_SUN_BASEINFO T7 ON T7.FR_ID = T.FR_ID AND T.COUNTY = T7.COUNTY AND T.VILLAGE = T7.VILLAGE AND T.TOWN = T7.TOWN AND T.GROUPID = T7.GROUPID AND T.DOORID = T7.DOORID AND T7.ISHOUSEHOST = '1' --WHERE T.FR_ID = V_FR_ID """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_01 = sqlContext.sql(sql) TMP_RPT_SUN_INFO_DETAIL_01.registerTempTable("TMP_RPT_SUN_INFO_DETAIL_01") sql=""" select src.ADDR --VARCHAR ,src.CUST_ID --VARCHAR ,src.CUST_NAME --VARCHAR ,src.FAM_TOTASSET --DECIMAL(22,2) ,src.FAM_DEBT --DECIMAL(22,2) ,dst.PRECREDIT --DECIMAL(22,2) ,dst.SIGNCREDIT --DECIMAL(22,2) ,dst.USECREDIT --DECIMAL(22,2) ,dst.FAM_CRE --DECIMAL(22,2) ,src.ELEC --DECIMAL(22,2) ,src.WATER --DECIMAL(22,2) ,src.FR_ID --VARCHAR ,src.ADDR_DESC --VARCHAR from TMP_RPT_SUN_INFO_DETAIL_01 src left join RPT_SUN_INFO_DETAIL dst on src.CUST_ID=dst.CUST_ID and src.FR_ID=dst.FR_ID """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_INNER1 = sqlContext.sql(sql) TMP_RPT_SUN_INFO_DETAIL_INNER1.registerTempTable("TMP_RPT_SUN_INFO_DETAIL_INNER1") sql=""" select src.ADDR --VARCHAR ,src.CUST_ID --VARCHAR ,src.CUST_NAME --VARCHAR ,src.FAM_TOTASSET --DECIMAL(22,2) ,src.FAM_DEBT --DECIMAL(22,2) ,dst.PRECREDIT --DECIMAL(22,2) ,dst.SIGNCREDIT --DECIMAL(22,2) ,dst.USECREDIT --DECIMAL(22,2) ,dst.FAM_CRE --DECIMAL(22,2) ,src.ELEC --DECIMAL(22,2) ,src.WATER --DECIMAL(22,2) ,src.FR_ID --VARCHAR ,src.ADDR_DESC --VARCHAR from RPT_SUN_INFO_DETAIL src left join TMP_RPT_SUN_INFO_DETAIL_INNER1 dst on src.CUST_ID=dst.CUST_ID and src.FR_ID=dst.FR_ID where dst.CUST_ID is null """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_INNER2 = sqlContext.sql(sql) TMP_RPT_SUN_INFO_DETAIL_INNER2.registerTempTable("TMP_RPT_SUN_INFO_DETAIL_INNER2") RPT_SUN_INFO_DETAIL_UNION = TMP_RPT_SUN_INFO_DETAIL_INNER2.unionAll(TMP_RPT_SUN_INFO_DETAIL_INNER1) dfn="RPT_SUN_INFO_DETAIL/"+V_DT+".parquet" RPT_SUN_INFO_DETAIL_UNION.cache() nrows = RPT_SUN_INFO_DETAIL_UNION.count() RPT_SUN_INFO_DETAIL_UNION.write.save(path=hdfs + '/' + dfn, mode='overwrite') RPT_SUN_INFO_DETAIL_UNION.unpersist() #复制当天数据进BK ret = os.system("hdfs dfs -rm -r /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") ret = os.system("hdfs dfs -cp -f /"+dbname+"/RPT_SUN_INFO_DETAIL/"+V_DT+".parquet /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") et = datetime.now() print("Step %d start[%s] end[%s] use %d seconds") % (V_STEP, st.strftime("%H:%M:%S"), et.strftime("%H:%M:%S"), (et-st).seconds) #任务[21] 001-01:: V_STEP = V_STEP + 1 RPT_SUN_INFO_DETAIL = sqlContext.read.parquet(hdfs+'/RPT_SUN_INFO_DETAIL/*') RPT_SUN_INFO_DETAIL.registerTempTable("RPT_SUN_INFO_DETAIL") #更新户主姓名 update操作 sql=""" select dst.ADDR --VARCHAR ,dst.CUST_ID --VARCHAR ,COALESCE(dst.CUST_NAME,src.HZ_NAME) AS CUST_NAME --VARCHAR ,dst.FAM_TOTASSET --DECIMAL(22,2) ,dst.FAM_DEBT --DECIMAL(22,2) ,dst.PRECREDIT --DECIMAL(22,2) ,dst.SIGNCREDIT --DECIMAL(22,2) ,dst.USECREDIT --DECIMAL(22,2) ,dst.FAM_CRE --DECIMAL(22,2) ,dst.ELEC --DECIMAL(22,2) ,dst.WATER --DECIMAL(22,2) ,dst.FR_ID --VARCHAR ,dst.ADDR_DESC --VARCHAR from RPT_SUN_INFO_DETAIL dst left join OCRM_F_CI_PER_CUST_INFO src on dst.CUST_ID=src.CUST_ID and dst.FR_ID=src.FR_ID """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_02 = sqlContext.sql(sql) dfn="RPT_SUN_INFO_DETAIL/"+V_DT+".parquet" TMP_RPT_SUN_INFO_DETAIL_02.cache() nrows = TMP_RPT_SUN_INFO_DETAIL_02.count() TMP_RPT_SUN_INFO_DETAIL_02.write.save(path=hdfs + '/' + dfn, mode='overwrite') TMP_RPT_SUN_INFO_DETAIL_02.unpersist() #复制当天数据进BK ret = os.system("hdfs dfs -rm -r /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") ret = os.system("hdfs dfs -cp -f /"+dbname+"/RPT_SUN_INFO_DETAIL/"+V_DT+".parquet /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") et = datetime.now() print("Step %d start[%s] end[%s] use %d seconds") % (V_STEP, st.strftime("%H:%M:%S"), et.strftime("%H:%M:%S"), (et-st).seconds) #任务[21] 001-01:: V_STEP = V_STEP + 1 RPT_SUN_INFO_DETAIL = sqlContext.read.parquet(hdfs+'/RPT_SUN_INFO_DETAIL/*') RPT_SUN_INFO_DETAIL.registerTempTable("RPT_SUN_INFO_DETAIL") #MERGE操作,更新：授信金额（PRECREDIT）、可用信：USECREDIT sql=""" SELECT A.FR_ID,A.CUST_ID, cast(SUM(CASE WHEN A.CONT_STS = '1000' AND A.PRODUCT_ID LIKE '3%' THEN COALESCE(A.CONT_AMT,0) END) as DECIMAL(22,2)) as CONT_AMT , cast(SUM(COALESCE(BAL,0)) as DECIMAL(22,2)) AS BAL FROM ACRM_F_CI_ASSET_BUSI_PROTO A JOIN RPT_SUN_INFO_DETAIL B ON B.FR_ID = A.FR_ID AND A.CUST_ID = B.CUST_ID GROUP BY A.FR_ID,A.CUST_ID """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_03 = sqlContext.sql(sql) TMP_RPT_SUN_INFO_DETAIL_03.registerTempTable("TMP_RPT_SUN_INFO_DETAIL_03") sql=""" select src.ADDR --VARCHAR ,src.CUST_ID --VARCHAR ,src.CUST_NAME --VARCHAR ,src.FAM_TOTASSET --DECIMAL(22,2) ,src.FAM_DEBT --DECIMAL(22,2) ,cast(CASE WHEN dst.CUST_ID is null then src.PRECREDIT else dst.CONT_AMT end as DECIMAL(22,2)) as PRECREDIT --DECIMAL(22,2) ,src.SIGNCREDIT --DECIMAL(22,2) ,cast(CASE WHEN dst.CUST_ID is null then src.USECREDIT else (dst.CONT_AMT - dst.BAL) end as DECIMAL(22,2)) as USECREDIT --DECIMAL(22,2) ,src.FAM_CRE --DECIMAL(22,2) ,src.ELEC --DECIMAL(22,2) ,src.WATER --DECIMAL(22,2) ,src.FR_ID --VARCHAR ,src.ADDR_DESC --VARCHAR from RPT_SUN_INFO_DETAIL src left join TMP_RPT_SUN_INFO_DETAIL_03 dst on src.CUST_ID=dst.CUST_ID and src.FR_ID=dst.FR_ID """ sql = re.sub(r"\bV_DT\b", "'"+V_DT10+"'", sql) TMP_RPT_SUN_INFO_DETAIL_04 = sqlContext.sql(sql) dfn="RPT_SUN_INFO_DETAIL/"+V_DT+".parquet" TMP_RPT_SUN_INFO_DETAIL_04.cache() nrows = TMP_RPT_SUN_INFO_DETAIL_04.count() TMP_RPT_SUN_INFO_DETAIL_04.write.save(path=hdfs + '/' + dfn, mode='overwrite') TMP_RPT_SUN_INFO_DETAIL_04.unpersist() #复制当天数据进BK ret = os.system("hdfs dfs -rm -r /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") ret = os.system("hdfs dfs -cp -f /"+dbname+"/RPT_SUN_INFO_DETAIL/"+V_DT+".parquet /"+dbname+"/RPT_SUN_INFO_DETAIL_BK/"+V_DT+".parquet") et = datetime.now() print("Step %d start[%s] end[%s] use %d seconds") % (V_STEP, st.strftime("%H:%M:%S"), et.strftime("%H:%M:%S"), (et-st).seconds)

[ "[email protected]" ]

[email protected]

6f2e0b21a9d3099d28f4f0e9656df7eb350b08b5

4086ded777dab91e3b88e376c9e86487ea4f670f

/src/Modules/Trinity.FFI/Trinity.FFI.Python/GraphEngine/Storage/cache_manager.py

1367785a64745e5cd5f3eed7f0436c7d8e31563d

[ "MIT" ]

permissive

qdoop/GraphEngine

a618c5c7459036e24342288e5ae13a023e4c7228

d83381c781edc4040824c1e31057789939530eff

refs/heads/master

2020-03-07T03:28:56.175677

2018-03-30T00:35:52

127,236,851

0

MIT

2018-03-29T04:30:59

null

UTF-8

Python

false

2,139

py

from GraphEngine import GraphMachine def filter_null_args(arg_list): return filter(lambda x: x is not None, arg_list) class CacheManager: is_accessor = False inst = None module_id = -1 def load_cell(self, cell_id): return self.inst.LoadCell(cell_id) def save_cell(self, index=None, cell_id=None, write_ahead_log_options=None): return self.inst.SaveCell(*filter_null_args((write_ahead_log_options, cell_id, index))) def get_id(self, index): return self.inst.CellGetId(index) def get_field(self, index, field_name): return self.inst.CellGetField(index, field_name) def set_field(self, index, field_name, value): return self.inst.CellSetField(index, field_name, value) def append_field(self, index, field_name, content): return self.inst.CellAppendField(index, field_name, content) def remove_field(self, index, field_name): return self.inst.CellRemoveField(index, field_name) def delete(self, index): return self.inst.Del(index) def dispose(self): return self.inst.Dispose() @staticmethod def remove_cell(cell_id): GraphMachine.storage.RemoveCellFromStorage(cell_id) GraphMachine.id_allocator.dealloc(cell_id) class CellAccessorManager(CacheManager): def __init__(self): self.inst = GraphMachine.storage.CellAccessorManager() self.module_id = self.inst.ModuleId self.is_accessor = False def use_cell(self, cell_id, options=None, cell_type=None): return self.inst.UseCell(cell_id, *filter_null_args((options, cell_type))) def __enter__(self): # TODO return self def __exit__(self, exc_type, exc_val, exc_tb): # TODO self.inst.Dispose() del self.inst class CellManager(CacheManager): def __init__(self): self.inst = GraphMachine.storage.CellManager() self.module_id = self.inst.ModuleId self.is_accessor = True def new_cell(self, cell_type, cell_id=None, content=None): return self.inst.NewCell(*filter_null_args((cell_type, cell_id, content)))

[ "[email protected]" ]

[email protected]

1ee6d53f727f5e366a1cf7cf58dc8d0241e40160

2ff7e53d5e512cd762217ca54317982e07a2bb0c

/cherrypy/_cpwsgi.py

2ff83942a96d2b4dc51c03d759b9c975d2127900

[]

no_license

nanxijw/Clara-Pretty-One-Dick

66d3d69426642b79e8fd4cc8e0bec23adeeca6d6

50de3488a2140343c364efc2615cf6e67f152be0

refs/heads/master

2021-01-19T09:25:07.555284

2015-02-17T21:49:33

null

0

null

UTF-8

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9,916

py

#Embedded file name: cherrypy\_cpwsgi.py """WSGI interface (see PEP 333 and 3333). Note that WSGI environ keys and values are 'native strings'; that is, whatever the type of "" is. For Python 2, that's a byte string; for Python 3, it's a unicode string. But PEP 3333 says: "even if Python's str type is actually Unicode "under the hood", the content of native strings must still be translatable to bytes via the Latin-1 encoding!" """ import sys as _sys import cherrypy as _cherrypy from cherrypy._cpcompat import BytesIO from cherrypy import _cperror from cherrypy.lib import httputil def downgrade_wsgi_ux_to_1x(environ): """Return a new environ dict for WSGI 1.x from the given WSGI u.x environ.""" env1x = {} url_encoding = environ[u'wsgi.url_encoding'] for k, v in environ.items(): if k in (u'PATH_INFO', u'SCRIPT_NAME', u'QUERY_STRING'): v = v.encode(url_encoding) elif isinstance(v, unicode): v = v.encode('ISO-8859-1') env1x[k.encode('ISO-8859-1')] = v return env1x class VirtualHost(object): """Select a different WSGI application based on the Host header. This can be useful when running multiple sites within one CP server. It allows several domains to point to different applications. For example:: root = Root() RootApp = cherrypy.Application(root) Domain2App = cherrypy.Application(root) SecureApp = cherrypy.Application(Secure()) vhost = cherrypy._cpwsgi.VirtualHost(RootApp, domains={'www.domain2.example': Domain2App, 'www.domain2.example:443': SecureApp, }) cherrypy.tree.graft(vhost) """ default = None use_x_forwarded_host = True domains = {} def __init__(self, default, domains = None, use_x_forwarded_host = True): self.default = default self.domains = domains or {} self.use_x_forwarded_host = use_x_forwarded_host def __call__(self, environ, start_response): domain = environ.get('HTTP_HOST', '') if self.use_x_forwarded_host: domain = environ.get('HTTP_X_FORWARDED_HOST', domain) nextapp = self.domains.get(domain) if nextapp is None: nextapp = self.default return nextapp(environ, start_response) class InternalRedirector(object): """WSGI middleware that handles raised cherrypy.InternalRedirect.""" def __init__(self, nextapp, recursive = False): self.nextapp = nextapp self.recursive = recursive def __call__(self, environ, start_response): redirections = [] while True: environ = environ.copy() try: return self.nextapp(environ, start_response) except _cherrypy.InternalRedirect as ir: sn = environ.get('SCRIPT_NAME', '') path = environ.get('PATH_INFO', '') qs = environ.get('QUERY_STRING', '') old_uri = sn + path if qs: old_uri += '?' + qs redirections.append(old_uri) if not self.recursive: new_uri = sn + ir.path if ir.query_string: new_uri += '?' + ir.query_string if new_uri in redirections: ir.request.close() raise RuntimeError('InternalRedirector visited the same URL twice: %r' % new_uri) environ['REQUEST_METHOD'] = 'GET' environ['PATH_INFO'] = ir.path environ['QUERY_STRING'] = ir.query_string environ['wsgi.input'] = BytesIO() environ['CONTENT_LENGTH'] = '0' environ['cherrypy.previous_request'] = ir.request class ExceptionTrapper(object): """WSGI middleware that traps exceptions.""" def __init__(self, nextapp, throws = (KeyboardInterrupt, SystemExit)): self.nextapp = nextapp self.throws = throws def __call__(self, environ, start_response): return _TrappedResponse(self.nextapp, environ, start_response, self.throws) class _TrappedResponse(object): response = iter([]) def __init__(self, nextapp, environ, start_response, throws): self.nextapp = nextapp self.environ = environ self.start_response = start_response self.throws = throws self.started_response = False self.response = self.trap(self.nextapp, self.environ, self.start_response) self.iter_response = iter(self.response) def __iter__(self): self.started_response = True return self def next(self): return self.trap(self.iter_response.next) def close(self): if hasattr(self.response, 'close'): self.response.close() def trap(self, func, *args, **kwargs): try: return func(*args, **kwargs) except self.throws: raise except StopIteration: raise except: tb = _cperror.format_exc() _cherrypy.log(tb, severity=40) if not _cherrypy.request.show_tracebacks: tb = '' s, h, b = _cperror.bare_error(tb) if self.started_response: self.iter_response = iter([]) else: self.iter_response = iter(b) try: self.start_response(s, h, _sys.exc_info()) except: _cherrypy.log(traceback=True, severity=40) raise if self.started_response: return ''.join(b) else: return b class AppResponse(object): """WSGI response iterable for CherryPy applications.""" def __init__(self, environ, start_response, cpapp): if environ.get(u'wsgi.version') == (u'u', 0): environ = downgrade_wsgi_ux_to_1x(environ) self.environ = environ self.cpapp = cpapp try: self.run() except: self.close() raise r = _cherrypy.serving.response self.iter_response = iter(r.body) self.write = start_response(r.output_status, r.header_list) def __iter__(self): return self def next(self): return self.iter_response.next() def close(self): """Close and de-reference the current request and response. (Core)""" self.cpapp.release_serving() def run(self): """Create a Request object using environ.""" env = self.environ.get local = httputil.Host('', int(env('SERVER_PORT', 80)), env('SERVER_NAME', '')) remote = httputil.Host(env('REMOTE_ADDR', ''), int(env('REMOTE_PORT', -1) or -1), env('REMOTE_HOST', '')) scheme = env('wsgi.url_scheme') sproto = env('ACTUAL_SERVER_PROTOCOL', 'HTTP/1.1') request, resp = self.cpapp.get_serving(local, remote, scheme, sproto) request.login = env('LOGON_USER') or env('REMOTE_USER') or None request.multithread = self.environ['wsgi.multithread'] request.multiprocess = self.environ['wsgi.multiprocess'] request.wsgi_environ = self.environ request.prev = env('cherrypy.previous_request', None) meth = self.environ['REQUEST_METHOD'] path = httputil.urljoin(self.environ.get('SCRIPT_NAME', ''), self.environ.get('PATH_INFO', '')) qs = self.environ.get('QUERY_STRING', '') rproto = self.environ.get('SERVER_PROTOCOL') headers = self.translate_headers(self.environ) rfile = self.environ['wsgi.input'] request.run(meth, path, qs, rproto, headers, rfile) headerNames = {'HTTP_CGI_AUTHORIZATION': 'Authorization', 'CONTENT_LENGTH': 'Content-Length', 'CONTENT_TYPE': 'Content-Type', 'REMOTE_HOST': 'Remote-Host', 'REMOTE_ADDR': 'Remote-Addr'} def translate_headers(self, environ): """Translate CGI-environ header names to HTTP header names.""" for cgiName in environ: if cgiName in self.headerNames: yield (self.headerNames[cgiName], environ[cgiName]) elif cgiName[:5] == 'HTTP_': translatedHeader = cgiName[5:].replace('_', '-') yield (translatedHeader, environ[cgiName]) class CPWSGIApp(object): """A WSGI application object for a CherryPy Application.""" pipeline = [('ExceptionTrapper', ExceptionTrapper), ('InternalRedirector', InternalRedirector)] head = None config = {} response_class = AppResponse def __init__(self, cpapp, pipeline = None): self.cpapp = cpapp self.pipeline = self.pipeline[:] if pipeline: self.pipeline.extend(pipeline) self.config = self.config.copy() def tail(self, environ, start_response): """WSGI application callable for the actual CherryPy application. You probably shouldn't call this; call self.__call__ instead, so that any WSGI middleware in self.pipeline can run first. """ return self.response_class(environ, start_response, self.cpapp) def __call__(self, environ, start_response): head = self.head if head is None: head = self.tail for name, callable in self.pipeline[::-1]: conf = self.config.get(name, {}) head = callable(head, **conf) self.head = head return head(environ, start_response) def namespace_handler(self, k, v): """Config handler for the 'wsgi' namespace.""" if k == 'pipeline': self.pipeline.extend(v) elif k == 'response_class': self.response_class = v else: name, arg = k.split('.', 1) bucket = self.config.setdefault(name, {}) bucket[arg] = v

[ "[email protected]" ]

[email protected]

53ab5d874fe9b4a2789f77ec49d2cfe1ddc0e0fd

f0d0ea29240c53b6ce1c4b06095b528ece02fdd7

/utils/stdvalue.py

93e1cb555fd015df9031244044dc821b516d2157

[]

no_license

zhifuliu/dianjing

477529ccd6159329e1bc121aeb2ff328ee499f4a

7b3f6d58f5bc0738651d8d72c9a24df4ade0ed36

refs/heads/master

2020-03-21T09:10:28.343268

2017-03-24T03:06:24

null

0

null

UTF-8

Python

false

172

py

# -*- coding: utf-8 -*- """ Author: Wang Chao <[email protected]> Filename: stdvalue Date Created: 2016-09-30 18:30 Description: """ MAX_INT = 2 ** 31 - 1

[ "[email protected]" ]

[email protected]

24a2a2e09bb18264bdfb641a5ed9b3275d98e05b

a9f56cfe2fafc7981ae4d37afd49d3049d2f98b9

/t_sms/models.py

b4639b553775a4ebef0802490b6ce52b673e181b

[]

no_license

talhajubair100/django_allauth_language_currence_test

78dc340e4f3392c0dd18cd2e666c02ae04eba7bc

9530d548ea092145bc583b8a839a9bac891ef098

refs/heads/main

2023-02-21T20:25:42.332322

2021-01-24T14:10:13

326,125,098

0

null

UTF-8

Python

false

829

py

from django.db import models import os from twilio.rest import Client # Create your models here. class Detail(models.Model): name = models.CharField(max_length=150) phone = models.CharField(max_length=14) details = models.CharField(max_length=200) def __str__(self): return self.name def save(self, *args, **kwargs): account_sid = '****************' auth_token = '******************' client = Client(account_sid, auth_token) message = client.messages.create( body=f'Hi {self.name}! {self.details}', from_='******', to='+8801735700187' ) print('your sms id',message.sid) return super().save(*args, **kwargs)

[ "[email protected]" ]

[email protected]

2569dc664dc758ba28cbbdbad398093631bd023b

ccfd5f8efc0cf6a9ec1867860e5a16d19beaee90

/neobistime/events/migrations/0009_event_image.py

a338af06b377c6da5159e7c0fa0d4c60f2a9b68a

[]

no_license

magina671/neobistime

bf9bc759acf39367e3be42164c05575c1b8ed7e8

6dc3f8c8195997cfd4cabd5666e89d6f80a7b95c

refs/heads/master

2022-12-26T21:37:16.171324

2020-10-01T18:37:31

null

0

null

UTF-8

Python

false

484

py

# Generated by Django 2.2.6 on 2020-08-05 14:28 from django.db import migrations import easy_thumbnails.fields class Migration(migrations.Migration): dependencies = [ ('events', '0008_auto_20200805_0623'), ] operations = [ migrations.AddField( model_name='event', name='image', field=easy_thumbnails.fields.ThumbnailerImageField(default='event_imgs/default.jpg', upload_to='event_imgs/%Y/%m/%d/'), ), ]

[ "[email protected]" ]

[email protected]

f11f47b153e424f308df2de51c0fff6667d742b7

34599596e145555fde0d4264a1d222f951f49051

/pcat2py/class/214bd114-5cc5-11e4-af55-00155d01fe08.py

b6a94cc57e3436b403a340fcb5162b16fe7d3c98

[ "MIT" ]

permissive

phnomcobra/PCAT2PY

dc2fcbee142ce442e53da08476bfe4e68619346d

937c3b365cdc5ac69b78f59070be0a21bdb53db0

refs/heads/master

2021-01-11T02:23:30.669168

2018-02-13T17:04:03

70,970,520

0

null

UTF-8

Python

false

1,573

py

#!/usr/bin/python ################################################################################ # 214bd114-5cc5-11e4-af55-00155d01fe08 # # Justin Dierking # [email protected] # [email protected] # # 10/24/2014 Original Construction ################################################################################ class Finding: def __init__(self): self.output = [] self.is_compliant = False self.uuid = "214bd114-5cc5-11e4-af55-00155d01fe08" def check(self, cli): # Initialize Compliance self.is_compliant = False # Get Registry DWORD dword = cli.get_reg_dword(r'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings\Zones\4', '1604') # Output Lines self.output = [r'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings\Zones\4', ('1604=' + str(dword))] if dword == 3: self.is_compliant = True return self.is_compliant def fix(self, cli): cli.powershell(r"New-Item -path 'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings'") cli.powershell(r"New-Item -path 'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings\Zones'") cli.powershell(r"New-Item -path 'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings\Zones\4'") cli.powershell(r"Set-ItemProperty -path 'HKLM:\Software\Policies\Microsoft\Windows\CurrentVersion\Internet Settings\Zones\4' -name '1604' -value 3 -Type DWord")

[ "[email protected]" ]

[email protected]

bdb8f58b08216a4bd2cdb0f892102352d8abb24b

f902bfafd93fe96515f5b12fa8630b365cf71ce9

/python/ht/inline/utils.py

d7802291d80c7175ed3b05e8c473baceebd95f5b

[]

no_license

hickb/Houdini-Toolbox

69e999a924f387313382c254de2771d66c649f64

5309b2608f86b12aab8e90e754269ed2d2a44653

refs/heads/master

2022-06-18T23:08:45.481414

2020-05-06T19:25:02

null

0

null

UTF-8

Python

false

10,440

py

"""Utility functions to support custom inlinecpp functions.""" # ============================================================================= # IMPORTS # ============================================================================= # Standard Library Imports import ctypes # Houdini Imports import hou # ============================================================================= # GLOBALS # ============================================================================= # Tuple of all valid attribute data types. _ALL_ATTRIB_DATA_TYPES = ( hou.attribData.Float, hou.attribData.Int, hou.attribData.String, ) # Tuple of all valid attribute types. _ALL_ATTRIB_TYPES = ( hou.attribType.Global, hou.attribType.Point, hou.attribType.Prim, hou.attribType.Vertex, ) # Mapping between hou.attribData and corresponding GA_StorageClass values. _ATTRIB_STORAGE_MAP = { hou.attribData.Int: 0, hou.attribData.Float: 1, hou.attribData.String: 2, } # Mapping between hou.attribTypes and corresponding GA_AttributeOwner values. _ATTRIB_TYPE_MAP = { hou.attribType.Vertex: 0, hou.attribType.Point: 1, hou.attribType.Prim: 2, hou.attribType.Global: 3, } # Mapping between geometry types and corresponding GA_AttributeOwner values. _GEOMETRY_ATTRIB_MAP = {hou.Vertex: 0, hou.Point: 1, hou.Prim: 2, hou.Geometry: 3} # Mapping between hou.geometryTypes and corresponding GA_AttributeOwner values. _GEOMETRY_TYPE_MAP = { hou.geometryType.Vertices: 0, hou.geometryType.Points: 1, hou.geometryType.Primitives: 2, } # Mapping between group types and corresponding GA_AttributeOwner values. _GROUP_ATTRIB_MAP = {hou.PointGroup: 1, hou.PrimGroup: 2} # Mapping between group types and corresponding GA_GroupType values. _GROUP_TYPE_MAP = {hou.PointGroup: 0, hou.PrimGroup: 1, hou.EdgeGroup: 2} # ============================================================================= # FUNCTIONS # ============================================================================= def build_c_double_array(values): """Convert a list of numbers to a ctypes double array. :param values: A list of floats. :type values: list(float) :return: The values as ctypes compatible values. :rtype: list(ctypes.c_double) """ arr = (ctypes.c_double * len(values))(*values) return arr def build_c_int_array(values): """Convert a list of numbers to a ctypes int array. :param values: A list of ints. :type values: list(int) :return: The values as ctypes compatible values. :rtype: list(ctypes.c_int) """ arr = (ctypes.c_int * len(values))(*values) return arr def build_c_string_array(values): """Convert a list of strings to a ctypes char * array. :param values: A list of strings. :type values: list(str) :return: The values as ctypes compatible values. :rtype: list(ctypes.c_char_p) """ arr = (ctypes.c_char_p * len(values))(*values) return arr def clean_string_values(values): """Process a string list, removing empty strings. :param values: A list of strings to clean. :type values: list(str) :return: A clean tuple. :rtype: tuple(str) """ return tuple([val for val in values if val]) def find_attrib(geometry, attrib_type, name): """Find an attribute with a given name and type on the geometry. :param geometry: The geometry to find an attribute on. :type geometry: hou.Geometry :param attrib_type: The attribute type. :type attrib_type: hou.attribType. :param name: The attribute name. :type name: str :return: A found attribute, otherwise None. :rtype: hou.Attrib or None """ if attrib_type == hou.attribType.Vertex: return geometry.findVertexAttrib(name) elif attrib_type == hou.attribType.Point: return geometry.findPointAttrib(name) elif attrib_type == hou.attribType.Prim: return geometry.findPrimAttrib(name) elif attrib_type == hou.attribType.Global: return geometry.findGlobalAttrib(name) else: raise ValueError("Expected hou.attribType, got {}".format(type(attrib_type))) def find_group(geometry, group_type, name): """Find a group with a given name and type. group_type corresponds to the integer returned by _get_group_type() :param geometry: The geometry to find the group in. :type geometry: hou.Geometry :param group_type: The group type. :type group_type: int :param name: The attribute name. :type name: str :return: A found group. :rtype: hou.EdgeGroup or hou.PointGroup or hou.PrimGroup """ if group_type == 0: return geometry.findPointGroup(name) elif group_type == 1: return geometry.findPrimGroup(name) elif group_type == 2: return geometry.findEdgeGroup(name) else: raise ValueError("Invalid group type {}".format(group_type)) def geo_details_match(geometry1, geometry2): """Test if two hou.Geometry objects point to the same detail. :param geometry1: A geometry detail. :type geometry1: hou.Geometry :param geometry2: A geometry detail. :type geometry2: hou.Geometry :return: Whether or not the objects represent the same detail. :rtype: bool """ # pylint: disable=protected-access handle1 = geometry1._guDetailHandle() handle2 = geometry2._guDetailHandle() details_match = int(handle1._asVoidPointer()) == int(handle2._asVoidPointer()) handle1.destroy() handle2.destroy() return details_match def get_attrib_owner(attribute_type): """Get an HDK compatible attribute owner value. :param attribute_type: The type of attribute. :type attribute_type: hou.attribType :return: An HDK attribute owner value. :rtype: int """ try: return _ATTRIB_TYPE_MAP[attribute_type] except KeyError: raise ValueError("Invalid attribute type: {}".format(attribute_type)) def get_attrib_owner_from_geometry_entity_type(entity_type): """Get an HDK compatible attribute owner value from a geometry class. The type can be of hou.Geometry, hou.Point, hou.Prim (or subclasses) or hou.Vertex. :param entity_type: The entity to get a attribute owner for. :type entity_type: hou.Vertex or hou.Point or hou.Prim or hou.Geometry :return: An HDK attribute owner value. :rtype: int """ # If the class is a base class in the map then just return it. try: return _GEOMETRY_ATTRIB_MAP[entity_type] except KeyError: pass # If it is not in the map then it is most likely a subclass of hou.Prim, # such as hou.Polygon, hou.Face, hou.Volume, etc. We will check the class # against being a subclass of any of our valid types and if it is, return # the owner of that class. for key, value in _GEOMETRY_ATTRIB_MAP.items(): if issubclass(entity_type, key): return value # Something went wrong so raise an exception. raise ValueError("Invalid entity type: {}".format(entity_type)) def get_attrib_owner_from_geometry_type(geometry_type): """Get an HDK compatible attribute owner value from a hou.geometryType. :param geometry_type: The entity to get a attribute owner for. :type geometry_type: hou.geometryType :return: An HDK attribute owner value. :rtype: int """ # If the class is a base class in the map then just return it. try: return _GEOMETRY_TYPE_MAP[geometry_type] except KeyError: # Something went wrong so raise an exception. raise ValueError("Invalid geometry type: {}".format(geometry_type)) def get_attrib_storage(data_type): """Get an HDK compatible attribute storage class value. :param data_type: The type of data to store. :type data_type: hou.attribData :return: An HDK attribute storage type. :rtype: int """ try: return _ATTRIB_STORAGE_MAP[data_type] except KeyError: raise ValueError("Invalid data type: {}".format(data_type)) def get_group_attrib_owner(group): """Get an HDK compatible group attribute type value. :param group: The group to get the attribute owner for. :type group: hou.PointGroup or hou.PrimGroup :return: An HDK attribute owner value. :rtype: int """ try: return _GROUP_ATTRIB_MAP[type(group)] except KeyError: raise ValueError("Invalid group type") def get_group_type(group): """Get an HDK compatible group type value. :param group: The group to get the group type for. :type group: hou.EdgeGroup or hou.PointGroup or hou.PrimGroup :return: An HDK group type value. :rtype: int """ try: return _GROUP_TYPE_MAP[type(group)] except KeyError: raise ValueError("Invalid group type") def get_nodes_from_paths(paths): """Convert a list of string paths to hou.Node objects. :param paths: A list of paths. :type paths: list(str) :return: A tuple of hou.Node objects. :rtype: tuple(hou.Node) """ return tuple([hou.node(path) for path in paths if path]) def get_points_from_list(geometry, point_list): """Convert a list of point numbers to hou.Point objects. :param geometry: The geometry to get points for. :type geometry: hou.Geometry :param point_list: A list of point numbers. :type point_list: list(int) :return: Matching points on the geometry. :rtype: tuple(hou.Point) """ # Return a empty tuple if the point list is empty. if not point_list: return () # Convert the list of integers to a space separated string. point_str = " ".join([str(i) for i in point_list]) # Glob for the specified points. return geometry.globPoints(point_str) def get_prims_from_list(geometry, prim_list): """Convert a list of primitive numbers to hou.Prim objects. :param geometry: The geometry to get prims for. :type geometry: hou.Geometry :param prim_list: A list of prim numbers. :type prim_list: list(int) :return: Matching prims on the geometry. :rtype: tuple(hou.Prim) """ # Return a empty tuple if the prim list is empty. if not prim_list: return () # Convert the list of integers to a space separated string. prim_str = " ".join([str(i) for i in prim_list]) # Glob for the specified prims. return geometry.globPrims(prim_str)

[ "[email protected]" ]

[email protected]

b8cec1ad804460eb9ff1f586909b5ef9f9b0f4bc

813eb2e364262450d43263a524074098a8934bf1

/gtdtst.py

9d9fa734bab2f939323fd8d55ac1555b71016cfc

[]

no_license

cniekel/gtdtool

67f0e9ab4622f5361959ed51e4369523f6cbccc3

38a23806efd697814c9ebc492d87f88403ace041

refs/heads/master

2016-09-06T16:15:31.820358

2008-12-11T21:43:46

88,992

2

1

null

UTF-8

Python

false

2,419

py

from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Frame, PageTemplate, BaseDocTemplate from reportlab.platypus import KeepTogether from reportlab.lib.styles import getSampleStyleSheet from reportlab.rl_config import defaultPageSize from reportlab.lib.units import inch,cm from reportlab.lib.pagesizes import A4 PAGE_HEIGHT=defaultPageSize[1]; PAGE_WIDTH=defaultPageSize[0] styles = getSampleStyleSheet() class GTDPageTemplate(PageTemplate): def __init__(self, id, pageSize=defaultPageSize): self.pageWidth = pageSize[0] self.pageHeight = pageSize[1] border = 0.3*cm miniwidth = (self.pageWidth / 2) - 2*border miniheight = (self.pageHeight / 2) - 2*border #self.f4 = Frame(border, border, miniwidth, miniheight, id='p4') #self.f1 = Frame(self.pageWidth/2 + border, border, miniwidth, miniheight, id='p1') #self.f2 = Frame(self.pageWidth/2 + border, self.pageHeight/2 + border, miniwidth, miniheight, id='p2') #self.f3 = Frame(border, self.pageHeight/2 + border, miniwidth, miniheight, id='p3') self.f4 = Frame(0, 0, miniwidth, miniheight, id='p4') self.f1 = Frame(miniwidth, 0, miniwidth, miniheight, id='p1') self.f2 = Frame(miniwidth, miniheight, miniwidth, miniheight, id='p2') self.f3 = Frame(0, miniheight, miniwidth, miniheight, id='p3') PageTemplate.__init__(self, id, [self.f1, self.f2, self.f3, self.f4]) class GTDDocTemplate(BaseDocTemplate): def __init__(self, file, **kw): BaseDocTemplate.__init__(self,file, **kw) def myPages(canvas, doc): canvas.saveState() canvas.setFont('Times-Roman', 9) canvas.drawString(inch, 0.75*inch, 'Page %d %s' % (doc.page, 'test') def go(): doc = GTDDocTemplate('phello.pdf', pageSize=A4) doc.addPageTemplates(GTDPageTemplate('gtd', doc.pagesize)) Story=[] style = styles['Normal'] style.leftIndent = 0.75*inch style.firstLineIndent = 0 style.spaceAfter = 3 style.refresh() style.listAttrs() for i in range(8): bogustext = ('This is <br>paragraph <font color="red"><i>number</i></font> %s' % i) * 20 p = KeepTogether([Paragraph('Yo %d'%i, style), Paragraph(bogustext, style)]) Story.append(p) Story.append(Spacer(1, 0.2*inch)) doc.build(Story)#, onFirstPage=myPages, onLaterPages=myPages) if __name__ == '__main__': go()

[ "=" ]

=

a02e2b2f451539a813e61106eaedd8268f16b09b

deb3c16ef887b6c496b8c920809d79b9f73aa2fe

/hosts/9cartoonme.py

bf89b8ff48e5e12ae354fae05d306d97a0c9da5c

[]

no_license

Yaser7440/cmdline_iptvplayer

1ea35f4fd36c708176a43d402a49342c4cf723a5

4e287021d86cab8d6525262b647d144c6141d6b1

refs/heads/master

2021-01-24T10:49:29.278730

2016-09-21T09:24:26

null

0

null

UTF-8

Python

false

19,520

py

# -*- coding: utf-8 -*- ################################################### # LOCAL import ################################################### from Plugins.Extensions.IPTVPlayer.dToolsSet.iptvplayerinit import TranslateTXT as _, SetIPTVPlayerLastHostError from Plugins.Extensions.IPTVPlayer.components.ihost import CHostBase, CBaseHostClass, CDisplayListItem, RetHost, CUrlItem, ArticleContent from Plugins.Extensions.IPTVPlayer.dToolsSet.iptvtools import printDBG, printExc, CSearchHistoryHelper, GetDefaultLang, remove_html_markup, GetLogoDir, GetCookieDir, byteify from Plugins.Extensions.IPTVPlayer.libs.pCommon import common, CParsingHelper import Plugins.Extensions.IPTVPlayer.libs.urlparser as urlparser from Plugins.Extensions.IPTVPlayer.libs.youtube_dl.utils import clean_html from Plugins.Extensions.IPTVPlayer.tools.iptvtypes import strwithmeta ################################################### ################################################### # FOREIGN import ################################################### from datetime import timedelta import time import re import urllib import urlparse import unicodedata import string import base64 try: import json except Exception: import simplejson as json from Components.config import config, ConfigSelection, ConfigYesNo, ConfigText, getConfigListEntry ################################################### ################################################### # E2 GUI COMMPONENTS ################################################### from Plugins.Extensions.IPTVPlayer.components.asynccall import MainSessionWrapper ################################################### ################################################### # Config options for HOST ################################################### #config.plugins.iptvplayer.CartoonME_language = ConfigSelection(default = "en", choices = [("en", _("English")), ("es", _("Spanish"))]) def GetConfigList(): optionList = [] #optionList.append(getConfigListEntry(_("Language:"), config.plugins.iptvplayer.CartoonME_language)) return optionList ################################################### def gettytul(): return 'http://9cartoon.me/' class CartoonME(CBaseHostClass): USER_AGENT = 'curl/7' def __init__(self): CBaseHostClass.__init__(self, {'history':'9cartoon.me', 'cookie':'CartoonME.cookie'}) self.defaultParams = {'use_cookie': True, 'load_cookie': True, 'save_cookie': True, 'cookiefile': self.COOKIE_FILE} self.MAIN_URL = 'http://9cartoon.me/' self.SEARCH_URL = self.MAIN_URL +'Search?s=' self.DEFAULT_ICON = "http://www.siwallpaperhd.com/wp-content/uploads/2015/07/spongebob_squarepants_face_wallpaper_hd_8_cartoon-724x453.png" self.MAIN_CAT_TAB = [{'category':'list_types', 'title': _('Cartoon list'), 'url':self.MAIN_URL+'CartoonList', 'icon':self.DEFAULT_ICON}, {'category':'categories', 'title': _('Genres'), 'url':self.MAIN_URL, 'icon':self.DEFAULT_ICON}, {'category':'search', 'title': _('Search'), 'search_item':True, 'icon':self.DEFAULT_ICON}, {'category':'search_history', 'title': _('Search history'), 'icon':self.DEFAULT_ICON} ] def getPage(self, baseUrl, params={}, post_data=None): if params == {}: params = dict(self.defaultParams) params['cloudflare_params'] = {'domain':'9cartoon.me', 'cookie_file':self.COOKIE_FILE, 'User-Agent':self.USER_AGENT, 'full_url_handle':self.getFullUrl} return self.cm.getPageCFProtection(baseUrl, params, post_data) def getIconUrl(self, url): url = self.getFullUrl(url) if url == '': return '' cookieHeader = self.cm.getCookieHeader(self.COOKIE_FILE) return strwithmeta(url, {'Cookie':cookieHeader, 'User-Agent':self.USER_AGENT}) def listCategories(self, cItem, nextCategory): printDBG("CartoonME.listCategories") sts, data = self.getPage(cItem['url']) if not sts: return tab = [] data = self.cm.ph.getDataBeetwenMarkers(data, 'genre right">', '</ul>', False)[1] data = re.compile('''<a[^>]+?href=['"]([^'^"]+?)['"][^>]*?>([^<]+?)<''').findall(data) for item in data: title = self.cleanHtmlStr(item[1]) url = self.getFullUrl(item[0]) tab.append({'title':title, 'url':url}) cItem = dict(cItem) cItem['category'] = nextCategory self.listsTab(tab, cItem) def listCartoonListTypes(self, cItem, nextCategory): printDBG("CartoonME.listCartoonListTypes") sts, data = self.getPage(cItem['url']) if not sts: return tab = [] data = self.cm.ph.getDataBeetwenMarkers(data, '<div class="list_search">', '</ul>', False)[1] data = re.compile('''<a[^>]+?href=['"]([^'^"]+?)['"][^>]*?>([^<]+?)<''').findall(data) for item in data: title = self.cleanHtmlStr(item[1]) url = self.getFullUrl(item[0]) tab.append({'title':title, 'url':url}) cItem = dict(cItem) cItem['category'] = nextCategory self.listsTab(tab, cItem) def listLetters(self, cItem, nextCategory): printDBG("CartoonME.listLetters") sts, data = self.getPage(cItem['url']) if not sts: return tab = [] data = self.cm.ph.rgetDataBeetwenMarkers(data, '<div class="list_search">', '<div class="anime_list_body">', False)[1] data = re.compile('''<a[^>]+?href=['"]([^'^"]+?)['"][^>]*?>([^<]+?)<''').findall(data) for item in data: title = self.cleanHtmlStr(item[1]) url = self.getFullUrl(item[0]) tab.append({'title':title, 'url':url}) cItem = dict(cItem) cItem['category'] = nextCategory self.listsTab(tab, cItem) def listItems1(self, cItem, nextCategory): printDBG("CartoonME.listItems1") page = cItem.get('page', 1) url = cItem['url'] tmp = url.split('?') url = tmp[0] if len(tmp)>1: query = tmp[1] else: query = '' if not url.endswith('/'): url += '/' if page > 1: url += '?page=%d&' % page else: url += '?' if query != '': url += query sts, data = self.getPage(url) if not sts: return nextPage = self.cm.ph.getDataBeetwenMarkers(data, '<div class="pagination">', '', False)[1] if ('>%d<' % (page+1)) in nextPage: nextPage = True else: nextPage = False m1 = '<div class="anime_movies_items">' data = self.cm.ph.getDataBeetwenMarkers(data, m1, '</section>', False)[1] data = data.split(m1) for item in data: icon = self.getFullUrl( self.cm.ph.getSearchGroups(item, '''src=['"]([^"^']+?)['"]''')[0] ) url = self.getFullUrl( self.cm.ph.getSearchGroups(item, '''href=['"]([^'^"]+?)['"]''')[0] ) title = self.cleanHtmlStr( self.cm.ph.getDataBeetwenMarkers(item, '<p class="name">', '</p>', True)[1] ) if title == '': title = self.cleanHtmlStr( self.cm.ph.getSearchGroups(item, '''title=['"]([^'^"]+?)['"]''')[0] ) if url.startswith('http'): params = dict(cItem) params.update({'title':title, 'url':url, 'icon':icon}) if '/WATCH/' in url.upper(): self.addVideo(params) else: params['category'] = nextCategory self.addDir(params) if nextPage: params = dict(cItem) params.update({'title':_('Next page'), 'page':page+1}) self.addDir(params) def listItems2(self, cItem, nextCategory): printDBG("CartoonME.listItems2") page = cItem.get('page', 1) url = cItem['url'] tmp = url.split('?') url = tmp[0] if len(tmp)>1: query = tmp[1] else: query = '' if not url.endswith('/'): url += '/' if page > 1: url += '?page=%d&' % page else: url += '?' if query != '': url += query sts, data = self.getPage(url) if not sts: return nextPage = self.cm.ph.getDataBeetwenMarkers(data, '<div class="pagination">', '', False)[1] if ('>%d<' % (page+1)) in nextPage: nextPage = True else: nextPage = False data = self.cm.ph.getDataBeetwenMarkers(data, '<div class="anime_list_body">', '</ul>', False)[1] data = self.cm.ph.getAllItemsBeetwenMarkers(data, '<li', '</li>') for item in data: icon = self.getFullUrl( self.cm.ph.getSearchGroups(item, '''src=['"]([^"^']+?)['"]''')[0] ) tmp = self.cm.ph.rgetDataBeetwenMarkers(item, '<a', '</a>')[1] url = self.getFullUrl( self.cm.ph.getSearchGroups(tmp, '''href=['"]([^'^"]+?)['"]''')[0] ) title = self.cleanHtmlStr( tmp ) desc = self.cleanHtmlStr( self.cm.ph.getSearchGroups(item, '''title=[']([^']+?)[']''')[0] ) if url.startswith('http'): params = dict(cItem) params.update({'title':title, 'url':url, 'icon':icon, 'desc':desc}) if '/WATCH/' in url.upper(): self.addVideo(params) else: params['category'] = nextCategory self.addDir(params) if nextPage: params = dict(cItem) params.update({'title':_('Next page'), 'page':page+1}) self.addDir(params) def listEpisodes(self, cItem): printDBG("CartoonME.listEpisodes") sts, data = self.getPage(cItem['url']) if not sts: return data = self.cm.ph.getDataBeetwenMarkers(data, '<div class="anime_info_body">', '</ul>', False)[1] data = data.split('<ul id="episode_related">') if len(data) < 2: return icon = self.getFullUrl( self.cm.ph.getSearchGroups(data[0], '''src=['"]([^"^']+?)['"]''')[0] ) if icon == '': icon = cItem.get('icon', '') title = self.cleanHtmlStr( self.cm.ph.getDataBeetwenMarkers(data[0], '<h1', '</h1>', True)[1] ) if title == '': icon = cItem['title'] desc = self.cleanHtmlStr( data[0].split('</h1>')[-1] ) data = self.cm.ph.getAllItemsBeetwenMarkers(data[1], '<li', '</li>') for item in data: eTitle = self.cleanHtmlStr(self.cleanHtmlStr(item)) videoUrl = self.getFullUrl( self.cm.ph.getSearchGroups(item, '''href=['"]([^"^']+?)['"]''', 1, True)[0] ) if not videoUrl.startswith('http'): continue params = dict(cItem) params.update({'title':title + ' ' + eTitle, 'url':videoUrl, 'icon':icon, 'desc':desc}) self.addVideo(params) def getLinksForVideo(self, cItem): printDBG("CartoonME.getLinksForVideo [%s]" % cItem) urlTab = [] if '9cartoon.me' not in cItem['url']: return [{'name':'', 'url':cItem['url'], 'need_resolve':1}] sts, data = self.getPage(cItem['url']) if not sts: return [] data = self.cm.ph.getDataBeetwenMarkers(data, '#player_load', 'success', False)[1] url = self.cm.ph.getSearchGroups(data, '''url: ['"]([^'^"]+?)['"]''')[0] post_data = self.cm.ph.getSearchGroups(data, '''data: ['"]([^"^']+?)['"]''')[0] sts, data = self.getPage(url, {'raw_post_data':True, 'header':{'Content-Type':'application/x-www-form-urlencoded; charset=UTF-8', 'X-Requested-With':'XMLHttpRequest'}}, post_data) if not sts: return [] printDBG(data) tmp = self.cm.ph.getDataBeetwenMarkers(data, 'Download', '<script ', False)[1] tmp = re.compile('''<a[^>]+?href=['"](http[^"^']+?)['"][^>]*?>([^<]+?)<''').findall(tmp) for item in tmp: urlTab.append({'name':item[1], 'url':item[0], 'need_resolve':1}) if 0 == len(urlTab): tmp = self.cm.ph.getDataBeetwenMarkers(data, 'player', '</script>', False)[1] if 'docid=' in tmp: docid = self.cm.ph.getSearchGroups(tmp, '''['"]([a-zA-Z0-9_-]{28})['"]''')[0] if docid != '': url = 'https://video.google.com/get_player?docid=%s&authuser=&eurl=%s' % (docid, urllib.quote(cItem['url'])) urlTab.append({'name':'video.google.com', 'url':url, 'need_resolve':1}) return urlTab def getVideoLinks(self, videoUrl): printDBG("CartoonME.getVideoLinks [%s]" % videoUrl) urlTab = [] if '/vload/' in videoUrl or 'redirector.googlevideo.com' in videoUrl: header = {'Referer':videoUrl, 'User-Agent':self.USER_AGENT, 'Accept':'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language':'pl,en-US;q=0.7,en;q=0.3', 'Accept-Encoding':'gzip, deflate'} params= {'return_data':False, 'use_cookie': True, 'save_cookie': True, 'load_cookie': True, 'cookiefile': self.COOKIE_FILE, 'header':header} try: sts, response = self.cm.getPage(videoUrl, params) url = response.geturl() response.close() urlTab.append({'name':'', 'url':url, 'need_resolve':0}) except Exception: printExc() elif videoUrl.startswith('http'): urlTab = self.up.getVideoLinkExt(videoUrl) return urlTab def listSearchResult(self, cItem, searchPattern, searchType): printDBG("CartoonME.listSearchResult cItem[%s], searchPattern[%s] searchType[%s]" % (cItem, searchPattern, searchType)) page = cItem.get('page', 1) cItem = dict(cItem) cItem['url'] = self.SEARCH_URL + urllib.quote_plus(searchPattern) self.listItems1(cItem, 'list_episodes') if 0 == len(self.currList): self.listEpisodes(cItem) def handleService(self, index, refresh = 0, searchPattern = '', searchType = ''): printDBG('handleService start') CBaseHostClass.handleService(self, index, refresh, searchPattern, searchType) name = self.currItem.get("name", '') category = self.currItem.get("category", '') mode = self.currItem.get("mode", '') printDBG( "handleService: |||||||||||||||||||||||||||||||||||| name[%s], category[%s] " % (name, category) ) self.currList = [] #MAIN MENU if name == None: self.listsTab(self.MAIN_CAT_TAB, {'name':'category'}) elif category == 'categories': self.listCategories(self.currItem, 'list_items_1') if category == 'list_items_1': self.listItems1(self.currItem, 'list_episodes') elif category == 'list_types': self.listCartoonListTypes(self.currItem, 'list_letters') elif category == 'list_letters': self.listLetters(self.currItem, 'list_items_2') if category == 'list_items_2': self.listItems2(self.currItem, 'list_episodes') if category == 'list_episodes': self.listEpisodes(self.currItem) #SEARCH elif category in ["search", "search_next_page"]: cItem = dict(self.currItem) cItem.update({'search_item':False, 'name':'category'}) self.listSearchResult(cItem, searchPattern, searchType) #HISTORIA SEARCH elif category == "search_history": self.listsHistory({'name':'history', 'category': 'search'}, 'desc', _("Type: ")) else: printExc() CBaseHostClass.endHandleService(self, index, refresh) class IPTVHost(CHostBase): def __init__(self): # for now we must disable favourites due to problem with links extraction for types other than movie CHostBase.__init__(self, CartoonME(), True, favouriteTypes=[]) #, [CDisplayListItem.TYPE_VIDEO, CDisplayListItem.TYPE_AUDIO]) def getLinksForVideo(self, Index = 0, selItem = None): retCode = RetHost.ERROR retlist = [] if not self.isValidIndex(Index): return RetHost(retCode, value=retlist) urlList = self.host.getLinksForVideo(self.host.currList[Index]) for item in urlList: retlist.append(CUrlItem(item["name"], item["url"], item['need_resolve'])) return RetHost(RetHost.OK, value = retlist) # end getLinksForVideo def getResolvedURL(self, url): # resolve url to get direct url to video file retlist = [] urlList = self.host.getVideoLinks(url) for item in urlList: need_resolve = 0 retlist.append(CUrlItem(item["name"], item["url"], need_resolve)) return RetHost(RetHost.OK, value = retlist) #def getArticleContent(self, Index = 0): # retCode = RetHost.ERROR # retlist = [] # if not self.isValidIndex(Index): return RetHost(retCode, value=retlist) # # hList = self.host.getArticleContent(self.host.currList[Index]) # for item in hList: # title = item.get('title', '') # text = item.get('text', '') # images = item.get("images", []) # othersInfo = item.get('other_info', '') # retlist.append( ArticleContent(title = title, text = text, images = images, richDescParams = othersInfo) ) # return RetHost(RetHost.OK, value = retlist) def converItem(self, cItem): hostList = [] searchTypesOptions = [] # ustawione alfabetycznie #searchTypesOptions.append((_("Movies"), "movie")) #searchTypesOptions.append((_("TV Shows"), "tv_shows")) hostLinks = [] type = CDisplayListItem.TYPE_UNKNOWN possibleTypesOfSearch = None if 'category' == cItem['type']: if cItem.get('search_item', False): type = CDisplayListItem.TYPE_SEARCH possibleTypesOfSearch = searchTypesOptions else: type = CDisplayListItem.TYPE_CATEGORY elif cItem['type'] == 'video': type = CDisplayListItem.TYPE_VIDEO elif 'more' == cItem['type']: type = CDisplayListItem.TYPE_MORE elif 'audio' == cItem['type']: type = CDisplayListItem.TYPE_AUDIO if type in [CDisplayListItem.TYPE_AUDIO, CDisplayListItem.TYPE_VIDEO]: url = cItem.get('url', '') if '' != url: hostLinks.append(CUrlItem("Link", url, 1)) title = cItem.get('title', '') description = cItem.get('desc', '') icon = self.host.getIconUrl( cItem.get('icon', '') ) return CDisplayListItem(name = title, description = description, type = type, urlItems = hostLinks, urlSeparateRequest = 1, iconimage = icon, possibleTypesOfSearch = possibleTypesOfSearch) # end converItem

[ "[email protected]" ]

[email protected]

d96e3355e5e62406b5e4338cbe35b7eaa929bbac

de24f83a5e3768a2638ebcf13cbe717e75740168

/moodledata/vpl_data/48/usersdata/102/16157/submittedfiles/estatistica.py

09d01593ac5da824c14d1683c4b56411be6a6d17

[]

no_license

rafaelperazzo/programacao-web

95643423a35c44613b0f64bed05bd34780fe2436

170dd5440afb9ee68a973f3de13a99aa4c735d79

refs/heads/master

2021-01-12T14:06:25.773146

2017-12-22T16:05:45

69,566,344

0

null

UTF-8

Python

false

926

py

# -*- coding: utf-8 -*- from __future__ import division def media(lista): soma = 0 for i in range(0,len(lista),1): soma = soma + lista[i] media = soma/len(lista) return media #Baseado na função acima, escreva a função para calcular o desvio padrão de uma lista a=[] b=[] n=input('digite a quantidade de elementos :') for i in range(0,n,1): a.append(input('digite um elemento ')) soma=0 for i in range (0,n,1): b.append(input('digite um elemnto ')) media_a= media(a) media_b= media(b) def desviopadrao(lista): soma=0 for i in range (0,len(lista),1): soma=soma+(lista[i]-media(lista))**2 s=((1/(len(lista)-1))*soma)**(1/2) return s s_a=s(a) s_b=s(b) print('%.2f :' %media_a) print('%.2f:'%s_a) print('%.2f:'%media_b) print('%.2f:'%s_b) #Por último escreva o programa principal, que pede a entrada e chama as funções criadas.

[ "[email protected]" ]

[email protected]

13cb23ca4016737d8fd059ed257d80f4cb853250

6be845bf70a8efaf390da28c811c52b35bf9e475

/windows/Resources/Python/Core/Lib/multiprocessing/forking.py

877cae88752b18f508c4d539767e20190edbd9dd

[]

no_license

kyeremalprime/ms

228194910bf2ed314d0492bc423cc687144bb459

47eea098ec735b2173ff0d4e5c493cb8f04e705d

refs/heads/master

2020-12-30T15:54:17.843982

2017-05-14T07:32:01

91,180,709

2

null

UTF-8

Python

false

12,561

py

# uncompyle6 version 2.9.10 # Python bytecode 2.7 (62211) # Decompiled from: Python 3.6.0b2 (default, Oct 11 2016, 05:27:10) # [GCC 6.2.0 20161005] # Embedded file name: forking.py import os import sys import signal from multiprocessing import util, process __all__ = [ 'Popen', 'assert_spawning', 'exit', 'duplicate', 'close', 'ForkingPickler'] def assert_spawning(self): if not Popen.thread_is_spawning(): raise RuntimeError('%s objects should only be shared between processes through inheritance' % type(self).__name__) from pickle import Pickler class ForkingPickler(Pickler): dispatch = Pickler.dispatch.copy() @classmethod def register(cls, type, reduce): def dispatcher(self, obj): rv = reduce(obj) self.save_reduce(obj=obj, *rv) cls.dispatch[type] = dispatcher def _reduce_method(m): if m.im_self is None: return (getattr, (m.im_class, m.im_func.func_name)) else: return ( getattr, (m.im_self, m.im_func.func_name)) return ForkingPickler.register(type(ForkingPickler.save), _reduce_method) def _reduce_method_descriptor(m): return ( getattr, (m.__objclass__, m.__name__)) ForkingPickler.register(type(list.append), _reduce_method_descriptor) ForkingPickler.register(type(int.__add__), _reduce_method_descriptor) try: from functools import partial except ImportError: pass else: def _reduce_partial(p): return (_rebuild_partial, (p.func, p.args, p.keywords or {})) def _rebuild_partial(func, args, keywords): return partial(func, *args, **keywords) ForkingPickler.register(partial, _reduce_partial) if sys.platform != 'win32': import time exit = os._exit duplicate = os.dup close = os.close class Popen(object): def __init__(self, process_obj): sys.stdout.flush() sys.stderr.flush() self.returncode = None self.pid = os.fork() if self.pid == 0: if 'random' in sys.modules: import random random.seed() code = process_obj._bootstrap() sys.stdout.flush() sys.stderr.flush() os._exit(code) return def poll(self, flag=os.WNOHANG): if self.returncode is None: try: pid, sts = os.waitpid(self.pid, flag) except os.error: return if pid == self.pid: if os.WIFSIGNALED(sts): self.returncode = -os.WTERMSIG(sts) else: self.returncode = os.WEXITSTATUS(sts) return self.returncode def wait(self, timeout=None): if timeout is None: return self.poll(0) else: deadline = time.time() + timeout delay = 0.0005 while 1: res = self.poll() if res is not None: break remaining = deadline - time.time() if remaining <= 0: break delay = min(delay * 2, remaining, 0.05) time.sleep(delay) return res def terminate(self): if self.returncode is None: try: os.kill(self.pid, signal.SIGTERM) except OSError as e: if self.wait(timeout=0.1) is None: raise return @staticmethod def thread_is_spawning(): return False else: import thread import msvcrt import _subprocess import time from _multiprocessing import win32, Connection, PipeConnection from .util import Finalize from pickle import load, HIGHEST_PROTOCOL def dump(obj, file, protocol=None): ForkingPickler(file, protocol).dump(obj) TERMINATE = 65536 WINEXE = sys.platform == 'win32' and getattr(sys, 'frozen', False) WINSERVICE = sys.executable.lower().endswith('pythonservice.exe') exit = win32.ExitProcess close = win32.CloseHandle if WINSERVICE: _python_exe = os.path.join(sys.exec_prefix, 'python.exe') else: _python_exe = sys.executable def set_executable(exe): global _python_exe _python_exe = exe def duplicate(handle, target_process=None, inheritable=False): if target_process is None: target_process = _subprocess.GetCurrentProcess() return _subprocess.DuplicateHandle(_subprocess.GetCurrentProcess(), handle, target_process, 0, inheritable, _subprocess.DUPLICATE_SAME_ACCESS).Detach() class Popen(object): """ Start a subprocess to run the code of a process object """ _tls = thread._local() def __init__(self, process_obj): rfd, wfd = os.pipe() rhandle = duplicate(msvcrt.get_osfhandle(rfd), inheritable=True) os.close(rfd) cmd = get_command_line() + [rhandle] cmd = ' '.join(('"%s"' % x for x in cmd)) hp, ht, pid, tid = _subprocess.CreateProcess(_python_exe, cmd, None, None, 1, 0, None, None, None) ht.Close() close(rhandle) self.pid = pid self.returncode = None self._handle = hp prep_data = get_preparation_data(process_obj._name) to_child = os.fdopen(wfd, 'wb') Popen._tls.process_handle = int(hp) try: dump(prep_data, to_child, HIGHEST_PROTOCOL) dump(process_obj, to_child, HIGHEST_PROTOCOL) finally: del Popen._tls.process_handle to_child.close() return @staticmethod def thread_is_spawning(): return getattr(Popen._tls, 'process_handle', None) is not None @staticmethod def duplicate_for_child(handle): return duplicate(handle, Popen._tls.process_handle) def wait(self, timeout=None): if self.returncode is None: if timeout is None: msecs = _subprocess.INFINITE else: msecs = max(0, int(timeout * 1000 + 0.5)) res = _subprocess.WaitForSingleObject(int(self._handle), msecs) if res == _subprocess.WAIT_OBJECT_0: code = _subprocess.GetExitCodeProcess(self._handle) if code == TERMINATE: code = -signal.SIGTERM self.returncode = code return self.returncode def poll(self): return self.wait(timeout=0) def terminate(self): if self.returncode is None: try: _subprocess.TerminateProcess(int(self._handle), TERMINATE) except WindowsError: if self.wait(timeout=0.1) is None: raise return def is_forking(argv): """ Return whether commandline indicates we are forking """ if len(argv) >= 2 and argv[1] == '--multiprocessing-fork': return True else: return False def freeze_support(): """ Run code for process object if this in not the main process """ if is_forking(sys.argv): main() sys.exit() def get_command_line(): """ Returns prefix of command line used for spawning a child process """ if process.current_process()._identity == () and is_forking(sys.argv): raise RuntimeError('\n Attempt to start a new process before the current process\n has finished its bootstrapping phase.\n\n This probably means that you are on Windows and you have\n forgotten to use the proper idiom in the main module:\n\n if __name__ == \'__main__\':\n freeze_support()\n ...\n\n The "freeze_support()" line can be omitted if the program\n is not going to be frozen to produce a Windows executable.') if getattr(sys, 'frozen', False): return [sys.executable, '--multiprocessing-fork'] else: prog = 'from multiprocessing.forking import main; main()' return [ _python_exe, '-c', prog, '--multiprocessing-fork'] def main(): """ Run code specifed by data received over pipe """ handle = int(sys.argv[-1]) fd = msvcrt.open_osfhandle(handle, os.O_RDONLY) from_parent = os.fdopen(fd, 'rb') process.current_process()._inheriting = True preparation_data = load(from_parent) prepare(preparation_data) self = load(from_parent) process.current_process()._inheriting = False from_parent.close() exitcode = self._bootstrap() exit(exitcode) def get_preparation_data(name): """ Return info about parent needed by child to unpickle process object """ from .util import _logger, _log_to_stderr d = dict(name=name, sys_path=sys.path, sys_argv=sys.argv, log_to_stderr=_log_to_stderr, orig_dir=process.ORIGINAL_DIR, authkey=process.current_process().authkey) if _logger is not None: d['log_level'] = _logger.getEffectiveLevel() if not WINEXE and not WINSERVICE: main_path = getattr(sys.modules['__main__'], '__file__', None) if not main_path and sys.argv[0] not in ('', '-c'): main_path = sys.argv[0] if main_path is not None: if not os.path.isabs(main_path) and process.ORIGINAL_DIR is not None: main_path = os.path.join(process.ORIGINAL_DIR, main_path) d['main_path'] = os.path.normpath(main_path) return d def reduce_connection(conn): if not Popen.thread_is_spawning(): raise RuntimeError('By default %s objects can only be shared between processes\nusing inheritance' % type(conn).__name__) return ( type(conn), (Popen.duplicate_for_child(conn.fileno()), conn.readable, conn.writable)) ForkingPickler.register(Connection, reduce_connection) ForkingPickler.register(PipeConnection, reduce_connection) old_main_modules = [] def prepare(data): """ Try to get current process ready to unpickle process object """ old_main_modules.append(sys.modules['__main__']) if 'name' in data: process.current_process().name = data['name'] if 'authkey' in data: process.current_process()._authkey = data['authkey'] if 'log_to_stderr' in data and data['log_to_stderr']: util.log_to_stderr() if 'log_level' in data: util.get_logger().setLevel(data['log_level']) if 'sys_path' in data: sys.path = data['sys_path'] if 'sys_argv' in data: sys.argv = data['sys_argv'] if 'dir' in data: os.chdir(data['dir']) if 'orig_dir' in data: process.ORIGINAL_DIR = data['orig_dir'] if 'main_path' in data: main_path = data['main_path'] main_name = os.path.splitext(os.path.basename(main_path))[0] if main_name == '__init__': main_name = os.path.basename(os.path.dirname(main_path)) if main_name != 'ipython': import imp if main_path is None: dirs = None elif os.path.basename(main_path).startswith('__init__.py'): dirs = [ os.path.dirname(os.path.dirname(main_path))] else: dirs = [ os.path.dirname(main_path)] file, path_name, etc = imp.find_module(main_name, dirs) try: main_module = imp.load_module('__parents_main__', file, path_name, etc) finally: if file: file.close() sys.modules['__main__'] = main_module main_module.__name__ = '__main__' for obj in main_module.__dict__.values(): try: if obj.__module__ == '__parents_main__': obj.__module__ = '__main__' except Exception: pass return

[ "[email protected]" ]

[email protected]

dfd560b021f274cf620269da02b8991453c27075

cf6a50732d708a3a3db0f297b73cb6f449a00b44

/Practice15_Dict_Comprehensions/Prac_15_3_4lists.py

08394fddeab789aa6f4927a312461f0c8229a29e

[]

no_license

subash319/PythonDepth

9fe3920f4b0a25be02a9abbeeb60976853ab812e

0de840b7776009e8e4362d059af14afaac6a8879

refs/heads/master

2022-11-16T03:03:56.874422

2020-07-17T01:19:39

266,921,459

0

null

UTF-8

Python

false

748

py

# # names = ['Ted', 'Sam', 'Jim', 'Rob', 'Anu'] # maths = [98,67,54,88,95] # physics = [88,64,78,99,78] # chemistry = [78,67,45,79,87] # These 4 lists contain the names and marks of students in 3 subjects. # Write a dictionary comprehension to create the following dictionary from the above 4 lists. # { 'Ted': [98, 88, 78], # 'Sam': [67, 64, 67], # 'Jim': [54, 78, 45], # 'Rob': [88, 99, 79], # 'Anu': [95, 78, 87] } names = ['Ted', 'Sam', 'Jim', 'Rob', 'Anu'] maths = [98, 67, 54, 88, 95] physics = [88, 64, 78, 99, 78] chemistry = [78, 67, 45, 79, 87] dict_list = {name : [math_marks, physics_marks, chemistry_marks] for name, math_marks, physics_marks, chemistry_marks in zip(names, maths, physics, chemistry)} print(dict_list)

[ "[email protected]" ]

[email protected]

e8671cf5ba3ec2529608a9c484cbb899180c4e45

439c87c48c6c2c812d1faca73cbf1b632e9403dc

/DAYS/Day23/Frequency_can_become_same.py

e3d4dbf245a9234ce1844db16bb8f4940835985b

[ "MIT" ]

permissive

saubhagyav/100_Days_Code_Challenge

14ca8db68e09c7ac7741f164fea8b62cb36bf2c0

bde41126b9342eacc488c79d01dc4b76a3651c93

refs/heads/main

2023-08-05T03:12:18.918079

2021-09-12T12:20:41

389,375,066

2

null

2021-07-25T15:06:18

2021-07-25T15:06:17

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from collections import Counter def Check_Frequency(Test_string): Test_dict = Counter(Test_string) Result = list(set(Test_dict.values())) if len(Result) > 2: return False elif len(Result) == 2 and Result[1]-Result[0] > 1: return False else: return True Test_string = "xxxyyzz" if Check_Frequency(Test_string): print("Yes") else: print("No")

[ "[email protected]" ]

[email protected]

960ac25a67fbf72976ab75e6b8dbf05281553012

758bf41e46a3093f4923af603f1f7f8063408b9c

/website/testFromRemoteRepo/_bsch3398/museum/python/django/contrib/gis/gdal/__init__.py

7c3a03b42b7bc94fdbb03cfa9c6a54e206c549f2

[ "BSD-3-Clause" ]

permissive

mpetyx/mpetyx.com

4033d97b21c9227a6ba505980fd0c1b57254e8fb

d50c379b4fe09e0135656573f7049225fc90ae36

refs/heads/master

2021-01-10T19:50:15.488371

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""" This module houses ctypes interfaces for GDAL objects. The following GDAL objects are supported: CoordTransform: Used for coordinate transformations from one spatial reference system to another. Driver: Wraps an OGR data source driver. DataSource: Wrapper for the OGR data source object, supports OGR-supported data sources. Envelope: A ctypes structure for bounding boxes (GDAL library not required). OGRGeometry: Object for accessing OGR Geometry functionality. OGRGeomType: A class for representing the different OGR Geometry types (GDAL library not required). SpatialReference: Represents OSR Spatial Reference objects. The GDAL library will be imported from the system path using the default library name for the current OS. The default library path may be overridden by setting `GDAL_LIBRARY_PATH` in your settings with the path to the GDAL C library on your system. GDAL links to a large number of external libraries that consume RAM when loaded. Thus, it may desirable to disable GDAL on systems with limited RAM resources -- this may be accomplished by setting `GDAL_LIBRARY_PATH` to a non-existant file location (e.g., `GDAL_LIBRARY_PATH='/null/path'`; setting to None/False/'' will not work as a string must be given). """ # Attempting to import objects that depend on the GDAL library. The # HAS_GDAL flag will be set to True if the library is present on # the system. try: from django.contrib.gis.gdal.driver import Driver from django.contrib.gis.gdal.datasource import DataSource from django.contrib.gis.gdal.libgdal import gdal_version, gdal_full_version, gdal_release_date, GEOJSON, GDAL_VERSION from django.contrib.gis.gdal.srs import SpatialReference, CoordTransform from django.contrib.gis.gdal.geometries import OGRGeometry HAS_GDAL = True except: HAS_GDAL, GEOJSON = False, False try: from django.contrib.gis.gdal.envelope import Envelope except ImportError: # No ctypes, but don't raise an exception. pass

[ "[email protected]" ]

[email protected]

ff60e6952245ffd8f266b0eaf56ff16ceb153997

d99ac626d62c663704444a9cce7e7fc793a9e75e

/crypto_implementations/virgil-crypto-c/wrappers/python/virgil_crypto_lib/foundation/_c_bridge/_vscf_round5.py

afe300c8a71a0d27ca50895ef9ae32e159be90fd

[ "LicenseRef-scancode-warranty-disclaimer", "BSD-2-Clause", "BSD-3-Clause", "LicenseRef-scancode-unknown-license-reference" ]

permissive

Experiment5X/CryptoFunctionDetection

3ab32d5573a249d24db1faf772721bc80b8d905d

dac700193e7e84963943593e36844b173211a8a1

refs/heads/master

2023-04-19T09:12:35.828268

2021-05-13T22:39:27

355,299,557

1

0

null

UTF-8

Python

false

10,073

py

# Copyright (C) 2015-2020 Virgil Security, Inc. # # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # (1) Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # (2) Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in # the documentation and/or other materials provided with the # distribution. # # (3) Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE AUTHOR ''AS IS'' AND ANY EXPRESS OR # IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, # INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) # HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, # STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING # IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. # # Lead Maintainer: Virgil Security Inc. <[email protected]> from virgil_crypto_lib._libs import * from ctypes import * from ._vscf_impl import vscf_impl_t from ._vscf_error import vscf_error_t from ._vscf_raw_public_key import vscf_raw_public_key_t from ._vscf_raw_private_key import vscf_raw_private_key_t from virgil_crypto_lib.common._c_bridge import vsc_buffer_t from virgil_crypto_lib.common._c_bridge import vsc_data_t class vscf_round5_t(Structure): pass class VscfRound5(object): """Provide post-quantum encryption based on the round5 implementation. For algorithm details check https://github.com/round5/code""" # Defines whether a public key can be imported or not. CAN_IMPORT_PUBLIC_KEY = True # Define whether a public key can be exported or not. CAN_EXPORT_PUBLIC_KEY = True # Define whether a private key can be imported or not. CAN_IMPORT_PRIVATE_KEY = True # Define whether a private key can be exported or not. CAN_EXPORT_PRIVATE_KEY = True def __init__(self): """Create underlying C context.""" self._ll = LowLevelLibs() self._lib = self._ll.foundation def vscf_round5_new(self): vscf_round5_new = self._lib.vscf_round5_new vscf_round5_new.argtypes = [] vscf_round5_new.restype = POINTER(vscf_round5_t) return vscf_round5_new() def vscf_round5_delete(self, ctx): vscf_round5_delete = self._lib.vscf_round5_delete vscf_round5_delete.argtypes = [POINTER(vscf_round5_t)] vscf_round5_delete.restype = None return vscf_round5_delete(ctx) def vscf_round5_use_random(self, ctx, random): vscf_round5_use_random = self._lib.vscf_round5_use_random vscf_round5_use_random.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t)] vscf_round5_use_random.restype = None return vscf_round5_use_random(ctx, random) def vscf_round5_generate_ephemeral_key(self, ctx, key, error): """Generate ephemeral private key of the same type. Note, this operation might be slow.""" vscf_round5_generate_ephemeral_key = self._lib.vscf_round5_generate_ephemeral_key vscf_round5_generate_ephemeral_key.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t), POINTER(vscf_error_t)] vscf_round5_generate_ephemeral_key.restype = POINTER(vscf_impl_t) return vscf_round5_generate_ephemeral_key(ctx, key, error) def vscf_round5_import_public_key(self, ctx, raw_key, error): """Import public key from the raw binary format. Return public key that is adopted and optimized to be used with this particular algorithm. Binary format must be defined in the key specification. For instance, RSA public key must be imported from the format defined in RFC 3447 Appendix A.1.1.""" vscf_round5_import_public_key = self._lib.vscf_round5_import_public_key vscf_round5_import_public_key.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_raw_public_key_t), POINTER(vscf_error_t)] vscf_round5_import_public_key.restype = POINTER(vscf_impl_t) return vscf_round5_import_public_key(ctx, raw_key, error) def vscf_round5_export_public_key(self, ctx, public_key, error): """Export public key to the raw binary format. Binary format must be defined in the key specification. For instance, RSA public key must be exported in format defined in RFC 3447 Appendix A.1.1.""" vscf_round5_export_public_key = self._lib.vscf_round5_export_public_key vscf_round5_export_public_key.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t), POINTER(vscf_error_t)] vscf_round5_export_public_key.restype = POINTER(vscf_raw_public_key_t) return vscf_round5_export_public_key(ctx, public_key, error) def vscf_round5_import_private_key(self, ctx, raw_key, error): """Import private key from the raw binary format. Return private key that is adopted and optimized to be used with this particular algorithm. Binary format must be defined in the key specification. For instance, RSA private key must be imported from the format defined in RFC 3447 Appendix A.1.2.""" vscf_round5_import_private_key = self._lib.vscf_round5_import_private_key vscf_round5_import_private_key.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_raw_private_key_t), POINTER(vscf_error_t)] vscf_round5_import_private_key.restype = POINTER(vscf_impl_t) return vscf_round5_import_private_key(ctx, raw_key, error) def vscf_round5_export_private_key(self, ctx, private_key, error): """Export private key in the raw binary format. Binary format must be defined in the key specification. For instance, RSA private key must be exported in format defined in RFC 3447 Appendix A.1.2.""" vscf_round5_export_private_key = self._lib.vscf_round5_export_private_key vscf_round5_export_private_key.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t), POINTER(vscf_error_t)] vscf_round5_export_private_key.restype = POINTER(vscf_raw_private_key_t) return vscf_round5_export_private_key(ctx, private_key, error) def vscf_round5_kem_shared_key_len(self, ctx, key): """Return length in bytes required to hold encapsulated shared key.""" vscf_round5_kem_shared_key_len = self._lib.vscf_round5_kem_shared_key_len vscf_round5_kem_shared_key_len.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t)] vscf_round5_kem_shared_key_len.restype = c_size_t return vscf_round5_kem_shared_key_len(ctx, key) def vscf_round5_kem_encapsulated_key_len(self, ctx, public_key): """Return length in bytes required to hold encapsulated key.""" vscf_round5_kem_encapsulated_key_len = self._lib.vscf_round5_kem_encapsulated_key_len vscf_round5_kem_encapsulated_key_len.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t)] vscf_round5_kem_encapsulated_key_len.restype = c_size_t return vscf_round5_kem_encapsulated_key_len(ctx, public_key) def vscf_round5_kem_encapsulate(self, ctx, public_key, shared_key, encapsulated_key): """Generate a shared key and a key encapsulated message.""" vscf_round5_kem_encapsulate = self._lib.vscf_round5_kem_encapsulate vscf_round5_kem_encapsulate.argtypes = [POINTER(vscf_round5_t), POINTER(vscf_impl_t), POINTER(vsc_buffer_t), POINTER(vsc_buffer_t)] vscf_round5_kem_encapsulate.restype = c_int return vscf_round5_kem_encapsulate(ctx, public_key, shared_key, encapsulated_key) def vscf_round5_kem_decapsulate(self, ctx, encapsulated_key, private_key, shared_key): """Decapsulate the shared key.""" vscf_round5_kem_decapsulate = self._lib.vscf_round5_kem_decapsulate vscf_round5_kem_decapsulate.argtypes = [POINTER(vscf_round5_t), vsc_data_t, POINTER(vscf_impl_t), POINTER(vsc_buffer_t)] vscf_round5_kem_decapsulate.restype = c_int return vscf_round5_kem_decapsulate(ctx, encapsulated_key, private_key, shared_key) def vscf_round5_setup_defaults(self, ctx): """Setup predefined values to the uninitialized class dependencies.""" vscf_round5_setup_defaults = self._lib.vscf_round5_setup_defaults vscf_round5_setup_defaults.argtypes = [POINTER(vscf_round5_t)] vscf_round5_setup_defaults.restype = c_int return vscf_round5_setup_defaults(ctx) def vscf_round5_generate_key(self, ctx, alg_id, error): """Generate new private key. Note, this operation might be slow.""" vscf_round5_generate_key = self._lib.vscf_round5_generate_key vscf_round5_generate_key.argtypes = [POINTER(vscf_round5_t), c_int, POINTER(vscf_error_t)] vscf_round5_generate_key.restype = POINTER(vscf_impl_t) return vscf_round5_generate_key(ctx, alg_id, error) def vscf_round5_shallow_copy(self, ctx): vscf_round5_shallow_copy = self._lib.vscf_round5_shallow_copy vscf_round5_shallow_copy.argtypes = [POINTER(vscf_round5_t)] vscf_round5_shallow_copy.restype = POINTER(vscf_round5_t) return vscf_round5_shallow_copy(ctx) def vscf_round5_impl(self, ctx): vscf_round5_impl = self._lib.vscf_round5_impl vscf_round5_impl.argtypes = [POINTER(vscf_round5_t)] vscf_round5_impl.restype = POINTER(vscf_impl_t) return vscf_round5_impl(ctx)

[ "[email protected]" ]

[email protected]

703d10b745c8000288c553adcd42e3990d554b8b

1b1a30bfa44ad30fa6fb4ac2e6254d9ff2bf9d46

/keytree/tests/test_write.py

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[]

no_license

imclab/keytree

bff25eee2c8e82aa95062ddbfdda32b0b3a0759b

db7dc932af92d4367bdb934632327c6d9963c2cb

refs/heads/master

2020-12-13T19:14:31.044506

2012-12-28T23:20:06

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from unittest import TestCase from xml.etree import ElementTree as etree from keytree import element KML = """<?xml version="1.0" encoding="UTF-8"?> <kml xmlns="http://www.opengis.net/kml/2.2"> <Document> </Document> </kml> """ class ElementWriterTestCase(TestCase): def setUp(self): self.doc = etree.fromstring(KML) def test_element(self): f = { 'id': '1', 'geometry': {'type': 'Point', 'coordinates': (0.0, 0.0)}, 'properties': { 'title': 'one', 'description': 'Point one' } } elem = element(self.doc, f) self.failUnlessEqual( elem.tag, '{http://www.opengis.net/kml/2.2}Placemark' ) self.failUnlessEqual(elem.attrib['id'], '1') self.failUnlessEqual( elem.find('{http://www.opengis.net/kml/2.2}name').text, 'one' ) self.failUnlessEqual( elem.find('{http://www.opengis.net/kml/2.2}Snippet').text, 'Point one' ) self.failUnlessEqual( elem.find('{http://www.opengis.net/kml/2.2}Point').find( '{http://www.opengis.net/kml/2.2}coordinates').text, '0.000000,0.000000,0.0' ) def test_element_kw(self): f = { 'id': '1', 'geometry': {'type': 'Point', 'coordinates': (0.0, 0.0)}, 'properties': {} } elem = element(self.doc, f, name='one', snippet='Point one') self.failUnlessEqual( elem.tag, '{http://www.opengis.net/kml/2.2}Placemark' ) self.failUnlessEqual(elem.attrib['id'], '1') self.failUnlessEqual( elem.find('{http://www.opengis.net/kml/2.2}name').text, 'one' ) self.failUnlessEqual( elem.find('{http://www.opengis.net/kml/2.2}Snippet').text, 'Point one' )

[ "[email protected]" ]

[email protected]

514a7cb7000a793365eac04a7428ab887b3fab7f

adb759899204e61042225fabb64f6c1a55dac8ce

/14500~14599/14501.py

ffaf69b3c4a49b459ac1f40535dc459b3e8d71b2

[]

no_license

geneeol/baekjoon-online-judge

21cdffc7067481b29b18c09c9152135efc82c40d

2b359aa3f1c90f178d0c86ce71a0580b18adad6f

refs/heads/master

2023-03-28T23:25:12.219487

2021-04-01T09:19:06

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null

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py

# 문제 # 상담원으로 일하고 있는 백준이는 퇴사를 하려고 한다. # 오늘부터 N+1일째 되는 날 퇴사를 하기 위해서, 남은 N일 동안 최대한 많은 상담을 하려고 한다. # 백준이는 비서에게 최대한 많은 상담을 잡으라고 부탁을 했고, 비서는 하루에 하나씩 서로 다른 사람의 상담을 잡아놓았다. # 각각의 상담은 상담을 완료하는데 걸리는 기간 Ti와 상담을 했을 때 받을 수 있는 금액 Pi로 이루어져 있다. # N = 7인 경우에 다음과 같은 상담 일정표를 보자. # 1일 2일 3일 4일 5일 6일 7일 # Ti 3 5 1 1 2 4 2 # Pi 10 20 10 20 15 40 200 # 1일에 잡혀있는 상담은 총 3일이 걸리며, 상담했을 때 받을 수 있는 금액은 10이다. # 5일에 잡혀있는 상담은 총 2일이 걸리며, 받을 수 있는 금액은 15이다. # 상담을 하는데 필요한 기간은 1일보다 클 수 있기 때문에, 모든 상담을 할 수는 없다. # 예를 들어서 1일에 상담을 하게 되면, 2일, 3일에 있는 상담은 할 수 없게 된다. # 2일에 있는 상담을 하게 되면, 3, 4, 5, 6일에 잡혀있는 상담은 할 수 없다. # 또한, N+1일째에는 회사에 없기 때문에, 6, 7일에 있는 상담을 할 수 없다. # 퇴사 전에 할 수 있는 상담의 최대 이익은 1일, 4일, 5일에 있는 상담을 하는 것이며, 이때의 이익은 10+20+15=45이다. # 상담을 적절히 했을 때, 백준이가 얻을 수 있는 최대 수익을 구하는 프로그램을 작성하시오. # 입력 # 첫째 줄에 N (1 ≤ N ≤ 15)이 주어진다. # 둘째 줄부터 N개의 줄에 Ti와 Pi가 공백으로 구분되어서 주어지며, 1일부터 N일까지 순서대로 주어진다. (1 ≤ Ti ≤ 5, 1 ≤ Pi ≤ 1,000) # 출력 # 첫째 줄에 백준이가 얻을 수 있는 최대 이익을 출력한다. n = int(input()) max_pay = [0] * n table = [list(map(int, input().split())) for _ in range(n)] for i in range(n - 1, -1, -1): current_day, current_pay = table[i][0], table[i][1] if current_day > n - i: if i != n - 1: max_pay[i] = max_pay[i + 1] continue if i == n - 1: max_pay[i] = current_pay elif i + current_day == n: max_pay[i] = max(current_pay, max_pay[i + 1]) else: max_pay[i] = max(current_pay + max_pay[i + current_day], max_pay[i + 1]) print(max_pay[0])

[ "[email protected]" ]

[email protected]

db3bddc10e70ca78c44d08749d8653382c4a955e

6ede8ffb96aabbe03feb7e739b645878abd7bc6d

/tensorflow/python/ops/bincount.py

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# Copyright 2020 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # maxlengthations under the License. # ============================================================================== """tf.sparse.bincount ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.python.framework import ops from tensorflow.python.framework import sparse_tensor from tensorflow.python.ops import array_ops from tensorflow.python.ops import check_ops from tensorflow.python.ops import gen_count_ops from tensorflow.python.ops.ragged import ragged_tensor from tensorflow.python.util.tf_export import tf_export @tf_export("sparse.bincount") def sparse_bincount(values, weights=None, axis=0, minlength=None, maxlength=None, binary_output=False, name=None): """Count the number of times an integer value appears in a tensor. This op takes an N-dimensional `Tensor`, `RaggedTensor`, or `SparseTensor`, and returns an N-dimensional int64 SparseTensor where element `[i0...i[axis], j]` contains the number of times the value `j` appears in slice `[i0...i[axis], :]` of the input tensor. Currently, only N=0 and N=-1 are supported. Args: values: A Tensor, RaggedTensor, or SparseTensor whose values should be counted. These tensors must have a rank of 1 or 2. weights: A 1-dimensional Tensor of weights. If specified, the input array is weighted by the weight array, i.e. if a value `n` is found at position `i`, `out[n]` will be increased by `weight[i]` instead of 1. axis: The axis to slice over. Axes at and below `axis` will be flattened before bin counting. Currently, only `0`, and `-1` are supported. If None, all axes will be flattened (identical to passing `0`). minlength: If given, skips `values` that are less than `minlength`, and ensures that the output has a `dense_shape` of at least `minlength` in the inner dimension. maxlength: If given, skips `values` that are greater than or equal to `maxlength`, and ensures that the output has a `dense_shape` of at most `maxlength` in the inner dimension. binary_output: If True, this op will output 1 instead of the number of times a token appears (equivalent to one_hot + reduce_any instead of one_hot + reduce_add). Defaults to False. name: A name for this op. Returns: A SparseTensor with `output.shape = values.shape[:axis] + [N]`, where `N` is * `maxlength` (if set); * `minlength` (if set, and `minlength > reduce_max(values)`); * `0` (if `values` is empty); * `reduce_max(values) + 1` otherwise. Examples: **Bin-counting every item in individual batches** This example takes an input (which could be a Tensor, RaggedTensor, or SparseTensor) and returns a SparseTensor where the value of (i,j) is the number of times value j appears in batch i. >>> data = np.array([[10, 20, 30, 20], [11, 101, 11, 10001]], dtype=np.int64) >>> output = tf.sparse.bincount(data, axis=-1) >>> print(output) SparseTensor(indices=tf.Tensor( [[ 0 10] [ 0 20] [ 0 30] [ 1 11] [ 1 101] [ 1 10001]], shape=(6, 2), dtype=int64), values=tf.Tensor([1 2 1 2 1 1], shape=(6,), dtype=int64), dense_shape=tf.Tensor([ 2 10002], shape=(2,), dtype=int64)) **Bin-counting with defined output shape** This example takes an input (which could be a Tensor, RaggedTensor, or SparseTensor) and returns a SparseTensor where the value of (i,j) is the number of times value j appears in batch i. However, all values of j above 'maxlength' are ignored. The dense_shape of the output sparse tensor is set to 'minlength'. Note that, while the input is identical to the example above, the value '10001' in batch item 2 is dropped, and the dense shape is [2, 500] instead of [2,10002] or [2, 102]. >>> minlength = maxlength = 500 >>> data = np.array([[10, 20, 30, 20], [11, 101, 11, 10001]], dtype=np.int64) >>> output = tf.sparse.bincount( ... data, axis=-1, minlength=minlength, maxlength=maxlength) >>> print(output) SparseTensor(indices=tf.Tensor( [[ 0 10] [ 0 20] [ 0 30] [ 1 11] [ 1 101]], shape=(5, 2), dtype=int64), values=tf.Tensor([1 2 1 2 1], shape=(5,), dtype=int64), dense_shape=tf.Tensor([ 2 500], shape=(2,), dtype=int64)) **Binary bin-counting** This example takes an input (which could be a Tensor, RaggedTensor, or SparseTensor) and returns a SparseTensor where (i,j) is 1 if the value j appears in batch i at least once and is 0 otherwise. Note that, even though some values (like 20 in batch 1 and 11 in batch 2) appear more than once, the 'values' tensor is all 1s. >>> data = np.array([[10, 20, 30, 20], [11, 101, 11, 10001]], dtype=np.int64) >>> output = tf.sparse.bincount(data, binary_output=True, axis=-1) >>> print(output) SparseTensor(indices=tf.Tensor( [[ 0 10] [ 0 20] [ 0 30] [ 1 11] [ 1 101] [ 1 10001]], shape=(6, 2), dtype=int64), values=tf.Tensor([1 1 1 1 1 1], shape=(6,), dtype=int64), dense_shape=tf.Tensor([ 2 10002], shape=(2,), dtype=int64)) **Weighted bin-counting** This example takes two inputs - a values tensor and a weights tensor. These tensors must be identically shaped, and have the same row splits or indices in the case of RaggedTensors or SparseTensors. When performing a weighted count, the op will output a SparseTensor where the value of (i, j) is the sum of the values in the weight tensor's batch i in the locations where the values tensor has the value j. In this case, the output dtype is the same as the dtype of the weights tensor. >>> data = np.array([[10, 20, 30, 20], [11, 101, 11, 10001]], dtype=np.int64) >>> weights = [[2, 0.25, 15, 0.5], [2, 17, 3, 0.9]] >>> output = tf.sparse.bincount(data, weights=weights, axis=-1) >>> print(output) SparseTensor(indices=tf.Tensor( [[ 0 10] [ 0 20] [ 0 30] [ 1 11] [ 1 101] [ 1 10001]], shape=(6, 2), dtype=int64), values=tf.Tensor([2. 0.75 15. 5. 17. 0.9], shape=(6,), dtype=float32), dense_shape=tf.Tensor([ 2 10002], shape=(2,), dtype=int64)) """ with ops.name_scope(name, "count", [values, weights]): if not isinstance(values, sparse_tensor.SparseTensor): values = ragged_tensor.convert_to_tensor_or_ragged_tensor( values, name="values") if weights is not None: if not isinstance(weights, sparse_tensor.SparseTensor): weights = ragged_tensor.convert_to_tensor_or_ragged_tensor( weights, name="weights") if weights is not None and binary_output: raise ValueError("binary_output and weights are mutually exclusive.") if axis is None: axis = 0 if axis not in [0, -1]: raise ValueError("Unsupported axis value %s. Only 0 and -1 are currently " "supported." % axis) minlength_value = minlength if minlength is not None else -1 maxlength_value = maxlength if maxlength is not None else -1 if axis == 0: if isinstance(values, sparse_tensor.SparseTensor): if weights is not None: weights = validate_sparse_weights(values, weights) values = values.values elif isinstance(values, ragged_tensor.RaggedTensor): if weights is not None: weights = validate_ragged_weights(values, weights) values = values.values else: if weights is not None: weights = array_ops.reshape(weights, [-1]) values = array_ops.reshape(values, [-1]) if isinstance(values, sparse_tensor.SparseTensor): weights = validate_sparse_weights(values, weights) c_ind, c_val, c_shape = gen_count_ops.sparse_count_sparse_output( values.indices, values.values, values.dense_shape, weights, minlength=minlength_value, maxlength=maxlength_value, binary_output=binary_output) elif isinstance(values, ragged_tensor.RaggedTensor): weights = validate_ragged_weights(values, weights) c_ind, c_val, c_shape = gen_count_ops.ragged_count_sparse_output( values.row_splits, values.values, weights, minlength=minlength_value, maxlength=maxlength_value, binary_output=binary_output) else: weights = validate_dense_weights(values, weights) c_ind, c_val, c_shape = gen_count_ops.dense_count_sparse_output( values, weights=weights, minlength=minlength_value, maxlength=maxlength_value, binary_output=binary_output) return sparse_tensor.SparseTensor(c_ind, c_val, c_shape) def validate_dense_weights(values, weights): """Validates the passed weight tensor or creates an empty one.""" if weights is None: return array_ops.constant([], dtype=values.dtype) if not isinstance(weights, ops.Tensor): raise ValueError( "`weights` must be a tf.Tensor if `values` is a tf.Tensor.") return weights def validate_sparse_weights(values, weights): """Validates the passed weight tensor or creates an empty one.""" if weights is None: return array_ops.constant([], dtype=values.values.dtype) if not isinstance(weights, sparse_tensor.SparseTensor): raise ValueError( "`weights` must be a SparseTensor if `values` is a SparseTensor.") checks = [] if weights.dense_shape is not values.dense_shape: checks.append( check_ops.assert_equal( weights.dense_shape, values.dense_shape, message="'weights' and 'values' must have the same dense shape.")) if weights.indices is not values.indices: checks.append( check_ops.assert_equal( weights.indices, values.indices, message="'weights' and 'values' must have the same indices.") ) if checks: with ops.control_dependencies(checks): weights = array_ops.identity(weights.values) else: weights = weights.values return weights def validate_ragged_weights(values, weights): """Validates the passed weight tensor or creates an empty one.""" if weights is None: return array_ops.constant([], dtype=values.values.dtype) if not isinstance(weights, ragged_tensor.RaggedTensor): raise ValueError( "`weights` must be a RaggedTensor if `values` is a RaggedTensor.") checks = [] if weights.row_splits is not values.row_splits: checks.append( check_ops.assert_equal( weights.row_splits, values.row_splits, message="'weights' and 'values' must have the same row splits.")) if checks: with ops.control_dependencies(checks): weights = array_ops.identity(weights.values) else: weights = weights.values return weights

[ "[email protected]" ]

[email protected]

d6cd28ae361ec931ad2dfaf604fbe17836bc2e04

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num = 10 def plus(): print(num) num += 1 plus()

[ "[email protected]" ]

[email protected]

eae1209cde503300621b2e4cd63576ae312a868e

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wusanshou2017/Leetcode

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class Solution: def coinChange(self, coins: [int], amount: int) -> int: dp = [0] + [float("inf")] *amount for coin in coins: for i in range (coin , amount+1): dp[i] = min (dp[i], dp[i-coin]+1) return dp[amount] if dp[amount]!= float("inf") else -1 so =Solution() print (so.coinChange())

[ "[email protected]" ]

[email protected]

6828a17057599731cc595b26995b3930f8a78e82

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/uncertainty_baselines/models/vit_mimo.py

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# coding=utf-8 # Copyright 2023 The Uncertainty Baselines 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. """MIMO Vision Transformer model.""" from typing import Any, Optional, Tuple import flax.linen as nn import jax import jax.numpy as jnp from uncertainty_baselines.models import vit Array = Any PRNGKey = Any Shape = Tuple[int] Dtype = Any class VisionTransformerMIMO(nn.Module): """MIMO Vision Transformer model.""" num_classes: int patches: Any transformer: Any hidden_size: int ensemble_size: int representation_size: Optional[int] = None classifier: str = 'token' fix_base_model: bool = False @nn.compact def __call__(self, inputs, *, train): """Function of shapes [B*R,h,w,c*E] -> [E*B*R,num_classes].""" out = {} x = inputs # We can merge s2d+emb into a single conv; it's the same. x = nn.Conv( features=self.hidden_size, kernel_size=self.patches.size, strides=self.patches.size, padding='VALID', name='embedding')( x) # Here, x is a grid of embeddings. # TODO(dusenberrymw): Switch to self.sow(.). out['stem'] = x # Transformer. n, h, w, c = x.shape x = jnp.reshape(x, [n, h * w, c]) # If we want to add a class token, add it here. if self.classifier == 'token': cls = self.param('cls', nn.initializers.zeros, (1, 1, c)) cls = jnp.tile(cls, [n, 1, 1]) x = jnp.concatenate([cls, x], axis=1) x = vit.Encoder(name='Transformer', **self.transformer)(x, train=train) out['transformed'] = x if self.classifier == 'token': x = x[:, 0] elif self.classifier == 'gap': x = jnp.mean(x, axis=list(range(1, x.ndim - 1))) # (1,) or (1,2) else: raise ValueError(f'Invalid classifier={self.classifier}') out['head_input'] = x if self.representation_size is not None: x = nn.Dense(features=self.representation_size, name='pre_logits')(x) out['pre_logits'] = x x = nn.tanh(x) else: x = vit.IdentityLayer(name='pre_logits')(x) out['pre_logits'] = x # TODO(markcollier): Fix base model without using stop_gradient. if self.fix_base_model: x = jax.lax.stop_gradient(x) # Shape: (batch_size, num_classes * ensemble_size). x = nn.Dense(self.num_classes * self.ensemble_size, name='head', kernel_init=nn.initializers.zeros)(x) # Shape: (batch_size * ensemble_size, num_classes). x = jnp.concatenate(jnp.split(x, self.ensemble_size, axis=-1)) out['logits'] = x return x, out def vision_transformer_mimo(num_classes: int, patches: Any, transformer: Any, hidden_size: int, ensemble_size: int, representation_size: Optional[int] = None, classifier: str = 'token', fix_base_model: bool = False): """Builds a BatchEnsemble Vision Transformer (ViT) model.""" # TODO(dusenberrymw): Add API docs once the config dict in VisionTransformerBE # is cleaned up. return VisionTransformerMIMO( num_classes=num_classes, patches=patches, transformer=transformer, hidden_size=hidden_size, ensemble_size=ensemble_size, representation_size=representation_size, classifier=classifier, fix_base_model=fix_base_model)

[ "[email protected]" ]

[email protected]

b7f7076f5afb4e3428632e25750722c00706b99e

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/scripts/match_districts.py

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meilinger/firecares

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import glob import os import sys sys.path.append(os.pardir) from firecares.firestation.management.commands.match_districts import Command from firecares.firestation.models import FireDepartment, FireStation from django.contrib.gis.geos import GeometryCollection as GC import django django.setup() files = glob.glob(sys.argv[1]+'*districts*.geojson') parsed_files = [(n.split('-')[1].upper(), n.split('-')[2], n) for n in files] for state, name, path in parsed_files: department = None try: department = FireDepartment.priority_departments.get(state=state, name__icontains=name.replace('_', ' ')) except FireDepartment.DoesNotExist: if name == 'los_angeles_city': department = FireDepartment.objects.get(id=87256) c = Command() c.handle(geojson_file=path, queryset=department.firestation_set.all()) geometry_collection = GC([n for n in department.firestation_set.all().values_list('district', flat=True) if n]) map(geometry_collection.append, [n for n in department.firestation_set.all().values_list('geom', flat=True) if n]) with open(os.path.join(sys.argv[1], 'processed', 'us-{0}-{1}-disticts_processed.geojson'.format(state.lower(), name, department.name.replace(' ', '_').lower())), 'w') as output: output.write(geometry_collection.json)

[ "[email protected]" ]

[email protected]

fdc77083dbf90bdb66b304f6e10d6aff7b96f4ab

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/common/logic/fish_array_3.py

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[]

no_license

rolllyroman/fish_

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refs/heads/master

2020-03-28T00:51:06.565231

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#!/usr/bin/env python # -*- coding:utf-8 -*- """ Author: $Author$ Date: $Date$ Revision: $Revision$ Description: 鱼阵3，等间距环形鱼阵 """ from common.data.scene import WIDTH, HEIGHT, CENTER_X, CENTER_Y from common.data.fish_init_areas import FishInitArea from common.arith.point_math import Point from common.data.fish_levels import FISH_LEVELS_DATA from common.data.pickfish_consts import TOLERATE_LAG_SECS import fish_array from common.gameobject import GameObject import random import math from common.pb_utils import pbAppendRoute class FishArrayInit(GameObject): def __init__(self, initArea, fishLevels, space, speed, counts): self.initArea = initArea self.fishLevels = fishLevels self.space = space self.speed = speed self.counts = counts class FishArray(fish_array.FishArray): def __init__(self, fishMgr): super(FishArray, self).__init__(fishMgr) #基础速度 self.speed = 54 #每个环间鱼的间距 self.space = -20 self.init_areas = [ #左边的环 FishArrayInit(FishInitArea(Point(0, CENTER_Y), Point(0, CENTER_Y), Point(WIDTH, CENTER_Y), Point(WIDTH, CENTER_Y)), [[3], [7], [12], [16]], self.space, self.speed, [48, 30, 12, 1]), \ #右边的环 FishArrayInit(FishInitArea(Point(WIDTH, CENTER_Y), Point(WIDTH, CENTER_Y), Point(0, CENTER_Y), Point(0, CENTER_Y)), [[3], [7], [12], [17]], self.space, self.speed, [48, 30, 12, 1]), \ ] def genFishs(self): self.genFishDatas = [] centerNLevelNRadius = [] for area in self.init_areas: centerP, direct, endP = area.initArea.getPointNDirect() count = len(area.fishLevels) levelNedges = [] for i in xrange(count): space = self.space level = random.choice(area.fishLevels[i]) levelData = FISH_LEVELS_DATA[level] if i == count - 1: centerP = centerP + (-direct) * (levelData.width/2.0) levelNedges.append((level, centerP)) else: width = levelData.width if i == count - 2: width = width/4.0 space = self.space * 2 elif i == 0: space = self.space else: space = self.space / 2 centerP = centerP + (-direct) * (width/2.0) levelNedges.append((level, centerP)) centerP = centerP + (-direct) * (width/2.0 + space) levelNRadius = [] for level, edgeP in levelNedges: levelNRadius.append((level, centerP.getDist(edgeP))) centerNLevelNRadius.append((centerP, levelNRadius)) longestDuration = 0 for idx, area in enumerate(self.init_areas): centerP, levelNRadius = centerNLevelNRadius[idx] initP, direct, endP = area.initArea.getPointNDirect() #获取初始角度 rad = direct.toRadian() initRot = math.degrees(rad) for i in xrange(len(levelNRadius)): level, radius = levelNRadius[i] deltaAngle = (math.pi*2)/area.counts[i] levelData = FISH_LEVELS_DATA[level] for i in xrange(area.counts[i]): offsetDir = direct.rotateSelfByRadian(deltaAngle*i).normalize() startP = centerP + (offsetDir*radius) curEndP = Point(endP.x, startP.y) + direct * (levelData.width/2.0) duration = curEndP.getDist(startP)/area.speed #优化，把初始化位置都设到屏幕外半个身位 realStartP = Point(initP.x, startP.y) + (-direct) * (levelData.width/2.0) realDuration = curEndP.getDist(realStartP)/area.speed if duration > longestDuration: longestDuration = duration self.genFishDatas.append(fish_array.FishInitData(0, level, levelData.order, initRot, \ realStartP.x, realStartP.y, realDuration, levelData.getMulti(), levelData.getPickedRate(), 0, \ pbAppendRoute([], 0, area.speed, realDuration + TOLERATE_LAG_SECS), \ fish_array.FISH_ARRAY_APPEAR_TICK + (duration - realDuration)*1000)) self.duration = longestDuration + TOLERATE_LAG_SECS super(FishArray, self).genFishs()

[ "[email protected]" ]

[email protected]

b1e07b55cc88e5fa72d84564acadc485d25057d2

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/colour/models/rgb/transfer_functions/nikon_nlog.py

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nodefeet/colour

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py

""" Nikon N-Log Log Encoding ======================== Defines the *Nikon N-Log* log encoding: - :func:`colour.models.log_encoding_NLog` - :func:`colour.models.log_decoding_NLog` References ---------- - :cite:`Nikon2018` : Nikon. (2018). N-Log Specification Document - Version 1.0.0 (pp. 1-5). Retrieved September 9, 2019, from http://download.nikonimglib.com/archive3/hDCmK00m9JDI03RPruD74xpoU905/\ N-Log_Specification_(En)01.pdf """ from __future__ import annotations import numpy as np from colour.algebra import spow from colour.hints import ( Boolean, FloatingOrArrayLike, FloatingOrNDArray, Integer, ) from colour.models.rgb.transfer_functions import full_to_legal, legal_to_full from colour.utilities import Structure, as_float, from_range_1, to_domain_1 __author__ = "Colour Developers" __copyright__ = "Copyright 2013 Colour Developers" __license__ = "New BSD License - http://opensource.org/licenses/BSD-3-Clause" __maintainer__ = "Colour Developers" __email__ = "[email protected]" __status__ = "Production" __all__ = [ "NLOG_CONSTANTS", "log_encoding_NLog", "log_decoding_NLog", ] NLOG_CONSTANTS: Structure = Structure( cut1=0.328, cut2=(452 / 1023), a=(650 / 1023), b=0.0075, c=(150 / 1023), d=(619 / 1023), ) """*Nikon N-Log* colourspace constants.""" def log_encoding_NLog( in_r: FloatingOrArrayLike, bit_depth: Integer = 10, out_normalised_code_value: Boolean = True, in_reflection: Boolean = True, constants: Structure = NLOG_CONSTANTS, ) -> FloatingOrNDArray: """ Define the *Nikon N-Log* log encoding curve / opto-electronic transfer function. Parameters ---------- in_r Linear reflection data :math`in`. bit_depth Bit depth used for conversion. out_normalised_code_value Whether the non-linear *Nikon N-Log* data :math:`out` is encoded as normalised code values. in_reflection Whether the light level :math`in` to a camera is reflection. constants *Nikon N-Log* constants. Returns ------- :class:`numpy.floating` or :class:`numpy.ndarray` Non-linear data :math:`out`. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``in_r`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``out_r`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`Nikon2018` Examples -------- >>> log_encoding_NLog(0.18) # doctest: +ELLIPSIS 0.3636677... """ in_r = to_domain_1(in_r) if not in_reflection: in_r = in_r * 0.9 cut1 = constants.cut1 a = constants.a b = constants.b c = constants.c d = constants.d out_r = np.where( in_r < cut1, a * spow(in_r + b, 1 / 3), c * np.log(in_r) + d, ) out_r_cv = ( out_r if out_normalised_code_value else legal_to_full(out_r, bit_depth) ) return as_float(from_range_1(out_r_cv)) def log_decoding_NLog( out_r: FloatingOrArrayLike, bit_depth: Integer = 10, in_normalised_code_value: Boolean = True, out_reflection: Boolean = True, constants: Structure = NLOG_CONSTANTS, ) -> FloatingOrNDArray: """ Define the *Nikon N-Log* log decoding curve / electro-optical transfer function. Parameters ---------- out_r Non-linear data :math:`out`. bit_depth Bit depth used for conversion. in_normalised_code_value Whether the non-linear *Nikon N-Log* data :math:`out` is encoded as normalised code values. out_reflection Whether the light level :math`in` to a camera is reflection. constants *Nikon N-Log* constants. Returns ------- :class:`numpy.floating` or :class:`numpy.ndarray` Linear reflection data :math`in`. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``out_r`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``in_r`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`Nikon2018` Examples -------- >>> log_decoding_NLog(0.36366777011713869) # doctest: +ELLIPSIS 0.1799999... """ out_r = to_domain_1(out_r) out_r = ( out_r if in_normalised_code_value else full_to_legal(out_r, bit_depth) ) cut2 = constants.cut2 a = constants.a b = constants.b c = constants.c d = constants.d in_r = np.where( out_r < cut2, spow(out_r / a, 3) - b, np.exp((out_r - d) / c), ) if not out_reflection: in_r = in_r / 0.9 return as_float(from_range_1(in_r))

[ "[email protected]" ]

[email protected]

7e93265e3e2ddc5409ba10e0b89e8c4bba613615

09a2d0231caf5231875270ca85dba3bf201d83c7

/linotak/mentions/migrations/0004_incoming_received.py

1d50965cd7e957d46d12464362c62a542df6d4ea

[]

no_license

pdc/linotak

898c2a014a2f2beed25127efc4b69db637c1a537

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refs/heads/develop

2023-03-09T19:39:59.013308

2022-12-19T19:58:49

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0

null

2023-02-15T20:20:01

2018-09-16T09:54:31

Python

UTF-8

Python

false

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py

# Generated by Django 3.0.8 on 2020-08-30 21:57 from django.db import migrations, models import django.utils.timezone class Migration(migrations.Migration): dependencies = [ ("mentions", "0003_post_i18n"), ] operations = [ migrations.AddField( model_name="incoming", name="received", field=models.DateTimeField( default=django.utils.timezone.now, verbose_name="received" ), ), ]

[ "[email protected]" ]

[email protected]

8e1afacf0cc3e334b5b5e95f56349940f2f1db5d

1eb50735e3861cde4bca8f4feab5afc730003078

/future/tqdm进度条.py

eda322f687b82450a99c954568d587570ce0ebd1

[]

no_license

chinaylssly/fluent-python

442e6458215e3c5a74c4d34d020b714da108f81d

126c1d3e7853628c4a2c0e6ff475362b7d7fe33a

refs/heads/master

2020-04-17T13:58:03.534184

2019-02-01T14:40:42

166,637,609

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null

UTF-8

Python

false

111

py

# -*- coding: utf-8 -*- from time import sleep from tqdm import tqdm for i in tqdm(range(10)): sleep(1)

[ "[email protected]" ]

[email protected]

575b7b48abf22f076b84e4ef15b11103ba8859b5

8cb8bfd2dae516612251039e0632173ea1ea4c8a

/modules/analyzes/door/doorsize/controller.py

9126c599a165028ae6febf61087f048a2c4fb0a5

[]

no_license

nyzsirt/lift-prod

563cc70700d26a5812a1bce0bd9795998dce6e99

9a5f28e49ad5e80e422a5d5efee77a2d0247aa2b

refs/heads/master

2020-04-22T01:05:42.262876

2019-02-09T13:31:15

170,003,361

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2019-02-10T17:11:50

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from abstracts.abstract_resource_controller import AbstractResourceController from modules.analyzes.door.doorsize.models import DoorSize from modules.helper2 import helper class ControllerDoorSize(AbstractResourceController): def __init__(self): self.helper = helper() self.abstract = super(ControllerDoorSize, self) self.main_model = DoorSize self.default_kwargs = dict() def get(self, get_args): return self.abstract.get(get_args) def create(self, data): return self.abstract.create(data) def update(self, mongoid, data): return self.abstract.update(mongoid, data) def delete(self, mongoid): return self.abstract.delete(mongoid)

[ "[email protected]" ]

[email protected]

6edd0fa849079349ad68374f58ae03751169c5a0

c4ab9448e4df33cc55db85dbf37afb4982edcab4

/isiscb/zotero/migrations/0003_auto_20160218_1614.py

33af73f3ff24f0fde46cfe84682b49e4b6333db4

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

upconsulting/IsisCB

659c1293b3606fb797611e138deb234b41c617f5

6c20899bf9193cc4cc6b4a2efea24ae86cbc51eb

refs/heads/master

2023-09-01T17:23:14.538601

2023-03-19T21:05:29

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2023-07-30T15:04:05

2015-08-06T12:40:51

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UTF-8

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# -*- coding: utf-8 -*- # Generated by Django 1.9.1 on 2016-02-18 16:14 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('zotero', '0002_auto_20160216_1622'), ] operations = [ migrations.AlterField( model_name='instanceresolutionevent', name='to_instance_id', field=models.CharField(max_length=1000), ), ]

[ "[email protected]" ]

[email protected]

e16cb457cd2bdec0206f1fb45a2bc62bd0834ae8

29d09c634ffdd8cab13631d62bc6e3ad00df49bf

/Algorithm/baekjoon/13023_ABCDE.py

668731e67b568111b79707b4d426bc57551db84d

[]

no_license

kim-taewoo/TIL_PUBLIC

f1d32c3b4f46344c1c99f02e95cc6d2a888a0374

ae86b542f8b1805b5dd103576d6538e3b1f5b9f4

refs/heads/master

2021-09-12T04:22:52.219301

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found = False import sys input = lambda: sys.stdin.readline() def dfs(v, cnt, origin): global found if found: return if cnt == 5: found = True return if cnt > chk_max[origin]: chk_max[origin] = cnt for i in board[v]: if not chk[i]: if chk_max[i]: if cnt + chk_max[i] < 5: continue chk[i] = True dfs(i, cnt + 1, origin) chk[i] = False n,m = map(int, input().split()) board = [set() for _ in range(n)] for i in range(m): a, b = map(int, input().split()) board[a].add(b) board[b].add(a) chk_max = [0 for _ in range(n)] chk = [False for _ in range(n)] for i in range(n): if found: break chk[i] = True dfs(i, 1, i) chk[i] = False if found: print(1) else: print(0)

[ "[email protected]" ]

[email protected]

d4cbaf36b608ec4f75a9244c59fad4ff17838dba

620d21623a300821e2a195eed5434bac67fb4dca

/abb_experimental_ws/build/abb_irb2400_moveit_config/catkin_generated/pkg.develspace.context.pc.py

bad71f63564b6113dd733b4f2835133b33daf66a

[]

no_license

yazici/Robarch-dev

bb63c04bd2e62386e7c1215bf5b116ccd763c455

9f8db4c418db3fc80454200cb6625cc2b2151382

refs/heads/master

2020-05-21T02:32:06.765535

2018-09-07T15:50:26

null

0

null

UTF-8

Python

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457

py

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "abb_irb2400_moveit_config" PROJECT_SPACE_DIR = "/home/jrv/Research/RoboticArcitecture/abb_experimental_ws/devel/.private/abb_irb2400_moveit_config" PROJECT_VERSION = "1.2.1"

[ "[email protected]" ]

[email protected]

5601aff2121e0430b64554af7112f5143e683c7f

e3365bc8fa7da2753c248c2b8a5c5e16aef84d9f

/indices/nnsurveyor.py

0f79817f723f9553af007d8121d2638228c52f5a

[]

no_license

psdh/WhatsintheVector

e8aabacc054a88b4cb25303548980af9a10c12a8

a24168d068d9c69dc7a0fd13f606c080ae82e2a6

refs/heads/master

2021-01-25T10:34:22.651619

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ii = [('CookGHP3.py', 1), ('RogePAV2.py', 1), ('CoolWHM2.py', 1), ('RogePAV.py', 1), ('RennJIT.py', 2), ('MartHSI2.py', 1), ('MarrFDI3.py', 1), ('PeckJNG.py', 5), ('FitzRNS3.py', 4), ('ClarGE2.py', 2), ('AinsWRR3.py', 1), ('CoolWHM.py', 1), ('ClarGE.py', 3), ('LyelCPG.py', 3), ('CrocDNL.py', 1), ('WadeJEB.py', 20), ('BachARE.py', 5), ('MereHHB3.py', 3), ('MereHHB.py', 1), ('FitzRNS4.py', 2), ('CoolWHM3.py', 5), ('FitzRNS.py', 11), ('FerrSDO.py', 1), ('MereHHB2.py', 4), ('JacoWHI.py', 1), ('ClarGE3.py', 6), ('FitzRNS2.py', 7), ('EvarJSP.py', 1), ('LyelCPG3.py', 2)]

[ "[email protected]" ]

[email protected]

137ce9f638c8cbef7f90ef43a198d1e2bbff6f71

b1152e66088975211a7b3ae61f68c69630644f4a

/MIX_Graph_Multi_Agent/Attention/attention.py

c49680b7c0cdad91350c6e900a3da5d1bf04167d

[]

no_license

lxjlu/H2G-MAAC

ef09a6f838816ff3b47b71781204dcb1fe11a30b

144542e098932d61b744bf337b3c6637b358a3b7

refs/heads/main

2023-06-21T22:26:22.018345

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import tensorflow as tf def scaled_dot_product_attention(q, k, v, mask): matmul_qk = tf.matmul(q, k, transpose_b=True) # (..., seq_len_q, seq_len_k) # scale matmul_qk dk = tf.cast(tf.shape(k)[-1], tf.float32) scaled_attention_logits = matmul_qk / tf.math.sqrt(dk) # add the mask to the scaled tensor. if mask is not None: scaled_attention_logits += (mask * -1e9) # softmax is normalized on the last axis (seq_len_k) so that the scores # add up to 1. attention_weights = tf.nn.softmax(scaled_attention_logits, axis=-1) # (..., seq_len_q, seq_len_k) output = tf.matmul(attention_weights, v) # (..., seq_len_q, depth_v) return output, attention_weights # ## Multi-head Attention # In[ ]: class MultiHeadAttention(tf.keras.layers.Layer): def __init__(self, d_model, num_heads): super(MultiHeadAttention, self).__init__() self.num_heads = num_heads self.d_model = d_model assert d_model % self.num_heads == 0 self.depth = d_model // self.num_heads self.wq = tf.keras.layers.Dense(d_model) self.wk = tf.keras.layers.Dense(d_model) self.wv = tf.keras.layers.Dense(d_model) self.dense = tf.keras.layers.Dense(d_model) def split_heads(self, x, batch_size): """Split the last dimension into (num_heads, depth). Transpose the result such that the shape is (batch_size, num_heads, seq_len, depth) """ x = tf.reshape(x, (batch_size, -1, self.num_heads, self.depth)) return tf.transpose(x, perm=[0, 2, 1, 3]) def call(self, v, k, q, mask=None): batch_size = tf.shape(q)[0] q = self.wq(q) # (batch_size, seq_len, d_model) k = self.wk(k) # (batch_size, seq_len, d_model) v = self.wv(v) # (batch_size, seq_len, d_model) q = self.split_heads(q, batch_size) # (batch_size, num_heads, seq_len_q, depth) k = self.split_heads(k, batch_size) # (batch_size, num_heads, seq_len_k, depth) v = self.split_heads(v, batch_size) # (batch_size, num_heads, seq_len_v, depth) # scaled_attention.shape == (batch_size, num_heads, seq_len_q, depth) # attention_weights.shape == (batch_size, num_heads, seq_len_q, seq_len_k) scaled_attention, attention_weights = scaled_dot_product_attention( q, k, v, mask) scaled_attention = tf.transpose(scaled_attention, perm=[0, 2, 1, 3]) # (batch_size, seq_len_q, num_heads, depth) concat_attention = tf.reshape(scaled_attention, (batch_size, -1, self.d_model)) # (batch_size, seq_len_q, d_model) output = self.dense(concat_attention) # (batch_size, seq_len_q, d_model) return output, attention_weights def main(): temp_mha = MultiHeadAttention(d_model=256, num_heads=4) q = tf.random.uniform((64, 1, 60)) # (batch_size, encoder_sequence, d_model) k = tf.random.uniform((64, 10, 60)) # (batch_size, encoder_sequence, d_model) out, attn = temp_mha(k, k=k, q=q, mask=None) print(out.shape, attn.shape) if __name__ == '__main__': main()

[ "[email protected]" ]

[email protected]

7f457300765fa9938e6a03720e657ddbc14780bf

33836016ea99776d31f7ad8f2140c39f7b43b5fe

/fip_collab/2017_01_18_predict_bulk_other_regressors/transform.py

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[]

no_license

earthexploration/MKS-Experimentation

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refs/heads/master

2023-03-17T23:11:11.313693

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import functions as rr import numpy as np # from sklearn.decomposition import PCA from constants import const import time import h5py def transform(ns, set_id, pca): st = time.time() C = const() n_corr = C['cmax'] f_red = h5py.File("spatial_reduced_L%s.hdf5" % C['H'], 'a') f_stats = h5py.File("spatial_L%s.hdf5" % C['H'], 'r') ff = f_stats.get('ff_%s' % set_id)[...] ff = ff.reshape(ns, n_corr*C['vmax']**3) ff_red = pca.transform(ff) f_red.create_dataset('reduced_%s' % set_id, data=ff_red, dtype='float64') f_red.close() f_stats.close() """calculate the error incurred in the PCA representation""" ff_ = pca.inverse_transform(ff_red) err = np.sqrt(np.sum((ff-ff_)**2))/ff.size msg = "PCA representation error for %s: %s" % (set_id, err) rr.WP(msg, C['wrt_file']) timeE = np.round(time.time()-st, 2) msg = "transform to low dimensional space, %s: %s s" % (set_id, timeE) rr.WP(msg, C['wrt_file']) if __name__ == '__main__': ns = 10 set_id = 'random' reduce(ns, set_id)

[ "[email protected]" ]

[email protected]

350f64bc1b133699e73ca47c6c2a94e3069fb404

43ede7b8fb546c00804c0ef94501f6e48ba170d6

/Cursos Python/Python 3 - João Batista/Coleções.py

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bopopescu/Python-13

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c8bef500f2d3e4a63d850f96dfa219eff2ecebda

refs/heads/master

2022-11-22T16:24:08.490879

2020-06-11T14:22:24

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0

null

2020-07-23T02:26:31

2020-07-23T02:26:30

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# # Listas # lista = ['eduardo - 0', 'atila - 1', 'lebiste - 2'] # # # print(lista) # # # # for i in lista: # # print(i) # # # print(lista[0]) # # lista.append('Erickson - 3') # # ['eduardo - 0', 'atila - 1', 'lebiste - 2', 'Erickson - 3'] # lista.insert(1, 'Lucas') # # print(dir(lista)) # # # Tuplas # tupla = (10, 20, 30) # # for loop in tupla: # if loop == 30: # print('show', loop) dicionario = {'numeros': [num for num in range(10)], 'segunda chave': 'segundo valor '} print(dicionario.get('numeros'))

[ "[email protected]" ]

[email protected]

b8a111842e89df90bce5aefed525fe7b800362c2

b25c4a44e5d33d4d2acf98219b0fbac324bad6c7

/Lv0__16_to_30/29.시저 암호.py

bc49a0dc8c9ad2fa45459fa03b81bf3f1b5989ab

[]

no_license

itwebMJ/algorithmStudy

409d46bfa4d0b63d7137a0c64dd09c640dc99460

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refs/heads/main

2023-07-12T18:08:45.157261

2021-08-29T12:45:45

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null

UTF-8

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916

py

''' 시저 암호 어떤 문장의 각 알파벳을 일정한 거리만큼 밀어서 다른 알파벳으로 바꾸는 암호화 방식을 시저 암호라고 합니다. 예를 들어 "AB"는 1만큼 밀면 "BC"가 되고, 3만큼 밀면 "DE"가 됩니다. "z"는 1만큼 밀면 "a"가 됩니다. 문자열 s와 거리 n을 입력받아 s를 n만큼 민 암호문을 만드는 함수, solution을 완성해 보세요. ''' def solution(s, n): answer = '' up = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' low = up.lower() s_list = [] for i in s: s_list.append(i) for j in range(len(s_list)): if s_list[j] in up: idx = up.index(s_list[j]) answer += up[int((idx + n) % 26)] elif s_list[j] in low: idx = low.index(s_list[j]) answer += low[int((idx + n) % 26)] elif s_list[j] == ' ': answer += ' ' return answer

[ "[email protected]" ]

[email protected]

df40bafe036762bbfa75bb8eeaedc532d98f0d1e

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/gi-stubs/repository/Vips/Combine.py

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[]

no_license

ttys3/pygobject-stubs

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refs/heads/master

2022-09-23T12:58:44.526554

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null

2020-06-05T15:57:54

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UTF-8

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py

# encoding: utf-8 # module gi.repository.Vips # from /usr/lib64/girepository-1.0/Vips-8.0.typelib # by generator 1.147 """ An object which wraps an introspection typelib. This wrapping creates a python module like representation of the typelib using gi repository as a foundation. Accessing attributes of the module will dynamically pull them in and create wrappers for the members. These members are then cached on this introspection module. """ # imports import gi as __gi import gi.overrides.GObject as __gi_overrides_GObject import gobject as __gobject class Combine(__gobject.GEnum): # no doc def as_integer_ratio(self): # real signature unknown; restored from __doc__ """ Return integer ratio. Return a pair of integers, whose ratio is exactly equal to the original int and with a positive denominator. >>> (10).as_integer_ratio() (10, 1) >>> (-10).as_integer_ratio() (-10, 1) >>> (0).as_integer_ratio() (0, 1) """ pass def bit_length(self): # real signature unknown; restored from __doc__ """ Number of bits necessary to represent self in binary. >>> bin(37) '0b100101' >>> (37).bit_length() 6 """ pass def conjugate(self, *args, **kwargs): # real signature unknown """ Returns self, the complex conjugate of any int. """ pass def from_bytes(self, *args, **kwargs): # real signature unknown """ Return the integer represented by the given array of bytes. bytes Holds the array of bytes to convert. The argument must either support the buffer protocol or be an iterable object producing bytes. Bytes and bytearray are examples of built-in objects that support the buffer protocol. byteorder The byte order used to represent the integer. If byteorder is 'big', the most significant byte is at the beginning of the byte array. If byteorder is 'little', the most significant byte is at the end of the byte array. To request the native byte order of the host system, use `sys.byteorder' as the byte order value. signed Indicates whether two's complement is used to represent the integer. """ pass def to_bytes(self, *args, **kwargs): # real signature unknown """ Return an array of bytes representing an integer. length Length of bytes object to use. An OverflowError is raised if the integer is not representable with the given number of bytes. byteorder The byte order used to represent the integer. If byteorder is 'big', the most significant byte is at the beginning of the byte array. If byteorder is 'little', the most significant byte is at the end of the byte array. To request the native byte order of the host system, use `sys.byteorder' as the byte order value. signed Determines whether two's complement is used to represent the integer. If signed is False and a negative integer is given, an OverflowError is raised. """ pass def __abs__(self, *args, **kwargs): # real signature unknown """ abs(self) """ pass def __add__(self, *args, **kwargs): # real signature unknown """ Return self+value. """ pass def __and__(self, *args, **kwargs): # real signature unknown """ Return self&value. """ pass def __bool__(self, *args, **kwargs): # real signature unknown """ self != 0 """ pass def __ceil__(self, *args, **kwargs): # real signature unknown """ Ceiling of an Integral returns itself. """ pass def __delattr__(self, *args, **kwargs): # real signature unknown """ Implement delattr(self, name). """ pass def __dir__(self, *args, **kwargs): # real signature unknown """ Default dir() implementation. """ pass def __divmod__(self, *args, **kwargs): # real signature unknown """ Return divmod(self, value). """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __float__(self, *args, **kwargs): # real signature unknown """ float(self) """ pass def __floordiv__(self, *args, **kwargs): # real signature unknown """ Return self//value. """ pass def __floor__(self, *args, **kwargs): # real signature unknown """ Flooring an Integral returns itself. """ pass def __format__(self, *args, **kwargs): # real signature unknown pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __getnewargs__(self, *args, **kwargs): # real signature unknown pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __index__(self, *args, **kwargs): # real signature unknown """ Return self converted to an integer, if self is suitable for use as an index into a list. """ pass def __init_subclass__(self, *args, **kwargs): # real signature unknown """ This method is called when a class is subclassed. The default implementation does nothing. It may be overridden to extend subclasses. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass def __int__(self, *args, **kwargs): # real signature unknown """ int(self) """ pass def __invert__(self, *args, **kwargs): # real signature unknown """ ~self """ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lshift__(self, *args, **kwargs): # real signature unknown """ Return self<<value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass def __mod__(self, *args, **kwargs): # real signature unknown """ Return self%value. """ pass def __mul__(self, *args, **kwargs): # real signature unknown """ Return self*value. """ pass def __neg__(self, *args, **kwargs): # real signature unknown """ -self """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __or__(self, *args, **kwargs): # real signature unknown """ Return self|value. """ pass def __pos__(self, *args, **kwargs): # real signature unknown """ +self """ pass def __pow__(self, *args, **kwargs): # real signature unknown """ Return pow(self, value, mod). """ pass def __radd__(self, *args, **kwargs): # real signature unknown """ Return value+self. """ pass def __rand__(self, *args, **kwargs): # real signature unknown """ Return value&self. """ pass def __rdivmod__(self, *args, **kwargs): # real signature unknown """ Return divmod(value, self). """ pass def __reduce_ex__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __rfloordiv__(self, *args, **kwargs): # real signature unknown """ Return value//self. """ pass def __rlshift__(self, *args, **kwargs): # real signature unknown """ Return value<<self. """ pass def __rmod__(self, *args, **kwargs): # real signature unknown """ Return value%self. """ pass def __rmul__(self, *args, **kwargs): # real signature unknown """ Return value*self. """ pass def __ror__(self, *args, **kwargs): # real signature unknown """ Return value|self. """ pass def __round__(self, *args, **kwargs): # real signature unknown """ Rounding an Integral returns itself. Rounding with an ndigits argument also returns an integer. """ pass def __rpow__(self, *args, **kwargs): # real signature unknown """ Return pow(value, self, mod). """ pass def __rrshift__(self, *args, **kwargs): # real signature unknown """ Return value>>self. """ pass def __rshift__(self, *args, **kwargs): # real signature unknown """ Return self>>value. """ pass def __rsub__(self, *args, **kwargs): # real signature unknown """ Return value-self. """ pass def __rtruediv__(self, *args, **kwargs): # real signature unknown """ Return value/self. """ pass def __rxor__(self, *args, **kwargs): # real signature unknown """ Return value^self. """ pass def __setattr__(self, *args, **kwargs): # real signature unknown """ Implement setattr(self, name, value). """ pass def __sizeof__(self, *args, **kwargs): # real signature unknown """ Returns size in memory, in bytes. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __subclasshook__(self, *args, **kwargs): # real signature unknown """ Abstract classes can override this to customize issubclass(). This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached). """ pass def __sub__(self, *args, **kwargs): # real signature unknown """ Return self-value. """ pass def __truediv__(self, *args, **kwargs): # real signature unknown """ Return self/value. """ pass def __trunc__(self, *args, **kwargs): # real signature unknown """ Truncating an Integral returns itself. """ pass def __xor__(self, *args, **kwargs): # real signature unknown """ Return self^value. """ pass denominator = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """the denominator of a rational number in lowest terms""" imag = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """the imaginary part of a complex number""" numerator = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """the numerator of a rational number in lowest terms""" real = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """the real part of a complex number""" value_name = property(lambda self: object(), lambda self, v: None, lambda self: None) # default value_nick = property(lambda self: object(), lambda self, v: None, lambda self: None) # default LAST = 3 MAX = 0 MIN = 2 SUM = 1 __class__ = type __dict__ = None # (!) real value is "mappingproxy({'__module__': 'gi.repository.Vips', '__dict__': <attribute '__dict__' of 'Combine' objects>, '__doc__': None, '__gtype__': <GType VipsCombine (94317410467168)>, '__enum_values__': {0: <enum VIPS_COMBINE_MAX of type Vips.Combine>, 1: <enum VIPS_COMBINE_SUM of type Vips.Combine>, 2: <enum VIPS_COMBINE_MIN of type Vips.Combine>, 3: <enum VIPS_COMBINE_LAST of type Vips.Combine>}, '__info__': gi.EnumInfo(Combine), 'MAX': <enum VIPS_COMBINE_MAX of type Vips.Combine>, 'SUM': <enum VIPS_COMBINE_SUM of type Vips.Combine>, 'MIN': <enum VIPS_COMBINE_MIN of type Vips.Combine>, 'LAST': <enum VIPS_COMBINE_LAST of type Vips.Combine>})" __enum_values__ = { 0: 0, 1: 1, 2: 2, 3: 3, } __gtype__ = None # (!) real value is '<GType VipsCombine (94317410467168)>' __info__ = gi.EnumInfo(Combine)

[ "[email protected]" ]

[email protected]

e8d44fcc8ab38010d57edd595269bffa26a9b608

6c791df92e63f8f1ba579c0aa326a7fdc9cfbf19

/Recheck/Test_Grad_Descent.py

f1b2aac7d945649530f9e92d50d4d83273d3c1a4

[]

no_license

krm9c/BDHeterogeneity

5261ca874d2923da3d1320ac1b02e23b23e8d64a

eabb9bcedbe0cf580c6391eeaf455a675803970a

refs/heads/master

2020-03-22T10:22:59.038734

2019-02-12T22:43:15

139,898,726

0

null

UTF-8

Python

false

5,040

py

# The test file import os os.environ['CUDA_VISIBLE_DEVICES'] = ' ' import Class_Recheck as NN_class import tensorflow as tf import numpy as np import traceback import random ################################################################################### def iterate_minibatches(inputs, targets, batchsize, shuffle=False): assert inputs.shape[0] == targets.shape[0] if shuffle: indices = np.arange(inputs.shape[0]) np.random.shuffle(indices) for start_idx in range(0, inputs.shape[0] - batchsize + 1, batchsize): if shuffle: excerpt = indices[start_idx:start_idx + batchsize] else: excerpt = slice(start_idx, start_idx + batchsize) yield inputs[excerpt], targets[excerpt] ################################################################################### def return_dict(placeholder, List, model, batch_x, batch_y, lr): S ={} for i, element in enumerate(List): S[placeholder[i]] = element S[model.Deep['FL_layer_10']] = batch_x S[model.classifier['Target'] ] = batch_y S[model.classifier["learning_rate"]] = lr return S #################################################################################### def sample_Z(X, m, n, kappa): # return(X+np.random.uniform(-2, 2, size=[m, n])) return ((X+np.random.normal(0,1, size=[m, n]))) #################################################################################### def Analyse_custom_Optimizer_GDR_old(X_train, y_train, X_test, y_test, kappa): import gc # Lets start with creating a model and then train batch wise. model = NN_class.learners() depth = [] depth.append(X_train.shape[1]) L = [100 for i in xrange(1)] depth.extend(L) lr = 0.001 model = model.init_NN_custom(classes, lr, depth, tf.nn.relu) try: t = xrange(Train_Glob_Iterations) from tqdm import tqdm for i in tqdm(t): ########### mini-batch learning update batch_number = 0 #for batch in iterate_minibatches(X_train, y_train, Train_batch_size, shuffle=True): for k in xrange(100): x_batch =[] y_batch =[] arr = random.sample(range(0, len(X_train)), 64) for idx in arr: x_batch.append(X_train[idx]) y_batch.append(y_train[idx]) batch_xs = np.asarray(x_batch) batch_ys = np.asarray(y_batch) model.sess.run([model.Trainer["Weight_op"]],\ feed_dict={model.Deep['FL_layer_10']: batch_xs, model.classifier['Target']: \ batch_ys, model.classifier["learning_rate"]:lr}) if i%20== 0: print "Step", i X_test_perturbed = sample_Z(X_test, X_test.shape[0], X_test.shape[1], kappa=0) print( "Accuracies", model.sess.run([model.Evaluation['accuracy']], \ feed_dict={model.Deep['FL_layer_10']: X_test_perturbed, model.classifier['Target']:\ y_test, model.classifier["learning_rate"]:lr}), model.sess.run([ model.Evaluation['accuracy']],\ feed_dict={model.Deep['FL_layer_10']: X_train, model.classifier['Target']:\ y_train}) ) # batch_number = batch_number + 1; # batch_xs, batch_ys = batch # batch_xs_pert =sample_Z(batch_xs, batch_xs.shape[0], batch_xs.shape[1], kappa=1)0 # model.sess.run([model.Trainer["Weight_op"]],\ # feed_dict={model.Deep['FL_layer_10']: batch_xs, model.classifier['Target']: \ # batch_ys, model.classifier["learning_rate"]:lr}) # if j % 1 == 0: # print(model.sess.run([model.Evaluation['accuracy'] ],\ # feed_dict={model.Deep['FL_layer_10']: X_test, model.classifier['Target']: \ # y_test, model.classifier["learning_rate"]:lr}) ) except Exception as e: print("I found an exception", e) traceback.print_exc() tf.reset_default_graph() del model gc.collect() return 0 ####################################################################################################### ################################ Parameters and function call########################################## ####################################################################################################### # Setup the parameters and call the functions Train_batch_size = 64 Train_Glob_Iterations = 501 Train_noise_Iterations = 1 from tqdm import tqdm from tensorflow.examples.tutorials.mnist import input_data classes = 4 mnist = input_data.read_data_sets("../MNIST_data/", one_hot=True) X_train = mnist.train.images X_test = mnist.test.images y_train = mnist.train.labels y_test = mnist.test.labels iterat_kappa = 1 Kappa_s = np.random.uniform(0, 1, size=[iterat_kappa]) Analyse_custom_Optimizer_GDR_old(X_train, y_train, X_test, y_test, Kappa_s[0])

[ "[email protected]" ]

[email protected]

d8f8e08efb7e0e9134c5ee0f78f8b256b26822b1

eae3d77ac72c168cee7701462f1fc45d7d4dcd91

/2115_벌꿀채취.py

a196922576c19447850463993fc206b2387b3b9a

[]

no_license

ByeongjunCho/Algorithm-TIL

ed2f018d50bd2483bd1175ff9bf7e91913c14766

ad79125a1498915fe97c1d57ee6860b06c410958

refs/heads/master

2022-07-19T15:12:23.689319

2020-05-18T08:37:09

256,399,493

0

null

UTF-8

Python

false

1,769

py

# SWEA 2115. [모의 SW 역량테스트] 벌꿀채취 def makemaxmap(): for i in range(N): for j in range(N-M+1): makeMaxSubset(i, j, 0, 0, 0) # i: 행, j: 열, cnt: 고려한원소수 # sum: 부분집합에 속한 원소의 합 # powSum: 부분집합에 속한 원소의 이익 def makeMaxSubset(i, j, cnt, sum, powSum): if sum > C: # 부분집합의 합은 목표량C를 초과하면 리턴 return if cnt == M: if maxMap[i][j-M] < powSum: maxMap[i][j - M] = powSum return # 선택 makeMaxSubset(i, j+1, cnt+1, sum+arr[i][j], powSum+(arr[i][j]**2)) # 비선택 makeMaxSubset(i, j + 1, cnt + 1, sum, powSum) def getMaxBenefit(): max = 0 # 조합적 선택후 최대이익값 temp = 0 # 1. 일꾼 A를 기준으로 선택 for i in range(N): for j in range(N-M+1): # 2. 일꾼 B 선택 # 2.1 같은행 기준 for j2 in range(j+M, N-M+1): temp = maxMap[i][j] + maxMap[i][j2] if max < temp: max = temp # 다음행부터 마지막까지 선택 for i2 in range(i+1, N): for j2 in range(N-M+1): temp = maxMap[i][j] + maxMap[i2][j2] if max < temp: max = temp return max T = int(input()) for tc in range(1, T+1): N, M, C = map(int, input().split()) arr = [list(map(int, input().split())) for _ in range(N)] maxMap = [[0 for _ in range(N)] for _ in range(N)] # 1. 각 위치에서 연속된 M개를 고려해 취할 수 있는 부분집합의 최대값 선택 makemaxmap() # 2. 최대값 출력 print("#{} {}".format(tc, getMaxBenefit()))

[ "[email protected]" ]

[email protected]

8579ba110a3dfce9e5b310a76a8b8b051ef5e561

a8544cedbec52f929e91e617a5f484d987352525

/src/tests/src/technique/transitive/test_transitive_calculator.py

3947a0e6a65c93529e95fe334898ef0a291bc475

[]

no_license

thearod5/Tracer

75df513ee2500bffc32c29139983990867239369

67ee3d7296fb4c788c111387b335ab9804815655

refs/heads/master

2023-05-31T13:53:34.640103

2021-06-18T01:00:10

349,507,401

1

0

null

2021-06-18T01:00:10

2021-03-19T17:41:37

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import numpy as np from api.extension.cache import Cache from api.technique.definitions.direct.calculator import DirectTechniqueData from api.technique.definitions.transitive.calculator import ( TransitiveTechniqueCalculator, TransitiveTechniqueData, append_direct_component_matrices, perform_transitive_aggregation, perform_transitive_aggregation_on_component_techniques, ) from api.technique.variationpoints.aggregation.aggregation_method import ( AggregationMethod, ) from tests.res.test_technique_helper import SimilarityMatrixMock, TestTechniqueHelper class TestIntermediateCalculationPipeline(TestTechniqueHelper): matrices = [ np.array([[0, 1, 0]]), np.array([[0], [1], [0]]), np.array([[0, 1], [0, 0]]), ] """ IntermediatePipeline """ def test_transitive_pipeline(self): counter_func, counter_dict = self.create_counter_func( self.get_transitive_definition().get_name() ) pipeline_funcs = [counter_func, counter_func] pipeline = TransitiveTechniqueCalculator( self.get_transitive_definition(), pipeline_funcs ) pipeline.run_pipeline_on_dataset(self.dataset) self.assertEqual(len(pipeline_funcs), counter_dict["value"]) """ IndirectTechniqueCalculator """ def test_transitive_technique_calculator_use_case(self): calculator = TransitiveTechniqueCalculator(self.get_transitive_definition()) technique_data = calculator.calculate_technique_data(self.dataset) matrix = technique_data.similarity_matrix self.assertEqual((1, 3), matrix.shape) """ calculate_technique_data """ def test_calculate_technique_data(self): original = Cache.CACHE_ON Cache.CACHE_ON = False def counter_func(data: DirectTechniqueData): data.similarity_matrix = SimilarityMatrixMock() pipeline_funcs = [counter_func] calculator = TransitiveTechniqueCalculator( self.get_transitive_definition(), pipeline_funcs ) technique_data = calculator.calculate_technique_data(self.dataset) self.assertEqual(self.dataset.name, technique_data.dataset.name) self.assertEqual( self.get_transitive_definition().get_name(), technique_data.technique.get_name(), ) self.assertIsNotNone(technique_data.similarity_matrix) Cache.CACHE_ON = original """ perform_transitive_aggregation """ def test_perform_transitive_aggregation(self): data = TransitiveTechniqueData( self.dataset, self.get_traced_transitive_definition() ) append_direct_component_matrices(data) perform_transitive_aggregation(data) self.assertEqual((1, 3), data.similarity_matrix.shape) self.assertEqual(1, data.similarity_matrix[0][0]) self.assertEqual(0, data.similarity_matrix[0][1]) self.assertEqual(1, data.similarity_matrix[0][2]) """ perform_transitive_aggregation_on_matrices """ def test_perform_transitive_aggregation_on_matrices(self): result = perform_transitive_aggregation_on_component_techniques( self.matrices, AggregationMethod.MAX ) self.assertEqual((1, 2), result.shape) self.assertEqual(1, result[0][1]) self.assertEqual(1, result.sum(axis=1).sum())

[ "[email protected]" ]

[email protected]

04e7c82d6bad587dcfbeabc467b229e6e694a43f

e121dcc5d23e225891420e730549b9cc7ebe8e88

/python/lib/direct/tkwidgets/Slider.py

71247acf6b23c510cf7a8708e9c291e631990509

[ "BSD-3-Clause", "BSD-2-Clause" ]

permissive

PlumpMath/panda3d-3

4f4cf7627eddae9b7f30795e0a0657b01fdf670d

5c0be0e1cd46b422d28d5b81ffb1e8b28c3ac914

refs/heads/master

2021-01-25T06:55:36.209044

2014-09-29T14:24:53

null

0

null

UTF-8

Python

false

19,536

py

""" Slider Class: Velocity style controller for floating point values with a label, entry (validated), and min/max slider """ __all__ = ['Slider', 'SliderWidget', 'rgbPanel'] from panda3d.direct.showbase.TkGlobal import * from Tkinter import * from Valuator import Valuator, rgbPanel, VALUATOR_MINI, VALUATOR_FULL from panda3d.direct.task import Task import math, sys, string import operator, Pmw from panda3d.pandac import ClockObject class Slider(Valuator): """ Valuator widget which includes an min/max slider and an entry for setting floating point values in a range """ def __init__(self, parent = None, **kw): INITOPT = Pmw.INITOPT optiondefs = ( ('min', 0.0, self.setMin), ('max', 100.0, self.setMax), ('style', VALUATOR_MINI, INITOPT), ) self.defineoptions(kw, optiondefs) Valuator.__init__(self, parent) # Can not enter None for min or max, update propertyDict to reflect self.propertyDict['min']['fNone'] = 0 self.propertyDict['min']['help'] = 'Minimum allowable value.' self.propertyDict['max']['fNone'] = 0 self.propertyDict['max']['help'] = 'Maximum allowable value.' self.initialiseoptions(Slider) def createValuator(self): self._valuator = self.createcomponent( 'valuator', (('slider', 'valuator'),), None, SliderWidget, (self.interior(),), style = self['style'], command = self.setEntry, value = self['value']) #self._valuator._widget.bind('<Double-ButtonPress-1>', self.mouseReset) # Add popup bindings to slider widget try: self._valuator._arrowBtn.bind( '<ButtonPress-3>', self._popupValuatorMenu) except AttributeError: pass self._valuator._minLabel.bind( '<ButtonPress-3>', self._popupValuatorMenu) self._valuator._maxLabel.bind( '<ButtonPress-3>', self._popupValuatorMenu) def packValuator(self): if self['style'] == VALUATOR_FULL: if self._label: self._label.grid(row = 0, column = 0, sticky = EW) self._entry.grid(row = 0, column = 1, sticky = EW) self._valuator.grid(row = 1, columnspan = 2, padx = 2, pady = 2, sticky = 'ew') self.interior().columnconfigure(0, weight = 1) else: if self._label: self._label.grid(row=0, column=0, sticky = EW) self._entry.grid(row=0, column=1, sticky = EW) self._valuator.grid(row=0, column=2, padx = 2, pady = 2) self.interior().columnconfigure(0, weight = 1) def setMin(self): if self['min'] is not None: self._valuator['min'] = self['min'] def setMax(self): if self['max'] is not None: self._valuator['max'] = self['max'] # Based on Pmw ComboBox code. class SliderWidget(Pmw.MegaWidget): def __init__(self, parent = None, **kw): # Define the megawidget options. INITOPT = Pmw.INITOPT optiondefs = ( # Appearance ('style', VALUATOR_MINI, INITOPT), ('relief', RAISED, self.setRelief), ('borderwidth', 2, self.setBorderwidth), ('background', 'grey75', self.setBackground), ('fliparrow', 0, INITOPT), # Behavior # Bounds ('min', 0.0, self.setMin), ('max', 100.0, self.setMax), # Initial value of slider, use self.set to change value ('value', 0.0, INITOPT), ('numDigits', 2, self.setNumDigits), # Command to execute on slider updates ('command', None, None), # Extra data to be passed to command function ('commandData', [], None), # Callback's to execute during mouse interaction ('preCallback', None, None), ('postCallback', None, None), # Extra data to be passed to callback function, needs to be a list ('callbackData', [], None), ) self.defineoptions(kw, optiondefs) # Initialise the base class (after defining the options). Pmw.MegaWidget.__init__(self, parent) # Create the components. interior = self.interior() # Current value self.value = self['value'] self.formatString = '%2f' self.increment = 0.01 # Interaction flags self._isPosted = 0 self._fUnpost = 0 self._fUpdate = 0 self._firstPress = 1 self._fPressInsde = 0 # Slider dimensions width = 100 self.xPad = xPad = 10 sliderWidth = width + 2 * xPad height = 20 self.left = left = -(width/2.0) self.right = right = (width/2.0) top = -5 bottom = top + height def createSlider(parent): # Create the slider inside the dropdown window. # Min label self._minLabel = Label(parent, text = self['min'], width = 8, anchor = W) self._minLabel.pack(side = LEFT) # Slider widget if self['style'] == VALUATOR_FULL: # Use a scale slider self._widgetVar = DoubleVar() self._widgetVar.set(self['value']) self._widget = self.createcomponent( 'slider', (), None, Scale, (interior,), variable = self._widgetVar, from_ = self['min'], to = self['max'], resolution = 0.0, width = 10, orient = 'horizontal', showvalue = 0, length = sliderWidth, relief = FLAT, bd = 2, highlightthickness = 0) else: # Use a canvas slider self._widget = self.createcomponent( 'slider', (), None, Canvas, (parent,), width = sliderWidth, height = height, bd = 2, highlightthickness = 0, scrollregion = (left - xPad, top, right + xPad, bottom)) # Interaction marker xShift = 1 # Shadow arrow self._marker = self._widget.create_polygon(-7 + xShift, 12, 7 + xShift, 12, xShift, 0, fill = 'black', tags = ('marker',)) # Arrow self._widget.create_polygon(-6.0, 10, 6.0, 10, 0, 0, fill = 'grey85', outline = 'black', tags = ('marker',)) # The indicator self._widget.create_line(left, 0, right, 0, width = 2, tags = ('line',)) self._widget.pack(side = LEFT, expand=1, fill=X) # Max label self._maxLabel = Label(parent, text = self['max'], width = 8, anchor = W) self._maxLabel.pack(side = LEFT) # Create slider if self['style'] == VALUATOR_MINI: # Create the arrow button to invoke slider self._arrowBtn = self.createcomponent( 'arrowbutton', (), None, Canvas, (interior,), borderwidth = 0, relief = FLAT, width = 14, height = 14, scrollregion = (-7, -7, 7, 7)) self._arrowBtn.pack(expand = 1, fill = BOTH) self._arrowBtn.create_polygon(-5, -5, 5, -5, 0, 5, fill = 'grey50', tags = 'arrow') self._arrowBtn.create_line(-5, 5, 5, 5, fill = 'grey50', tags = 'arrow') # Create the dropdown window. self._popup = self.createcomponent( 'popup', (), None, Toplevel, (interior,), relief = RAISED, borderwidth = 2) self._popup.withdraw() self._popup.overrideredirect(1) # Create popup slider createSlider(self._popup) # Bind events to the arrow button. self._arrowBtn.bind('<1>', self._postSlider) self._arrowBtn.bind('<Enter>', self.highlightWidget) self._arrowBtn.bind('<Leave>', self.restoreWidget) # Need to unpost the popup if the arrow Button is unmapped (eg: # its toplevel window is withdrawn) while the popup slider is # displayed. self._arrowBtn.bind('<Unmap>', self._unpostSlider) # Bind events to the dropdown window. self._popup.bind('<Escape>', self._unpostSlider) self._popup.bind('<ButtonRelease-1>', self._widgetBtnRelease) self._popup.bind('<ButtonPress-1>', self._widgetBtnPress) self._popup.bind('<Motion>', self._widgetMove) self._widget.bind('<Left>', self._decrementValue) self._widget.bind('<Right>', self._incrementValue) self._widget.bind('<Shift-Left>', self._bigDecrementValue) self._widget.bind('<Shift-Right>', self._bigIncrementValue) self._widget.bind('<Home>', self._goToMin) self._widget.bind('<End>', self._goToMax) else: createSlider(interior) self._widget['command'] = self._firstScaleCommand self._widget.bind('<ButtonRelease-1>', self._scaleBtnRelease) self._widget.bind('<ButtonPress-1>', self._scaleBtnPress) # Check keywords and initialise options. self.initialiseoptions(SliderWidget) # Adjust relief if not kw.has_key('relief'): if self['style'] == VALUATOR_FULL: self['relief'] = FLAT self.updateIndicator(self['value']) def destroy(self): if (self['style'] == VALUATOR_MINI) and self._isPosted: Pmw.popgrab(self._popup) Pmw.MegaWidget.destroy(self) #====================================================================== # Public methods def set(self, value, fCommand = 1): """ self.set(value, fCommand = 1) Set slider to new value, execute command if fCommand == 1 """ # Send command if any if fCommand and (self['command'] != None): apply(self['command'], [value] + self['commandData']) # Record value self.value = value def get(self): """ self.get() Get current slider value """ return self.value def updateIndicator(self, value): if self['style'] == VALUATOR_MINI: # Get current marker position percentX = (value - self['min'])/float(self['max'] - self['min']) newX = percentX * (self.right - self.left) + self.left markerX = self._getMarkerX() dx = newX - markerX self._widget.move('marker', dx, 0) else: # Update scale's variable, which update scale without # Calling scale's command self._widgetVar.set(value) #====================================================================== # Private methods for slider. def _postSlider(self, event = None): self._isPosted = 1 self._fUpdate = 0 # Make sure that the arrow is displayed sunken. self.interior()['relief'] = SUNKEN self.update_idletasks() # Position popup so that marker is immediately below center of # Arrow button # Find screen space position of bottom/center of arrow button x = (self._arrowBtn.winfo_rootx() + self._arrowBtn.winfo_width()/2.0 - self.interior()['bd']) # string.atoi(self.interior()['bd'])) y = self._arrowBtn.winfo_rooty() + self._arrowBtn.winfo_height() # Popup border width bd = self._popup['bd'] # bd = string.atoi(self._popup['bd']) # Get width of label minW = self._minLabel.winfo_width() # Width of canvas to adjust for cw = (self._getMarkerX() - self.left) + self.xPad popupOffset = bd + minW + cw ch = self._widget.winfo_height() sh = self.winfo_screenheight() # Compensate if too close to edge of screen if y + ch > sh and y > sh / 2: y = self._arrowBtn.winfo_rooty() - ch # Popup window Pmw.setgeometryanddeiconify(self._popup, '+%d+%d' % (x-popupOffset, y)) # Grab the popup, so that all events are delivered to it, and # set focus to the slider, to make keyboard navigation # easier. Pmw.pushgrab(self._popup, 1, self._unpostSlider) self._widget.focus_set() # Ignore the first release of the mouse button after posting the # dropdown slider, unless the mouse enters the dropdown slider. self._fUpdate = 0 self._fUnpost = 0 self._firstPress = 1 self._fPressInsde = 0 def _updateValue(self, event): mouseX = self._widget.canvasx( event.x_root - self._widget.winfo_rootx()) if mouseX < self.left: mouseX = self.left if mouseX > self.right: mouseX = self.right # Update value sf = (mouseX - self.left)/(self.right - self.left) newVal = sf * (self['max'] - self['min']) + self['min'] self.set(newVal) def _widgetBtnPress(self, event): # Check behavior for this button press widget = self._popup xPos = event.x_root - widget.winfo_rootx() yPos = event.y_root - widget.winfo_rooty() fInside = ((xPos > 0) and (xPos < widget.winfo_width()) and (yPos > 0) and (yPos < widget.winfo_height())) # Set flags based upon result if fInside: self._fPressInside = 1 self._fUpdate = 1 if self['preCallback']: apply(self['preCallback'], self['callbackData']) self._updateValue(event) else: self._fPressInside = 0 self._fUpdate = 0 def _widgetMove(self, event): if self._firstPress and not self._fUpdate: canvasY = self._widget.canvasy( event.y_root - self._widget.winfo_rooty()) if canvasY > 0: self._fUpdate = 1 if self['preCallback']: apply(self['preCallback'], self['callbackData']) self._unpostOnNextRelease() elif self._fUpdate: self._updateValue(event) def _scaleBtnPress(self, event): if self['preCallback']: apply(self['preCallback'], self['callbackData']) def _scaleBtnRelease(self, event): # Do post callback if any if self['postCallback']: apply(self['postCallback'], self['callbackData']) def _widgetBtnRelease(self, event): # Do post callback if any if self._fUpdate and self['postCallback']: apply(self['postCallback'], self['callbackData']) if (self._fUnpost or (not (self._firstPress or self._fPressInside))): self._unpostSlider() # Otherwise, continue self._fUpdate = 0 self._firstPress = 0 self._fPressInside = 0 def _unpostOnNextRelease(self, event = None): self._fUnpost = 1 def _unpostSlider(self, event=None): if not self._isPosted: # It is possible to get events on an unposted popup. For # example, by repeatedly pressing the space key to post # and unpost the popup. The <space> event may be # delivered to the popup window even though # Pmw.popgrab() has set the focus away from the # popup window. (Bug in Tk?) return # Restore the focus before withdrawing the window, since # otherwise the window manager may take the focus away so we # can't redirect it. Also, return the grab to the next active # window in the stack, if any. Pmw.popgrab(self._popup) self._popup.withdraw() self._isPosted = 0 # Raise up arrow button self.interior()['relief'] = RAISED def _incrementValue(self, event): self.set(self.value + self.increment) def _bigIncrementValue(self, event): self.set(self.value + self.increment * 10.0) def _decrementValue(self, event): self.set(self.value - self.increment) def _bigDecrementValue(self, event): self.set(self.value - self.increment * 10.0) def _goToMin(self, event): self.set(self['min']) def _goToMax(self, event): self.set(self['max']) def _firstScaleCommand(self, val): """ Hack to avoid calling command on instantiation of Scale """ self._widget['command'] = self._scaleCommand def _scaleCommand(self, val): self.set(string.atof(val)) # Methods to modify floater characteristics def setMin(self): self._minLabel['text'] = self.formatString % self['min'] if self['style'] == VALUATOR_FULL: self._widget['from_'] = self['min'] self.updateIndicator(self.value) def setMax(self): self._maxLabel['text'] = self.formatString % self['max'] if self['style'] == VALUATOR_FULL: self._widget['to'] = self['max'] self.updateIndicator(self.value) def setNumDigits(self): self.formatString = '%0.' + ('%d' % self['numDigits']) + 'f' self._minLabel['text'] = self.formatString % self['min'] self._maxLabel['text'] = self.formatString % self['max'] self.updateIndicator(self.value) self.increment = pow(10, -self['numDigits']) def _getMarkerX(self): # Get marker triangle coordinates c = self._widget.coords(self._marker) # Marker postion defined as X position of third vertex return c[4] def setRelief(self): self.interior()['relief'] = self['relief'] def setBorderwidth(self): self.interior()['borderwidth'] = self['borderwidth'] def setBackground(self): self._widget['background'] = self['background'] def highlightWidget(self, event): self._arrowBtn.itemconfigure('arrow', fill = 'black') def restoreWidget(self, event): self._arrowBtn.itemconfigure('arrow', fill = 'grey50')

[ "[email protected]" ]

[email protected]

75c48e2a11389ce75a618495581d70c80b79da56

09e32f424b4f1e54709b7bc483023c273c28b559

/w4/lucyflowers/lucyflowers.py

eb2fcb9e72ab8e75a0375018f68a92fae82f3361

[]

no_license

lenin2ud/hackerrank

6d4283e4d86ad0778ad19f85f5cb8d4d7d98bff6

7996542d87c32c6fffdc0d005dea92b57a18cd26

refs/heads/master

2021-03-27T04:30:32.732800

2014-06-13T00:10:30

null

0

null

UTF-8

Python

false

1,311

py

# https://www.hackerrank.com/contests/w4/challenges/lucy-and-flowers MOD = 10 ** 9 + 9 MAX_N = 5000 dp = [1] * (MAX_N + 1) inv = [0] * (MAX_N + 1) mem = [0] * (MAX_N + 1) def extended_gcd(aa, bb): lastremainder, remainder = abs(aa), abs(bb) x, lastx, y, lasty = 0, 1, 1, 0 while remainder: lastremainder, (quotient, remainder) = remainder, divmod(lastremainder, remainder) x, lastx = lastx - quotient*x, x y, lasty = lasty - quotient*y, y return lastremainder, lastx * (-1 if aa < 0 else 1), lasty * (-1 if bb < 0 else 1) def modinv(a, m): g, x, y = extended_gcd(a, m) if g != 1: raise ValueError return x % m def precompute(n): for i in range(1, n + 1): r = 0 for j in range(i): r += (dp[j] * dp[i - j - 1]) % MOD dp[i] = r % MOD for i in range(1, MAX_N + 1): inv[i] = modinv(i, MOD) def solve(n): if mem[n] != 0: return mem[n] result = 0 comb = 1 for i in range(1, n + 1): comb = (comb * (n - i + 1) * inv[i]) % MOD result = (result + dp[i] * comb) % MOD mem[n] = result return result if __name__ == '__main__': precompute(MAX_N) T = int(raw_input()) for t in range(T): n = int(raw_input()) print solve(n)

[ "[email protected]" ]

[email protected]

3289fda5e1f37200848fba7f873c3f84f00ef0cf

a6e4a6f0a73d24a6ba957277899adbd9b84bd594

/sdk/python/pulumi_azure_native/automation/v20170515preview/get_source_control.py

bd8cc3a9b818a03ca55f93a52a7bcfd1acd42b85

[ "BSD-3-Clause", "Apache-2.0" ]

permissive

MisinformedDNA/pulumi-azure-native

9cbd75306e9c8f92abc25be3f73c113cb93865e9

de974fd984f7e98649951dbe80b4fc0603d03356

refs/heads/master

2023-03-24T22:02:03.842935

2021-03-08T21:16:19

null

0

null

UTF-8

Python

false

7,646

py

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables __all__ = [ 'GetSourceControlResult', 'AwaitableGetSourceControlResult', 'get_source_control', ] @pulumi.output_type class GetSourceControlResult: """ Definition of the source control. """ def __init__(__self__, auto_sync=None, branch=None, creation_time=None, description=None, folder_path=None, id=None, last_modified_time=None, name=None, publish_runbook=None, repo_url=None, source_type=None, type=None): if auto_sync and not isinstance(auto_sync, bool): raise TypeError("Expected argument 'auto_sync' to be a bool") pulumi.set(__self__, "auto_sync", auto_sync) if branch and not isinstance(branch, str): raise TypeError("Expected argument 'branch' to be a str") pulumi.set(__self__, "branch", branch) if creation_time and not isinstance(creation_time, str): raise TypeError("Expected argument 'creation_time' to be a str") pulumi.set(__self__, "creation_time", creation_time) if description and not isinstance(description, str): raise TypeError("Expected argument 'description' to be a str") pulumi.set(__self__, "description", description) if folder_path and not isinstance(folder_path, str): raise TypeError("Expected argument 'folder_path' to be a str") pulumi.set(__self__, "folder_path", folder_path) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if last_modified_time and not isinstance(last_modified_time, str): raise TypeError("Expected argument 'last_modified_time' to be a str") pulumi.set(__self__, "last_modified_time", last_modified_time) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if publish_runbook and not isinstance(publish_runbook, bool): raise TypeError("Expected argument 'publish_runbook' to be a bool") pulumi.set(__self__, "publish_runbook", publish_runbook) if repo_url and not isinstance(repo_url, str): raise TypeError("Expected argument 'repo_url' to be a str") pulumi.set(__self__, "repo_url", repo_url) if source_type and not isinstance(source_type, str): raise TypeError("Expected argument 'source_type' to be a str") pulumi.set(__self__, "source_type", source_type) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter(name="autoSync") def auto_sync(self) -> Optional[bool]: """ The auto sync of the source control. Default is false. """ return pulumi.get(self, "auto_sync") @property @pulumi.getter def branch(self) -> Optional[str]: """ The repo branch of the source control. Include branch as empty string for VsoTfvc. """ return pulumi.get(self, "branch") @property @pulumi.getter(name="creationTime") def creation_time(self) -> Optional[str]: """ The creation time. """ return pulumi.get(self, "creation_time") @property @pulumi.getter def description(self) -> Optional[str]: """ The description. """ return pulumi.get(self, "description") @property @pulumi.getter(name="folderPath") def folder_path(self) -> Optional[str]: """ The folder path of the source control. """ return pulumi.get(self, "folder_path") @property @pulumi.getter def id(self) -> str: """ Fully qualified resource Id for the resource """ return pulumi.get(self, "id") @property @pulumi.getter(name="lastModifiedTime") def last_modified_time(self) -> Optional[str]: """ The last modified time. """ return pulumi.get(self, "last_modified_time") @property @pulumi.getter def name(self) -> str: """ The name of the resource """ return pulumi.get(self, "name") @property @pulumi.getter(name="publishRunbook") def publish_runbook(self) -> Optional[bool]: """ The auto publish of the source control. Default is true. """ return pulumi.get(self, "publish_runbook") @property @pulumi.getter(name="repoUrl") def repo_url(self) -> Optional[str]: """ The repo url of the source control. """ return pulumi.get(self, "repo_url") @property @pulumi.getter(name="sourceType") def source_type(self) -> Optional[str]: """ The source type. Must be one of VsoGit, VsoTfvc, GitHub. """ return pulumi.get(self, "source_type") @property @pulumi.getter def type(self) -> str: """ The type of the resource. """ return pulumi.get(self, "type") class AwaitableGetSourceControlResult(GetSourceControlResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetSourceControlResult( auto_sync=self.auto_sync, branch=self.branch, creation_time=self.creation_time, description=self.description, folder_path=self.folder_path, id=self.id, last_modified_time=self.last_modified_time, name=self.name, publish_runbook=self.publish_runbook, repo_url=self.repo_url, source_type=self.source_type, type=self.type) def get_source_control(automation_account_name: Optional[str] = None, resource_group_name: Optional[str] = None, source_control_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetSourceControlResult: """ Definition of the source control. :param str automation_account_name: The name of the automation account. :param str resource_group_name: Name of an Azure Resource group. :param str source_control_name: The name of source control. """ __args__ = dict() __args__['automationAccountName'] = automation_account_name __args__['resourceGroupName'] = resource_group_name __args__['sourceControlName'] = source_control_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:automation/v20170515preview:getSourceControl', __args__, opts=opts, typ=GetSourceControlResult).value return AwaitableGetSourceControlResult( auto_sync=__ret__.auto_sync, branch=__ret__.branch, creation_time=__ret__.creation_time, description=__ret__.description, folder_path=__ret__.folder_path, id=__ret__.id, last_modified_time=__ret__.last_modified_time, name=__ret__.name, publish_runbook=__ret__.publish_runbook, repo_url=__ret__.repo_url, source_type=__ret__.source_type, type=__ret__.type)

[ "[email protected]" ]

[email protected]

fd8475f2fa48aed730dfe0df90c3253f83661d75

5d61565651b7ba5fa8fade3313a5e82fca8b6686

/goodstype/forms.py

bab317474e9e54bac606219efd097ee9de0e8a3c

[]

no_license

lonelyxmas/ISMS

d597b00072bfa77907875f575b866fbb1fb53295

08c5e2f3518fc639cf1a1f2869f4b2f3ae58e306

refs/heads/master

2023-08-14T12:02:59.001215

2021-03-22T03:34:58

null

0

null

UTF-8

Python

false

2,013

py

from django.forms import ModelForm from django import forms from django.forms import widgets as Fwidgets from .models import * class GoosTypeModelForm(ModelForm): class Meta: model = goodstype fields = '__all__' widgets = { 'FID': Fwidgets.Input(attrs={'type': 'hidden'}), 'FGoodsTypeID': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FGoodsType': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FDeviationType': Fwidgets.Select(attrs={'lay-verify': 'required'}), 'FPositiveDeviation': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FNegativeDeviation': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FDesc': Fwidgets.Input(attrs={'class': 'layui-input', 'autocomplete': 'off'}) } class SubTypeModelForm(ModelForm): FPID = forms.ChoiceField(widget=forms.Select(attrs={'lay-verify': 'required', 'disabled': 'disabled'}), required=False) class Meta: model = goodstype fields = '__all__' widgets = { 'FID': Fwidgets.Input(attrs={'type': 'hidden'}), 'FGoodsTypeID': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FGoodsType': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FDeviationType': Fwidgets.Select(attrs={'lay-verify': 'required'}), 'FPositiveDeviation': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FNegativeDeviation': Fwidgets.Input(attrs={'class': 'layui-input', 'lay-verify': 'required', 'autocomplete': 'off'}), 'FDesc': Fwidgets.Input(attrs={'class': 'layui-input', 'autocomplete': 'off'}) }

[ "[email protected]" ]

[email protected]