xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

ca13483e057b5c3832eaa8c8bbd1c731f059f862

6,375

py

Python

compmech/stiffpanelbay/tests/test_stiffpanelbay.py

mrosemeier/compmech

f18f6d0471c72b26a3b014d2df41df3463505eae

[ "BSD-3-Clause" ]

4

2019-02-05T06:12:12.000Z

2022-03-25T14:41:18.000Z

compmech/stiffpanelbay/tests/test_stiffpanelbay.py

mrosemeier/compmech

f18f6d0471c72b26a3b014d2df41df3463505eae

[ "BSD-3-Clause" ]

null

compmech/stiffpanelbay/tests/test_stiffpanelbay.py

mrosemeier/compmech

f18f6d0471c72b26a3b014d2df41df3463505eae

[ "BSD-3-Clause" ]

2

2019-06-05T07:19:35.000Z

2020-12-29T00:22:18.000Z

import numpy as np from compmech.stiffpanelbay import StiffPanelBay from compmech.analysis import freq, lb def test_freq_models(): print('Testing frequency analysis for StiffPanelBay with 2 plates') # From Table 4 of # Lee and Lee. "Vibration analysis of anisotropic plates with eccentric # stiffeners". Computers & Structures, Vol. 57, No. 1, pp. 99-105, # 1995. for model in ['plate_clt_donnell_bardell', 'cpanel_clt_donnell_bardell', 'kpanel_clt_donnell_bardell']: spb = StiffPanelBay() spb.a = 0.5 spb.b = 0.250 spb.plyt = 0.00013 spb.laminaprop = (128.e9, 11.e9, 0.25, 4.48e9, 1.53e9, 1.53e9) spb.stack = [0, -45, +45, 90, 90, +45, -45, 0] spb.model = model spb.r = 1.e6 spb.alphadeg = 0. spb.mu = 1.5e3 spb.m = 9 spb.n = 10 # clamping spb.w1rx = 0. spb.w2rx = 0. spb.w1ry = 0. spb.w2ry = 0. spb.add_panel(0, spb.b/2., plyt=spb.plyt) spb.add_panel(spb.b/2., spb.b, plyt=spb.plyt) k0 = spb.calc_k0(silent=True) M = spb.calc_kM(silent=True) eigvals, eigvecs = freq(k0, M, silent=True) ref = [85.12907802-0.j, 134.16422850-0.j, 206.77295186-0.j, 216.45992453-0.j, 252.24546171-0.j] assert np.allclose(eigvals[:5]/2/np.pi, ref, atol=0.1, rtol=0) def test_lb_Stiffener1D(): print('Testing linear buckling for StiffPanelBay with a 1D Stiffener') spb = StiffPanelBay() spb.a = 1. spb.b = 0.5 spb.stack = [0, 90, 90, 0] spb.plyt = 1e-3*0.125 spb.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) spb.model = 'plate_clt_donnell_bardell' spb.mu = 1.3e3 spb.m = 15 spb.n = 16 spb.add_panel(y1=0, y2=spb.b/2., plyt=spb.plyt, Nxx=-1.) spb.add_panel(y1=spb.b/2., y2=spb.b, plyt=spb.plyt, Nxx_cte=1000.) spb.add_bladestiff1d(ys=spb.b/2., Fx=0., bf=0.05, fstack=[0, 90, 90, 0], fplyt=spb.plyt, flaminaprop=spb.laminaprop) k0 = spb.calc_k0(silent=True) kG = spb.calc_kG0(silent=True) eigvals, eigvecs = lb(k0, kG, silent=True) assert np.isclose(eigvals[0].real, 297.54633, atol=0.1, rtol=0) def test_lb_Stiffener2D(): print('Testing linear buckling for StiffPanelBay with a 2D Stiffener') spb = StiffPanelBay() spb.a = 1. spb.b = 0.5 spb.stack = [0, 90, 90, 0] spb.plyt = 1e-3*0.125 spb.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) spb.model = 'plate_clt_donnell_bardell' spb.mu = 1.3e3 spb.m = 15 spb.n = 16 spb.add_panel(y1=0, y2=spb.b/2., plyt=spb.plyt, Nxx=-1.) spb.add_panel(y1=spb.b/2., y2=spb.b, plyt=spb.plyt, Nxx_cte=1000.) spb.add_bladestiff2d(ys=spb.b/2., m1=14, n1=11, bf=0.05, fstack=[0, 90, 90, 0], fplyt=spb.plyt, flaminaprop=spb.laminaprop) k0 = spb.calc_k0(silent=True) kG = spb.calc_kG0(silent=True) eigvals, eigvecs = lb(k0, kG, silent=True) assert np.isclose(eigvals[0].real, 301.0825234, atol=0.1, rtol=0) def test_freq_Stiffener1D(): print('Testing frequency analysis for StiffPanelBay with a 1D Stiffener') spb = StiffPanelBay() spb.a = 2. spb.b = 0.5 spb.stack = [0, 90, 90, 0] spb.plyt = 1e-3*0.125 spb.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) spb.model = 'plate_clt_donnell_bardell' spb.mu = 1.3e3 spb.m = 15 spb.n = 16 spb.add_panel(y1=0, y2=spb.b/2., plyt=spb.plyt) spb.add_panel(y1=spb.b/2., y2=spb.b, plyt=spb.plyt) spb.add_bladestiff1d(ys=spb.b/2., Fx=0., bf=0.08, fstack=[0, 90, 90, 0]*5, fplyt=spb.plyt, flaminaprop=spb.laminaprop) k0 = spb.calc_k0(silent=True) M = spb.calc_kM(silent=True) eigvals, eigvecs = freq(k0, M, silent=True, num_eigvalues=10) assert np.isclose(eigvals[0].real, 79.5906673583, atol=0.1, rtol=0) def test_freq_Stiffener2D(): print('Testing frequency analysis for StiffPanelBay with a 2D Stiffener') spb = StiffPanelBay() spb.a = 1. spb.b = 0.5 spb.stack = [0, 90, 90, 0] spb.plyt = 1e-3*0.125 spb.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) spb.model = 'plate_clt_donnell_bardell' spb.mu = 1.3e3 spb.m = 11 spb.n = 12 spb.add_panel(y1=0, y2=spb.b/2., plyt=spb.plyt) spb.add_panel(y1=spb.b/2., y2=spb.b, plyt=spb.plyt) spb.add_bladestiff2d(ys=spb.b/2., m1=14, n1=11, bf=0.08, fstack=[0, 90, 90, 0]*5, fplyt=spb.plyt, flaminaprop=spb.laminaprop) k0 = spb.calc_k0(silent=True) M = spb.calc_kM(silent=True) eigvals, eigvecs = freq(k0, M, silent=True) assert np.isclose(eigvals[0].real, 137.97927190657148, atol=0.01, rtol=0) def test_Lee_and_Lee_table4(): print('Testing Lee and Lee Table 4') # Lee and Lee. "Vibration analysis of anisotropic plates with eccentric # stiffeners". Computers & Structures, Vol. 57, No. 1, pp. 99-105, # 1995. models = ( ('model4', 0.00208, 0.0060, 138.99917796302756), ('model5', 0.00260, 0.0075, 175.00597239286196), ('model7', 0.00364, 0.0105, 205.433509024)) for model, hf, bf, value in models: spb = StiffPanelBay() spb.model = 'plate_clt_donnell_bardell' spb.mu = 1.500e3 # plate material density in kg / m^3 spb.laminaprop = (128.e9, 11.e9, 0.25, 4.48e9, 1.53e9, 1.53e9) spb.stack = [0, -45, +45, 90, 90, +45, -45, 0] plyt = 0.00013 spb.plyt = plyt spb.a = 0.5 spb.b = 0.250 spb.m = 14 spb.n = 15 hf = hf bf = bf n = int(hf/plyt) fstack = [0]*(n//4) + [90]*(n//4) + [90]*(n//4) + [0]*(n//4) # clamping spb.w1rx = 0. spb.w2rx = 0. spb.w1ry = 0. spb.w2ry = 0. spb.add_panel(y1=0, y2=spb.b/2.) spb.add_panel(y1=spb.b/2., y2=spb.b) spb.add_bladestiff1d(mu=spb.mu, ys=spb.b/2., bb=0., bf=bf, fstack=fstack, fplyt=plyt, flaminaprop=spb.laminaprop) k0 = spb.calc_k0(silent=True) M = spb.calc_kM(silent=True) eigvals, eigvecs = freq(k0, M, silent=True) herz = eigvals[0].real/2/np.pi assert np.isclose(herz, value, atol=0.001, rtol=0.001)

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ca31492fc3fb6ac5e525636c924d66466aa54803

431

py

Python

gpvolve/__init__.py

clararehmann/gpvolve

4e45b53b72184425c24d57b2e8779d3d51de39d7

[ "MIT" ]

1

2021-12-05T23:00:59.000Z

gpvolve/__init__.py

clararehmann/gpvolve

4e45b53b72184425c24d57b2e8779d3d51de39d7

[ "MIT" ]

null

gpvolve/__init__.py

clararehmann/gpvolve

4e45b53b72184425c24d57b2e8779d3d51de39d7

[ "MIT" ]

null

from .__version__ import __version__ from . import simulate from . import markov from . import utils from . import check from . import pyplot from .markovmodel import GenotypePhenotypeMSM from .slimsim import GenotypePhenotypeSLiM # from .visualization import * #from .utils import * # from .fitness import * # from .fixation import * from .flux import * # from .paths import * # from .analysis import * # from .cluster import *

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py

Python

Pandas/DataFrame1.py

mehmet-karagoz/Python-Pandas

7e2ac2962f94e4ffd28b0f6b74935ace6e6b51a0

[ "MIT" ]

1

2020-10-06T05:51:41.000Z

Pandas/DataFrame1.py

mehmet-karagoz/Python-Pandas

7e2ac2962f94e4ffd28b0f6b74935ace6e6b51a0

[ "MIT" ]

null

Pandas/DataFrame1.py

mehmet-karagoz/Python-Pandas

7e2ac2962f94e4ffd28b0f6b74935ace6e6b51a0

[ "MIT" ]

null

import pandas as pd import numpy as np #sozluk yapisi ve seriler ile Dataframe olusturma # data = { # 'first':pd.Series([1,2,3,4,5],index=['a','b','c','d','e']), # 'second':pd.Series([5,4,3,2],index=['a','b','c','d']) # } # df = pd.DataFrame(data) # print(df) # print('-'*50) # print(df.index) # print('-'*50) # print(df.columns) #sozluk yapisi ve ndarray ile Dataframe olusturma # data = { # 'ilk':[1.,2.,3.,4.], # 'ikinci':[5.,3.,2.,6.] # } # df = pd.DataFrame(data) # print(df) #structure ile Dataframe olusturma # data = [(1, 2., 'Hello'), (2, 3., "World")] # df = pd.DataFrame(data,columns=['A','B','C']) # print(df) #sozluk listesi ile Dataframe olusturma # data = [{'a':1,'b':2},{'a':4,'b':6,'c':3}] # df = pd.DataFrame(data) # print(df) #sozluk tuple ile Dataframe olusturma # data = { # ('a', 'b'): {('A', 'B'): 1, ('A', 'C'): 2}, # ('a', 'a'): {('A', 'C'): 2, ('A', 'B'): 3}, # ('a', 'c'): {('A', 'B'): 3, ('A', 'C'): 4}, # ('b', 'a'): {('A', 'B'): 5, ('A', 'C'): 6}, # } # df = pd.DataFrame(data) # print(df) #column secme, ekleme, silme islemleri # data = { # 'bir':[1.,2.,3.,4], # 'iki':[5.,6.,4.,8.] # } # df = pd.DataFrame(data) # print(df) # print('-'*50) # print(df['bir']) #secme islemi # print('-'*50) # df['uc'] = df['bir'] * df['iki'] #ekleme islemi # print(df) # print('-'*50) # df['dort'] = df['iki'] > 6 #ekleme islemi # print(df) # print('-'*50) # del df['iki'] #silme islemi # print(df) # print('-'*50) # df.pop('uc') #silme islemi # print(df) # print('-'*50) # df.insert(1,'lake',[8.,7.,6.,5.]) #ekleme islemi 1--> kacinci indexteki column a eklenecegi , lake column adi , 3.siradaki de column un degerleri # print(df)

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py

Python

instance/config.py

tw8130/News-Article

fa1457d53d3b68b401cfc064051c7ea2043f7592

[ "Unlicense" ]

null

instance/config.py

tw8130/News-Article

fa1457d53d3b68b401cfc064051c7ea2043f7592

[ "Unlicense" ]

null

instance/config.py

tw8130/News-Article

fa1457d53d3b68b401cfc064051c7ea2043f7592

[ "Unlicense" ]

null

NEWS_API_KEY ='82c66d6d002e4468a5b3199925f4e5de' SECRET_KEY='Flashpill'

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ca731fd66ec6d9fd8b8e5404558c90f37d97acd9

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py

Python

metalearner/ppo2ttifrutti_agent.py

aborghi/retro_contest_agent

fc41634962d1210ce306048d7c46c377d404c34a

[ "MIT" ]

33

2018-06-22T17:09:34.000Z

2021-06-24T03:40:31.000Z

metalearner/ppo2ttifrutti_agent.py

aborghi/retro_contest_agent

fc41634962d1210ce306048d7c46c377d404c34a

[ "MIT" ]

null

metalearner/ppo2ttifrutti_agent.py

aborghi/retro_contest_agent

fc41634962d1210ce306048d7c46c377d404c34a

[ "MIT" ]

5

2018-06-27T09:52:50.000Z

2019-04-05T02:09:17.000Z

#!/usr/bin/env python """ Train an agent on Sonic using PPO2ttifrutti, a variant of OpenAI PPO2 baseline. """ import tensorflow as tf import numpy as np import gym import gym_remote.exceptions as gre import os import math from baselines.common.vec_env.dummy_vec_env import DummyVecEnv from baselines.common.vec_env.subproc_vec_env import SubprocVecEnv import ppo2ttifrutti import ppo2ttifrutti_policies as policies import ppo2ttifrutti_sonic_env as env def main(): """Run PPO until the environment throws an exception.""" config = tf.ConfigProto() #os.environ["CUDA_VISIBLE_DEVICES"]="-1" config.gpu_options.allow_growth = True # pylint: disable=E1101 with tf.Session(config=config): # Take more timesteps than we need to be sure that # we stop due to an exception. ppo2ttifrutti.learn(policy=policies.CnnPolicy, env=SubprocVecEnv([env.make_train_0, env.make_train_1, env.make_train_2, env.make_train_3, env.make_train_4, env.make_train_5, env.make_train_6, env.make_train_7, env.make_train_8, env.make_train_9, env.make_train_10, env.make_train_11, env.make_train_12, env.make_train_13, env.make_train_14, env.make_train_15, env.make_train_16, env.make_train_17, env.make_train_18, env.make_train_19, env.make_train_20, env.make_train_21, env.make_train_22, env.make_train_23, env.make_train_24, env.make_train_25, env.make_train_26, env.make_train_27, env.make_train_28, env.make_train_29, env.make_train_30, env.make_train_31, env.make_train_32, env.make_train_33, env.make_train_34, env.make_train_35, env.make_train_36, env.make_train_37, env.make_train_38, env.make_train_39, env.make_train_40, env.make_train_41, env.make_train_42, env.make_train_43, env.make_train_44, env.make_train_45, env.make_train_46, env.make_val_0, env.make_val_1, env.make_val_2, env.make_val_3, env.make_val_4, env.make_val_5, env.make_val_6, env.make_val_7, env.make_val_8, env.make_val_9, env.make_val_10, env.make_extra_0, env.make_extra_1, env.make_extra_2, env.make_extra_3, env.make_extra_4, env.make_extra_5, env.make_extra_6, env.make_extra_7, env.make_extra_8, env.make_extra_9, env.make_extra_10, env.make_extra_11, env.make_extra_12, env.make_extra_13, env.make_extra_14, env.make_extra_15, env.make_extra_16, env.make_extra_17, env.make_extra_18, env.make_extra_19, env.make_extra_20, env.make_extra_21, env.make_extra_22, env.make_extra_23, env.make_extra_24, env.make_extra_25, env.make_extra_26, env.make_extra_27, env.make_extra_28, env.make_extra_29, env.make_extra_30, env.make_extra_31, env.make_extra_32, env.make_extra_33, env.make_extra_34, env.make_extra_35, env.make_extra_36, env.make_extra_37, env.make_extra_38, env.make_extra_39]), nsteps=2048, nminibatches=16, lam=0.95, gamma=0.99, noptepochs=4, log_interval=1, ent_coef=0.01, lr=lambda _: 2e-4, cliprange=lambda _: 0.1, total_timesteps=int(1e9), save_interval=25) if __name__ == '__main__': try: main() except gre.GymRemoteError as exc: print('exception', exc)

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py

Python

libs/data.py

masloff-open-projects/OpenCV-Webcam-Recorder-and-Streamer

c915c3f5c4789280a5628d0e4ec43235aa62d54a

[ "MIT" ]

7

2021-09-14T19:54:05.000Z

2022-03-28T06:32:52.000Z

libs/data.py

iRTEX-MIT/OpenCV-Webcam-Recorder-and-Streamer

c915c3f5c4789280a5628d0e4ec43235aa62d54a

[ "MIT" ]

null

libs/data.py

iRTEX-MIT/OpenCV-Webcam-Recorder-and-Streamer

c915c3f5c4789280a5628d0e4ec43235aa62d54a

[ "MIT" ]

5

2021-11-09T11:41:07.000Z

2022-03-01T00:38:39.000Z

class data: def __init__(self): self._ = {} def set(self, key, data_): self._[key] = data_ return data_ def get(self, key): if key in self._: return self._[key] else: return False

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py

Python

fedml-server/executor/conf/__init__.py

MichaelLee-ceo/FedSAUC

8c00008772213562ff6a07bf9fa92c3831713118

[ "Apache-2.0" ]

1

2022-03-24T09:14:58.000Z

fedml-server/executor/conf/__init__.py

MichaelLee-ceo/FedSAUC

8c00008772213562ff6a07bf9fa92c3831713118

[ "Apache-2.0" ]

null

fedml-server/executor/conf/__init__.py

MichaelLee-ceo/FedSAUC

8c00008772213562ff6a07bf9fa92c3831713118

[ "Apache-2.0" ]

1

2022-03-24T09:15:01.000Z

# -*- coding: utf-8 -*-n import os from fedml_mobile.server.executor.conf.env import EnvWrapper ENV = EnvWrapper(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), True, 'TrainingExecutor')

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py

Python

CCICApp/models.py

kiddhmh/DjangoSpiders

e14b88305acf769f344ef910c238bf55afbec273

[ "MIT" ]

2

2018-04-19T02:51:05.000Z

2019-08-12T03:23:31.000Z

CCICApp/models.py

kiddhmh/DjangoSpiders

e14b88305acf769f344ef910c238bf55afbec273

[ "MIT" ]

1

2018-04-23T06:45:45.000Z

CCICApp/models.py

kiddhmh/DjangoSpiders

e14b88305acf769f344ef910c238bf55afbec273

[ "MIT" ]

1

2018-04-23T02:12:33.000Z

from django.db import models # 微博Model class vvebo(models.Model): id = models.IntegerField(primary_key=True) keyword = models.TextField(max_length=1000, default="") user_id = models.TextField(max_length=1000, default="") user_name = models.TextField(max_length=1000, default="") time = models.CharField(max_length=1000, default="") comment = models.TextField(max_length=1000, default="") shoucang = models.IntegerField(default=0) zhuanfa = models.IntegerField(default=0) pinglun = models.IntegerField(default=0) dianzan = models.IntegerField(default=0) device = models.TextField(max_length=1000, default="") url = models.TextField(max_length=1000, default="") # 知乎Model class zhihu(models.Model): keyword = models.TextField(max_length=100, default="") question_id = models.CharField(max_length=20, default="") question_name = models.TextField(max_length=100, default="") answer_id = models.CharField(max_length=20, default="") comment = models.TextField(max_length=30000, default="") time = models.CharField(max_length=20, default="") voteup_count = models.IntegerField(default=0) user_name = models.CharField(max_length=20, default="") #微信Model class wechat(models.Model): id = models.IntegerField(primary_key=True) keyword = models.TextField(max_length=1000, default="") article_title = models.TextField(max_length=1000, default="") article_url = models.TextField(max_length=1000, default="") article_imgs = models.TextField(max_length=1000, default="") comment = models.TextField(max_length=1000, default="") time = models.TextField(max_length=1000, default="") gzh_profile_url = models.TextField(max_length=1000, default="") gzh_headimage = models.TextField(max_length=1000, default="") user_name = models.TextField(max_length=1000, default="") gzh_isv = models.IntegerField(default=0)

38.52

68

0.724818

238

1,926

5.697479

0.210084

0.152655

0.238938

0.318584

0.738938

0.730826

0.557522

0.349558

0.334808

0

0.053647

0.138629

1,926

49

69

39.306122

0.763713

0.011423

0

0.228571

0

1

0

false

0

0.028571

0

1

0

null

0

1

0

1

0

null

0

1

0

4

04ae5dd12facb29dcebed0d6a8a168e5d91756ab

1,580

py

Python

src/python/backends/py/sprite/__init__.py

andyjost/Sprite

7ecd6fc7d48d7f62da644e48c12c7b882e1a2929

[ "MIT" ]

1

2022-03-16T16:37:11.000Z

src/python/backends/py/sprite/__init__.py

andyjost/Sprite

7ecd6fc7d48d7f62da644e48c12c7b882e1a2929

[ "MIT" ]

null

src/python/backends/py/sprite/__init__.py

andyjost/Sprite

7ecd6fc7d48d7f62da644e48c12c7b882e1a2929

[ "MIT" ]

null

'''Python wrappers for libsprite.so.''' from ._sprite import * import itertools, six from six.moves import range def Fingerprint__iter__(self): for i in range(self.capacity): v = self.get(i) if v != UNDETERMINED: yield i, v def Fingerprint__repr__(self, limit=32): def parts(): for i,v in self: yield "%s%s" % (i, 'L' if v == LEFT else 'R') body = list(itertools.islice(parts(), limit)) if len(body) == limit: body += '...' return '<%s>' % ''.join(body) def Fingerprint__reduce__(self): return Fingerprint, (), None, None, self.__iter__() def Fingerprint__eq__(self, rhs): return all(a==b for a,b in six.moves.zip_longest(self, rhs)) def Fingerprint__ne__(self, rhs): return not (self == rhs) def Fingerprint__le__(self, rhs): return all(i not in self or self.get(i) == lr for i,lr in rhs) def Fingerprint__ge__(self, rhs): return rhs <= self def Fingerprint__lt__(self, rhs): return self <= rhs and (self != rhs) def Fingerprint__gt__(self, rhs): return rhs < self def Fingerprint_consistentWith_(self, rhs): if self.depth < rhs.depth: return self < rhs else: return rhs < self Fingerprint.__iter__ = Fingerprint__iter__ Fingerprint.__repr__ = Fingerprint__repr__ Fingerprint.__reduce__ = Fingerprint__reduce__ Fingerprint.__eq__ = Fingerprint__eq__ Fingerprint.__ne__ = Fingerprint__ne__ Fingerprint.__le__ = Fingerprint__le__ Fingerprint.__ge__ = Fingerprint__ge__ Fingerprint.__lt__ = Fingerprint__lt__ Fingerprint.__gt__ = Fingerprint__gt__ Fingerprint.consistentWith = Fingerprint_consistentWith_

26.333333

64

0.723418

217

1,580

4.723502

0.271889

0.081951

0.076098

0.061463

0.066341

0

0.001511

0.162025

1,580

59

65

26.779661

0.772659

0.020886

0

0.044444

0

0.008442

0

1

0.244444

false

0

0.066667

0.155556

0.533333

0.466667

0

null

0

null

0

1

0

1

0

4

04ef06e5dcbd3424cf55c28bd283b02d45bfdad0

195

py

Python

chapter-04/exercise005.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

chapter-04/exercise005.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

chapter-04/exercise005.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

x = 3 y = 12.5 print('The rabbit is ', x, '.', sep='') print('The rabbit is', x, 'years old.') print(y, 'is average.') print(y, ' * ', x, '.', sep='') print(y, ' * ', x, ' is ', x*y, '.', sep='')

27.857143

44

0.461538

33

195

2.727273

0.393939

0.1

0.311111

0.355556

0.377778

0

0.025641

0.2

195

7

44

27.857143

0.551282

0

0.311224

0

1

0

false

0

0.714286

0

null

0

1

0

1

0

null

0

1

0

4

04f6a64d3c381809f0c0f17895926f4d6a5c7017

1,080

py

Python

pyramid_rest_route/view.py

rickmak/pyramid_resources

b497704e23916989ef690cfb1c729fa94bd2266d

[ "MIT" ]

null

pyramid_rest_route/view.py

rickmak/pyramid_resources

b497704e23916989ef690cfb1c729fa94bd2266d

[ "MIT" ]

null

pyramid_rest_route/view.py

rickmak/pyramid_resources

b497704e23916989ef690cfb1c729fa94bd2266d

[ "MIT" ]

2

2015-07-14T06:59:53.000Z

2019-05-28T08:50:35.000Z

import logging from pyramid.httpexceptions import HTTPNotImplemented from pyramid.renderers import render, render_to_response log = logging.getLogger(__name__) class RestView(object): renderers = {} def __init__(self, request): self.request = request self.params = request.params self.url = request.route_url self.c = request.tmpl_context self.routes = self.request.matchdict def render_(self, *args, **kwargs): kwargs['request'] = self.request return render(*args, **kwargs) def render(self, *args, **kwargs): kwargs['request'] = self.request return render_to_response(*args, **kwargs) def index(self): raise HTTPNotImplemented() def new(self): raise HTTPNotImplemented() def create(self): raise HTTPNotImplemented() def view(self): raise HTTPNotImplemented() def edit(self): raise HTTPNotImplemented() def update(self): raise HTTPNotImplemented() def delete(self): raise HTTPNotImplemented()

22.978723

56

0.65

112

1,080

6.133929

0.348214

0.091703

0.275109

0.262009

0.171761

0

0.250926

1,080

47

57

22.978723

0.849197

0

0.28125

0

0.012951

0

1

0.3125

false

0

0.09375

0

0.53125

0

null

0

1

0

null

0

1

0

1

0

4

04fbf91a6332b5a1b474ed67ff0d7a69f456439d

154

py

Python

test/drafts/2016-10-17_1931 Context Integration/a01 first rough draft.py

friedrichromstedt/upy

4b6b890259fb34bc69265fc400881587157b03a3

[ "MIT" ]

3

2015-06-01T23:09:38.000Z

2015-10-06T13:14:23.000Z

test/drafts/2016-10-17_1931 Context Integration/a01 first rough draft.py

friedrichromstedt/upy

4b6b890259fb34bc69265fc400881587157b03a3

[ "MIT" ]

null

test/drafts/2016-10-17_1931 Context Integration/a01 first rough draft.py

friedrichromstedt/upy

4b6b890259fb34bc69265fc400881587157b03a3

[ "MIT" ]

null

import upy2 from upy2.typesetting.scientific import ScientificTypesetter a = upy2.undarray(10, 2) with ScientificTypesetter(2, 3): print a print a

15.4

60

0.772727

21

154

5.666667

0.619048

0.10084

0

0.061538

0.155844

154

9

61

17.111111

0.853846

0

0.333333

0

null

0

0.333333

null

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

4

04fe159d755c988a213e903e5a3f55facc8d1c18

141

py

Python

Olympiad Solutions/DMOJ/boolean.py

p1yush/code-DS-ALGO

f015f766e75cb61ca908e30bb600bdd6d2fb2e82

[ "MIT" ]

36

2019-12-27T08:23:08.000Z

2022-01-24T20:35:47.000Z

Olympiad Solutions/DMOJ/boolean.py

p1yush/code-DS-ALGO

f015f766e75cb61ca908e30bb600bdd6d2fb2e82

[ "MIT" ]

10

2019-11-13T02:55:18.000Z

2021-10-13T23:28:09.000Z

Olympiad Solutions/DMOJ/boolean.py

p1yush/code-DS-ALGO

f015f766e75cb61ca908e30bb600bdd6d2fb2e82

[ "MIT" ]

53

2020-08-15T11:08:40.000Z

2021-10-09T15:51:38.000Z

# Ivan Carvalho # Solution to https://dmoj.ca/problem/boolean #!/usr/bin/env python2.7 # -*- coding : utf-8 -*- a = raw_input() print eval(a)

23.5

45

0.666667

23

141

4.043478

0.956522

0

0.02459

0.134752

141

6

46

23.5

0.737705

0.730496

0

null

0

null

0.5

1

0

null

0

1

0

null

0

1

0

1

0

4

b6d9e74e11c76c18da277b15e5aba538d9f0cbc1

474

py

Python

cm4/abstractclass/DatabaseManagerABC.py

swsachith/cm

d99837917f0dafe60c25829cf78ae77bbe02bd85

[ "Apache-2.0" ]

null

cm4/abstractclass/DatabaseManagerABC.py

swsachith/cm

d99837917f0dafe60c25829cf78ae77bbe02bd85

[ "Apache-2.0" ]

null

cm4/abstractclass/DatabaseManagerABC.py

swsachith/cm

d99837917f0dafe60c25829cf78ae77bbe02bd85

[ "Apache-2.0" ]

null

import abc class DatabaseManagerABC (metaclass=abc.ABCMeta): @abc.abstractmethod def update_document(self): """ update document in database/storage """ pass @abc.abstractmethod def find_document(self): """ find document in database/stroage """ pass @abc.abstractmethod def delete_document(self): """ delete any document in database/storage """ pass

18.230769

49

0.57384

44

474

6.113636

0.431818

0.189591

0.223048

0.185874

0.215613

0

0.339662

474

25

50

18.96

0.859425

0.229958

0

0.545455

0

1

0.272727

false

0.272727

0.090909

0

0.454545

0

null

0

1

0

null

0

1

0

1

0

4

b6dc9f22280151da48c2987c070d2e6947fd962e

100

py

Python

notes/demos/nn.py

Clickity-Clack/iceberg

e0c7e4f29c238502cbea3b951d30616ba3eeacd0

[ "MIT" ]

null

notes/demos/nn.py

Clickity-Clack/iceberg

e0c7e4f29c238502cbea3b951d30616ba3eeacd0

[ "MIT" ]

null

notes/demos/nn.py

Clickity-Clack/iceberg

e0c7e4f29c238502cbea3b951d30616ba3eeacd0

[ "MIT" ]

1

2018-01-05T23:11:12.000Z

import gym import numpy as np import random import tensorflow as tf import matplotlib.pyplot as plt

16.666667

31

0.83

17

100

4.882353

0.647059

0

0.16

100

5

32

20

0.988095

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

8e0cc0f9c4e1b4b0cd8fb9940b2837fd1a7b79ce

156

py

Python

db/hello.py

alicezehner/sql

cb5219209ff65ae157c0624fdd6d887e3725c47c

[ "MIT" ]

null

db/hello.py

alicezehner/sql

cb5219209ff65ae157c0624fdd6d887e3725c47c

[ "MIT" ]

null

db/hello.py

alicezehner/sql

cb5219209ff65ae157c0624fdd6d887e3725c47c

[ "MIT" ]

null

from faker import Faker fake = Faker() # generate random names print(fake.first_name(), fake.last_name()) print(fake.job()) # push fake data into database

19.5

42

0.74359

24

156

4.75

0.666667

0.157895

0

0.134615

156

7

43

22.285714

0.844444

0.320513

0

1

0

1

0

false

0

0.25

0

0.25

0.5

1

0

null

0

1

0

1

0

null

0

1

0

4

8e142c763fdb8d924ffaccc126ec69589aa927d1

640

py

Python

openre/agent/server/action/utils.py

openre/openre

c5969df92cac83bdafd049e1c0a3bcf56b51223a

[ "MIT" ]

null

openre/agent/server/action/utils.py

openre/openre

c5969df92cac83bdafd049e1c0a3bcf56b51223a

[ "MIT" ]

null

openre/agent/server/action/utils.py

openre/openre

c5969df92cac83bdafd049e1c0a3bcf56b51223a

[ "MIT" ]

1

2016-02-14T11:20:57.000Z

# -*- coding: utf-8 -*- from openre.agent.decorators import action import logging @action(namespace='server') def ping(event): return 'pong' @action(namespace='server') def exception(event): raise Exception('Test exception') @action(namespace='server') def check_args(event, *args, **kwargs): return {'args': args, 'kwargs': kwargs} @action(namespace='server') def debug(event): logging.debug('Debug message: %s', event.data) @action(namespace='server') def error(event): logging.error('Error message: %s', event.data) @action(namespace='server') def warn(event): logging.warn('Warn message: %s', event.data)

22.068966

50

0.69375

82

640

5.402439

0.353659

0.20316

0.284424

0.325056

0.185102

0

0.001799

0.13125

640

28

51

22.857143

0.794964

0.032813

0

0.3

0

0.184765

0

1

0.3

false

0

0.1

0.5

0

null

1

0

null

0

1

0

4

8e2c8ea26343525dca9a833b62e3ed6507179602

72

py

Python

test/remote/__init__.py

ScorpionResponse/kbwc_api_client

3f327a8ddd1ef2bcee6a499ae2af867f10e5d61b

[ "Apache-2.0" ]

1

2020-07-22T16:51:17.000Z

test/remote/__init__.py

ScorpionResponse/kbwc_api_client

3f327a8ddd1ef2bcee6a499ae2af867f10e5d61b

[ "Apache-2.0" ]

null

test/remote/__init__.py

ScorpionResponse/kbwc_api_client

3f327a8ddd1ef2bcee6a499ae2af867f10e5d61b

[ "Apache-2.0" ]

null

import OpenURL import Rest __all__ = [OpenURL.__name__, Rest.__name__]

14.4

43

0.791667

9

72

5

0.555556

0

0.125

72

4

44

18

0.714286

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

f3d1a295c7e7f0c6332bbe9bcc9bf044f8eae33b

98

py

Python

goals_search/apps.py

machakux/dgs

46de3cdaced5e4afef46fa46c7a3303d53df0da0

[ "Unlicense" ]

6

2017-11-06T02:50:31.000Z

2021-09-18T08:12:05.000Z

goals_search/apps.py

machakux/dgs

46de3cdaced5e4afef46fa46c7a3303d53df0da0

[ "Unlicense" ]

5

2017-07-08T07:58:07.000Z

2017-09-11T06:13:03.000Z

goals_search/apps.py

machakux/dgs

46de3cdaced5e4afef46fa46c7a3303d53df0da0

[ "Unlicense" ]

2

2017-09-15T20:49:41.000Z

2019-09-10T11:03:59.000Z

from django.apps import AppConfig class GoalsSearchConfig(AppConfig): name = 'goals_search'

16.333333

35

0.77551

11

98

6.818182

0.909091

0

0.153061

98

5

36

19.6

0.903614

0

0.122449

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6d07153e68c1d9372772f8f69478bb21aaaff009

163

py

Python

iati/__init__.py

mcarans/hdx-scraper-iati-viz

b252b3ab99ae45c788eebf260368790681607721

[ "MIT" ]

null

iati/__init__.py

mcarans/hdx-scraper-iati-viz

b252b3ab99ae45c788eebf260368790681607721

[ "MIT" ]

null

iati/__init__.py

mcarans/hdx-scraper-iati-viz

b252b3ab99ae45c788eebf260368790681607721

[ "MIT" ]

null

# -*- coding: utf-8 -*- from iati.covid_checks import CovidChecks from iati.ebola_checks import EbolaChecks checks = {'covid': CovidChecks, 'ebola': EbolaChecks}

27.166667

53

0.748466

20

163

6

0.55

0.133333

0

0.006993

0.122699

163

5

54

32.6

0.832168

0.128834

0

0.071429

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6d5b9db2ef3c280e75f116340f39ee60fd487560

1,035

py

Python

api server/server/routes/front_routes.py

rabo452/flipbook

f892d568fd4acff84414098dfbad17867fc0fc7b

[ "MIT" ]

null

api server/server/routes/front_routes.py

rabo452/flipbook

f892d568fd4acff84414098dfbad17867fc0fc7b

[ "MIT" ]

null

api server/server/routes/front_routes.py

rabo452/flipbook

f892d568fd4acff84414098dfbad17867fc0fc7b

[ "MIT" ]

null

# routes for front-end part of project from flask import url_for, render_template, request from server import app @app.route('/', methods = ['GET']) def index_page(): return render_template('/front-end/index.html') @app.route('/login', methods = ['GET']) def login_page(): return render_template('/front-end/login.html') @app.route('/forgot', methods = ['GET']) def forgot_page(): return render_template('/front-end/forgot.html') @app.route('/flipbook', methods = ['GET']) def flipbook_page(): try: id = request.args.get('id') facebook_logo_image_url = request.url_root + url_for('files', filename=f'{id}/logo_image/logo.jpg') return render_template('/front-end/flipbook.html', facebook_logo_image_url = facebook_logo_image_url) except: return render_template('/front-end/flipbook.html', facebook_logo_image_url = '') @app.route('/confirm-page', methods = ['GET']) def confirm_page(): return render_template('/front-end/confirm-page.html')

32.34375

110

0.675362

138

1,035

4.862319

0.289855

0.083458

0.178838

0.223547

0.369598

0.178838

0

0.165217

1,035

31

111

33.387097

0.77662

0.034783

0

0.229814

0.169772

0

1

0.227273

false

0

0.090909

0.181818

0.590909

0

null

0

1

0

null

0

1

0

1

0

4

edcc99ba35cb469b4352ad6be312b3c17204649e

26

py

Python

src/pip/__init__.py

ehashman/pip

d67d98dd914e2ce80ece43594554f0a226558db0

[ "MIT" ]

1

2021-01-23T16:43:24.000Z

src/pip/__init__.py

ehashman/pip

d67d98dd914e2ce80ece43594554f0a226558db0

[ "MIT" ]

null

src/pip/__init__.py

ehashman/pip

d67d98dd914e2ce80ece43594554f0a226558db0

[ "MIT" ]

1

2019-06-28T05:23:31.000Z

__version__ = "18.0.dev0"

13

25

0.692308

4

26

3.5

1

0

0.173913

0.115385

26

1

26

0.434783

0

0.346154

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

4

edd3884ebad4f816fc880ec2083447f9befb84ec

480

py

Python

src/sleuthdeck/plugins/sound/actions.py

sleuth-io/sleuth-deck

289b9967e7d395de8aa05268eb5e686b67285c1e

[ "Apache-2.0" ]

null

src/sleuthdeck/plugins/sound/actions.py

sleuth-io/sleuth-deck

289b9967e7d395de8aa05268eb5e686b67285c1e

[ "Apache-2.0" ]

null

src/sleuthdeck/plugins/sound/actions.py

sleuth-io/sleuth-deck

289b9967e7d395de8aa05268eb5e686b67285c1e

[ "Apache-2.0" ]

null

from pydub import AudioSegment from pydub.playback import play from sleuthdeck.deck import Action from sleuthdeck.deck import ClickType from sleuthdeck.deck import Key from sleuthdeck.deck import KeyScene class Play(Action): def __init__(self, sound_file: str, gain: int = 0): sound = AudioSegment.from_file(sound_file) sound += gain self._sound = sound def __call__(self, scene: KeyScene, key: Key, click: ClickType): play(self._sound)

28.235294

68

0.727083

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480

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0.390625

0.166667

0.214286

0.285714

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0.197917

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null

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null

0

1

0

1

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6107990a85204fd28b051978ee8270908e30a034

501

py

Python

pykivdroid/screen.py

Sahil-pixel/Pykivdroid

91da72ffe36c6aadb86c197e4391bab073a3c6bf

[ "MIT" ]

8

2021-06-12T17:22:00.000Z

2022-03-14T14:49:40.000Z

pykivdroid/screen.py

Sahil-pixel/Pykivdroid

91da72ffe36c6aadb86c197e4391bab073a3c6bf

[ "MIT" ]

null

pykivdroid/screen.py

Sahil-pixel/Pykivdroid

91da72ffe36c6aadb86c197e4391bab073a3c6bf

[ "MIT" ]

2

2021-05-31T19:16:30.000Z

2022-01-08T23:33:57.000Z

from pykivdroid import mActivity,WindowManagerNLayoutParams,Window,run_on_ui_thread,View @run_on_ui_thread def set_full_screen(): return mActivity.getWindow().getDecorView().setSystemUiVisibility( View.SYSTEM_UI_FLAG_FULLSCREEN |View.SYSTEM_UI_FLAG_LAYOUT_FULLSCREEN | View.SYSTEM_UI_FLAG_IMMERSIVE_STICKY | View.SYSTEM_UI_FLAG_HIDE_NAVIGATION | View.SYSTEM_UI_FLAG_LAYOUT_HIDE_NAVIGATION)

38.538462

88

0.692615

54

501

5.907407

0.5

0.15674

0.188088

0.250784

0

0.255489

501

12

89

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0.855228

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null

0

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null

0

1

0

1

0

4

6122ae363a20d824466864bbbe967cbb5808cb1d

134

py

Python

deepxde/maps/__init__.py

Orcuslc/deepxde

79074f225351ce439c80389318a6e3e6b5b3d90f

[ "Apache-2.0" ]

8

2021-03-21T18:43:52.000Z

2021-05-26T04:01:53.000Z

deepxde/maps/__init__.py

mafeiyao/lululxvi-deepxde

295e0faed10d1a5aae3ab14ae92a40fec9ab93c7

[ "Apache-2.0" ]

null

deepxde/maps/__init__.py

mafeiyao/lululxvi-deepxde

295e0faed10d1a5aae3ab14ae92a40fec9ab93c7

[ "Apache-2.0" ]

1

2021-11-27T10:15:48.000Z

from __future__ import absolute_import from .fnn import FNN from .mfnn import MfNN from .opnn import OpNN from .resnet import ResNet

19.142857

38

0.813433

21

134

4.952381

0.380952

0

0.156716

134

6

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0.920354

0

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true

0

1

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0

null

0

1

0

null

0

1

0

1

0

4

b6299767ae3e54f798f0664dd60df47dd083daa4

203

py

Python

web/streams/views/streamdetailview.py

CleyFaye/gtlive-info

9e54e81b47f4292586211e83b776eec24214ab46

[ "MIT" ]

null

web/streams/views/streamdetailview.py

CleyFaye/gtlive-info

9e54e81b47f4292586211e83b776eec24214ab46

[ "MIT" ]

22

2019-03-23T21:08:08.000Z

2019-03-25T07:34:58.000Z

web/streams/views/streamdetailview.py

CleyFaye/gtlive-info

9e54e81b47f4292586211e83b776eec24214ab46

[ "MIT" ]

null

"""Display stream details""" from django.views.generic.detail import DetailView from streams.models import Stream class StreamDetailView(DetailView): """Display a stream info""" model = Stream

22.555556

50

0.753695

24

203

6.375

0.708333

0

0.147783

203

8

51

25.375

0.884393

0.216749

0

1

0

false

0

0.5

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

b6565da636f05be651f332cbf4d82a3cc6269146

20

py

Python

pybmrb/__init__.py

jonwedell/PyBMRB

f9dd15bcffd30d29a02b885529100ab028e72dcf

[ "MIT" ]

null

pybmrb/__init__.py

jonwedell/PyBMRB

f9dd15bcffd30d29a02b885529100ab028e72dcf

[ "MIT" ]

null

pybmrb/__init__.py

jonwedell/PyBMRB

f9dd15bcffd30d29a02b885529100ab028e72dcf

[ "MIT" ]

null

__all__ = ['csviz']

10

19

0.6

2

20

4

1

0

0.15

20

1

20

0.470588

0

0.25

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null

0

1

0

1

0

null

0

4

b66e2b8c6e4dd50bcf74903dd471b7173a9b1f32

159

py

Python

datahub_core/printable.py

grovesy/datahub

57bd1a837b9996c2dae5e052a94131b8fc56e3fb

[ "Apache-2.0" ]

67

2020-05-15T09:37:20.000Z

2022-03-18T04:12:08.000Z

datahub_core/printable.py

grovesy/datahub

57bd1a837b9996c2dae5e052a94131b8fc56e3fb

[ "Apache-2.0" ]

37

2020-05-15T08:03:17.000Z

2020-10-28T12:24:30.000Z

datahub_core/printable.py

grovesy/datahub

57bd1a837b9996c2dae5e052a94131b8fc56e3fb

[ "Apache-2.0" ]

10

2020-05-16T14:11:12.000Z

2021-10-06T19:20:47.000Z

from pprint import pformat class Printable: def __repr__(self): return "<" + type(self).__name__ + "> " + pformat(vars(self), indent=4, width=1)

22.714286

88

0.641509

20

159

4.7

0.85

0

0.015873

0.207547

159

6

89

26.5

0.730159

0

0.018868

0

1

0.25

false

0

0.25

1

0.25

1

0

null

0

1

0

null

0

1

0

1

0

4

b6700d566b4e375b2ac9c79300663ebb05604d0a

184

py

Python

Kivy/gui/crud.py

joao0710/primeiro-repo

4fe1240c417d42fb4ec17861003a13b0d0e9310d

[ "MIT" ]

null

Kivy/gui/crud.py

joao0710/primeiro-repo

4fe1240c417d42fb4ec17861003a13b0d0e9310d

[ "MIT" ]

null

Kivy/gui/crud.py

joao0710/primeiro-repo

4fe1240c417d42fb4ec17861003a13b0d0e9310d

[ "MIT" ]

null

from kivy.app import App from kivy.uix.boxlayout import BoxLayout class Principal(BoxLayout): pass class Crud(App): def build(self): return Principal() Crud().run()

15.333333

40

0.695652

25

184

5.12

0.6

0.125

0

0.201087

184

11

41

16.727273

0.870748

0

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0.125

false

0.125

0.25

0.125

0.75

0

1

0

null

0

null

0

1

0

1

0

4

b67a7082d8780fb7d33a02062987db61e0bd4271

152

py

Python

vb2py/converter.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/converter.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/converter.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

"""Wrapper around project converter to convert a project""" from vb2py import projectconverter if __name__ == '__main__': projectconverter.main()

21.714286

59

0.756579

17

152

6.294118

0.823529

0

0.007752

0.151316

152

7

60

21.714286

0.821705

0.348684

0

0.085106

0

1

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true

0

0.333333

0

0.333333

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1

0

null

0

1

0

null

0

1

0

1

0

4

b69602368fed215695fc035838212d570896136d

24,285

py

Python

ppgan/datasets/lapstyle_dataset.py

JackMcCoy/PaddleGAN

a89fa7a1d7edd6a0e227c2941f0641700b20fe70

[ "Apache-2.0" ]

null

ppgan/datasets/lapstyle_dataset.py

JackMcCoy/PaddleGAN

a89fa7a1d7edd6a0e227c2941f0641700b20fe70

[ "Apache-2.0" ]

null

ppgan/datasets/lapstyle_dataset.py

JackMcCoy/PaddleGAN

a89fa7a1d7edd6a0e227c2941f0641700b20fe70

[ "Apache-2.0" ]

null

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import os, math, glob import numpy as np import random from PIL import Image import paddle import paddle.vision.transforms as T from paddle.io import Dataset import cv2 import warnings warnings.filterwarnings("ignore") from .builder import DATASETS logger = logging.getLogger(__name__) def data_transform(crop_size): transform_list = [T.RandomCrop(crop_size)] return T.Compose(transform_list) @DATASETS.register() class LapStyleDataset(Dataset): """ coco2017 dataset for LapStyle model """ def __init__(self, content_root, style_root, load_size, crop_size, style_upsize=1): super(LapStyleDataset, self).__init__() self.content_root = content_root self.paths = os.listdir(self.content_root) random.shuffle(self.paths) self.style_root = style_root self.style_upsize = style_upsize self.style_paths = [os.path.join(self.style_root,i) for i in os.listdir(self.style_root)] if self.style_root[-1]=='/' else [self.style_root] self.load_size = load_size self.crop_size = crop_size self.transform = data_transform(self.crop_size) def __getitem__(self, index): """Get training sample return: ci: content image with shape [C,W,H], si: style image with shape [C,W,H], ci_path: str """ path = self.paths[index] content_img = cv2.imread(os.path.join(self.content_root, path)) try: if content_img.ndim == 2: content_img = cv2.cvtColor(content_img, cv2.COLOR_GRAY2RGB) else: content_img = cv2.cvtColor(content_img, cv2.COLOR_BGR2RGB) except: print(path) content_img = Image.fromarray(content_img) small_edge = min(content_img.width,content_img.height) if small_edge==content_img.width: intermediate_width = self.load_size ratio = content_img.height/content_img.width intermediate_height = math.floor(self.load_size*ratio) else: intermediate_height = self.load_size ratio = content_img.width/content_img.height intermediate_width = math.floor(self.load_size*ratio) content_img = content_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) content_img = np.array(content_img) style_path = random.choice(self.style_paths) if len(self.style_paths)>1 else self.style_paths[0] style_img = cv2.imread(style_path) style_img = cv2.cvtColor(style_img, cv2.COLOR_BGR2RGB) style_img = Image.fromarray(style_img) small_edge = min(style_img.width,style_img.height) if small_edge==style_img.width: intermediate_width = math.floor(self.load_size* self.style_upsize) ratio = style_img.height/style_img.width intermediate_height = math.floor(self.load_size*ratio* self.style_upsize) else: intermediate_height = math.floor(self.load_size* self.style_upsize) ratio = style_img.width/style_img.height intermediate_width = math.floor(self.load_size* ratio* self.style_upsize) style_img = style_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) style_img = style_img.resize((intermediate_width,intermediate_height),Image.BILINEAR) style_img = np.array(style_img) content_img = self.transform(content_img) style_img = self.transform(style_img) content_img = self.img(content_img) style_img = self.img(style_img) return {'ci': content_img, 'si': style_img, 'ci_path': path} def img(self, img): """make image with [0,255] and HWC to [0,1] and CHW return: img: image with shape [3,W,H] and value [0, 1]. """ # [0,255] to [0,1] img = img.astype(np.float32) / 255. # some images have 4 channels if img.shape[2] > 3: img = img[:, :, :3] # HWC to CHW img = np.transpose(img, (2, 0, 1)).astype('float32') return img def __len__(self): return len(self.paths) def name(self): return 'LapStyleDataset' @DATASETS.register() class LapStyleThumbset(Dataset): """ coco2017 dataset for LapStyle model """ def __init__(self, content_root, style_root, load_size, crop_size, thumb_size, style_upsize=1): super(LapStyleThumbset, self).__init__() self.content_root = content_root self.paths = os.listdir(self.content_root) random.shuffle(self.paths) self.style_root = style_root self.style_paths = [os.path.join(self.style_root,i) for i in os.listdir(self.style_root)] if self.style_root[-1]=='/' else [self.style_root] self.load_size = load_size self.crop_size = crop_size self.thumb_size = thumb_size self.style_upsize = style_upsize self.transform = data_transform(self.crop_size) self.transform_patch = data_transform(self.load_size) def __getitem__(self, index): """Get training sample return: ci: content image with shape [C,W,H], si: style image with shape [C,W,H], ci_path: str """ path = self.paths[index] content_img = cv2.imread(os.path.join(self.content_root, path)) try: if content_img.ndim == 2: content_img = cv2.cvtColor(content_img, cv2.COLOR_GRAY2RGB) else: content_img = cv2.cvtColor(content_img, cv2.COLOR_BGR2RGB) except: print(path) content_img = Image.fromarray(content_img) small_edge = min(content_img.width,content_img.height) if small_edge==content_img.width: small_edge='width' intermediate_width = self.load_size final_width = self.thumb_size ratio = content_img.height/content_img.width intermediate_height = math.ceil(self.load_size*ratio) final_height = math.ceil(self.thumb_size*ratio) else: small_edge='height' final_height = self.thumb_size intermediate_height = self.load_size ratio = content_img.width/content_img.height intermediate_width = math.ceil(self.load_size*ratio) final_width = math.ceil(self.thumb_size*ratio) content_img = content_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) content_patches = np.array(content_img) content_img = content_img.resize((final_width, final_height), Image.BILINEAR) content_img = np.array(content_img) if small_edge=='height': topmost=self.crop_size #will be divided by content_img bottommost=0 if content_img.shape[0]<self.thumb_size-1: leftmost= random.choice(list(range(0, content_img.shape[0] - self.thumb_size,2))) rightmost=leftmost+self.crop_size else: leftmost=0 rightmost=self.crop_size else: rightmost=self.crop_size leftmost=0 if content_img.shape[1]<self.thumb_size-1: bottommost = random.choice(list(range(0, content_img.shape[1] - self.thumb_size,2))) topmost=bottommost+self.crop_size else: bottommost = 0 topmost = self.crop_size content_img =content_img[bottommost:topmost,leftmost:rightmost] content_patches = content_patches[bottommost*2:topmost*2,leftmost*2:rightmost*2] randx = random.choice(list(range(0, self.crop_size,2))) randy = random.choice(list(range(0, self.crop_size,2))) position = [randx, randx + self.crop_size, randy, randy+self.crop_size] half_position = [math.floor(randx*.5), math.floor((randx + self.crop_size)*.5), math.floor(randy*.5), math.floor((randy+self.crop_size)*.5)] content_patches = content_patches[randx:randx + self.crop_size, randy:randy+self.crop_size] style_path = random.choice(self.style_paths) if len(self.style_paths)>1 else self.style_paths[0] style_img = cv2.imread(style_path) style_img = cv2.cvtColor(style_img, cv2.COLOR_BGR2RGB) style_img = Image.fromarray(style_img) small_edge = min(style_img.width,style_img.height) if small_edge==style_img.width: intermediate_width = math.floor(self.load_size* self.style_upsize) final_width = math.ceil(self.thumb_size*self.style_upsize) ratio = style_img.height/style_img.width intermediate_height = math.floor(self.load_size*ratio* self.style_upsize) final_height = math.ceil(self.thumb_size*ratio* self.style_upsize) else: intermediate_height = math.floor(self.load_size* self.style_upsize) final_height = math.ceil(self.thumb_size * self.style_upsize) ratio = style_img.width/style_img.height intermediate_width = math.floor(self.load_size* ratio* self.style_upsize) final_width = math.ceil(self.thumb_size*ratio* self.style_upsize) style_patch = style_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) style_img = style_patch.resize((final_width,final_height),Image.BILINEAR) style_img = np.array(style_img) style_patch = np.array(style_patch) style_img = self.transform(style_img) style_patch = self.transform_patch(style_patch) style_patch = self.img(style_patch) content_img = self.img(content_img) style_img = self.img(style_img) content_patches = self.img(content_patches) return {'ci': content_img, 'si': style_img, 'sp':style_patch, 'ci_path': path,'cp':content_patches,'position':position,'half_position':half_position} def img(self, img): """make image with [0,255] and HWC to [0,1] and CHW return: img: image with shape [3,W,H] and value [0, 1]. """ # [0,255] to [0,1] img = img.astype(np.float32) / 255. # some images have 4 channels if img.shape[2] > 3: img = img[:, :, :3] # HWC to CHW img = np.transpose(img, (2, 0, 1)).astype('float32') return img def __len__(self): return len(self.paths) def name(self): return 'LapStyleThumbset' def get_crop_bounds(thumb_size,img_width,img_height): if thumb_size==img_width: leftmost=0 else: leftmost= random.choice(list(range(0, int(img_width - thumb_size),4))) rightmost=leftmost+thumb_size if thumb_size==img_height: bottommost=0 else: bottommost = random.choice(list(range(0, int(img_height - thumb_size),4))) topmost=bottommost+thumb_size return [leftmost,bottommost,rightmost,topmost] @DATASETS.register() class MultiPatchSet(Dataset): """ coco2017 dataset for LapStyle model """ def __init__(self, content_root, style_root, load_size, crop_size, thumb_size, patch_depth,style_upsize=1): super(MultiPatchSet, self).__init__() self.content_root = content_root self.paths = os.listdir(self.content_root) random.shuffle(self.paths) self.style_root = style_root self.style_paths = [os.path.join(self.style_root,i) for i in os.listdir(self.style_root)] if self.style_root[-1]=='/' else [self.style_root] self.load_size = load_size self.crop_size = crop_size self.thumb_size = thumb_size self.style_upsize = style_upsize self.patch_depth = patch_depth self.style_img = False self.transform = data_transform(self.crop_size) self.transform_patch = data_transform(self.crop_size*2) def __getitem__(self, index): """Get training sample return: ci: content image with shape [C,W,H], si: style image with shape [C,W,H], ci_path: str """ content_stack=[] style_stack= [] position_stack = [] size_stack = [] path = self.paths[index] content_img = cv2.imread(os.path.join(self.content_root, path)) try: if content_img.ndim == 2: content_img = cv2.cvtColor(content_img, cv2.COLOR_GRAY2RGB) else: content_img = cv2.cvtColor(content_img, cv2.COLOR_BGR2RGB) except: print(path) content_img = Image.fromarray(content_img) small_edge = min(content_img.width,content_img.height) if small_edge==content_img.width: small_edge='width' intermediate_width = self.load_size ratio = content_img.height/content_img.width intermediate_height = math.ceil(self.load_size*ratio) else: small_edge='height' final_height = self.thumb_size intermediate_height = self.load_size ratio = content_img.width/content_img.height intermediate_width = math.ceil(self.load_size*ratio) final_width = math.ceil(self.thumb_size*ratio) content_img = content_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) style_img = cv2.imread(random.choice(self.style_paths)) style_img = cv2.cvtColor(style_img, cv2.COLOR_BGR2RGB) style_img = Image.fromarray(style_img) small_edge = min(style_img.width,style_img.height) if small_edge==style_img.width: intermediate_width = math.floor(self.load_size* self.style_upsize) ratio = style_img.height/style_img.width intermediate_height = math.floor(self.load_size*ratio* self.style_upsize) else: intermediate_height = math.floor(self.load_size* self.style_upsize) ratio = style_img.width/style_img.height intermediate_width = math.floor(self.load_size* ratio* self.style_upsize) style_img = style_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) style_img = style_img.crop(box=get_crop_bounds(self.load_size,style_img.width,style_img.height)) style_patch = style_img.resize((self.crop_size,self.crop_size)) style_patch = np.array(style_patch) style_patch = self.img(style_patch) style_stack.append(style_patch) content_img = content_img.crop(box=get_crop_bounds(self.load_size,content_img.width,content_img.height)) content_patch = content_img.resize((self.crop_size,self.crop_size)) content_patch = np.array(content_patch) content_patch = self.img(content_patch) content_stack.append(content_patch) for i in range(self.patch_depth): content_patch = content_img for c in position_stack: content_patch=content_patch.crop(box=(c[0],c[1],c[2],c[3])) size_stack.append(content_patch.width) position_stack.append(get_crop_bounds(content_patch.width/2,content_patch.width,content_patch.height)) content_patch=content_patch.crop(box=(position_stack[-1][0],position_stack[-1][1],position_stack[-1][2],position_stack[-1][3])) content_patch = content_patch.resize((self.crop_size,self.crop_size), Image.BILINEAR) content_patch = np.array(content_patch) content_patch = self.img(content_patch) content_stack.append(content_patch) style_stack.append(self.img(np.array(style_img))) output = {} for idx,i in enumerate(content_stack): output['content_stack_'+str(idx+1)]=i for idx,i in enumerate(style_stack): output['style_stack_'+str(idx+1)]=i output['position_stack']=position_stack output['content']=self.img(np.array(content_img)) output['size_stack']=size_stack return output def img(self, img): """make image with [0,255] and HWC to [0,1] and CHW return: img: image with shape [3,W,H] and value [0, 1]. """ # [0,255] to [0,1] img = img.astype(np.float32) / 255. # some images have 4 channels if img.shape[2] > 3: img = img[:, :, :3] # HWC to CHW img = np.transpose(img, (2, 0, 1)).astype('float32') return img def __len__(self): return len(self.paths) def name(self): return 'MultiPatchSet' @DATASETS.register() class LapStyleThumbsetInference(Dataset): """ coco2017 dataset for LapStyle model """ def __init__(self, content_root, style_root, load_size, crop_size, thumb_size, patch_depth,style_upsize=1): super(LapStyleThumbsetInference, self).__init__() self.content_root = content_root self.paths = os.listdir(self.content_root) random.shuffle(self.paths) self.style_root = style_root self.style_paths = [os.path.join(self.style_root,i) for i in os.listdir(self.style_root)] if self.style_root[-1]=='/' else [self.style_root] self.load_size = load_size self.crop_size = crop_size self.thumb_size = thumb_size self.style_upsize = style_upsize self.patch_depth = patch_depth self.transform = data_transform(self.crop_size) self.transform_patch = data_transform(self.crop_size*2) style_img = cv2.imread(self.style_paths[0]) style_img = cv2.cvtColor(style_img, cv2.COLOR_BGR2RGB) self.style_img = Image.fromarray(style_img) def __getitem__(self, index): """Get training sample return: ci: content image with shape [C,W,H], si: style image with shape [C,W,H], ci_path: str """ content_stack=[] style_stack= [] position_stack = [] size_stack = [] path = self.paths[index] content_img = cv2.imread(os.path.join(self.content_root, path)) try: if content_img.ndim == 2: content_img = cv2.cvtColor(content_img, cv2.COLOR_GRAY2RGB) else: content_img = cv2.cvtColor(content_img, cv2.COLOR_BGR2RGB) except: print(path) content_img = Image.fromarray(content_img) small_edge = min(content_img.width,content_img.height) if small_edge==content_img.width: small_edge='width' intermediate_width = self.load_size ratio = content_img.height/content_img.width #reduce_ratio = content_img.width/content_img.height intermediate_height = math.ceil(self.load_size*ratio) final_width = self.thumb_size final_height = math.ceil(self.thumb_size*ratio) else: small_edge='height' intermediate_height = self.load_size ratio = content_img.width/content_img.height #reduce_ratio = content_img.width/content_img.height intermediate_width = math.ceil(self.load_size*ratio) final_height = self.thumb_size final_width = math.ceil(self.thumb_size*ratio) content_img = content_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) content_thumb = content_img.resize((final_width, final_height), Image.BILINEAR) style_path = random.choice(self.style_paths) if len(self.style_paths)>1 else self.style_paths[0] small_edge = min(self.style_img.width,self.style_img.height) max_size=max(final_height,final_width) if small_edge==self.style_img.width: intermediate_width = math.floor(self.load_size* self.style_upsize) final_width = math.ceil(max_size* self.style_upsize) ratio = style_img.height/self.style_img.width intermediate_height = math.floor(self.load_size*ratio* self.style_upsize) final_height = math.ceil((max_size*self.style_upsize)*ratio) else: intermediate_height = math.floor(self.load_size* self.style_upsize) final_height = math.ceil(max_size* self.style_upsize) ratio = self.style_img.width/self.style_img.height intermediate_width = math.floor(self.load_size* ratio* self.style_upsize) final_width = math.ceil(max_size* self.style_upsize*ratio) style_thumb = self.style_img.resize((final_width,final_height)) transform = data_transform((content_thumb.height,content_thumb.width)) style_thumb = transform(style_thumb) style_img = self.style_img.resize((intermediate_width, intermediate_height), Image.BILINEAR) style_img = style_img.crop(box=get_crop_bounds(self.load_size,style_img.width,style_img.height)) style_img = np.array(style_img) content_img = np.array(content_img) content_thumb = np.array(content_thumb) content_thumb = self.img(content_thumb) style_thumb = np.array(style_thumb) style_thumb = self.img(style_thumb) style_img = self.img(style_img) sizes=style_thumb.shape ratio = math.floor(self.load_size/self.crop_size) content_img = self.img(content_img) #content_img = np.expand_dims(content_img, axis=0) if sizes[-1]%16!=0: closest=math.floor(sizes[-1]/16) style_thumb=style_thumb[:,:,:closest*16] content_thumb=content_thumb[:,:,:closest*16] content_img = content_img[:,:,:closest*16*ratio] if sizes[-2]%16!=0: closest=math.floor(sizes[-2]/16) style_thumb=style_thumb[:,:closest*16,:] content_thumb=content_thumb[:,:closest*16,:] content_img = content_img[:,:closest*16*ratio,:] assert content_thumb.shape == style_thumb.shape for i in range(self.patch_depth): bottommost = random.choice(list(range(0, content_img.shape[1] - content_thumb.shape[1],2))) topmost=bottommost+content_thumb.shape[1] leftmost = random.choice(list(range(0, content_img.shape[2] - content_thumb.shape[2],2))) rightmost = leftmost+content_thumb.shape[2] position_stack.append((math.floor(bottommost/2),math.floor(topmost/2),math.floor(leftmost/2),math.floor(rightmost/2))) #output = {'content':content_img,'style':style_img,'content_thumb':zero_thumb,'style_thumb':style_thumb,'content_shape':thumb_shape} output={'content':content_img,'ci':content_thumb,'position':position_stack,'cp':content_thumb,'si':style_thumb,'sp':style_thumb,'style':style_img,'ci_path':path} return output def img(self, img): """make image with [0,255] and HWC to [0,1] and CHW return: img: image with shape [3,W,H] and value [0, 1]. """ # [0,255] to [0,1] img = img.astype(np.float32) / 255. # some images have 4 channels if img.shape[2] > 3: img = img[:, :, :3] # HWC to CHW img = np.transpose(img, (2, 0, 1)).astype('float32') return img def __len__(self): return len(self.paths) def name(self): return 'LapStyleThumbsetInference'

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fcaed27722a9660f38f131ecde2a5f85a803f929

91

py

Python

django_web_app/telegram/apps.py

alexzanderr/django_web_app

2e4d0774510072bbaf4fef3c2858e9e94e3f39f3

[ "MIT" ]

null

django_web_app/telegram/apps.py

alexzanderr/django_web_app

2e4d0774510072bbaf4fef3c2858e9e94e3f39f3

[ "MIT" ]

44

2020-05-13T20:15:26.000Z

2022-03-04T02:58:58.000Z

django_web_app/telegram/apps.py

alexzanderr/django_web_app

2e4d0774510072bbaf4fef3c2858e9e94e3f39f3

[ "MIT" ]

4

2020-06-05T17:59:52.000Z

2021-02-06T19:09:43.000Z

from django.apps import AppConfig class TelegramConfig(AppConfig): name = 'telegram'

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fcb6ba9fbf1fe84bcdb66d58d9f8a16155d29a5d

428

bzl

Python

bazel/docker/initialize.bzl

mlab-lattice/lattice

8ad7070f7c0c5d2a24373b59567797afd669201f

[ "Apache-2.0" ]

1

2018-10-01T17:33:36.000Z

bazel/docker/initialize.bzl

mlab-lattice/lattice

8ad7070f7c0c5d2a24373b59567797afd669201f

[ "Apache-2.0" ]

59

2018-08-23T17:07:35.000Z

2018-10-09T15:55:05.000Z

bazel/docker/initialize.bzl

mlab-lattice/lattice

8ad7070f7c0c5d2a24373b59567797afd669201f

[ "Apache-2.0" ]

3

2018-10-09T05:38:16.000Z

2018-10-10T16:58:57.000Z

load("@io_bazel_rules_docker//go:image.bzl", go_image_repositories="repositories") load("@io_bazel_rules_docker//container:container.bzl", container_repositories = "repositories") def initialize_rules_docker(): container_repositories() go_image_repositories() load("@distroless//package_manager:package_manager.bzl", "package_manager_repositories",) def initialize_rules_package_manager(): package_manager_repositories()

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0

null

0

1

0

4

fcbea55c8526f80a0db46f3a6eb3fa8a6222c7d9

1,372

py

Python

test/test_g2p.py

gantzgraf/vape

f939cb527d72d852cb0919a57332110c15c5fd4a

[ "MIT" ]

4

2020-03-25T06:09:39.000Z

2021-03-23T11:22:00.000Z

test/test_g2p.py

gantzgraf/vape

f939cb527d72d852cb0919a57332110c15c5fd4a

[ "MIT" ]

1

2020-10-02T14:50:30.000Z

2020-10-12T15:24:24.000Z

test/test_g2p.py

gantzgraf/vape

f939cb527d72d852cb0919a57332110c15c5fd4a

[ "MIT" ]

1

2021-02-20T11:32:34.000Z

from .utils import * def test_g2p(): output = get_tmp_out() input = os.path.join(dir_path, 'test_data', 'ex2.bcf') test_args = dict( no_warnings=True, input=input, output=output, ped=os.path.join(dir_path, "test_data", "test.ped"), de_novo=True, biallelic=True, csq=['default'], check_g2p_consequence=True, check_g2p_inheritance=True, g2p=os.path.join(dir_path, "test_data", "test_g2p.csv") ) results, expected = run_args(test_args, output, sys._getframe().f_code.co_name) assert_equal(results, expected) os.remove(output) def test_g2p_snpeff(): output = get_tmp_out() input = os.path.join(dir_path, 'test_data', 'ex2.snpeff.bcf') test_args = dict( no_warnings=True, snpeff=True, input=input, output=output, ped=os.path.join(dir_path, "test_data", "test.ped"), de_novo=True, biallelic=True, csq=['default'], check_g2p_consequence=True, check_g2p_inheritance=True, g2p=os.path.join(dir_path, "test_data", "test_g2p.csv") ) results, expected = run_args(test_args, output, 'test_g2p') assert_equal(results, expected) os.remove(output) if __name__ == '__main__': import nose nose.run(defaultTest=__name__)

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null

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1

0

null

0

4

fcccddf6b0bdd238df5af63dd2a19fc5d8160f16

3,615

py

Python

histolab/data/_registry.py

nipeone/histolab

78854423df04c95c7168d03a95ae8665e3e957d8

[ "Apache-2.0" ]

null

histolab/data/_registry.py

nipeone/histolab

78854423df04c95c7168d03a95ae8665e3e957d8

[ "Apache-2.0" ]

null

histolab/data/_registry.py

nipeone/histolab

78854423df04c95c7168d03a95ae8665e3e957d8

[ "Apache-2.0" ]

null

# flake8: noqa # in legacy datasets we need to put our sample data within the data dir legacy_datasets = ["cmu_small_region.svs"] # Registry of datafiles that can be downloaded along with their SHA256 hashes # To generate the SHA256 hash, use the command # openssl sha256 filename registry = { "histolab/broken.svs": "b1325916876afa17ad5e02d2e7298ee883e758ed25369470d85bc0990e928e11", "histolab/kidney.png": "5c6dc1b9ae10a2865302d9c8eda360362ec47732cb3e9766c38ed90cb9f4c371", "data/cmu_small_region.svs": "ed92d5a9f2e86df67640d6f92ce3e231419ce127131697fbbce42ad5e002c8a7", "aperio/JP2K-33003-1.svs": "6205ccf75a8fa6c32df7c5c04b7377398971a490fb6b320d50d91f7ba6a0e6fd", "aperio/JP2K-33003-2.svs": "1a13cef86b55b51127cebd94a1f6069f7de494c98e3e708640d1ce7181d9e3fd", "tcga/breast/TCGA-A8-A082-01A-01-TS1.3cad4a77-47a6-4658-becf-d8cffa161d3a.svs": "e955f47b83c8a5ae382ff8559493548f90f85c17c86315dd03134c041f44df70", "tcga/breast/TCGA-A1-A0SH-01Z-00-DX1.90E71B08-E1D9-4FC2-85AC-062E56DDF17C.svs": "6de90fe92400e592839ab7f87c15d9924bc539c61ee3b3bc8ef044f98d16031b", "tcga/breast/TCGA-E9-A24A-01Z-00-DX1.F0342837-5750-4172-B60D-5F902E2A02FD.svs": "55c694262c4d44b342e08eb3ef2082eeb9e9deeb3cb445e4776419bb9fa7dc21", "tcga/breast/TCGA-BH-A201-01Z-00-DX1.6D6E3224-50A0-45A2-B231-EEF27CA7EFD2.svs": "e1ccf3360078844abbec4b96c5da59a029a441c1ab6d7f694ec80d9d79bd3837", "tcga/prostate/TCGA-CH-5753-01A-01-BS1.4311c533-f9c1-4c6f-8b10-922daa3c2e3e.svs": "93ed7aa906c9e127c8241bc5da197902ebb71ccda4db280aefbe0ecd952b9089", "tcga/ovarian/TCGA-13-1404-01A-01-TS1.cecf7044-1d29-4d14-b137-821f8d48881e.svs": "6796e23af7cd219b9ff2274c087759912529fec9f49e2772a868ba9d85d389d6", "9798433/?format=tif": "7db49ff9fc3f6022ae334cf019e94ef4450f7d4cf0d71783e0f6ea82965d3a52", "9798554/?format=tif": "8a4318ac713b4cf50c3314760da41ab7653e10e90531ecd0c787f1386857a4ef", } APERIO_REPO_URL = "http://openslide.cs.cmu.edu/download/openslide-testdata/Aperio" TCGA_REPO_URL = "https://api.gdc.cancer.gov/data" IDR_REPO_URL = "https://idr.openmicroscopy.org/webclient/render_image_download" registry_urls = { "histolab/broken.svs": "https://raw.githubusercontent.com/histolab/histolab/master/tests/fixtures/svs-images/broken.svs", "histolab/kidney.png": "https://user-images.githubusercontent.com/4196091/100275351-132cc880-2f60-11eb-8cc8-7a3bf3723260.png", "aperio/JP2K-33003-1.svs": f"{APERIO_REPO_URL}/JP2K-33003-1.svs", "aperio/JP2K-33003-2.svs": f"{APERIO_REPO_URL}/JP2K-33003-2.svs", "tcga/breast/TCGA-A8-A082-01A-01-TS1.3cad4a77-47a6-4658-becf-d8cffa161d3a.svs": f"{TCGA_REPO_URL}/ad9ed74a-2725-49e6-bf7a-ef100e299989", "tcga/breast/TCGA-A1-A0SH-01Z-00-DX1.90E71B08-E1D9-4FC2-85AC-062E56DDF17C.svs": f"{TCGA_REPO_URL}/3845b8bd-cbe0-49cf-a418-a8120f6c23db", "tcga/breast/TCGA-E9-A24A-01Z-00-DX1.F0342837-5750-4172-B60D-5F902E2A02FD.svs": f"{TCGA_REPO_URL}/682e4d74-2200-4f34-9e96-8dee968b1568", "tcga/breast/TCGA-BH-A201-01Z-00-DX1.6D6E3224-50A0-45A2-B231-EEF27CA7EFD2.svs": f"{TCGA_REPO_URL}/e70c89a5-1c2f-43f8-b6be-589beea55338", "tcga/prostate/TCGA-CH-5753-01A-01-BS1.4311c533-f9c1-4c6f-8b10-922daa3c2e3e.svs": f"{TCGA_REPO_URL}/5a8ce04a-0178-49e2-904c-30e21fb4e41e", "tcga/ovarian/TCGA-13-1404-01A-01-TS1.cecf7044-1d29-4d14-b137-821f8d48881e.svs": f"{TCGA_REPO_URL}/e968375e-ef58-4607-b457-e6818b2e8431", "9798433/?format=tif": f"{IDR_REPO_URL}/9798433/?format=tif", "9798554/?format=tif": f"{IDR_REPO_URL}/9798554/?format=tif", } legacy_registry = { ("data/" + filename): registry["data/" + filename] for filename in legacy_datasets }

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1e0dae1b3513d3a8edaa965d13268367fc74f036

212

py

Python

models/1-Tom/train/kaggle-hubmap-main/src/02_train/umap.py

navekshasood/HuBMAP---Hacking-the-Kidney

018100fe4bfa5e8764b9df5a9d188e2c670ac061

[ "MIT" ]

null

models/1-Tom/train/kaggle-hubmap-main/src/02_train/umap.py

navekshasood/HuBMAP---Hacking-the-Kidney

018100fe4bfa5e8764b9df5a9d188e2c670ac061

[ "MIT" ]

null

models/1-Tom/train/kaggle-hubmap-main/src/02_train/umap.py

navekshasood/HuBMAP---Hacking-the-Kidney

018100fe4bfa5e8764b9df5a9d188e2c670ac061

[ "MIT" ]

null

import umap # import umap.umap_ as umap import pickle train_data = pickle.load(open("feature_train", "rb")) test_data = pickle.load(open("feature_test", "rb")) embedding = umap.UMAP().fit_transform(train_data)

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1e1194850bf1c9cb226ea7cee2ea3e68d51eaf5f

64

py

Python

micro-ecommerce/payment_gateway/__init__.py

nelsonwenner/bookstore-api

566357e841f97d083400047b604ae5fdf64c7efa

[ "MIT" ]

49

2020-08-26T18:32:33.000Z

2022-03-28T03:45:00.000Z

micro-ecommerce/payment_gateway/__init__.py

nelsonwenner/bookstore-api

566357e841f97d083400047b604ae5fdf64c7efa

[ "MIT" ]

14

2021-01-05T02:32:30.000Z

2022-03-12T00:53:38.000Z

micro-ecommerce/payment_gateway/__init__.py

nelsonwenner/bookstore-api

566357e841f97d083400047b604ae5fdf64c7efa

[ "MIT" ]

24

2020-08-28T01:56:48.000Z

2022-03-28T18:32:23.000Z

default_app_config = 'payment_gateway.apps.PaymentGatewayConfig'

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0

1

0

null

0

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null

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4

1e2fe111cbac19550fa36403d83402b0f4ff2800

347

py

Python

panther_ioc_rules/sunburst_sha256_iocs.py

panther-labs/panther-cli

4e5c0a21570e1a02dada990fd91e324416afac96

[ "MIT" ]

4

2019-10-17T19:33:29.000Z

2019-10-21T15:23:30.000Z

panther_ioc_rules/sunburst_sha256_iocs.py

jacknagz/panther-analysis

fceab78ba5624136776596ee1b25fa0dc8a02a42

[ "Apache-2.0" ]

null

panther_ioc_rules/sunburst_sha256_iocs.py

jacknagz/panther-analysis

fceab78ba5624136776596ee1b25fa0dc8a02a42

[ "Apache-2.0" ]

null

from panther_iocs import SUNBURST_SHA256_IOCS, ioc_match def rule(event): return any(ioc_match(event.get("p_any_sha256_hashes"), SUNBURST_SHA256_IOCS)) def title(event): hashes = ",".join(ioc_match(event.get("p_any_sha256_hashes"), SUNBURST_SHA256_IOCS)) return f"Sunburst Indicator of Compromise Detected [SHA256 hash]: {hashes}"

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null

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1

0

1

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4

1e82a2e65e1b2723a928d80fb55eaebd1e00c3cf

157

py

Python

recette/__init__.py

pennacchio/recette

1749b0d7763498420102588e377d1c68fd0df19f

[ "MIT" ]

null

recette/__init__.py

pennacchio/recette

1749b0d7763498420102588e377d1c68fd0df19f

[ "MIT" ]

null

recette/__init__.py

pennacchio/recette

1749b0d7763498420102588e377d1c68fd0df19f

[ "MIT" ]

null

from recette.steps import prep_step_dummy, prep_step_other from recette.utils import combine # Package version single source of truth __version__ = "0.2.1"

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null

0

1

0

1

0

4

1e8567be9870d63385b355af8801e4fe48be9f55

2,491

py

Python

app_code/models.py

sivarki/hjarnuc

4acc9437af0f0fdc44d68dd0d6923e1039a4911b

[ "Apache-2.0" ]

null

app_code/models.py

sivarki/hjarnuc

4acc9437af0f0fdc44d68dd0d6923e1039a4911b

[ "Apache-2.0" ]

null

app_code/models.py

sivarki/hjarnuc

4acc9437af0f0fdc44d68dd0d6923e1039a4911b

[ "Apache-2.0" ]

null

from django.db import models from app_asset.models import Host # Create your models here. class Project(models.Model): project_name = models.CharField(max_length=32,unique=True) project_msg = models.CharField(max_length=64,null=True) def __unicode__(self): return self.project_name class GitCode(models.Model): git_name = models.CharField(max_length=64,unique=True) git_msg = models.CharField(max_length=64, null=True) git_language = models.CharField(max_length=64, null=True) project = models.ForeignKey(to='Project',on_delete=models.SET_NULL,null=True) git_url = models.CharField(max_length=128,unique=True) git_user = models.CharField(max_length=64, null=True) git_passwd = models.CharField(max_length=64, null=True) git_sshkey = models.TextField( null=True) def __unicode__(self): return self.git_name class Publist(models.Model): gitcode = models.ForeignKey(to='GitCode',on_delete=models.CASCADE) host_ip = models.ForeignKey(to=Host,on_delete=models.CASCADE) publist_dir = models.CharField(max_length=128) publist_msg = models.CharField(max_length=128,null=True) current_version = models.CharField(max_length=64,null=True) version_info = models.CharField(max_length=512,null=True) author = models.CharField(max_length=64,null=True) publist_date = models.CharField(max_length=64,null=True) update_time = models.DateTimeField(auto_now=True,null=True) def __unicode__(self): return self.gitcode class PublistRecord(models.Model): publist = models.ForeignKey(to='Publist',on_delete=models.CASCADE) current_version = models.CharField(max_length=64,null=True) version_info = models.CharField(max_length=1024, null=True) author = models.CharField(max_length=64, null=True) publist_date = models.CharField(max_length=64, null=True) update_time = models.DateTimeField(auto_now_add=True,null=True) up_content = models.TextField(null=True) def __unicode__(self): return self.publist class Wchartlog(models.Model): site_name = models.CharField(max_length=64, null=True) from_user = models.CharField(max_length=64, null=True) content= models.CharField(max_length=2048, null=True) up_id = models.CharField(max_length=64, null=True) status = models.CharField(max_length=64, default="waiting") add_time = models.DateTimeField(auto_now_add=True,null=True) def __unicode__(self): return self.Site_name

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1

0

null

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1

0

null

0

1

0

4

1ea1ff4cca16c27755d779c438a0f766e3f0597f

91

py

Python

pyproc/views/__init__.py

cmin764/pyproc

be69b5a35fbe3818accea472735effec0825f17c

[ "MIT" ]

null

pyproc/views/__init__.py

cmin764/pyproc

be69b5a35fbe3818accea472735effec0825f17c

[ "MIT" ]

null

pyproc/views/__init__.py

cmin764/pyproc

be69b5a35fbe3818accea472735effec0825f17c

[ "MIT" ]

null

"""All views and routes exposed by the pyproc web app.""" from . import ( message, )

13

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91

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true

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null

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1

0

1

0

4

1ed6c472a3e3ebca7687498a3cd8af7d6986cd28

3,653

py

Python

kaze_project/preprocessing.py

Albert-Aiqi-Zhang/Typhoon-Web-Application

b464e4cf21a33d0ee10ea625bda6be446f4fe352

[ "MIT" ]

null

kaze_project/preprocessing.py

Albert-Aiqi-Zhang/Typhoon-Web-Application

b464e4cf21a33d0ee10ea625bda6be446f4fe352

[ "MIT" ]

null

kaze_project/preprocessing.py

Albert-Aiqi-Zhang/Typhoon-Web-Application

b464e4cf21a33d0ee10ea625bda6be446f4fe352

[ "MIT" ]

null

import numpy as np import pandas as pd from datetime import datetime from pandas.io import sql import pymysql import csv import os import sys import pymysql df1 = pd.read_csv("../database_engineering/data_of_typhoon/table2001.csv", encoding="SHIFT-JIS") f = lambda x: datetime(x["年"], x["月"], x["日"], x["時（UTC）"], 0, 0) df1["datetime"] = df1.apply(f, axis=1) df1.drop(columns=["年", "月", "日", "時（UTC）"], inplace=True) df1_new = df1.iloc[:,[14,0,1,2,3,4,5,6,7,8,9,10,11,12,13]] df1_new.columns = ["datetime", "typhoon_number", "typhoon_name", "class", "latitude", "longitude", "center_pressure", "max_velocity", "50KT_major_direction", "50KT_major", "50KT_minor", "30KT_major_direction", "30KT_major", "30KT_minor", "landing"] df1_new.to_csv("../database_engineering/data_after/table2001.csv") f = lambda x: datetime(x["年"], x["月"], x["日"], x["時（UTC）"], 0, 0) for i in range(2, 19): if i < 10: r = "0" + str(i) else: r = str(i) df = pd.read_csv("../database_engineering/data_of_typhoon/table20" + r + ".csv", encoding="SHIFT-JIS") df["datetime"] = df.apply(f, axis=1) df.drop(columns=["年", "月", "日", "時（UTC）"], inplace=True) df_new = df.iloc[:,[14,0,1,2,3,4,5,6,7,8,9,10,11,12,13]] df_new.columns = ["datetime", "typhoon_number", "typhoon_name", "class", "latitude", "longitude", "center_pressure", "max_velocity", "50KT_major_direction", "50KT_major", "50KT_minor", "30KT_major_direction", "30KT_major", "30KT_minor", "landing"] df_new.to_csv("../database_engineering/data_after/table20" + r + ".csv") pymysql.install_as_MySQLdb() data = pd.read_csv("../database_engineering/data_after/table2001.csv") db = MySQLdb.connect(host = "localhost", user = "root", passwd = "12345678", db = "kaze", charset = "utf8") conn = MySQLdb.Connection(host = 'localhost',user = 'root',password = '12345678',port = 3306, database = 'kaze') #sql.to_sql(data, 'train', db) #db.close() cur = pymysql.cursors.Cursor(connection = conn) cur.execute(""" create table tbl01( id int auto_increment primary key, dtime datetime, typhoon_number int, typhoon_name varchar(256), class int, latitude float, longitude float, center_pressure int, max_velocity int, 50KT_major_direction int, 50KT_major int, 50KT_minor int, 30KT_major_direction int, 30KT_major int, 30KT_minor int, landing int)""") conn.commit() data = pd.read_csv('../database_engineering/data_after/table2001.csv') data = data.astype(str).iloc[:, 1:].values.tolist() cur.executemany("insert into tbl01 values(null, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)", data) conn.commit() local_dir=r'../database_engineering/data_after/table2001.csv' csv_reader(local_dir) for i in range(2, 19): if i < 10: r = "0" + str(i) else: r = str(i) cur = pymysql.cursors.Cursor(connection = conn) cur.execute(""" create table tbl""" + r + """( id int auto_increment primary key, dtime datetime, typhoon_number int, typhoon_name varchar(256), class int, latitude float, longitude float, center_pressure int, max_velocity int, 50KT_major_direction int, 50KT_major int, 50KT_minor int, 30KT_major_direction int, 30KT_major int, 30KT_minor int, landing int)""") conn.commit() data = pd.read_csv("../database_engineering/data_after/table20" + r + ".csv") data = data.astype(str).iloc[:, 1:].values.tolist() cur.executemany("insert into tbl" + r + " values(null, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)", data) conn.commit()

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0

1

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null

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4

1ee389ea08e9dc83d962636990f89404cc255720

99

py

Python

package/niflow/ants/brainextraction/__init__.py

rciric/poldracklab-antsbrainextraction

78544a1b72b4b9b505c3a72654990789fad554a4

[ "BSD-3-Clause" ]

null

package/niflow/ants/brainextraction/__init__.py

rciric/poldracklab-antsbrainextraction

78544a1b72b4b9b505c3a72654990789fad554a4

[ "BSD-3-Clause" ]

1

2018-11-06T17:31:13.000Z

package/niflow/ants/brainextraction/__init__.py

rciric/poldracklab-antsbrainextraction

78544a1b72b4b9b505c3a72654990789fad554a4

[ "BSD-3-Clause" ]

2

2018-10-20T03:11:24.000Z

2018-11-23T11:46:28.000Z

from .__about__ import __version__ from .workflows.brainextraction import init_brain_extraction_wf

33

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null

0

1

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1

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4

9495752f36e07120a23f8cb91134e78a77ef6722

10,896

py

Python

hungarian_tf_tests.py

shaolinkhoa/rec-attend-public

678407e98fcd4c3b72f101dda3e4bc8c120bca0f

[ "MIT" ]

118

2017-04-10T00:41:31.000Z

2022-03-28T09:34:28.000Z

hungarian_tf_tests.py

shaolinkhoa/rec-attend-public

678407e98fcd4c3b72f101dda3e4bc8c120bca0f

[ "MIT" ]

10

2017-10-02T04:23:27.000Z

2022-03-09T08:09:12.000Z

hungarian_tf_tests.py

shaolinkhoa/rec-attend-public

678407e98fcd4c3b72f101dda3e4bc8c120bca0f

[ "MIT" ]

51

2017-05-23T02:46:16.000Z

2021-10-09T05:21:34.000Z

import numpy as np import tensorflow as tf import unittest hungarian_module = tf.load_op_library("hungarian.so") class HungarianTests(unittest.TestCase): def test_min_weighted_bp_cover_1(self): W = np.array([[3, 2, 2], [1, 2, 0], [2, 2, 1]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() c_0 = c_0.eval() c_1 = c_1.eval() c_0_t = np.array([2, 1, 1]) c_1_t = np.array([1, 1, 0]) M_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) self.assertTrue((c_0.flatten() == c_0_t.flatten()).all()) self.assertTrue((c_1.flatten() == c_1_t.flatten()).all()) self.assertTrue((M == M_t).all()) pass def test_min_weighted_bp_cover_2(self): W = np.array([[5, 0, 4, 0], [0, 4, 6, 8], [4, 0, 5, 7]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() c_0 = c_0.eval() c_1 = c_1.eval() c_0_t = np.array([5, 6, 5]) c_1_t = np.array([0, 0, 0, 2]) M_t = np.array([[1, 0, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]) self.assertTrue((c_0.flatten() == c_0_t.flatten()).all()) self.assertTrue((c_1.flatten() == c_1_t.flatten()).all()) self.assertTrue((M == M_t).all()) def test_min_weighted_bp_cover_3(self): W = np.array([[5, 0, 2], [3, 1, 0], [0, 5, 0]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() c_0 = c_0.eval() c_1 = c_1.eval() c_0_t = np.array([2, 0, 4]) c_1_t = np.array([3, 1, 0]) M_t = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0]]) self.assertTrue((c_0.flatten() == c_0_t.flatten()).all()) self.assertTrue((c_1.flatten() == c_1_t.flatten()).all()) self.assertTrue((M == M_t).all()) def test_min_weighted_bp_cover_4(self): W = np.array([[[5, 0, 2], [3, 1, 0], [0, 5, 0]], [[3, 2, 2], [1, 2, 0], [2, 2, 1]]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() c_0 = c_0.eval() c_1 = c_1.eval() c_0_t = np.array([[2, 0, 4], [2, 1, 1]]) c_1_t = np.array([[3, 1, 0], [1, 1, 0]]) M_t = np.array([[[0, 0, 1], [1, 0, 0], [0, 1, 0]], [[1, 0, 0], [0, 1, 0], [0, 0, 1]]]) self.assertTrue((c_0.flatten() == c_0_t.flatten()).all()) self.assertTrue((c_1.flatten() == c_1_t.flatten()).all()) self.assertTrue((M == M_t).all()) def test_real_values_1(self): # Test the while loop terminates with real values. W = np.array( [[0.90, 0.70, 0.30, 0.20, 0.40, 0.001, 0.001, 0.001, 0.001, 0.001], [0.80, 0.75, 0.92, 0.10, 0.15, 0.001, 0.001, 0.001, 0.001, 0.001], [0.78, 0.85, 0.66, 0.29, 0.21, 0.001, 0.001, 0.001, 0.001, 0.001], [0.42, 0.55, 0.23, 0.43, 0.33, 0.002, 0.001, 0.001, 0.001, 0.001], [0.64, 0.44, 0.33, 0.33, 0.34, 0.001, 0.002, 0.001, 0.001, 0.001], [0.22, 0.55, 0.43, 0.43, 0.14, 0.001, 0.001, 0.002, 0.001, 0.001], [0.43, 0.33, 0.34, 0.22, 0.14, 0.001, 0.001, 0.001, 0.002, 0.001], [0.33, 0.42, 0.23, 0.13, 0.43, 0.001, 0.001, 0.001, 0.001, 0.002], [0.39, 0.24, 0.53, 0.56, 0.89, 0.001, 0.001, 0.001, 0.001, 0.001], [0.12, 0.34, 0.82, 0.82, 0.77, 0.001, 0.001, 0.001, 0.001, 0.001]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() M_t = np.array( [[1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0]]) self.assertTrue((M == M_t).all()) def test_real_values_2(self): W = np.array([[ 0.00604139, 0.0126045, 0.0117373, 0.01245, 0.00808836, 0.0162662, 0.0137996, 0.00403898, 0.0123786, 1e-05 ], [ 0.00604229, 0.0126071, 0.0117400, 0.0124528, 0.00808971, 0.0162703, 0.0138028, 0.00403935, 0.0123812, 1e-05 ], [ 0.00604234, 0.0126073, 0.0117402, 0.012453, 0.00808980, 0.0162706, 0.0138030, 0.00403937, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ], [ 0.00604235, 0.0126073, 0.0117402, 0.012453, 0.00808981, 0.0162706, 0.0138030, 0.00403938, 0.0123814, 1e-05 ]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() def test_real_values_3(self): W = np.array([[ 0.00302646, 0.00321431, 0.0217552, 0.00836773, 0.0256353, 0.0177026, 0.0289461, 0.0214768, 0.0101898, 1e-05 ], [ 0.00302875, 0.003217, 0.0217628, 0.00836405, 0.0256229, 0.0177137, 0.0289468, 0.0214719, 0.0101904, 1e-05 ], [ 0.00302897, 0.00321726, 0.0217636, 0.00836369, 0.0256217, 0.0177148, 0.0289468, 0.0214714, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.0177149, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.0177149, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.017715, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.017715, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.017715, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.017715, 0.0289468, 0.0214713, 0.0101905, 1e-05 ], [ 0.003029, 0.0032173, 0.0217637, 0.00836364, 0.0256216, 0.017715, 0.0289468, 0.0214713, 0.0101905, 1e-05 ]]) M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() def test_real_values_4(self): W = np.array([[ 1e-05, 0.0634311, 1e-05, 4.76687e-05, 1.00079e-05, 1.00378e-05, 1e-05, 1e-05, 1e-05, 3.9034e-05 ], [ 1e-05, 3.42696e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1.0122e-05, 3.43236e-05, 1e-05 ], [ 1e-05, 0.0426792, 0.031155, 1.0008e-05, 0.00483961, 0.0228187, 1e-05, 1e-05, 1e-05, 0.102463 ], [ 1e-05, 1e-05, 1e-05, 1.07065e-05, 1e-05, 1.00185e-05, 1e-05, 1e-05, 1e-05, 1.00007e-05 ], [ 1e-05, 4.22947e-05, 0.00062168, 0.623917, 1.03468e-05, 0.00588984, 1.00004e-05, 1.44433e-05, 1.00014e-05, 0.000213425 ], [ 1e-05, 1.01764e-05, 1e-05, 0.000667249, 1e-05, 0.000485082, 1e-05, 1e-05, 1.00002e-05, 1e-05 ], [ 1e-05, 1e-05, 1.50331e-05, 1e-05, 0.11269, 1e-05, 1e-05, 1e-05, 1e-05, 1.13251e-05 ], [ 1.0001e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 0.0246974, 1e-05, 1e-05, 1e-05 ], [ 1e-05, 2.89144e-05, 1e-05, 1.05147e-05, 1e-05, 0.000894762, 1.03587e-05, 0.150301, 1e-05, 1.00045e-05 ], [ 1e-05, 3.97901e-05, 1e-05, 1.11641e-05, 1e-05, 2.34249e-05, 1.0007e-05, 2.42828e-05, 1e-05, 1.10529e-05 ]]) p = 1e6 W = np.round(W * p) / p M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() def test_real_values_5(self): W = np.array([[ 1.4e-05, 1e-05, 1e-05, 0.053306, 0.044139, 1e-05, 1.2e-05, 1e-05, 1e-05, 1e-05 ], [ 0.001234, 1e-05, 1e-05, 2.1e-05, 1e-05, 0.001535, 0.019553, 1e-05, 1e-05, 1e-05 ], [ 0.002148, 1e-05, 1e-05, 1.6e-05, 0.651536, 2e-05, 7.4e-05, 0.002359, 1e-05, 1e-05 ], [ 3.8e-05, 1e-05, 0.000592, 4.7e-05, 0.09173, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05 ], [ 1e-05, 1e-05, 1e-05, 0.213736, 1e-05, 4.5e-05, 0.000768, 1e-05, 1e-05, 1e-05 ], [ 1e-05, 1e-05, 1e-05, 0.317609, 1e-05, 1e-05, 0.002151, 1e-05, 1e-05, 1e-05 ], [ 0.002802, 1e-05, 1.2e-05, 1e-05, 1e-05, 0.002999, 4.8e-05, 1.1e-05, 0.000919, 1e-05 ], [ 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 0.028816, 1e-05 ], [ 1e-05, 1e-05, 0.047335, 1e-05, 1.2e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05 ], [1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05, 1e-05]]) p = 1e6 W = np.round(W * p) / p M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() def test_real_values_6(self): W = np.array([[ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ], [ 0.003408, 0.010531, 0.002795, 1e-05, 0.019786, 0.010435, 0.002743, 0.023617, 0.010436, 0.003116 ]]) p = 1e6 W = np.round(W * p) / p M, c_0, c_1 = hungarian_module.hungarian(W) with tf.Session() as sess: M = M.eval() if __name__ == '__main__': suite = unittest.TestLoader().loadTestsFromTestCase(HungarianTests) unittest.TextTestRunner(verbosity=2).run(suite)

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testreport/views.py

mikiec84/badger-api

d0764fa0fd35ebfd7581e2a0218b59be9d13e814

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null

testreport/views.py

mikiec84/badger-api

d0764fa0fd35ebfd7581e2a0218b59be9d13e814

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2021-06-10T23:08:34.000Z

testreport/views.py

gaybro8777/badger-api

d0764fa0fd35ebfd7581e2a0218b59be9d13e814

[ "MIT" ]

null

from django.views.generic import TemplateView import logging log = logging.getLogger(__name__) class Base(TemplateView): template_name = 'base.html'

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Python

_playground/in_progress/sand.py

the-deep/DEEPL

93f7bf7d61d7424250d01c1fc510347375d767c4

[ "MIT" ]

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_playground/in_progress/sand.py

eoglethorpe/DEEPL

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_playground/in_progress/sand.py

eoglethorpe/DEEPL

fb6403ceb63197ecd314905f060a2e5f1e790f66

[ "MIT" ]

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2018-10-04T21:27:58.000Z

import nltk txt = nltk.data.load('/Users/ewanog/Dropbox/Work/ACAPS/nlp/text.txt') print(txt)

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Python

tests/unit/conftest.py

stefanhoelzl/synopse

07e5966b675d85d60e2e2484a62780a5735b2ed9

[ "MIT" ]

1

2021-03-09T23:04:28.000Z

tests/unit/conftest.py

stefanhoelzl/synopse

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[ "MIT" ]

null

tests/unit/conftest.py

stefanhoelzl/synopse

07e5966b675d85d60e2e2484a62780a5735b2ed9

[ "MIT" ]

null

import pytest from synopse.core.component import Component @pytest.fixture def create_component_class(): def wrapper(**attributes): return type("ComponentToTest", (Component,), attributes) return wrapper

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maskrcnn_benchmark/layers/nv_decode.py

DeLightCMU/MAL

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[ "MIT" ]

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2020-09-05T11:15:10.000Z

2021-07-26T08:12:28.000Z

maskrcnn_benchmark/layers/nv_decode.py

DeLightCMU/MAL

a03d4d3ed2ea4200ac6b4c6d980f3138b29d94ee

[ "MIT" ]

null

maskrcnn_benchmark/layers/nv_decode.py

DeLightCMU/MAL

a03d4d3ed2ea4200ac6b4c6d980f3138b29d94ee

[ "MIT" ]

3

2020-11-26T03:54:58.000Z

2021-07-26T08:12:33.000Z

from maskrcnn_benchmark import _C nv_decode = _C.nv_decode

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gesund_projekt/goals/apps.py

asis2016/gesund-projekt

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[ "MIT" ]

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gesund_projekt/goals/apps.py

asis2016/gesund-projekt

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gesund_projekt/goals/apps.py

asis2016/gesund-projekt

cb3828b69cd6a86deeab16943e38b6ebffd86abb

[ "MIT" ]

null

from django.apps import AppConfig class GoalsConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'goals' def ready(self): import goals.signals

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Python

wireciendpoint/__init__.py

frawhst/gooncogs

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[ "MIT" ]

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2021-10-06T15:25:40.000Z

wireciendpoint/__init__.py

frawhst/gooncogs

2301ba28b58c4d039c5064a9a014503e224578a4

[ "MIT" ]

null

wireciendpoint/__init__.py

frawhst/gooncogs

2301ba28b58c4d039c5064a9a014503e224578a4

[ "MIT" ]

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2021-09-11T23:44:44.000Z

2022-03-26T09:54:13.000Z

from redbot.core.bot import Red from .wireciendpoint import WireCiEndpoint async def setup(bot: Red): bot.add_cog(WireCiEndpoint(bot))

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py

Python

scvi/external/__init__.py

njbernstein/scvi-tools

8c3ca358418d7dd1da5244dd9c3652a4a8cbe3c2

[ "BSD-3-Clause" ]

398

2017-10-11T06:19:23.000Z

2020-09-14T02:46:25.000Z

scvi/external/__init__.py

njbernstein/scvi-tools

8c3ca358418d7dd1da5244dd9c3652a4a8cbe3c2

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708

2017-11-13T14:51:21.000Z

2020-09-16T21:09:19.000Z

scvi/external/__init__.py

njbernstein/scvi-tools

8c3ca358418d7dd1da5244dd9c3652a4a8cbe3c2

[ "BSD-3-Clause" ]

154

2017-10-16T06:53:59.000Z

2020-09-11T23:06:30.000Z

from .cellassign import CellAssign from .gimvi import GIMVI from .solo import SOLO from .stereoscope import RNAStereoscope, SpatialStereoscope __all__ = ["SOLO", "GIMVI", "RNAStereoscope", "SpatialStereoscope", "CellAssign"]

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bfd3022becdddafa973c831885d554772e936813

1,131

py

Python

database/wowaccounts/models.py

DiegoLing33/prestij.xyz-api

69a11a2c93dd98975f9becbc4b8f596e4941a05f

[ "MIT" ]

null

database/wowaccounts/models.py

DiegoLing33/prestij.xyz-api

69a11a2c93dd98975f9becbc4b8f596e4941a05f

[ "MIT" ]

null

database/wowaccounts/models.py

DiegoLing33/prestij.xyz-api

69a11a2c93dd98975f9becbc4b8f596e4941a05f

[ "MIT" ]

null

# ██╗░░░░░██╗███╗░░██╗░██████╗░░░░██████╗░██╗░░░░░░█████╗░░█████╗░██╗░░██╗ # ██║░░░░░██║████╗░██║██╔════╝░░░░██╔══██╗██║░░░░░██╔══██╗██╔══██╗██║░██╔╝ # ██║░░░░░██║██╔██╗██║██║░░██╗░░░░██████╦╝██║░░░░░███████║██║░░╚═╝█████═╝░ # ██║░░░░░██║██║╚████║██║░░╚██╗░░░██╔══██╗██║░░░░░██╔══██║██║░░██╗██╔═██╗░ # ███████╗██║██║░╚███║╚██████╔╝░░░██████╦╝███████╗██║░░██║╚█████╔╝██║░╚██╗ # ╚══════╝╚═╝╚═╝░░╚══╝░╚═════╝░░░░╚═════╝░╚══════╝╚═╝░░╚═╝░╚════╝░╚═╝░░╚═╝ # # Developed by Yakov V. Panov (C) Ling • Black 2020 # @site http://ling.black from sqlalchemy import Column, Integer, ForeignKey, String, Boolean from sqlalchemy.orm import relationship from database import Base from database.core.models import CoreModel from database.wow.models import BlizzardUserModel class WAccountModel(Base, CoreModel): __tablename__ = 'waccounts' user_id = Column(Integer, ForeignKey("blizzard_users.blizzard_id")) wow_id = Column(Integer) name = Column(String) realm_id = Column(Integer) realm_title = Column(String) level = Column(Integer) faction = Column(String) user = relationship(BlizzardUserModel)

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0

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449f491f827ed537119e735ca9342e37bea7d015

1,559

py

Python

2021-08/demo001.py

zhouyuanmin/MyDemo

664977a6243992c77931e58b98f5262745759d1a

[ "MIT" ]

null

2021-08/demo001.py

zhouyuanmin/MyDemo

664977a6243992c77931e58b98f5262745759d1a

[ "MIT" ]

null

2021-08/demo001.py

zhouyuanmin/MyDemo

664977a6243992c77931e58b98f5262745759d1a

[ "MIT" ]

null

sql_1 = """INSERT INTO `pt_exam`.`user_order` (`id`, `exam_id`, `user_id`, `order_number`, `pre_pay_number`, `entry_fee`, `actual_pay_fee`, `status`, `pay_url`, `pay_time`, `create_time`) VALUES (NULL, {exam_id}, {user_id}, 'zsyl20210811103413909170a3{user_id}{exam_id}', NULL, 1, 1, 1, 'weixin://wxpay/bizpayurl?pr=hDqke8nzz', '2021-08-11 12:00:00.000000', '2021-08-11 12:00:00');""" sql_2 = """INSERT INTO `pt_exam`.`user_exam` (`id`, `exam_id`, `user_id`, `room_id`, `step`, `id_photo_url`, `ticket_no`, `ticket_url`, `level`, `flag`, `certificate_url`, `certificate_no`, `create_time`, `resit_flag`) VALUES (null, {exam_id}, {user_id}, NULL, 1, NULL, NULL, NULL, NULL, 0, NULL, NULL, '2021-08-11 12:00:00', 0);""" # 配置 exam_id = 34 # 初级认证的人 # user_ids = [873, 1152, 1153, 1154, 1155, 1156, 1157, 1159, 264, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 535, 1180, 925, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 543, 297, 1194, 171, 1196, 1197, 1198, 1201, 1202, 1203, 1205, 1206, 1181, 1207, 1208, 574, 459, 1160, 849, 478, 873, 1005, 622, 249, 762, 252, 1149, 1150, 1151] # 中级认证 # user_ids = [480, 292, 581, 305, 819, 189, 537, 475, 348, 349, 1196, 1183, 1005] user_ids = [1211] # 陈默 1196 # 周源苠 1183 # 廖敏 1208 # 刁青青 1005 # 冯丹 1207 user_ids = list(set(user_ids)) # user_order表 for user_id in user_ids: print(sql_1.format(exam_id=exam_id, user_id=user_id)) # user_exam表 for user_id in user_ids: print(sql_2.format(exam_id=exam_id, user_id=user_id)) # print(user_ids)

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44a539f8897e3cf939be64e4260e6de784c27227

4,559

py

Python

tests/test_resource_library_parser.py

tervay/the-blue-alliance

e14c15cb04b455f90a2fcfdf4c1cdbf8454e17f8

[ "MIT" ]

266

2015-01-04T00:10:48.000Z

2022-03-28T18:42:05.000Z

tests/test_resource_library_parser.py

gregmarra/the-blue-alliance

5bedaf5c80b4623984760d3da3289640639112f9

[ "MIT" ]

2,673

2015-01-01T20:14:33.000Z

2022-03-31T18:17:16.000Z

tests/test_resource_library_parser.py

gregmarra/the-blue-alliance

5bedaf5c80b4623984760d3da3289640639112f9

[ "MIT" ]

230

2015-01-04T00:10:48.000Z

2022-03-26T18:12:04.000Z

import unittest2 import json from datafeeds.resource_library_parser import ResourceLibraryParser class TestResourceLibraryParser(unittest2.TestCase): def test_parse_hall_of_fame(self): with open('test_data/hall_of_fame.html', 'r') as f: teams, _ = ResourceLibraryParser.parse(f.read()) # Test number of teams self.assertEqual(len(teams), 14) # Test team 987 team = teams[0] self.assertEqual(team["team_id"], "frc987") self.assertEqual(team["team_number"], 987) self.assertEqual(team["year"], 2016) self.assertEqual(team["video"], "wpv-9yd_CJk") self.assertEqual(team["presentation"], "ILxVggTpXhs") self.assertEqual(team["essay"], "https://www.firstinspires.org/sites/default/files/uploads/resource_library/frc/game-and-season-info/awards/2016/chairmans/week-five/team-987.pdf") # Test team 597 team = teams[1] self.assertEqual(team["team_id"], "frc597") self.assertEqual(team["team_number"], 597) self.assertEqual(team["year"], 2015) self.assertEqual(team["video"], "2FKks-d6LOo") self.assertEqual(team["presentation"], "RBXj490clow") self.assertEqual(team["essay"], None) # Test team 27 team = teams[2] self.assertEqual(team["team_id"], "frc27") self.assertEqual(team["team_number"], 27) self.assertEqual(team["year"], 2014) self.assertEqual(team["video"], "BCz2yTVPxbM") self.assertEqual(team["presentation"], "1rE67fTRl98") self.assertEqual(team["essay"], "https://www.firstinspires.org/sites/default/files/uploads/resource_library/frc/game-and-season-info/awards/2015/2014-67-chairmans-handout.pdf") # Test team 1538 team = teams[3] self.assertEqual(team["team_id"], "frc1538") self.assertEqual(team["team_number"], 1538) self.assertEqual(team["year"], 2013) self.assertEqual(team["video"], "p62jRCMkoiw") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 1114 team = teams[4] self.assertEqual(team["team_id"], "frc1114") self.assertEqual(team["team_number"], 1114) self.assertEqual(team["year"], 2012) self.assertEqual(team["video"], "VqciMgjw-SY") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 359 team = teams[5] self.assertEqual(team["team_id"], "frc359") self.assertEqual(team["team_number"], 359) self.assertEqual(team["year"], 2011) self.assertEqual(team["video"], "e9IV1chHJtg") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 341 team = teams[6] self.assertEqual(team["team_id"], "frc341") self.assertEqual(team["team_number"], 341) self.assertEqual(team["year"], 2010) self.assertEqual(team["video"], "-AzvT02ZCNk") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 236 team = teams[7] self.assertEqual(team["team_id"], "frc236") self.assertEqual(team["team_number"], 236) self.assertEqual(team["year"], 2009) self.assertEqual(team["video"], "NmzCLohIZLg") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 842 team = teams[8] self.assertEqual(team["team_id"], "frc842") self.assertEqual(team["team_number"], 842) self.assertEqual(team["year"], 2008) self.assertEqual(team["video"], "N0LMLz6LK7U") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 365 team = teams[9] self.assertEqual(team["team_id"], "frc365") self.assertEqual(team["team_number"], 365) self.assertEqual(team["year"], 2007) self.assertEqual(team["video"], "f8MT7pSRXtg") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None) # Test team 111 team = teams[10] self.assertEqual(team["team_id"], "frc111") self.assertEqual(team["team_number"], 111) self.assertEqual(team["year"], 2006) self.assertEqual(team["video"], "SfCjZMMIt0k") self.assertEqual(team["presentation"], None) self.assertEqual(team["essay"], None)

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null

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44bc7feed227f738bf70037d970caf854f291e75

165

py

Python

src/mlalgms/calcutils.py

sandeepbhojwani/foremast-brain

b083ea08c0506517ede8501b9ad44408e89afdc6

[ "Apache-2.0" ]

null

src/mlalgms/calcutils.py

sandeepbhojwani/foremast-brain

b083ea08c0506517ede8501b9ad44408e89afdc6

[ "Apache-2.0" ]

null

src/mlalgms/calcutils.py

sandeepbhojwani/foremast-brain

b083ea08c0506517ede8501b9ad44408e89afdc6

[ "Apache-2.0" ]

null

#import numpy as np """ #moving avg #Parameters array of ts value #Returns moving avg """ #def moving_average(series, n): # return np.average(series[-n:])

13.75

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4

44d6fc186fe5f7b94930cbbd4516e7f34b023d02

513

py

Python

test/test_db.py

ndrini/10Opportunities

995b5bab974c856b05ea965935dbb1e5e2fb6145

[ "MIT" ]

null

test/test_db.py

ndrini/10Opportunities

995b5bab974c856b05ea965935dbb1e5e2fb6145

[ "MIT" ]

null

test/test_db.py

ndrini/10Opportunities

995b5bab974c856b05ea965935dbb1e5e2fb6145

[ "MIT" ]

null

from usefull import read_db def test_read_csv_db_simple(): ''' page msg parent choice end 1 1. Mi sembra che 0 False False 2 ...se ti trovassi 1 True False ''' assert read_db('db_simple.csv')[0]['page'] == 1 assert read_db('db_simple.csv')[0]['msg'][-3:] == 'che' assert read_db('db_simple.csv')[1]['msg'][:9] == '...se ti ' assert read_db('db_simple.csv')[0]['end'] == False def test_read_real_db(): assert len(read_db('db.csv')) == 167

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null

0

1

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4

44ff8250e602c081731b500fd7f016a2d72f7ce9

68

py

Python

main.py

AnEnigmaticBug/Connect-3

479c5a9cfda182f1959395594ce9c6d2e1f17d24

[ "MIT" ]

null

main.py

AnEnigmaticBug/Connect-3

479c5a9cfda182f1959395594ce9c6d2e1f17d24

[ "MIT" ]

null

main.py

AnEnigmaticBug/Connect-3

479c5a9cfda182f1959395594ce9c6d2e1f17d24

[ "MIT" ]

null

# NISHANT MAHAJAN # 2017A7PS0112P from gui import Gui Gui().loop()

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5.555556

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null

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1

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1

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4

7812a64c76a1b0cf4d9af364e1e9dae7223dc8a7

338

py

Python

tests/test_topics.py

Inria-Chile/risotto-backend

c2e597ac10724f4e8f30a6cd7fa2cc0c6fa806ea

[ "CECILL-B" ]

null

tests/test_topics.py

Inria-Chile/risotto-backend

c2e597ac10724f4e8f30a6cd7fa2cc0c6fa806ea

[ "CECILL-B" ]

null

tests/test_topics.py

Inria-Chile/risotto-backend

c2e597ac10724f4e8f30a6cd7fa2cc0c6fa806ea

[ "CECILL-B" ]

null

def test_get_topics(client): response = client.get("/topics/") contents = response.get_json() assert contents["status"] == "OK" assert type(contents["payload"]) is dict assert type(contents["payload"]["topics"]) is list assert type(contents["payload"]["subtopics"]) is dict assert response.status_code == 200

33.8

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null

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1

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4

781362495bb438b5389eabd92fef0d024f207f5a

29

py

Python

spin/tests/__init__.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

null

spin/tests/__init__.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

1

2019-10-26T12:42:59.000Z

spin/tests/__init__.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

null

"""SPIN module test unit."""

14.5

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0

1

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null

0

1

0

4

781fb6916fe464abca0f4c951e6c639b121a70e3

182

py

Python

django_dicom/models/utils/__init__.py

ZviBaratz/django-dicom

fc5d5443ebcab9af9705a2e81c58662789a34c62

[ "Apache-2.0" ]

8

2018-12-25T11:00:31.000Z

2022-02-03T12:05:56.000Z

django_dicom/models/utils/__init__.py

ZviBaratz/django-dicom

fc5d5443ebcab9af9705a2e81c58662789a34c62

[ "Apache-2.0" ]

49

2019-09-04T11:36:00.000Z

2022-03-20T12:33:04.000Z

django_dicom/models/utils/__init__.py

ZviBaratz/django-dicom

fc5d5443ebcab9af9705a2e81c58662789a34c62

[ "Apache-2.0" ]

4

2019-06-23T18:09:07.000Z

2019-08-30T15:43:18.000Z

""" Utilities for the :mod:`~django_dicom.models` module. """ from django_dicom.models.utils.utils import ( get_dicom_root, snake_case_to_camel_case, ) # flake8: noqa: F401

18.2

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1

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null

0

1

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4

782a71ba07dfa1012bcbb82312804ad3ca021f37

382

py

Python

third_party/p7zip/Utils/file_P7ZIP.py

VirtualLib/juice

3d5912059f3a80ec1fef5c5031a395578904fe9c

[ "MIT" ]

null

third_party/p7zip/Utils/file_P7ZIP.py

VirtualLib/juice

3d5912059f3a80ec1fef5c5031a395578904fe9c

[ "MIT" ]

null

third_party/p7zip/Utils/file_P7ZIP.py

VirtualLib/juice

3d5912059f3a80ec1fef5c5031a395578904fe9c

[ "MIT" ]

null

files_c=[ 'C/Threads.c', ] files_cpp=[ 'CPP/7zip/UI/P7ZIP/wxP7ZIP.cpp', 'CPP/Common/IntToString.cpp', 'CPP/Common/MyString.cpp', 'CPP/Common/MyVector.cpp', 'CPP/Common/StringConvert.cpp', 'CPP/Windows/FileDir.cpp', 'CPP/Windows/FileFind.cpp', 'CPP/Windows/FileIO.cpp', 'CPP/Windows/FileName.cpp', 'CPP/Common/MyWindows.cpp', 'CPP/myWindows/wine_date_and_time.cpp', ]

19.1

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0

null

1

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null

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4

7867336d033fecd4522cc24b40fe95d3630ecec8

275

py

Python

python/tvm/relay/op/_transform.py

Rasterer/tvm

1b863732ddd91423b1083626c64fba0523204a70

[ "Apache-2.0" ]

2

2018-09-10T09:48:03.000Z

2018-09-11T05:40:57.000Z

python/tvm/relay/op/_transform.py

Rasterer/tvm

1b863732ddd91423b1083626c64fba0523204a70

[ "Apache-2.0" ]

null

python/tvm/relay/op/_transform.py

Rasterer/tvm

1b863732ddd91423b1083626c64fba0523204a70

[ "Apache-2.0" ]

null

#pylint: disable=invalid-name, unused-argument """Backend compiler related feature registration""" from __future__ import absolute_import from . import op as _reg from .op import schedule_injective # strided_slice _reg.register_schedule("strided_slice", schedule_injective)

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null

0

1

0

1

0

1

0

4

78b1a07d25bb2f618f40e24ffc85d90df88326f4

89

py

Python

djnic/cambios/apps.py

avdata99/nic

70399bd78fd2b4b496d338e7959867ad12cdf477

[ "MIT" ]

8

2021-05-01T13:03:22.000Z

2021-12-17T21:50:04.000Z

djnic/cambios/apps.py

avdata99/nic

70399bd78fd2b4b496d338e7959867ad12cdf477

[ "MIT" ]

16

2020-11-20T23:18:22.000Z

2021-04-08T20:09:35.000Z

djnic/cambios/apps.py

OpenDataCordoba/nic

f9528856e13d106bdfb476cab1236bc5b8a92183

[ "MIT" ]

null

from django.apps import AppConfig class CambiosConfig(AppConfig): name = 'cambios'

14.833333

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89

6.7

0.9

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17.8

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false

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null

0

1

0

null

0

1

0

1

0

4

78c83ac5442915f637cfef0b30d9e2b358200620

389

py

Python

2021learning/logica.py

rulgamer03/Python-Projects

89a2418fadce0fd4674d3f7d3fa682a9aaa4b14d

[ "Apache-2.0" ]

1

2021-06-18T16:29:46.000Z

2021learning/logica.py

rulgamer03/Python-Projects

89a2418fadce0fd4674d3f7d3fa682a9aaa4b14d

[ "Apache-2.0" ]

null

2021learning/logica.py

rulgamer03/Python-Projects

89a2418fadce0fd4674d3f7d3fa682a9aaa4b14d

[ "Apache-2.0" ]

null

# operador logico print("Ingrese el valor de a") a = float(input()) print("Ingrese el valor de b") b = float(input()) print("b es mayor que a") print(b > a) print(type(b > a)) print("b es menor que a") print(b < a) print("b es mayor o igual que a") print(b >= a) print("b es menor o igual que a") print(b <= a) print("b es diferente de a") print(b != a) var = b == a print("b = a? ", var)

20.473684

33

0.619537

80

389

3.0125

0.25

0.273859

0.290456

0.19917

0.701245

0.435685

0.286307

0.207469

0

0.195373

389

18

34

21.611111

0.769968

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0.823529

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null

1

0

null

0

1

0

4

153bc4e6bb32d6b5175c608bdd91ccb925665630

211

py

Python

feedback/forms.py

davidavi1/ecosystem1

51033968e1548a08625fb42aa6e98017dc91ed65

[ "Unlicense" ]

null

feedback/forms.py

davidavi1/ecosystem1

51033968e1548a08625fb42aa6e98017dc91ed65

[ "Unlicense" ]

null

feedback/forms.py

davidavi1/ecosystem1

51033968e1548a08625fb42aa6e98017dc91ed65

[ "Unlicense" ]

null

from django import forms from .models import FeedBackModel class FeedBackForms(forms.ModelForm): class Meta: model = FeedBackModel fields = ('name', 'last_name', 'subject', 'text')

23.444444

58

0.658768

22

211

6.272727

0.727273

0

0.241706

211

8

59

26.375

0.8625

0

0.118227

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1

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false

0

0.333333

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null

0

1

0

null

0

1

0

1

0

4

156b9f30f0dfeefca81a2eedc9cb5062d26dcda5

268

py

Python

ib/ext/cfg/EWrapperMsgGenerator.py

gkatsQT/ibpy

d92fc7b03fc92bde0260adbcb217bac3aae27e2d

[ "BSD-3-Clause" ]

1

2016-11-23T23:55:35.000Z

ib/ext/cfg/EWrapperMsgGenerator.py

keven/ibpy

3a96091e1f798d60001c47dc731ffd65c12c0797

[ "BSD-3-Clause" ]

null

ib/ext/cfg/EWrapperMsgGenerator.py

keven/ibpy

3a96091e1f798d60001c47dc731ffd65c12c0797

[ "BSD-3-Clause" ]

1

2016-07-25T09:22:21.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """ ib.ext.cfg.EWrapperMsgGenerator -> config module for EWrapperMsgGenerator.java. """ modulePreamble = [ 'from ib.ext.AnyWrapperMsgGenerator import AnyWrapperMsgGenerator', 'from ib.ext.Util import Util', ]

26.8

83

0.701493

29

268

6.482759

0.689655

0.079787

0.095745

0

0.004386

0.149254

268

9

84

29.777778

0.820175

0.455224

0

0.676471

0.375

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

4

1586fdc938864aa8657885eb20f4ab9d341d045e

101

py

Python

1095.py

FahimFBA/URI-Problem-Solve

d718a95e5a873dffbce19d850998e8917ec87ebb

[ "Apache-2.0" ]

3

2020-11-25T19:05:31.000Z

2021-03-29T07:29:36.000Z

1095.py

FahimFBA/URI-Problem-Solve

d718a95e5a873dffbce19d850998e8917ec87ebb

[ "Apache-2.0" ]

null

1095.py

FahimFBA/URI-Problem-Solve

d718a95e5a873dffbce19d850998e8917ec87ebb

[ "Apache-2.0" ]

null

j,i=65,-2 for I in range (1,14): J= j-5 I=i+3 print('I=%d J=%d' %(I,J)) j=J i=I

12.625

29

0.39604

27

101

1.481481

0.481481

0.15

0

0.121212

0.346535

101

8

30

12.625

0.484848

0

0.088235

0

1

0

false

0

0.142857

1

0

1

null

0

1

0

1

0

null

0

4

15957c8e2d7c1506061057ba07ae93f4d1345623

613

py

Python

venv/Lib/site-packages/sqlalchemy/event/__init__.py

svercillo/flaskwebapi

48e3417c25fc25166203cb88f959345f548a38bc

[ "Apache-2.0" ]

2

2020-05-27T19:53:05.000Z

2020-05-27T19:53:07.000Z

venv/Lib/site-packages/sqlalchemy/event/__init__.py

svercillo/flaskwebapi

48e3417c25fc25166203cb88f959345f548a38bc

[ "Apache-2.0" ]

null

venv/Lib/site-packages/sqlalchemy/event/__init__.py

svercillo/flaskwebapi

48e3417c25fc25166203cb88f959345f548a38bc

[ "Apache-2.0" ]

null

# event/__init__.py # Copyright (C) 2005-2020 the SQLAlchemy authors and contributors # <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: http://www.opensource.org/licenses/mit-license.php from .api import CANCEL # noqa from .api import contains # noqa from .api import listen # noqa from .api import listens_for # noqa from .api import NO_RETVAL # noqa from .api import remove # noqa from .attr import RefCollection # noqa from .base import dispatcher # noqa from .base import Events # noqa from .legacy import _legacy_signature # noqa

34.055556

70

0.734095

89

613

4.966292

0.539326

0.162896

0.176471

0.192308

0

0.016227

0.195759

613

17

71

36.058824

0.880325

0.446982

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

ec65a2014d2302002135041aa6a23005e8b3ebc8

948

py

Python

app/update_logs_test.py

limshengli/tinypilot

aeba23e2e108008bea2b7577f16cfef949238648

[ "MIT" ]

1,334

2020-07-14T01:53:02.000Z

2021-06-08T09:48:28.000Z

app/update_logs_test.py

limshengli/tinypilot

aeba23e2e108008bea2b7577f16cfef949238648

[ "MIT" ]

320

2020-07-07T20:18:05.000Z

2021-06-07T21:18:42.000Z

app/update_logs_test.py

limshengli/tinypilot

aeba23e2e108008bea2b7577f16cfef949238648

[ "MIT" ]

124

2020-07-23T16:39:06.000Z

2021-06-04T10:22:53.000Z

import unittest import update_logs class UpdateLogsTest(unittest.TestCase): def test_get_new_logs_with_more_next_logs(self): self.assertEqual( "56789", update_logs.get_new_logs(prev_logs="01234", next_logs="0123456789")) def test_get_new_logs_with_more_prev_logs(self): self.assertEqual( "", update_logs.get_new_logs(prev_logs="0123456789", next_logs="01234")) def test_get_new_logs_with_no_common_logs(self): self.assertEqual( "56789", update_logs.get_new_logs(prev_logs="01234", next_logs="56789")) def test_get_new_logs_with_no_prev_logs(self): self.assertEqual( "0123456789", update_logs.get_new_logs(prev_logs="", next_logs="0123456789")) def test_get_new_logs_with_no_next_logs(self): self.assertEqual( "", update_logs.get_new_logs(prev_logs="01234", next_logs=""))

30.580645

80

0.671941

125

948

4.608

0.176

0.104167

0.173611

0.112847

0.810764

0.743056

0.560764

0.439236

0

0.101902

0.223629

948

30

81

31.6

0.680707

0

0.318182

0

0.079114

0

0.227273

1

0.227273

false

0

0.090909

0

0.363636

0

null

0

1

0

null

0

1

0

4

ec75cdcde97f555a405ef3a9aab448d7e1208cd7

248

py

Python

backend/backend/helps/apps.py

Redaloukil/PackageWay

977cf865c067bf6004cc9d82a995cd31be1c4889

[ "MIT" ]

null

backend/backend/helps/apps.py

Redaloukil/PackageWay

977cf865c067bf6004cc9d82a995cd31be1c4889

[ "MIT" ]

15

2019-12-28T10:54:22.000Z

2022-03-15T19:17:54.000Z

backend/backend/helps/apps.py

Redaloukil/PackageWay

977cf865c067bf6004cc9d82a995cd31be1c4889

[ "MIT" ]

1

2020-03-25T00:24:55.000Z

from django.apps import AppConfig class HelpsAppConfig(AppConfig): name = "backend.helps" verbose_name = "Helps" def ready(self): try: import users.signals # noqa F401 except ImportError: pass

20.666667

45

0.612903

26

248

5.807692

0.846154

0

0.017647

0.314516

248

12

46

20.666667

0.870588

0.03629

0

0.07563

0

1

0.111111

false

0.111111

0.333333

0

0.777778

0

1

0

null

0

null

0

1

0

1

0

4

ec8abd98b8afeba4e09a0db96f72cb66cd1ee3d5

208

wsgi

Python

alzhetect.wsgi

raidel123/AlzheTect

882e808d8ca30cd30d9e814f5dcc02c4395094a5

[ "Apache-2.0" ]

7

2018-05-23T02:00:04.000Z

2021-12-22T07:35:27.000Z

alzhetect.wsgi

raidel123/AlzheTect

882e808d8ca30cd30d9e814f5dcc02c4395094a5

[ "Apache-2.0" ]

7

2020-01-28T22:21:49.000Z

2022-02-09T23:35:51.000Z

alzhetect.wsgi

raidel123/AlzheTect

882e808d8ca30cd30d9e814f5dcc02c4395094a5

[ "Apache-2.0" ]

1

2019-10-17T19:25:18.000Z

#! /usr/bin/python import sys import logging logging.basicConfig(stream=sys.stderr) sys.path.insert(0,"/var/www/AlzheTect/") from trunk import app as application application.secret_key = 'freekeyforthesite'

23.111111

44

0.793269

29

208

5.655172

0.793103

0

0.005263

0.086538

208

8

45

26

0.857895

0.081731

0

0.189474

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ec95f038099c2f4d40e17ff06a718c7caf996d99

78

py

Python

Week 1 - Not so-simple Hello World/AhmadHelloWorld.py

Jasleenk47/BeginnerRoom-2020

32903f6917a236fe685106c148b8531c62210f1f

[ "Unlicense" ]

5

2021-01-19T00:31:22.000Z

2021-03-05T02:31:10.000Z

Week 1 - Not so-simple Hello World/AhmadHelloWorld.py

Jasleenk47/BeginnerRoom-2020

32903f6917a236fe685106c148b8531c62210f1f

[ "Unlicense" ]

34

2021-01-14T21:00:18.000Z

2021-03-11T17:57:26.000Z

Week 1 - Not so-simple Hello World/AhmadHelloWorld.py

Jasleenk47/BeginnerRoom-2020

32903f6917a236fe685106c148b8531c62210f1f

[ "Unlicense" ]

43

2021-01-14T20:40:47.000Z

2021-03-11T02:29:30.000Z

print("Starter") print("Ahmad") print("Hello World") print("Not so Simple")

19.5

22

0.679487

11

78

4.818182

0.727273

0

0.115385

78

4

22

19.5

0.768116

0

0.473684

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

4

eca3badb2edcb11210236b0e654dfdf450f51092

62

py

Python

django_mako_plus/models.py

wynnw/django-mako-plus

8a33eb3911fc84ddddd590152f475fd78c6a501f

[ "Apache-2.0" ]

79

2015-01-21T23:29:16.000Z

2021-08-22T03:38:20.000Z

django_mako_plus/models.py

wynnw/django-mako-plus

8a33eb3911fc84ddddd590152f475fd78c6a501f

[ "Apache-2.0" ]

34

2015-01-08T03:11:07.000Z

2021-09-07T15:04:43.000Z

django_mako_plus/models.py

wynnw/django-mako-plus

8a33eb3911fc84ddddd590152f475fd78c6a501f

[ "Apache-2.0" ]

23

2015-01-08T03:11:26.000Z

2021-05-22T11:12:24.000Z

# this app has no models; file here just to conform to Django

31

61

0.758065

12

62

3.916667

0.916667

0

0.209677

62

1

62

0.959184

0.951613

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

ecae0aa4c5127e932d611672cbee45f11d930aca

48

py

Python

__init__.py

fonsecag/Cluster_tools

a0bb250e49f185aea7632dbf0152319074fce038

[ "MIT" ]

null

__init__.py

fonsecag/Cluster_tools

a0bb250e49f185aea7632dbf0152319074fce038

[ "MIT" ]

null

__init__.py

fonsecag/Cluster_tools

a0bb250e49f185aea7632dbf0152319074fce038

[ "MIT" ]

null

from run import MainHandler __version__ = '0.1'

16

27

0.770833

7

48

4.714286

1

0

0.04878

0.145833

48

3

28

16

0.756098

0

0.061224

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

ecc35a532a3f26436634c487e5568644f8258c16

6,219

py

Python

apps/breakfast/tools/Life/tools/cx/messages/CxDownload.py

mtaghiza/tinyos-main-1

cac075f7eae46c6a37409e66137a78b9bc3a64b1

[ "BSD-3-Clause" ]

null

apps/breakfast/tools/Life/tools/cx/messages/CxDownload.py

mtaghiza/tinyos-main-1

cac075f7eae46c6a37409e66137a78b9bc3a64b1

[ "BSD-3-Clause" ]

null

apps/breakfast/tools/Life/tools/cx/messages/CxDownload.py

mtaghiza/tinyos-main-1

cac075f7eae46c6a37409e66137a78b9bc3a64b1

[ "BSD-3-Clause" ]

1

2022-02-21T14:31:18.000Z

# # This class is automatically generated by mig. DO NOT EDIT THIS FILE. # This class implements a Python interface to the 'CxDownload' # message type. # import tinyos.message.Message # The default size of this message type in bytes. DEFAULT_MESSAGE_SIZE = 9 # The Active Message type associated with this message. AM_TYPE = 208 class CxDownload(tinyos.message.Message.Message): # Create a new CxDownload of size 9. def __init__(self, data="", addr=None, gid=None, base_offset=0, data_length=9): tinyos.message.Message.Message.__init__(self, data, addr, gid, base_offset, data_length) self.amTypeSet(AM_TYPE) # Get AM_TYPE def get_amType(cls): return AM_TYPE get_amType = classmethod(get_amType) # # Return a String representation of this message. Includes the # message type name and the non-indexed field values. # def __str__(self): s = "Message <CxDownload> \n" try: s += " [networkSegment=0x%x]\n" % (self.get_networkSegment()) except: pass try: s += " [padding="; for i in range(0, 8): s += "0x%x " % (self.getElement_padding(i) & 0xff) s += "]\n"; except: pass return s # Message-type-specific access methods appear below. # # Accessor methods for field: networkSegment # Field type: short # Offset (bits): 0 # Size (bits): 8 # # # Return whether the field 'networkSegment' is signed (False). # def isSigned_networkSegment(self): return False # # Return whether the field 'networkSegment' is an array (False). # def isArray_networkSegment(self): return False # # Return the offset (in bytes) of the field 'networkSegment' # def offset_networkSegment(self): return (0 / 8) # # Return the offset (in bits) of the field 'networkSegment' # def offsetBits_networkSegment(self): return 0 # # Return the value (as a short) of the field 'networkSegment' # def get_networkSegment(self): return self.getUIntElement(self.offsetBits_networkSegment(), 8, 1) # # Set the value of the field 'networkSegment' # def set_networkSegment(self, value): self.setUIntElement(self.offsetBits_networkSegment(), 8, value, 1) # # Return the size, in bytes, of the field 'networkSegment' # def size_networkSegment(self): return (8 / 8) # # Return the size, in bits, of the field 'networkSegment' # def sizeBits_networkSegment(self): return 8 # # Accessor methods for field: padding # Field type: short[] # Offset (bits): 8 # Size of each element (bits): 8 # # # Return whether the field 'padding' is signed (False). # def isSigned_padding(self): return False # # Return whether the field 'padding' is an array (True). # def isArray_padding(self): return True # # Return the offset (in bytes) of the field 'padding' # def offset_padding(self, index1): offset = 8 if index1 < 0 or index1 >= 8: raise IndexError offset += 0 + index1 * 8 return (offset / 8) # # Return the offset (in bits) of the field 'padding' # def offsetBits_padding(self, index1): offset = 8 if index1 < 0 or index1 >= 8: raise IndexError offset += 0 + index1 * 8 return offset # # Return the entire array 'padding' as a short[] # def get_padding(self): tmp = [None]*8 for index0 in range (0, self.numElements_padding(0)): tmp[index0] = self.getElement_padding(index0) return tmp # # Set the contents of the array 'padding' from the given short[] # def set_padding(self, value): for index0 in range(0, len(value)): self.setElement_padding(index0, value[index0]) # # Return an element (as a short) of the array 'padding' # def getElement_padding(self, index1): return self.getUIntElement(self.offsetBits_padding(index1), 8, 1) # # Set an element of the array 'padding' # def setElement_padding(self, index1, value): self.setUIntElement(self.offsetBits_padding(index1), 8, value, 1) # # Return the total size, in bytes, of the array 'padding' # def totalSize_padding(self): return (64 / 8) # # Return the total size, in bits, of the array 'padding' # def totalSizeBits_padding(self): return 64 # # Return the size, in bytes, of each element of the array 'padding' # def elementSize_padding(self): return (8 / 8) # # Return the size, in bits, of each element of the array 'padding' # def elementSizeBits_padding(self): return 8 # # Return the number of dimensions in the array 'padding' # def numDimensions_padding(self): return 1 # # Return the number of elements in the array 'padding' # def numElements_padding(): return 8 # # Return the number of elements in the array 'padding' # for the given dimension. # def numElements_padding(self, dimension): array_dims = [ 8, ] if dimension < 0 or dimension >= 1: raise IndexException if array_dims[dimension] == 0: raise IndexError return array_dims[dimension] # # Fill in the array 'padding' with a String # def setString_padding(self, s): l = len(s) for i in range(0, l): self.setElement_padding(i, ord(s[i])); self.setElement_padding(l, 0) #null terminate # # Read the array 'padding' as a String # def getString_padding(self): carr = ""; for i in range(0, 4000): if self.getElement_padding(i) == chr(0): break carr += self.getElement_padding(i) return carr

26.130252

96

0.586429

745

6,219

4.806711

0.190604

0.049148

0.050265

0.040212

0.414409

0.241832

0.187936

0.14186

0.106116

0.064786

0

0.02018

0.322721

6,219

237

97

26.240506

0.83001

0.330921

0

0.232323

1

0

0.016515

0.005669

0

0.000986

0

1

0.282828

false

0.020202

0.010101

0.171717

0.545455

0

null

0

1

0

null

0

1

0

1

0

4

ece8955cfab2b69803e74e963f5ac76b16e9c256

117

py

Python

admin_tools/theming/apps.py

asherf/django-admin-tools

26a993545de7d68286be56ac640fe12acf1a1abe

[ "MIT" ]

711

2015-06-21T10:08:06.000Z

2022-03-25T08:46:37.000Z

admin_tools/theming/apps.py

asherf/django-admin-tools

26a993545de7d68286be56ac640fe12acf1a1abe

[ "MIT" ]

102

2015-06-22T12:38:21.000Z

2022-03-29T14:00:54.000Z

admin_tools/theming/apps.py

asherf/django-admin-tools

26a993545de7d68286be56ac640fe12acf1a1abe

[ "MIT" ]

149

2015-06-21T10:16:49.000Z

2022-03-28T13:11:47.000Z

# coding: utf-8 from django.apps import AppConfig class ThemingConfig(AppConfig): name = 'admin_tools.theming'

16.714286

33

0.752137

15

117

5.8

0.933333

0

0.010101

0.153846

117

6

34

19.5

0.868687

0.111111

0

0.186275

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ecee3bdc2df3c4340135e376313418070504c4bf

81

py

Python

aulaspythonintermediario/exercicios01/exercicio01/exercicio01.py

lel352/Curso-Python

d65484c807db52d57042eee20ccbd3131825fa98

[ "MIT" ]

1

2021-09-04T14:34:34.000Z

aulaspythonintermediario/exercicios01/exercicio01/exercicio01.py

lel352/Curso-Python

d65484c807db52d57042eee20ccbd3131825fa98

[ "MIT" ]

null

aulaspythonintermediario/exercicios01/exercicio01/exercicio01.py

lel352/Curso-Python

d65484c807db52d57042eee20ccbd3131825fa98

[ "MIT" ]

null

def saudacao(saudar, nome): print(saudar, nome) saudacao('Olá', 'Leandro')

13.5

27

0.666667

10

81

5.4

0.7

0.37037

0

0.160494

81

5

28

16.2

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1

0.333333

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1

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1

0

null

0

1

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4

ecf30a51d8793fd4c825e5bb2417de48539638e0

235

py

Python

time_series_transform/__init__.py

mrdragonbear/Time-Series-Transformer

a12bbd0c4563b4b150b4a47006e3e11457daef1b

[ "MIT" ]

1

2021-11-16T01:51:43.000Z

time_series_transform/__init__.py

sbhakat/Time-Series-Transformer

a12bbd0c4563b4b150b4a47006e3e11457daef1b

[ "MIT" ]

null

time_series_transform/__init__.py

sbhakat/Time-Series-Transformer

a12bbd0c4563b4b150b4a47006e3e11457daef1b

[ "MIT" ]

1

2020-11-06T06:57:23.000Z

from time_series_transform.transform_core_api import ( Pandas_Time_Series_Panel_Dataset, Pandas_Time_Series_Tensor_Dataset, ) from time_series_transform.stock_transform import ( Portfolio_Extractor, Stock_Extractor )

21.363636

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01b5f7952de578fc3d83a0bfbbf650bd840627a1

4,925

py

Python

dataactcore/migrations/versions/9960bbbe4d92_indexing_domain_models.py

brianherman/data-act-broker-backend

80eb055b9d245046192f7ad4fd0be7d0e11d2dec

[ "CC0-1.0" ]

1

2019-06-22T21:53:16.000Z

dataactcore/migrations/versions/9960bbbe4d92_indexing_domain_models.py

brianherman/data-act-broker-backend

80eb055b9d245046192f7ad4fd0be7d0e11d2dec

[ "CC0-1.0" ]

3

2021-08-22T11:47:45.000Z

2022-03-29T22:06:49.000Z

dataactcore/migrations/versions/9960bbbe4d92_indexing_domain_models.py

brianherman/data-act-broker-backend

80eb055b9d245046192f7ad4fd0be7d0e11d2dec

[ "CC0-1.0" ]

1

2020-07-17T23:50:56.000Z

"""Indexing domain models Revision ID: 9960bbbe4d92 Revises: d35ecdfc1da7 Create Date: 2017-09-06 13:09:21.210982 """ # revision identifiers, used by Alembic. revision = '9960bbbe4d92' down_revision = 'd35ecdfc1da7' branch_labels = None depends_on = None from alembic import op import sqlalchemy as sa def upgrade(engine_name): globals()["upgrade_%s" % engine_name]() def downgrade(engine_name): globals()["downgrade_%s" % engine_name]() def upgrade_data_broker(): ### commands auto generated by Alembic - please adjust! ### op.create_index(op.f('ix_cfda_program_archived_date'), 'cfda_program', ['archived_date'], unique=False) op.create_index(op.f('ix_cfda_program_program_number'), 'cfda_program', ['program_number'], unique=False) op.create_index(op.f('ix_cfda_program_published_date'), 'cfda_program', ['published_date'], unique=False) op.create_index(op.f('ix_city_code_city_code'), 'city_code', ['city_code'], unique=False) op.create_index(op.f('ix_city_code_state_code'), 'city_code', ['state_code'], unique=False) op.create_index(op.f('ix_county_code_county_number'), 'county_code', ['county_number'], unique=False) op.create_index(op.f('ix_county_code_state_code'), 'county_code', ['state_code'], unique=False) op.create_index(op.f('ix_program_activity_account_number'), 'program_activity', ['account_number'], unique=False) op.create_index(op.f('ix_program_activity_agency_id'), 'program_activity', ['agency_id'], unique=False) op.create_index(op.f('ix_program_activity_budget_year'), 'program_activity', ['budget_year'], unique=False) op.create_index(op.f('ix_program_activity_program_activity_code'), 'program_activity', ['program_activity_code'], unique=False) op.create_index(op.f('ix_program_activity_program_activity_name'), 'program_activity', ['program_activity_name'], unique=False) op.create_index(op.f('ix_sf_133_agency_identifier'), 'sf_133', ['agency_identifier'], unique=False) op.create_index(op.f('ix_sf_133_allocation_transfer_agency'), 'sf_133', ['allocation_transfer_agency'], unique=False) op.create_index(op.f('ix_sf_133_fiscal_year'), 'sf_133', ['fiscal_year'], unique=False) op.create_index(op.f('ix_sf_133_period'), 'sf_133', ['period'], unique=False) op.create_index('ix_sf_133_tas_group', 'sf_133', ['tas', 'fiscal_year', 'period', 'line'], unique=True) op.drop_index('ix_sf_133_tas', table_name='sf_133') op.create_index(op.f('ix_sf_133_tas'), 'sf_133', ['tas'], unique=False) op.create_index(op.f('ix_states_state_code'), 'states', ['state_code'], unique=False) op.create_index(op.f('ix_zips_congressional_district_no'), 'zips', ['congressional_district_no'], unique=False) op.create_index(op.f('ix_zips_county_number'), 'zips', ['county_number'], unique=False) op.create_index(op.f('ix_zips_state_abbreviation'), 'zips', ['state_abbreviation'], unique=False) ### end Alembic commands ### def downgrade_data_broker(): ### commands auto generated by Alembic - please adjust! ### op.drop_index(op.f('ix_zips_state_abbreviation'), table_name='zips') op.drop_index(op.f('ix_zips_county_number'), table_name='zips') op.drop_index(op.f('ix_zips_congressional_district_no'), table_name='zips') op.drop_index(op.f('ix_states_state_code'), table_name='states') op.drop_index(op.f('ix_sf_133_tas'), table_name='sf_133') op.create_index('ix_sf_133_tas', 'sf_133', ['tas', 'fiscal_year', 'period', 'line'], unique=True) op.drop_index('ix_sf_133_tas_group', table_name='sf_133') op.drop_index(op.f('ix_sf_133_period'), table_name='sf_133') op.drop_index(op.f('ix_sf_133_fiscal_year'), table_name='sf_133') op.drop_index(op.f('ix_sf_133_allocation_transfer_agency'), table_name='sf_133') op.drop_index(op.f('ix_sf_133_agency_identifier'), table_name='sf_133') op.drop_index(op.f('ix_program_activity_program_activity_name'), table_name='program_activity') op.drop_index(op.f('ix_program_activity_program_activity_code'), table_name='program_activity') op.drop_index(op.f('ix_program_activity_budget_year'), table_name='program_activity') op.drop_index(op.f('ix_program_activity_agency_id'), table_name='program_activity') op.drop_index(op.f('ix_program_activity_account_number'), table_name='program_activity') op.drop_index(op.f('ix_county_code_state_code'), table_name='county_code') op.drop_index(op.f('ix_county_code_county_number'), table_name='county_code') op.drop_index(op.f('ix_city_code_state_code'), table_name='city_code') op.drop_index(op.f('ix_city_code_city_code'), table_name='city_code') op.drop_index(op.f('ix_cfda_program_published_date'), table_name='cfda_program') op.drop_index(op.f('ix_cfda_program_program_number'), table_name='cfda_program') op.drop_index(op.f('ix_cfda_program_archived_date'), table_name='cfda_program') ### end Alembic commands ###

57.941176

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0

null

0

1

0

null

0

4

01c505d3cae8d51474445b8e18b08db6a7cc9659

112

py

Python

api/src/application/wsgi.py

iliaskaras/VCFHandler

5372659e4472207be964e0d233994a0ffff536fe

[ "MIT" ]

null

api/src/application/wsgi.py

iliaskaras/VCFHandler

5372659e4472207be964e0d233994a0ffff536fe

[ "MIT" ]

null

api/src/application/wsgi.py

iliaskaras/VCFHandler

5372659e4472207be964e0d233994a0ffff536fe

[ "MIT" ]

null

from application.factories import vcf_handler_api application = vcf_handler_api( name="VCF Handler API", )

18.666667

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112

5.6

0.533333

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112

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0

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1

0

false

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0.25

0

1

0

null

1

0

1

0

null

0

4

01e4d8cad531270d0858cb5534a73935f7804e5e

103

py

Python

kjn_biedronka_demo/kjn_pricetag/apps.py

kornellewy/kjn_biedronka_demo

a1b0d3baaaee5bca4977b76fa0b3934a533a2f59

[ "MIT" ]

1

2020-10-20T10:33:58.000Z

kjn_biedronka_demo/kjn_pricetag/apps.py

kornellewy/kjn_biedronka_demo

a1b0d3baaaee5bca4977b76fa0b3934a533a2f59

[ "MIT" ]

null

kjn_biedronka_demo/kjn_pricetag/apps.py

kornellewy/kjn_biedronka_demo

a1b0d3baaaee5bca4977b76fa0b3934a533a2f59

[ "MIT" ]

null

from django.apps import AppConfig class KjnPricetagConfig(AppConfig): name = 'kjn_pricetag'

17.166667

36

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103

6.818182

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103

5

37

20.6

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0.122449

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1

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false

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1

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1

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null

0

1

0

null

0

1

0

1

0

4

bf0ff252d5a80eb424fe2ca9f264baafddb04d3e

47

py

Python

venv/lib/python3.7/hmac.py

OseiasBeu/PyECom

2ea4e7e3be4ca015fb1bbc1083aa3f2d44accc5f

[ "CC0-1.0" ]

1

2020-08-16T04:04:23.000Z

venv/lib/python3.7/hmac.py

OseiasBeu/PyECom

2ea4e7e3be4ca015fb1bbc1083aa3f2d44accc5f

[ "CC0-1.0" ]

null

venv/lib/python3.7/hmac.py

OseiasBeu/PyECom

2ea4e7e3be4ca015fb1bbc1083aa3f2d44accc5f

[ "CC0-1.0" ]

null

/home/oseiasbeu/anaconda3/lib/python3.7/hmac.py

47

0.829787

8

47

4.875

1

0

0.06383

0

47

1

47

0.765957

0

null

0

null

0

1

0

null

0

1

0

null

0

1

0

4

bf1bc3b976e8f06a9301d90ff36fcbbeff7628e4

230

py

Python

src/sage/version.py

yzpopulation/sage

d2dc2f80b5a8e039701e292653e25366e3e5ec1e

[ "BSL-1.0" ]

null

src/sage/version.py

yzpopulation/sage

d2dc2f80b5a8e039701e292653e25366e3e5ec1e

[ "BSL-1.0" ]

null

src/sage/version.py

yzpopulation/sage

d2dc2f80b5a8e039701e292653e25366e3e5ec1e

[ "BSL-1.0" ]

null

# Sage version information for Python scripts # This file is auto-generated by the sage-update-version script, do not edit! version = '9.5.beta2' date = '2021-09-26' banner = 'SageMath version 9.5.beta2, Release Date: 2021-09-26'

38.333333

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4.384615

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0.163743

0

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230

5

78

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null

0

1

0

1

0

1

0

1

0

null

0

4

bf1c9599a424608600110263d2e23b1761467296

747

py

Python

python.py

weijie88/test

d2f0c4ff4ca88fa1ef6518ba2b1f040216142125

[ "Apache-2.0" ]

null

python.py

weijie88/test

d2f0c4ff4ca88fa1ef6518ba2b1f040216142125

[ "Apache-2.0" ]

null

python.py

weijie88/test

d2f0c4ff4ca88fa1ef6518ba2b1f040216142125

[ "Apache-2.0" ]

null

# class Cat(Resource): # def get(self): # return {'data':'get'} # # def post(self): # return {'data': 'post'} # # def put(self): # return {'data': 'put'} # # def delete(self): # return {'data': 'delete'} from pip._vendor.distlib.resources import Resource class Home(Resource): def get(self): # return render_template('test.html') pass class Market(Resource): def get(self): # return render_template('market/market.html') pass class Cart(Resource): def get(self): # return render_template('art/cart.html') pass class Mine(Resource): def get(self): # return render_template('mine/mine.html') pass print("sss")

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null

0

1

0

1

0

1

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4

170d1e755079223aa85454344429845bca8ebd51

464

py

Python

bfgame/components/shield.py

ChrisLR/BasicDungeonRL

b293d40bd9a0d3b7aec41b5e1d58441165997ff1

[ "MIT" ]

3

2017-10-28T11:28:38.000Z

2018-09-12T09:47:00.000Z

bfgame/components/shield.py

ChrisLR/BasicDungeonRL

b293d40bd9a0d3b7aec41b5e1d58441165997ff1

[ "MIT" ]

null

bfgame/components/shield.py

ChrisLR/BasicDungeonRL

b293d40bd9a0d3b7aec41b5e1d58441165997ff1

[ "MIT" ]

null

from core.components import Component, listing @listing.register class Shield(Component): NAME = "shield" __slots__ = ["armor_class_melee", "armor_class_missile"] def __init__(self, armor_class_melee, armor_class_missile): super().__init__() self.armor_class_melee = armor_class_melee self.armor_class_missile = armor_class_missile def copy(self): return Shield(self.armor_class_melee, self.armor_class_missile)

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72

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0

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0.636364

0

null

1

0

null

0

1

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4

17871ee3057c619c366c976b876ad96d5d051de6

156

py

Python

QAStrategy/__init__.py

vx-qa/QAStrategy

6f8bcf94d31d2e0a6d7cf339067322366e44e6fc

[ "MIT" ]

null

QAStrategy/__init__.py

vx-qa/QAStrategy

6f8bcf94d31d2e0a6d7cf339067322366e44e6fc

[ "MIT" ]

null

QAStrategy/__init__.py

vx-qa/QAStrategy

6f8bcf94d31d2e0a6d7cf339067322366e44e6fc

[ "MIT" ]

null

__version__ = '0.0.22' __author__ = 'yutiansut' from QAStrategy.util import QA_data_futuremin_resample from QAStrategy.qactabase import QAStrategyCTABase

22.285714

54

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156

6.263158

0.789474

0.235294

0

0.028571

0.102564

156

6

55

26

0.821429

0

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1

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false

0

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0

1

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null

1

0

1

0

null

0

1

0

4

bd7296575889784868618f14db8687ff341b387d

26

py

Python

grow/settings/__init__.py

jpk0727/growApp

016d56de740c14e89440a6bf61fccc937e792473

[ "MIT" ]

null

grow/settings/__init__.py

jpk0727/growApp

016d56de740c14e89440a6bf61fccc937e792473

[ "MIT" ]

null

grow/settings/__init__.py

jpk0727/growApp

016d56de740c14e89440a6bf61fccc937e792473

[ "MIT" ]

null

""" Settings for grow """

13

25

0.576923

3

26

5

1

0

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26

1

26

0.714286

0.653846

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

bd87d35dc8ef1a62928df58d50d1b4875fac32f4

297

py

Python

tests/test_rocket_powered_landing.py

yuokamoto/PythonRobotics

754256d15e074f6091bc6c9b7e8e6499df865fb6

[ "MIT" ]

11

2019-03-21T17:55:19.000Z

2021-11-18T01:25:48.000Z

tests/test_rocket_powered_landing.py

yuokamoto/PythonRobotics

754256d15e074f6091bc6c9b7e8e6499df865fb6

[ "MIT" ]

null

tests/test_rocket_powered_landing.py

yuokamoto/PythonRobotics

754256d15e074f6091bc6c9b7e8e6499df865fb6

[ "MIT" ]

5

2019-03-26T10:36:14.000Z

2020-04-16T07:24:25.000Z

from unittest import TestCase import sys sys.path.append("./AerialNavigation/rocket_powered_landing/") from AerialNavigation.rocket_powered_landing import rocket_powered_landing as m print(__file__) class Test(TestCase): def test1(self): m.show_animation = False m.main()

19.8

79

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297

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0.334884

0

0.004

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297

14

80

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false

0

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0.555556

0.111111

0

null

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1

0

null

0

1

0

1

0

4

bdbdffb8d5a6c27b50f218d5b692d0f7f8c5a5d7

185

py

Python

utils/language_modeling/__init__.py

Lednik7/data_fusion

2cac8ee2ca6c144218731795bc118f6c355bd477

[ "MIT" ]

1

2022-01-23T10:18:16.000Z

utils/language_modeling/__init__.py

Lednik7/data_fusion

2cac8ee2ca6c144218731795bc118f6c355bd477

[ "MIT" ]

null

utils/language_modeling/__init__.py

Lednik7/data_fusion

2cac8ee2ca6c144218731795bc118f6c355bd477

[ "MIT" ]

null

from .data import ( get_dataloaders, Collator ) from .train import Trainer from .model import get_model __all__ = ['get_dataloaders', 'Collator', 'Trainer', 'get_model']

23.125

65

0.697297

22

185

5.5

0.454545

0.14876

0.363636

0

0.194595

185

8

65

23.125

0.812081

0

0.217877

0

1

0

false

0

0.428571

0

0.428571

0

1

0

null

0

1

0

1

0

null

0

1

0

4

bdd279599e1187ff595e03201dfe2b321502e136

212

py

Python

py/solutions/goorm/financial_crisis.py

aid95/algorithm-diary

ee7df895761b095d02a08f762c682af5b93add4b

[ "MIT" ]

null

py/solutions/goorm/financial_crisis.py

aid95/algorithm-diary

ee7df895761b095d02a08f762c682af5b93add4b

[ "MIT" ]

null

py/solutions/goorm/financial_crisis.py

aid95/algorithm-diary

ee7df895761b095d02a08f762c682af5b93add4b

[ "MIT" ]

null

def solution(salaries: list[int]) -> int: return sorted(salaries)[1] if __name__ == '__main__': user_input = input() param = [int(x) for x in user_input.split()] print(solution(salaries=param))

23.555556

48

0.65566

29

212

4.448276

0.655172

0.248062

0

0.005814

0.188679

212

8

49

26.5

0.744186

0

0.037736

0

1

0.166667

false

0

0.166667

0.333333

0.166667

1

0

null

1

0

1

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null

0

1

0

4

bdebaf164c0ff546fcd1eead404c3f46b7076366

2,997

py

Python

tb_rest_client/api/api_pe/__init__.py

maksonlee/python_tb_rest_client

a6cd17ef4de31f68c3226b7a9835292fbac4b1fa

[ "Apache-2.0" ]

1

2021-07-19T10:09:04.000Z

tb_rest_client/api/api_pe/__init__.py

moravcik94/python_tb_rest_client

985361890cdf4ccce93d2b24905ad9003c8dfcaa

[ "Apache-2.0" ]

null

tb_rest_client/api/api_pe/__init__.py

moravcik94/python_tb_rest_client

985361890cdf4ccce93d2b24905ad9003c8dfcaa

[ "Apache-2.0" ]

null

# Copyright 2020. ThingsBoard # # # 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 absolute_import # flake8: noqa # import apis into api_pe package from .admin_controller_api import AdminControllerApi from .alarm_controller_api import AlarmControllerApi from .asset_controller_api import AssetControllerApi from .audit_log_controller_api import AuditLogControllerApi from .blob_entity_controller_api import BlobEntityControllerApi from .converter_controller_api import ConverterControllerApi from .custom_menu_controller_api import CustomMenuControllerApi from .custom_translation_controller_api import CustomTranslationControllerApi from .customer_controller_api import CustomerControllerApi from .dashboard_controller_api import DashboardControllerApi from .device_controller_api import DeviceControllerApi from .entity_group_controller_api import EntityGroupControllerApi from .entity_view_controller_api import EntityViewControllerApi from .event_controller_api import EventControllerApi from .group_permission_controller_api import GroupPermissionControllerApi from .http_integration_controller_api import HttpIntegrationControllerApi from .integration_controller_api import IntegrationControllerApi from .ocean_connect_integration_controller_api import OceanConnectIntegrationControllerApi from .owner_controller_api import OwnerControllerApi from .report_controller_api import ReportControllerApi from .role_controller_api import RoleControllerApi from .rule_chain_controller_api import RuleChainControllerApi from .rule_engine_controller_api import RuleEngineControllerApi from .scheduler_event_controller_api import SchedulerEventControllerApi from .self_registration_controller_api import SelfRegistrationControllerApi from .sig_fox_integration_controller_api import SigFoxIntegrationControllerApi from .sign_up_controller_api import SignUpControllerApi from .t_mobile_iot_cdp_integration_controller_api import TMobileIotCdpIntegrationControllerApi from .tenant_controller_api import TenantControllerApi from .thing_park_integration_controller_api import ThingParkIntegrationControllerApi from .trail_controller_api import TrailControllerApi from .user_controller_api import UserControllerApi from .user_permissions_controller_api import UserPermissionsControllerApi from .white_labeling_controller_api import WhiteLabelingControllerApi from .widgets_bundle_controller_api import WidgetsBundleControllerApi

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da513afea0870e586c6e6f6c68b2dc83e2f2c9d2

170

py

Python

python/syndicate/rg/drivers/s3/config.py

jcnelson/syndicate

4837265be3e0aa18cdf4ee50316dbfc2d1f06e5b

[ "Apache-2.0" ]

16

2015-01-02T15:39:04.000Z

2016-03-17T06:38:46.000Z

python/syndicate/rg/drivers/s3/config.py

jcnelson/syndicate

4837265be3e0aa18cdf4ee50316dbfc2d1f06e5b

[ "Apache-2.0" ]

37

2015-01-28T20:58:05.000Z

2016-03-22T04:01:32.000Z

python/syndicate/rg/drivers/s3/config.py

jcnelson/syndicate

4837265be3e0aa18cdf4ee50316dbfc2d1f06e5b

[ "Apache-2.0" ]

8

2015-04-08T02:26:03.000Z

2016-03-04T05:56:24.000Z

#!/usr/bin/python CONFIG = { "BUCKET": "sd_s3_testbucket", "EXEC_FMT": "/usr/bin/python -m syndicate.rg.gateway", "DRIVER": "syndicate.rg.drivers.s3" }

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da5aaf00a6ad5e06519d62f96aea28416baf2d0d

207

py

Python

appaddrule/__init__.py

wanghaisheng/azure_func_pywebio_wsgi_starter

b5f210b7c867ab8bef456bc476c19bda6deb9795

[ "MIT" ]

1

2022-03-28T18:08:30.000Z

appnoshare/__init__.py

wanghaisheng/azure_func_pywebio_wsgi_starter

b5f210b7c867ab8bef456bc476c19bda6deb9795

[ "MIT" ]

null

appnoshare/__init__.py

wanghaisheng/azure_func_pywebio_wsgi_starter

b5f210b7c867ab8bef456bc476c19bda6deb9795

[ "MIT" ]

null

import azure.functions as func from .add_url_rule import app def main(req: func.HttpRequest, context: func.Context) -> func.HttpResponse: return func.WsgiMiddleware(app.wsgi_app).handle(req, context)

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null

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4

da750d0740739eec48b98e5fcd911525f9a9b4a3

525

py

Python

codewars/8kyu/counting sheep/main_test.py

ictcubeMENA/Training_one

dff6bee96ba42babe4888e5cf9a9448a6fd93fc3

[ "MIT" ]

null

codewars/8kyu/counting sheep/main_test.py

ictcubeMENA/Training_one

dff6bee96ba42babe4888e5cf9a9448a6fd93fc3

[ "MIT" ]

2

2019-01-22T10:53:42.000Z

2019-01-31T08:02:48.000Z

codewars/8kyu/counting sheep/main_test.py

ictcubeMENA/Training_one

dff6bee96ba42babe4888e5cf9a9448a6fd93fc3

[ "MIT" ]

13

2019-01-22T10:37:42.000Z

2019-01-25T13:30:43.000Z

import main import unittest class testsheep(unittest.TestCase): def testing(self): array1 = [True, True, True, False, True, True, True, True , True, False, True, False, True, False, False, True , True, True, True, True , False, False, True, True ]; self.assertEqual(main.count_sheeps(array1), 17, "There are 17 sheeps in total, not %s" % count_sheeps(array1)) if __name__ == '__main__': unittest.main()

32.8125

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525

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118

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null

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null

0

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0

4

da8fceb32a06d24f6058a6fcba8fc9efb8cbbeea

504

py

Python

OpenCV Python/4. Image Processing/10. histograms/3. 2D histogram.py

Ashleshk/Machine-Learning-Data-Science-Deep-Learning

03357ab98155bf73b8f1d2fd53255cc16bea2333

[ "MIT" ]

1

2020-05-24T06:55:31.000Z

OpenCV Python/4. Image Processing/10. histograms/3. 2D histogram.py

Ashleshk/Machine-Learning-Data-Science-Deep-Learning

03357ab98155bf73b8f1d2fd53255cc16bea2333

[ "MIT" ]

null

OpenCV Python/4. Image Processing/10. histograms/3. 2D histogram.py

Ashleshk/Machine-Learning-Data-Science-Deep-Learning

03357ab98155bf73b8f1d2fd53255cc16bea2333

[ "MIT" ]

null

import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2.imread('home.jpg') hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) hist = cv2.calcHist( [hsv], [0, 1], None, [180, 256], [0, 180, 0, 256] ) plt.imshow(hist,interpolation = 'nearest') plt.show() # in numpy import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2.imread('home.jpg') hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) hist, xbins, ybins = np.histogram2d(h.ravel(),s.ravel(),[180,256],[[0,180],[0,256]])

24

84

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85

504

4.117647

0.411765

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504

20

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null

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1

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4

16ffa203132158dc3fd91b6c3eb252393aac5ec3

69

py

Python

multitag-code/src/test.py

terencelee-uni/multitag-heroku

38945052912ddb55f5d98773e081ccc7b98c6373

[ "MIT" ]

null

multitag-code/src/test.py

terencelee-uni/multitag-heroku

38945052912ddb55f5d98773e081ccc7b98c6373

[ "MIT" ]

null

multitag-code/src/test.py

terencelee-uni/multitag-heroku

38945052912ddb55f5d98773e081ccc7b98c6373

[ "MIT" ]

null

import gc import torch gc.collect() torch.cuda.empty_cache()

9.857143

25

0.695652

10

69

4.7

0.7

0

0.202899

69

6

26

11.5

0.854545

0

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0

true

0

0.5

0

0.5

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1

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null

0

1

0

null

0

1

0

1

0

4

e517a95cdcc18e8221e9ea92c1671b9454843640

610

py

Python

lunchmoney/__init__.py

Christofon/lunchmoney-python

8f55af2717bc979577debfe940941dc3627c6018

[ "MIT" ]

null

lunchmoney/__init__.py

Christofon/lunchmoney-python

8f55af2717bc979577debfe940941dc3627c6018

[ "MIT" ]

null

lunchmoney/__init__.py

Christofon/lunchmoney-python

8f55af2717bc979577debfe940941dc3627c6018

[ "MIT" ]

null

from .tags import Tags from .categories import Categories import os import requests # TODO maybe only for testing needed # LUNCHMONEY_API_KEY = os.environ.get('LUNCHMONEY_API_KEY', None) from dotenv import load_dotenv load_dotenv() LUNCHMONEY_API_KEY = os.getenv('LUNCHMONEY_API_KEY') class APIKeyMissingError(Exception): pass if LUNCHMONEY_API_KEY is None: raise APIKeyMissingError( 'All functionality require an API key. Visit "https://my.lunchmoney.app/developers" to get one.' ) session = requests.Session() session.params = {} session.params['access_token'] = LUNCHMONEY_API_KEY

24.4

104

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610

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0.210989

0.079121

0

0.144262

610

24

105

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0

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false

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null

0

1

0

1

0

4

e5305625c9e9dae45c52f19c66a53acf6a2aebc6

264

py

Python

scripts/common/base.py

gokhankesler/python-etl-design

155e1d693310a71c808e3b56c369d8ebac30fb6d

[ "MIT" ]

null

scripts/common/base.py

gokhankesler/python-etl-design

155e1d693310a71c808e3b56c369d8ebac30fb6d

[ "MIT" ]

1

2022-03-25T21:19:29.000Z

2022-03-25T22:26:03.000Z

scripts/common/base.py

gokhankesler/python-etl-design

155e1d693310a71c808e3b56c369d8ebac30fb6d

[ "MIT" ]

null

from sqlalchemy import create_engine from sqlalchemy.orm import Session from sqlalchemy.orm import declarative_base engine = create_engine( 'postgresql+psycopg2://postgres:password@localhost:1234/postgres' ) session = Session(engine) Base = declarative_base()

29.333333

69

0.818182

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264

6.625

0.46875

0.198113

0.160377

0.216981

0

0.021097

0.102273

264

9

70

29.333333

0.873418

0

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false

0.125

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0.375

0

null

0

1

0

1

0

null

0

1

0

4

e5411285dd40466069ba2a8ee625afaa460ac90a

125

py

Python

main.py

hsnakkaya/XpyFollowers

17e6acdeffb9f6a6df956fe725283b93c8e2fc89

[ "MIT" ]

null

main.py

hsnakkaya/XpyFollowers

17e6acdeffb9f6a6df956fe725283b93c8e2fc89

[ "MIT" ]

null

main.py

hsnakkaya/XpyFollowers

17e6acdeffb9f6a6df956fe725283b93c8e2fc89

[ "MIT" ]

null

from XpyFollowers import* # scraper(27, 28, 'twitter_list') nodes_process(27, 'twitter_list') edges_process(27)

6.944444

33

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16

125

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0.078431

0.184

125

17

34

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0.735294

0.248

0

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true

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null

1

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null

0

1

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1

0

4

e56ab6f523c0e56fee048e434b02d05c5574230f

398

py

Python

splikes/connections/__init__.py

bblais/Plasticnet

e450e56a9b993e361873b6a235fdcc55a5690abb

[ "MIT" ]

null

splikes/connections/__init__.py

bblais/Plasticnet

e450e56a9b993e361873b6a235fdcc55a5690abb

[ "MIT" ]

null

splikes/connections/__init__.py

bblais/Plasticnet

e450e56a9b993e361873b6a235fdcc55a5690abb

[ "MIT" ]

1

2020-01-16T18:20:53.000Z

from .BCM import BCM_LawCooper from .BCM import BCM from .BCM import BCM_LawCooper_Offset from .BCM import BCM_TwoThreshold from .calcium import calcium from .STDP import STDP from .Triplet import Gerstner2006 from .Triplet import Triplet_BCM from .Triplet import Triplet_BCM_LawCooper from .Triplet import Triplet_BCM_LawCooper2 from .triplet_julijana import triplet_julijana from . import process

33.166667

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398

12

47

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