xszheng2020/the_stack_dedup_python_hits_3 · Datasets at Hugging Face

0d947c35c21b3239f4d20a797f709237eaf0ece0

247

py

Python

tests/test_runner_deprecation_app/tests.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

1

2019-02-10T19:33:27.000Z

tests/test_runner_deprecation_app/tests.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

null

tests/test_runner_deprecation_app/tests.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

1

2020-05-03T20:42:29.000Z

import warnings from django.test import TestCase warnings.warn("module-level warning from deprecation_app", DeprecationWarning) class DummyTest(TestCase): def test_warn(self): warnings.warn("warning from test", DeprecationWarning)

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0

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0

1

0

3

0da4e0fd133dd93d9666709ef0d8d3b74297b789

1,519

py

Python

test_utils.py

moritz-gerster/separating_periodic_from_aperiodic_PSDs

79d771e8cac21098aac26ee369e0994add3e2bf9

[ "MIT" ]

2

2021-11-05T14:58:34.000Z

2022-01-05T09:11:33.000Z

test_utils.py

moritz-gerster/separating_periodic_from_aperiodic_PSDs

79d771e8cac21098aac26ee369e0994add3e2bf9

[ "MIT" ]

null

test_utils.py

moritz-gerster/separating_periodic_from_aperiodic_PSDs

79d771e8cac21098aac26ee369e0994add3e2bf9

[ "MIT" ]

null

import numpy as np from utils import elec_phys_signal # Test simulation of electrophysiological signals def test_elec_phys_signal(): # test output output = elec_phys_signal(1) assert isinstance(output, tuple) assert isinstance(output[0], np.ndarray) assert isinstance(output[1], np.ndarray) # test impact of 1/f exponent assert not np.allclose(elec_phys_signal(1)[0], elec_phys_signal(2)[0]) # test impact of periodic_params params1 = dict(exponent=1, periodic_params=[(1, 1, 1), (2, 2, 2)]) params2 = dict(exponent=1, periodic_params=[(3, 3, 3), (2, 2, 2)]) aperiodic_signal1, full_signal1 = elec_phys_signal(**params1) aperiodic_signal2, full_signal2 = elec_phys_signal(**params2) assert not np.allclose(full_signal1, full_signal2) assert np.allclose(aperiodic_signal1, aperiodic_signal2) # test impact of noise level assert not np.allclose(elec_phys_signal(1, nlv=1)[0], elec_phys_signal(1, nlv=2)[0]) # test impact of highpass assert not np.allclose(elec_phys_signal(1, highpass=1)[0], elec_phys_signal(1, highpass=0)[0]) # test duration of signal assert elec_phys_signal(1, sample_rate=24, duration=1)[0].shape[0] == 24-2 assert elec_phys_signal(1, sample_rate=1, duration=24)[0].shape[0] == 24-2 # test impact of seed assert not np.allclose(elec_phys_signal(1, seed=0)[0], elec_phys_signal(1, seed=1)[0])

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0da65955b301e345723b597b834f1ffd2509a527

520

py

Python

apps/controllerx/core/integration/deconz.py

sreknob/controllerx

f5e4475dae93d171ba3056399378107df1d52fa5

[ "MIT" ]

1

2020-02-28T17:26:36.000Z

apps/controllerx/core/integration/deconz.py

sreknob/controllerx

f5e4475dae93d171ba3056399378107df1d52fa5

[ "MIT" ]

null

apps/controllerx/core/integration/deconz.py

sreknob/controllerx

f5e4475dae93d171ba3056399378107df1d52fa5

[ "MIT" ]

null

from core.integration import Integration class DeCONZIntegration(Integration): def get_name(self): return "deconz" def get_actions_mapping(self): return self.controller.get_deconz_actions_mapping() def listen_changes(self, controller_id): self.controller.listen_event(self.callback, "deconz_event", id=controller_id) async def callback(self, event_name, data, kwargs): type_ = self.kwargs.get("type", "event") await self.controller.handle_action(data[type_])

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0

null

0

null

0

1

0

1

0

3

0daeb0a90ad16d9893602d4410fcfd44b9ab93ae

316

py

Python

python/learn/base/data/set.py

qrsforever/workspace

53c7ce7ca7da62c9fbb3d991ae9e4e34d07ece5f

[ "MIT" ]

2

2017-06-07T03:20:42.000Z

2020-01-07T09:14:26.000Z

python/learn/base/data/set.py

qrsforever/workspace

53c7ce7ca7da62c9fbb3d991ae9e4e34d07ece5f

[ "MIT" ]

null

python/learn/base/data/set.py

qrsforever/workspace

53c7ce7ca7da62c9fbb3d991ae9e4e34d07ece5f

[ "MIT" ]

null

#!/usr/bin/python2.7 #coding:utf-8 print dir(set) s = {'x', 'y', 'z'} print len(s) # print s.count('x') # 错误， Set里面的元素没有重复的, 方法没有意义 a = set('aabbccdef') print a b = set('abcdeffgg') print b print a - b # 在a中不在b中 print a | b print a & b print a ^ b # 不同时在a，b中 print { x for x in 'abcdefg' if x not in 'cdef' }

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1

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3

0db733f1532a37504cff2a5192eab073a5544177

125

py

Python

src/features/feature_normalization.py

t-wyrwas/Titanic

aad7e4431ec926e59821fbe7926767fc7f380ef2

[ "MIT" ]

null

src/features/feature_normalization.py

t-wyrwas/Titanic

aad7e4431ec926e59821fbe7926767fc7f380ef2

[ "MIT" ]

null

src/features/feature_normalization.py

t-wyrwas/Titanic

aad7e4431ec926e59821fbe7926767fc7f380ef2

[ "MIT" ]

null

def normalize(df, features): for f in features: range = df[f].max() - df[f].min() df[f] = df[f] / range

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null

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null

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1

0

3

0dd761b338c111a00b86dc8b3ddbd3beb9de5179

78

py

Python

pythonexercicios/ex110/ex110-modulos.py

marroni1103/exercicios-pyton

734162cc4b63ed30d754a6efe4c5622baaa1a50b

[ "MIT" ]

null

pythonexercicios/ex110/ex110-modulos.py

marroni1103/exercicios-pyton

734162cc4b63ed30d754a6efe4c5622baaa1a50b

[ "MIT" ]

null

pythonexercicios/ex110/ex110-modulos.py

marroni1103/exercicios-pyton

734162cc4b63ed30d754a6efe4c5622baaa1a50b

[ "MIT" ]

null

import moeda p = float(input('Digite um valor: R$ ')) moeda.resumo(p, 10, 10)

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0ddb76da1a8c48b1d8cd59059a0eb5c0268cbd9f

60

py

Python

src/greenbudget/app/user/__init__.py

nickmflorin/django-proper-architecture-testing

da7c4019697e85f921695144375d2f548f1e98ad

[ "MIT" ]

null

src/greenbudget/app/user/__init__.py

nickmflorin/django-proper-architecture-testing

da7c4019697e85f921695144375d2f548f1e98ad

[ "MIT" ]

null

src/greenbudget/app/user/__init__.py

nickmflorin/django-proper-architecture-testing

da7c4019697e85f921695144375d2f548f1e98ad

[ "MIT" ]

null

default_app_config = 'greenbudget.app.user.apps.UserConfig'

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null

0

1

0

1

null

0

3

0de6eaae871446eb0296a2a1ba100ce19a9b744b

9,310

py

Python

scratch/lidar.py

zkoppanyi/uni

32dbf0a425c6922264e737e9d59f794b32bb9c95

[ "MIT" ]

null

scratch/lidar.py

zkoppanyi/uni

32dbf0a425c6922264e737e9d59f794b32bb9c95

[ "MIT" ]

null

scratch/lidar.py

zkoppanyi/uni

32dbf0a425c6922264e737e9d59f794b32bb9c95

[ "MIT" ]

null

# %% External imports %matplotlib qt import numpy as np from mpl_toolkits import mplot3d import matplotlib.pyplot as plt from numpy.core.fromnumeric import size import viz from scipy.spatial.transform import Rotation # %% Pose definiations R_cams = [] t_cams = [] R_cams.append(np.array([[0.46224950999999997,-0.88642706999999998,0.023925829999999999],[-0.88672448999999998,-0.46227224,0.0049042499999999998],[0.0067129900000000003,-0.023482610000000001,-0.99970170999999997]])) t_cams.append(np.array([37.288039423382166,-10.165071594832114,1.8727184629264104])) R_cams.append(np.array([[0.46651118000000003,-0.88420001999999998,0.02361473],[-0.88449507999999999,-0.46651474999999998,0.0056951700000000003],[0.0059809499999999996,-0.023543979999999999,-0.99970490999999995]])) t_cams.append(np.array([37.659737128609429,6.2026050253511551,1.806322197411959])) R_cams.append(np.array([[0.46728996,-0.88381131000000002,0.02275201],[-0.88407325000000003,-0.46733393000000001,0.0036717999999999998],[0.0073876100000000002,-0.021830229999999999,-0.99973440000000002]])) t_cams.append(np.array([37.110483017656314,-26.062842185291906,2.1648932375751877])) R_cams.append(np.array([[0.49233894,-0.87008560000000001,0.023524920000000001],[-0.87039502000000002,-0.49227402999999997,0.0088764099999999995],[0.00385747,-0.024846179999999999,-0.99968383999999999]])) t_cams.append(np.array([-5.4967235887385559,31.091132695336771,1.610341169355259])) R_cams.append(np.array([[0.50085186000000004,-0.86521892,0.02331571],[-0.86552704000000003,-0.50076681999999995,0.0097747300000000006],[0.0032184499999999999,-0.025076060000000001,-0.99968036999999998]])) t_cams.append(np.array([-5.5377931849465023,14.710846119800054,1.7300687232930638])) R_cams.append(np.array([[0.47180678999999998,-0.88143651000000001,0.021633989999999999],[-0.88162320000000005,-0.47195058000000001,-0.0017871199999999999],[0.01178541,-0.018229849999999999,-0.99976436000000002]])) t_cams.append(np.array([37.384051130187636,-41.633462546113947,2.1158634448314526])) R_cams.append(np.array([[0.47189439999999999,-0.88132094000000005,0.024270690000000001],[-0.88162231000000002,-0.47193537000000002,0.0043717900000000004],[0.0076012500000000004,-0.023460600000000002,-0.99969585999999999]])) t_cams.append(np.array([37.970831512826429,22.702039449830167,2.2784408494325161])) R_cams.append(np.array([[0.49323628000000003,-0.86958290999999999,0.023313810000000001],[-0.86987912999999994,-0.49321372000000002,0.0071084499999999997],[0.0053173099999999996,-0.02378634,-0.99970292000000005]])) t_cams.append(np.array([-5.7895992643088299,47.41667398960805,1.3434057619016124])) R_cams.append(np.array([[0.52530100000000002,-0.85062040000000005,0.022445380000000001],[-0.85089974999999995,-0.52527330999999999,0.0075872400000000003],[0.0053360999999999999,-0.02308435,-0.99971927999999999]])) t_cams.append(np.array([-4.180344666992224,-17.63113751842792,1.6293067869202613])) R_cams.append(np.array([[0.67739077000000003,-0.73556431,0.0093213199999999993],[-0.73555954000000001,-0.67744453999999998,-0.0045894100000000004],[0.0096904799999999996,-0.00374756,-0.99994601999999999]])) t_cams.append(np.array([-54.873649641752209,13.564125668214011,2.0621008471261026])) R_cams.append(np.array([[0.46154272000000002,-0.88673528000000001,0.026055149999999999],[-0.88708531000000002,-0.46157870000000001,0.0049759699999999997],[0.0076141400000000001,-0.02540976,-0.99964812000000003]])) t_cams.append(np.array([38.403466611833693,38.517046653437177,2.6255313556474733])) R_cams.append(np.array([[0.52497444000000004,-0.85077981999999996,0.023990129999999998],[-0.85109480000000004,-0.52495965,0.00741715],[0.0062834900000000001,-0.02431169,-0.99968467999999999]])) t_cams.append(np.array([-3.1792848847595057,-33.939470542312002,1.3347059664748238])) R_cams.append(np.array([[0.68604211999999998,-0.72722567999999999,0.02211378],[-0.72739374999999995,-0.68622002999999998,-0.00063688000000000004],[0.015638079999999999,-0.015648499999999999,-0.99975526000000003]])) t_cams.append(np.array([-49.141419809434737,-2.7622727471745492,1.8123658774813083])) R_cams.append(np.array([[0.66895943999999996,-0.74293441999999998,0.023274739999999999],[-0.74317641000000001,-0.66908968000000002,0.0027978299999999998],[0.013494280000000001,-0.019168879999999999,-0.99972519000000004]])) t_cams.append(np.array([-45.14375735420402,-17.020471172497622,0.74002029836796157])) R_cams.append(np.array([[0.46577089999999999,-0.88465850000000001,0.020900169999999999],[-0.88480402999999996,-0.46594503999999998,-0.0041277900000000001],[0.013390020000000001,-0.01656995,-0.99977305000000005]])) t_cams.append(np.array([36.921765921296576,-58.333465843194972,2.0277098339924837])) R_cams.append(np.array([[0.48385872000000002,-0.87480838999999999,0.02431088],[-0.87512471000000003,-0.48385447999999998,0.0064485300000000001],[0.0061216999999999999,-0.02439523,-0.99968365000000003]])) t_cams.append(np.array([-5.3925073936428083,63.572360842694366,1.2795696460166441])) R_cams.append(np.array([[0.64499671000000003,-0.76379189000000003,0.024519200000000001],[-0.76410549000000005,-0.64506109,0.0062437899999999999],[0.011047420000000001,-0.02276247,-0.99967985999999998]])) t_cams.append(np.array([-42.318382286406617,-31.469204848937117,0.40737715271141517])) R_cams.append(np.array([[0.61809161000000001,-0.78570704000000002,0.025044219999999999],[-0.78604348999999996,-0.61813068000000004,0.0070777100000000001],[0.0099196000000000006,-0.024060519999999998,-0.99966129000000004]])) t_cams.append(np.array([-40.624343186101939,-45.960225675511538,0.35988156190389997])) # %% import laspy las_file_path = '/home/zoltan/Repo/pix/sandbox/output/lidar_filtered_only.las' pts = [] with laspy.open(las_file_path) as las: print(f"Point format: {las.header.point_format}") print(f"Number of points: {las.header.point_count}") print(f"Number of vlrs: {len(las.header.vlrs)}") las_pts = next(las.chunk_iterator(las.header.point_count)) x = np.array(las_pts.x.copy()) y = np.array(las_pts.y.copy()) z = np.array(las_pts.z.copy()) pts = np.concatenate(([x], [y], [z]), axis=0).T cog = np.array([542419.58606533124, 127532.132639184, 239.43887577800001]) pts = pts - cog # %% fig = plt.figure(figsize=(12,10)) ax = plt.axes(projection='3d') msize = np.ones((pts.shape[0], 1))*0.1, ax.scatter3D(pts[:, 0], pts[:, 1], pts[:, 2], msize, c='g', marker='.', linewidth=0.1) for k in range(len(R_cams)): X = -R_cams[k].T @ t_cams[k] viz.plot_fustrum(ax, X, R_cams[k], f=1.0, scale=10) viz.set_3d_axes_equal(ax) # %% Compute the lidar station # [14:06:28] [Picked] - [shifted] (37.389999;-26.330000;-84.983002) # [14:06:28] [Picked] - [original] (542456.969999;127505.800000;154.446998) # [14:06:52] [Picked] - [shifted] (40.630001;-28.370001;-85.163002) # [14:06:52] [Picked] - [original] (542460.210001;127503.759999;154.266998) # [14:07:03] [Picked] - [shifted] (40.000000;-25.570000;-85.053001) # [14:07:03] [Picked] - [original] (542459.580000;127506.560000;154.376999) # [14:07:10] [Picked] - [shifted] (38.150002;-28.950001;-85.133003) # [14:07:10] [Picked] - [original] (542457.730002;127503.179999;154.296997) station_pts = np.array([[542456.969999, 127505.800000, 154.446998], [542460.210001, 127503.759999, 154.266998], [542459.580000, 127506.560000, 154.376999], [542457.730002, 127503.179999, 154.296997]]) station_xyz = np.mean(station_pts, axis=0) station_xyz_loc = station_xyz - cog # %% fig = plt.figure(figsize=(12,10)) ax = plt.axes(projection='3d') #msize = np.ones((pts.shape[0], 1))*0.1, #ax.scatter3D(pts[:, 0], pts[:, 1], pts[:, 2], msize, c='g', marker='.', linewidth=0.1) #ax.scatter3D(station_xyz_loc[0], station_xyz_loc[1], station_xyz_loc[2], c='b', marker='+') def plot_fustrum(ax, X, R, f=1, scale=1, w=1, h=1): cam_dir = -scale * R @ np.array([[0, 0, f]]).T cam_dir_line = np.array([[X[0], X[0]+cam_dir[0, 0]], [X[1], X[1]+cam_dir[1, 0]], [X[2], X[2]+cam_dir[2, 0]]]).T ax.plot3D(X[0], X[1], X[2], c='r', marker='o') ax.plot3D(cam_dir_line[:, 0], cam_dir_line[:, 1], cam_dir_line[:, 2], 'gray') f_pt_0 = np.array([[-w, -h, 0], [-w, h, 0], [w, h, 0], [w, -h, 0], [-w, -h, 0]]) fustrum = scale * (R @ f_pt_0.T ).T + np.array([X[0] - cam_dir[0, 0], X[1] - cam_dir[1, 0], X[2] - cam_dir[2, 0]]) ax.plot3D(fustrum[:,0], fustrum[:,1], fustrum[:,2], c='r') for pt in fustrum: ax.plot3D([X[0], pt[0]], [X[1], pt[1]], [X[2], pt[2]], c='r') scale = 8.8 / 3700 / 1000 # one pixel size in m w = 1500 h = 1500 scale = 1 for kappa in np.linspace(0, 360, 9): for omega in np.linspace(0, 180, 5): R = Rotation.from_euler('xyz', [omega, 0, kappa], degrees=True).as_matrix() print(f'R << {R[0,0]}, {R[0,1]}, {R[0,2]}, {R[1,0]}, {R[1,1]}, {R[1,2]}, {R[2,0]}, {R[2,1]}, {R[2,2]};') print(f'virt_cam_poses.push_back(R);') #plot_fustrum(ax, station_xyz_loc, R, f=3000.0, scale=scale, w=1300, h=1300) plot_fustrum(ax, station_xyz_loc, R, f=1.0, scale=scale, w=w/3000, h=h/3000) viz.set_3d_axes_equal(ax) # %% Create fake image #import cv2 #img = np.ones((w,h,1), np.uint8)*255 #cv2.imwrite('/home/zoltan/Repo/pix/sandbox/input/lidar.png', img) # %%

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0

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3

2177a7a5e622a623db5afca53545157c7bcc5d39

1,375

py

Python

api/analyses/analyses.py

capdragon/cannlytics

47eeda80b1faf54d709def3641d9476501508fec

[ "MIT" ]

null

api/analyses/analyses.py

capdragon/cannlytics

47eeda80b1faf54d709def3641d9476501508fec

[ "MIT" ]

null

api/analyses/analyses.py

capdragon/cannlytics

47eeda80b1faf54d709def3641d9476501508fec

[ "MIT" ]

null

""" Analyses Views | Cannlytics API Created: 4/21/2021 API to interface with cannabis regulation information. """ from rest_framework import status from rest_framework.decorators import api_view from rest_framework.response import Response @api_view(['GET', 'POST', 'DELETE']) def analyses(request, format=None): """Get, create, or update information about cannabis analyses.""" if request.method == 'GET': # TODO: Implement filters! # data = get_collection(f"labs/{org_id}/analyses") return Response({'error': 'not_implemented'}, content_type='application/json') elif request.method == 'POST': return Response({'error': 'not_implemented'}, content_type='application/json') elif request.method == 'DELETE': return Response({'error': 'not_implemented'}, content_type='application/json') @api_view(['GET', 'POST', 'DELETE']) def analytes(request, format=None): """Get, create, or update information about cannabis analysis analytes.""" if request.method == 'GET': return Response({'error': 'not_implemented'}, content_type='application/json') elif request.method == 'POST': return Response({'error': 'not_implemented'}, content_type='application/json') elif request.method == 'DELETE': return Response({'error': 'not_implemented'}, content_type='application/json')

30.555556

86

0.690909

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1,375

5.849057

0.345912

0.083871

0.122581

0.141935

0.649462

0.6

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1,375

44

87

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0.802609

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0.736842

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null

0

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null

0

1

0

1

0

3

217866a576361526a8d13c0ad771761199c4b595

712

py

Python

algo-grave.py

bcgreen24/ten-lines-or-less

7a34ff7d7222fd3946e9cbb418afc992bc84e5e5

[ "MIT" ]

44

2018-08-15T08:32:43.000Z

2022-02-15T20:25:03.000Z

algo-grave.py

bcgreen24/ten-lines-or-less

7a34ff7d7222fd3946e9cbb418afc992bc84e5e5

[ "MIT" ]

null

algo-grave.py

bcgreen24/ten-lines-or-less

7a34ff7d7222fd3946e9cbb418afc992bc84e5e5

[ "MIT" ]

7

2018-09-08T20:05:58.000Z

2021-11-22T12:46:15.000Z

Clock.bpm=144; Scale.default="lydianMinor" d1 >> play("x-o{-[-(-o)]}", sample=0).every([28,4], "trim", 3) d2 >> play("(X )( X)N{ xv[nX]}", drive=0.2, lpf=var([0,40],[28,4]), rate=PStep(P[5:8],[-1,-2],1)).sometimes("sample.offadd", 1, 0.75) d3 >> play("e", amp=var([0,1],[PRand(8,16)/2,1.5]), dur=PRand([1/2,1/4]), pan=var([-1,1],2)) c1 >> play("#", dur=32, room=1, amp=2).spread() var.switch = var([0,1],[32]) p1 >> karp(dur=1/4, rate=PWhite(40), pan=PWhite(-1,1), amplify=var.switch, amp=1, room=0.5) p2 >> sawbass(var([0,1,5,var([4,6],[14,2])],1), dur=PDur(3,8), cutoff=4000, sus=1/2, amplify=var.switch) p3 >> glass(oct=6, rate=linvar([-2,2],16), shape=0.5, amp=1.5, amplify=var([0,var.switch],64), room=0.5)

71.2

133

0.580056

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712

2.664516

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0.048426

0.03632

0

0.145038

0.080056

712

9

134

79.111111

0.485496

0

0.085674

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1

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true

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null

0

1

0

1

0

null

0

1

0

3

217f0e3eccdc307d3d3f3bd3ab150b392da4a088

136

py

Python

bot/credentials_template.py

stanleykao72/Deepfake-Detection

417de0a0c7756397cf3a611b26008b7ed64727e9

[ "Apache-2.0" ]

1

2020-09-30T09:33:28.000Z

bot/credentials_template.py

stanleykao72/Deepfake-Detection

417de0a0c7756397cf3a611b26008b7ed64727e9

[ "Apache-2.0" ]

null

bot/credentials_template.py

stanleykao72/Deepfake-Detection

417de0a0c7756397cf3a611b26008b7ed64727e9

[ "Apache-2.0" ]

null

import os bot_token = '1168941932:XXGiYEV79cjssoQX_rZ5IwE4nbFhliKlh5M' bot_user_name = 'xxx_bot' URL = "https://cf45064e05ed.ngrok.io"

22.666667

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0.801471

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136

6.117647

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0.177419

0.088235

136

5

61

27.2

0.66129

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0.602941

0.338235

0

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false

0

0.25

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0.25

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1

0

null

0

1

0

1

0

null

0

3

2182051e14a8401743524d6ab0d1f557a1bde734

33

py

Python

debug.py

andrewtremblay/game-linkage

b7ef3f433cff68aee8f425c4575f2cc251c57064

[ "Apache-2.0" ]

null

debug.py

andrewtremblay/game-linkage

b7ef3f433cff68aee8f425c4575f2cc251c57064

[ "Apache-2.0" ]

null

debug.py

andrewtremblay/game-linkage

b7ef3f433cff68aee8f425c4575f2cc251c57064

[ "Apache-2.0" ]

null

hide_native_cursor = False #True

16.5

32

0.818182

5

33

5

1

0

0.121212

33

1

33

0.862069

0.121212

0

1

0

false

0

1

0

null

0

1

0

null

0

3

21a961f1700602ed46e95f0a1130b3d95c12010f

1,027

py

Python

resolwe/flow/views/__init__.py

plojyon/resolwe

1bee6f0860fdd087534adf1680e9350d79ab97cf

[ "Apache-2.0" ]

27

2015-12-07T18:29:12.000Z

2022-03-16T08:01:47.000Z

resolwe/flow/views/__init__.py

plojyon/resolwe

1bee6f0860fdd087534adf1680e9350d79ab97cf

[ "Apache-2.0" ]

681

2015-12-01T11:52:24.000Z

2022-03-21T07:43:37.000Z

resolwe/flow/views/__init__.py

plojyon/resolwe

1bee6f0860fdd087534adf1680e9350d79ab97cf

[ "Apache-2.0" ]

28

2015-12-01T08:32:57.000Z

2021-12-14T00:04:16.000Z

""".. Ignore pydocstyle D400. ========== Flow Views ========== .. autoclass:: resolwe.flow.views.collection.CollectionViewSet :members: .. autoclass:: resolwe.flow.views.data.DataViewSet :members: .. autoclass:: resolwe.flow.views.descriptor.DescriptorSchemaViewSet :members: .. autoclass:: resolwe.flow.views.entity.EntityViewSet :members: .. autoclass:: resolwe.flow.views.process.ProcessViewSet :members: .. autoclass:: resolwe.flow.views.relation.RelationViewSet :members: .. autoclass:: resolwe.flow.views.storage.StorageViewSet :members: """ from .collection import CollectionViewSet from .data import DataViewSet from .descriptor import DescriptorSchemaViewSet from .entity import EntityViewSet from .process import ProcessViewSet from .relation import RelationViewSet from .storage import StorageViewSet __all__ = ( "CollectionViewSet", "DataViewSet", "DescriptorSchemaViewSet", "EntityViewSet", "ProcessViewSet", "RelationViewSet", "StorageViewSet", )

22.326087

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0.735151

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1,027

8.344444

0.277778

0.095872

0.186418

0.233023

0.255659

0

0.00339

0.138267

1,027

45

69

22.822222

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0.560857

0

0.241535

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1

0

false

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0.4375

0

null

0

1

0

null

0

1

0

3

21ab7b5c543e49cf59fea2226a38a076def48564

814

py

Python

gaz/lpg/models.py

aafedotov/lpg

ee3eb015e6c5ccf01a3114c35d1c0b127d5570ea

[ "MIT" ]

null

gaz/lpg/models.py

aafedotov/lpg

ee3eb015e6c5ccf01a3114c35d1c0b127d5570ea

[ "MIT" ]

null

gaz/lpg/models.py

aafedotov/lpg

ee3eb015e6c5ccf01a3114c35d1c0b127d5570ea

[ "MIT" ]

null

from django.db import models import os class Lpg(models.Model): date = models.DateTimeField() price = models.FloatField() volume = models.FloatField() benz_price = models.FloatField() cost = models.FloatField() mileage = models.FloatField() mileage_total = models.FloatField() consump = models.FloatField() saving = models.FloatField() maintenance = models.IntegerField(blank=True, default=0) lpg_maintenance = models.IntegerField(blank=True, default=0) class Meta: ordering = ['-date'] def __str__(self): return str(self.date.date()) class File(models.Model): file = models.FileField(upload_to='') def filename(self): return os.path.basename(self.file.name) def __str__(self): return self.filename()

23.941176

64

0.662162

92

814

5.728261

0.434783

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0.079696

0.129032

0.174573

0

0.003145

0.218673

814

34

65

23.941176

0.825472

0

0.083333

0

0.006135

0

1

0.125

false

0

0.083333

0.125

0.958333

0

null

1

0

null

0

1

0

3

21ad90b72ec41af156af000c9948419be81a478a

80

py

Python

apps/fithm-gateway/libs/exceptions.py

sergio1221/flask-backend

11a9e0db5b5e664fcc820919d97039738176ac62

[ "BSD-3-Clause" ]

3

2022-03-04T03:05:55.000Z

2022-03-04T09:02:32.000Z

apps/fithm-gateway/libs/exceptions.py

sergio1221/flask-backend

11a9e0db5b5e664fcc820919d97039738176ac62

[ "BSD-3-Clause" ]

null

apps/fithm-gateway/libs/exceptions.py

sergio1221/flask-backend

11a9e0db5b5e664fcc820919d97039738176ac62

[ "BSD-3-Clause" ]

null

from werkzeug.exceptions import BadRequest Http_400_BadRequest = BadRequest

20

43

0.8375

9

80

7.222222

0.777778

0

0.043478

0.1375

80

3

44

26.666667

0.898551

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

3

21b877126c1f6c0c9851f58312d99e755f641028

344

py

Python

rightarrow/enforce.py

wuzzeb/python-rightarrow

bc26059d272e4a903fa2a18db9ebb484e7f74aed

[ "Apache-2.0" ]

1

2020-04-30T22:24:41.000Z

rightarrow/enforce.py

wuzzeb/python-rightarrow

bc26059d272e4a903fa2a18db9ebb484e7f74aed

[ "Apache-2.0" ]

null

rightarrow/enforce.py

wuzzeb/python-rightarrow

bc26059d272e4a903fa2a18db9ebb484e7f74aed

[ "Apache-2.0" ]

null

from rightarrow.parser import Parser def check(ty, val): "Checks that `val` adheres to type `ty`" if isinstance(ty, basestring): ty = Parser().parse(ty) return ty.enforce(val) def guard(ty): "A decorator that wraps a function so it the type passed is enforced via `check`" return lambda f: check(ty, f)

22.933333

85

0.651163

52

344

4.307692

0.634615

0.0625

0

0.247093

344

14

86

24.571429

0.864865

0.343023

0

0.341108

0

1

0.222222

false

0.111111

0

0.555556

0

null

0

null

0

1

0

1

0

1

0

3

21c22c252f9293d6166a6c3ca0cfe32490ca1342

1,888

py

Python

ssm/init_state_distns.py

adelaneh/ssm

0e8ef2619eae1cdd0f884f1437f2c990251038d7

[ "MIT" ]

208

2018-06-14T16:20:11.000Z

2020-08-18T01:13:46.000Z

ssm/init_state_distns.py

adelaneh/ssm

0e8ef2619eae1cdd0f884f1437f2c990251038d7

[ "MIT" ]

82

2018-06-28T15:15:41.000Z

2020-07-30T15:00:46.000Z

ssm/init_state_distns.py

adelaneh/ssm

0e8ef2619eae1cdd0f884f1437f2c990251038d7

[ "MIT" ]

83

2018-06-28T22:23:27.000Z

2020-10-02T19:27:53.000Z

from functools import partial from warnings import warn import autograd.numpy as np import autograd.numpy.random as npr from autograd.scipy.special import logsumexp from autograd.misc.optimizers import sgd, adam from autograd import grad from ssm.util import ensure_args_are_lists class InitialStateDistribution(object): def __init__(self, K, D, M=0): self.K, self.D, self.M = K, D, M self.log_pi0 = -np.log(K) * np.ones(K) @property def params(self): return (self.log_pi0,) @params.setter def params(self, value): self.log_pi0 = value[0] @property def initial_state_distn(self): return np.exp(self.log_pi0 - logsumexp(self.log_pi0)) @property def log_initial_state_distn(self): return self.log_pi0 - logsumexp(self.log_pi0) @ensure_args_are_lists def initialize(self, datas, inputs=None, masks=None, tags=None): pass def permute(self, perm): """ Permute the discrete latent states. """ self.log_pi0 = self.log_pi0[perm] def log_prior(self): return 0 def m_step(self, expectations, datas, inputs, masks, tags, **kwargs): pi0 = sum([Ez[0] for Ez, _, _ in expectations]) + 1e-8 self.log_pi0 = np.log(pi0 / pi0.sum()) class FixedInitialStateDistribution(InitialStateDistribution): def __init__(self, K, D, pi0=None, M=0): super(FixedInitialStateDistribution, self).__init__(K, D, M=M) if pi0 is not None: # Handle the case where user passes a numpy array of (K, 1) instead of (K,) pi0 = np.squeeze(np.array(pi0)) assert len(pi0) == K, "Array passed as pi0 is of the wrong length" self.log_pi0 = np.log(pi0 + 1e-16) def m_step(self, expectations, datas, inputs, masks, tags, **kwargs): # Don't change the distribution pass

30.451613

87

0.648305

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1,888

4.388889

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0.092827

0.03038

0.260759

0.163713

0.133333

0.084388

0

0.022472

0.245763

1,888

62

88

30.451613

0.809691

0.074153

0

0.162791

0

0.024362

0

0.023256

1

0.255814

false

0.069767

0.186047

0.093023

0.581395

0

null

0

null

0

1

0

1

0

1

0

3

21c4efefc7b5ce36cd0fc119863a360c0f7f77e0

405

py

Python

farm_ecomm/orders/models.py

SumeetSanwal/Farmer-Ecomm

021e79e1129a23d12970538451407a52bfe7938d

[ "MIT" ]

null

farm_ecomm/orders/models.py

SumeetSanwal/Farmer-Ecomm

021e79e1129a23d12970538451407a52bfe7938d

[ "MIT" ]

null

farm_ecomm/orders/models.py

SumeetSanwal/Farmer-Ecomm

021e79e1129a23d12970538451407a52bfe7938d

[ "MIT" ]

null

from django.db import models # Create your models here. class Order(models.Model): name=models.CharField(max_length=30) phone=models.CharField(max_length=10) qty=models.CharField(max_length=3) address=models.CharField(max_length=30) pin=models.CharField(max_length=10) day=models.DateField() product=models.CharField(max_length=30) class Meta: db_table="myorders"

28.928571

43

0.735802

57

405

5.105263

0.491228

0.309278

0.371134

0.494845

0.446735

0

0.03207

0.153086

405

14

44

28.928571

0.816327

0.059259

0

0.021053

0

1

0

false

0

0.090909

0

0.909091

0

null

1

0

null

0

3

21c5a0d877b9ea5b0aec8dcdbfeac7309ad9d58f

1,132

py

Python

pydfs_lineup_optimizer/sites/draftkings/showdown/settings.py

BenikaH/pydfs-lineup-optimizer

20dd39dfb738b8eb114c012a1d455c201da60400

[ "MIT" ]

null

pydfs_lineup_optimizer/sites/draftkings/showdown/settings.py

BenikaH/pydfs-lineup-optimizer

20dd39dfb738b8eb114c012a1d455c201da60400

[ "MIT" ]

null

pydfs_lineup_optimizer/sites/draftkings/showdown/settings.py

BenikaH/pydfs-lineup-optimizer

20dd39dfb738b8eb114c012a1d455c201da60400

[ "MIT" ]

null

from pydfs_lineup_optimizer.settings import BaseSettings, LineupPosition from pydfs_lineup_optimizer.constants import Sport, Site from pydfs_lineup_optimizer.sites.sites_registry import SitesRegistry from pydfs_lineup_optimizer.sites.draftkings.showdown.importer import DraftKingsShowdownGolfModeCSVImporter POSITIONS = [ LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), ] class DraftKingsShowdownGolfModeSettings(BaseSettings): site = Site.DRAFTKINGS_SHOWDOWN_GOLF budget = 50000 max_from_one_team = 6 csv_importer = DraftKingsShowdownGolfModeCSVImporter positions = [ LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), LineupPosition('G', ('G',)), ] @SitesRegistry.register_settings class DraftKingsShowdownGolfSettings(DraftKingsShowdownGolfModeSettings): sport = Sport.GOLF positions = POSITIONS[:]

31.444444

107

0.690813

102

1,132

7.509804

0.313725

0.234987

0.250653

0.391645

0.446475

0.370757

0

0.006322

0.161661

1,132

35

108

32.342857

0.800843

0

0.413793

0

0.021201

0

1

0

false

0

0.172414

0

0.482759

0

null

1

0

null

0

3

21cd8e3e4efaef5b184e48ac3e2c48f9b1b2f8c3

1,615

py

Python

Magic_Square.py

Sandeep6262/Logical-questions-in-python

2923a615622090fdb23699c7301d44c2975fec36

[ "MIT" ]

null

Magic_Square.py

Sandeep6262/Logical-questions-in-python

2923a615622090fdb23699c7301d44c2975fec36

[ "MIT" ]

null

Magic_Square.py

Sandeep6262/Logical-questions-in-python

2923a615622090fdb23699c7301d44c2975fec36

[ "MIT" ]

null

magic_square = [ [8, 3, 4], [1, 5, 9], [6, 7, 2] ] print("Row") print(magic_square[0][0]+magic_square[0][1]+magic_square[0][2]) print(magic_square[1][0]+magic_square[1][1]+magic_square[1][2]) print(magic_square[2][0]+magic_square[2][1]+magic_square[2][2]) print("colume") print(magic_square[0][0]+magic_square[1][0]+magic_square[2][0]) print(magic_square[0][1]+magic_square[1][1]+magic_square[2][1]) print(magic_square[0][2]+magic_square[1][2]+magic_square[2][2]) print("diagonals") print(magic_square[0][0]+magic_square[1][1]+magic_square[2][2]) print(magic_square[0][2]+magic_square[1][1]+magic_square[2][0]) # magic_square = [ # [8, 3, 4], # [1, 5, 9], # [6, 7, 2] # ] # total = 0 # for i in magic_square: # sum_1 = 0 # for j in i: # sum_1+=j # # print(sum_1) # total+=sum_1 # if total % sum_1 == 0: # m = True # # print(m) # m = sum_1 # sec_total = 0 # for y in range(len(magic_square)): # add = 0 # for i in magic_square: # for j in range(len(i)): # if j == y: # a=i[j] # # print(a) # add+=a # # print(add) # sec_total+=add # # print(sec_total) # # print(add) # if sec_total%add==0: # n = True # # print(n) # n=add # ples=0 # add=0 # y=0 # o=2 # for i in magic_square: # for j in range(len(i)): # if j == y: # b=i[y] # y+=1 # # print(b) # ples+=b # break # # print(ples) # for i in magic_square: # for j in range(len(i)): # if j == o: # c=i[o] # add+=c # o-=1 # # print(c) # break # # print(add) # if add==ples and add==m and m==n: # print("magic_square hai") # else: # print("magic_square nahi hai")

18.77907

63

0.569659

300

1,615

2.923333

0.136667

0.413911

0.18244

0.116306

0.574686

0.554162

0.424173

0.304447

0.167617

0

0.065574

0.206811

1,615

85

64

19

0.619048

0.525697

0

0.026012

0

1

0

false

0

0.6875

0

null

1

0

null

0

1

0

3

21d680533a4be44e6732c40401a607d45ad605dc

188

py

Python

0x0A-python-inheritance/6-base_geometry.py

ricardo1470/holbertonschool-higher_level_programming

aab73c8efee665b0215958ee7b338871f13634bc

[ "CNRI-Python" ]

null

0x0A-python-inheritance/6-base_geometry.py

ricardo1470/holbertonschool-higher_level_programming

aab73c8efee665b0215958ee7b338871f13634bc

[ "CNRI-Python" ]

null

0x0A-python-inheritance/6-base_geometry.py

ricardo1470/holbertonschool-higher_level_programming

aab73c8efee665b0215958ee7b338871f13634bc

[ "CNRI-Python" ]

null

#!/usr/bin/python3 """a class empty""" class BaseGeometry(): """create class""" pass def area(self): """area""" raise Exception("area() is not implemented")

15.666667

52

0.558511

21

188

5

0.809524

0

0.007143

0.255319

188

11

53

17.090909

0.742857

0.260638

0

0.203252

0

1

0.25

false

0.25

0

0.5

0

1

0

null

0

null

0

1

0

1

0

3

21da228590fc9fc17ae581924abaf6a76cdb4469

828

py

Python

control_demo.py

Alinamoo/SODD

5d0dc01927f8f9dced6eb9e67f7da82e0bf01761

[ "MIT" ]

null

control_demo.py

Alinamoo/SODD

5d0dc01927f8f9dced6eb9e67f7da82e0bf01761

[ "MIT" ]

null

control_demo.py

Alinamoo/SODD

5d0dc01927f8f9dced6eb9e67f7da82e0bf01761

[ "MIT" ]

null

from djitellopy import Tello import time tello = Tello() tello.connect() user_input = ' ' while user_input != 'x': user_input = input() if user_input == 't': print("takeoff") tello.takeoff() if user_input == 'l': print("land") tello.land() if user_input == 'a': print("left") tello.move_left(30) if user_input == 'w': print("forward") tello.move_forward(30) if user_input == 'd': print("right") tello.move_right(30) if user_input == 's': print("back") tello.move_back(30) if user_input == 'e': print("up") tello.move_up(30) if user_input == 'q': print("down") tello.move_down(30) print("exit")

19.714286

31

0.491546

97

828

4.020619

0.319588

0.253846

0.225641

0.166667

0

0.022901

0.36715

828

41

32

20.195122

0.721374

0

0.064803

0

1

0

false

0

0.0625

0

0.0625

0.28125

0

null

1

0

null

0

3

21e04da272da6204e5721ac0e715c76af39b9c45

453

py

Python

day14.py

dos1/AoC21

9095b96b831aac76cb9f0ce06e3f639db2da3977

[ "MIT" ]

null

day14.py

dos1/AoC21

9095b96b831aac76cb9f0ce06e3f639db2da3977

[ "MIT" ]

null

day14.py

dos1/AoC21

9095b96b831aac76cb9f0ce06e3f639db2da3977

[ "MIT" ]

null

def I(d,i,v):d[i]=d.setdefault(i,0)+v L=open("inputday14").readlines();t,d,p=L[0],dict([l.strip().split(' -> ')for l in L[2:]]),{};[I(p,t[i:i+2],1)for i in range(len(t)-2)] def E(P):o=dict(P);[(I(P,p,-o[p]),I(P,p[0]+n,o[p]),I(P,n+p[1],o[p]))for p,n in d.items()if p in o.keys()];return P def C(P):e={};[I(e,c,v)for p,v in P.items()for c in p];return{x:-int(e[x]/2//-1)for x in e} print((r:=[max(e:=C(E(p)).values())-min(e)for i in range(40)])[9],r[-1])

75.5

134

0.547461

129

453

1.922481

0.294574

0.032258

0.03629

0.08871

0

0.038278

0.077263

453

5

135

90.6

0.555024

0

0.030905

0

1

0.6

false

0

0.6

0.2

0

1

null

0

1

0

null

0

1

0

3

21f53aba046b659c91bf763398dadb13c3006f7a

82

py

Python

2017.TensorFlow&Python/2.python_syntax/test10.py

primetong/LearningCollectionOfWitt

a15dc8ac80618a3995c2b930c634b87ed8f1f0af

[ "MIT" ]

null

2017.TensorFlow&Python/2.python_syntax/test10.py

primetong/LearningCollectionOfWitt

a15dc8ac80618a3995c2b930c634b87ed8f1f0af

[ "MIT" ]

14

2020-06-30T20:52:56.000Z

2022-03-02T14:53:18.000Z

2017.TensorFlow&Python/2.python_syntax/test10.py

primetong/LearningCollectionOfWitt

a15dc8ac80618a3995c2b930c634b87ed8f1f0af

[ "MIT" ]

null

import os a = os.path.abspath('.') for filename in os.listdir(a): print filename

16.4

30

0.707317

14

82

4.142857

0.714286

0

0.146341

82

4

31

20.5

0.828571

0

0.012195

0

null

0

0.25

null

0.25

1

0

null

0

1

0

null

0

1

0

3

0dfe026616e5a537c4c4e00665aa901d409c2565

138

py

Python

eastbot/__init__.py

nexusz99/eastpot_slackbot

d7e67abf6f722cdcd06a39d4f6d89d920d7f2e25

[ "Apache-2.0" ]

null

eastbot/__init__.py

nexusz99/eastpot_slackbot

d7e67abf6f722cdcd06a39d4f6d89d920d7f2e25

[ "Apache-2.0" ]

null

eastbot/__init__.py

nexusz99/eastpot_slackbot

d7e67abf6f722cdcd06a39d4f6d89d920d7f2e25

[ "Apache-2.0" ]

null

from apscheduler.schedulers.background import BackgroundScheduler from slackbot.bot import Bot sched = BackgroundScheduler() bot = Bot()

23

65

0.826087

15

138

7.6

0.6

0

0.108696

138

6

66

23

0.926829

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

3

df2082c8994361a6c2e1ea094b2e6bff4292282e

1,548

py

Python

NoteBooks/Curso de Python/Python/Examples/High_Patterns/Patrones de diseño/Estructurales/Adapter.py

Alejandro-sin/Learning_Notebooks

161d6bed4c7b1d171b45f61c0cc6fa91e9894aad

[ "MIT" ]

1

2021-02-26T13:12:22.000Z

NoteBooks/Curso de Python/Python/Examples/High_Patterns/Patrones de diseño/Estructurales/Adapter.py

Alejandro-sin/Learning_Notebooks

161d6bed4c7b1d171b45f61c0cc6fa91e9894aad

[ "MIT" ]

null

NoteBooks/Curso de Python/Python/Examples/High_Patterns/Patrones de diseño/Estructurales/Adapter.py

Alejandro-sin/Learning_Notebooks

161d6bed4c7b1d171b45f61c0cc6fa91e9894aad

[ "MIT" ]

null

''' Este snipet tiene como propósito revisar lso conceptos el patrón de diseño adaptador. ''' class Korean: def __ini__(self): self.name ="Korean" def speak_korean(self): return "An-neyong?" class British: '''English spear''' def __init__(self): self.name ="British" def speak_english(self): return 'How are you?' class Adapter: '''Esto cambia el nomre del método genérico a nombres indiviudales''' def __init__(self, object, **adapted_method): '''Cambia el nombre del méotodo Añade un diccionario que establece el mapeo entre un método genérico speak() y un méotod concreto Recibe la palabra reservada object cualquiera instancia que recive ''' self._object = object # Aceptará un diccionario , la llave será el nombre dle metodo # El valor será el nombre individualziado del método self.__dict__.update(**adapted_method) def __getattr__(self,attr): '''Retorna el resto de los atributos''' return getattr(self._object,attr) if __name__ =='__main__': # Lista para almacenar los objetos speaker objects =[] #Creo objeto korea korean = Korean() british = British() # Hago un append en lal lista objects.append(Adapter(korean, speak=korean.speak_korean)) objects.append(Adapter(british, speak=british.speak_english)) print(objects[0].__dict__) """ for obj in objects: print("{} says `{}` \n".format(obj.name, obj.speak())) """

24.571429

105

0.649871

190

1,548

5.084211

0.526316

0.034161

0.024845

0

0.000863

0.251292

1,548

63

106

24.571429

0.832614

0.381783

0

0.053885

0

0.047619

0

1

0.26087

false

0

0.086957

0.521739

0.043478

0

null

0

null

0

1

0

1

0

1

0

3

df2c7d0bb93d126d91f0e1f6dc37cb5f7855e990

82

py

Python

pygamebook/SourceCode_PyGame/File Input Output/readmyself_rstrip.py

satrapade/sofia

f8903eb48a88eb9575823b4fe9f61435b882cdd4

[ "MIT" ]

null

pygamebook/SourceCode_PyGame/File Input Output/readmyself_rstrip.py

satrapade/sofia

f8903eb48a88eb9575823b4fe9f61435b882cdd4

[ "MIT" ]

9

2018-06-18T11:17:44.000Z

2018-06-19T21:00:48.000Z

pygamebook/SourceCode_PyGame/File Input Output/readmyself_rstrip.py

satrapade/sofia

f8903eb48a88eb9575823b4fe9f61435b882cdd4

[ "MIT" ]

null

import os f = open('readmyself.py', 'r') for line in f: print line, f.close()

13.666667

30

0.621951

15

82

3.4

0.8

0

0.207317

82

6

31

13.666667

0.784615

0

0.168675

0

null

0

0.2

null

0.2

1

0

null

0

1

0

null

0

1

0

3

df507194a9b78951826034e5e5ad1e47787f90be

1,345

py

Python

sysinv/cgts-client/cgts-client/cgtsclient/v1/iextoam.py

etaivan/stx-config

281e1f110973f96e077645fb01f67b646fc253cc

[ "Apache-2.0" ]

10

2020-02-07T18:57:44.000Z

2021-09-11T10:29:34.000Z

sysinv/cgts-client/cgts-client/cgtsclient/v1/iextoam.py

etaivan/stx-config

281e1f110973f96e077645fb01f67b646fc253cc

[ "Apache-2.0" ]

1

2021-01-14T12:01:55.000Z

sysinv/cgts-client/cgts-client/cgtsclient/v1/iextoam.py

etaivan/stx-config

281e1f110973f96e077645fb01f67b646fc253cc

[ "Apache-2.0" ]

10

2020-10-13T08:37:46.000Z

2022-02-09T00:21:25.000Z

# # Copyright (c) 2013-2014 Wind River Systems, Inc. # # SPDX-License-Identifier: Apache-2.0 # # -*- encoding: utf-8 -*- # from cgtsclient.common import base from cgtsclient import exc CREATION_ATTRIBUTES = ['extoamservers', 'forisystemid'] class iextoam(base.Resource): def __repr__(self): return "<iextoam %s>" % self._info class iextoamManager(base.Manager): resource_class = iextoam @staticmethod def _path(id=None): return '/v1/iextoam/%s' % id if id else '/v1/iextoam' def list(self): return self._list(self._path(), "iextoams") def get(self, iextoam_id): try: return self._list(self._path(iextoam_id))[0] except IndexError: return None def create(self, **kwargs): # path = '/v1/iextoam' new = {} for (key, value) in kwargs.items(): if key in CREATION_ATTRIBUTES: new[key] = value else: raise exc.InvalidAttribute('%s' % key) return self._create(self._path(), new) def delete(self, iextoam_id): # path = '/v1/iextoam/%s' % iextoam_id return self._delete(self._path(iextoam_id)) def update(self, iextoam_id, patch): # path = '/v1/iextoam/%s' % iextoam_id return self._update(self._path(iextoam_id), patch)

24.454545

61

0.601487

163

1,345

4.797546

0.392638

0.092072

0.038363

0.065217

0.140665

0.084399

0

0.017259

0.267658

1,345

54

62

24.907407

0.77665

0.150929

0

0.06366

0

1

0.233333

false

0

0.066667

0.166667

0.666667

0

null

0

null

0

1

0

1

0

3

df831b720e11ab51a02a48d1e4db6e52906f815e

885

py

Python

alerter/src/monitorables/nodes/node.py

SimplyVC/panic

2f5c327ea0d14b6a49dc8f4599a255048bc2ff6d

[ "Apache-2.0" ]

41

2019-08-23T12:40:42.000Z

2022-03-28T11:06:02.000Z

alerter/src/monitorables/nodes/node.py

SimplyVC/panic

2f5c327ea0d14b6a49dc8f4599a255048bc2ff6d

[ "Apache-2.0" ]

147

2019-08-30T22:09:48.000Z

2022-03-30T08:46:26.000Z

alerter/src/monitorables/nodes/node.py

SimplyVC/panic

2f5c327ea0d14b6a49dc8f4599a255048bc2ff6d

[ "Apache-2.0" ]

3

2019-09-03T21:12:28.000Z

2021-08-18T14:27:56.000Z

from abc import abstractmethod, ABC from typing import Any class Node(ABC): def __init__(self, node_name: str, node_id: str, parent_id: str) -> None: self._node_name = node_name self._node_id = node_id self._parent_id = parent_id def __str__(self) -> str: return self._node_name def __eq__(self, other: Any) -> bool: return self.__dict__ == other.__dict__ @property def node_name(self) -> str: return self._node_name @property def node_id(self) -> str: return self._node_id @property def parent_id(self) -> str: return self._parent_id def set_node_name(self, node_name: str) -> None: self._node_name = node_name def set_parent_id(self, parent_id: str) -> None: self._parent_id = parent_id @abstractmethod def reset(self) -> None: pass

23.289474

77

0.633898

123

885

4.113821

0.203252

0.158103

0.142292

0.134387

0.413043

0.205534

0.106719

0

0.272316

885

37

78

23.918919

0.785714

0

0.333333

0

1

0.333333

false

0.037037

0.074074

0.185185

0.62963

0

null

0

null

0

1

0

1

0

3

10c31cb94a752244b1e3c2554ce2f87592641186

177

py

Python

sak_sql/setup.py

lodrion/sak

1ab2b151cb61688696dbc0c432420350136ba9ad

[ "MIT" ]

null

sak_sql/setup.py

lodrion/sak

1ab2b151cb61688696dbc0c432420350136ba9ad

[ "MIT" ]

null

sak_sql/setup.py

lodrion/sak

1ab2b151cb61688696dbc0c432420350136ba9ad

[ "MIT" ]

null

from setuptools import find_packages, setup setup( name='sak-sql', version='0.0.1', packages=find_packages(), install_requires=[ "sqlalchemy" ], )

14.75

43

0.621469

20

177

5.35

0.75

0.224299

0

0.022388

0.242938

177

11

44

16.090909

0.776119

0

0.124294

0

1

0

true

0

0.111111

0

0.111111

0

1

0

null

1

0

null

0

1

0

3

10c50aaff57ece032b6b4157ee1e3745167966b6

1,418

py

Python

floyd_warshall.py

sara-02/dsa_sg

7c34b17772db728419070d35664ad75c67645b1e

[ "MIT" ]

null

floyd_warshall.py

sara-02/dsa_sg

7c34b17772db728419070d35664ad75c67645b1e

[ "MIT" ]

null

floyd_warshall.py

sara-02/dsa_sg

7c34b17772db728419070d35664ad75c67645b1e

[ "MIT" ]

null

INF = 999999 class FloydWarshall(object): def __init__(self, num_vertices): self.dist = [[INF] * num_vertices for i in range(num_vertices)] self.num_vertices = num_vertices @classmethod def get_graph_size(cls, graph_row): return len(graph_row) def initial_dist(self, graph): for i in range(self.num_vertices): for j in range(self.num_vertices): self.dist[i][j] = graph[i][j] def floyd_warshall(self): for i in range(self.num_vertices): for j in range(self.num_vertices): for k in range(self.num_vertices): self.dist[j][k] = min( self.dist[j][k], self.dist[j][i] + self.dist[i][k]) def print_distance_matrix(self): for i in range(self.num_vertices): for j in range(self.num_vertices): d = self.dist[i][j] if d == INF: d = 'INF' print d, print "\n" def main(): graph = [[0, 5, INF, 10], [INF, 0, 3, INF], [INF, INF, 0, 1], [INF, INF, INF, 0] ] num_vertices = FloydWarshall.get_graph_size(graph[0]) fwd = FloydWarshall(num_vertices) fwd.initial_dist(graph) fwd.floyd_warshall() fwd.print_distance_matrix() if __name__ == "__main__": main()

27.269231

71

0.527504

185

1,418

3.827027

0.232432

0.217514

0.190678

0.138418

0.322034

0.289548

0.285311

0.231638

0

0.017448

0.353315

1,418

51

72

27.803922

0.754635

0

0.15

0

0.009168

0

null

0

null

0.1

0

null

1

0

null

0

1

0

3

10fbfb348a160188f309e723551e25ae198980b6

1,144

py

Python

hwtGraph/elk/fromHwt/defauts.py

Nic30/hwtGraph

d11535d61ee8c1357720e502ac254c9dbf6dab7d

[ "MIT" ]

6

2018-06-20T21:28:51.000Z

2022-03-16T18:06:39.000Z

hwtGraph/elk/fromHwt/defauts.py

Nic30/hwtGraph

d11535d61ee8c1357720e502ac254c9dbf6dab7d

[ "MIT" ]

2

2021-01-05T09:13:52.000Z

2021-03-15T22:17:07.000Z

hwtGraph/elk/fromHwt/defauts.py

Nic30/hwtGraph

d11535d61ee8c1357720e502ac254c9dbf6dab7d

[ "MIT" ]

null

from hwt.synthesizer.dummyPlatform import DummyPlatform from hwtGraph.elk.fromHwt.extractSplits import extractSplits from hwtGraph.elk.fromHwt.flattenTrees import flattenTrees from hwtGraph.elk.fromHwt.mergeSplitsOnInterfaces import mergeSplitsOnInterfaces from hwtGraph.elk.fromHwt.netlistPreprocessors import unhideResultsOfIndexingAndConcatOnPublicSignals from hwtGraph.elk.fromHwt.reduceUselessAssignments import reduceUselessAssignments from hwtGraph.elk.fromHwt.resolveSharedConnections import resolveSharedConnections from hwtGraph.elk.fromHwt.sortStatementPorts import sortStatementPorts from hwtGraph.elk.fromHwt.propagatePresets import propagatePresets DEFAULT_PLATFORM = DummyPlatform() DEFAULT_PLATFORM.beforeHdlArchGeneration.extend([ unhideResultsOfIndexingAndConcatOnPublicSignals, propagatePresets, ]) DEFAULT_LAYOUT_OPTIMIZATIONS = [ # optimizations reduceUselessAssignments, extractSplits, lambda root: flattenTrees(root, lambda node: node.cls == "Operator" and node.name == "CONCAT", True), mergeSplitsOnInterfaces, resolveSharedConnections, # prettyfications sortStatementPorts, ]

40.857143

105

0.846154

95

1,144

10.147368

0.347368

0.099585

0.124481

0.182573

0

0.097902

1,144

27

106

42.37037

0.934109

0.02535

0

0.01259

0

1

0

false

0

0.409091

0

0.409091

0

1

null

0

1

0

null

0

1

0

3

800c7a6103e8a74ffeb1ed325cf2415ad7ffda51

539

py

Python

app/api/data/tests/test_friend.py

rummens1337/federated-social-network

e9b15342e7640a0b154787303c8660fa75acba14

[ "MIT" ]

null

app/api/data/tests/test_friend.py

rummens1337/federated-social-network

e9b15342e7640a0b154787303c8660fa75acba14

[ "MIT" ]

null

app/api/data/tests/test_friend.py

rummens1337/federated-social-network

e9b15342e7640a0b154787303c8660fa75acba14

[ "MIT" ]

null

# from flask import Blueprint, request # from app.api.utils import good_json_response, bad_json_response # import requests # blueprint.route('/add', methods=['POST']) def test_register(): pass # url = 'http://localhost:5000/json' # resp = requests.get(url) # assert resp.status_code == 200 # assert resp.json()["code"] == 1 # print(resp.text) # blueprint.route('/delete', methods=['POST']) def test_delete(): pass def f(): return 4 def test_function(): assert f() == 4 __all__ = ('blueprint')

17.966667

65

0.643785

70

539

4.785714

0.571429

0.062687

0.083582

0.107463

0

0.023095

0.19666

539

29

66

18.586207

0.750577

0.636364

0

0.222222

0

0.048649

0

0.111111

1

0.444444

false

0.222222

0

0.111111

0.555556

0.111111

0

null

0

null

0

1

0

1

0

1

0

3

80101bbd94c02d1585a9392dd98b40bfa9499de0

423

py

Python

mymm/__init__.py

jbardhan/molman

6dcf9e15a769363c87b2d3532baba249ac0f0b82

[ "MIT" ]

null

mymm/__init__.py

jbardhan/molman

6dcf9e15a769363c87b2d3532baba249ac0f0b82

[ "MIT" ]

null

mymm/__init__.py

jbardhan/molman

6dcf9e15a769363c87b2d3532baba249ac0f0b82

[ "MIT" ]

null

import os, sys, subprocess, re from .atom import * from .molecule import * from .namd import * from .fepoptions import * from .mutator import * from .spheresolute import * from .titrationdata import * from .titrationstate import * from .chargingfepinput import * from .selector import * from .patch import * from .radii import * from .topology import * from .sites import * from .runfile import * from .altmansrf import *

22.263158

31

0.751773

53

423

6

0.415094

0.471698

0

0.165485

423

18

32

23.5

0.90085

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

3

801b2b0f4542d347f10be305c1e8b55ff71e0d79

1,520

py

Python

smspdu/smspdu/__main__.py

cclauss/CommunityCellularManager

4a4e951b03380dcf5f16091d33bc52afbb3eca21

[ "BSD-3-Clause" ]

84

2016-11-03T20:51:09.000Z

2018-09-13T04:36:18.000Z

smspdu/smspdu/__main__.py

cclauss/CommunityCellularManager

4a4e951b03380dcf5f16091d33bc52afbb3eca21

[ "BSD-3-Clause" ]

79

2016-11-10T06:30:58.000Z

2018-06-01T14:29:39.000Z

smspdu/smspdu/__main__.py

cclauss/CommunityCellularManager

4a4e951b03380dcf5f16091d33bc52afbb3eca21

[ "BSD-3-Clause" ]

37

2016-11-03T22:53:22.000Z

2018-09-07T15:32:16.000Z

#!/usr/bin/env python3 """ Copyright (c) 2016-present, Facebook, Inc. All rights reserved. This source code is licensed under the BSD-style license found in the LICENSE file in the root directory of this source tree. An additional grant of patent rights can be found in the PATENTS file in the same directory. """ from .pdu import dump if __name__ == '__main__': import sys dump(sys.argv[1]) # Copyright (c) 2011 eKit.com Inc (http://www.ekit.com/) # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE.

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0

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8027d63aecfb0a5f9af1d3155c791bf1d6f70f14

263

py

Python

modules/pm.py

freakyLuffy/Teleuserbot

d5871e919b37d6b63de7e3115fd9d1d3bb6ce33b

[ "MIT" ]

null

modules/pm.py

freakyLuffy/Teleuserbot

d5871e919b37d6b63de7e3115fd9d1d3bb6ce33b

[ "MIT" ]

null

modules/pm.py

freakyLuffy/Teleuserbot

d5871e919b37d6b63de7e3115fd9d1d3bb6ce33b

[ "MIT" ]

1

2021-09-06T08:57:43.000Z

from start import client from telethon import events @client.on(events.NewMessage(incoming=True, func=lambda e: e.is_private)) async def my_event_handler(event): if event.chat_id not in white: await client.send_message(event.chat_id,CUSTOM_TEXT['pm'])

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0.125475

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null

0

1

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null

0

1

0

1

0

3

80576b9e520fcec90a0191aa2686d17a6fdf6fe4

371

py

Python

ch06/06_15.py

TeikyungKim/book-cryptocurrency

c44459a5ef5ca1d0d4d552472b85d75573bebb07

[ "Apache-2.0" ]

121

2019-03-23T13:53:06.000Z

2022-03-28T15:15:03.000Z

ch06/06_15.py

TeikyungKim/book-cryptocurrency

c44459a5ef5ca1d0d4d552472b85d75573bebb07

[ "Apache-2.0" ]

3

2021-04-14T14:31:26.000Z

2021-05-09T13:46:14.000Z

ch06/06_15.py

TeikyungKim/book-cryptocurrency

c44459a5ef5ca1d0d4d552472b85d75573bebb07

[ "Apache-2.0" ]

114

2019-03-21T13:43:03.000Z

2022-03-31T18:42:11.000Z

import time import datetime now = datetime.datetime.now() mid = datetime.datetime(now.year, now.month, now.day) + datetime.timedelta(1) while True: now = datetime.datetime.now() if mid < now < mid + datetime.timedelta(seconds=10) : print("정각입니다") mid = datetime.datetime(now.year, now.month, now.day) + datetime.timedelta(1) time.sleep(1)

26.5

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null

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3392f9eb4b53cd3a18f27e745776ec923137b486

238

py

Python

output/models/nist_data/list_pkg/ncname/schema_instance/nistschema_sv_iv_list_ncname_pattern_2_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

1

2021-08-14T17:59:21.000Z

output/models/nist_data/list_pkg/ncname/schema_instance/nistschema_sv_iv_list_ncname_pattern_2_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

4

2020-02-12T21:30:44.000Z

2020-04-15T20:06:46.000Z

output/models/nist_data/list_pkg/ncname/schema_instance/nistschema_sv_iv_list_ncname_pattern_2_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

null

from output.models.nist_data.list_pkg.ncname.schema_instance.nistschema_sv_iv_list_ncname_pattern_2_xsd.nistschema_sv_iv_list_ncname_pattern_2 import NistschemaSvIvListNcnamePattern2 __all__ = [ "NistschemaSvIvListNcnamePattern2", ]

39.666667

182

0.886555

29

238

6.586207

0.655172

0.125654

0.146597

0.188482

0.335079

0

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183

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null

0

1

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1

0

null

0

3

339d026962fbdb096e0ee1965911c5aed4384a09

159

py

Python

sesion28/tictactoe/core/routing.py

joelibaceta/backend-codigo-10

75256580ce9975bcfa831fde884362787d82b71f

[ "MIT" ]

1

2021-11-23T03:05:23.000Z

sesion28/tictactoe/core/routing.py

joelibaceta/backend-codigo-10

75256580ce9975bcfa831fde884362787d82b71f

[ "MIT" ]

1

2021-11-23T02:49:01.000Z

2021-11-23T02:55:14.000Z

sesion28/tictactoe/core/routing.py

joelibaceta/backend-codigo-10

75256580ce9975bcfa831fde884362787d82b71f

[ "MIT" ]

1

2022-01-26T19:54:33.000Z

from django.conf.urls import url from core.consumer import TicTacToeConsumer websocket_urlpatterns = [ url(r'^ws/play/$', TicTacToeConsumer.as_asgi()) ]

19.875

51

0.761006

20

159

5.95

0.8

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0.125786

159

8

52

19.875

0.856115

0

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1

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false

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null

0

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0

null

0

1

0

3

33a092f53a8bc5888be974799c120b8dea9282a2

8,431

py

Python

source/rttov_test/profile-datasets-py/div52_zen50deg/038.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

null

source/rttov_test/profile-datasets-py/div52_zen50deg/038.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

1

2022-03-12T12:19:59.000Z

source/rttov_test/profile-datasets-py/div52_zen50deg/038.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

null

""" Profile ../profile-datasets-py/div52_zen50deg/038.py file automaticaly created by prof_gen.py script """ self["ID"] = "../profile-datasets-py/div52_zen50deg/038.py" self["Q"] = numpy.array([ 1.619327, 5.956785, 4.367512, 5.966544, 5.988635, 7.336613, 6.150054, 10.02425 , 7.748795, 6.746565, 7.848652, 8.143708, 6.399868, 6.944384, 6.637736, 5.71046 , 5.909629, 5.561485, 5.516982, 5.451449, 5.354534, 5.23527 , 5.090619, 4.882784, 4.665495, 4.445971, 4.33555 , 4.24455 , 4.228264, 4.206028, 4.109932, 4.016939, 3.978498, 3.943255, 3.926937, 3.91893 , 3.913817, 3.914332, 3.914846, 3.919975, 3.925441, 3.934397, 3.947211, 3.959719, 3.971488, 3.982999, 3.995186, 4.007807, 4.018579, 4.019045, 4.019496, 4.01493 , 4.008386, 4.016698, 4.058516, 4.099514, 4.590187, 5.10988 , 6.011561, 7.189825, 8.460967, 10.05411 , 11.61838 , 14.50413 , 17.40478 , 19.78103 , 21.90165 , 24.44011 , 27.48018 , 30.31075 , 32.63891 , 35.01159 , 38.0444 , 41.01917 , 41.96547 , 42.89666 , 48.38523 , 53.96574 , 59.23674 , 64.47107 , 70.1626 , 76.54991 , 85.13889 , 93.71093 , 102.2625 , 107.7171 , 111.8628 , 114.223 , 114.8452 , 113.5177 , 110.5433 , 108.2854 , 110.1149 , 104.2918 , 93.99163 , 78.51031 , 50.08795 , 15.39714 , 14.97929 , 14.57806 , 14.19263 ]) self["P"] = numpy.array([ 5.00000000e-03, 1.61000000e-02, 3.84000000e-02, 7.69000000e-02, 1.37000000e-01, 2.24400000e-01, 3.45400000e-01, 5.06400000e-01, 7.14000000e-01, 9.75300000e-01, 1.29720000e+00, 1.68720000e+00, 2.15260000e+00, 2.70090000e+00, 3.33980000e+00, 4.07700000e+00, 4.92040000e+00, 5.87760000e+00, 6.95670000e+00, 8.16550000e+00, 9.51190000e+00, 1.10038000e+01, 1.26492000e+01, 1.44559000e+01, 1.64318000e+01, 1.85847000e+01, 2.09224000e+01, 2.34526000e+01, 2.61829000e+01, 2.91210000e+01, 3.22744000e+01, 3.56504000e+01, 3.92566000e+01, 4.31001000e+01, 4.71882000e+01, 5.15278000e+01, 5.61259000e+01, 6.09895000e+01, 6.61252000e+01, 7.15398000e+01, 7.72395000e+01, 8.32310000e+01, 8.95203000e+01, 9.61138000e+01, 1.03017000e+02, 1.10237000e+02, 1.17777000e+02, 1.25646000e+02, 1.33846000e+02, 1.42385000e+02, 1.51266000e+02, 1.60496000e+02, 1.70078000e+02, 1.80018000e+02, 1.90320000e+02, 2.00989000e+02, 2.12028000e+02, 2.23441000e+02, 2.35234000e+02, 2.47408000e+02, 2.59969000e+02, 2.72919000e+02, 2.86262000e+02, 3.00000000e+02, 3.14137000e+02, 3.28675000e+02, 3.43618000e+02, 3.58966000e+02, 3.74724000e+02, 3.90892000e+02, 4.07474000e+02, 4.24470000e+02, 4.41882000e+02, 4.59712000e+02, 4.77961000e+02, 4.96630000e+02, 5.15720000e+02, 5.35232000e+02, 5.55167000e+02, 5.75525000e+02, 5.96306000e+02, 6.17511000e+02, 6.39140000e+02, 6.61192000e+02, 6.83667000e+02, 7.06565000e+02, 7.29886000e+02, 7.53627000e+02, 7.77789000e+02, 8.02371000e+02, 8.27371000e+02, 8.52788000e+02, 8.78620000e+02, 9.04866000e+02, 9.31523000e+02, 9.58591000e+02, 9.86066000e+02, 1.01395000e+03, 1.04223000e+03, 1.07092000e+03, 1.10000000e+03]) self["CO2"] = numpy.array([ 317.3675, 317.3661, 317.3666, 317.3661, 317.3661, 317.3657, 317.366 , 317.3648, 317.3655, 317.3659, 317.3655, 317.3654, 317.366 , 317.3658, 317.3659, 317.3662, 317.3661, 317.3662, 317.3662, 317.3663, 317.3663, 317.3663, 317.3664, 317.3665, 317.3665, 317.3666, 317.3666, 317.3667, 317.3667, 317.3667, 317.3667, 318.3637, 319.4287, 320.5647, 321.7717, 323.0537, 324.4127, 325.8497, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3667, 327.3665, 327.3663, 327.366 , 327.3656, 327.3652, 327.3647, 327.3642, 327.3633, 327.3623, 327.3615, 327.3608, 327.36 , 327.359 , 327.3581, 327.3573, 327.3565, 327.3555, 327.3546, 327.3543, 327.354 , 327.3522, 327.3503, 327.3486, 327.3469, 327.345 , 327.3429, 327.3401, 327.3373, 327.3345, 327.3327, 327.3314, 327.3306, 327.3304, 327.3308, 327.3318, 327.3326, 327.332 , 327.3339, 327.3372, 327.3423, 327.3516, 327.363 , 327.3631, 327.3632, 327.3634]) self["T"] = numpy.array([ 208.144, 225.372, 233.177, 245.265, 257.004, 262.226, 265.74 , 267.391, 269.015, 267.988, 260.633, 246.779, 232.854, 221.232, 213.507, 209.05 , 206.15 , 204.447, 203.83 , 204.139, 205.414, 207.06 , 208.488, 208.879, 208.928, 208.778, 208.504, 208.203, 207.538, 206.933, 206.776, 206.624, 206.568, 206.519, 205.985, 205.254, 204.689, 204.443, 204.205, 205.121, 206.132, 207.086, 207.98 , 208.86 , 210.119, 211.349, 212.399, 213.315, 214.179, 214.82 , 215.447, 216.055, 216.649, 217.224, 217.769, 218.303, 218.725, 219.129, 219.394, 219.556, 219.661, 219.603, 219.545, 219.437, 219.327, 219.153, 218.952, 218.772, 218.614, 218.547, 218.732, 218.952, 219.486, 220.013, 220.743, 221.461, 222.301, 223.132, 224.021, 224.901, 225.805, 226.67 , 227.448, 228.168, 228.832, 229.468, 230.089, 230.695, 231.138, 231.335, 231.256, 231.052, 231.12 , 230.943, 230.323, 229.145, 225.92 , 216.233, 216.233, 216.233, 216.233]) self["O3"] = numpy.array([ 0.4900558 , 0.519964 , 0.5800554 , 0.6837994 , 0.8980769 , 1.136376 , 1.48558 , 1.992239 , 2.507364 , 3.082146 , 3.839641 , 4.766185 , 5.593402 , 6.175221 , 6.486727 , 6.579967 , 6.593362 , 6.525838 , 6.401646 , 6.232317 , 5.973736 , 5.652493 , 5.336404 , 5.090563 , 4.898364 , 4.739892 , 4.463794 , 4.180877 , 3.854482 , 3.558012 , 3.486732 , 3.417758 , 3.274348 , 3.13235 , 2.961193 , 2.780333 , 2.620231 , 2.4972 , 2.377505 , 2.279946 , 2.186869 , 2.075623 , 1.944017 , 1.814595 , 1.639969 , 1.469459 , 1.29283 , 1.112821 , 0.9414424 , 0.8033797 , 0.6682922 , 0.5882987 , 0.5313038 , 0.4850611 , 0.4617138 , 0.4388317 , 0.3812881 , 0.3218576 , 0.2606511 , 0.1984164 , 0.1433774 , 0.1075164 , 0.07230547, 0.05926259, 0.04750463, 0.0433533 , 0.04262317, 0.04276686, 0.04394101, 0.04542562, 0.04783386, 0.0502069 , 0.052577 , 0.05490744, 0.05686248, 0.05878674, 0.06004279, 0.06125448, 0.06145147, 0.06160804, 0.06150028, 0.06146972, 0.06166167, 0.06197792, 0.06241002, 0.06286282, 0.06332897, 0.06382601, 0.06415119, 0.06443305, 0.06480372, 0.06553336, 0.06655114, 0.06732265, 0.06764013, 0.06758204, 0.06678987, 0.06998377, 0.0699838 , 0.06998383, 0.06998385]) self["CTP"] = 500.0 self["CFRACTION"] = 0.0 self["IDG"] = 0 self["ISH"] = 0 self["ELEVATION"] = 0.0 self["S2M"]["T"] = 216.233 self["S2M"]["Q"] = 15.5386538073 self["S2M"]["O"] = 0.0699837594526 self["S2M"]["P"] = 1004.71 self["S2M"]["U"] = -1.39825 self["S2M"]["V"] = -0.27037 self["S2M"]["WFETC"] = 100000.0 self["SKIN"]["SURFTYPE"] = 0 self["SKIN"]["WATERTYPE"] = 1 self["SKIN"]["T"] = 215.154 self["SKIN"]["SALINITY"] = 35.0 self["SKIN"]["FOAM_FRACTION"] = 0.0 self["SKIN"]["FASTEM"] = numpy.array([ 3. , 5. , 15. , 0.1, 0.3]) self["ZENANGLE"] = 50.0 self["AZANGLE"] = 0.0 self["SUNZENANGLE"] = 0.0 self["SUNAZANGLE"] = 0.0 self["LATITUDE"] = 67.8369 self["GAS_UNITS"] = 2 self["BE"] = 0.0 self["COSBK"] = 0.0 self["DATE"] = numpy.array([1993, 12, 15]) self["TIME"] = numpy.array([6, 0, 0])

55.104575

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null

0

1

0

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33a3ee095d9406fe660570aebe62ca788d5da6af

207

py

Python

modules/stage_1.py

ElijahBeach/C2-Server-Project

89e6d418790493aa222cca5b6ea7f3f519e4e478

[ "MIT" ]

3

2022-01-14T01:55:25.000Z

2022-03-30T01:08:16.000Z

modules/stage_1.py

ElijahBeach/C2-Server-Project

89e6d418790493aa222cca5b6ea7f3f519e4e478

[ "MIT" ]

null

modules/stage_1.py

ElijahBeach/C2-Server-Project

89e6d418790493aa222cca5b6ea7f3f519e4e478

[ "MIT" ]

2

2022-01-15T14:30:55.000Z

2022-01-15T16:04:15.000Z

import json def run(**args): print('[$] Enter stage 1') basic_config =json.dumps([{"module" : "dir_lister"},{"module" : "enviro"},{"module" : "sleep"},{"module" : "stage_2_qrw"}]) return basic_config

29.571429

125

0.63285

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4.666667

0.740741

0.174603

0

0.011111

0.130435

207

6

126

34.5

0.688889

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0

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null

0

1

0

null

0

1

0

3

33aa8315bfe8d7a1e0fa6fd460a2c19cb2e4da53

1,182

py

Python

pyfileconf_datacode/dchooks.py

nickderobertis/pyfileconf-datacode

cb9b8cdaca7cc680c9c75d748a024efc13b4a308

[ "MIT" ]

null

pyfileconf_datacode/dchooks.py

nickderobertis/pyfileconf-datacode

cb9b8cdaca7cc680c9c75d748a024efc13b4a308

[ "MIT" ]

2

2021-12-20T00:10:31.000Z

2021-12-20T00:10:32.000Z

pyfileconf_datacode/dchooks.py

nickderobertis/pyfileconf-datacode

cb9b8cdaca7cc680c9c75d748a024efc13b4a308

[ "MIT" ]

null

""" Hooks into datacode to update pyfileconf context with datacode operations """ from typing import Optional import datacode.hooks as dc_hooks from datacode.models.pipeline.operations.operation import DataOperation from pyfileconf import context def update_pfc_context_to_pipeline_section_path(operation: DataOperation) -> None: """ Get the section path of the operation's pipeline and update the pyfileconf currently running context to this section path :param operation: The operation which is about to be executed :return: None """ context.stack.add_running_item(operation.pipeline._section_path_str) # type: ignore def update_pfc_context_to_original(operation: DataOperation) -> None: """ Revert the change to pyfileconf currently running context made by :func:`update_pfc_context_to_pipeline_section_path` :param operation: The operation which was just executed :return: None """ context.stack.pop_frame() def add_hooks(): dc_hooks.chain( "on_begin_execute_operation", update_pfc_context_to_pipeline_section_path ) dc_hooks.chain("on_end_execute_operation", update_pfc_context_to_original)

31.105263

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1,182

5.55414

0.382166

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0.091743

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0.383028

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null

0

1

0

1

0

1

0

3

33d044b0f48623a2e8a3f707f4fd9b01cf4e5e04

1,637

py

Python

Swing/util/Scanmap.py

jiawu/Roller

a70e350905a59c2254dcefda7ab23c6417cf8f7d

[ "MIT" ]

null

Swing/util/Scanmap.py

jiawu/Roller

a70e350905a59c2254dcefda7ab23c6417cf8f7d

[ "MIT" ]

2

2015-07-13T18:51:22.000Z

2015-07-16T15:35:24.000Z

Swing/util/Scanmap.py

jiawu/Roller

a70e350905a59c2254dcefda7ab23c6417cf8f7d

[ "MIT" ]

null

class Scanmap: """A heatmap and line plot combined into one figure""" def __init__(self, dim = None): if dim: self.set_dimensions(dim) else: default_dim = { 'gp_left': 0.2, 'gp_bottom': 0.1, 'gp_width': 0.7, 'gp_height': 0.2, 'padding': 0.01, 'numTFs': 20, 'dm_left': 0.2, 'dm_bottom': 0.32, 'dm_width':0.7, 'box_height':0.03, 'dm_height':0.6 } self.set_dimensions(default_dim) #initialize colormap self.tableau20 = [((152,223,138),(31, 119, 180), (174, 199, 232), (255, 127, 14),(255, 187, 120), (44, 160, 44), (255, 152, 150),(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229),(214,39,40)] for i in range(len(tableau20)): r,g,b = self.tableau20[i] self.tableau20[i] = (r/255., g/255., b/255.) #initialize axes f = plt.figure(figsize=(10,10)) d = self.dimensions axarr2 = f.add_axes(d['gp_left'],d['gp_bottom'],d['gp_width'],d['gp_height']) axarr1 = f.add_axes(d['dm_left'],d['dm_bottom'],d['dm_width'],d['dm_height']) def set_dimensions(self, dim_dict): self.dimensions = dim_dict return(dim_dict)

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null

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1

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3

33d252fe0327d46a0f541037910a341692b0b42d

163

py

Python

ML_Chinahadoop/04/code/test/test3.py

lsieun/learn-AI

0a164bc2e6317de3aa03c747c0e6f15d93e7f49a

[ "Apache-2.0" ]

1

2019-03-27T23:22:44.000Z

ML_Chinahadoop/04/code/test/test3.py

lsieun/learn-AI

0a164bc2e6317de3aa03c747c0e6f15d93e7f49a

[ "Apache-2.0" ]

null

ML_Chinahadoop/04/code/test/test3.py

lsieun/learn-AI

0a164bc2e6317de3aa03c747c0e6f15d93e7f49a

[ "Apache-2.0" ]

null

#coding:utf-8 import numpy as np # d = np.random.rand(5) # [0, 1) d = np.random.rand(5,3) print(d) print(d.shape) x = [2,3] t = tuple(x) print(t) print(type(t))

12.538462

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0.583333

0.060606

0.181818

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0.282828

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0.5

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null

0

1

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null

0

1

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3

33dc1874ceed63291aedd783dca53879f4114561

1,077

py

Python

insights/parsers/tests/test_neutron_ovs_agent_log.py

mglantz/insights-core

6f20bbbe03f53ee786f483b2a28d256ff1ad0fd4

[ "Apache-2.0" ]

121

2017-05-30T20:23:25.000Z

2022-03-23T12:52:15.000Z

insights/parsers/tests/test_neutron_ovs_agent_log.py

mglantz/insights-core

6f20bbbe03f53ee786f483b2a28d256ff1ad0fd4

[ "Apache-2.0" ]

1,977

2017-05-26T14:36:03.000Z

2022-03-31T10:38:53.000Z

insights/parsers/tests/test_neutron_ovs_agent_log.py

mglantz/insights-core

6f20bbbe03f53ee786f483b2a28d256ff1ad0fd4

[ "Apache-2.0" ]

244

2017-05-30T20:22:57.000Z

2022-03-26T10:09:39.000Z

from insights.parsers.neutron_ovs_agent_log import NeutronOVSAgentLog from insights.tests import context_wrap from datetime import datetime LOG = """ 2016-11-09 14:39:25.348 3153 WARNING oslo_config.cfg [-] Option "rabbit_password" from group "oslo_messaging_rabbit" is deprecated for removal. Its value may be silently ignored in the future. 2016-11-09 14:39:25.348 3153 WARNING oslo_config.cfg [-] Option "rabbit_userid" from group "oslo_messaging_rabbit" is deprecated for removal. Its value may be silently ignored in the future. 2016-11-09 14:39:25.352 3153 INFO ryu.base.app_manager [-] loading app neutron.plugins.ml2.drivers.openvswitch.agent.openflow.native.ovs_ryuapp 2016-11-09 14:39:27.171 3153 INFO ryu.base.app_manager [-] loading app ryu.app.ofctl.service 2016-11-09 14:39:27.190 3153 INFO ryu.base.app_manager [-] loading app ryu.controller.ofp_handler """ def test_neutron_ovs_agent_log(): log = NeutronOVSAgentLog(context_wrap(LOG)) assert len(log.get("WARNING")) == 2 assert len(list(log.get_after(datetime(2016, 11, 9, 14, 39, 26)))) == 2

56.684211

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null

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1

0

null

0

1

0

3

33de7fea4433b78d4b5d4914f3c786cf038c352c

62

py

Python

test/login.py

smartliit/gz02

d6ccc2137538eb9035a08ee0e53b15c8cfaffc6b

[ "MIT" ]

null

test/login.py

smartliit/gz02

d6ccc2137538eb9035a08ee0e53b15c8cfaffc6b

[ "MIT" ]

null

test/login.py

smartliit/gz02

d6ccc2137538eb9035a08ee0e53b15c8cfaffc6b

[ "MIT" ]

null

num = 1 num1 = 10 num2 = 20 num3 = 40 num3 = 30 num4 = 50

5.636364

9

0.548387

12

62

2.833333

0.916667

0

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62

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0.45

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1

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null

0

1

0

1

0

null

0

3

33e4384b255fb7af165ebd7c743b407be5757e1e

100

py

Python

fig/example_traceback.py

bagrow/WhirlwindTourOfPython

bd77cbd8b6a68f5b854d2b29ed266d36c8170d77

[ "CC0-1.0" ]

7

2017-01-16T19:36:35.000Z

2021-11-08T08:54:35.000Z

fig/example_traceback.py

bagrow/WhirlwindTourOfPython

bd77cbd8b6a68f5b854d2b29ed266d36c8170d77

[ "CC0-1.0" ]

null

fig/example_traceback.py

bagrow/WhirlwindTourOfPython

bd77cbd8b6a68f5b854d2b29ed266d36c8170d77

[ "CC0-1.0" ]

null

# example_traceback.py def loader(filename): fin = open(filenam) loader("data/result_ab.txt")

14.285714

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0.14

100

6

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1

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null

0

1

0

null

0

1

0

3

33f694b2af13996c72f3d160e40aa32e1652a122

439

py

Python

Appointmast/pages/migrations/0009_auto_20190911_0029.py

Paresh98000/AppointMaster

c17cf43456cfadfbb90bd99c714ea7f84d51b340

[ "bzip2-1.0.6" ]

null

Appointmast/pages/migrations/0009_auto_20190911_0029.py

Paresh98000/AppointMaster

c17cf43456cfadfbb90bd99c714ea7f84d51b340

[ "bzip2-1.0.6" ]

11

2020-06-05T23:13:03.000Z

2022-03-11T23:59:58.000Z

Appointmast/pages/migrations/0009_auto_20190911_0029.py

Paresh98000/AppointMaster

c17cf43456cfadfbb90bd99c714ea7f84d51b340

[ "bzip2-1.0.6" ]

null

# Generated by Django 2.2.2 on 2019-09-10 18:59 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('pages', '0008_auto_20190911_0021'), ] operations = [ migrations.RemoveField( model_name='appointment', name='city', ), migrations.RemoveField( model_name='appointment', name='location', ), ]

19.954545

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0.016393

0.213115

0.245902

0.368852

0

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0.321185

439

21

48

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0

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0

null

0

1

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1

0

null

0

3

1d1cca8eb9833144e8a286f6736f6f6ae5462a63

2,745

py

Python

InventorySystem/order/migrations/0014_auto_20210628_0012.py

guyueming/PythonWeb

e8a38fc26c06ec78e1de61d65055dcfc480ef8f1

[ "MIT" ]

null

InventorySystem/order/migrations/0014_auto_20210628_0012.py

guyueming/PythonWeb

e8a38fc26c06ec78e1de61d65055dcfc480ef8f1

[ "MIT" ]

null

InventorySystem/order/migrations/0014_auto_20210628_0012.py

guyueming/PythonWeb

e8a38fc26c06ec78e1de61d65055dcfc480ef8f1

[ "MIT" ]

null

# Generated by Django 3.2.3 on 2021-06-27 16:12 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('skin', '0003_skinmodel_factory'), ('paper', '0003_auto_20210618_0709'), ('order', '0013_ordernumbermodel_order_date'), ] operations = [ migrations.AlterField( model_name='ordermodel', name='note', field=models.TextField(blank=True, default='', max_length=256, verbose_name='备注'), ), migrations.AlterField( model_name='ordermodel', name='other_paper', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='other_paper', to='paper.papermodel', verbose_name='纸张2'), ), migrations.AlterField( model_name='ordermodel', name='other_paper_count', field=models.IntegerField(blank=True, default=0, verbose_name='纸张数量'), ), migrations.AlterField( model_name='ordermodel', name='packaging', field=models.TextField(blank=True, default='', max_length=64, verbose_name='包装'), ), migrations.AlterField( model_name='ordermodel', name='paper', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='paper.papermodel', verbose_name='纸张1'), ), migrations.AlterField( model_name='ordermodel', name='paperCount', field=models.IntegerField(blank=True, default=0, verbose_name='纸张数量'), ), migrations.AlterField( model_name='ordermodel', name='skin', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='skin.skinmodel', verbose_name='桉木皮'), ), migrations.AlterField( model_name='ordermodel', name='skinCount', field=models.IntegerField(blank=True, default=0, verbose_name='桉木皮数量'), ), migrations.AlterField( model_name='ordermodel', name='thickness', field=models.TextField(blank=True, default='', max_length=64, verbose_name='厚度'), ), migrations.AlterField( model_name='ordermodel', name='trademark', field=models.TextField(blank=True, default='', max_length=64, verbose_name='商标'), ), migrations.AlterField( model_name='ordermodel', name='word', field=models.TextField(blank=True, default='', max_length=64, verbose_name='打字'), ), ]

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null

0

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1d34af5080c27fee9894d1dd5eac6c33f3446666

3,370

py

Python

Code/controller/bridge/carla/sensor/GNSSSensor.py

tum-esi/attack_generation_framework

5fe1fbdca7491677e57f019ab83b8b726ea50f95

[ "MIT" ]

null

Code/controller/bridge/carla/sensor/GNSSSensor.py

tum-esi/attack_generation_framework

5fe1fbdca7491677e57f019ab83b8b726ea50f95

[ "MIT" ]

null

Code/controller/bridge/carla/sensor/GNSSSensor.py

tum-esi/attack_generation_framework

5fe1fbdca7491677e57f019ab83b8b726ea50f95

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- # Avoid cyclic imports while using type hints from __future__ import annotations # Imports import numpy as np import math import carla from bridge.carla.core.VectorData import VectorData from bridge.carla.core.Unit import Unit from bridge.carla.sensor.Sensor import Sensor class GNSSSensor(Sensor): """ """ def __init__(self, controller: DataController, name: str, update_interval: float = 1.0) -> None: """Constructor""" # Call constructor of base class Sensor.__init__(self, controller, name, 'body', update_interval) # Init class attributes self.type = 'gnss' # Create IMU sensor in carla world self.carla_blueprint = self.controller.get_blueprint_library().find('sensor.other.gnss') self.carla_blueprint.set_attribute('sensor_tick', f'{self.update_interval}') self.carla_transform = carla.Transform(carla.Location(0, 0, 0), carla.Rotation(0, 0, 0)) self.respawn_sensor() self.set_enabled(True) def set_noise_alt_bias(self, bias: float) -> None: self.update_sensor_attribute('noise_alt_bias', f'{bias}') def set_noise_alt_stddev(self, stddev: float) -> None: self.update_sensor_attribute('noise_alt_stddev', f'{stddev}') def set_noise_lat_bias(self, bias: float) -> None: self.update_sensor_attribute('noise_lat_bias', f'{bias}') def set_noise_lat_stddev(self, stddev: float) -> None: self.update_sensor_attribute('noise_lat_stddev', f'{stddev}') def set_noise_lon_bias(self, bias: float) -> None: self.update_sensor_attribute('noise_lon_bias', f'{bias}') def set_noise_lon_stddev(self, stddev: float) -> None: self.update_sensor_attribute('noise_lon_stddev', f'{stddev}') def get_noise_alt_bias(self) -> float: return self.carla_blueprint.get_attribute('noise_alt_bias').as_float() def get_noise_alt_stddev(self) -> float: return self.carla_blueprint.get_attribute('noise_alt_stddev').as_float() def get_noise_lat_bias(self) -> float: return self.carla_blueprint.get_attribute('noise_lat_bias').as_float() def get_noise_lat_stddev(self) -> float: return self.carla_blueprint.get_attribute('noise_lat_stddev').as_float() def get_noise_lon_bias(self) -> float: return self.carla_blueprint.get_attribute('noise_lon_bias').as_float() def get_noise_lon_stddev(self) -> float: return self.carla_blueprint.get_attribute('noise_lon_stddev').as_float() def sensor_callback(self, data: carla.SensorData) -> None: # Check if we want to process this update (only relevant if server rate is higher than user selected update rate) if (data.frame >= self.next_frame) and self.is_enabled(): # Compute next frame when sensor data should be received self.next_frame = data.frame + \ int(math.ceil(self.update_interval / self.controller.get_world_step())) # Get data position = VectorData(Unit.GEOGRAPHIC_POSITION, data.frame, data.timestamp, np.array([data.latitude, data.longitude, data.altitude])) # Put data in queue for further processing if position: self.data_queue.put(position)

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null

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0

1

0

1

0

3

1d5209bc43edb0cef67c19d935b4bdff1c153cba

367

py

Python

src/__init__.py

Fernando-Montes/TimeSeries

45e882b33f4a7e1fed6d0de491f32cfb31278cb5

[ "MIT" ]

null

src/__init__.py

Fernando-Montes/TimeSeries

45e882b33f4a7e1fed6d0de491f32cfb31278cb5

[ "MIT" ]

null

src/__init__.py

Fernando-Montes/TimeSeries

45e882b33f4a7e1fed6d0de491f32cfb31278cb5

[ "MIT" ]

null

# Importing all libraries from src.models.utilities import * from src.visualization.visualize import * from src.models.RNN import * from src.models.LSTM import * import pandas as pd import numpy as np import itertools from statsmodels.graphics import tsaplots import matplotlib.pyplot as plt from sklearn.metrics import mean_squared_error plt.style.use('default')

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3

1d6310e6f4999ff88b6080b65f9b222ecf73e177

119

py

Python

config.py

PMA-2020/agile

ab1f5b93897a8fe0cc71714bcf1b710ce3927adc

[ "MIT" ]

null

config.py

PMA-2020/agile

ab1f5b93897a8fe0cc71714bcf1b710ce3927adc

[ "MIT" ]

null

config.py

PMA-2020/agile

ab1f5b93897a8fe0cc71714bcf1b710ce3927adc

[ "MIT" ]

null

"""Config""" import os PKG_PATH = os.path.dirname(os.path.realpath(__file__)) + '/' OUTPUT_DIR = PKG_PATH + 'output/'

19.833333

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null

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1

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null

0

1

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3

1d6f1a24b3aaa646e56ca4d6354b46891af42daa

657

py

Python

src/postal/settings.py

michael-hahn/django-postal

082000839b20a8ee0aeaa6f8c76cc459409310e4

[ "MIT" ]

6

2015-01-07T10:01:00.000Z

2020-03-23T21:28:12.000Z

src/postal/settings.py

michael-hahn/django-postal

082000839b20a8ee0aeaa6f8c76cc459409310e4

[ "MIT" ]

5

2015-02-24T08:09:16.000Z

2015-11-25T10:02:07.000Z

src/postal/settings.py

michael-hahn/django-postal

082000839b20a8ee0aeaa6f8c76cc459409310e4

[ "MIT" ]

8

2015-01-30T05:49:54.000Z

2021-08-17T22:06:33.000Z

from django.conf import settings from django.utils.translation import ugettext_lazy as _ POSTAL_ADDRESS_L10N = getattr(settings, 'POSTAL_ADDRESS_L10N', True) # each address line is a tuple of format (field_label, required) POSTAL_ADDRESS_LINE1 = getattr(settings, "POSTAL_ADDRESS_LINE1", (_(u"Street"), False)) POSTAL_ADDRESS_LINE2 = getattr(settings, "POSTAL_ADDRESS_LINE2", (_(u"Area"), False)) POSTAL_ADDRESS_CITY = getattr(settings, "POSTAL_ADDRESS_CITY", (_(u"City"), False)) POSTAL_ADDRESS_STATE = getattr(settings, "POSTAL_ADDRESS_STATE", (_(u"State"), False)) POSTAL_ADDRESS_CODE = getattr(settings, "POSTAL_ADDRESS_CODE", (_(u"Zip code"), False))

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null

1

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null

0

3

1d723a23b9bf3bdf90138946e21473ba46af1b58

129

py

Python

src/main/python/rgb_effects/common/display_signals.py

alu0101233598/VPC2122

7c2ed0bb3309d20b6dd4798027290e2848840612

[ "ISC" ]

null

src/main/python/rgb_effects/common/display_signals.py

alu0101233598/VPC2122

7c2ed0bb3309d20b6dd4798027290e2848840612

[ "ISC" ]

10

2021-12-10T20:37:59.000Z

2022-01-16T19:09:17.000Z

src/main/python/rgb_effects/common/display_signals.py

alu0101233598/VPC2122

7c2ed0bb3309d20b6dd4798027290e2848840612

[ "ISC" ]

null

from PyQt5.QtCore import pyqtSignal, QObject class DisplaySignals(QObject): done = pyqtSignal(tuple) error = pyqtSignal(str)

25.8

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null

0

1

0

null

0

1

0

3

1d7599ec1e5692ac0ce7ed47842574b0c0767e65

290

py

Python

Chap.17/17.4.py

joonion/daily-coding-problems

8e313d28c3a989a41d87024588d38bd60a98b2c6

[ "MIT" ]

null

Chap.17/17.4.py

joonion/daily-coding-problems

8e313d28c3a989a41d87024588d38bd60a98b2c6

[ "MIT" ]

null

Chap.17/17.4.py

joonion/daily-coding-problems

8e313d28c3a989a41d87024588d38bd60a98b2c6

[ "MIT" ]

null

def nth_sevenish_number(n): answer, bit_place = 0, 0 while n > 0: if n & 1 == 1: answer += 7 ** bit_place n >>= 1 bit_place += 1 return answer # n = 1 # print(nth_sevenish_number(n)) for n in range(1, 10): print(nth_sevenish_number(n))

19.333333

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0.221477

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0.362416

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1

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0

0.2

0.1

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null

1

0

null

0

3

1d76618577dd3caa6129749e58d6fc645589cf23

556

py

Python

pymatex/node/Integral.py

Gawaboumga/PyMatex

3ccc0aa23211a064aa31a9b509b108cd606a4992

[ "MIT" ]

1

2019-03-05T09:45:04.000Z

pymatex/node/Integral.py

Gawaboumga/PyMatex

3ccc0aa23211a064aa31a9b509b108cd606a4992

[ "MIT" ]

null

pymatex/node/Integral.py

Gawaboumga/PyMatex

3ccc0aa23211a064aa31a9b509b108cd606a4992

[ "MIT" ]

null

from pymatex.listener import MatexASTVisitor from pymatex.node.IterativeFunction import IterativeFunction, IterativeType class Integral(IterativeFunction): def __init__(self, variable, start_range, end_range, expression): super().__init__(IterativeType.SUM, variable, start_range, end_range, expression) def __str__(self): return '\\int_{{{}}}^{{{}}}{{{} d{}}}'.format(self.start_range, self.end_range, self.expression, self.variable) def accept(self, visitor: MatexASTVisitor): return visitor.visit_integral(self)

37.066667

119

0.735612

61

556

6.377049

0.459016

0.077121

0.092545

0.107969

0.18509

0

0.138489

556

14

120

39.714286

0.812109

0

0.052158

0.041367

0

1

0.333333

false

0

0.222222

0.888889

0

null

0

null

0

1

0

1

0

3

1d8512d3ba0f35bc000e58936bd16d6cb08ae6bc

207

py

Python

esst/listener/__init__.py

etcher-be/esst

ac41cd0c07af8ca8532997f533756c529c9609a4

[ "MIT" ]

4

2018-06-24T14:03:44.000Z

2019-01-21T01:20:02.000Z

esst/listener/__init__.py

etcher-be/esst

ac41cd0c07af8ca8532997f533756c529c9609a4

[ "MIT" ]

106

2018-06-24T13:59:52.000Z

2019-11-26T09:05:14.000Z

esst/listener/__init__.py

theendsofinvention/esst

ac41cd0c07af8ca8532997f533756c529c9609a4

[ "MIT" ]

null

# coding=utf-8 """ Manages a UDP socket and does two things: 1. Retrieve incoming messages from DCS and update :py:class:`esst.core.status.status` 2. Sends command to the DCS application via the socket """

25.875

85

0.748792

35

207

4.428571

0.857143

0

0.017143

0.154589

207

7

86

29.571429

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0.951691

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null

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null

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0

1

0

null

0

1

0

3

d552476c75a5ad80a50b5a912fd1f4dce56e3bcd

7,000

py

Python

day19.py

ecnerwala/aoc-2019

9a8a273804395da1d269bea94f260e320946f26c

[ "CC0-1.0" ]

5

2021-01-26T03:25:01.000Z

2021-04-12T21:56:13.000Z

day19.py

ecnerwala/aoc-2019

9a8a273804395da1d269bea94f260e320946f26c

[ "CC0-1.0" ]

null

day19.py

ecnerwala/aoc-2019

9a8a273804395da1d269bea94f260e320946f26c

[ "CC0-1.0" ]

1

2021-03-02T19:33:51.000Z

from functools import * from collections import * from itertools import * from math import * from sys import exit from dataclasses import dataclass import re from builtins import pow from heapq import heappush, heappop, heappushpop, heapify, heapreplace import pyperclip def cprint(a): print(a) pyperclip.copy(a) class NeedInput_(): pass NeedInput = NeedInput_() class Computer(): def __init__(self, prog): self.mem = defaultdict(lambda: 0) for i,v in enumerate(prog): self.mem[i] = v self.pc = 0 self.out = [] self.relative_base = 0 self.halted = False self.out_ctr = 0 def run_with_inp(self, inp=None): if self.halted: return self if inp is None: inp = [] inp = iter(inp) while True: instr = self.mem[self.pc] op = instr % 100 instr //= 100 next_pc = self.pc+1 def get_param(): nonlocal next_pc nonlocal instr v = self.mem[next_pc] next_pc += 1 mode = instr % 10 instr //= 10 return (mode, v) def get_read_param(): mode, v = get_param() if mode == 0: return self.mem[v] elif mode == 1: return v elif mode == 2: addr = self.relative_base + v assert 0 <= addr return self.mem[addr] else: assert False def get_write_addr(): mode, v = get_param() if mode == 0: return v elif mode == 1: assert False elif mode == 2: addr = self.relative_base + v assert 0 <= addr return addr else: assert False def do_jump(loc): self.pc = loc if op == 99: self.halted = True return self elif op == 1: s1 = get_read_param() s2 = get_read_param() d = get_write_addr() self.mem[d] = s1 + s2 elif op == 2: s1 = get_read_param() s2 = get_read_param() d = get_write_addr() self.mem[d] = s1 * s2 elif op == 3: try: v = next(inp) except StopIteration: return self d = get_write_addr() self.mem[d] = v elif op == 4: s = get_read_param() self.out.append(s) elif op == 5: s1 = get_read_param() s2 = get_read_param() if s1 != 0: next_pc = s2 elif op == 6: s1 = get_read_param() s2 = get_read_param() if s1 == 0: next_pc = s2 elif op == 7: s1 = get_read_param() s2 = get_read_param() d = get_write_addr() self.mem[d] = (1 if s1 < s2 else 0) elif op == 8: s1 = get_read_param() s2 = get_read_param() d = get_write_addr() self.mem[d] = (1 if s1 == s2 else 0) elif op == 9: s1 = get_read_param() self.relative_base += s1 else: assert False self.pc = next_pc def pop_output(self, l=None): if l is None: return self.pop_output(1)[0] assert l + self.out_ctr <= len(self.out) self.out_ctr += l return self.out[self.out_ctr-l:self.out_ctr] def has_output(self, l=1): return self.out_ctr + l <= len(self.out) def main(inp, is_real): if not is_real: return inp = inp.strip() inp = inp.split(',') prog = tuple(map(int, inp)) def get_beam(i,j): if i < 0 or j < 0: return False return Computer(prog).run_with_inp([i,j]).pop_output() == 1 for i in range(1000): if i >= 2: assert get_beam(i, (3*i+1)//2) for i in range(60): s = '' for j in range(60): s += '.#'[get_beam(i,j)] print(s) def get_diag_first(s): r = s * 2 // 5 c = s - r while not get_beam(r, c): r -= 1 c += 1 while get_beam(r+1, c-1): r += 1 c -= 1 assert get_beam(r, c) return r,c def get_diag_width(s): r, c = get_diag_first(s) lo = c hi = s+1 while hi - lo > 1: md = (lo + hi) >> 1 if get_beam(s-md, md): lo = md else: hi = md return hi - c s = 2500 while get_diag_width(s) < 100: s += 1 print(s) r, c = get_diag_first(s) x, y = r - 99, c cprint(x*10000+y) for i in range(100): for j in range(100): assert get_beam(x+i, y+j) print(get_diag_width(s)) for i in range(-100,100): s = '' for j in range(-100,100): s += '.#'[get_beam(x+i,y+j)] print(s) #exit(0) samp_inp = r""" """ real_inp = r""" 109,424,203,1,21102,1,11,0,1106,0,282,21101,0,18,0,1106,0,259,1202,1,1,221,203,1,21101,0,31,0,1105,1,282,21102,38,1,0,1105,1,259,20102,1,23,2,21201,1,0,3,21102,1,1,1,21101,0,57,0,1105,1,303,2101,0,1,222,20102,1,221,3,21002,221,1,2,21101,0,259,1,21101,0,80,0,1106,0,225,21102,1,152,2,21101,91,0,0,1106,0,303,1201,1,0,223,21001,222,0,4,21101,0,259,3,21102,225,1,2,21101,0,225,1,21102,1,118,0,1105,1,225,20101,0,222,3,21102,61,1,2,21101,133,0,0,1106,0,303,21202,1,-1,1,22001,223,1,1,21102,148,1,0,1105,1,259,2101,0,1,223,21001,221,0,4,21001,222,0,3,21101,0,14,2,1001,132,-2,224,1002,224,2,224,1001,224,3,224,1002,132,-1,132,1,224,132,224,21001,224,1,1,21101,0,195,0,105,1,109,20207,1,223,2,20101,0,23,1,21102,-1,1,3,21102,214,1,0,1105,1,303,22101,1,1,1,204,1,99,0,0,0,0,109,5,2101,0,-4,249,21202,-3,1,1,21202,-2,1,2,21201,-1,0,3,21102,1,250,0,1106,0,225,22101,0,1,-4,109,-5,2106,0,0,109,3,22107,0,-2,-1,21202,-1,2,-1,21201,-1,-1,-1,22202,-1,-2,-2,109,-3,2105,1,0,109,3,21207,-2,0,-1,1206,-1,294,104,0,99,22102,1,-2,-2,109,-3,2105,1,0,109,5,22207,-3,-4,-1,1206,-1,346,22201,-4,-3,-4,21202,-3,-1,-1,22201,-4,-1,2,21202,2,-1,-1,22201,-4,-1,1,21202,-2,1,3,21101,343,0,0,1106,0,303,1105,1,415,22207,-2,-3,-1,1206,-1,387,22201,-3,-2,-3,21202,-2,-1,-1,22201,-3,-1,3,21202,3,-1,-1,22201,-3,-1,2,22101,0,-4,1,21101,0,384,0,1106,0,303,1105,1,415,21202,-4,-1,-4,22201,-4,-3,-4,22202,-3,-2,-2,22202,-2,-4,-4,22202,-3,-2,-3,21202,-4,-1,-2,22201,-3,-2,1,21201,1,0,-4,109,-5,2106,0,0 """ print("Sample:") main(samp_inp, False) print("Actual:") main(real_inp, True)

31.818182

1,465

0.481714

1,129

7,000

2.894597

0.171833

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null

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1

0

1

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null

0

3

d5602f60583a5ee8fff192152e26a808fb8ee237

208

py

Python

boxes/__init__.py

gregbugaj/form-processor

0c803de43a98b4a02efa956803e64793995256ff

[ "MIT" ]

null

boxes/__init__.py

gregbugaj/form-processor

0c803de43a98b4a02efa956803e64793995256ff

[ "MIT" ]

1

2021-11-09T11:11:32.000Z

boxes/__init__.py

gregbugaj/form-processor

0c803de43a98b4a02efa956803e64793995256ff

[ "MIT" ]

null

""" Name : __init__.py boxes module This import path is important to allow importing correctly as package """ import os, sys sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '.')))

23.111111

81

0.735577

33

208

4.393939

0.727273

0.124138

0

0.005464

0.120192

208

8

82

26

0.786885

0.490385

0

0.010204

0

1

0

true

0

0.5

0

0.5

0

null

0

1

0

null

0

1

0

1

0

3

d5705b1544fe2fc2f711adfa0a90fc24288d51e3

110

py

Python

backend/harmlessBuddy/harmlessBuddy/sentiment_analysis/apps.py

alecadub/ConUHacks5

bf3329be7866a1943883a01bdc302baefab77c17

[ "MIT" ]

null

backend/harmlessBuddy/harmlessBuddy/sentiment_analysis/apps.py

alecadub/ConUHacks5

bf3329be7866a1943883a01bdc302baefab77c17

[ "MIT" ]

13

2020-06-05T20:43:05.000Z

2022-03-02T07:06:10.000Z

backend/harmlessBuddy/harmlessBuddy/sentiment_analysis/apps.py

alecadub/ConUHacks5

bf3329be7866a1943883a01bdc302baefab77c17

[ "MIT" ]

1

2020-10-14T06:48:32.000Z

from django.apps import AppConfig class SentimentAnalysisConfig(AppConfig): name = 'sentiment_analysis'

18.333333

41

0.8

11

110

7.909091

0.909091

0

0.136364

110

5

42

22

0.915789

0

0.163636

0

1

0

false

0

0.333333

0

1

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null

0

1

0

null

0

1

0

3

6337a1c9f62a8aa4d32a1a131f18b20efe00d460

295

py

Python

example_test.py

dprogm/bazel_pybind_sample

8e0813ac6ad7732b89213de379e5da39f6621f5a

[ "Apache-2.0" ]

2

2020-10-22T09:27:05.000Z

2021-11-12T13:42:27.000Z

example_test.py

dprogm/bazel_pybind_sample

8e0813ac6ad7732b89213de379e5da39f6621f5a

[ "Apache-2.0" ]

null

example_test.py

dprogm/bazel_pybind_sample

8e0813ac6ad7732b89213de379e5da39f6621f5a

[ "Apache-2.0" ]

2

2021-11-12T13:41:49.000Z

2022-03-01T13:58:35.000Z

import os import sys print('about to import', file=sys.stderr) print('python is', sys.version_info) print('pid is', os.getpid()) import my_pb_mod print('imported, about to call', file=sys.stderr) result = my_pb_mod.add(2, 3) print(result) assert result == 5 print('done!', file=sys.stderr)

17.352941

49

0.718644

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295

4.058824

0.509804

0.101449

0.188406

0

0.011628

0.125424

295

16

50

18.4375

0.790698

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0

0.090909

1

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false

0

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0.454545

0.545455

0

null

0

1

0

null

0

1

0

1

0

3

634348f6beb8ae7a79d54c8ae7dedfc2a3eb5caf

13,574

py

Python

source/rttov_test/profile-datasets-py/div83/040.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

null

source/rttov_test/profile-datasets-py/div83/040.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

1

2022-03-12T12:19:59.000Z

source/rttov_test/profile-datasets-py/div83/040.py

bucricket/projectMAScorrection

89489026c8e247ec7c364e537798e766331fe569

[ "BSD-3-Clause" ]

null

""" Profile ../profile-datasets-py/div83/040.py file automaticaly created by prof_gen.py script """ self["ID"] = "../profile-datasets-py/div83/040.py" self["Q"] = numpy.array([ 1.890026, 2.119776, 2.622053, 3.246729, 3.667537, 4.216342, 4.862296, 5.531749, 6.100783, 6.376119, 6.376069, 6.30519 , 6.187932, 5.998564, 5.778127, 5.603999, 5.44443 , 5.194473, 4.915426, 4.653008, 4.45 , 4.296832, 4.148003, 4.015564, 3.910205, 3.839615, 3.790106, 3.753656, 3.721226, 3.693996, 3.677826, 3.674526, 3.655867, 3.640757, 3.644617, 3.663107, 3.679716, 3.683656, 3.678676, 3.667877, 3.655367, 3.648067, 3.646037, 3.644827, 3.651267, 3.691236, 3.765886, 3.858565, 3.940824, 3.994534, 4.097813, 4.351141, 4.794867, 5.49314 , 6.497828, 8.015136, 10.60419 , 15.81985 , 21.16895 , 24.30741 , 23.60504 , 24.79699 , 27.87162 , 33.67817 , 42.22522 , 52.68792 , 65.67979 , 82.04257 , 102.6225 , 116.7384 , 124.9514 , 131.6637 , 137.0252 , 130.226 , 119.7127 , 105.9718 , 104.862 , 125.6962 , 167.5619 , 234.0722 , 297.3785 , 359.7445 , 423.0569 , 497.9349 , 552.8482 , 569.9959 , 545.77 , 535.4481 , 711.82 , 1148.918 , 1499.767 , 1580.109 , 1531.92 , 1436.304 , 1228.928 , 1011.186 , 845.8809 , 853.3132 , 830.1563 , 807.9197 , 786.5588 ]) self["P"] = numpy.array([ 5.00000000e-03, 1.61000000e-02, 3.84000000e-02, 7.69000000e-02, 1.37000000e-01, 2.24400000e-01, 3.45400000e-01, 5.06400000e-01, 7.14000000e-01, 9.75300000e-01, 1.29720000e+00, 1.68720000e+00, 2.15260000e+00, 2.70090000e+00, 3.33980000e+00, 4.07700000e+00, 4.92040000e+00, 5.87760000e+00, 6.95670000e+00, 8.16550000e+00, 9.51190000e+00, 1.10038000e+01, 1.26492000e+01, 1.44559000e+01, 1.64318000e+01, 1.85847000e+01, 2.09224000e+01, 2.34526000e+01, 2.61829000e+01, 2.91210000e+01, 3.22744000e+01, 3.56505000e+01, 3.92566000e+01, 4.31001000e+01, 4.71882000e+01, 5.15278000e+01, 5.61260000e+01, 6.09895000e+01, 6.61253000e+01, 7.15398000e+01, 7.72396000e+01, 8.32310000e+01, 8.95204000e+01, 9.61138000e+01, 1.03017000e+02, 1.10237000e+02, 1.17778000e+02, 1.25646000e+02, 1.33846000e+02, 1.42385000e+02, 1.51266000e+02, 1.60496000e+02, 1.70078000e+02, 1.80018000e+02, 1.90320000e+02, 2.00989000e+02, 2.12028000e+02, 2.23442000e+02, 2.35234000e+02, 2.47408000e+02, 2.59969000e+02, 2.72919000e+02, 2.86262000e+02, 3.00000000e+02, 3.14137000e+02, 3.28675000e+02, 3.43618000e+02, 3.58966000e+02, 3.74724000e+02, 3.90893000e+02, 4.07474000e+02, 4.24470000e+02, 4.41882000e+02, 4.59712000e+02, 4.77961000e+02, 4.96630000e+02, 5.15720000e+02, 5.35232000e+02, 5.55167000e+02, 5.75525000e+02, 5.96306000e+02, 6.17511000e+02, 6.39140000e+02, 6.61192000e+02, 6.83667000e+02, 7.06565000e+02, 7.29886000e+02, 7.53628000e+02, 7.77790000e+02, 8.02371000e+02, 8.27371000e+02, 8.52788000e+02, 8.78620000e+02, 9.04866000e+02, 9.31524000e+02, 9.58591000e+02, 9.86067000e+02, 1.01395000e+03, 1.04223000e+03, 1.07092000e+03, 1.10000000e+03]) self["CO2"] = numpy.array([ 370.8133, 370.8152, 370.819 , 370.8248, 370.8346, 370.8484, 370.8592, 370.8579, 370.8967, 370.9416, 370.9656, 370.9707, 371.0187, 371.0558, 371.0859, 371.1189, 371.164 , 371.2181, 371.2882, 371.3753, 371.4853, 371.5974, 371.7105, 371.8065, 371.8855, 371.9556, 371.9716, 371.9786, 371.9036, 371.8306, 371.8296, 371.8286, 371.9816, 372.1516, 372.3736, 372.6286, 372.8946, 373.1656, 373.4526, 373.8036, 374.1786, 374.5586, 374.9416, 375.3396, 375.6096, 375.8926, 376.1336, 376.3425, 376.5465, 376.6605, 376.7785, 376.8464, 376.8902, 376.9449, 377.0346, 377.128 , 377.324 , 377.549 , 377.852 , 378.2698, 378.7031, 379.2006, 379.7134, 380.1292, 380.5039, 380.8129, 380.989 , 381.1627, 381.2329, 381.3075, 381.3593, 381.4038, 381.4637, 381.5393, 381.6193, 381.7075, 381.794 , 381.882 , 381.973 , 382.0935, 382.2253, 382.3864, 382.5441, 382.6894, 382.8332, 382.9886, 383.1448, 383.2917, 383.3489, 383.3001, 383.2863, 383.3892, 383.5445, 383.7251, 383.9945, 384.3599, 385.021 , 385.4928, 385.8484, 386.0688, 386.149 ]) self["CO"] = numpy.array([ 5.07834 , 4.978429 , 4.783627 , 4.465066 , 4.009665 , 3.428986 , 2.1168 , 0.7107151 , 0.3604568 , 0.1722319 , 0.09253791, 0.06835487, 0.06619429, 0.06226643, 0.05921646, 0.05582889, 0.05210092, 0.04852775, 0.04563088, 0.0435902 , 0.04266791, 0.04196062, 0.04131023, 0.04063314, 0.03983114, 0.03892895, 0.03783966, 0.03667146, 0.03530527, 0.03391147, 0.03270558, 0.03146188, 0.03095409, 0.03045309, 0.03021789, 0.03010279, 0.03018719, 0.03073179, 0.03131748, 0.03369348, 0.03659667, 0.04005435, 0.04421134, 0.04900962, 0.05320021, 0.05796649, 0.06307856, 0.06862024, 0.07462111, 0.07899018, 0.08380636, 0.08758932, 0.09090566, 0.09480198, 0.1001443 , 0.1059952 , 0.1139498 , 0.1231891 , 0.1334292 , 0.1447495 , 0.1573193 , 0.1683598 , 0.180545 , 0.1902606 , 0.1989896 , 0.2064601 , 0.2107932 , 0.2151723 , 0.2166698 , 0.2182195 , 0.2193496 , 0.220384 , 0.2215356 , 0.222791 , 0.2240452 , 0.2252751 , 0.2264323 , 0.2273394 , 0.2281768 , 0.2287195 , 0.2293438 , 0.2301862 , 0.2313281 , 0.2330089 , 0.234985 , 0.2372327 , 0.2394283 , 0.2416156 , 0.2436684 , 0.2454167 , 0.2468103 , 0.2475702 , 0.2474194 , 0.2469778 , 0.2469551 , 0.2485434 , 0.2532306 , 0.2569715 , 0.255173 , 0.2553855 , 0.2556078 ]) self["T"] = numpy.array([ 201.756, 208.959, 221.236, 232.895, 242.747, 248.786, 248.329, 240.903, 229.68 , 220.741, 219.585, 222.314, 223.457, 223.196, 222.551, 222.843, 222.789, 222.21 , 221.367, 220.664, 220.666, 221.42 , 221.862, 221.833, 221.445, 221.116, 221.34 , 221.609, 221.876, 222.239, 222.762, 223.15 , 223.03 , 222.598, 221.894, 221.35 , 221.172, 221.079, 220.7 , 220.162, 219.576, 219.085, 218.821, 218.548, 218.069, 217.619, 217.047, 216.42 , 215.951, 215.682, 215.498, 215.293, 215.002, 214.535, 213.791, 212.72 , 211.396, 210.082, 209.266, 208.907, 209.051, 209.749, 211.078, 212.777, 214.68 , 216.699, 218.741, 220.833, 222.97 , 225.147, 227.187, 229.093, 230.856, 232.34 , 233.77 , 235.146, 236.509, 237.94 , 239.449, 241.132, 242.895, 244.697, 246.497, 248.304, 250.093, 251.797, 253.356, 254.716, 255.748, 256.257, 256.617, 256.449, 255.921, 255.521, 254.315, 252.591, 250.969, 251.339, 251.339, 251.339, 251.339]) self["N2O"] = numpy.array([ 1.59999700e-04, 6.39998600e-04, 9.99997400e-04, 1.28999600e-03, 3.35998800e-03, 3.46998500e-03, 2.00999000e-03, 9.29994900e-04, 7.69995300e-04, 1.55999000e-03, 3.49997800e-03, 4.09997400e-03, 3.60997800e-03, 3.51997900e-03, 3.85997800e-03, 5.33997000e-03, 7.33996000e-03, 1.04899500e-02, 1.34499300e-02, 1.60199300e-02, 1.84799200e-02, 2.20899100e-02, 2.61798900e-02, 3.00898800e-02, 5.58597800e-02, 8.34796800e-02, 1.10069600e-01, 1.41009500e-01, 1.72649400e-01, 2.03189200e-01, 2.29059200e-01, 2.39769100e-01, 2.50139100e-01, 2.60199100e-01, 2.68909000e-01, 2.72829000e-01, 2.76629000e-01, 2.80329000e-01, 2.79099000e-01, 2.77989000e-01, 2.76929000e-01, 2.78389000e-01, 2.81049000e-01, 2.83589000e-01, 2.87389000e-01, 2.91148900e-01, 2.94858900e-01, 2.98488800e-01, 3.01988800e-01, 3.05358800e-01, 3.08538700e-01, 3.11508600e-01, 3.14228500e-01, 3.16658300e-01, 3.18747900e-01, 3.19607400e-01, 3.20386600e-01, 3.21084900e-01, 3.21683200e-01, 3.22162200e-01, 3.22532400e-01, 3.22752000e-01, 3.22831000e-01, 3.22829100e-01, 3.22826400e-01, 3.22823000e-01, 3.22818800e-01, 3.22813500e-01, 3.22806900e-01, 3.22802300e-01, 3.22799700e-01, 3.22797500e-01, 3.22795800e-01, 3.22798000e-01, 3.22801400e-01, 3.22805800e-01, 3.22806100e-01, 3.22799400e-01, 3.22785900e-01, 3.22764400e-01, 3.22744000e-01, 3.22723900e-01, 3.22703400e-01, 3.22679200e-01, 3.22661500e-01, 3.22656000e-01, 3.22663800e-01, 3.22667100e-01, 3.22610200e-01, 3.22469100e-01, 3.22355800e-01, 3.22329900e-01, 3.22345400e-01, 3.22376300e-01, 3.22443300e-01, 3.22513500e-01, 3.22566900e-01, 3.22564500e-01, 3.22572000e-01, 3.22579200e-01, 3.22586100e-01]) self["O3"] = numpy.array([ 0.510174 , 0.5621888 , 0.6514743 , 0.7822175 , 0.9318276 , 1.063576 , 1.310564 , 1.76503 , 2.535005 , 3.648507 , 4.547261 , 4.78841 , 4.92361 , 5.275468 , 5.694327 , 5.762868 , 5.783319 , 5.893709 , 6.03422 , 6.160551 , 6.228622 , 6.203113 , 6.153684 , 6.089276 , 6.012956 , 5.923467 , 5.849328 , 5.783048 , 5.734829 , 5.679589 , 5.574619 , 5.39368 , 5.244621 , 5.120821 , 4.922902 , 4.727543 , 4.524263 , 4.246424 , 3.923376 , 3.604037 , 3.319568 , 3.047309 , 2.75112 , 2.482241 , 2.317652 , 2.148792 , 1.885393 , 1.603124 , 1.397604 , 1.272585 , 1.146755 , 0.9980887 , 0.8611839 , 0.729153 , 0.5870622 , 0.4483724 , 0.3575272 , 0.2652448 , 0.1737753 , 0.1178921 , 0.09092905, 0.07172082, 0.05827958, 0.05142367, 0.04863645, 0.04841805, 0.04816644, 0.04715373, 0.04594748, 0.04495205, 0.0455781 , 0.04686353, 0.04873582, 0.04975662, 0.0501041 , 0.04979462, 0.04934463, 0.04914342, 0.04915406, 0.04921568, 0.04915478, 0.04893549, 0.04849328, 0.04805416, 0.04794348, 0.04790108, 0.0476205 , 0.04700432, 0.04654844, 0.04632991, 0.04646221, 0.04573811, 0.04403783, 0.04091335, 0.03254705, 0.02640277, 0.02501912, 0.02442054, 0.02442111, 0.02442165, 0.02442218]) self["CH4"] = numpy.array([ 0.04183322, 0.07070085, 0.09215896, 0.1150766 , 0.1600424 , 0.1895992 , 0.203706 , 0.2216318 , 0.2513385 , 0.2618113 , 0.2802002 , 0.3011591 , 0.323238 , 0.3478319 , 0.3743778 , 0.4088557 , 0.4408626 , 0.4700776 , 0.4956766 , 0.5058676 , 0.5155767 , 0.5382237 , 0.5665796 , 0.5937466 , 0.6694654 , 0.7486761 , 0.8249039 , 0.9082426 , 0.9919303 , 1.046986 , 1.106076 , 1.169336 , 1.236905 , 1.290275 , 1.341695 , 1.390245 , 1.434895 , 1.474525 , 1.496414 , 1.519504 , 1.543804 , 1.569344 , 1.596164 , 1.637644 , 1.659294 , 1.681934 , 1.697794 , 1.708283 , 1.718413 , 1.722753 , 1.727263 , 1.729712 , 1.731132 , 1.7327 , 1.734659 , 1.736686 , 1.740032 , 1.743762 , 1.748043 , 1.753067 , 1.758228 , 1.763046 , 1.768011 , 1.77186 , 1.775215 , 1.778026 , 1.779713 , 1.781404 , 1.782387 , 1.783412 , 1.784227 , 1.784995 , 1.785885 , 1.786897 , 1.788006 , 1.78924 , 1.790502 , 1.791825 , 1.793189 , 1.79475 , 1.796366 , 1.798093 , 1.799748 , 1.801223 , 1.802603 , 1.803951 , 1.805294 , 1.806622 , 1.807672 , 1.80842 , 1.809452 , 1.811134 , 1.812978 , 1.815059 , 1.817833 , 1.821496 , 1.829131 , 1.834953 , 1.839252 , 1.841891 , 1.842819 ]) self["CTP"] = 500.0 self["CFRACTION"] = 0.0 self["IDG"] = 0 self["ISH"] = 0 self["ELEVATION"] = 0.0 self["S2M"]["T"] = 251.339 self["S2M"]["Q"] = 786.558838187 self["S2M"]["O"] = 0.0244221754008 self["S2M"]["P"] = 1007.16998 self["S2M"]["U"] = 0.0 self["S2M"]["V"] = 0.0 self["S2M"]["WFETC"] = 100000.0 self["SKIN"]["SURFTYPE"] = 1 self["SKIN"]["WATERTYPE"] = 1 self["SKIN"]["T"] = 251.339 self["SKIN"]["SALINITY"] = 35.0 self["SKIN"]["FOAM_FRACTION"] = 0.0 self["SKIN"]["FASTEM"] = numpy.array([ 3. , 5. , 15. , 0.1, 0.3]) self["ZENANGLE"] = 0.0 self["AZANGLE"] = 0.0 self["SUNZENANGLE"] = 0.0 self["SUNAZANGLE"] = 0.0 self["LATITUDE"] = 72.967 self["GAS_UNITS"] = 2 self["BE"] = 0.0 self["COSBK"] = 0.0 self["DATE"] = numpy.array([2007, 1, 20]) self["TIME"] = numpy.array([0, 0, 0])

57.516949

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639b3be3ffc4882950b2537d142e6095224bc2ad

596

py

Python

lawyerd/products/management_/commands/domain_check.py

loobinsk/customer_project

4f43d4c6db2c99926715ea16451511466569c4ae

[ "MIT" ]

null

lawyerd/products/management_/commands/domain_check.py

loobinsk/customer_project

4f43d4c6db2c99926715ea16451511466569c4ae

[ "MIT" ]

null

lawyerd/products/management_/commands/domain_check.py

loobinsk/customer_project

4f43d4c6db2c99926715ea16451511466569c4ae

[ "MIT" ]

null

from time import sleep from django.core.management.base import BaseCommand, CommandError # from products.tasks import domain_check # class Command(BaseCommand): # help = 'Check few site' # # # def add_arguments(self, parser): # # parser.add_argument('poll_ids', nargs='+', type=int) # # def handle(self, *args, **options): # no_delay = True # for i in range(100): # res = domain_check(no_delay) # if res == -1: # sleep(30) # # self.stdout.write(self.style.SUCCESS(f'Updated sites: {res}')) # pass

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null

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1

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63a695d16dd20d6dfc932a28143d90ee5bdb2056

2,167

py

Python

src/api/models.py

Dr4kk0nnys/django-schedule-api

bcb83661f19847fbd9e6d9dc576010e837e612fd

[ "MIT" ]

2

2020-10-24T20:33:44.000Z

2020-10-29T18:24:01.000Z

src/api/models.py

Dr4kk0nnys/django-schedule-api

bcb83661f19847fbd9e6d9dc576010e837e612fd

[ "MIT" ]

null

src/api/models.py

Dr4kk0nnys/django-schedule-api

bcb83661f19847fbd9e6d9dc576010e837e612fd

[ "MIT" ]

null

from django.db import models from django.core.validators import MaxValueValidator, MinValueValidator class User(models.Model): email = models.EmailField(default='No email provided.') password = models.CharField(max_length=256, default='No password provided.') token_id = models.CharField(max_length=256, default='No token id provided.') api_calls = models.IntegerField(default=0) objects = models.Manager() def __str__(self): return self.email class ScheduledDate(models.Model): date = models.DateTimeField('scheduled meeting') count = models.IntegerField(default=0, validators=[ MaxValueValidator(5), MinValueValidator(1) ]) objects = models.Manager() def __str__(self): return str(self.date) class Information(models.Model): scheduled_date = models.ForeignKey(ScheduledDate, on_delete=models.CASCADE) user = models.ForeignKey(User, on_delete=models.CASCADE) def __str__(self): return '' class Register(models.Model): email = models.EmailField() password = models.CharField(max_length=256) objects = models.Manager() def __str__(self): return str(self.email) class TimeList(models.Model): day = models.CharField(max_length=2) month = models.CharField(max_length=2) year = models.CharField(max_length=4) token_id = models.CharField(max_length=256) objects = models.Manager() def __str__(self): return '-'.join([self.day, self.month, self.year]) class ScheduleApi(models.Model): day = models.CharField(max_length=2) month = models.CharField(max_length=2) year = models.CharField(max_length=4) hours = models.CharField(max_length=2) minutes = models.CharField(max_length=2) company_name = models.CharField(max_length=200) token_id = models.CharField(max_length=256) objects = models.Manager() def __str__(self): return self.company_name class ApiCall(models.Model): token_id = models.CharField(max_length=256) api_credits = models.IntegerField(default=0) objects = models.Manager() def __str__(self): return self.token_id

26.108434

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0.184049

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null

0

1

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null

0

1

0

3

63b087acaf36016c331bc3fdce37ca553a022ec4

511

py

Python

src/users/models.py

vinay-pad/commit_service

6f2113ba77fad6466969173c3e518ef565096920

[ "MIT" ]

null

src/users/models.py

vinay-pad/commit_service

6f2113ba77fad6466969173c3e518ef565096920

[ "MIT" ]

null

src/users/models.py

vinay-pad/commit_service

6f2113ba77fad6466969173c3e518ef565096920

[ "MIT" ]

null

from __future__ import unicode_literals from django.db import models from django.contrib.auth.models import AbstractUser from rest_framework.authtoken.models import Token from django.dispatch import receiver from django.db.models.signals import post_save from django.conf import settings @receiver(post_save, sender=settings.AUTH_USER_MODEL) def create_auth_token(sender, instance=None, created=False, **kwargs): if created: Token.objects.create(user=instance) class User(AbstractUser): pass

30.058824

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0.059553

0

0.117417

511

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0.89357

0

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0.076923

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0.692308

0

null

0

null

0

1

0

1

0

3

63c52307946b28edaffca66cd20d561925cd8860

154

py

Python

nautobot/core/management/commands/start.py

psmware-ltd/nautobot

ac516287fb8edcc3482bd011839de837c6bbf0df

[ "Apache-2.0" ]

384

2021-02-24T01:40:40.000Z

2022-03-30T10:30:59.000Z

nautobot/core/management/commands/start.py

psmware-ltd/nautobot

ac516287fb8edcc3482bd011839de837c6bbf0df

[ "Apache-2.0" ]

1,067

2021-02-24T00:58:08.000Z

2022-03-31T23:38:23.000Z

nautobot/core/management/commands/start.py

psmware-ltd/nautobot

ac516287fb8edcc3482bd011839de837c6bbf0df

[ "Apache-2.0" ]

128

2021-02-24T02:45:16.000Z

2022-03-20T18:48:36.000Z

from django_webserver.management.commands.pyuwsgi import Command as uWSGICommand class Command(uWSGICommand): help = "Start Nautobot uWSGI server."

25.666667

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null

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3

891d00de94862749b3d00d8d56f2a893158bdab0

1,474

py

Python

hard-gists/e76e7c2a2aff228d7807/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

21

2019-07-08T08:26:45.000Z

2022-01-24T23:53:25.000Z

hard-gists/e76e7c2a2aff228d7807/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

5

2019-06-15T14:47:47.000Z

2022-02-26T05:02:56.000Z

hard-gists/e76e7c2a2aff228d7807/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

17

2019-05-16T03:50:34.000Z

2021-01-14T14:35:12.000Z

# original file name: solve_sssa_attack.sage from sage.all import * p = 16857450949524777441941817393974784044780411511252189319 A = 16857450949524777441941817393974784044780411507861094535 B = 77986137112576 E = EllipticCurve(GF(p), [A, B]) print E.order() == p g = E(5732560139258194764535999929325388041568732716579308775, 14532336890195013837874850588152996214121327870156054248) v = E(2609506039090139098835068603396546214836589143940493046, 8637771092812212464887027788957801177574860926032421582) def hensel_lift(curve, p, point): A, B = map(long, (E.a4(), E.a6())) x, y = map(long, point.xy()) fr = y**2 - (x**3 + A*x + B) t = (- fr / p) % p t *= inverse_mod(2 * y, p) # (y**2)' = 2 * y t %= p new_y = y + p * t return x, new_y # lift points x1, y1 = hensel_lift(E, p, g) x2, y2 = hensel_lift(E, p, v) # calculate new A, B (actually, they will be the same here) mod = p ** 2 A2 = y2**2 - y1**2 - (x2**3 - x1**3) A2 = A2 * inverse_mod(x2 - x1, mod) A2 %= mod B2 = y1**2 - x1**3 - A2 * x1 B2 %= mod # new curve E2 = EllipticCurve(IntegerModRing(p**2), [A2, B2]) # calculate dlog g2s = (p - 1) * E2(x1, y1) v2s = (p - 1) * E2(x2, y2) x1s, y1s = map(long, g2s.xy()) x2s, y2s = map(long, v2s.xy()) dx1 = (x1s - x1) / p % p dx2 = (y1s - y1) / p dy1 = (x2s - x2) dy2 = (y2s - y2) % p print "%d, %d, %d, %d, %d" % (dx1, dy1, dx2, dy2, p) m = dy1 * inverse_mod(dx1, p) * dx2 * inverse_mod(dy2, p) m %= p print m

23.774194

120

0.624152

222

1,474

4.094595

0.351351

0.030803

0.009901

0.026403

0

0.362306

0.211669

1,474

61

121

24.163934

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1

0

1

0

null

0

1

0

3

8925ce37bab22ff983851fb7f4b5ffa1ebcbdb05

367

py

Python

bmc/library.py

reich6534/SumoPY

fb03db75e3799bad2759c0017f8919893690b289

[ "Apache-2.0" ]

null

bmc/library.py

reich6534/SumoPY

fb03db75e3799bad2759c0017f8919893690b289

[ "Apache-2.0" ]

4

2020-08-10T15:07:40.000Z

2020-08-25T19:30:29.000Z

bmc/library.py

reich6534/SumoPY

fb03db75e3799bad2759c0017f8919893690b289

[ "Apache-2.0" ]

1

2020-06-19T14:21:26.000Z

class Library(object): def __init__(self): self.dictionary = { "Micah": ["Judgement on Samaria and Judah", "Reason for the judgement", "Judgement on wicked leaders", "Messianic Kingdom", "Birth of the Messiah", "Indictment 1, 2", "Promise of salvation"] } def get(self, book): return self.dictionary.get(book)

36.7

114

0.618529

43

367

5.186047

0.72093

0.125561

0

0.00738

0.26158

367

9

115

40.777778

0.815498

0

0.430518

0

1

0.25

false

0

0.125

0.5

0

null

0

1

0

null

0

1

0

1

0

3

893b9e065a28f5630ccaded0f017079ecfaf7dc8

200

py

Python

empyres/log/__init__.py

waigore/empyres4x

aa3bbf94ea0bca280152e92d485d5825a4b352ca

[ "Apache-2.0" ]

null

empyres/log/__init__.py

waigore/empyres4x

aa3bbf94ea0bca280152e92d485d5825a4b352ca

[ "Apache-2.0" ]

null

empyres/log/__init__.py

waigore/empyres4x

aa3bbf94ea0bca280152e92d485d5825a4b352ca

[ "Apache-2.0" ]

null

import logging import logging.config import os logging.config.fileConfig(os.path.join(os.path.dirname(__file__), 'logging.conf')) logger = logging.getLogger(__name__) logger.info('Logging set up.')

22.222222

82

0.785

28

200

5.321429

0.571429

0.174497

0

0.08

200

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1

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null

0

1

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3

895b9204b1c7babcc360e02ed5bd834e6e8b6c56

136

py

Python

DMOJ/DMOPC/DMOPC_14_C1P1_Median_Mark.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

null

DMOJ/DMOPC/DMOPC_14_C1P1_Median_Mark.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-10-14T18:26:56.000Z

DMOJ/DMOPC/DMOPC_14_C1P1_Median_Mark.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-08-06T03:39:55.000Z

import math import statistics c = [] for i in range(int(input())): c.append(int(input())) print(math.ceil(statistics.median(c)))

13.6

38

0.669118

21

136

4.333333

0.666667

0.175824

0

0.147059

136

9

39

15.111111

0.784483

0

1

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false

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0

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1

0

null

0

1

0

null

0

1

0

3

896363c649069897110f5ef453bca2a7e5aa1e13

5,793

py

Python

experiments/models/dcgan.py

zhaodongsun/pnp_dip

f8f3802af8c607b3063fc7b92e20729f148d36c1

[ "MIT" ]

4

2021-10-12T09:13:08.000Z

2022-02-14T19:59:43.000Z

experiments/models/dcgan.py

zhaodongsun/pnp_dip

f8f3802af8c607b3063fc7b92e20729f148d36c1

[ "MIT" ]

1

2021-05-20T04:22:00.000Z

2021-05-21T06:44:47.000Z

experiments/models/dcgan.py

zhaodongsun/pnp_dip

f8f3802af8c607b3063fc7b92e20729f148d36c1

[ "MIT" ]

1

2021-11-27T11:35:06.000Z

import torch import torch.nn as nn import torch.nn.functional as F def dcgan(inp=2, ndf=32, num_ups=4, need_sigmoid=True, need_bias=True, pad='zero', upsample_mode='nearest', need_convT = True): layers= [nn.ConvTranspose2d(inp, ndf, kernel_size=3, stride=1, padding=0, bias=False), nn.BatchNorm2d(ndf), nn.LeakyReLU(True)] for i in range(num_ups-3): if need_convT: layers += [ nn.ConvTranspose2d(ndf, ndf, kernel_size=4, stride=2, padding=1, bias=False), nn.BatchNorm2d(ndf), nn.LeakyReLU(True)] else: layers += [ nn.Upsample(scale_factor=2, mode=upsample_mode), nn.Conv2d(ndf, ndf, kernel_size=3, stride=1, padding=1, bias=False), nn.BatchNorm2d(ndf), nn.LeakyReLU(True)] if need_convT: layers += [nn.ConvTranspose2d(ndf, 3, 4, 2, 1, bias=False),] else: layers += [nn.Upsample(scale_factor=2, mode='bilinear'), nn.Conv2d(ndf, 3, kernel_size=3, stride=1, padding=1, bias=False)] if need_sigmoid: layers += [nn.Sigmoid()] model =nn.Sequential(*layers) return model class DCGAN_XRAY(nn.Module): def __init__(self, nz, ngf=64, output_size=256, nc=3, num_measurements=1000): super(DCGAN_XRAY, self).__init__() self.nc = nc self.output_size = output_size self.conv1 = nn.ConvTranspose2d(nz, ngf, 4, 1, 0, bias=False) self.bn1 = nn.BatchNorm2d(ngf) self.conv2 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn2 = nn.BatchNorm2d(ngf) self.conv3 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn3 = nn.BatchNorm2d(ngf) self.conv4 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn4 = nn.BatchNorm2d(ngf) self.conv5 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn5 = nn.BatchNorm2d(ngf) self.conv6 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn6 = nn.BatchNorm2d(ngf) self.conv7 = nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False) # output is image def forward(self, z): input_size = z.size() x = F.relu(self.bn1(self.conv1(z))) x = F.relu(self.bn2(self.conv2(x))) x = F.relu(self.bn3(self.conv3(x))) x = F.relu(self.bn4(self.conv4(x))) x = F.relu(self.bn5(self.conv5(x))) x = F.relu(self.bn6(self.conv6(x))) x = torch.sigmoid(self.conv7(x, output_size=(-1, self.nc, self.output_size, self.output_size))) return x class DCGAN_MNIST(nn.Module): def __init__(self, nz, ngf=64, output_size=28, nc=1, num_measurements=10): super(DCGAN_MNIST, self).__init__() self.nc = nc self.output_size = output_size self.conv1 = nn.ConvTranspose2d(nz, ngf * 8, 2, 1, 0, bias=False) self.bn1 = nn.BatchNorm2d(ngf * 8) self.conv2 = nn.ConvTranspose2d(ngf * 8, ngf * 4, 4, 1, 0, bias=False) self.bn2 = nn.BatchNorm2d(ngf * 4) self.conv3 = nn.ConvTranspose2d(ngf * 4, ngf * 2, 3, 1, 1, bias=False) self.bn3 = nn.BatchNorm2d(ngf * 2) self.conv4 = nn.ConvTranspose2d(ngf * 2, ngf, 3, 1, 1, bias=False) self.bn4 = nn.BatchNorm2d(ngf) self.conv5 = nn.ConvTranspose2d(ngf, nc, 3, 1, 1, bias=False) def forward(self, x): input_size = x.size() # DCGAN_MNIST with old PyTorch version # x = F.upsample(F.relu(self.bn1(self.conv1(x))),scale_factor=2) # x = F.relu(self.bn2(self.conv2(x))) # x = F.upsample(F.relu(self.bn3(self.conv3(x))),scale_factor=2) # x = F.upsample(F.relu(self.bn4(self.conv4(x))),scale_factor=2) # x = torch.tanh(self.conv5(x,output_size=(-1,self.nc,self.output_size,self.output_size))) x = F.interpolate(F.relu(self.bn1(self.conv1(x))), scale_factor=2) x = F.relu(self.bn2(self.conv2(x))) x = F.interpolate(F.relu(self.bn3(self.conv3(x))), scale_factor=2) x = F.interpolate(F.relu(self.bn4(self.conv4(x))), scale_factor=2) x = torch.sigmoid(self.conv5(x, output_size=(-1, self.nc, self.output_size, self.output_size))) return x class DCGAN_RETINO(nn.Module): def __init__(self, nz, ngf=64, output_size=256, nc=3, num_measurements=1000): super(DCGAN_RETINO, self).__init__() self.nc = nc self.output_size = output_size self.conv1 = nn.ConvTranspose2d(nz, ngf, 4, 1, 0, bias=False) self.bn1 = nn.BatchNorm2d(ngf) self.conv2 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn2 = nn.BatchNorm2d(ngf) self.conv3 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn3 = nn.BatchNorm2d(ngf) self.conv4 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn4 = nn.BatchNorm2d(ngf) self.conv5 = nn.ConvTranspose2d(ngf, ngf, 6, 2, 2, bias=False) self.bn5 = nn.BatchNorm2d(ngf) self.conv6 = nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False) # self.fc = nn.Linear((output_size)*(output_size)*nc,num_measurements, bias=False) #fc layer - old version def forward(self, x): input_size = x.size() x = F.relu(self.bn1(self.conv1(x))) x = F.relu(self.bn2(self.conv2(x))) x = F.relu(self.bn3(self.conv3(x))) x = F.relu(self.bn4(self.conv4(x))) x = F.relu(self.bn5(self.conv5(x))) x = torch.sigmoid(self.conv6(x, output_size=(-1, self.nc, self.output_size, self.output_size))) return x

43.231343

115

0.582945

846

5,793

3.893617

0.117021

0.065574

0.051913

0.039466

0.81269

0.765938

0.744687

0.693078

0.626897

0.585914

0

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5,793

134

116

43.231343

0.720283

0.081132

0

0.533981

0

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1

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false

0

0.029126

0

0.165049

0

null

0

1

0

null

0

3

8966c49bdc27990bdccb45446aa23c8fa6bda9e4

442

py

Python

description_widgets.py

athrn/kognitivo

15822338778213c09ea654ec4e06a300129f9478

[ "Apache-2.0" ]

80

2017-11-13T21:58:55.000Z

2022-01-03T20:10:42.000Z

description_widgets.py

athrn/kognitivo

15822338778213c09ea654ec4e06a300129f9478

[ "Apache-2.0" ]

null

description_widgets.py

athrn/kognitivo

15822338778213c09ea654ec4e06a300129f9478

[ "Apache-2.0" ]

21

2017-11-14T09:47:41.000Z

2021-11-23T06:44:31.000Z

from kivy.uix.label import Label from kivy.uix.widget import Widget from utils import import_kv import_kv(__file__) class BaseDescriptionWidget(Widget): pass class TextDescriptionWidget(Label, BaseDescriptionWidget): pass class SymbolTextDescriptionWidget(Label, BaseDescriptionWidget): def __init__(self, **kwargs): super(SymbolTextDescriptionWidget, self).__init__(**kwargs) self.font_name = "glyphicons"

22.1

67

0.771493

46

442

7.086957

0.478261

0.04908

0.067485

0

0.149321

442

19

68

23.263158

0.867021

0

0.166667

0

0.022624

0

1

0.083333

false

0.166667

0.333333

0

0.666667

0

null

0

null

0

1

0

1

0

3

897f94342875182a66572e8bd80ae93237c11276

962

py

Python

easyrules/__init__.py

wffzxyl/easyrules

8874718fec629435c69ce360cd43a281da162627

[ "MIT" ]

1

2020-10-03T12:34:01.000Z

easyrules/__init__.py

wffzxyl/easyrules

8874718fec629435c69ce360cd43a281da162627

[ "MIT" ]

null

easyrules/__init__.py

wffzxyl/easyrules

8874718fec629435c69ce360cd43a281da162627

[ "MIT" ]

null

# coding: utf-8 # flake8: noqa from __future__ import absolute_import VERSION = (0, 2, 1) __version__ = VERSION __versionstr__ = ".".join(map(str, VERSION)) import logging logger = logging.getLogger("easyrules") logger.addHandler(logging.NullHandler()) from . import config from .api import Action from .api import Condition from .api import Fact from .api import Facts from .api import Rule from .api import RuleDecorator from .api import RulesEngineListener from .api import RuleListener from .api import Rules from .api import RulesEngine from .api import RulesEngineParameters from .core import DefaultRule from .core import DefaultRuleEngine from .core import RuleBuilder from .support import ActivationRuleGroup from .support import CompositeRule from .support import ConditionalRuleGroup from .support import UnitRuleGroup from .support import YamlRuleDefinitionReader from .support import YamlRuleFactory from .utils import logger, exception_handler

26.722222

45

0.816008

120

962

6.425

0.416667

0.09987

0.185473

0

0.005945

0.12578

962

35

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27.485714

0.91082

0.027027

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0

0.827586

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0.827586

0

null

0

1

0

null

0

1

0

1

0

3

8980817119457f47f4b367ebe86b8a28179da299

354

py

Python

notes/my_bad_script.py

areed1192/python-for-starters

bcb38a80cff5d2087ce95f9f815c8c1909737861

[ "MIT" ]

1

2021-05-26T01:08:39.000Z

notes/my_bad_script.py

areed1192/python-for-starters

bcb38a80cff5d2087ce95f9f815c8c1909737861

[ "MIT" ]

null

notes/my_bad_script.py

areed1192/python-for-starters

bcb38a80cff5d2087ce95f9f815c8c1909737861

[ "MIT" ]

4

2021-04-28T00:37:06.000Z

2022-03-04T00:00:55.000Z

def split_full_name(string: str) -> list: """Takes a full name and splits it into first and last. Parameters ---------- string : str The full name to be parsed. Returns ------- list The first and the last name. """ return string.split(" ") # Test it out. print(split_full_name(string=100000000))

16.857143

59

0.581921

47

354

4.297872

0.553191

0.158416

0.128713

0.188119

0

0.035857

0.29096

354

20

60

17.7

0.768924

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0.008264

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false

0

0.666667

0.333333

0

null

0

1

0

null

0

1

0

1

0

3

8990b721037221c7126af1a48dedddaaf5536512

1,290

py

Python

per/migrations/0003_auto_20190416_1021.py

IFRCGo/ifrcgo-api

c1c3e0cf1076ab48d03db6aaf7a00f8485ca9e1a

[ "MIT" ]

11

2018-06-11T06:05:12.000Z

2022-03-25T09:31:44.000Z

per/migrations/0003_auto_20190416_1021.py

IFRCGo/ifrcgo-api

c1c3e0cf1076ab48d03db6aaf7a00f8485ca9e1a

[ "MIT" ]

498

2017-11-07T21:20:13.000Z

2022-03-31T14:37:18.000Z

per/migrations/0003_auto_20190416_1021.py

IFRCGo/ifrcgo-api

c1c3e0cf1076ab48d03db6aaf7a00f8485ca9e1a

[ "MIT" ]

6

2018-04-11T13:29:50.000Z

2020-07-16T16:52:11.000Z

# Generated by Django 2.0.12 on 2019-04-16 10:21 from django.db import migrations, models import django.utils.timezone import uuid class Migration(migrations.Migration): dependencies = [ ('per', '0002_form_ns'), ] operations = [ migrations.AddField( model_name='form', name='comment', field=models.TextField(blank=True, null=True), ), migrations.AddField( model_name='form', name='ended_at', field=models.DateTimeField(default=django.utils.timezone.now), ), migrations.AddField( model_name='form', name='started_at', field=models.DateTimeField(default=django.utils.timezone.now), ), migrations.AddField( model_name='form', name='submitted_at', field=models.DateTimeField(default=django.utils.timezone.now), ), migrations.AddField( model_name='form', name='unique_id', field=models.UUIDField(default=uuid.uuid4, editable=False, unique=True), ), migrations.AddField( model_name='form', name='validated', field=models.BooleanField(default=False), ), ]

28.043478

84

0.569767

126

1,290

5.738095

0.412698

0.149378

0.190871

0.224066

0.529737

0.481328

0.373444

0

0.023675

0.312403

1,290

45

85

28.666667

0.791432

0.035659

0

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1

0

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0

1

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false

0

0.076923

0

0.153846

0

null

0

1

0

1

0

null

0

3

899277d3f0483bc888d114acb38804f3316ed7d3

198

py

Python

python/cdp_los_angeles_backend/__init__.py

mattyweb/los-angeles

dc3354915e196fb805a87f40f35e5707f29c1652

[ "MIT" ]

null

python/cdp_los_angeles_backend/__init__.py

mattyweb/los-angeles

dc3354915e196fb805a87f40f35e5707f29c1652

[ "MIT" ]

null

python/cdp_los_angeles_backend/__init__.py

mattyweb/los-angeles

dc3354915e196fb805a87f40f35e5707f29c1652

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Top-level package for Los Angeles CDP instance backend. """ __author__ = "Matt Webster" __version__ = "1.0.0" def get_module_version() -> str: return __version__

14.142857

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0.666667

26

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4.538462

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0

0.024691

0.181818

198

13

34

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0.393939

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0

0.25

0.5

0

1

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null

0

null

0

1

0

1

0

3

899315b2a317eab99147fe92d0ac2e4a2758abe4

139

py

Python

src/analytics/urls.py

TolgaKara/prodai

a858d39226a072a2a52513d942dd046bb3787da8

[ "Apache-2.0" ]

null

src/analytics/urls.py

TolgaKara/prodai

a858d39226a072a2a52513d942dd046bb3787da8

[ "Apache-2.0" ]

7

2020-10-09T09:24:28.000Z

2022-03-12T00:14:07.000Z

src/analytics/urls.py

TolgaKara/prodai

a858d39226a072a2a52513d942dd046bb3787da8

[ "Apache-2.0" ]

null

from django.urls import path, include from src.analytics import views urlpatterns = [ path('', views.analytics, name='analytics'), ]

17.375

48

0.719424

17

139

5.882353

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0.158273

139

7

49

19.857143

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null

0

1

0

null

0

1

0

3

89bd7a1c82d4de4c7a0ffcee38c719ac45f52dc0

636

py

Python

embiggen/layers/tensorflow/__init__.py

monarch-initiative/N2V

8ae02ca125f1d24ca158c2849f2d9bb1711920b9

[ "BSD-3-Clause" ]

2

2020-01-30T11:57:37.000Z

2020-05-02T00:05:49.000Z

embiggen/layers/tensorflow/__init__.py

monarch-initiative/N2V

8ae02ca125f1d24ca158c2849f2d9bb1711920b9

[ "BSD-3-Clause" ]

93

2020-01-26T00:43:51.000Z

2020-05-10T03:29:54.000Z

embiggen/layers/tensorflow/__init__.py

monarch-initiative/N2V

8ae02ca125f1d24ca158c2849f2d9bb1711920b9

[ "BSD-3-Clause" ]

5

2020-02-13T07:18:11.000Z

2020-03-19T08:03:34.000Z

"""Submodule providing tensorflow layers.""" from embiggen.layers.tensorflow.graph_convolution_layer import GraphConvolution from embiggen.layers.tensorflow.noise_contrastive_estimation import NoiseContrastiveEstimation from embiggen.layers.tensorflow.sampled_softmax import SampledSoftmax from embiggen.layers.tensorflow.embedding_lookup import EmbeddingLookup from embiggen.layers.tensorflow.flat_embedding import FlatEmbedding from embiggen.layers.tensorflow.l2_norm import L2Norm __all__ = [ "GraphConvolution", "NoiseContrastiveEstimation", "SampledSoftmax", "EmbeddingLookup", "FlatEmbedding", "L2Norm" ]

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1

0

null

0

1

0

3

983c65097575f5f76dccd3df94eea5f5102e6339

255

py

Python

setup.py

Kesel/django

f3fc3617c4b39b18e54bfb4c2fc8940e40f8fa25

[ "MIT" ]

null

setup.py

Kesel/django

f3fc3617c4b39b18e54bfb4c2fc8940e40f8fa25

[ "MIT" ]

null

setup.py

Kesel/django

f3fc3617c4b39b18e54bfb4c2fc8940e40f8fa25

[ "MIT" ]

null

from setuptools import setup setup(name='django-on-openshift', version='2.0', description='Django on OpenShift', author='Biwin John', author_email='mail@biwin.in', url='https://github.com/biwin/django-on-openshift', )

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255

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0

null

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1

0

3

98402d2772ebb180a88617d9578741a4df8acf0a

957

py

Python

cardbuilder/input/word_list.py

jrhoff/cardbuilder

857360b1827494a286cee9928cb004af882e55b4

[ "MIT" ]

null

cardbuilder/input/word_list.py

jrhoff/cardbuilder

857360b1827494a286cee9928cb004af882e55b4

[ "MIT" ]

null

cardbuilder/input/word_list.py

jrhoff/cardbuilder

857360b1827494a286cee9928cb004af882e55b4

[ "MIT" ]

null

from abc import ABC from copy import copy from typing import List, Iterable, Optional, Union from cardbuilder.input.word import Word, WordForm class WordList(ABC): def __init__(self, word_input_forms: Iterable[str], language: str, additional_forms: Optional[List[WordForm]]): self.words = [Word(input_form, language, additional_forms) for input_form in word_input_forms] def __getitem__(self, index: Union[int, slice]) -> Union[Word, 'WordList']: if isinstance(index, int): return self.words[index] elif isinstance(index, slice): list_copy = copy(self) list_copy.words = self.words[index] return list_copy else: raise TypeError('WordList indices must be either integers or slices') def __iter__(self): return iter(self.words) def __len__(self): return len(self.words) def __repr__(self): return repr(self.words)

29.90625

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0.666667

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957

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957

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116

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0.136364

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0

null

0

null

0

1

0

1

0

3

98585c83774a96ddf3fb29e2caa3b89cf21e0fa1

282

py

Python

pyfor/__init__.py

brycefrank/pyfor

efd34bcd7440358abea770c1bf5cad5e05a6fbe3

[ "MIT" ]

68

2018-04-02T18:00:29.000Z

2022-03-14T09:41:21.000Z

pyfor/__init__.py

brycefrank/PyFor

efd34bcd7440358abea770c1bf5cad5e05a6fbe3

[ "MIT" ]

68

2018-04-04T19:15:21.000Z

2020-02-14T19:03:49.000Z

pyfor/__init__.py

brycefrank/PyFor

efd34bcd7440358abea770c1bf5cad5e05a6fbe3

[ "MIT" ]

23

2018-04-03T16:30:40.000Z

2021-09-16T08:06:05.000Z

from __future__ import absolute_import __version__ = "0.3.6" from pyfor import cloud from pyfor import rasterizer from pyfor import gisexport from pyfor import clip from pyfor import ground_filter from pyfor import collection from pyfor import voxelizer from pyfor import metrics

21.692308

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null

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9869ad66b58a9f4a34f0b342f504102754bd1a4e

1,093

py

Python

src/pyhees/section10_j1_d.py

jjj-design/pyhees

d63e7cd84abfc2f509bc1cd1256598a10aac1825

[ "MIT" ]

null

src/pyhees/section10_j1_d.py

jjj-design/pyhees

d63e7cd84abfc2f509bc1cd1256598a10aac1825

[ "MIT" ]

null

src/pyhees/section10_j1_d.py

jjj-design/pyhees

d63e7cd84abfc2f509bc1cd1256598a10aac1825

[ "MIT" ]

null

# 洗濯機 def get_E_Elc_washer_d_t(E_Elc_washer_wash_rtd, tm_washer_wash_d_t): """時刻別消費電力量を計算する Parameters ---------- E_Elc_washer_wash_rtd : float 標準コースの洗濯の定格消費電力量,Wh tm_washer_wash_d_t : ndarray(N-dimensional array) 1年間の全時間の洗濯回数を格納したND配列, 回 d日t時の洗濯回数が年開始時から8760個連続して格納されている Returns ---------- E_Elc_toilet_seat_heater_d_t : ndarray(N-dimensional array) 1年間の全時間の消費電力量を格納したND配列, Wh d日t時の消費電力量が年開始時から8760個連続して格納されている """ E_Elc_washer_wash = get_E_Elc_washer_wash(E_Elc_washer_wash_rtd) E_Elc_washer_d_t = E_Elc_washer_wash * tm_washer_wash_d_t E_Elc_washer_d_t = E_Elc_washer_d_t * 10**(-3) return E_Elc_washer_d_t def get_E_Elc_washer_wash(E_Elc_washer_wash_rtd): """洗濯時の消費電力量を計算する Parameters ---------- E_Elc_washer_wash_rtd : float 標準コースの洗濯の定格消費電力量,Wh Returns ---------- E_Elc_washer_wash : float 1回の洗濯の消費電力量,Wh """ E_Elc_washer_wash = 1.3503 * E_Elc_washer_wash_rtd - 42.848 return E_Elc_washer_wash

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0.276498

0.27957

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0.104455

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0

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null

0

1

0

null

0

1

0

3

9871e79d855a7f9da8d94e60b5f377510b9de886

1,759

py

Python

api.flask.v1/controllers/status.py

davelosert/medishare

bbe1a61f185e1cf6ffe6f37b8d37577dda29a01c

[ "MIT" ]

1

2020-12-14T15:20:15.000Z

api.flask.v1/controllers/status.py

davelosert/medishare

bbe1a61f185e1cf6ffe6f37b8d37577dda29a01c

[ "MIT" ]

5

2021-10-06T14:03:45.000Z

2022-02-27T01:33:33.000Z

api.flask.v1/controllers/status.py

davelosert/medishare

bbe1a61f185e1cf6ffe6f37b8d37577dda29a01c

[ "MIT" ]

null

from flask import request, jsonify from flask.views import MethodView from models import Status from db import db class StatusAPI(MethodView): def get(self, id): if id is None: return jsonify([s.serialize for s in Status.query.all()]) else: status = Status.query.filter_by(id=id).one_or_none() if not status: return jsonify({'message' : 'Status not found'}), 404 return jsonify(status.serialize) def post(self): new_status = Status.fromJson(request.get_json()) if new_status is None: return jsonify({'message' : 'Status title missing'}), 400 db.session.add(new_status) db.session.commit() return jsonify({'message' : 'New Status created!'}), 201 def delete(self, id): if id is None: return jsonify({'message' : 'Invalid request'}), 400 status = Status.query.filter_by(id=id).one_or_none() if not status: return jsonify({'message' : 'Status not found'}), 404 db.session.delete(status) db.session.commit() return jsonify({'message' : 'Status deleted'}), 202 def put(self, id): if id is None: return jsonify({'message' : 'Invalid request'}), 400 new_status = Status.fromJson(request.get_json()) if new_status is None: return jsonify({'message' : 'Status data missing or incomplete'}), 400 status = Status.query.filter_by(id=id).one_or_none() if not status: return jsonify({'message' : 'Status not found'}), 404 status.name = new_status.name db.session.commit() return jsonify({'message' : 'Status updated'}), 202

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0

null

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null

0

1

0

3

987de15c788602a643de269378bdb5af47c0f1a0

2,259

py

Python

SimpleCV/tests/DisplayTester.py

nikhilgk/SimpleCV

ee64451c16db1f40b4da221115273020a6a7b01a

[ "BSD-3-Clause" ]

2

2016-04-30T12:23:05.000Z

2022-03-02T00:01:10.000Z

SimpleCV/tests/DisplayTester.py

nikhilgk/SimpleCV

ee64451c16db1f40b4da221115273020a6a7b01a

[ "BSD-3-Clause" ]

null

SimpleCV/tests/DisplayTester.py

nikhilgk/SimpleCV

ee64451c16db1f40b4da221115273020a6a7b01a

[ "BSD-3-Clause" ]

null

import time from SimpleCV import * from SimpleCV.Display import Display, pg w = 400 h = 300 t=1 display = Display(resolution = (w,h)) #create a new display to draw images on img = Image('../sampleimages/aerospace.jpg') img = img.scale(800,600) img2 = img.scale(w,h) smallWbigH = img.scale(100,400) smallHbigW = img2.scale(500,100) smallW = img2.scale(100,h) smallH = img2.scale(w,100) small = img2.scale(99,23) big = img2.scale(555,432) foo = "Image:"+str((img.width,img.height)) print(foo) print('Image should scale clean') display.writeFrame(img) time.sleep(t) foo = "Image:"+str((img2.width,img2.height)) print(foo) print('Image should scale clean') display.writeFrame(img2) time.sleep(t) foo = "Image:"+str((smallWbigH.width,smallWbigH.height)) print(foo) display.writeFrame(smallWbigH) time.sleep(t) foo = "Image:"+str((smallHbigW.width,smallHbigW.height)) print(foo) display.writeFrame(smallHbigW) time.sleep(t) foo = "Image:"+str((smallW.width,smallW.height)) print(foo) display.writeFrame(smallW) time.sleep(t) foo = "Image:"+str((smallH.width,smallH.height)) print(foo) display.writeFrame(smallH) time.sleep(t) foo = "Image:"+str((small.width,small.height)) print(foo) display.writeFrame(small) time.sleep(t) foo = "Image:"+str((big.width,big.height)) print(foo) display.writeFrame(big) time.sleep(t) foo = "Crop Image:"+str((img.width,img.height)) print(foo) display.writeFrame(img, fit=False) time.sleep(t) foo = "Crop Image:"+str((img2.width,img2.height)) print(foo) display.writeFrame(img2, fit=False) time.sleep(t) foo = "Crop Image:"+str((smallWbigH.width,smallWbigH.height)) print(foo) display.writeFrame(smallWbigH, fit=False) time.sleep(t) foo = "Crop Image:"+str((smallHbigW.width,smallHbigW.height)) print(foo) display.writeFrame(smallHbigW, fit=False) time.sleep(t) foo = "Crop Image:"+str((smallW.width,smallW.height)) print(foo) display.writeFrame(smallW, fit=False) time.sleep(t) foo = "Crop Image:"+str((smallH.width,smallH.height)) print(foo) display.writeFrame(smallH, fit=False) time.sleep(t) foo = "Crop Image:"+str((small.width,small.height)) print(foo) display.writeFrame(small, fit=False) time.sleep(t) foo = "Crop Image:"+str((big.width,big.height)) print(foo) display.writeFrame(big, fit=False) time.sleep(t)

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null

0

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null

0

3

98aa429642c9bfeff4ee8a19c9d429a407cad0fd

559

py

Python

dns_shark/errors/dns_refused_error.py

jmiiller/dns_shark

80ee4c7ec32fc3fec202e5142cf745d432770947

[ "MIT" ]

3

2020-01-21T20:32:35.000Z

2020-08-01T07:14:55.000Z

dns_shark/errors/dns_refused_error.py

jmiiller/dns_shark

80ee4c7ec32fc3fec202e5142cf745d432770947

[ "MIT" ]

4

2020-01-20T01:16:39.000Z

2020-01-20T01:34:27.000Z

dns_shark/errors/dns_refused_error.py

jmiiller/dns_shark

80ee4c7ec32fc3fec202e5142cf745d432770947

[ "MIT" ]

null

from dns_shark.errors.dns_shark_error import DNSSharkError class DNSRefusedError(DNSSharkError): """ An error that indicates an rcode of 5 was returned by a dns message. 'Refused - The name server refuses to perform the specified operation for policy reasons. For example, a name server may not wish to provide the information to the particular requester, or a name server may not wish to perform a particular operation (e.g., zone transfer) for particular data.' see https://tools.ietf.org/rfc/rfc1035.txt for more info. """

39.928571

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1

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3

7f5c908d10f8ff7c172832a0c9aad1b644569501

631

py

Python

src/model/utils.py

ahamza1/instance-segmentation-mask-rcnn

b4be9dfcfeea5e56f0923bb2500b56b36cfdbd77

[ "MIT" ]

null

src/model/utils.py

ahamza1/instance-segmentation-mask-rcnn

b4be9dfcfeea5e56f0923bb2500b56b36cfdbd77

[ "MIT" ]

1

2021-09-07T18:16:54.000Z

src/model/utils.py

ahamza1/instance-segmentation-mask-rcnn

b4be9dfcfeea5e56f0923bb2500b56b36cfdbd77

[ "MIT" ]

null

import argparse def get_args(): ap = argparse.ArgumentParser() ap.add_argument("-d", "--data", required=True) ap.add_argument("-l", "--labels", required=True) ap.add_argument("-w", "--weights", required=False) args = vars(ap.parse_args()) return args["data"], args["labels"], args["weights"] def get_args_inference(): ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True) ap.add_argument("-l", "--labels", required=True) ap.add_argument("-w", "--weights", required=True) args = vars(ap.parse_args()) return args["image"], args["labels"], args["weights"]

31.55

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1

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null

0

3

7f6504d862774e895b590da3b392c2330d3d150a

883

py

Python

framework/transactions/utils.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

1

2015-10-02T18:35:53.000Z

framework/transactions/utils.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

13

2020-03-24T15:29:41.000Z

2022-03-11T23:15:28.000Z

framework/transactions/utils.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from flask import make_response from framework.exceptions import HTTPError from framework.routing import JSONRenderer, render_mako_string from website.util import is_json_request def get_error_message(error): """Retrieve error message from error, if available. """ try: return error.args[0] except IndexError: return '' def handle_error(code): """Display an error thrown outside a routed view function. :param int code: Error status code :return: Flask `Response` object """ # TODO: Remove circular import from website.routes import OsfWebRenderer json_renderer = JSONRenderer() web_renderer = OsfWebRenderer('', render_mako_string) error = HTTPError(code) renderer = json_renderer if is_json_request() else web_renderer return make_response(renderer.handle_error(error))

24.527778

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0.051696

0

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1

0

1

0

3

7f68f45294bdba63c039e75b3f968c36731a619a

5,937

py

Python

tests/test_avl.py

Anirban166/tstl

73dac02f084b10e1bf2f172a5d1306bb5fbd7f7e

[ "Apache-2.0" ]

90

2015-04-07T10:26:53.000Z

2022-03-07T15:14:57.000Z

tests/test_avl.py

Anirban166/tstl

73dac02f084b10e1bf2f172a5d1306bb5fbd7f7e

[ "Apache-2.0" ]

14

2015-10-13T16:25:59.000Z

2021-01-21T18:31:03.000Z

tests/test_avl.py

Anirban166/tstl

73dac02f084b10e1bf2f172a5d1306bb5fbd7f7e

[ "Apache-2.0" ]

32

2015-04-07T10:41:29.000Z

2022-02-26T05:17:28.000Z

from __future__ import print_function import os import subprocess import glob from unittest import TestCase class TestAVL(TestCase): def setUp(self): os.chdir("examples/AVL") def tearDown(self): os.chdir("../..") def test_AVL(self): if (os.getenv("TRAVIS") == "TRUE") and (os.getenv("TASK") != "AVL"): return dnull = open(os.devnull, 'w') r = subprocess.call(["tstl", "avlbuggy.tstl"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_rt", "--noCover", "--output", ".avltest.test", "--silentSUT"]) self.assertEqual(r, 255) r = subprocess.call( ["tstl_rt", "--output", ".avltest.test", "--silentSUT", "--multiple", "--quickTests", "--timeout", "45"], stdout=dnull, stderr=dnull) self.assertEqual(r, 255) self.assertNotEqual(len(glob.glob("quick.*.test")), 0) r = subprocess.call(["tstl_replay", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call( ["tstl_reduce", ".avltest.test", ".avltest.norm.test"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_replay", ".avltest.norm.test", "--verbose"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call( ["tstl_reduce", ".avltest.test", ".avltest.keepnorm.test", "--keepLast"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_replay", ".avltest.keepnorm.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call( ["tstl_reduce", ".avltest.full.test", ".avltest.ddnorm.test", "--ddmin"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_replay", ".avltest.ddnorm.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call(["tstl_generalize", ".avltest.norm.test"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_standalone", ".avltest.norm.test", ".avltest.norm.py"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["python", ".avltest.norm.py"], stdout=dnull, stderr=dnull) self.assertEqual(r, 1) r = subprocess.call( ["tstl_rt", "--swarm", "--output", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call(["tstl_rt", "--exploit", "0.8", "--Pmutate", "0.8", "--output", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call(["tstl_rt", "--multiple", "--timeout", "20", "--output", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call(["tstl_rt", "--multiple", "--timeout", "20", "--noCover", "--normalize", "--output", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call( ["tstl_regress .avltest*"], shell=True, stdout=dnull) self.assertEqual(r, 255) r = subprocess.call( ["tstl_rt", "--timeout", "20", "--noCover", "--generateLOC", ".avltest.loc", "--uncaught", "--noCheck"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_rt", "--timeout", "20", "--biasLOC", ".avltest.loc", "--multiple", "--output", ".avltest.test"], stdout=dnull) self.assertEqual(r, 255) r = subprocess.call(["tstl_triage", ".avltest*"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["tstl", "avlnew.tstl"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["tstl_rt", "--timeout", "20"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_rt", "--timeout", "20", "--noCover"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_rt", "--timeout", "20", "--swarm"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["tstl_rt", "--timeout", "20", "--exploit", "0.8", "--Pmutate", "0.8", "--trackMaxCoverage", ".avltest.maxcov.test"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["tstl_standalone", ".avltest.maxcov.test", ".avltest.maxcov.py", "--regression", "--verbose"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call(["python", ".avltest.maxcov.py"], stdout=dnull) self.assertEqual(r, 0) r = subprocess.call( ["tstl_regress .avltest*"], shell=True, stdout=dnull) self.assertEqual(r, 0) for f in glob.glob(".avltest*"): os.remove(f) os.remove("coverage.out")

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7f7b2058eb8418cc5265706ff8f42738c36b44a1

77

py

Python

data/studio21_generated/interview/0269/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/0269/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/0269/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

class Solution: def kLengthApart(self, nums: List[int], k: int) -> bool:

25.666667

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0.662338

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null

0

1

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3

7f822ce131a341c7f102ca63d584a64ec1b779c0

843

py

Python

tests/bench/test_MComp.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

377

2016-10-13T20:52:44.000Z

2022-03-29T18:04:14.000Z

tests/bench/test_MComp.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

160

2016-10-13T16:11:53.000Z

2022-03-28T04:21:34.000Z

tests/bench/test_MComp.py

jmabry/pyaf

afbc15a851a2445a7824bf255af612dc429265af

[ "BSD-3-Clause" ]

63

2017-03-09T14:51:18.000Z

2022-03-27T20:52:57.000Z

import pyaf.Bench.TS_datasets as tsds import pyaf.Bench.MComp as mcomp #tester1 = mcomp.cMComp_Tester(tsds.load_M1_comp()); #tester1.testSignals('') #tester1.testAllSignals() #tester2 = mcomp.cMComp_Tester(tsds.load_M2_comp()); #tester1.testSignals('') #tester2.testAllSignals() #tester3 = mcomp.cMComp_Tester(tsds.load_M3_Y_comp()); #tester1.testSignals('') #tester3.testAllSignals() #tester4 = mcomp.cMComp_Tester(tsds.load_M3_Q_comp()); #tester1.testSignals('') #tester4.testAllSignals() #tester5 = mcomp.cMComp_Tester(tsds.load_M3_M_comp()); #tester1.testSignals('') #tester5.testAllSignals() #tester6 = mcomp.cMComp_Tester(tsds.load_M3_Other_comp()); #tester1.testSignals('') #tester6.testAllSignals() tester7 = mcomp.cMComp_Tester(tsds.load_M4_comp("FINANCE") , "M4COMP"); tester7.testSignals('FIN1') # tester7.testAllSignals()

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7f83beb5e4a4d9a75218a8462a09d0d2a7efa122

2,583

py

Python

python/ray/autoscaler/_private/readonly/node_provider.py

linyiyue/ray

90d2456ec70270a1f894ec3ef6f3004533859e03

[ "Apache-2.0" ]

21,382

2016-09-26T23:12:52.000Z

2022-03-31T21:47:45.000Z

python/ray/autoscaler/_private/readonly/node_provider.py

linyiyue/ray

90d2456ec70270a1f894ec3ef6f3004533859e03

[ "Apache-2.0" ]

19,689

2016-09-17T08:21:25.000Z

2022-03-31T23:59:30.000Z

python/ray/autoscaler/_private/readonly/node_provider.py

gramhagen/ray

c18caa4db36d466718bdbcb2229aa0b2dc03da1f

[ "Apache-2.0" ]

4,114

2016-09-23T18:54:01.000Z

2022-03-31T15:07:32.000Z

from typing import Tuple, List from ray.autoscaler.node_provider import NodeProvider from ray.autoscaler.tags import (TAG_RAY_NODE_KIND, NODE_KIND_HEAD, TAG_RAY_USER_NODE_TYPE, TAG_RAY_NODE_NAME, TAG_RAY_NODE_STATUS, STATUS_UP_TO_DATE) from ray.autoscaler._private.util import format_readonly_node_type class ReadOnlyNodeProvider(NodeProvider): """A node provider that merely reports the current cluster state. This is used for laptop mode / manual cluster setup modes, in order to provide status reporting in the same way for users.""" def __init__(self, provider_config, cluster_name): NodeProvider.__init__(self, provider_config, cluster_name) self.nodes = {} def is_readonly(self): return True def _set_nodes(self, nodes: List[Tuple[str, str]]): """Update the set of nodes in the cluster. Args: nodes: List of (node_id, node_manager_address) tuples. """ new_nodes = {} for node_id, node_manager_address in nodes: # We make up a fake node type for each node (since each node # could have its own unique configuration). new_nodes[node_id] = { # Keep prefix in sync with node config gen in monitor.py "node_type": format_readonly_node_type(node_id), "ip": node_manager_address, } self.nodes = new_nodes def non_terminated_nodes(self, tag_filters): return list(self.nodes.keys()) def is_running(self, node_id): return node_id in self.nodes def is_terminated(self, node_id): return node_id not in self.nodes def node_tags(self, node_id): tags = { TAG_RAY_NODE_KIND: NODE_KIND_HEAD, TAG_RAY_USER_NODE_TYPE: self.nodes[node_id]["node_type"], TAG_RAY_NODE_NAME: node_id, TAG_RAY_NODE_STATUS: STATUS_UP_TO_DATE } return tags def external_ip(self, node_id): return node_id def internal_ip(self, node_id): return node_id def set_node_tags(self, node_id, tags): raise AssertionError("Readonly node provider cannot be updated") def create_node(self, node_config, tags, count): raise AssertionError("Readonly node provider cannot be updated") def terminate_node(self, node_id): raise AssertionError("Readonly node provider cannot be updated") @staticmethod def bootstrap_config(cluster_config): return cluster_config

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0

null

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null

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7f998496cbf16bedaf0905ee189350d501e19416

2,045

py

Python

openstreetmap-scraper/venv/lib/python3.7/site-packages/OSMPythonTools/api.py

espoo-urban-planning/urbanplanningGAN

e921211b7a9f9f02d16e8f14ea29bf81139886c2

[ "MIT" ]

null

openstreetmap-scraper/venv/lib/python3.7/site-packages/OSMPythonTools/api.py

espoo-urban-planning/urbanplanningGAN

e921211b7a9f9f02d16e8f14ea29bf81139886c2

[ "MIT" ]

null

openstreetmap-scraper/venv/lib/python3.7/site-packages/OSMPythonTools/api.py

espoo-urban-planning/urbanplanningGAN

e921211b7a9f9f02d16e8f14ea29bf81139886c2

[ "MIT" ]

null

from bs4 import BeautifulSoup from OSMPythonTools.element import Element from OSMPythonTools.internal.cacheObject import CacheObject def _raiseException(prefix, msg): sys.tracebacklimit = None raise(Exception('[OSMPythonTools.' + prefix + '] ' + msg)) class Api(CacheObject): def __init__(self, endpoint='http://www.openstreetmap.org/api/0.6/', **kwargs): super().__init__('api', endpoint, jsonResult=False, **kwargs) def _queryString(self, query, params={}): return (query, query, params) def _queryRequest(self, endpoint, queryString, params={}): return endpoint + queryString def _rawToResult(self, data, queryString): return ApiResult(data, queryString) class ApiResult(Element): def __init__(self, xml, queryString): self._isValid = (xml != {} and xml is not None) self._xml = xml self._soup = None soupElement = None if self._isValid: self._soup = BeautifulSoup(xml, 'xml') if len(self._soup.find_all('node')) > 0: soupElement = self._soup.node if len(self._soup.find_all('way')) > 0: soupElement = self._soup.way if len(self._soup.find_all('relation')) > 0: soupElement = self._soup.relation super().__init__(soup=soupElement) self._queryString = queryString def isValid(self): return self._isValid def toXML(self): return self._xml def queryString(self): return self._queryString def __get(self, prop): return self._soup.attrs[prop] if self._isValid and prop in self._soup.attrs else None ### general information def version(self): return self.__get('version') def generator(self): return self.__get('generator') def copyright(self): return self.__get('copyright') def attribution(self): return self.__get('attribution') def license(self): return self.__get('license')

32.460317

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0.626895

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5.438053

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0.091131

0.069162

0.04882

0

0.003966

0.260147

2,045

62

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32.983871

0.808328

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0

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0

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0.306122

false

0

0.061224

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0

null

0

null

0

1

0

1

0

3

7fa9fdfc5add3e476b8eacc4fb5602386f476d00

1,680

py

Python

ansys/dpf/core/operators/utility/__init__.py

jfthuong/pydpf-core

bf2895ebc546e0004f759289bfc9a23196559ac3

[ "MIT" ]

18

2021-10-16T10:38:29.000Z

2022-03-29T11:26:42.000Z

ansys/dpf/core/operators/utility/__init__.py

jfthuong/pydpf-core

bf2895ebc546e0004f759289bfc9a23196559ac3

[ "MIT" ]

79

2021-10-11T23:18:54.000Z

2022-03-29T14:53:14.000Z

ansys/dpf/core/operators/utility/__init__.py

jfthuong/pydpf-core

bf2895ebc546e0004f759289bfc9a23196559ac3

[ "MIT" ]

5

2021-11-29T18:35:37.000Z

2022-03-16T16:49:21.000Z

from .merge_result_infos import merge_result_infos from .field_to_fc import field_to_fc from .html_doc import html_doc from .unitary_field import unitary_field from .extract_field import extract_field from .bind_support import bind_support from .scalars_to_field import scalars_to_field from .change_location import change_location from .strain_from_voigt import strain_from_voigt from .set_property import set_property from .forward_field import forward_field from .forward_fields_container import forward_fields_container from .forward_meshes_container import forward_meshes_container from .forward import forward from .txt_file_to_dpf import txt_file_to_dpf from .bind_support_fc import bind_support_fc from .default_value import default_value from .extract_time_freq import extract_time_freq from .python_generator import python_generator from .make_overall import make_overall from .merge_fields_containers import merge_fields_containers from .merge_scopings import merge_scopings from .merge_materials import merge_materials from .merge_property_fields import merge_property_fields from .remote_workflow_instantiate import remote_workflow_instantiate from .remote_operator_instantiate import remote_operator_instantiate from .merge_fields_by_label import merge_fields_by_label from .merge_scopings_containers import merge_scopings_containers from .merge_meshes import merge_meshes from .merge_time_freq_supports import merge_time_freq_supports from .merge_fields import merge_fields from .merge_supports import merge_supports from .merge_meshes_containers import merge_meshes_containers from .change_shell_layers import change_shell_layers

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0

0.10119

1,680

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null

0

1

0

1

0

1

0

3

7fb6bd7ad92ceab221631aaebad8f831b543d2c5

3,095

py

Python

python/cugraph/ktruss/ktruss_max.py

ogreen/cugraph

d94ab29f14e6212a0c8bb5ec5fbe9e300cd57594

[ "Apache-2.0" ]

null

python/cugraph/ktruss/ktruss_max.py

ogreen/cugraph

d94ab29f14e6212a0c8bb5ec5fbe9e300cd57594

[ "Apache-2.0" ]

null

python/cugraph/ktruss/ktruss_max.py

ogreen/cugraph

d94ab29f14e6212a0c8bb5ec5fbe9e300cd57594

[ "Apache-2.0" ]

null

# Copyright (c) 2019, NVIDIA CORPORATION. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from cugraph.ktruss import ktruss_max_wrapper def ktruss_max(G): """ Finds the maximal k-truss of a graph. The k-truss of a graph is subgraph where each edge is part of at least (k−2) triangles. The maximal k-truss in a graph, denoted by k=k_max is the largest k-truss in the graph where the set of satisfying edges is not empty. k-trusses are used for finding tighlty knit groups of vertices in a graph. A k-truss is a relaxation of a k-clique in the graph and was define in [1]. Finding cliques is computationally demanding and finding the maximal k-clique is known to be NP-Hard. In contrast, finding a k-truss is computationally tractable as its key building block, namely triangle counting counting, can be executed in polnymomial time. Typically, it takes many iterations of triangle counting to find the k-truss of a graph. Yet these iterations operate on a weakly monotonically shrinking graph. Therefore, finding the k-truss of a graph can be done in a fairly reasonable amount of time. The solution in cuGraph is based on a GPU algorithm first shown in [2] and uses the triangle counting algoritm from [3]. [1] Cohen, J., "Trusses: Cohesive subgraphs for social network analysis" National security agency technical report, 2008 [2] O. Green, J. Fox, E. Kim, F. Busato, et al. “Quickly Finding a Truss in a Haystack” IEEE High Performance Extreme Computing Conference (HPEC), 2017 https://doi.org/10.1109/HPEC.2017.8091038 [3] O. Green, P. Yalamanchili, L.M. Munguia, “Fast Triangle Counting on GPU” Irregular Applications: Architectures and Algorithms (IA3), 2014 Parameters ---------- G : cuGraph.Graph cuGraph graph descriptor with connectivity information. k-Trusses are defined for only undirected graphs as they are defined for undirected triangle in a graph. Returns ------- k_max : int The largest k in the graph s.t. a non-empty k-truss in the graph exists. Examples -------- >>> M = cudf.read_csv('datasets/karate.csv', delimiter=' ', >>> dtype=['int32', 'int32', 'float32'], header=None) >>> sources = cudf.Series(M['0']) >>> destinations = cudf.Series(M['1']) >>> G = cugraph.Graph() >>> G.add_edge_list(sources, destinations, None) >>> k_max = cugraph.ktruss_max(G) """ k_max = ktruss_max_wrapper.ktruss_max(G) return k_max

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3

f68a6c3b04e97ce3df8e57a9f74367abf54ae284

2,445

py

Python

LDERPdjango/login/models.py

Ignoramuss/LDERP

2524eb2a4c73a079a5d8f563c45de23cfe7836f6

[ "Apache-2.0" ]

3

2017-06-09T09:22:17.000Z

2017-06-14T03:42:55.000Z

LDERPdjango/login/models.py

Ignoramuss/LDERP

2524eb2a4c73a079a5d8f563c45de23cfe7836f6

[ "Apache-2.0" ]

2

2017-06-14T07:24:47.000Z

2017-06-14T10:50:57.000Z

LDERPdjango/login/models.py

Ignoramuss/LDERP

2524eb2a4c73a079a5d8f563c45de23cfe7836f6

[ "Apache-2.0" ]

null

from django.db import models from datetime import date # Create your models here. class LanguageDisability(models.Model): disability_name = models.CharField(max_length=200) def __str__(self): return self.disability_name # student = models.ForeignKey(StudentInfo, on_delete=models.CASCADE) class MathematicalDisability(models.Model): disability_name = models.CharField(max_length=200) def __str__(self): return self.disability_name # student = models.ForeignKey(StudentInfo, on_delete=models.CASCADE) class ParentalMetric(models.Model): metric_name = models.CharField(max_length=200) def __str__(self): return self.metric_name #Model of the students class StudentInfo(models.Model): #Personal information stud_name = models.CharField(max_length = 200) stud_school = models.CharField(max_length = 200) stud_standard = models.CharField(max_length = 30) stud_div = models.CharField(max_length = 30) date_of_fill = models.DateField() date_of_birth = models.DateField() #Guardian information #Father father_name = models.CharField(max_length=200) father_contact = models.CharField(max_length=10) father_email = models.EmailField(max_length = 200) father_education = models.CharField(max_length=200) father_occupation = models.CharField(max_length=200) #Mother mother_name = models.CharField(max_length=200) mother_contact = models.CharField(max_length=10) mother_email = models.EmailField(max_length = 200) mother_education = models.CharField(max_length=200) mother_occupation = models.CharField(max_length=200) #Academic info stud_grades = models.TextField() language_disabilities = models.ManyToManyField(LanguageDisability) mathematical_disabilities = models.ManyToManyField(MathematicalDisability) # parent_awareness_scores = models.OneToOneField(ParentAwarenessScore) def __str__(self): return self.stud_name def get_language_disabilities(self): return ", ".join([ld.disability_name for ld in self.language_disabilities.all()]) def get_mathematical_disabilities(self): return ", ".join([md.disability_name for md in self.mathematical_disabilities.all()]) class ParentalMetricScore(models.Model): metric_type = models.ForeignKey(ParentalMetric) metric_score= models.IntegerField() student = models.ForeignKey(StudentInfo, null=True)

37.615385

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null

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f69fe25a771ef82201f3ce3b2cb530a64e86f1af

295

py

Python

src/vivarium/exceptions.py

ihmeuw/vivarium

77393d2e84ff2351c926f65b33272b7225cf9628

[ "BSD-3-Clause" ]

41

2017-07-14T03:39:06.000Z

2022-03-20T05:36:33.000Z

src/vivarium/exceptions.py

ihmeuw/vivarium

77393d2e84ff2351c926f65b33272b7225cf9628

[ "BSD-3-Clause" ]

26

2017-08-08T22:13:44.000Z

2021-08-18T00:14:54.000Z

src/vivarium/exceptions.py

ihmeuw/vivarium

77393d2e84ff2351c926f65b33272b7225cf9628

[ "BSD-3-Clause" ]

8

2017-08-03T17:15:39.000Z

2021-09-30T21:57:50.000Z

""" ========== Exceptions ========== Module containing framework-wide exception definitions. Exceptions for particular subsystems are defined in their respective modules. """ class VivariumError(Exception): """Generic exception raised for errors in ``vivarium`` simulations.""" pass

19.666667

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0.708475

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295

7.206897

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0

0.145763

295

14

75

21.071429

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null

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null

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0

3

f6cc4e2375a4556416ea9043cc4eb25beda4e1bd

111

py

Python

Codewars/8kyu/super-duper-easy/Python/solution1.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

7

2017-09-20T16:40:39.000Z

2021-08-31T18:15:08.000Z

Codewars/8kyu/super-duper-easy/Python/solution1.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

Codewars/8kyu/super-duper-easy/Python/solution1.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

# Python - 3.4.3 def problem(a): try: return float(a) * 50 + 6 except: return 'Error'

13.875

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0.495495

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111

3.4375

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111

7

33

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1

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null

0

1

0

null

0

1

0

3

f6cc6c0f42834cc66f02e39d068d2c7f6ecd17bd

110

py

Python

Notification/Desktop Notification.py

Amara-Manikanta/Python-Automations

8f7d2eb7a0cd145c13f329920204ed3f311a4989

[ "MIT" ]

null

Notification/Desktop Notification.py

Amara-Manikanta/Python-Automations

8f7d2eb7a0cd145c13f329920204ed3f311a4989

[ "MIT" ]

null

Notification/Desktop Notification.py

Amara-Manikanta/Python-Automations

8f7d2eb7a0cd145c13f329920204ed3f311a4989

[ "MIT" ]

null

import win10toast toaster=win10toast.ToastNotifier() toaster.show_toast('python','Hellow Mani',duration = 10)

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110

6.769231

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0.058252

0.063636

110

4

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null

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f6d5571e4a9320bd8961ea32e4d8f734a7fae9ce

370

py

Python

tag/timer.py

funge/ai4games

b72be3648fa0da611b999aa01aec8560728bcdd7

[ "MIT" ]

1

2020-01-11T18:53:53.000Z

tag/timer.py

funge/ai4games

b72be3648fa0da611b999aa01aec8560728bcdd7

[ "MIT" ]

null

tag/timer.py

funge/ai4games

b72be3648fa0da611b999aa01aec8560728bcdd7

[ "MIT" ]

1

2019-08-27T17:24:27.000Z

# Source code distributed under the Copyright (c) 2008, John David Funge # Original author: John David Funge (www.jfunge.com) # # Licensed under the Academic Free License version 3.0 # (for details see LICENSE.txt in this directory). import pygame # time is measured in milliseconds ticksPerSec = 1000.0 def getTime(): return pygame.time.get_ticks()/ticksPerSec

26.428571

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370

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0.035484

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370

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null

0

null

0

1

0

1

0

3

f6eb502e77829b816e2a8d4979b70e96248a3bf9

144

py

Python

django_test/meuapp/apps.py

fmhiga/Django_study

92193b18bb03b4deb90187b9fec0ef6e66dbd00b

[ "MIT" ]

1

2021-08-19T02:38:47.000Z

p1/meuapp/apps.py

mentoriacompartilhada/helenamagaldi-v0

d26e5b4ae887382b02c00092c2487437bc9ffb78

[ "MIT" ]

null

p1/meuapp/apps.py

mentoriacompartilhada/helenamagaldi-v0

d26e5b4ae887382b02c00092c2487437bc9ffb78

[ "MIT" ]

null

from django.apps import AppConfig class MeuappConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'meuapp'

20.571429

56

0.756944

17

144

6.294118

0.882353

0

0.152778

144

6

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0

1

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3