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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a51038591bd238a6d8f04230ce9c6a8b5c0876c7 | 148 | py | Python | bs/builders/clike_builder.py | chasinglogic/bs | ea91630d9050e261e8f3f3f29c0c5af43725bc6e | [
"Apache-2.0"
] | 1 | 2020-02-13T17:46:51.000Z | 2020-02-13T17:46:51.000Z | bs/builders/clike_builder.py | chasinglogic/bs | ea91630d9050e261e8f3f3f29c0c5af43725bc6e | [
"Apache-2.0"
] | null | null | null | bs/builders/clike_builder.py | chasinglogic/bs | ea91630d9050e261e8f3f3f29c0c5af43725bc6e | [
"Apache-2.0"
] | null | null | null | from bs.builder import Builder
class ClikeBuilder(Builder):
"""A subclass of Builder that supports the link_with and system_lib arguments."""
| 24.666667 | 85 | 0.77027 | 21 | 148 | 5.333333 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.155405 | 148 | 5 | 86 | 29.6 | 0.896 | 0.506757 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
eb8eadc48f666d8b23af757cd587f1e8bb87d341 | 224 | py | Python | podcaststore_api/models/__init__.py | viniarck/podcaststore-django | 90316ffb18793b089291a0e28ac3ee2bb5e458cb | [
"Apache-2.0"
] | null | null | null | podcaststore_api/models/__init__.py | viniarck/podcaststore-django | 90316ffb18793b089291a0e28ac3ee2bb5e458cb | [
"Apache-2.0"
] | 3 | 2019-09-22T17:58:27.000Z | 2019-09-22T18:20:20.000Z | podcaststore_api/models/__init__.py | viniarck/podcaststore-django | 90316ffb18793b089291a0e28ac3ee2bb5e458cb | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from .podcast import Podcast # noqa
from .track import Track # noqa
from .tag import Tag # noqa
from .reaction import Reaction # noqa
from .download import Download # noqa
| 24.888889 | 38 | 0.700893 | 32 | 224 | 4.90625 | 0.46875 | 0.203822 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005525 | 0.191964 | 224 | 8 | 39 | 28 | 0.861878 | 0.299107 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
69040d3f321c40a56d8daf12eb2a58fc52866e41 | 72 | py | Python | src/events/__init__.py | cornzz/robolab-tud-spring18 | 958915181fc8cab9a3567d9b2670be8a1b704488 | [
"MIT"
] | null | null | null | src/events/__init__.py | cornzz/robolab-tud-spring18 | 958915181fc8cab9a3567d9b2670be8a1b704488 | [
"MIT"
] | null | null | null | src/events/__init__.py | cornzz/robolab-tud-spring18 | 958915181fc8cab9a3567d9b2670be8a1b704488 | [
"MIT"
] | null | null | null | from . import EventList, EventRegistry, Event, EventHandler, EventNames
| 36 | 71 | 0.819444 | 7 | 72 | 8.428571 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 72 | 1 | 72 | 72 | 0.921875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
69198ba1a39bb581abb4560034edb61c5f5536a7 | 128 | py | Python | trick_sims/Cannon/SIM_cannon_numeric/RUN_test/input.py | TheCivilAge/RogueKitten | 0b9fbe17624e77752f6160463c6d8aa5a781aad1 | [
"NASA-1.3"
] | null | null | null | trick_sims/Cannon/SIM_cannon_numeric/RUN_test/input.py | TheCivilAge/RogueKitten | 0b9fbe17624e77752f6160463c6d8aa5a781aad1 | [
"NASA-1.3"
] | null | null | null | trick_sims/Cannon/SIM_cannon_numeric/RUN_test/input.py | TheCivilAge/RogueKitten | 0b9fbe17624e77752f6160463c6d8aa5a781aad1 | [
"NASA-1.3"
] | null | null | null |
execfile("Modified_data/realtime.py")
execfile("Modified_data/cannon.dr")
dyn_integloop.getIntegrator(trick.Runge_Kutta_4, 5)
| 21.333333 | 51 | 0.820313 | 18 | 128 | 5.555556 | 0.833333 | 0.32 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016393 | 0.046875 | 128 | 5 | 52 | 25.6 | 0.803279 | 0 | 0 | 0 | 0 | 0 | 0.377953 | 0.377953 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
15cdc4c0c6057aa268d02bfcd2940ceb295483d6 | 27,937 | py | Python | deep-conus/09_dlmodel_interpretor.py | mariajmolina/deep-conus | 33f9e2af3e39d9f03c7f9b8388fe9cd29224b624 | [
"MIT"
] | 5 | 2020-09-28T16:48:52.000Z | 2021-03-19T07:54:27.000Z | deep-conus/09_dlmodel_interpretor.py | mariajmolina/deep-conus | 33f9e2af3e39d9f03c7f9b8388fe9cd29224b624 | [
"MIT"
] | null | null | null | deep-conus/09_dlmodel_interpretor.py | mariajmolina/deep-conus | 33f9e2af3e39d9f03c7f9b8388fe9cd29224b624 | [
"MIT"
] | 2 | 2021-03-08T21:58:44.000Z | 2021-03-09T06:50:38.000Z | import keras
import tensorflow as tf
#from keras import backend as K
from tensorflow.keras import backend as K
from keras.models import load_model
from scipy.ndimage import gaussian_filter
import xarray as xr
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.pyplot import cm
from metpy.plots import colortables
import matplotlib.colors as colors
tf.compat.v1.disable_eager_execution()
class InterpretDLModel:
"""Class instantiation of InterpretDLModel:
Here we load the variable data for interpretation of the trained deep convolutional neural network.
Attributes:
climate (str): Whether analyzing ``current`` or ``future`` climate simulation.
variable (str): Variable name for saliency map output. Options include:
``EU1``, ``EU3``, ``EU5``, ``EU7``,
``EV1``, ``EV3``, ``EV5``, ``EV7``,
``TK1``, ``TK3``, ``TK5``, ``TK7``,
``QVAPOR1``, ``QVAPOR3``, ``QVAPOR5``, ``QVAPOR7``,
``W1``, ``W3``, ``W5``, ``W7``,
``P1``, ``P3``, ``P5``, ``P7``,
``WMAX``, ``DBZ``,``CTT``,``UH25``, and``UH03``.
dist_directory (str): The directory path where the produced files were saved.
model_directory (str): Directory where the deep learning model is saved.
model_num (str): The number of the model as it was saved.
comp_directory (str): Directory where the composite files were saved.
mask (boolean): Whether to train using the masked data or the non-masked data. Defaults to ``False``.
mask_train (boolean): Whether to train using masked state variable data. Defaults to ``False``. Will override ``mask`` to ``True``.
unbalanced (boolean): Whether training data will be artificially balanced (``False``) or left unbalanced (``True``). Defaults to ``False``.
isotonic (boolean): Whether model has an isotonic regression applied to output. Defaults to ``False``.
random_choice (int): The integer the respective ``random`` method file was saved as. Defaults to ``None``.
outliers (boolean): Whether evaluating outlier storms. Defaults to ``True``.
Raises:
Exceptions: Checks whether correct values were input for ``climate`` and ``method``.
"""
def __init__(self, climate, variable, dist_directory, model_directory, model_num, comp_directory,
mask=False, mask_train=False, unbalanced=False, isotonic=False,
random_choice=None, outliers=False):
if climate!='current' and climate!='future':
raise Exception("Please enter ``current`` or ``future`` as string for climate period selection.")
else:
self.climate=climate
self.method='random'
self.variable=variable
self.dist_directory=dist_directory
self.model_directory=model_directory
self.model_num=model_num
self.comp_directory=comp_directory
self.mask=mask
if not self.mask:
self.mask_str='nomask'
if self.mask:
self.mask_str='mask'
self.mask_train=mask_train
self.unbalanced=unbalanced
self.isotonic=isotonic
self.random_choice=random_choice
self.outliers = outliers
def variable_translate(self):
"""Variable name for the respective filenames.
Args:
variable (str): The variable to feed into the dictionary.
Returns:
variable (str): The variable name to use for opening saved files.
Raises:
ValueError: If provided variable is not available.
"""
var={ 'EU1':'EU', 'EU3':'EU', 'EU5':'EU', 'EU7':'EU',
'EV1':'EV', 'EV3':'EV', 'EV5':'EV', 'EV7':'EV',
'TK1':'TK', 'TK3':'TK', 'TK5':'TK', 'TK7':'TK',
'QVAPOR1':'QVAPOR', 'QVAPOR3':'QVAPOR', 'QVAPOR5':'QVAPOR', 'QVAPOR7':'QVAPOR',
'WMAX':'MAXW',
'W1':'W', 'W3':'W', 'W5':'W', 'W7':'W',
'P1':'P', 'P3':'P', 'P5':'P', 'P7':'P',
'DBZ':'DBZ',
'CTT':'CTT',
'UH25':'UH25',
'UH03':'UH03',
}
try:
out=var[self.variable]
return out
except:
raise ValueError("Please enter ``TK``, ``EV``, ``EU``, ``QVAPOR``, ``PRESS``, ``W_vert``, ``UH25``, ``UH03``, ``MAXW``, ``CTT``, or ``DBZ`` as variable with height AGL appended (1, 3, 5, or 7).")
def convert_string_height(self):
"""Convert the string variable name's height to integer for indexing mean and standard deviation data.
"""
the_hgt=int(self.variable[-1])
heights=np.array([1,3,5,7])
the_indx=np.where(heights==the_hgt)
return the_indx
def extract_variable_mean_and_std(self):
"""Open the file containing mean and std information for the selected variable.
"""
if not self.unbalanced:
data=xr.open_dataset(
f"/{self.dist_directory}/{self.climate}_{self.variable_translate().lower()}_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(
f"/{self.dist_directory}/{self.climate}_{self.variable_translate().lower()}_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.variable_mean=data.train_mean.values[self.convert_string_height()[0][0]]
self.variable_std=data.train_std.values[self.convert_string_height()[0][0]]
def extract_eu_mean_and_std(self):
"""Open the file containing mean and std information for u winds (earth relative).
"""
if not self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_eu_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_eu_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.eu_mean=data.train_mean.values[self.convert_string_height()[0][0]]
self.eu_std=data.train_std.values[self.convert_string_height()[0][0]]
def extract_ev_mean_and_std(self):
"""Open the file containing mean and std information for v winds (earth relative).
"""
if not self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_ev_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_ev_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.ev_mean=data.train_mean.values[self.convert_string_height()[0][0]]
self.ev_std=data.train_std.values[self.convert_string_height()[0][0]]
def extract_uh03_mean_and_std(self):
"""Open the file containing mean and std information for UH (0-3 km AGL).
"""
if not self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_uh03_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_uh03_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.uh03_mean=data['train_mean'].values[0]
self.uh03_std=data['train_std'].values[0]
def extract_uh25_mean_and_std(self):
"""Open the file containing mean and std information for UH (2-5 km AGL).
"""
if not self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_uh25_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_uh25_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.uh25_mean=data['train_mean'].values[0]
self.uh25_std=data['train_std'].values[0]
def extract_dbz_mean_and_std(self):
"""Open the file containing mean and std information for dBZ (simulated reflectivity).
"""
if not self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_dbz_{self.mask_str}_dldata_traindist.nc")
if self.unbalanced:
data=xr.open_dataset(f"/{self.dist_directory}/{self.climate}_dbz_{self.mask_str}_dldata_traindist_unbalanced.nc")
self.dbz_mean=data['train_mean'].values[0]
self.dbz_std=data['train_std'].values[0]
def extract_model(self):
"""Load the keras model from h5 data set.
"""
loaded_model=load_model(f'{self.model_directory}/model_{self.model_num}_current.h5')
print(loaded_model.summary())
return loaded_model
def extract_variable_and_dbz(self):
"""Open the file containing the test data.
"""
if not self.outliers:
ds = xr.open_dataset(f'{self.comp_directory}/composite_results_{self.mask_str}_model{self.model_num}_{self.method}{self.random_choice}.nc')
if self.outliers:
ds = xr.open_dataset(f'{self.comp_directory}/composite_outresults_{self.mask_str}_model{self.model_num}_{self.method}{self.random_choice}.nc')
return ds
def extract_variable_index(self, data):
"""Find the variable index from the respective test data set.
Args:
data (xarray dataset): Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values==self.variable)[0][0]
def extract_dbz_index(self, data):
"""Find the ``DBZ`` index from the respective test data set.
Args:
data: Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values=='DBZ')[0][0]
def extract_uh03_index(self, data):
"""Find the ``UH03`` index from the respective test data set.
Args:
data: Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values=='UH03')[0][0]
def extract_uh25_index(self, data):
"""Find the ``UH25`` index from the respective test data set.
Args:
data: Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values=='UH25')[0][0]
def extract_EV_index(self, data):
"""Find the ``EV`` (v-wind) index from the respective test data set for the corresponding variable height.
Args:
data: Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values=='EV'+self.variable[-1])[0][0]
def extract_EU_index(self, data):
"""Find the ``EU`` (u-wind) index from the respective test data set for the corresponding variable height.
Args:
data: Dataset opened with ``extract_variable_and_dbz()``.
"""
return np.where(data.coords['features'].values=='EU'+self.variable[-1])[0][0]
def preview_dbz(self, composite_group, input_index, test_data):
"""Preview the testing data ``DBZ`` values to help choose the example for ``saliency_preview``.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): The example's index to preview.
test_data (numpy array): The test data to use for saliency map generation.
"""
levels=[0,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80]
cmap = colortables.get_colortable('NWSReflectivity')
return xr.plot.contourf(test_data[composite_group][input_index, :, :, test.extract_dbz_index(test_data)] * test.dbz_std + test.dbz_mean,
cmap=cmap, levels=levels)
def preview_uh25(self, composite_group, input_index, test_data):
"""Preview the testing data ``UH 2-5 km`` values to help choose the example for ``saliency_preview``.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): The example's index to preview.
test_data (numpy array): The test data to use for saliency map generation.
"""
cmap = plt.cm.get_cmap("Reds")
print(np.nanmax(test_data[composite_group][input_index, :, :, test.extract_uh25_index(test_data)] * test.uh25_std + test.uh25_mean))
return xr.plot.pcolormesh(
test_data[composite_group][input_index, :, :, test.extract_uh25_index(test_data)] * test.uh25_std + test.uh25_mean,
cmap=cmap, vmin=-75, vmax=75)
def grab_dbz(self, composite_group, input_index, test_data):
"""Grab the testing data ``DBZ`` values to help choose the example for ``saliency_preview``.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): The example's index to preview.
test_data (numpy array): The test data to use for saliency map generation.
"""
return test_data[composite_group][input_index, :, :, test.extract_dbz_index(test_data)] * test.dbz_std + test.dbz_mean
def preview_saliency(self, composite_group, input_index, dl_model, test_data):
"""Preview the deep learning model input using saliency maps.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): The example's index to to preview.
dl_model (Keras saved model): The DL model to preview. Layers and activations will be extracted from loaded model.
test_data (numpy array): The test data to use for saliency map generation.
"""
testdata=test_data[composite_group]
fig, axes=plt.subplots(4, 8, figsize=(16, 8), sharex=True, sharey=True)
plt.subplots_adjust(0.02, 0.02, 0.96, 0.94, wspace=0,hspace=0)
for conv_filter, ax in enumerate(axes.ravel()):
print(conv_filter)
out_diff=K.abs(dl_model.layers[-4].output[0, conv_filter] - 1) #dense layer that was added
grad=K.gradients(out_diff, [dl_model.input])[0]
grad/=K.maximum(K.std(grad), K.epsilon())
iterate=K.function([dl_model.input, K.learning_phase()], [out_diff, grad])
input_img_data_neuron_grad=np.zeros((1, 32, 32, 20))
input_img_data_neuron=np.copy(testdata[input_index:input_index+1,:,:,:-6])
out_loss, out_grad=iterate([input_img_data_neuron, 1])
#DBZ
levels=[0,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80]
cmap_dbz = colortables.get_colortable('NWSReflectivity')
ax.contourf(test_data[composite_group][input_index, :, :, self.extract_dbz_index(testdata)] * self.dbz_std + self.dbz_mean,
cmap=cmap_dbz, levels=levels, alpha=0.2)
ax.contour(gaussian_filter(-out_grad[0, :, :, self.extract_variable_index(testdata)], 1),
[-3, -2, -1, 1, 2, 3], vmin=-3, vmax=3, cmap="seismic", linewidths=3.0)
ax.set_xticks([])
ax.set_yticks([])
ax.xaxis.set_ticklabels([])
ax.yaxis.set_ticklabels([])
ax.text(16, 16, conv_filter, fontsize=14)
plt.suptitle("Final Convolution Filter Saliency Maps", fontsize=14, y=0.98)
plt.show()
def preview_inputgrad(self, composite_group, input_index, dl_model, test_data):
"""Preview the deep learning model input using input x gradient maps.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): The example's index to to preview.
dl_model (Keras saved model): The DL model to preview. Layers and activations will be extracted from loaded model.
test_data (numpy array): The test data to use for saliency map generation.
"""
testdata=test_data[composite_group]
fig, axes=plt.subplots(4, 8, figsize=(16, 8), sharex=True, sharey=True)
plt.subplots_adjust(0.02, 0.02, 0.96, 0.94, wspace=0,hspace=0)
for conv_filter, ax in enumerate(axes.ravel()):
print(conv_filter)
out_diff=K.abs(dl_model.layers[-4].output[0, conv_filter] - 1) #dense layer that was added
grad=K.gradients(out_diff, [dl_model.input])[0]
grad/=K.maximum(K.std(grad), K.epsilon())
iterate=K.function([dl_model.input, K.learning_phase()], [out_diff, grad])
input_img_data_neuron_grad=np.zeros((1, 32, 32, 20))
input_img_data_neuron=np.copy(testdata[input_index:input_index+1,:,:,:-6])
out_loss, out_grad=iterate([input_img_data_neuron, 1])
#DBZ
levels=[0,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80]
cmap_dbz = colortables.get_colortable('NWSReflectivity')
ax.contourf(test_data[composite_group][input_index, :, :, self.extract_dbz_index(testdata)] * self.dbz_std + self.dbz_mean,
cmap=cmap_dbz, levels=levels, alpha=0.2)
ax.contour(gaussian_filter(
(test_data[composite_group][input_index,:,:,self.extract_variable_index(testdata)]*(
-out_grad[0, :, :, self.extract_variable_index(testdata)])), 1),
[-3, -2, -1, 1, 2, 3], vmin=-3, vmax=3, cmap="seismic", linewidths=3.0)
ax.set_xticks([])
ax.set_yticks([])
ax.xaxis.set_ticklabels([])
ax.yaxis.set_ticklabels([])
ax.text(16, 16, conv_filter, fontsize=14)
plt.suptitle("Final Convolution Filter Input x Gradient Maps", fontsize=14, y=0.98)
plt.show()
def save_saliency_maps(self, composite_group, input_index, dl_model, test_data):
"""Save the features using chosen indices to generate final images using the next module.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): Index of sample to generate saliency maps for.
dl_model (Keras saved model): The DL model to preview. Layers and activations will be extracted from loaded model.
test_data (numpy array): The test data to use for saliency map generation.
"""
testdata=test_data[composite_group]
for_contours={}
for conv_filter in range(0,32):
out_diff=K.abs(dl_model.layers[-4].output[0, conv_filter] - 1) #dense layer that was added
grad=K.gradients(out_diff, [dl_model.input])[0]
grad/=K.maximum(K.std(grad), K.epsilon())
iterate=K.function([dl_model.input, K.learning_phase()], [out_diff, grad])
input_img_data_neuron_grad=np.zeros((1, 32, 32, 20))
input_img_data_neuron=np.copy(testdata[input_index:input_index+1,:,:,:-6])
out_loss, out_grad=iterate([input_img_data_neuron, 1])
for_contours[conv_filter]=gaussian_filter(-out_grad[0, :, :, self.extract_variable_index(testdata)], 1)
array=[p[1] for p in for_contours.items()]
thecontours=np.asarray(array)
thedbz=test_data[composite_group][input_index, :, :, self.extract_dbz_index(testdata)] * self.dbz_std + self.dbz_mean
theeu=test_data[composite_group][input_index, :, :, self.extract_EU_index(testdata)] * self.eu_std + self.eu_mean
theev=test_data[composite_group][input_index, :, :, self.extract_EV_index(testdata)] * self.ev_std + self.ev_mean
theuh25=test_data[composite_group][input_index, :, :, self.extract_uh25_index(testdata)] * self.uh25_std + self.uh25_mean
theuh03=test_data[composite_group][input_index, :, :, self.extract_uh03_index(testdata)] * self.uh03_std + self.uh03_mean
data=xr.Dataset({
'saliency_maps':(['a','x','y'], thecontours),
'dbz':(['x','y'], thedbz),
'eu':(['x','y'], theeu),
'ev':(['x','y'], theev),
'uh25':(['x','y'], theuh25),
'uh03':(['x','y'], theuh03),
})
data.to_netcdf(
f"{self.comp_directory}/saliency_{self.mask_str}_model{self.model_num}_{self.method}{self.random_choice}_{composite_group}_{str(input_index)}_{self.variable}.nc")
return
def save_inputgrad_maps(self, composite_group, input_index, dl_model, test_data):
"""Save the features using chosen indices to generate final images using the next module.
Args:
composite_group (str): The subset of the test data based on prediction outcome. Choices include true positive ``tp``,
true positive > 99% probability ``tp_99``, false positive ``fp``, false positive > 99% probability
``fp_99``, false negative ``fn``, false negative < 1% probability ``fn_01``, true negative ``tn``,
true negative < 1% probability ``tn_01``.
input_index (int): Index of sample to generate saliency maps for.
dl_model (Keras saved model): The DL model to preview. Layers and activations will be extracted from loaded model.
test_data (numpy array): The test data to use for saliency map generation.
"""
testdata=test_data[composite_group]
for_contours={}
for conv_filter in range(0,32):
out_diff=K.abs(dl_model.layers[-4].output[0, conv_filter] - 1) #dense layer that was added
grad=K.gradients(out_diff, [dl_model.input])[0]
grad/=K.maximum(K.std(grad), K.epsilon())
iterate=K.function([dl_model.input, K.learning_phase()], [out_diff, grad])
input_img_data_neuron_grad=np.zeros((1, 32, 32, 20))
input_img_data_neuron=np.copy(testdata[input_index:input_index+1,:,:,:-6])
out_loss, out_grad=iterate([input_img_data_neuron, 1])
for_contours[conv_filter]=gaussian_filter(
(test_data[composite_group][input_index,:,:,self.extract_variable_index(testdata)]*(
-out_grad[0, :, :, self.extract_variable_index(testdata)])), 1)
array=[p[1] for p in for_contours.items()]
thecontours=np.asarray(array)
thedbz=test_data[composite_group][input_index, :, :, self.extract_dbz_index(testdata)] * self.dbz_std + self.dbz_mean
theeu=test_data[composite_group][input_index, :, :, self.extract_EU_index(testdata)] * self.eu_std + self.eu_mean
theev=test_data[composite_group][input_index, :, :, self.extract_EV_index(testdata)] * self.ev_std + self.ev_mean
theuh25=test_data[composite_group][input_index, :, :, self.extract_uh25_index(testdata)] * self.uh25_std + self.uh25_mean
theuh03=test_data[composite_group][input_index, :, :, self.extract_uh03_index(testdata)] * self.uh03_std + self.uh03_mean
data=xr.Dataset({
'saliency_maps':(['a','x','y'], thecontours),
'dbz':(['x','y'], thedbz),
'eu':(['x','y'], theeu),
'ev':(['x','y'], theev),
'uh25':(['x','y'], theuh25),
'uh03':(['x','y'], theuh03),
})
data.to_netcdf(
f"{self.comp_directory}/inputgrad_{self.mask_str}_model{self.model_num}_{self.method}{self.random_choice}_{composite_group}_{str(input_index)}_{self.variable}.nc")
return
def auto_saliency(self, data):
"""Preview the saved saliency maps.
Args:
data (xarray dataset): Saliency map opened netCDF file.
"""
sm_data=data.saliency_maps
fig, axes=plt.subplots(4, 8, figsize=(16, 8), sharex=True, sharey=True)
plt.subplots_adjust(0.02, 0.02, 0.96, 0.94, wspace=0,hspace=0)
for conv_filter, ax in enumerate(axes.ravel()):
levels=[0,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80]
cmap_dbz = colortables.get_colortable('NWSReflectivity')
ax.contourf(data.dbz,
cmap=cmap_dbz, levels=levels, alpha=0.2)
ax.contour(sm_data[conv_filter, :, :],
[-3, -2, -1, 1, 2, 3], vmin=-3, vmax=3, cmap="seismic", linewidths=3.0)
ax.set_xticks([])
ax.set_yticks([])
ax.xaxis.set_ticklabels([])
ax.yaxis.set_ticklabels([])
ax.text(16, 16, conv_filter, fontsize=14)
plt.suptitle("Final Convolution Filter Saliency Maps", fontsize=14, y=0.98)
plt.show()
| 49.533688 | 207 | 0.59133 | 3,516 | 27,937 | 4.511092 | 0.110637 | 0.030767 | 0.029948 | 0.037829 | 0.778324 | 0.756888 | 0.751466 | 0.745665 | 0.730912 | 0.726373 | 0 | 0.031689 | 0.281598 | 27,937 | 563 | 208 | 49.62167 | 0.758595 | 0.329635 | 0 | 0.483516 | 0 | 0.025641 | 0.144074 | 0.094754 | 0 | 0 | 0 | 0 | 0 | 1 | 0.091575 | false | 0 | 0.043956 | 0 | 0.194139 | 0.014652 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
15ce59e057dd6da1c41f8f9f6f3b4f2f20161844 | 275 | py | Python | webdriver_test_tools/config/browserstack.py | connordelacruz/webdriver-test-tools | fe6906839e4423562c6d4d0aa6b10b2ea90bff6b | [
"MIT"
] | 5 | 2018-07-02T13:18:59.000Z | 2019-10-14T04:55:31.000Z | webdriver_test_tools/config/browserstack.py | connordelacruz/webdriver-test-tools | fe6906839e4423562c6d4d0aa6b10b2ea90bff6b | [
"MIT"
] | 1 | 2019-10-16T20:54:25.000Z | 2019-10-16T20:54:25.000Z | webdriver_test_tools/config/browserstack.py | connordelacruz/webdriver-test-tools | fe6906839e4423562c6d4d0aa6b10b2ea90bff6b | [
"MIT"
] | 1 | 2019-09-03T05:29:41.000Z | 2019-09-03T05:29:41.000Z | """This module imports the :class:`BrowserStackConfig
<webdriver_test_tools.config.browser.BrowserStackConfig>` class for consistency
with test project configs. See the documentation for
:mod:`webdriver_test_tools.config.browser`.
"""
from .browser import BrowserStackConfig
| 39.285714 | 79 | 0.829091 | 33 | 275 | 6.787879 | 0.636364 | 0.116071 | 0.160714 | 0.214286 | 0.276786 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083636 | 275 | 6 | 80 | 45.833333 | 0.888889 | 0.825455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
15f6dc80a9b4fb48131b4b669a3881520630de59 | 145 | py | Python | politics/wsgi.py | microstack/main-front | ea235eff2933fbccf401686470eefb89abeef634 | [
"MIT"
] | null | null | null | politics/wsgi.py | microstack/main-front | ea235eff2933fbccf401686470eefb89abeef634 | [
"MIT"
] | 62 | 2016-07-13T15:51:26.000Z | 2016-09-03T04:28:08.000Z | politics/wsgi.py | microstack/main-front | ea235eff2933fbccf401686470eefb89abeef634 | [
"MIT"
] | null | null | null | from views import app
from settings import FRONT_POLITICS_PORT
if __name__ == "__main__":
app.run(host='0.0.0.0', port=FRONT_POLITICS_PORT)
| 24.166667 | 53 | 0.758621 | 24 | 145 | 4.083333 | 0.583333 | 0.061224 | 0.346939 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031746 | 0.131034 | 145 | 5 | 54 | 29 | 0.746032 | 0 | 0 | 0 | 0 | 0 | 0.103448 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c60faeca0586fa8c89277107e343d11a4c5bff3b | 46 | py | Python | src/crystallise/__init__.py | rosalindfranklininstitute/crystallise | 31f9179f93eb7561da66ac6482ad21d1d04b0b59 | [
"Apache-2.0"
] | null | null | null | src/crystallise/__init__.py | rosalindfranklininstitute/crystallise | 31f9179f93eb7561da66ac6482ad21d1d04b0b59 | [
"Apache-2.0"
] | null | null | null | src/crystallise/__init__.py | rosalindfranklininstitute/crystallise | 31f9179f93eb7561da66ac6482ad21d1d04b0b59 | [
"Apache-2.0"
] | null | null | null | from crystallise.crystallise import * # noqa
| 23 | 45 | 0.782609 | 5 | 46 | 7.2 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152174 | 46 | 1 | 46 | 46 | 0.923077 | 0.086957 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c6118a625a5e62d448b2e98642f5d128b52f485f | 17,669 | py | Python | weld/pandas_weld/tests/core/test_frame.py | radujica/data-analysis-pipelines | 64a6e5613cb1ab2ba2eb2f763c2aa1e3bc5e0d3b | [
"MIT"
] | 5 | 2018-03-05T13:19:35.000Z | 2020-11-17T15:59:41.000Z | weld/pandas_weld/tests/core/test_frame.py | radujica/data-analysis-pipelines | 64a6e5613cb1ab2ba2eb2f763c2aa1e3bc5e0d3b | [
"MIT"
] | 1 | 2021-06-01T22:27:44.000Z | 2021-06-01T22:27:44.000Z | weld/pandas_weld/tests/core/test_frame.py | radujica/data-analysis-pipelines | 64a6e5613cb1ab2ba2eb2f763c2aa1e3bc5e0d3b | [
"MIT"
] | null | null | null | import unittest
import numpy as np
import pandas_weld as pdw
from indexes.test_multi import test_equal_multiindex
from pandas_weld.tests.core.test_series import test_equal_series
from pandas_weld.tests.utils import evaluate_if_necessary
# TODO: add method to check equal DataFrame
class DataFrameTests(unittest.TestCase):
def setUp(self):
data = {'col1': np.array([1, 2, 3, 4]),
'col2': np.array([5., 6., 7., 8.])}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
self.df = pdw.DataFrame(data, index)
def test_getitem_column(self):
expected_result = np.array([1, 2, 3, 4])
result = evaluate_if_necessary(self.df['col1'])
np.testing.assert_array_equal(expected_result, result)
def test_getitem_slice(self):
data = {'col1': np.array([1, 2]),
'col2': np.array([5., 6.])}
index = pdw.MultiIndex([np.array([1, 2]), np.array([3, 4])],
[np.array([0, 0]), np.array([0, 1])],
['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df[:2]
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col1']),
evaluate_if_necessary(result['col1']))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
def test_getitem_list(self):
data = {'col1': np.array([1, 2, 3, 4]),
'col2': np.array([5., 6., 7., 8.])}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df[['col1', 'col2']]
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col1']),
evaluate_if_necessary(result['col1']))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
# i.e. filter like df[df[column] < 10]
def test_getitem_series(self):
data = {'col1': np.array([1, 2]),
'col2': np.array([5., 6.])}
index = pdw.MultiIndex([np.array([1, 2]), np.array([3, 4])], [np.array([0, 0]), np.array([0, 1])], ['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df[self.df['col1'] < 3]
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col1']),
evaluate_if_necessary(result['col1']))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
def test_setitem_new(self):
new_column = np.array([11, 12, 13, 14])
self.df['col3'] = new_column
np.testing.assert_array_equal(new_column, evaluate_if_necessary(self.df['col3']))
def test_setitem_series(self):
new_column = np.array([11, 12, 13, 14])
self.df['col3'] = pdw.Series(new_column, new_column.dtype, self.df.index)
np.testing.assert_array_equal(new_column, evaluate_if_necessary(self.df['col3']))
def test_setitem_replace(self):
new_column = np.array([11, 12, 13, 14])
self.df['col2'] = new_column
np.testing.assert_array_equal(new_column, evaluate_if_necessary(self.df['col2']))
def test_drop_str(self):
data = {'col2': np.array([5., 6., 7., 8.])}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df.drop('col1')
self.assertListEqual(expected_result.data.keys(), result.data.keys())
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
def test_drop_list(self):
data = {}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df.drop(['col1', 'col2'])
self.assertListEqual(expected_result.data.keys(), result.data.keys())
test_equal_multiindex(expected_result.index, result.index)
# noinspection PyMethodMayBeStatic
def test_element_wise_operation(self):
expected_data = {'col1': np.array([2, 4, 6, 8]),
'col2': np.array([10, 12, 14, 16])}
expected_index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
expected_result = pdw.DataFrame(expected_data, expected_index)
data = {'col1': np.array([1, 2, 3, 4]),
'col2': np.array([5, 6, 7, 8])}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
result = pdw.DataFrame(data, index) * 2
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col1']),
evaluate_if_necessary(result['col1']))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
def test_aggregate(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.Series(np.array([26., 10.], dtype=np.float64),
np.dtype(np.float64),
np.array(['col2', 'col1'], dtype=np.str))
result = self.df.sum()
test_equal_series(expected_result, result)
def test_describe(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.DataFrame({'col1': np.array([1, 4, 2.5, 1.29089], np.float64),
'col2': np.array([5, 8, 6.5, 1.29099], np.float64)},
pdw.Index(np.array(['min', 'max', 'mean', 'std'], dtype=np.str),
np.dtype(np.str),
"Index"))
result = self.df.describe(['min', 'max', 'mean', 'std']).evaluate()
np.testing.assert_array_equal(evaluate_if_necessary(expected_result.index),
evaluate_if_necessary(result.index))
test_equal_series(expected_result['col1'].evaluate(), result['col1'].evaluate())
test_equal_series(expected_result['col2'].evaluate(), result['col2'].evaluate())
def test_aggregate_min(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.Series(np.array([5., 1.], dtype=np.float64),
np.dtype(np.float64),
np.array(['col2', 'col1'], dtype=np.str))
result = self.df.min()
test_equal_series(expected_result, result)
def test_rename(self):
data = {'col3': np.array([1, 2, 3, 4]),
'col2': np.array([5., 6., 7., 8.])}
index = pdw.MultiIndex.from_product([np.array([1, 2]), np.array([3, 4])], ['a', 'b'])
expected_result = pdw.DataFrame(data, index)
result = self.df.rename(columns={'col1': 'col3'})
self.assertListEqual(expected_result.data.keys(), result.data.keys())
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col3']),
evaluate_if_necessary(result['col3']))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result['col2']),
evaluate_if_necessary(result['col2']))
test_equal_multiindex(expected_result.index, result.index)
def test_count(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.Series(np.array([4, 4], dtype=np.int64),
np.dtype(np.int64),
np.array(['col2', 'col1'], dtype=np.str))
result = self.df.count()
test_equal_series(expected_result, result)
def test_mean(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.Series(np.array([6.5, 2.5], dtype=np.float64),
np.dtype(np.float64),
np.array(['col2', 'col1'], dtype=np.str))
result = self.df.mean()
test_equal_series(expected_result, result)
def test_std(self):
# reversed because of dict and not OrderedDict
expected_result = pdw.Series(np.array([1.2909944487358056, 1.2909944487358056], dtype=np.float64),
np.dtype(np.float64),
np.array(['col2', 'col1'], dtype=np.str))
result = self.df.std()
test_equal_series(expected_result, result)
def test_agg(self):
expected_result = pdw.DataFrame({'col1': np.array([1, 4], dtype=np.float64),
'col2': np.array([5, 8], dtype=np.float64)},
pdw.Index(np.array(['min', 'max'], dtype=np.dtype('str')),
np.dtype('str')))
result = self.df.agg(['min', 'max'])
np.testing.assert_array_equal(evaluate_if_necessary(expected_result.index),
evaluate_if_necessary(result.index))
test_equal_series(expected_result['col1'], result['col1'])
test_equal_series(expected_result['col2'], result['col2'])
# noinspection PyMethodMayBeStatic
def test_join_1d_index(self):
df1 = pdw.DataFrame({'col1': np.array([1, 2, 3, 4, 5])},
pdw.Index(np.array([1, 3, 4, 5, 6]), np.dtype(np.int64)))
df2 = pdw.DataFrame({'col2': np.array([1, 2, 3])},
pdw.Index(np.array([2, 3, 5]), np.dtype(np.int64)))
result = df1.merge(df2)
expected_result = pdw.DataFrame({'col1': np.array([2, 4]), 'col2': np.array([2, 3])},
pdw.Index(np.array([3, 5]), np.dtype(np.int64)))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result.index),
evaluate_if_necessary(result.index))
test_equal_series(expected_result['col1'], result['col1'])
test_equal_series(expected_result['col2'], result['col2'])
# noinspection PyMethodMayBeStatic
def test_join_multiindex(self):
df1 = pdw.DataFrame({'col1': np.arange(8)},
pdw.MultiIndex.from_product([np.array([1, 2]),
np.array([3, 4]),
np.array([5, 6])],
['i1', 'i2', 'i3']))
df2 = pdw.DataFrame({'col2': np.arange(12)},
pdw.MultiIndex.from_product([np.array([1, 2, 3]),
np.array([3, 5]),
np.array([5, 6])],
['i1', 'i2', 'i3']))
result = df1.merge(df2)
expected_result = pdw.DataFrame({'col1': np.array([0, 1, 4, 5]), 'col2': np.array([0, 1, 4, 5])},
pdw.MultiIndex([np.array([1, 2]),
np.array([3, 4]),
np.array([5, 6])],
[np.array([0, 0, 1, 1]),
np.array([0, 0, 0, 0]),
np.array([0, 1, 0, 1])],
['i1', 'i2', 'i3']))
test_equal_multiindex(expected_result.index, result.index)
test_equal_series(expected_result['col1'], result['col1'])
test_equal_series(expected_result['col2'], result['col2'])
# noinspection PyMethodMayBeStatic
def test_groupby_single_column_sum(self):
df = pdw.DataFrame({'col1': np.array([1, 1, 2, 3, 3], dtype=np.int32),
'col2': np.array([3, 4, 5, 5, 6], dtype=np.int64),
'col3': np.array([5., 6., 7., 7., 7.], dtype=np.float32)},
pdw.MultiIndex([np.array([1, 2, 3], dtype=np.int32),
np.array([5., 6., 7.], dtype=np.float32)],
[np.array([0, 0, 1, 2, 2], dtype=np.int64),
np.array([0, 1, 2, 2, 2], dtype=np.int64)],
['i32', 'f32']))
result = df.groupby('col1').sum()
expected_result = pdw.DataFrame({'col2': np.array([7, 5, 11], dtype=np.int64),
'col3': np.array([11., 7., 14.], dtype=np.float32)},
pdw.Index(np.array([1, 2, 3], dtype=np.int32), np.dtype('int32'), 'col1'))
# TODO: test equal 1d index method (both rangeindex and index should work)
np.testing.assert_array_equal(np.sort(evaluate_if_necessary(expected_result.index)),
np.sort(evaluate_if_necessary(result.index)))
# assume correct values but in different order; just check the values
np.testing.assert_array_equal(np.sort(expected_result['col2'].evaluate().data),
np.sort(result['col2'].evaluate().data))
np.testing.assert_array_equal(np.sort(expected_result['col3'].evaluate().data),
np.sort(result['col3'].evaluate().data))
# noinspection PyMethodMayBeStatic
def test_groupby_multiple_columns_sum(self):
df = pdw.DataFrame({'col1': np.array([1, 1, 2, 3, 3], dtype=np.int32),
'col2': np.array([3, 4, 5, 5, 6], dtype=np.int64),
'col3': np.array([5., 6., 7., 7., 7.], dtype=np.float32)},
pdw.MultiIndex([np.array([1, 2, 3], dtype=np.int32),
np.array([5., 6., 7.], dtype=np.float32)],
[np.array([0, 0, 1, 2, 2], dtype=np.int64),
np.array([0, 1, 2, 2, 2], dtype=np.int64)],
['i32', 'f32']))
result = df.groupby(['col1', 'col3']).sum()
expected_result = pdw.DataFrame({'col2': np.array([3, 4, 5, 11], dtype=np.int64)},
pdw.MultiIndex([np.array([1, 2, 3], dtype=np.int32),
np.array([5., 6., 7.], dtype=np.float32)],
[np.array([0, 0, 1, 2], dtype=np.int64),
np.array([0, 1, 2, 2], dtype=np.int64)],
['col1', 'col3']))
# TODO: test equal 1d index method (both rangeindex and index should work)
# assume correct index values but in different order; just check the values
levels_result = [np.sort(level.evaluate()) for level in result.index.levels]
labels_result = [np.sort(label.evaluate()) for label in result.index.labels]
levels_expected = [np.sort(level) for level in expected_result.index.levels]
labels_expected = [np.sort(label) for label in expected_result.index.labels]
np.testing.assert_array_equal(result.index.names, expected_result.index.names)
for i in range(2):
np.testing.assert_array_equal(levels_result[i], levels_expected[i])
np.testing.assert_array_equal(labels_result[i], labels_expected[i])
# assume correct values but in different order; just check the values
np.testing.assert_array_equal(np.sort(expected_result['col2'].evaluate().data),
np.sort(result['col2'].evaluate().data))
def test_reset_index(self):
result = self.df.reset_index()
expected_result = pdw.DataFrame({'col1': np.array([1, 2, 3, 4]),
'col2': np.array([5., 6., 7., 8.]),
'a': np.array([1, 1, 2, 2]),
'b': np.array([3, 4, 3, 4])},
pdw.RangeIndex(0, 4, 1))
np.testing.assert_array_equal(evaluate_if_necessary(expected_result.index),
evaluate_if_necessary(result.index))
test_equal_series(expected_result['col1'], result['col1'])
test_equal_series(expected_result['col2'], result['col2'])
test_equal_series(expected_result['a'], result['a'])
test_equal_series(expected_result['b'], result['b'])
def main():
unittest.main()
if __name__ == '__main__':
main()
| 49.21727 | 118 | 0.522554 | 2,068 | 17,669 | 4.299807 | 0.071083 | 0.081871 | 0.07906 | 0.026316 | 0.804431 | 0.754161 | 0.721885 | 0.709739 | 0.655308 | 0.625281 | 0 | 0.051055 | 0.329334 | 17,669 | 358 | 119 | 49.354749 | 0.699325 | 0.049182 | 0 | 0.474308 | 0 | 0 | 0.034801 | 0 | 0 | 0 | 0 | 0.002793 | 0.114625 | 1 | 0.098814 | false | 0 | 0.023715 | 0 | 0.126482 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
c611a5d2c494ee3213726af8c9ab627de39feff0 | 99 | py | Python | src/interpreter/functions/setindex.py | incrementals/b-star | 325bb51eafd5c5173582bf065b82d10ef9669275 | [
"MIT"
] | 2 | 2021-11-02T04:28:32.000Z | 2021-11-05T14:27:08.000Z | src/interpreter/functions/setindex.py | incrementals/b-star | 325bb51eafd5c5173582bf065b82d10ef9669275 | [
"MIT"
] | null | null | null | src/interpreter/functions/setindex.py | incrementals/b-star | 325bb51eafd5c5173582bf065b82d10ef9669275 | [
"MIT"
] | null | null | null | import copy
def setindex(arr, index, val):
arr = copy.copy(arr)
arr[index] = val
return arr
| 14.142857 | 30 | 0.666667 | 16 | 99 | 4.125 | 0.5 | 0.242424 | 0.333333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.212121 | 99 | 6 | 31 | 16.5 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.2 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
c6195f1ffb9aca5dfe81df56011cb4e75de5dc78 | 221 | py | Python | snake_rl/algorithms/baselines/a2c/__init__.py | alex-petrenko/snake-rl | ca7000120985da7fcac4047747ad7937693abcfe | [
"MIT"
] | 1 | 2021-08-28T10:37:33.000Z | 2021-08-28T10:37:33.000Z | snake_rl/algorithms/baselines/a2c/__init__.py | dre2004/snake-rl | ca7000120985da7fcac4047747ad7937693abcfe | [
"MIT"
] | null | null | null | snake_rl/algorithms/baselines/a2c/__init__.py | dre2004/snake-rl | ca7000120985da7fcac4047747ad7937693abcfe | [
"MIT"
] | 1 | 2021-02-18T00:22:40.000Z | 2021-02-18T00:22:40.000Z | from snake_rl.algorithms.baselines.a2c.a2c_utils import CURRENT_ENV, CURRENT_EXPERIMENT
from snake_rl.algorithms.baselines.a2c.agent_a2c import AgentA2C
from snake_rl.algorithms.baselines.a2c import train_a2c, enjoy_a2c
| 44.2 | 87 | 0.873303 | 34 | 221 | 5.411765 | 0.441176 | 0.146739 | 0.179348 | 0.342391 | 0.538043 | 0.538043 | 0 | 0 | 0 | 0 | 0 | 0.038835 | 0.067873 | 221 | 4 | 88 | 55.25 | 0.854369 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c63dcc58ec9634b73251728571dae551f43abd71 | 116 | py | Python | HW6/YuliiaKutsyk/1_distance_between_two_points.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | null | null | null | HW6/YuliiaKutsyk/1_distance_between_two_points.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | null | null | null | HW6/YuliiaKutsyk/1_distance_between_two_points.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | 6 | 2022-02-22T22:30:49.000Z | 2022-03-28T12:51:19.000Z | import math
def distance(x1, y1, x2, y2):
return round(math.sqrt(math.pow(x2 - x1,2) + math.pow(y2-y1, 2)), 2)
| 23.2 | 72 | 0.62931 | 23 | 116 | 3.173913 | 0.565217 | 0.191781 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114583 | 0.172414 | 116 | 4 | 73 | 29 | 0.645833 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0.333333 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 5 |
c64960740fce0133ef5230374d70c57b8b70b497 | 52 | py | Python | src/operators/__init__.py | headout/ergo-airflow | 6fbdeea1e8bb1ac87bf635be10c7a770cbf3884c | [
"MIT"
] | null | null | null | src/operators/__init__.py | headout/ergo-airflow | 6fbdeea1e8bb1ac87bf635be10c7a770cbf3884c | [
"MIT"
] | null | null | null | src/operators/__init__.py | headout/ergo-airflow | 6fbdeea1e8bb1ac87bf635be10c7a770cbf3884c | [
"MIT"
] | 1 | 2020-09-26T20:26:02.000Z | 2020-09-26T20:26:02.000Z | from .task_producer import ErgoTaskProducerOperator
| 26 | 51 | 0.903846 | 5 | 52 | 9.2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.076923 | 52 | 1 | 52 | 52 | 0.958333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c658902a66503eaf5a56f0eef0e908236d1b46d5 | 141 | py | Python | client/src/state/__init__.py | juan-nunez/Space_combat | e732ef932e89c404827ac0c96aebb4f0446cefdf | [
"MIT"
] | null | null | null | client/src/state/__init__.py | juan-nunez/Space_combat | e732ef932e89c404827ac0c96aebb4f0446cefdf | [
"MIT"
] | null | null | null | client/src/state/__init__.py | juan-nunez/Space_combat | e732ef932e89c404827ac0c96aebb4f0446cefdf | [
"MIT"
] | null | null | null |
from state_machine import StateMachine
from state import State
from end import *
from play import *
from waiting import *
from home import * | 20.142857 | 38 | 0.801418 | 21 | 141 | 5.333333 | 0.428571 | 0.267857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.170213 | 141 | 7 | 39 | 20.142857 | 0.957265 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
d67d4f7b4ca9a59351175fb1ac8fc8328e4e8cce | 129 | py | Python | sys_test.py | Xingxiangrui/MTCNN_for_head_detection | 5f036271ab0e00a29721855282b8d2e8feef0238 | [
"MIT"
] | 5 | 2019-09-01T10:31:17.000Z | 2019-12-30T06:37:19.000Z | sys_test.py | Xingxiangrui/MTCNN_for_head_detection | 5f036271ab0e00a29721855282b8d2e8feef0238 | [
"MIT"
] | null | null | null | sys_test.py | Xingxiangrui/MTCNN_for_head_detection | 5f036271ab0e00a29721855282b8d2e8feef0238 | [
"MIT"
] | 2 | 2019-09-01T10:31:20.000Z | 2020-03-20T09:34:27.000Z | """
author:xing xiangrui
test os.system()
"""
import os
os.chdir("mAP/")
#os.system("cd mAP/")
os.system("python main.py -na") | 11.727273 | 31 | 0.643411 | 21 | 129 | 3.952381 | 0.666667 | 0.289157 | 0.26506 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.124031 | 129 | 11 | 31 | 11.727273 | 0.734513 | 0.457364 | 0 | 0 | 0 | 0 | 0.349206 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
d68f945d0942dab0027cfeba47eefb7e2bd02027 | 69 | py | Python | cv2_rolling_ball/__init__.py | ImprolabFIT/opencv-rolling-ball | 41462eec83ec652af0ee35ef9193049fa7e56e91 | [
"MIT"
] | 33 | 2018-03-11T13:09:43.000Z | 2022-03-23T11:40:27.000Z | cv2_rolling_ball/__init__.py | ImprolabFIT/opencv-rolling-ball | 41462eec83ec652af0ee35ef9193049fa7e56e91 | [
"MIT"
] | 3 | 2018-03-12T17:05:20.000Z | 2022-01-17T18:55:37.000Z | cv2_rolling_ball/__init__.py | ImprolabFIT/opencv-rolling-ball | 41462eec83ec652af0ee35ef9193049fa7e56e91 | [
"MIT"
] | 7 | 2018-03-12T12:26:03.000Z | 2021-06-17T09:30:52.000Z |
from .background_subtractor import subtract_background_rolling_ball
| 23 | 67 | 0.913043 | 8 | 69 | 7.375 | 0.875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072464 | 69 | 2 | 68 | 34.5 | 0.921875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
d6903c70f2b10b156f594902cc77a8ed74e6f0af | 44 | py | Python | workers/__init__.py | fwallacevt/notion-recurring-tasks | 21092c20c5a6441509854e07ecf1121c3fd42b76 | [
"MIT"
] | 1 | 2022-01-14T20:18:04.000Z | 2022-01-14T20:18:04.000Z | workers/__init__.py | fwallacevt/notion-recurring-tasks | 21092c20c5a6441509854e07ecf1121c3fd42b76 | [
"MIT"
] | null | null | null | workers/__init__.py | fwallacevt/notion-recurring-tasks | 21092c20c5a6441509854e07ecf1121c3fd42b76 | [
"MIT"
] | 1 | 2022-01-11T00:46:30.000Z | 2022-01-11T00:46:30.000Z | """Entry points for Notion applications."""
| 22 | 43 | 0.727273 | 5 | 44 | 6.4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.113636 | 44 | 1 | 44 | 44 | 0.820513 | 0.840909 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
d6954bdc17858fe95e46a4319e51ea3b3f4ee367 | 95 | py | Python | mysql_to_sqlite3/__init__.py | danihodovic/mysql-to-sqlite3 | 0e3f78def35d573a8278eac83d32830e607a78ee | [
"MIT"
] | 97 | 2019-04-08T02:24:01.000Z | 2022-03-29T20:22:55.000Z | mysql_to_sqlite3/__init__.py | danihodovic/mysql-to-sqlite3 | 0e3f78def35d573a8278eac83d32830e607a78ee | [
"MIT"
] | 25 | 2019-03-23T16:38:48.000Z | 2022-03-27T13:50:54.000Z | mysql_to_sqlite3/__init__.py | danihodovic/mysql-to-sqlite3 | 0e3f78def35d573a8278eac83d32830e607a78ee | [
"MIT"
] | 14 | 2019-03-23T16:16:39.000Z | 2022-03-03T17:25:34.000Z | """Utility to transfer data from MySQL to SQLite 3."""
from .transporter import MySQLtoSQLite
| 23.75 | 54 | 0.768421 | 13 | 95 | 5.615385 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012346 | 0.147368 | 95 | 3 | 55 | 31.666667 | 0.888889 | 0.505263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
d6cfffc54e8774c2069e723a041aceb6b5a8bd86 | 222 | py | Python | pogo/pogoBot/mod.py | cqian19/PokeGo-Idle | d6c58b5466f2f3633b69c322e1d9d0e9d6a09554 | [
"MIT"
] | 1 | 2017-04-09T18:00:11.000Z | 2017-04-09T18:00:11.000Z | pogo/pogoBot/mod.py | cqian19/PokeGo-Idle | d6c58b5466f2f3633b69c322e1d9d0e9d6a09554 | [
"MIT"
] | 3 | 2016-08-12T07:39:29.000Z | 2016-08-23T23:46:11.000Z | pogo/pogoBot/mod.py | cqian19/PokeGo-Idle | d6c58b5466f2f3633b69c322e1d9d0e9d6a09554 | [
"MIT"
] | 1 | 2016-08-26T10:29:32.000Z | 2016-08-26T10:29:32.000Z | class Handler():
def __init__(self, session, logger, config):
self.session = session
self.logger = logger
self.config = config
def setSession(self, session):
self.session = session | 24.666667 | 48 | 0.621622 | 24 | 222 | 5.583333 | 0.375 | 0.328358 | 0.268657 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.283784 | 222 | 9 | 49 | 24.666667 | 0.842767 | 0 | 0 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0 | 0 | 0.428571 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
d6d4c2c239aefb47884879365008e23145ad7a5c | 8,319 | py | Python | test/test_intercept.py | dawid-czarnecki/wpgarlic | 54b7393504a3ab25b17db47c92ecd0cc5d88e48a | [
"MIT"
] | 47 | 2022-02-26T12:34:52.000Z | 2022-03-31T15:17:41.000Z | test/test_intercept.py | dawid-czarnecki/wpgarlic | 54b7393504a3ab25b17db47c92ecd0cc5d88e48a | [
"MIT"
] | 1 | 2022-03-16T18:46:41.000Z | 2022-03-19T20:11:57.000Z | test/test_intercept.py | dawid-czarnecki/wpgarlic | 54b7393504a3ab25b17db47c92ecd0cc5d88e48a | [
"MIT"
] | 6 | 2022-02-27T12:11:48.000Z | 2022-03-15T03:34:56.000Z | import collections
import re
import subprocess
import unittest
import fuzzer_container
import fuzzer_output_regexes
class FuzzerInterceptTest(unittest.TestCase):
@staticmethod
def setUpClass():
fuzzer_container.reinitialize_containers()
@staticmethod
def tearDownClass():
subprocess.call(["docker-compose", "stop"])
@staticmethod
def _clean(s: str):
s = re.sub(fuzzer_output_regexes.HEADER_RE, "", s)
s = re.sub(fuzzer_output_regexes.INTERCEPT_RE, "", s)
return s.strip()
def test_payload_randomization(self):
stdouts = []
for i in range(15):
commands = fuzzer_container.fuzz_file_or_folder(
"RANDOM", "/fuzzer/test/echo.php"
)
for command in commands:
self.assertIn(
command["cmd"],
[
"export INTERCEPT_PROB=100; export PAYLOAD_ID=RANDOM; "
"cd /fuzzer/test && php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=50; export PAYLOAD_ID=RANDOM; "
"cd /fuzzer/test && php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=33; export PAYLOAD_ID=RANDOM; "
"cd /fuzzer/test && php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=25; export PAYLOAD_ID=RANDOM; "
"cd /fuzzer/test && php /fuzzer/execute/run_file.php 'echo.php'",
],
)
stdouts.append(self._clean(command["stdout"]))
counter = collections.Counter(stdouts)
self.assertGreaterEqual(counter["GARLIC GARLIC\\'\\\"`"], 5)
self.assertGreaterEqual(counter["invalidfolderGARLIC/filenameGARLIC"], 5)
self.assertGreaterEqual(counter["magic"], 5)
self.assertGreaterEqual(counter["legitimateGARLIC"], 5)
def test_php_input_stream(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_php_input.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]),
"sh: 1: Syntax error: end of file unexpected",
)
def test_sql_query(self):
commands = fuzzer_container.fuzz_file_or_folder(
"1", "/fuzzer/test/mysql_query.php"
)
self.assertTrue("GARLIC" in commands[0]["stdout"])
self.assertTrue("error in your SQL syntax" in commands[0]["stdout"])
def test_file_listing(self):
commands = fuzzer_container.fuzz_file_or_folder("0", "/fuzzer/test/listing.php")
self.assertTrue(
"/var/www/html/wp-content/test_file_GARLIC" in commands[0]["stdout"]
)
def test_GET(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_get.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_POST(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_post.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_COOKIE(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_cookie.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_REQUEST(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_request.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_HTTP_USER_AGENT_header(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_server_http_user_agent.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_echo(self):
commands = fuzzer_container.fuzz_file_or_folder("1", "/fuzzer/test/echo.php")
self.assertTrue("</GARLIC" in commands[0]["stdout"])
def test_include(self):
commands = fuzzer_container.fuzz_file_or_folder("0", "/fuzzer/test/include.php")
self.assertTrue(
"GARLIC): failed to open stream: No such file or directory"
in commands[0]["stdout"]
)
def test_json_decode(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/system_json_decode.php"
)
self.assertEqual(
self._clean(commands[0]["stderr"]), "sh: 1: legitimateGARLIC: not found"
)
def test_file_get_contents(self):
commands = fuzzer_container.fuzz_file_or_folder(
"0", "/fuzzer/test/file_get_contents.php"
)
self.assertTrue(
"GARLIC): failed to open stream: No such file or directory"
in commands[0]["stdout"]
)
def test_probabilistic_intercept(self):
commands = fuzzer_container.fuzz_file_or_folder("0", "/fuzzer/test/echo.php")
num_all = 0
num_intercepted = 0
for command in commands:
self.assertIn(
command["cmd"],
[
"export INTERCEPT_PROB=100; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=50; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=33; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'echo.php'",
"export INTERCEPT_PROB=25; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'echo.php'",
],
)
if "GARLIC" in command["stdout"]:
num_intercepted += 1
num_all += 1
self.assertGreaterEqual(num_intercepted, 10)
self.assertLessEqual(num_intercepted, num_all - 3)
def test_we_are_immune_to_sleep(self):
commands = fuzzer_container.fuzz_file_or_folder("0", "/fuzzer/test/sleep.php")
num_all = 0
num_intercepted = 0
for command in commands[1:]:
self.assertIn(
command["cmd"],
[
"export INTERCEPT_PROB=100; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'sleep.php'",
"export INTERCEPT_PROB=50; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'sleep.php'",
"export INTERCEPT_PROB=33; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'sleep.php'",
"export INTERCEPT_PROB=25; export PAYLOAD_ID=0; cd /fuzzer/test && "
"php /fuzzer/execute/run_file.php 'sleep.php'",
],
)
if "GARLIC" in command.get("stdout", ""):
num_intercepted += 1
num_all += 1
self.assertGreaterEqual(num_intercepted, 3)
self.assertLessEqual(num_intercepted, num_all / 2 - 3)
def test_patched_equality(self):
commands = fuzzer_container.fuzz_file_or_folder(
"RANDOM", "/fuzzer/test/equality.php"
)
counter = collections.Counter(
[command["stdout"].strip() for command in commands]
)
self.assertGreaterEqual(counter["bool(false)"], 20)
self.assertGreaterEqual(counter["bool(true)"], 10)
def test_patched_strict_equality(self):
commands = fuzzer_container.fuzz_file_or_folder(
"RANDOM", "/fuzzer/test/strict_equality.php"
)
counter = collections.Counter(
[command["stdout"].strip() for command in commands]
)
self.assertGreaterEqual(counter["bool(false)"], 20)
self.assertGreaterEqual(counter["bool(true)"], 10)
| 38.513889 | 89 | 0.582041 | 920 | 8,319 | 5.054348 | 0.146739 | 0.062366 | 0.084086 | 0.09871 | 0.770753 | 0.763441 | 0.730753 | 0.722796 | 0.705591 | 0.705591 | 0 | 0.016815 | 0.299435 | 8,319 | 215 | 90 | 38.693023 | 0.781057 | 0 | 0 | 0.44086 | 0 | 0 | 0.306768 | 0.107345 | 0 | 0 | 0 | 0 | 0.150538 | 1 | 0.107527 | false | 0 | 0.032258 | 0 | 0.150538 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ba55d439e5f459e57d39bb21b4bfab8ebb75dd14 | 135 | py | Python | dosearch.py | deapplegate/wtgpipeline | 9693e8562022cc97bf5a96427e22965e1a5e8497 | [
"MIT"
] | 1 | 2019-03-15T04:01:19.000Z | 2019-03-15T04:01:19.000Z | dosearch.py | deapplegate/wtgpipeline | 9693e8562022cc97bf5a96427e22965e1a5e8497 | [
"MIT"
] | 5 | 2017-12-11T00:11:39.000Z | 2021-07-09T17:05:16.000Z | dosearch.py | deapplegate/wtgpipeline | 9693e8562022cc97bf5a96427e22965e1a5e8497 | [
"MIT"
] | 2 | 2017-08-15T21:19:11.000Z | 2017-10-12T00:36:35.000Z | #! /usr/bin/env python
import sys
from telarchive import archive_search
if __name__ == "__main__":
archive_search.main(sys.argv)
| 13.5 | 37 | 0.748148 | 19 | 135 | 4.789474 | 0.736842 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148148 | 135 | 9 | 38 | 15 | 0.791304 | 0.155556 | 0 | 0 | 0 | 0 | 0.071429 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
ba5b645aef15b56394a7183ee73018ff95b93822 | 3,340 | py | Python | test/test_extract.py | vkazei/deepwave | 032bb06328673f4f824fbca20f09ba7bb277c8d1 | [
"MIT"
] | 73 | 2018-07-16T13:57:09.000Z | 2022-03-24T04:08:27.000Z | test/test_extract.py | vkazei/deepwave | 032bb06328673f4f824fbca20f09ba7bb277c8d1 | [
"MIT"
] | 41 | 2018-07-14T15:44:13.000Z | 2022-03-25T09:35:08.000Z | test/test_extract.py | vkazei/deepwave | 032bb06328673f4f824fbca20f09ba7bb277c8d1 | [
"MIT"
] | 20 | 2018-12-02T14:42:59.000Z | 2022-03-21T15:52:52.000Z | import torch
import deepwave.base.model
import deepwave.base.extract
def test_set_survey_pad():
"""Check conversion of float to list."""
survey_pad = deepwave.base.extract._set_survey_pad(1.0, 2)
assert survey_pad == [1.0, 1.0, 1.0, 1.0]
def test_survey_extents1():
"""Two shots, padded survey within model."""
dx = [5.0, 5.0]
nx = (5, 5)
properties = {'a': torch.ones(nx),
'b': torch.zeros(nx)}
model = deepwave.base.model.Model(properties, dx)
survey_pad = [5.0] * 4
num_shots = 2
num_sources_per_shot = 2
num_receivers_per_shot = 2
# sources and receivers located in center of model
source_locs = torch.ones(num_shots, num_sources_per_shot, 2) * 2 * 5.0
receiver_locs = torch.ones(num_shots, num_receivers_per_shot, 2) * 2 * 5.0
expected_extents = [slice(1, 4), slice(1, 4)]
survey_extents = \
deepwave.base.extract._get_survey_extents(model.shape, model.dx,
survey_pad,
source_locs, receiver_locs)
assert survey_extents == expected_extents
def test_survey_pad2():
"""Two shots, padded survey exceeds model."""
dx = torch.Tensor([5.0, 4.0, 3.0])
nx = (5, 5, 5)
properties = {'a': torch.ones(nx),
'b': torch.zeros(nx)}
model = deepwave.base.model.Model(properties, dx)
survey_pad = [5.0] * 6
num_shots = 2
num_sources_per_shot = 2
num_receivers_per_shot = 2
# sources and receivers located in center of model
source_locs = torch.ones(num_shots, num_sources_per_shot, 3) * 2 * dx
receiver_locs = torch.ones(num_shots, num_receivers_per_shot, 3) * 2 * dx
# except for these ones that cause padding to go outside the model
source_locs[0, 0, 1] = 1 * dx[1]
receiver_locs[-1, -1, 2] = 4 * dx[2]
expected_extents = [slice(None)] * 3
expected_extents[0] = slice(1, 4)
survey_extents = \
deepwave.base.extract._get_survey_extents(model.shape, model.dx,
survey_pad, source_locs,
receiver_locs)
assert survey_extents == expected_extents
def test_survey_pad3():
"""Two shots, uses varying list of pad values."""
dx = torch.Tensor([5.0, 4.0, 3.0])
nx = (5, 5, 5)
properties = {'a': torch.ones(nx),
'b': torch.zeros(nx)}
model = deepwave.base.model.Model(properties, dx)
survey_pad = [2.0, 6.0, 0.0, 5.0, None, 1.0]
num_shots = 2
num_sources_per_shot = 2
num_receivers_per_shot = 2
# sources and receivers located in center of model
source_locs = torch.ones(num_shots, num_sources_per_shot, 3) * 2 * dx
receiver_locs = torch.ones(num_shots, num_receivers_per_shot, 3) * 2 * dx
# except for these ones that cause padding to go outside the model
source_locs[0, 0, 1] = 1 * dx[1]
receiver_locs[-1, -1, 2] = 4 * dx[2]
expected_extents = [slice(1, None), slice(1, None), slice(None)]
survey_extents = \
deepwave.base.extract._get_survey_extents(model.shape, model.dx,
survey_pad, source_locs,
receiver_locs)
assert survey_extents == expected_extents
| 40.240964 | 78 | 0.600898 | 477 | 3,340 | 3.991614 | 0.148847 | 0.044118 | 0.033613 | 0.053571 | 0.799895 | 0.799895 | 0.791492 | 0.791492 | 0.791492 | 0.791492 | 0 | 0.045664 | 0.285329 | 3,340 | 82 | 79 | 40.731707 | 0.75199 | 0.13024 | 0 | 0.661538 | 0 | 0 | 0.002083 | 0 | 0 | 0 | 0 | 0 | 0.061538 | 1 | 0.061538 | false | 0 | 0.046154 | 0 | 0.107692 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ba6fd1ccb4e825393d0a71210631b5975fe42373 | 177 | py | Python | logfile/log.py | 5610110083/Safety-in-residential-project | 000a48f8c5e94f69497a40529f3540d6b1603ad1 | [
"Apache-2.0"
] | null | null | null | logfile/log.py | 5610110083/Safety-in-residential-project | 000a48f8c5e94f69497a40529f3540d6b1603ad1 | [
"Apache-2.0"
] | null | null | null | logfile/log.py | 5610110083/Safety-in-residential-project | 000a48f8c5e94f69497a40529f3540d6b1603ad1 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python
print("Content-type: text/html")
print("")
print("<html><head>")
print("")
print("</head><body>")
print("Hello from Python.")
print("</body></html>")
| 19.666667 | 33 | 0.59322 | 23 | 177 | 4.565217 | 0.521739 | 0.209524 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.112994 | 177 | 8 | 34 | 22.125 | 0.66879 | 0.090395 | 0 | 0.285714 | 0 | 0 | 0.503145 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
ba756a904fb6ac9c2ce08e538aa7af1ae08d41c8 | 45 | py | Python | core/target_manager/random_case_generator.py | r0ck3rt/metarget | 909468b6c6819b862ed3ee6feaae890b7c2b165f | [
"Apache-2.0"
] | 295 | 2021-05-10T09:03:19.000Z | 2021-08-12T08:30:32.000Z | core/target_manager/random_case_generator.py | r0ck3rt/metarget | 909468b6c6819b862ed3ee6feaae890b7c2b165f | [
"Apache-2.0"
] | 24 | 2021-08-16T03:27:04.000Z | 2022-03-23T02:05:17.000Z | core/target_manager/random_case_generator.py | r0ck3rt/metarget | 909468b6c6819b862ed3ee6feaae890b7c2b165f | [
"Apache-2.0"
] | 52 | 2021-05-10T09:10:02.000Z | 2021-08-09T06:28:11.000Z | """
"""
class RandomCaseGenerator:
pass | 7.5 | 26 | 0.622222 | 3 | 45 | 9.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222222 | 45 | 6 | 27 | 7.5 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
bab85a25fa07cdcdb0b52d9cf2788d7428d60fd2 | 24 | py | Python | catalyst/__version__.py | metya/catalyst | 011b43e64aa59d5e91f4b1e8e1c7fc13f8a58557 | [
"Apache-2.0"
] | null | null | null | catalyst/__version__.py | metya/catalyst | 011b43e64aa59d5e91f4b1e8e1c7fc13f8a58557 | [
"Apache-2.0"
] | null | null | null | catalyst/__version__.py | metya/catalyst | 011b43e64aa59d5e91f4b1e8e1c7fc13f8a58557 | [
"Apache-2.0"
] | 1 | 2021-12-20T07:32:25.000Z | 2021-12-20T07:32:25.000Z | __version__ = "19.12.1"
| 12 | 23 | 0.666667 | 4 | 24 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.238095 | 0.125 | 24 | 1 | 24 | 24 | 0.333333 | 0 | 0 | 0 | 0 | 0 | 0.291667 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
babdd05852fbfef583271fc4760122aaa1e3dc3b | 54 | py | Python | BuildPackages/example/sublime/Packages/AAAPackageDev/tests/test_sublime_lib/test_view/test_sels.py | cohero/boxstarter | bb298cae0aef485e3547e9d654f60afbd16f93d1 | [
"Apache-2.0"
] | 583 | 2015-01-04T11:35:23.000Z | 2018-04-27T13:39:27.000Z | BuildPackages/example/sublime/Packages/AAAPackageDev/tests/test_sublime_lib/test_view/test_sels.py | cohero/boxstarter | bb298cae0aef485e3547e9d654f60afbd16f93d1 | [
"Apache-2.0"
] | 269 | 2015-01-06T14:11:44.000Z | 2018-04-06T12:24:56.000Z | BuildPackages/example/sublime/Packages/AAAPackageDev/tests/test_sublime_lib/test_view/test_sels.py | cohero/boxstarter | bb298cae0aef485e3547e9d654f60afbd16f93d1 | [
"Apache-2.0"
] | 114 | 2015-01-27T11:39:13.000Z | 2018-03-29T18:03:54.000Z | import sys
import os
import mock
import sublime | 9 | 14 | 0.740741 | 8 | 54 | 5 | 0.625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.259259 | 54 | 6 | 14 | 9 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
baf95ed2f09b1133c2a673d5347963a7102ec4ab | 225 | py | Python | src/billing/admin.py | sachitanandpandey/videoup | e9231262de484893dac88da493bc1d3d5518a569 | [
"MIT"
] | 79 | 2015-02-17T13:28:19.000Z | 2022-03-26T04:36:24.000Z | src/billing/admin.py | sachitanandpandey/videoup | e9231262de484893dac88da493bc1d3d5518a569 | [
"MIT"
] | 5 | 2021-03-18T20:47:30.000Z | 2022-03-11T23:26:28.000Z | src/billing/admin.py | sachitanandpandey/videoup | e9231262de484893dac88da493bc1d3d5518a569 | [
"MIT"
] | 67 | 2015-02-04T16:04:55.000Z | 2022-01-17T16:22:41.000Z | from django.contrib import admin
# Register your models here.
from .models import Membership, Transaction, UserMerchantId
admin.site.register(Membership)
admin.site.register(Transaction)
admin.site.register(UserMerchantId) | 28.125 | 60 | 0.831111 | 27 | 225 | 6.925926 | 0.481481 | 0.144385 | 0.272727 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088889 | 225 | 8 | 61 | 28.125 | 0.912195 | 0.115556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
24017657972c4c2496fd24275f85a8806600368c | 447 | py | Python | HW9/Olenka_M/funct_return_instance.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | null | null | null | HW9/Olenka_M/funct_return_instance.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | null | null | null | HW9/Olenka_M/funct_return_instance.py | kolyasalubov/Lv-677.PythonCore | c9f9107c734a61e398154a90b8a3e249276c2704 | [
"MIT"
] | 6 | 2022-02-22T22:30:49.000Z | 2022-03-28T12:51:19.000Z | class Human():
def __init__(self):
super().__init__()
class Man(Human):
def __init__(self):
super().__init__()
class Woman(Human):
def __init__(self):
super().__init__()
adam = Man()
eve = Woman()
def God():
return [adam, eve]
#Saw version below at codewars. It`s simpler ... LOL:
class Human:
pass
class Man(Human):
pass
class Woman(Human):
pass
def God():
return [Man(), Woman()] | 15.964286 | 53 | 0.590604 | 57 | 447 | 4.210526 | 0.385965 | 0.1 | 0.15 | 0.2 | 0.354167 | 0.354167 | 0.25 | 0 | 0 | 0 | 0 | 0 | 0.255034 | 447 | 28 | 54 | 15.964286 | 0.720721 | 0.116331 | 0 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.238095 | false | 0.142857 | 0 | 0.095238 | 0.619048 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 5 |
243b9af3b2fa934814af7635b14bad4f6611d5de | 163 | py | Python | Admission Counselling For Direct Second Year/Web-Application/AdmissionDirectSecondYear/AllIndiaColleges/urls.py | atharvaagrawal/direct-second-year-admission-analysis | 4744753c5b69d5e06211f006d56150997793c5bf | [
"MIT"
] | null | null | null | Admission Counselling For Direct Second Year/Web-Application/AdmissionDirectSecondYear/AllIndiaColleges/urls.py | atharvaagrawal/direct-second-year-admission-analysis | 4744753c5b69d5e06211f006d56150997793c5bf | [
"MIT"
] | 1 | 2020-03-25T11:06:18.000Z | 2020-03-25T11:06:18.000Z | Admission Counselling For Direct Second Year/Web-Application/AdmissionDirectSecondYear/AllIndiaColleges/urls.py | atharvaagrawal/direct-second-year-admission-analysis | 4744753c5b69d5e06211f006d56150997793c5bf | [
"MIT"
] | null | null | null | from django.urls import path
from . import views
urlpatterns = [
path('All-India-Colleges/',views.all_india_college,name="all_india_college")
]
| 20.375 | 81 | 0.693252 | 21 | 163 | 5.190476 | 0.571429 | 0.220183 | 0.275229 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.196319 | 163 | 8 | 82 | 20.375 | 0.832061 | 0 | 0 | 0 | 0 | 0 | 0.229299 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
24488b8cc8d481fcc020712cd98a4b10e3473b73 | 166 | py | Python | utils/encrypt.py | httpcn/dreamops_api | ea4877e240fb62e0f1b6675e6849043eaec426e9 | [
"Apache-2.0"
] | null | null | null | utils/encrypt.py | httpcn/dreamops_api | ea4877e240fb62e0f1b6675e6849043eaec426e9 | [
"Apache-2.0"
] | null | null | null | utils/encrypt.py | httpcn/dreamops_api | ea4877e240fb62e0f1b6675e6849043eaec426e9 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# -*- coding:utf-8 -*-
# @Author : httpcn
import hashlib
def encry(raw_str):
return hashlib.sha256(raw_str.encode('utf-8')).hexdigest()
| 16.6 | 62 | 0.662651 | 24 | 166 | 4.5 | 0.791667 | 0.074074 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.035211 | 0.144578 | 166 | 9 | 63 | 18.444444 | 0.725352 | 0.355422 | 0 | 0 | 0 | 0 | 0.048077 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0.333333 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 5 |
0319100ee423b758c824967357806c92a82279f8 | 115 | py | Python | dmripreproc/interfaces/__init__.py | slimnsour/dmripreproc | a1e4482baf1c9c7dfb3593126ffa448f075dc26c | [
"BSD-3-Clause"
] | 1 | 2019-07-31T15:32:27.000Z | 2019-07-31T15:32:27.000Z | dmripreproc/interfaces/__init__.py | slimnsour/dmripreproc | a1e4482baf1c9c7dfb3593126ffa448f075dc26c | [
"BSD-3-Clause"
] | 5 | 2019-07-29T14:25:18.000Z | 2019-07-29T15:51:12.000Z | dmripreproc/interfaces/__init__.py | slimnsour/dmripreproc | a1e4482baf1c9c7dfb3593126ffa448f075dc26c | [
"BSD-3-Clause"
] | 2 | 2019-07-25T20:52:36.000Z | 2020-01-09T20:58:41.000Z | #!/usr/bin/env python
from .fmap import FieldEnhance, FieldToRadS, FieldToHz, Phasediff2Fieldmap, Phases2Fieldmap
| 28.75 | 91 | 0.817391 | 12 | 115 | 7.833333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019231 | 0.095652 | 115 | 3 | 92 | 38.333333 | 0.884615 | 0.173913 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
033cac46fd6ebe4bcd5106f026afc3850717456c | 85 | py | Python | enthought/tvtk/wrapper_gen.py | enthought/etsproxy | 4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347 | [
"BSD-3-Clause"
] | 3 | 2016-12-09T06:05:18.000Z | 2018-03-01T13:00:29.000Z | enthought/tvtk/wrapper_gen.py | enthought/etsproxy | 4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347 | [
"BSD-3-Clause"
] | 1 | 2020-12-02T00:51:32.000Z | 2020-12-02T08:48:55.000Z | enthought/tvtk/wrapper_gen.py | enthought/etsproxy | 4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347 | [
"BSD-3-Clause"
] | null | null | null | # proxy module
from __future__ import absolute_import
from tvtk.wrapper_gen import *
| 21.25 | 38 | 0.835294 | 12 | 85 | 5.416667 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.129412 | 85 | 3 | 39 | 28.333333 | 0.878378 | 0.141176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
0341a566c0504f6b3cdb29add1bee43be2829d94 | 88 | py | Python | src/tso/tsocli/__init__.py | elijah-ward/TSO | 610565a32284cab23e9262c3431ce6d34116bfcf | [
"MIT"
] | 4 | 2018-11-05T21:36:08.000Z | 2019-04-15T13:05:39.000Z | src/tso/observation/__init__.py | elijah-ward/TSO | 610565a32284cab23e9262c3431ce6d34116bfcf | [
"MIT"
] | 2 | 2019-02-23T07:13:40.000Z | 2019-04-07T17:50:44.000Z | src/tso/tsocli/__init__.py | elijah-ward/TSO | 610565a32284cab23e9262c3431ce6d34116bfcf | [
"MIT"
] | 2 | 2020-12-09T07:03:09.000Z | 2021-07-17T02:32:46.000Z | # Left blank to tell python this is a package
# TODO: Add initialization code if needed
| 29.333333 | 45 | 0.772727 | 15 | 88 | 4.533333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.193182 | 88 | 2 | 46 | 44 | 0.957746 | 0.943182 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0.5 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
03458b0ab9e606ce6fffd948dcdecb447b3a71c3 | 79 | py | Python | tests/modules/contrib/test_cmus.py | spxtr/bumblebee-status | 45125f39af8323775aeabf809ae5ae80cfe3ccd9 | [
"MIT"
] | 1,089 | 2016-11-06T10:02:53.000Z | 2022-03-26T12:53:30.000Z | tests/modules/contrib/test_cmus.py | spxtr/bumblebee-status | 45125f39af8323775aeabf809ae5ae80cfe3ccd9 | [
"MIT"
] | 817 | 2016-11-05T05:42:39.000Z | 2022-03-25T19:43:52.000Z | tests/modules/contrib/test_cmus.py | spxtr/bumblebee-status | 45125f39af8323775aeabf809ae5ae80cfe3ccd9 | [
"MIT"
] | 317 | 2016-11-05T00:35:06.000Z | 2022-03-24T13:35:03.000Z | import pytest
def test_load_module():
__import__("modules.contrib.cmus")
| 13.166667 | 38 | 0.746835 | 10 | 79 | 5.3 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.139241 | 79 | 5 | 39 | 15.8 | 0.779412 | 0 | 0 | 0 | 0 | 0 | 0.25641 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0 | 0.666667 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
0354f24f09bc331743d810dd26f4402c865c8910 | 580 | py | Python | 3day/for05.py | jsjang93/joony | 62f7a325094c887212b894932263bf84500e0f03 | [
"MIT"
] | null | null | null | 3day/for05.py | jsjang93/joony | 62f7a325094c887212b894932263bf84500e0f03 | [
"MIT"
] | null | null | null | 3day/for05.py | jsjang93/joony | 62f7a325094c887212b894932263bf84500e0f03 | [
"MIT"
] | null | null | null | # for05.py
'''
1: *
2: **
3: ***
4: ****
5: *****
'''
for i in range(1,6):
print("{}: {}".format(i, "*"*i))
print("===========================")
for i in range(1,6,1):
print(i, end=': ')
for j in range(1, i+1):
print('*', end='')
print()
print("===========================")
for i in range(1,21):
print("{}".format(i), end=' ')
if i%5==0:
print()
print("===========================")
m=0
for i in range(1, 5):
for j in range(0, 5):
print("{}".format(i+j+m), end='\t')
print()
m += 4
| 10.357143 | 43 | 0.336207 | 79 | 580 | 2.468354 | 0.265823 | 0.215385 | 0.205128 | 0.225641 | 0.307692 | 0.246154 | 0 | 0 | 0 | 0 | 0 | 0.059952 | 0.281034 | 580 | 55 | 44 | 10.545455 | 0.407674 | 0.075862 | 0 | 0.3 | 0 | 0 | 0.192157 | 0.158824 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.55 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
035578fad79efd1750a49f6652ce3e2a544a9cda | 891 | py | Python | tests/kyu_8_tests/test_training_js_7_if_else_ternary.py | the-zebulan/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 40 | 2016-03-09T12:26:20.000Z | 2022-03-23T08:44:51.000Z | tests/kyu_8_tests/test_training_js_7_if_else_ternary.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | null | null | null | tests/kyu_8_tests/test_training_js_7_if_else_ternary.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 36 | 2016-11-07T19:59:58.000Z | 2022-03-31T11:18:27.000Z | import unittest
from katas.kyu_8.training_js_7_if_else_ternary import sale_hotdogs
class HotDogsTestCase(unittest.TestCase):
def test_equal_1(self):
self.assertEqual(sale_hotdogs(0), 0)
def test_equal_2(self):
self.assertEqual(sale_hotdogs(1), 100)
def test_equal_3(self):
self.assertEqual(sale_hotdogs(2), 200)
def test_equal_4(self):
self.assertEqual(sale_hotdogs(3), 300)
def test_equal_5(self):
self.assertEqual(sale_hotdogs(4), 400)
def test_equal_6(self):
self.assertEqual(sale_hotdogs(5), 475)
def test_equal_7(self):
self.assertEqual(sale_hotdogs(9), 855)
def test_equal_8(self):
self.assertEqual(sale_hotdogs(10), 900)
def test_equal_9(self):
self.assertEqual(sale_hotdogs(11), 990)
def test_equal_10(self):
self.assertEqual(sale_hotdogs(100), 9000)
| 24.75 | 66 | 0.690236 | 129 | 891 | 4.48062 | 0.317829 | 0.209343 | 0.207612 | 0.397924 | 0.519031 | 0 | 0 | 0 | 0 | 0 | 0 | 0.078762 | 0.20202 | 891 | 35 | 67 | 25.457143 | 0.734177 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.434783 | 1 | 0.434783 | false | 0 | 0.086957 | 0 | 0.565217 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ceee1063dd58b15acb47042b31b350efa859caf9 | 143 | py | Python | src/darknet/__init__.py | csmith49/maude | b6287230a1cfb5b785f8153910970acbf3077bfd | [
"MIT"
] | null | null | null | src/darknet/__init__.py | csmith49/maude | b6287230a1cfb5b785f8153910970acbf3077bfd | [
"MIT"
] | null | null | null | src/darknet/__init__.py | csmith49/maude | b6287230a1cfb5b785f8153910970acbf3077bfd | [
"MIT"
] | null | null | null | from .config import loadConfigDir
from .model import modelFromConfig
from .image import Image, imageFromFile
from .video import videoFromDevice | 35.75 | 39 | 0.853147 | 17 | 143 | 7.176471 | 0.588235 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111888 | 143 | 4 | 40 | 35.75 | 0.96063 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
3032b0a6a6a348cd0703f59fd127819b15ede6c7 | 35 | py | Python | backend/__init__.py | atharva-naik/XNLI-annotator | adf307259ec18036692cf436246d6bd63870d05c | [
"MIT"
] | null | null | null | backend/__init__.py | atharva-naik/XNLI-annotator | adf307259ec18036692cf436246d6bd63870d05c | [
"MIT"
] | null | null | null | backend/__init__.py | atharva-naik/XNLI-annotator | adf307259ec18036692cf436246d6bd63870d05c | [
"MIT"
] | null | null | null | # all the backend code resides here | 35 | 35 | 0.8 | 6 | 35 | 4.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.171429 | 35 | 1 | 35 | 35 | 0.965517 | 0.942857 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
3043ee7676d2a30d6b4300374d7e8fa11e5a4791 | 141 | py | Python | rdkit/Chem/fmcs/__init__.py | kazuyaujihara/rdkit | 06027dcd05674787b61f27ba46ec0d42a6037540 | [
"BSD-3-Clause"
] | 1,609 | 2015-01-05T02:41:13.000Z | 2022-03-30T21:57:24.000Z | rdkit/Chem/fmcs/__init__.py | kazuyaujihara/rdkit | 06027dcd05674787b61f27ba46ec0d42a6037540 | [
"BSD-3-Clause"
] | 3,412 | 2015-01-06T12:13:33.000Z | 2022-03-31T17:25:41.000Z | rdkit/Chem/fmcs/__init__.py | bp-kelley/rdkit | e0de7c9622ce73894b1e7d9568532f6d5638058a | [
"BSD-3-Clause"
] | 811 | 2015-01-11T03:33:48.000Z | 2022-03-28T11:57:49.000Z | """ Actual implementation of the FMCS algorithm
This code should be used by importing rdkit.Chem.MCS
"""
from rdkit.Chem.fmcs.fmcs import *
| 23.5 | 52 | 0.765957 | 22 | 141 | 4.909091 | 0.818182 | 0.166667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148936 | 141 | 5 | 53 | 28.2 | 0.9 | 0.680851 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
06339dfaf43161f06bfec864917addcf8ec8b161 | 28 | py | Python | pay.py | sdd1992/yeah-yeah | 6b14f3a00f291b246f837d1575e2d7caafe30a57 | [
"MIT"
] | null | null | null | pay.py | sdd1992/yeah-yeah | 6b14f3a00f291b246f837d1575e2d7caafe30a57 | [
"MIT"
] | null | null | null | pay.py | sdd1992/yeah-yeah | 6b14f3a00f291b246f837d1575e2d7caafe30a57 | [
"MIT"
] | null | null | null | num =100
num =200000000000
| 7 | 17 | 0.75 | 4 | 28 | 5.25 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.652174 | 0.178571 | 28 | 3 | 18 | 9.333333 | 0.26087 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
0663ffab2a1d2ed99b13d2e344686c7e26dff122 | 118 | py | Python | view/height.py | italoaalves/ed-arvores-e-busca | 54088c5fce77ad9a8857c80a78c1525d856863ba | [
"Apache-2.0"
] | null | null | null | view/height.py | italoaalves/ed-arvores-e-busca | 54088c5fce77ad9a8857c80a78c1525d856863ba | [
"Apache-2.0"
] | null | null | null | view/height.py | italoaalves/ed-arvores-e-busca | 54088c5fce77ad9a8857c80a78c1525d856863ba | [
"Apache-2.0"
] | null | null | null | def height_view(tree):
print("Height\n")
print(f'Tree height: {tree.height}')
input("ENTER to continue")
| 19.666667 | 40 | 0.644068 | 17 | 118 | 4.411765 | 0.647059 | 0.266667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.186441 | 118 | 5 | 41 | 23.6 | 0.78125 | 0 | 0 | 0 | 0 | 0 | 0.432203 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0 | 0.25 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
0672436a0fa3bda1745003bbc1738c0da84072e8 | 283 | py | Python | pip_services3_gcp/containers/__init__.py | pip-services3-python/pip-services3-gcp-python | ae41a8277cd11df9c736658919b7b3b8f4a6596d | [
"MIT"
] | null | null | null | pip_services3_gcp/containers/__init__.py | pip-services3-python/pip-services3-gcp-python | ae41a8277cd11df9c736658919b7b3b8f4a6596d | [
"MIT"
] | null | null | null | pip_services3_gcp/containers/__init__.py | pip-services3-python/pip-services3-gcp-python | ae41a8277cd11df9c736658919b7b3b8f4a6596d | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
__all__ = ['CloudFunctionRequestHelper', 'CloudFunction', 'CommandableCloudFunction']
from .CloudFunctionRequestHelper import CloudFunctionRequestHelper
from .CloudFunction import CloudFunction
from .CommandableCloudFunction import CommandableCloudFunction
| 35.375 | 85 | 0.833922 | 19 | 283 | 12.210526 | 0.473684 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003861 | 0.084806 | 283 | 7 | 86 | 40.428571 | 0.891892 | 0.074205 | 0 | 0 | 0 | 0 | 0.242308 | 0.192308 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.75 | 0 | 0.75 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
068aa047057ddbcbc793fcc9d8caef9f4c5d5ce1 | 30 | py | Python | chartilo/__init__.py | hyper-hronoz/Chartilo | 92c16f367846f7a43015099907cd5bfd4976ad07 | [
"MIT"
] | 1 | 2021-11-20T15:44:02.000Z | 2021-11-20T15:44:02.000Z | chartilo/__init__.py | hyper-hronoz/Chartilo | 92c16f367846f7a43015099907cd5bfd4976ad07 | [
"MIT"
] | null | null | null | chartilo/__init__.py | hyper-hronoz/Chartilo | 92c16f367846f7a43015099907cd5bfd4976ad07 | [
"MIT"
] | null | null | null | from .chartilo import Chartilo | 30 | 30 | 0.866667 | 4 | 30 | 6.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 30 | 1 | 30 | 30 | 0.962963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
06a182dcb314efe83876cb3cf08a3dac0fb4eba0 | 5,967 | py | Python | src/extensions/animals.py | MJxMRB/1 | 69a74b52b188eb9e410a4b6060bc558c9c11aa5f | [
"MIT"
] | 11 | 2021-08-08T16:32:50.000Z | 2022-03-28T08:24:02.000Z | src/extensions/animals.py | DeadManGTPS/wm_bot | 6b2233b4b35d81c6e1570e9a990d63031c74a913 | [
"MIT"
] | null | null | null | src/extensions/animals.py | DeadManGTPS/wm_bot | 6b2233b4b35d81c6e1570e9a990d63031c74a913 | [
"MIT"
] | 15 | 2021-08-08T14:37:56.000Z | 2022-02-04T19:09:28.000Z | """Animals Cog"""
import discord
from discord.ext import commands
class Animals(commands.Cog):
"""Sends a random cute picture of animals"""
def __init__(self, bot):
self.bot = bot
@commands.command(aliases=["kitty"], extras={"image": "https://i.imgur.com/J8vTsyK.gif"})
async def cat(self, ctx):
"""Sends a random random cute cat picture"""
url = "https://some-random-api.ml/animal/cat"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
await ctx.send(
embed=discord.Embed(title="Heres a cat picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["doggo", "puppy"], extras={"image": "https://i.imgur.com/nJIyoLq.gif"})
async def dog(self, ctx):
"""Sends a random random cute dog picture"""
url = "https://some-random-api.ml/animal/dog"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
await ctx.send(
embed=discord.Embed(title="Heres a dog picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["pnd"], extras={"image": "https://i.imgur.com/GjsQ5AB.gif"})
async def panda(self, ctx):
"""Sends a random random cute panda picture"""
url = "https://some-random-api.ml/animal/panda"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
await ctx.send(
embed=discord.Embed(title="Heres a panda picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["rdpnd"], extras={"image": "https://i.imgur.com/jgjohiu.gif"})
async def redpanda(self, ctx):
"""Sends a random random cute red panda picture"""
url = "https://some-random-api.ml/animal/red_panda"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
if not parsed_json.get("fact"):
return await ctx.send(embed=discord.Embed(title="Heres a red panda picture").set_image(url=img_url))
await ctx.send(
embed=discord.Embed(title="Heres a red panda picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["kl"], extras={"image": "https://i.imgur.com/y8VhA8d.gif"})
async def koala(self, ctx):
"""Sends a random cute koala picture"""
url = "https://some-random-api.ml/animal/koala"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
if not parsed_json.get("fact"):
return await ctx.send(embed=discord.Embed(title="Heres a koala picture").set_image(url=img_url))
await ctx.send(
embed=discord.Embed(title="Heres a koala picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["birb"], extras={"image": "https://i.imgur.com/wittKiF.gif"})
async def bird(self, ctx):
"""Sends a random cute bird picture"""
url = "https://some-random-api.ml/animal/birb"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
await ctx.send(
embed=discord.Embed(title="Heres a bird picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["rcn"], extras={"image": "https://i.imgur.com/u7xuVvG.gif"})
async def racoon(self, ctx):
"""Sends a random racoon picture"""
url = "https://some-random-api.ml/animal/racoon"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
if not parsed_json.get("fact"):
return await ctx.send(embed=discord.Embed(title="Heres a racoon picture").set_image(url=img_url))
await ctx.send(
embed=discord.Embed(title="Heres a racoon picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["kng"], extras={"image": "https://i.imgur.com/rPvwWVW.gif"})
async def kangaroo(self, ctx):
"Sends a random kangaroo picture"
url = "https://some-random-api.ml/animal/kangaroo"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
if not parsed_json.get("fact"):
return await ctx.send(embed=discord.Embed(title="Heres a kangaroo picture").set_image(url=img_url))
await ctx.send(
embed=discord.Embed(title="Heres a kangaroo picture")
.set_image(url=img_url)
.set_footer(text="Fun Fact: " + parsed_json["fact"])
)
@commands.command(aliases=["fx"], extras={"image": "https://i.imgur.com/eHN5GZT.gif"})
async def fox(self, ctx):
"Sends a random high quality fox picture"
url = "https://randomfox.ca/floof/"
async with self.bot.session.get(url) as response:
parsed_json = await response.json()
img_url = parsed_json["image"]
await ctx.send(embed=discord.Embed(title="Heres a fox picture").set_image(url=img_url))
def setup(bot):
"""Adds the cog to the bot"""
bot.add_cog(Animals(bot))
| 40.869863 | 112 | 0.608513 | 796 | 5,967 | 4.462312 | 0.11809 | 0.084459 | 0.043919 | 0.062218 | 0.840653 | 0.824606 | 0.741554 | 0.708896 | 0.648086 | 0.625 | 0 | 0.00133 | 0.243841 | 5,967 | 145 | 113 | 41.151724 | 0.785904 | 0.012402 | 0 | 0.491071 | 0 | 0 | 0.220032 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.017857 | false | 0 | 0.017857 | 0 | 0.080357 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
2301d0834618b36cae7e09c2bb489230e1c7bdbd | 91 | py | Python | test/test_main.py | tebriel/chrisbot | 113ed18993b762aa344709e0929f2d3ef85935fc | [
"Unlicense"
] | null | null | null | test/test_main.py | tebriel/chrisbot | 113ed18993b762aa344709e0929f2d3ef85935fc | [
"Unlicense"
] | null | null | null | test/test_main.py | tebriel/chrisbot | 113ed18993b762aa344709e0929f2d3ef85935fc | [
"Unlicense"
] | null | null | null | """Main module test"""
def test_batman():
"""The batman principle"""
assert True
| 13 | 30 | 0.615385 | 11 | 91 | 5 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.21978 | 91 | 6 | 31 | 15.166667 | 0.774648 | 0.406593 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 | 0.5 | true | 0 | 0 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
230bf08f897fb19c15fc39a6d6231703416d2d38 | 178 | py | Python | moduleFinder/countUpUsedModules/sample.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null | moduleFinder/countUpUsedModules/sample.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null | moduleFinder/countUpUsedModules/sample.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null |
from numeric.npmod import saynp
from numeric.scimod import say_hello
from visualization.pltmod import sayhello
def main():
print("Hi")
if __name__ == '__main__':
main() | 19.777778 | 41 | 0.741573 | 24 | 178 | 5.125 | 0.708333 | 0.178862 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.162921 | 178 | 9 | 42 | 19.777778 | 0.825503 | 0 | 0 | 0 | 0 | 0 | 0.05618 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | true | 0 | 0.428571 | 0 | 0.571429 | 0.142857 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
235c535a4acb9daff9c22ab16991210523631356 | 60 | py | Python | submission/artificial_idiot/evaluation/__init__.py | Dovermore/artificial_intelligence_project | 2d71afd241490b456dd58e71b8f1fa92e8e2f0b7 | [
"MIT"
] | null | null | null | submission/artificial_idiot/evaluation/__init__.py | Dovermore/artificial_intelligence_project | 2d71afd241490b456dd58e71b8f1fa92e8e2f0b7 | [
"MIT"
] | null | null | null | submission/artificial_idiot/evaluation/__init__.py | Dovermore/artificial_intelligence_project | 2d71afd241490b456dd58e71b8f1fa92e8e2f0b7 | [
"MIT"
] | null | null | null | from artificial_idiot.evaluation import evaluator_generator
| 30 | 59 | 0.916667 | 7 | 60 | 7.571429 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.066667 | 60 | 1 | 60 | 60 | 0.946429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
236c9da18b558cab9f58c98effc3e0a4d976c4d2 | 351 | py | Python | bio_embeddings/extract/annotations/__init__.py | neksa/bio_embeddings | cfb8edd455857d3d6b47effe65a11940d236445a | [
"MIT"
] | 2 | 2021-06-28T13:47:46.000Z | 2021-07-25T14:44:49.000Z | bio_embeddings/extract/annotations/__init__.py | Xinxinatg/bio_embeddings | 66e15676e70acac937482d99dc7eab4b24f4827a | [
"MIT"
] | null | null | null | bio_embeddings/extract/annotations/__init__.py | Xinxinatg/bio_embeddings | 66e15676e70acac937482d99dc7eab4b24f4827a | [
"MIT"
] | null | null | null | from bio_embeddings.extract.annotations.Disorder import Disorder
from bio_embeddings.extract.annotations.Location import Location
from bio_embeddings.extract.annotations.Membrane import Membrane
from bio_embeddings.extract.annotations.SecondaryStructure import SecondaryStructure
__all__ = ["Disorder", "Location", "Membrane", "SecondaryStructure"]
| 43.875 | 84 | 0.85755 | 37 | 351 | 7.918919 | 0.297297 | 0.095563 | 0.232082 | 0.327645 | 0.477816 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.068376 | 351 | 7 | 85 | 50.142857 | 0.896024 | 0 | 0 | 0 | 0 | 0 | 0.12 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.8 | 0 | 0.8 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
237adc73cfef21ed8bb1045628319c4931efa65e | 41 | py | Python | contrastverify/__init__.py | Contrast-Security-OSS/integration-verify-github-action | 537a2d0223a9c3ab294627e1f08787cf1892cd1c | [
"MIT"
] | null | null | null | contrastverify/__init__.py | Contrast-Security-OSS/integration-verify-github-action | 537a2d0223a9c3ab294627e1f08787cf1892cd1c | [
"MIT"
] | 8 | 2022-02-25T17:37:46.000Z | 2022-03-30T23:53:59.000Z | contrastverify/__init__.py | Contrast-Security-OSS/integration-verify-github-action | 537a2d0223a9c3ab294627e1f08787cf1892cd1c | [
"MIT"
] | 1 | 2022-02-23T19:20:14.000Z | 2022-02-23T19:20:14.000Z | from .verify import ContrastVerifyAction
| 20.5 | 40 | 0.878049 | 4 | 41 | 9 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.097561 | 41 | 1 | 41 | 41 | 0.972973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
88be5d71727e0476fc60e1a2a6d0d40bd51519ca | 186 | py | Python | exercicios/ex46.py | gabrielaraujo3/exercicios-python | 37a431854205e489cb7cede8fcae459bfef75a39 | [
"MIT"
] | null | null | null | exercicios/ex46.py | gabrielaraujo3/exercicios-python | 37a431854205e489cb7cede8fcae459bfef75a39 | [
"MIT"
] | null | null | null | exercicios/ex46.py | gabrielaraujo3/exercicios-python | 37a431854205e489cb7cede8fcae459bfef75a39 | [
"MIT"
] | null | null | null | from time import sleep
import emoji
for cont in range(10, -1, -1):
print(cont)
sleep(1)
print(emoji.emojize(":fireworks: :fireworks: :fireworks: :fireworks:", use_aliases=True))
| 26.571429 | 89 | 0.704301 | 27 | 186 | 4.814815 | 0.62963 | 0.415385 | 0.415385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031447 | 0.145161 | 186 | 6 | 90 | 31 | 0.786164 | 0 | 0 | 0 | 0 | 0 | 0.252688 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0.333333 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
001b675d89062787d69651f4dc1dd9779075a7b2 | 1,755 | py | Python | examples/掌控板代码/Bxy/发送消息-publish/main.py | vvlink/SIoT | ea759437e04ddb23567b921565f85c3682fd582a | [
"MIT"
] | 67 | 2019-05-04T05:04:32.000Z | 2022-03-18T14:34:56.000Z | examples/掌控板代码/Bxy/发送消息-publish/main.py | vvlink/SIoT | ea759437e04ddb23567b921565f85c3682fd582a | [
"MIT"
] | 7 | 2019-05-22T06:26:10.000Z | 2021-07-12T03:02:24.000Z | examples/掌控板代码/Bxy/发送消息-publish/main.py | vvlink/SIoT | ea759437e04ddb23567b921565f85c3682fd582a | [
"MIT"
] | 32 | 2019-06-03T06:23:30.000Z | 2021-08-29T22:43:20.000Z | # 功能：发布光线数据
# 实验：这个实验需要2个掌控板，一个发布光线数据一个订阅光线数据
# 发布的掌控板，给光线传感器不同的光照，光线强度将被发布到
# EasyIot的对应主题，供其他设备使用
#注意事项：这个实验需要2个掌控板，这是发布端代码
# 1.本实验可用EasyIot物联网，用户需要注册EasyIot账号，添加
# 2.本实验可用Siot物联网，用户搭建Siot服务器：https://github.com/vvlink/SIoT/blob/master/source/setup/02_run.rst
# 产品和设备，并将产品设备信息更新到这个示例中
from mpython import light
from Iot import Iot
from umqtt.simple import MQTTClient
from machine import Timer
import machine
import time
import json
import network
WIFI_SSID = 'yourSSID'#替换成你的WIFI热点名称
WIFI_PASSWORD = 'yourPASSWD'#替换成你的WIFI热点密码
IOT_SERVER = "server address" #EASYIOT的服务器为iot.dfrobot.com.cn；Siot地址为用户搭建的服务器的ip地址，例如：192.168.0.100
IOT_PORT = 1883
IOT_ClientID = "your ClientID"#替换成你的ClientID，可为空
IOT_UserName = "your UserName"#替换成你的UserName
IOT_PassWord = "your PassWord"#替换成你的PassWord
IOT_pubTopic = 'your PubTopic' #如果是siot，自定义的topic中需要添加"/"，例如:"abc/abc"
myIot = Iot(IOT_SERVER, IOT_UserName, IOT_ClientID, IOT_PassWord)
client = MQTTClient(myIot.client_id, myIot.mqttserver, port = IOT_PORT, user = myIot.username, password = myIot.password)
tim1 = Timer(1)
def connectWIFI():
station = network.WLAN(network.STA_IF)
station.active(True)
station.connect(WIFI_SSID,WIFI_PASSWORD)
while station.isconnected() == False:
pass
print('Connection successful')
print(station.ifconfig())
def restart():
time.sleep(10)
machine.reset()
def check(_):
try:
msg = {}
client.check_msg()
msg["light"] = light.read()
print(json.dumps(msg))
client.publish(IOT_pubTopic,json.dumps(msg))
lastTime = time.time()
except OSError as e:
tim1.deinit()
restart()
connectWIFI()
client.connect()
tim1.init(period=5000, mode=Timer.PERIODIC,callback=check)
while True:
pass
| 1,755 | 1,755 | 0.74188 | 220 | 1,755 | 5.822727 | 0.554545 | 0.020297 | 0.018735 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01996 | 0.14359 | 1,755 | 1 | 1,755 | 1,755 | 0.832335 | 0.990313 | 0 | 0.043478 | 0 | 0 | 0.08751 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.065217 | false | 0.152174 | 0.173913 | 0 | 0.23913 | 0.065217 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
0043559eb17aea52de35b13cffb8744477808898 | 133 | py | Python | canopy/sim_version_to_number.py | CanopySimulations/canopy-python | 9ec37e674e65d6fbef0402ac0c612c163d55631e | [
"MIT"
] | null | null | null | canopy/sim_version_to_number.py | CanopySimulations/canopy-python | 9ec37e674e65d6fbef0402ac0c612c163d55631e | [
"MIT"
] | 1 | 2022-01-31T10:18:08.000Z | 2022-01-31T10:18:08.000Z | canopy/sim_version_to_number.py | CanopySimulations/canopy-python | 9ec37e674e65d6fbef0402ac0c612c163d55631e | [
"MIT"
] | null | null | null |
def sim_version_to_number(sim_version: str):
if sim_version.startswith('1.'):
return int(sim_version[2:])
return 0
| 19 | 44 | 0.676692 | 20 | 133 | 4.2 | 0.65 | 0.47619 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028302 | 0.203008 | 133 | 6 | 45 | 22.166667 | 0.764151 | 0 | 0 | 0 | 0 | 0 | 0.015152 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
0052bca2edb7969f29052c2c9ccaa546a495a0a6 | 73 | py | Python | src/query_optimizer/test.py | alilakda/Eva | e3d447f81e1e47172e21758c059ad6f5ee21ffa4 | [
"Apache-2.0"
] | 1 | 2019-11-06T03:30:08.000Z | 2019-11-06T03:30:08.000Z | src/query_optimizer/test.py | alilakda/Eva | e3d447f81e1e47172e21758c059ad6f5ee21ffa4 | [
"Apache-2.0"
] | 1 | 2019-11-18T03:09:56.000Z | 2019-11-18T03:09:56.000Z | src/query_optimizer/test.py | asrayousuf/Eva | f652e5d398556055490c146f37e7a2d7a9d091f3 | [
"Apache-2.0"
] | null | null | null | import sys
print(sys.path)
import loaders
def test():
print("hi")
| 8.111111 | 15 | 0.657534 | 11 | 73 | 4.363636 | 0.727273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.205479 | 73 | 8 | 16 | 9.125 | 0.827586 | 0 | 0 | 0 | 0 | 0 | 0.027397 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | true | 0 | 0.4 | 0 | 0.6 | 0.4 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
cc3e87932e7049dce0e63ab7fec69b92475851cd | 37 | py | Python | tests/fixture_05.py | brianjbuck/noeval | 685fd2b057e967d5653c25f47f9875b98d7cc78b | [
"MIT"
] | null | null | null | tests/fixture_05.py | brianjbuck/noeval | 685fd2b057e967d5653c25f47f9875b98d7cc78b | [
"MIT"
] | null | null | null | tests/fixture_05.py | brianjbuck/noeval | 685fd2b057e967d5653c25f47f9875b98d7cc78b | [
"MIT"
] | null | null | null | import ast
ast.literal_eval("True")
| 9.25 | 24 | 0.756757 | 6 | 37 | 4.5 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.108108 | 37 | 3 | 25 | 12.333333 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0.108108 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
cc587ad07d074c1db06cc3cc538c599171dc2f8a | 143 | py | Python | app/wrapper/pynubank_wrapper/models/__init__.py | brunoanhaia/budget-planner | edb030591fd8425e1e4132f869693bb10b941771 | [
"MIT"
] | null | null | null | app/wrapper/pynubank_wrapper/models/__init__.py | brunoanhaia/budget-planner | edb030591fd8425e1e4132f869693bb10b941771 | [
"MIT"
] | 2 | 2022-03-02T14:10:53.000Z | 2022-03-17T22:56:25.000Z | app/wrapper/pynubank_wrapper/models/__init__.py | brunoanhaia/budget-planner | edb030591fd8425e1e4132f869693bb10b941771 | [
"MIT"
] | null | null | null | import pathlib
import sys
sys.path.append(str(pathlib.Path(__file__).parent))
from .account import *
from .card import *
from .user import *
| 15.888889 | 51 | 0.755245 | 21 | 143 | 4.952381 | 0.571429 | 0.192308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.132867 | 143 | 8 | 52 | 17.875 | 0.83871 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.833333 | 0 | 0.833333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
cc5b331105091093fac03ff2e0138723d26ad31e | 104 | py | Python | seqal/stoppers/__init__.py | tech-sketch/SeqAL | 05999f722438fbb418768393d8dc209a18383b6b | [
"MIT"
] | null | null | null | seqal/stoppers/__init__.py | tech-sketch/SeqAL | 05999f722438fbb418768393d8dc209a18383b6b | [
"MIT"
] | 20 | 2022-01-13T05:14:51.000Z | 2022-03-11T07:30:40.000Z | seqal/stoppers/__init__.py | tech-sketch/SeqAL | 05999f722438fbb418768393d8dc209a18383b6b | [
"MIT"
] | null | null | null | from .base import BaseStopper # noqa: F401
from .stopper import BudgetStopper, F1Stopper # noqa: F401
| 34.666667 | 59 | 0.769231 | 13 | 104 | 6.153846 | 0.692308 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.08046 | 0.163462 | 104 | 2 | 60 | 52 | 0.83908 | 0.201923 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
cc6c07cfe81f2108a9a6705b769db86bcc4f23fb | 3,204 | py | Python | private/julio/nasch/periodic_boundary_conditions/plot_time_vs_current.py | tachidok/cellular_automata | 73e3c15b14333835c4613edd98296cf5d7b58741 | [
"MIT"
] | null | null | null | private/julio/nasch/periodic_boundary_conditions/plot_time_vs_current.py | tachidok/cellular_automata | 73e3c15b14333835c4613edd98296cf5d7b58741 | [
"MIT"
] | null | null | null | private/julio/nasch/periodic_boundary_conditions/plot_time_vs_current.py | tachidok/cellular_automata | 73e3c15b14333835c4613edd98296cf5d7b58741 | [
"MIT"
] | null | null | null | import matplotlib.pyplot as plt
import numpy as np
Linewidth = 2;
# Density value
rho = 0.8
# -------------------------------------------------------------------------------------
# Density vs Current plots
# -------------------------------------------------------------------------------------
fig1, ax1 = plt.subplots()
filename = 'RESLT/current_vs_time_bp_0_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.0$', color='red', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.1_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.1$', color='blue', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.2_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.2$', color='green', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.3_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.3$', color='violet', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.4_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.4$', color='orange', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.5_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.5$', color='cyan', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.6_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.6$', color='yellow', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.7_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.7$', color='pink', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.8_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.8$', color='black', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_0.9_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 0.9$', color='lime', linestyle='solid', linewidth=Linewidth)
filename = 'RESLT/current_vs_time_bp_1_rho_' + str(rho) + '.dat'
density, current = np.loadtxt(filename, delimiter='\t', unpack=True)
ax1.plot(density, current, label=r'$bp = 1.0$', color='saddlebrown', linestyle='solid', linewidth=Linewidth)
ax1.grid()
#plt.xticks(np.arange(0,10,step=1))
#plt.yticks(np.arange(0,1.1,step=0.1))
#plt.xlim([0,10])
#plt.ylim([0,1])
ax1.set_xlabel(r'Time (t)')
ax1.set_ylabel(r'Current $(J)$')
ax1.set_title("Time vs Current")
ax1.legend()
plt.show()
| 47.820896 | 108 | 0.674157 | 468 | 3,204 | 4.467949 | 0.149573 | 0.147298 | 0.105213 | 0.115734 | 0.794835 | 0.794835 | 0.794835 | 0.780966 | 0.780966 | 0.780966 | 0 | 0.026424 | 0.090512 | 3,204 | 66 | 109 | 48.545455 | 0.691146 | 0.09769 | 0 | 0.25 | 0 | 0 | 0.237335 | 0.124566 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.045455 | 0 | 0.045455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ccc10423f672a339835c4fae8a9941c16fd70830 | 24 | py | Python | mag-python/mag/__init__.py | bootstrappersUNDP/scientific_collabs | 6c864893a03e47cde4ec99c2d06d08d0cc929e44 | [
"MIT"
] | 33 | 2017-09-19T09:17:56.000Z | 2021-11-17T13:32:02.000Z | mag-python/mag/__init__.py | bootstrappersUNDP/scientific_collabs | 6c864893a03e47cde4ec99c2d06d08d0cc929e44 | [
"MIT"
] | 4 | 2018-03-23T16:03:26.000Z | 2020-04-07T12:01:18.000Z | mag-python/mag/__init__.py | bootstrappersUNDP/scientific_collabs | 6c864893a03e47cde4ec99c2d06d08d0cc929e44 | [
"MIT"
] | 12 | 2017-09-07T13:54:19.000Z | 2021-02-28T05:40:42.000Z | from .inquirer import *
| 12 | 23 | 0.75 | 3 | 24 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 24 | 1 | 24 | 24 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
aebea3e80edcb907950a682d98ac9aac96993cbf | 89 | py | Python | api_permission/api_settings.py | jayvdb/django-api-permission | ba771314b4a9c5c2edc5161b423e257012be8922 | [
"MIT"
] | null | null | null | api_permission/api_settings.py | jayvdb/django-api-permission | ba771314b4a9c5c2edc5161b423e257012be8922 | [
"MIT"
] | null | null | null | api_permission/api_settings.py | jayvdb/django-api-permission | ba771314b4a9c5c2edc5161b423e257012be8922 | [
"MIT"
] | null | null | null | from django.conf import settings
API_PREFIX = getattr(settings, 'API_PREFIX', '/api/')
| 17.8 | 53 | 0.741573 | 12 | 89 | 5.333333 | 0.666667 | 0.34375 | 0.53125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.123596 | 89 | 4 | 54 | 22.25 | 0.820513 | 0 | 0 | 0 | 0 | 0 | 0.168539 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
aedb8a67f41702df398d18a834b8575272c8c75e | 73 | py | Python | some_module2/__init__.py | jasmith79/unit-testing-talk | 5cf02138848e032934439093ef659fa1fb03e611 | [
"MIT"
] | null | null | null | some_module2/__init__.py | jasmith79/unit-testing-talk | 5cf02138848e032934439093ef659fa1fb03e611 | [
"MIT"
] | null | null | null | some_module2/__init__.py | jasmith79/unit-testing-talk | 5cf02138848e032934439093ef659fa1fb03e611 | [
"MIT"
] | null | null | null | """__init__.py"""
from .some_module import not_quite_some_fun, is_valid
| 18.25 | 53 | 0.780822 | 12 | 73 | 4 | 0.916667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.09589 | 73 | 3 | 54 | 24.333333 | 0.727273 | 0.150685 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
aeed4a1f745aa1b6589a20633d294626c3caf0b6 | 1,774 | py | Python | src/getAttribute.py | wotjd4305/DatabaseProject | c6c6fc5006d54fb42fed18e8f655f847d998b751 | [
"MIT"
] | null | null | null | src/getAttribute.py | wotjd4305/DatabaseProject | c6c6fc5006d54fb42fed18e8f655f847d998b751 | [
"MIT"
] | 4 | 2018-10-10T03:57:09.000Z | 2018-10-29T07:42:42.000Z | src/getAttribute.py | getChan/DatabaseProject | 7dae1e8f3a998697e78fedc2d036f841f367d12b | [
"MIT"
] | 1 | 2018-10-09T02:44:36.000Z | 2018-10-09T02:44:36.000Z | from dbQuery import dbQuery, dfFilter, dfPlot
# 다른 노래 차트진입일
def chartInDays(title, artist, dbname):
# 쿼리문 입력
query = " SELECT * FROM zuzak."+dbname+" where title != \""+title+"\" and artist = \""+artist+"\" and YYMMDD<= (select YYMMDD from zuzak."+dbname+" where title = \""+title+"\" order by YYMMDD limit 1); "
Chartdf = dbQuery(query)
Chartdf = dfFilter(Chartdf)
# 쿼리결과 없으면
if Chartdf.empty:
return 0
# 쿼리 결과
else :
return len(Chartdf)
# 랭킹 상승 평균치
def rankIncreaseMean(title, dbname):
# 쿼리문 입력
query = """ SELECT * FROM zuzak."""+dbname+""" where title = \""""+title+"""\" and YYMMDD<=
(select YYMMDD from zuzak."""+dbname+""" where title = \""""+title+"""\" and cast(ranking as unsigned) <=5 order by YYMMDD limit 1); """
Chartdf = dbQuery(query)
Chartdf = dfFilter(Chartdf)
# 쿼리결과 없으면
if Chartdf.empty:
return 0
# 쿼리 결과
elif len(Chartdf) == 1 :
sum = 100-Chartdf['ranking'].iloc[0]
return sum
else:
sum = 0
a = len(Chartdf)
for i in range(1, a):
num = (Chartdf['ranking'].iloc[i-1]) - (Chartdf['ranking'].iloc[i])
sum = sum + num
return sum/(a-1)
# 5위 진입 전까지 일수
def rankInDays(title, dbname):
# 쿼리문 입력
query = """ SELECT * FROM zuzak."""+dbname+""" where title = \""""+title+"""\" and YYMMDD<=(SELECT YYMMDD FROM zuzak."""+dbname+""" where title = \""""+title+"""\" and cast(ranking as unsigned) <=5 order by YYMMDD limit 1); """
Chartdf = dbQuery(query)
Chartdf = dfFilter(Chartdf)
# 쿼리결과 없으면
if Chartdf.empty:
return 0
# 쿼리 결과
else :
return len(Chartdf) | 28.15873 | 232 | 0.542841 | 213 | 1,774 | 4.521127 | 0.28169 | 0.056075 | 0.093458 | 0.124611 | 0.714434 | 0.714434 | 0.714434 | 0.714434 | 0.714434 | 0.714434 | 0 | 0.014528 | 0.301578 | 1,774 | 63 | 233 | 28.15873 | 0.762712 | 0.05637 | 0 | 0.5 | 0 | 0 | 0.281588 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.088235 | false | 0 | 0.029412 | 0 | 0.323529 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
aef61e3748d7a396b6d8a44abe12c6b142819299 | 99 | py | Python | gaft/analysis/__init__.py | lizhaofu/gaft | 883ce7d5b7b48e9cb3d1d4819570c42b69f3f679 | [
"MIT"
] | null | null | null | gaft/analysis/__init__.py | lizhaofu/gaft | 883ce7d5b7b48e9cb3d1d4819570c42b69f3f679 | [
"MIT"
] | null | null | null | gaft/analysis/__init__.py | lizhaofu/gaft | 883ce7d5b7b48e9cb3d1d4819570c42b69f3f679 | [
"MIT"
] | null | null | null | from .console_output import ConsoleOutputAnalysis
from .fitness_store import FitnessStoreAnalysis
| 24.75 | 49 | 0.888889 | 10 | 99 | 8.6 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 99 | 3 | 50 | 33 | 0.955556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
4e11e86eb7b74ed44fedf2d77d3aa2fe95362088 | 220 | py | Python | player.py | Kappeh/Alpha-Zero-General | 344a2253bf48a3d12163258d27b1e81bfeb3b4f8 | [
"MIT"
] | null | null | null | player.py | Kappeh/Alpha-Zero-General | 344a2253bf48a3d12163258d27b1e81bfeb3b4f8 | [
"MIT"
] | null | null | null | player.py | Kappeh/Alpha-Zero-General | 344a2253bf48a3d12163258d27b1e81bfeb3b4f8 | [
"MIT"
] | null | null | null | class Player:
def __init__(self, game, name = 'Player'):
self.game = game
self.name = name
def get_name(self):
return self.name
def get_action(self, state_history):
pass | 20 | 46 | 0.577273 | 28 | 220 | 4.285714 | 0.464286 | 0.133333 | 0.166667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.327273 | 220 | 11 | 47 | 20 | 0.810811 | 0 | 0 | 0 | 0 | 0 | 0.027149 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.375 | false | 0.125 | 0 | 0.125 | 0.625 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 5 |
4e22ce5a1373df2082dcfd35b6ea4370c5213fe7 | 68 | py | Python | testing/example_scripts/fixtures/fill_fixtures/test_extend_fixture_conftest_conftest/pkg/conftest.py | markshao/pytest | 611b579d21f7e62b4c8ed54ab70fbfee7c6f5f64 | [
"MIT"
] | 9,225 | 2015-06-15T21:56:14.000Z | 2022-03-31T20:47:38.000Z | testing/example_scripts/fixtures/fill_fixtures/test_extend_fixture_conftest_conftest/pkg/conftest.py | markshao/pytest | 611b579d21f7e62b4c8ed54ab70fbfee7c6f5f64 | [
"MIT"
] | 7,794 | 2015-06-15T21:06:34.000Z | 2022-03-31T10:56:54.000Z | testing/example_scripts/fixtures/fill_fixtures/test_extend_fixture_conftest_conftest/pkg/conftest.py | markshao/pytest | 611b579d21f7e62b4c8ed54ab70fbfee7c6f5f64 | [
"MIT"
] | 2,598 | 2015-06-15T21:42:39.000Z | 2022-03-29T13:48:22.000Z | import pytest
@pytest.fixture
def spam(spam):
return spam * 2
| 9.714286 | 19 | 0.691176 | 10 | 68 | 4.7 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018868 | 0.220588 | 68 | 6 | 20 | 11.333333 | 0.867925 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0.25 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
9d6cb99a303a416fa2b91f774aac1941ff39379c | 277 | py | Python | specHdl/rawdata/LookupManagePI.py | huhub/prototypeTester | 3ebb1af5afef26c678fad8d36f945ca2fd804b7d | [
"Apache-2.0"
] | null | null | null | specHdl/rawdata/LookupManagePI.py | huhub/prototypeTester | 3ebb1af5afef26c678fad8d36f945ca2fd804b7d | [
"Apache-2.0"
] | null | null | null | specHdl/rawdata/LookupManagePI.py | huhub/prototypeTester | 3ebb1af5afef26c678fad8d36f945ca2fd804b7d | [
"Apache-2.0"
] | null | null | null | LookupManage = ['cuMacHit', 'cuMacIdx', 'cuMacPcpHit', 'cuMacPcpIdx', 'cuIpDscpHit', 'cuIpDscpIdx', 'cuIpSportHit', 'cuIpSportIdx', 'cuIpDportHit', 'cuIpDportIdx', 'hostRouteLeftHit', 'hostRouteRightHit', 'ipRouteLookup', 'ipRouteIdx', 'macDaLValid', 'macDaRValid', 'macDaIdx'] | 277 | 277 | 0.743682 | 18 | 277 | 11.444444 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.064982 | 277 | 1 | 277 | 277 | 0.795367 | 0 | 0 | 0 | 0 | 0 | 0.697842 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
9dcd72e762c5ea5f5f7fb861915d2040a0acfcdc | 66 | py | Python | ovl/directions/__init__.py | frc1937/ovl | 1954edf0ab946dbb42d90eba1dac97eeb157c567 | [
"Apache-2.0"
] | 1 | 2021-05-13T12:15:29.000Z | 2021-05-13T12:15:29.000Z | ovl/directions/__init__.py | frc1937/ovl | 1954edf0ab946dbb42d90eba1dac97eeb157c567 | [
"Apache-2.0"
] | null | null | null | ovl/directions/__init__.py | frc1937/ovl | 1954edf0ab946dbb42d90eba1dac97eeb157c567 | [
"Apache-2.0"
] | null | null | null | from .directing_functions import *
from .director import Director
| 22 | 34 | 0.833333 | 8 | 66 | 6.75 | 0.625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121212 | 66 | 2 | 35 | 33 | 0.931034 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
9dec5125f2b2fdddee7e660e823a3609317d4bbc | 58 | py | Python | jivago/wsgi/invocation/missing_route_invocation_argument.py | keotl/jivago | 892dfb0cae773e36245083c3e56f0f8523145523 | [
"MIT"
] | 12 | 2018-03-19T20:57:44.000Z | 2020-01-27T14:11:24.000Z | jivago/wsgi/invocation/missing_route_invocation_argument.py | keotl/jivago | 892dfb0cae773e36245083c3e56f0f8523145523 | [
"MIT"
] | 73 | 2018-04-20T22:26:00.000Z | 2021-12-01T14:17:37.000Z | jivago/wsgi/invocation/missing_route_invocation_argument.py | keotl/jivago | 892dfb0cae773e36245083c3e56f0f8523145523 | [
"MIT"
] | 1 | 2019-02-28T13:33:45.000Z | 2019-02-28T13:33:45.000Z | class MissingRouteInvocationArgument(Exception):
pass
| 19.333333 | 48 | 0.827586 | 4 | 58 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.12069 | 58 | 2 | 49 | 29 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
9df1236faf316774fcf1ad488e78d2c6f24b829d | 105 | py | Python | cwltool/errors.py | codelithic/cwltool | a294ac76f7182ffd6ba13c0e2a699644f808385b | [
"Apache-2.0"
] | 2 | 2017-07-06T13:25:23.000Z | 2017-07-06T13:26:15.000Z | cwltool/errors.py | codelithic/cwltool | a294ac76f7182ffd6ba13c0e2a699644f808385b | [
"Apache-2.0"
] | 1 | 2017-09-08T18:32:41.000Z | 2017-11-30T18:28:43.000Z | cwltool/errors.py | codelithic/cwltool | a294ac76f7182ffd6ba13c0e2a699644f808385b | [
"Apache-2.0"
] | 2 | 2021-10-01T10:08:32.000Z | 2021-10-01T11:53:48.000Z | class WorkflowException(Exception):
pass
class UnsupportedRequirement(WorkflowException):
pass
| 15 | 48 | 0.790476 | 8 | 105 | 10.375 | 0.625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152381 | 105 | 6 | 49 | 17.5 | 0.932584 | 0 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
0603cb1938693c35e7487a990489385215cc57b6 | 101 | py | Python | source/exceptions/TooManyPackagesError.py | Gwindalmir/PackageRouting | 8bc518dd60b0c8cb5919b7d7e49dc25c184b19c5 | [
"MIT"
] | null | null | null | source/exceptions/TooManyPackagesError.py | Gwindalmir/PackageRouting | 8bc518dd60b0c8cb5919b7d7e49dc25c184b19c5 | [
"MIT"
] | null | null | null | source/exceptions/TooManyPackagesError.py | Gwindalmir/PackageRouting | 8bc518dd60b0c8cb5919b7d7e49dc25c184b19c5 | [
"MIT"
] | null | null | null | from .Error import Error
class TooManyPackagesError(Error):
"""Truck has too many packages."""
| 16.833333 | 38 | 0.722772 | 12 | 101 | 6.083333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.168317 | 101 | 5 | 39 | 20.2 | 0.869048 | 0.277228 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
060652f171c23e9869411002af995a995785a22d | 39 | py | Python | data/exceptions.py | i3Cheese/MatBoy | 29dd65f07393087758179d14d4b40d5974816759 | [
"WTFPL"
] | 10 | 2020-04-24T02:39:22.000Z | 2021-07-22T13:12:55.000Z | data/exceptions.py | i3Cheese/MatBoy | 29dd65f07393087758179d14d4b40d5974816759 | [
"WTFPL"
] | null | null | null | data/exceptions.py | i3Cheese/MatBoy | 29dd65f07393087758179d14d4b40d5974816759 | [
"WTFPL"
] | 4 | 2020-05-31T12:34:55.000Z | 2020-06-25T17:35:43.000Z | class StatusError(Exception):
pass
| 13 | 29 | 0.74359 | 4 | 39 | 7.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.179487 | 39 | 2 | 30 | 19.5 | 0.90625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
888789628887ff94953691d7e3417ada503c9fcb | 8,688 | py | Python | boilermaker/cpp/gen_containersSerializeToHumon.py | spacemeat/boilermaker | f5ffb308d426806f098fdb9dc34327454dab9cf6 | [
"MIT"
] | null | null | null | boilermaker/cpp/gen_containersSerializeToHumon.py | spacemeat/boilermaker | f5ffb308d426806f098fdb9dc34327454dab9cf6 | [
"MIT"
] | null | null | null | boilermaker/cpp/gen_containersSerializeToHumon.py | spacemeat/boilermaker | f5ffb308d426806f098fdb9dc34327454dab9cf6 | [
"MIT"
] | null | null | null | def gen_builtIn(self):
if 'humon|builtIn' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|builtIn'] = None
it = self.indent()
src = f'''
{it}template <class T>
{it}struct HumonFormat : public SerializedFormat<T>
{it}{{
{it}{it}HumonFormat(T const & t)
{it}{it}: SerializedFormat<T>(t)
{it}{it}{{ }}
{it}}};
{it}template <class T>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<T> const & obj)
{it}{{
{it}{it}out << * obj;
{it}{it}return out;
{it}}}'''
self.appendSrc('serializerFormatWrappersDecl', src)
def gen_array(self):
if 'humon|array' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|array'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'array', '#include <array>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class T, unsigned long N>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::array<T, N>> const & obj)
{it}{{
{it}{it}out << "[ ";
{it}{it}for (std::size_t i = 0; i < N; ++i)
{it}{it}{{
{it}{it}{it}out << HumonFormat( (* obj)[i] ) << " ";
{it}{it}}}
{it}{it}out << "]";
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_pair(self):
if 'humon|pair' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|pair'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'pair', '#include <utility>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class T0, class T1>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::pair<T0, T1>> const & obj)
{it}{{
{it}{it}out << '[' << HumonFormat(std::get<0>(* obj)) << ' ' << HumonFormat(std::get<1>(* obj)) << ']';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_tuple(self):
if 'humon|tuple' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|tuple'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'tuple', '#include <tuple>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class... Ts>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::tuple<Ts...>> const & obj)
{it}{{
{it}{it}out << "[ ";
{it}{it}apply(
{it}{it}{it}[&out](auto &&... args)
{it}{it}{it}{it}{{ ((out << HumonFormat(args) << ' '), ...); }},
{it}{it}{it}* obj);
{it}{it}out << "]";
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_vector(self):
if 'humon|vector' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|vector'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'vector', '#include <vector>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class T, class A>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::vector<T, A>> const & obj)
{it}{{
{it}{it}out << "[ ";
{it}{it}for (auto const & elem : * obj)
{it}{it}{{
{it}{it}{it}out << HumonFormat(elem) << ' ';
{it}{it}}}
{it}{it}out << ']';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_set(self):
if 'humon|set' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|set'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'set', '#include <set>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class K, class C, class A>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::set<K, C, A>> const & obj)
{it}{{
{it}{it}out << "[ ";
{it}{it}for (auto const & elem : * obj)
{it}{it}{{
{it}{it}{it}out << HumonFormat(elem) << ' ';
{it}{it}}}
{it}{it}out << ']';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_unordered_set(self):
if 'humon|unordered_set' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|unordered_set'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'unordered_set', '#include <unordered_set>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class K, class H, class E, class A>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::unordered_set<K, H, E, A>> const & obj)
{it}{{
{it}{it}out << "[ ";
{it}{it}for (auto const & elem : * obj)
{it}{it}{{
{it}{it}{it}out << HumonFormat(elem) << ' ';
{it}{it}}}
{it}{it}out << ']';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_map(self):
if 'humon|map' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|map'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'map', '#include <map>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class K, class T, class C, class A>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::map<K, T, C, A>> const & obj)
{it}{{
{it}{it}out << "{{ ";
{it}{it}for (auto const & elem : * obj)
{it}{it}{{
{it}{it}{it}out << HumonFormat(elem.first) << ": " << HumonFormat(elem.second) << ' ';
{it}{it}}}
{it}{it}out << '}}';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_unordered_map(self):
if 'humon|unordered_map' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|unordered_map'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'unordered_map', '#include <unordered_map>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class K, class T, class H, class E, class A>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::unordered_map<K, T, H, E, A>> const & obj)
{it}{{
{it}{it}out << "{{ ";
{it}{it}for (auto const & elem : * obj)
{it}{it}{{
{it}{it}{it}out << HumonFormat(elem.first) << ": " << HumonFormat(elem.second) << ' ';
{it}{it}}}
{it}{it}out << '}}';
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_optional(self):
if 'humon|optional' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|optional'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'optional', '#include <optional>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class T>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::optional<T>> const & obj)
{it}{{
{it}{it}if (obj->has_value())
{it}{it}{it}{{ out << HumonFormat(** obj); }}
{it}{it}else
{it}{it}{it}{{ out << '_'; }}
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
def gen_variant(self):
if 'humon|variant' in self.containersSerializerTypes:
return
self.containersSerializerTypes['humon|variant'] = None
it = self.indent()
self.includeForType('humon|serializersDecl', 'variant', '#include <variant>')
self.includeForType('humon|serializersDecl', 'ostream', '#include <iostream>')
self.includeOutputFile('humon|serializersDecl', 'commonHeader')
src = f'''
{it}template <class... Ts>
{it}std::ostream & operator << (std::ostream & out, HumonFormat<std::variant<Ts...>> const & obj)
{it}{{
{it}{it}constexpr auto const names = VariantTypeNames<std::variant<Ts...>>::names;
{it}{it}
{it}{it}std::visit(
{it}{it}{it}[&](auto && o)
{it}{it}{it}{it}{{ out << HumonFormat(o) << " @type: " << names[obj->index()]; }},
{it}{it}{it}* obj);
{it}{it}return out;
{it}}}'''
self.appendSrc('humon|serializersDecl', src)
| 29.154362 | 111 | 0.638582 | 1,052 | 8,688 | 5.249049 | 0.074144 | 0.080406 | 0.060848 | 0.042376 | 0.842267 | 0.839913 | 0.812206 | 0.713872 | 0.588917 | 0.522456 | 0 | 0.000946 | 0.148135 | 8,688 | 297 | 112 | 29.252525 | 0.74517 | 0 | 0 | 0.626126 | 0 | 0.076577 | 0.624655 | 0.158955 | 0 | 0 | 0 | 0 | 0 | 1 | 0.04955 | false | 0 | 0 | 0 | 0.099099 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
88b788771025589033c8264ca4560fc76058ca64 | 126 | py | Python | cl/asr_models/__init__.py | aalto-speech/speechbrain-cl | 57263893bc79ae3bd4358984d81bf9bb393c5886 | [
"MIT"
] | null | null | null | cl/asr_models/__init__.py | aalto-speech/speechbrain-cl | 57263893bc79ae3bd4358984d81bf9bb393c5886 | [
"MIT"
] | null | null | null | cl/asr_models/__init__.py | aalto-speech/speechbrain-cl | 57263893bc79ae3bd4358984d81bf9bb393c5886 | [
"MIT"
] | null | null | null | from .asr_aku import ASR_Aku as ASR # this is the main Brain.
from .asr_base import ASR_Old
from .asr_w2v2 import AsrWav2Vec2 | 42 | 62 | 0.801587 | 24 | 126 | 4 | 0.583333 | 0.21875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.037736 | 0.15873 | 126 | 3 | 63 | 42 | 0.867925 | 0.18254 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
ee34b14bd37b3ca21be5bebd29821ae973d26eb0 | 88 | py | Python | core/utils/helper.py | DipeshAggarwal/PneumoniaNet | 29aea7189fc97d7262d2abf1ab5c2d33f476c684 | [
"MIT"
] | null | null | null | core/utils/helper.py | DipeshAggarwal/PneumoniaNet | 29aea7189fc97d7262d2abf1ab5c2d33f476c684 | [
"MIT"
] | null | null | null | core/utils/helper.py | DipeshAggarwal/PneumoniaNet | 29aea7189fc97d7262d2abf1ab5c2d33f476c684 | [
"MIT"
] | null | null | null | def info(msg):
print("[INFO] " + msg)
def warn(msg):
print("[WARNING] " + msg)
| 14.666667 | 29 | 0.534091 | 12 | 88 | 3.916667 | 0.5 | 0.297872 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.238636 | 88 | 5 | 30 | 17.6 | 0.701493 | 0 | 0 | 0 | 0 | 0 | 0.193182 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0 | 0.5 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
c9eb313136b5bd0f3b57bad53a5c0e197bf26a71 | 83 | py | Python | loadbalancer_interface/__init__.py | juju-solutions/loadbalancer-interface | ee84fb93ea52e55506f267cde28935df7d60a16d | [
"Apache-2.0"
] | null | null | null | loadbalancer_interface/__init__.py | juju-solutions/loadbalancer-interface | ee84fb93ea52e55506f267cde28935df7d60a16d | [
"Apache-2.0"
] | 2 | 2021-01-19T22:29:02.000Z | 2021-03-12T16:55:06.000Z | loadbalancer_interface/__init__.py | juju-solutions/loadbalancer-interface | ee84fb93ea52e55506f267cde28935df7d60a16d | [
"Apache-2.0"
] | null | null | null | from .requires import LBProvider # noqa
from .provides import LBConsumers # noqa
| 27.666667 | 41 | 0.783133 | 10 | 83 | 6.5 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.168675 | 83 | 2 | 42 | 41.5 | 0.942029 | 0.108434 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
4e57f401e3f1743c9bde3e50a0abbeb85adf0eba | 624 | py | Python | tests/adventofcode/year_2015/test_day_15_2015.py | Frazzer951/Advent-Of-Code | 419a6b7915a529fd49215639db79dcf5bde9cab7 | [
"MIT"
] | null | null | null | tests/adventofcode/year_2015/test_day_15_2015.py | Frazzer951/Advent-Of-Code | 419a6b7915a529fd49215639db79dcf5bde9cab7 | [
"MIT"
] | 2 | 2022-02-02T15:59:34.000Z | 2022-02-02T15:59:44.000Z | tests/adventofcode/year_2015/test_day_15_2015.py | Frazzer951/Advent-Of-Code | 419a6b7915a529fd49215639db79dcf5bde9cab7 | [
"MIT"
] | null | null | null | from adventofcode.year_2015.day_15_2015 import part_one
from adventofcode.year_2015.day_15_2015 import part_two
def test_part_one():
assert 62842880 == part_one(
[
"Butterscotch: capacity -1, durability -2, flavor 6, texture 3, calories 8",
"Cinnamon: capacity 2, durability 3, flavor -2, texture -1, calories 3",
]
)
def test_part_two():
assert 57600000 == part_two(
[
"Butterscotch: capacity -1, durability -2, flavor 6, texture 3, calories 8",
"Cinnamon: capacity 2, durability 3, flavor -2, texture -1, calories 3",
]
)
| 29.714286 | 88 | 0.628205 | 80 | 624 | 4.725 | 0.3375 | 0.055556 | 0.10582 | 0.126984 | 0.798942 | 0.798942 | 0.798942 | 0.798942 | 0.798942 | 0.571429 | 0 | 0.123348 | 0.272436 | 624 | 20 | 89 | 31.2 | 0.709251 | 0 | 0 | 0.25 | 0 | 0 | 0.455128 | 0 | 0 | 0 | 0 | 0 | 0.125 | 1 | 0.125 | true | 0 | 0.125 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
4e6cc45b9cf3de11f7faf4208d5561de82614300 | 17,828 | py | Python | fn_create_webex_meeting/fn_create_webex_meeting/util/customize.py | esirt14/resilient-community-apps | 4925ebd5ce8762717af76e47b64faa3bb341c922 | [
"MIT"
] | null | null | null | fn_create_webex_meeting/fn_create_webex_meeting/util/customize.py | esirt14/resilient-community-apps | 4925ebd5ce8762717af76e47b64faa3bb341c922 | [
"MIT"
] | null | null | null | fn_create_webex_meeting/fn_create_webex_meeting/util/customize.py | esirt14/resilient-community-apps | 4925ebd5ce8762717af76e47b64faa3bb341c922 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""Generate the Resilient customizations required for fn_create_webex_meeting"""
from __future__ import print_function
from resilient_circuits.util import *
def customization_data(client=None):
"""Produce any customization definitions (types, fields, message destinations, etc)
that should be installed by `resilient-circuits customize`
"""
# This import data contains:
# Function inputs:
# webex_meeting_agenda
# webex_meeting_end_time
# webex_meeting_name
# webex_meeting_password
# webex_meeting_start_time
# Message Destinations:
# fn_create_webex_meeting
# Functions:
# fn_create_webex_meeting
# Workflows:
# example_create_webex_meeting
# Rules:
# Example: Create WebEx Meeting: Incident
yield ImportDefinition(u"""
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"""
)
| 70.188976 | 87 | 0.969823 | 345 | 17,828 | 50.026087 | 0.886957 | 0.006953 | 0.005215 | 0.003476 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.124554 | 0.024568 | 17,828 | 253 | 88 | 70.466403 | 0.867913 | 0.033991 | 0 | 0 | 1 | 0 | 0.985859 | 0.972998 | 0 | 1 | 0 | 0 | 0 | 1 | 0.004425 | false | 0 | 0.013274 | 0 | 0.017699 | 0.004425 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
14c21b64b422045f467121036d6761b053f4f39f | 42 | py | Python | helloBoulder.py | SaishRedkar/HelloBoulder | 42721d5cce16e0c303341d9db40bfce8bc35e0af | [
"MIT"
] | null | null | null | helloBoulder.py | SaishRedkar/HelloBoulder | 42721d5cce16e0c303341d9db40bfce8bc35e0af | [
"MIT"
] | null | null | null | helloBoulder.py | SaishRedkar/HelloBoulder | 42721d5cce16e0c303341d9db40bfce8bc35e0af | [
"MIT"
] | null | null | null | #!/usr/bin/python
print " Hello Boulder"
| 10.5 | 22 | 0.690476 | 6 | 42 | 4.833333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 42 | 3 | 23 | 14 | 0.805556 | 0.380952 | 0 | 0 | 0 | 0 | 0.56 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 1 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
14e15ab336413c55c9867f150dadce43ec1e5d4e | 136 | py | Python | python/dragonradio-tools/dragonradio/tools/logging/__init__.py | drexelwireless/dragonradio | 885abd68d56af709e7a53737352641908005c45b | [
"MIT"
] | 8 | 2020-12-05T20:30:54.000Z | 2022-01-22T13:32:14.000Z | python/dragonradio-tools/dragonradio/tools/logging/__init__.py | drexelwireless/dragonradio | 885abd68d56af709e7a53737352641908005c45b | [
"MIT"
] | 3 | 2020-10-28T22:15:27.000Z | 2021-01-27T14:43:41.000Z | python/dragonradio-tools/dragonradio/tools/logging/__init__.py | drexelwireless/dragonradio | 885abd68d56af709e7a53737352641908005c45b | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
# Copyright 2018-2020 Drexel University
# Author: Geoffrey Mainland <mainland@drexel.edu>
from .logging import *
| 27.2 | 49 | 0.772059 | 18 | 136 | 5.833333 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.075 | 0.117647 | 136 | 4 | 50 | 34 | 0.8 | 0.786765 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
14e5f09bcb56efc1beb2f55195633df651cbc4f4 | 64 | py | Python | peachbox/fs/__init__.py | philipppahl/peachbox | 39dad31d56fd9096684e8cf12fab678b3b65d10b | [
"Apache-2.0"
] | null | null | null | peachbox/fs/__init__.py | philipppahl/peachbox | 39dad31d56fd9096684e8cf12fab678b3b65d10b | [
"Apache-2.0"
] | null | null | null | peachbox/fs/__init__.py | philipppahl/peachbox | 39dad31d56fd9096684e8cf12fab678b3b65d10b | [
"Apache-2.0"
] | null | null | null | from .local_fs import LocalFs
from .amazon_dfs import AmazonDfs
| 21.333333 | 33 | 0.84375 | 10 | 64 | 5.2 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 64 | 2 | 34 | 32 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
091d38436bb6ab82c27206a6452d25ee9835a3e4 | 638 | py | Python | face_web/run.py | Face-Recognition-Learning-Group/face_service | c23a8519cbf0f0f6297d7b43a5db8077438c58dd | [
"Apache-2.0"
] | 6 | 2021-05-19T06:48:35.000Z | 2021-11-09T11:52:11.000Z | face_web/run.py | VSOURCE-Platform/VSOURCE_FACE_PLATFORM | c23a8519cbf0f0f6297d7b43a5db8077438c58dd | [
"Apache-2.0"
] | 1 | 2021-05-09T08:29:39.000Z | 2021-05-09T08:29:39.000Z | face_web/run.py | VSOURCE-Platform/VSOURCE_FACE_PLATFORM | c23a8519cbf0f0f6297d7b43a5db8077438c58dd | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# @Author : Ecohnoch(xcy)
# @File : run.py
# @Function : TODO
from app import app
from pages import page_print
from login.app.web_login import login_print
from face_service import face_service_print
from speaker_service import speaker_service_print
from face_detection_service import face_detection_service_print
app.register_blueprint(page_print)
app.register_blueprint(login_print)
app.register_blueprint(face_service_print)
app.register_blueprint(speaker_service_print)
app.register_blueprint(face_detection_service_print)
if __name__ == '__main__':
app.run(host='0.0.0.0', port=12349, debug=True)
| 30.380952 | 63 | 0.808777 | 94 | 638 | 5.106383 | 0.361702 | 0.15 | 0.166667 | 0.260417 | 0.26875 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017483 | 0.103448 | 638 | 20 | 64 | 31.9 | 0.821678 | 0.130094 | 0 | 0 | 0 | 0 | 0.027273 | 0 | 0 | 0 | 0 | 0.05 | 0 | 1 | 0 | true | 0 | 0.461538 | 0 | 0.461538 | 0.769231 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 5 |
093c73f9e2d703bbf460302e01fe607ff9cb9d9f | 311 | py | Python | src/api/pdi/application/dashboard/GetDataOperationJobWidget/GetDataOperationJobWidgetResponse.py | ahmetcagriakca/pythondataintegrator | 079b968d6c893008f02c88dbe34909a228ac1c7b | [
"MIT"
] | 1 | 2020-12-18T21:37:28.000Z | 2020-12-18T21:37:28.000Z | src/api/pdi/application/dashboard/GetDataOperationJobWidget/GetDataOperationJobWidgetResponse.py | ahmetcagriakca/pythondataintegrator | 079b968d6c893008f02c88dbe34909a228ac1c7b | [
"MIT"
] | null | null | null | src/api/pdi/application/dashboard/GetDataOperationJobWidget/GetDataOperationJobWidgetResponse.py | ahmetcagriakca/pythondataintegrator | 079b968d6c893008f02c88dbe34909a228ac1c7b | [
"MIT"
] | 1 | 2020-12-18T21:37:31.000Z | 2020-12-18T21:37:31.000Z | from typing import List
from pdip.cqrs.decorators import responseclass
from pdi.application.dashboard.GetDataOperationJobWidget.GetDataOperationJobWidgetDto import \
GetDataOperationJobWidgetDto
@responseclass
class GetDataOperationJobWidgetResponse:
Data: List[GetDataOperationJobWidgetDto] = None
| 25.916667 | 94 | 0.855305 | 25 | 311 | 10.64 | 0.68 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.102894 | 311 | 11 | 95 | 28.272727 | 0.953405 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.428571 | 0 | 0.714286 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
11a60168a01373d1c718d30489eb2a9200ed2366 | 39 | py | Python | processors/BasicProcessor.py | JohnTheNerd/PySarra | 6d9afc17b43b8d83c8198d810c64a4119a91ffd2 | [
"Unlicense"
] | 2 | 2019-05-03T01:29:36.000Z | 2020-02-14T14:54:02.000Z | processors/BasicProcessor.py | JohnTheNerd/PySarra | 6d9afc17b43b8d83c8198d810c64a4119a91ffd2 | [
"Unlicense"
] | 4 | 2018-07-25T15:10:49.000Z | 2020-07-31T00:25:47.000Z | processors/BasicProcessor.py | JohnTheNerd/PySarra | 6d9afc17b43b8d83c8198d810c64a4119a91ffd2 | [
"Unlicense"
] | null | null | null | def process(message):
print(message)
| 13 | 21 | 0.74359 | 5 | 39 | 5.8 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.128205 | 39 | 2 | 22 | 19.5 | 0.852941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0 | 0.5 | 0.5 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
eeab1ddca5eec400d17d59f6be5d31e6f9a5a711 | 162 | py | Python | src/yellowdog_client/model/attribute_definition.py | yellowdog/yellowdog-sdk-python-public | da69a7d6e45c92933e34fefcaef8b5d98dcd6036 | [
"Apache-2.0"
] | null | null | null | src/yellowdog_client/model/attribute_definition.py | yellowdog/yellowdog-sdk-python-public | da69a7d6e45c92933e34fefcaef8b5d98dcd6036 | [
"Apache-2.0"
] | null | null | null | src/yellowdog_client/model/attribute_definition.py | yellowdog/yellowdog-sdk-python-public | da69a7d6e45c92933e34fefcaef8b5d98dcd6036 | [
"Apache-2.0"
] | null | null | null | from dataclasses import dataclass, field
from .named import Named
@dataclass
class AttributeDefinition(Named):
type: str = field(default=None, init=False)
| 18 | 47 | 0.771605 | 20 | 162 | 6.25 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148148 | 162 | 8 | 48 | 20.25 | 0.905797 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.4 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
eeb9d6784815e30e711d02b54152a2d5a081ec85 | 144 | py | Python | shorturls/admin.py | sjy5386/subshorts | d8170ee4a66989c3e852f86aa83bab6341e3aa10 | [
"MIT"
] | 3 | 2022-03-08T19:02:41.000Z | 2022-03-16T23:04:37.000Z | shorturls/admin.py | sjy5386/subshorts | d8170ee4a66989c3e852f86aa83bab6341e3aa10 | [
"MIT"
] | 5 | 2022-03-17T02:16:52.000Z | 2022-03-18T02:55:25.000Z | shorturls/admin.py | sjy5386/subshorts | d8170ee4a66989c3e852f86aa83bab6341e3aa10 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import ShortUrl, BlockedDomain
admin.site.register(ShortUrl)
admin.site.register(BlockedDomain)
| 20.571429 | 43 | 0.833333 | 18 | 144 | 6.666667 | 0.555556 | 0.15 | 0.283333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090278 | 144 | 6 | 44 | 24 | 0.916031 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
eedb2b4cd23a0759b41ddd8b77d89041eb1002e4 | 185 | py | Python | database/models/__init__.py | AtsushiSun/Nixest | ecf598269474438f15070138056be216dd338ae4 | [
"MIT"
] | 1 | 2020-06-03T20:24:48.000Z | 2020-06-03T20:24:48.000Z | database/models/__init__.py | AtsushiSun/Nixest | ecf598269474438f15070138056be216dd338ae4 | [
"MIT"
] | null | null | null | database/models/__init__.py | AtsushiSun/Nixest | ecf598269474438f15070138056be216dd338ae4 | [
"MIT"
] | null | null | null | #import's necessários
from .guild import Guild
"""
- Observação:
O Arquivo __init__.py vai ser meio que uma importação 'global'
de todo os modulos e configuração da pasta Models.
""" | 23.125 | 63 | 0.751351 | 28 | 185 | 4.821429 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.167568 | 185 | 8 | 64 | 23.125 | 0.876623 | 0.108108 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
eefa1edc9578e933164b149d27b4527091ddb6c4 | 207 | py | Python | tests/errors/syntax_blockers/functions_in_template.py | dina-fouad/pyccel | f4d919e673b400442b9c7b81212b6fbef749c7b7 | [
"MIT"
] | 206 | 2018-06-28T00:28:47.000Z | 2022-03-29T05:17:03.000Z | tests/errors/syntax_blockers/functions_in_template.py | dina-fouad/pyccel | f4d919e673b400442b9c7b81212b6fbef749c7b7 | [
"MIT"
] | 670 | 2018-07-23T11:02:24.000Z | 2022-03-30T07:28:05.000Z | tests/errors/syntax_blockers/functions_in_template.py | dina-fouad/pyccel | f4d919e673b400442b9c7b81212b6fbef749c7b7 | [
"MIT"
] | 19 | 2019-09-19T06:01:00.000Z | 2022-03-29T05:17:06.000Z | # pylint: disable=missing-function-docstring, missing-module-docstring/
#$ header template S(int|real)
#$ header template T((int)(int)|(real)(real))
#$ header function f(T, S)
def f(g, a):
return g(a)
| 23 | 71 | 0.681159 | 32 | 207 | 4.40625 | 0.53125 | 0.198582 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135266 | 207 | 8 | 72 | 25.875 | 0.78771 | 0.806763 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0.5 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
e11b4d2ab045fe71dcfcc189fa97d90888b152fc | 449 | py | Python | src/decisionengine/framework/util/tests/test_reaper.py | moibenko/decisionengine | 4c458e0c225ec2ce1e82d56e752724983331b7d1 | [
"Apache-2.0"
] | 9 | 2018-06-11T20:06:50.000Z | 2020-10-01T17:02:02.000Z | src/decisionengine/framework/util/tests/test_reaper.py | moibenko/decisionengine | 4c458e0c225ec2ce1e82d56e752724983331b7d1 | [
"Apache-2.0"
] | 551 | 2018-06-25T21:06:37.000Z | 2022-03-31T13:47:32.000Z | src/decisionengine/framework/util/tests/test_reaper.py | goodenou/decisionengine | b203e2c493cf501562accf1013c6257c348711b7 | [
"Apache-2.0"
] | 70 | 2018-06-11T20:07:01.000Z | 2022-02-10T16:18:24.000Z | # SPDX-FileCopyrightText: 2017 Fermi Research Alliance, LLC
# SPDX-License-Identifier: Apache-2.0
"""
The utils/reaper.py is one of our console entry points.
Testing it requires the test user be either root or decisionengine,
since this isn't 'CI' friendly we are just making sure it is valid python.
"""
def test_valid_python():
"""make sure it is valid python"""
from decisionengine.framework.util import reaper # noqa: F401
pass
| 28.0625 | 74 | 0.741648 | 69 | 449 | 4.797101 | 0.797101 | 0.099698 | 0.048338 | 0.07855 | 0.114804 | 0 | 0 | 0 | 0 | 0 | 0 | 0.024324 | 0.175947 | 449 | 15 | 75 | 29.933333 | 0.87027 | 0.741648 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 5 |
012007db0402c47adf666ffb05aef38560e3d63f | 35 | py | Python | cutlass/__main__.py | antoniouaa/cutlass | 072b9859b7f0effaaef15a8ed92a92c55149b3c2 | [
"MIT"
] | null | null | null | cutlass/__main__.py | antoniouaa/cutlass | 072b9859b7f0effaaef15a8ed92a92c55149b3c2 | [
"MIT"
] | 3 | 2021-07-29T23:53:28.000Z | 2021-08-08T18:04:37.000Z | cutlass/__main__.py | antoniouaa/cutlass | 072b9859b7f0effaaef15a8ed92a92c55149b3c2 | [
"MIT"
] | null | null | null | from cutlass.cli import run
run()
| 8.75 | 27 | 0.742857 | 6 | 35 | 4.333333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.171429 | 35 | 3 | 28 | 11.666667 | 0.896552 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
0133f585cdd64645739b9c0d6fdeb4a7db6af53f | 91 | py | Python | core/admin.py | jakobzmrzlikar/Capitals | c4775d62ff4d73144acefb3926fe567cced663ee | [
"MIT"
] | null | null | null | core/admin.py | jakobzmrzlikar/Capitals | c4775d62ff4d73144acefb3926fe567cced663ee | [
"MIT"
] | null | null | null | core/admin.py | jakobzmrzlikar/Capitals | c4775d62ff4d73144acefb3926fe567cced663ee | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import Country
admin.site.register(Country) | 18.2 | 32 | 0.824176 | 13 | 91 | 5.769231 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.10989 | 91 | 5 | 33 | 18.2 | 0.925926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
0134a590f21fd33cfbee9472197fc6b27f238085 | 64 | py | Python | rax_kernel/__init__.py | chosia/IRax | 51eaa1e6739d17a86030a6d2995db505d06df5e9 | [
"BSD-3-Clause"
] | null | null | null | rax_kernel/__init__.py | chosia/IRax | 51eaa1e6739d17a86030a6d2995db505d06df5e9 | [
"BSD-3-Clause"
] | null | null | null | rax_kernel/__init__.py | chosia/IRax | 51eaa1e6739d17a86030a6d2995db505d06df5e9 | [
"BSD-3-Clause"
] | null | null | null | """A Rax kernel for Jupyter"""
from .kernel import __version__
| 16 | 31 | 0.734375 | 9 | 64 | 4.777778 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.15625 | 64 | 3 | 32 | 21.333333 | 0.796296 | 0.375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
013d1b4692ba4cbe09aa5af005fbf4ece5754076 | 532 | py | Python | test.py | awhite862/cqcpy | e9e6da17c302d84d89e2c53ced57e3d222c440cb | [
"MIT"
] | 5 | 2019-10-28T15:26:11.000Z | 2021-12-10T17:16:23.000Z | test.py | awhite862/cqcpy | e9e6da17c302d84d89e2c53ced57e3d222c440cb | [
"MIT"
] | null | null | null | test.py | awhite862/cqcpy | e9e6da17c302d84d89e2c53ced57e3d222c440cb | [
"MIT"
] | 2 | 2019-10-29T22:35:37.000Z | 2022-01-17T23:29:36.000Z | import unittest
try:
import pyscf
with_pyscf = True
except ImportError:
with_pyscf = False
from cqcpy.tests.test_cc_ampl import *
from cqcpy.tests.test_cc_rdm import *
from cqcpy.tests.test_ci_utils import *
from cqcpy.tests.test_ft_utils import *
if with_pyscf:
from cqcpy.tests.test_integrals import *
from cqcpy.tests.test_lambda_equations import *
from cqcpy.tests.test_spin_utils import *
from cqcpy.tests.test_utils import *
from cqcpy.tests.test_test import *
if __name__ == '__main__':
unittest.main()
| 25.333333 | 47 | 0.778195 | 81 | 532 | 4.790123 | 0.320988 | 0.208763 | 0.324742 | 0.417526 | 0.528351 | 0.224227 | 0 | 0 | 0 | 0 | 0 | 0 | 0.146617 | 532 | 20 | 48 | 26.6 | 0.854626 | 0 | 0 | 0 | 0 | 0 | 0.015038 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
0188d045da7644310b8b18af2091e486620b8802 | 195 | py | Python | .ipynb_checkpoints/config-checkpoint.py | huntingcarlisle/Gentrification-Project | 1c40a8992f53c150e8a37696e2c40b08c36c176e | [
"Apache-2.0"
] | null | null | null | .ipynb_checkpoints/config-checkpoint.py | huntingcarlisle/Gentrification-Project | 1c40a8992f53c150e8a37696e2c40b08c36c176e | [
"Apache-2.0"
] | 1 | 2021-07-31T19:36:26.000Z | 2021-07-31T19:36:26.000Z | .ipynb_checkpoints/config-checkpoint.py | huntingcarlisle/Gentrification-Project | 1c40a8992f53c150e8a37696e2c40b08c36c176e | [
"Apache-2.0"
] | 4 | 2020-05-08T02:14:31.000Z | 2021-07-31T19:32:24.000Z | yelp_api_key = "qjcL1NNqA1x3wjDHlxalyy4lvfeMz9sFI5yi34aaszWd0VBWaQ9hWMdwZY2wTaok360OFyAF8vHHooJHKittKbxndd0XHv-FwEui6ZvVxr9AS-pxKIv5wTF_g8O0XnYx"
gkey = "AIzaSyA1OXbpZJ7AIotiqOLfawzaMWrIn8pfs7I" | 65 | 145 | 0.928205 | 9 | 195 | 19.777778 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.132275 | 0.030769 | 195 | 3 | 146 | 65 | 0.809524 | 0 | 0 | 0 | 0 | 0 | 0.852041 | 0.852041 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
6d75d86df5000ced515d1ce4f12f8747bc8b44c1 | 110 | py | Python | src/pipedown/cross_validation/implementations/__init__.py | brendanhasz/drainpype | a183acec7cae1ef9fde260868e2b021516a8cd7f | [
"MIT"
] | 2 | 2021-03-03T12:11:24.000Z | 2021-03-18T15:09:52.000Z | src/pipedown/cross_validation/implementations/__init__.py | brendanhasz/pipedown | a183acec7cae1ef9fde260868e2b021516a8cd7f | [
"MIT"
] | null | null | null | src/pipedown/cross_validation/implementations/__init__.py | brendanhasz/pipedown | a183acec7cae1ef9fde260868e2b021516a8cd7f | [
"MIT"
] | null | null | null | from .cross_validation_implementation import CrossValidationImplementation
from .sequential import Sequential
| 36.666667 | 74 | 0.909091 | 10 | 110 | 9.8 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072727 | 110 | 2 | 75 | 55 | 0.960784 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
6db24bbaad5af29b4e7c4dc7ad0828a7833a2f78 | 113 | py | Python | snippets/python-2d-array.py | district10/snippet-manager | bebe45a601368947168e3ee6e6ab8c1fc2ee2055 | [
"MIT"
] | 7 | 2018-08-04T09:28:19.000Z | 2020-10-19T17:46:34.000Z | snippets/python-2d-array.py | district10/snippet-manager | bebe45a601368947168e3ee6e6ab8c1fc2ee2055 | [
"MIT"
] | null | null | null | snippets/python-2d-array.py | district10/snippet-manager | bebe45a601368947168e3ee6e6ab8c1fc2ee2055 | [
"MIT"
] | 2 | 2018-07-31T04:14:55.000Z | 2020-04-02T01:22:39.000Z | lst_2d = [[0] * 3] * 3 # 2d array, good
lst_2d = [[0] * 3 for i in xrange(3)] # 2d array, bad
| 37.666667 | 56 | 0.451327 | 20 | 113 | 2.45 | 0.55 | 0.204082 | 0.244898 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 0.380531 | 113 | 2 | 57 | 56.5 | 0.557143 | 0.247788 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
6dc3ddfa29eba02b79ac538e8f7f36d2924a4c79 | 557 | py | Python | profileqc/routines/__init__.py | sharksmhi/profileqc | dfc96445231ce1974be11536cf839299e908d231 | [
"MIT"
] | null | null | null | profileqc/routines/__init__.py | sharksmhi/profileqc | dfc96445231ce1974be11536cf839299e908d231 | [
"MIT"
] | 1 | 2022-03-30T09:10:12.000Z | 2022-03-30T09:10:12.000Z | profileqc/routines/__init__.py | sharksmhi/profileqc | dfc96445231ce1974be11536cf839299e908d231 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# Copyright (c) 2022 SMHI, Swedish Meteorological and Hydrological Institute.
# License: MIT License (see LICENSE.txt or http://opensource.org/licenses/mit).
"""
Created on 2020-02-20 13:26
@author: a002028
"""
from profileqc.routines.continuous import Decreasing, Increasing # noqa: F401
from profileqc.routines.dependencies import Dependencies # noqa: F401
from profileqc.routines.diff import DataDiff # noqa: F401
from profileqc.routines.range import Range # noqa: F401
from profileqc.routines.spike import Spike # noqa: F401
| 39.785714 | 79 | 0.777379 | 75 | 557 | 5.773333 | 0.6 | 0.150115 | 0.242494 | 0.193995 | 0.267898 | 0 | 0 | 0 | 0 | 0 | 0 | 0.075975 | 0.125673 | 557 | 13 | 80 | 42.846154 | 0.813142 | 0.493716 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
6de8b4bea4a39c1a1dbfac1b121f709bce2928f7 | 18 | py | Python | services/netorare/app.py | HH-0rg/pwnhub | 47380d602e6f561683603bd8eeb7891b0d86bf1a | [
"MIT"
] | 4 | 2020-12-27T13:52:45.000Z | 2021-11-25T17:35:43.000Z | services/netorare/app.py | SuhitAgarwal/PwnHub | 839d4f9039912d9d6d048478b1d96d45d0d4dd9f | [
"MIT"
] | 1 | 2021-04-23T17:42:39.000Z | 2021-04-23T17:42:39.000Z | services/netorare/app.py | SuhitAgarwal/PwnHub | 839d4f9039912d9d6d048478b1d96d45d0d4dd9f | [
"MIT"
] | 1 | 2021-03-07T17:40:51.000Z | 2021-03-07T17:40:51.000Z | print ("Netorare") | 18 | 18 | 0.722222 | 2 | 18 | 6.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.055556 | 18 | 1 | 18 | 18 | 0.764706 | 0 | 0 | 0 | 0 | 0 | 0.421053 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
09799c3ef4f9dfc7d92e55b179f3feeeee920ea3 | 57 | py | Python | hello-world-peter-w.py | pwillits/astr-119-section-assignments | 34182ecd992cb6cdbaf7aada15a7f952893ee137 | [
"MIT"
] | 2 | 2018-09-28T18:46:05.000Z | 2018-09-28T19:00:27.000Z | hello-world-peter-w.py | pwillits/astr-119-section-assignments | 34182ecd992cb6cdbaf7aada15a7f952893ee137 | [
"MIT"
] | 67 | 2018-09-26T06:39:43.000Z | 2018-10-03T15:32:12.000Z | hello-world-peter-w.py | pwillits/astr-119-section-assignments | 34182ecd992cb6cdbaf7aada15a7f952893ee137 | [
"MIT"
] | 62 | 2018-09-27T20:12:32.000Z | 2018-10-03T23:53:47.000Z | #!/usr/bin/env python3
print("Hello From Peter Willits") | 19 | 33 | 0.736842 | 9 | 57 | 4.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019608 | 0.105263 | 57 | 3 | 33 | 19 | 0.803922 | 0.368421 | 0 | 0 | 0 | 0 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
099e621c783088c3130cfcc0c3f4fb6505321b42 | 201 | py | Python | env/lib/python3.7/site-packages/mpl_toolkits/axes_grid/axes_rgb.py | MarcoMancha/BreastCancerDetector | be0dfdcebd1ae66da6d0cf48e2525c24942ae877 | [
"Apache-2.0"
] | 102 | 2016-10-09T01:33:00.000Z | 2022-01-28T01:03:23.000Z | env/lib/python3.7/site-packages/mpl_toolkits/axes_grid/axes_rgb.py | MarcoMancha/BreastCancerDetector | be0dfdcebd1ae66da6d0cf48e2525c24942ae877 | [
"Apache-2.0"
] | 41 | 2017-06-04T16:09:43.000Z | 2022-01-20T21:11:42.000Z | env/lib/python3.7/site-packages/mpl_toolkits/axes_grid/axes_rgb.py | MarcoMancha/BreastCancerDetector | be0dfdcebd1ae66da6d0cf48e2525c24942ae877 | [
"Apache-2.0"
] | 50 | 2017-05-10T06:25:36.000Z | 2021-08-02T20:28:54.000Z | from mpl_toolkits.axes_grid1.axes_rgb import (
make_rgb_axes, imshow_rgb, RGBAxesBase)
from mpl_toolkits.axisartist.axislines import Axes
class RGBAxes(RGBAxesBase):
_defaultAxesClass = Axes
| 25.125 | 50 | 0.810945 | 26 | 201 | 5.961538 | 0.576923 | 0.090323 | 0.193548 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005714 | 0.129353 | 201 | 7 | 51 | 28.714286 | 0.88 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
09c5dd0cfdefd908c42618ef62811ea6692a3cb1 | 93 | py | Python | utils/pixiv.py | dp0973/Hiyobot | 33b9a2661f3108d27fa9c177b923db64c342c701 | [
"BSD-3-Clause"
] | 20 | 2020-06-29T13:08:05.000Z | 2021-08-22T05:24:03.000Z | utils/pixiv.py | dp0973/Hiyobot | 33b9a2661f3108d27fa9c177b923db64c342c701 | [
"BSD-3-Clause"
] | 47 | 2020-06-29T22:28:50.000Z | 2021-08-22T16:02:42.000Z | utils/pixiv.py | dp0973/Hiyobot | 33b9a2661f3108d27fa9c177b923db64c342c701 | [
"BSD-3-Clause"
] | 35 | 2020-06-23T00:36:49.000Z | 2022-03-24T09:53:00.000Z | # pyright: strict
from pypixiv.client import PixivClient
class Pixiv(PixivClient):
...
| 13.285714 | 38 | 0.731183 | 10 | 93 | 6.8 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.172043 | 93 | 6 | 39 | 15.5 | 0.883117 | 0.16129 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
110057aab9ff92df3f5aecc052a6f9d4b8f522a7 | 28 | py | Python | marknote/tests/__init__.py | sheldonkwoodward/marknote | d752f86b5b29416e77d38ec31090841d6119a750 | [
"MIT"
] | 5 | 2018-09-07T02:14:19.000Z | 2018-11-13T16:37:22.000Z | marknote/tests/__init__.py | sheldonkwoodward/marknote | d752f86b5b29416e77d38ec31090841d6119a750 | [
"MIT"
] | 2 | 2020-02-11T23:19:58.000Z | 2020-06-05T18:53:11.000Z | marknote/tests/__init__.py | sheldonkwoodward/marknote | d752f86b5b29416e77d38ec31090841d6119a750 | [
"MIT"
] | 1 | 2018-09-07T14:48:04.000Z | 2018-09-07T14:48:04.000Z | # sheldon woodward
# 9/6/18
| 9.333333 | 18 | 0.678571 | 5 | 28 | 3.8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.173913 | 0.178571 | 28 | 2 | 19 | 14 | 0.652174 | 0.821429 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
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