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e6017a5092bc8f5d1e4a0cfdb930c0da3b7bd988
8,317
py
Python
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
herleraja/WiCoSens
f31bcfd73900f76073510ec8e40e753bbcdbb404
[ "Apache-2.0" ]
null
null
null
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
herleraja/WiCoSens
f31bcfd73900f76073510ec8e40e753bbcdbb404
[ "Apache-2.0" ]
null
null
null
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
herleraja/WiCoSens
f31bcfd73900f76073510ec8e40e753bbcdbb404
[ "Apache-2.0" ]
null
null
null
import dl_classification as dl_clf import ml_utils import numpy as np # source_dir_path = ml_utils.get_source_dir_path() source_dir_path_color_space_one = "./datarecording_discrete/color_concept_latest/xyz/" source_dir_path_color_space_two = "./datarecording_discrete/color_concept_latest/hsv/" source_dir_path_color_space_three = "./datarecording_discrete/color_concept_latest/rgb/" config_save_load_dir_path = "./configs/color_concept_latest/multiple_color_space/" input_shape = 18 # 18 for 3 color space, 12 for two color space if __name__ == "__main__": train_bottom_data_color_space_one, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'train_bottom.csv', start_column=4, end_column=10) train_left_data_color_space_one, train_left_labels_raw, train_left_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'train_left.csv', start_column=7, end_column=13) train_right_data_color_space_one, train_right_labels_raw, train_right_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'train_right.csv', start_column=7, end_column=13) test_bottom_data_color_space_one, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'test_bottom.csv', start_column=4, end_column=10) test_left_data_color_space_one, test_left_labels_raw, test_left_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'test_left.csv', start_column=7, end_column=13) test_right_data_color_space_one, test_right_labels_raw, test_right_labels = ml_utils.parse_file( source_dir_path_color_space_one + 'test_right.csv', start_column=7, end_column=13) train_bottom_data_color_space_two, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'train_bottom.csv', start_column=4, end_column=10) train_left_data_color_space_two, train_left_labels_raw, train_left_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'train_left.csv', start_column=7, end_column=13) train_right_data_color_space_two, train_right_labels_raw, train_right_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'train_right.csv', start_column=7, end_column=13) test_bottom_data_color_space_two, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'test_bottom.csv', start_column=4, end_column=10) test_left_data_color_space_two, test_left_labels_raw, test_left_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'test_left.csv', start_column=7, end_column=13) test_right_data_color_space_two, test_right_labels_raw, test_right_labels = ml_utils.parse_file( source_dir_path_color_space_two + 'test_right.csv', start_column=7, end_column=13) if input_shape == 18: train_bottom_data_color_space_three, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'train_bottom.csv', start_column=4, end_column=10) train_left_data_color_space_three, train_left_labels_raw, train_left_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'train_left.csv', start_column=7, end_column=13) train_right_data_color_space_three, train_right_labels_raw, train_right_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'train_right.csv', start_column=7, end_column=13) test_bottom_data_color_space_three, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'test_bottom.csv', start_column=4, end_column=10) test_left_data_color_space_three, test_left_labels_raw, test_left_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'test_left.csv', start_column=7, end_column=13) test_right_data_color_space_three, test_right_labels_raw, test_right_labels = ml_utils.parse_file( source_dir_path_color_space_three + 'test_right.csv', start_column=7, end_column=13) train_bottom_data = np.concatenate( (train_bottom_data_color_space_one, train_bottom_data_color_space_two, train_bottom_data_color_space_three), axis=1) train_left_data = np.concatenate( (train_left_data_color_space_one, train_left_data_color_space_two, train_left_data_color_space_three), axis=1) train_right_data = np.concatenate( (train_right_data_color_space_one, train_right_data_color_space_two, train_right_data_color_space_three), axis=1) test_bottom_data = np.concatenate( (test_bottom_data_color_space_one, test_bottom_data_color_space_two, test_bottom_data_color_space_three), axis=1) test_left_data = np.concatenate( (test_left_data_color_space_one, test_left_data_color_space_two, test_left_data_color_space_three), axis=1) test_right_data = np.concatenate( (test_right_data_color_space_one, test_right_data_color_space_two, test_right_data_color_space_three), axis=1) else: train_bottom_data = np.concatenate((train_bottom_data_color_space_one, train_bottom_data_color_space_two), axis=1) train_left_data = np.concatenate((train_left_data_color_space_one, train_left_data_color_space_two), axis=1) train_right_data = np.concatenate((train_right_data_color_space_one, train_right_data_color_space_two), axis=1) test_bottom_data = np.concatenate((test_bottom_data_color_space_one, test_bottom_data_color_space_two), axis=1) test_left_data = np.concatenate((test_left_data_color_space_one, test_left_data_color_space_two), axis=1) test_right_data = np.concatenate((test_right_data_color_space_one, test_right_data_color_space_two), axis=1) # earlyStopping = keras.callbacks.EarlyStopping(monitor='val_loss', patience=10, verbose=1, mode='auto') model_bottom = dl_clf.build_model(5, input_shape) history_bottom = model_bottom.fit(train_bottom_data, train_bottom_labels, epochs=20, validation_data=(test_bottom_data, test_bottom_labels), batch_size=500, verbose=2) model_left = dl_clf.build_model(7, input_shape) history_left = model_left.fit(train_left_data, train_left_labels, epochs=20, validation_data=(test_left_data, test_left_labels), batch_size=500, verbose=2) model_right = dl_clf.build_model(8, input_shape) history_right = model_right.fit(train_right_data, train_right_labels, epochs=20, validation_data=(test_right_data, test_right_labels), batch_size=500, verbose=2) ml_utils.save_model(model_bottom, 'model_bottom.h5', config_save_load_dir_path) ml_utils.save_model(model_left, 'model_left.h5', config_save_load_dir_path) ml_utils.save_model(model_right, 'model_right.h5', config_save_load_dir_path) test_predicted_bottom_res = model_bottom.predict(test_bottom_data, batch_size=1) print('\n****************Classification result for Bottom************************') ml_utils.display_result(test_bottom_labels_raw, test_predicted_bottom_res.argmax(axis=1), 'Bottom') # Print the classification result # for result in test_predicted_bottom_res: # ml_utils.display_confidence(result) test_predicted_left_res = model_left.predict(test_left_data, batch_size=1) print('\n****************Classification result for Left************************') ml_utils.display_result(test_left_labels_raw, test_predicted_left_res.argmax(axis=1), 'Left') # Print the classification result # for result in test_predicted_left_res: # ml_utils.display_confidence(result) test_predicted_right_res = model_right.predict(test_right_data, batch_size=1) print('\n****************Classification result for Right************************') ml_utils.display_result(test_right_labels_raw, test_predicted_right_res.argmax(axis=1), 'Right') # Print the classification result # for result in test_predicted_right_res: # ml_utils.display_confidence(result)
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e61d4cb64f9add1b220b438815aa8254e952f834
95
py
Python
third/emoji_demo.py
gottaegbert/penter
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
[ "MIT" ]
13
2020-01-04T07:37:38.000Z
2021-08-31T05:19:58.000Z
third/emoji_demo.py
gottaegbert/penter
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
[ "MIT" ]
3
2020-06-05T22:42:53.000Z
2020-08-24T07:18:54.000Z
third/emoji_demo.py
gottaegbert/penter
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
[ "MIT" ]
9
2020-10-19T04:53:06.000Z
2021-08-31T05:20:01.000Z
from emoji import emojize print(emojize(":thumbs_up:")) # https://github.com/carpedm20/emoji
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5
e62c27b3fe3513eda2bf109dcdb7ea0da19b70cf
281
py
Python
Leetcode9.py
cherytony/test1
506ce4cab6f641beff817c81d7a616db29a7131d
[ "Apache-2.0" ]
null
null
null
Leetcode9.py
cherytony/test1
506ce4cab6f641beff817c81d7a616db29a7131d
[ "Apache-2.0" ]
null
null
null
Leetcode9.py
cherytony/test1
506ce4cab6f641beff817c81d7a616db29a7131d
[ "Apache-2.0" ]
null
null
null
class Solution: def isPalindrome(self,x): # if x > 0 : # r = int(str(x)[::-1]) # # if r ==x: # return True # else: # return False # # else: # return False
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050551001ea2cbc3bb46a4a0d1cf37d38ef44710
449
py
Python
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
saketkc/EE-546-project
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
[ "BSD-2-Clause" ]
1
2020-11-02T07:05:09.000Z
2020-11-02T07:05:09.000Z
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
saketkc/EE-546-project
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
[ "BSD-2-Clause" ]
null
null
null
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
saketkc/EE-546-project
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
[ "BSD-2-Clause" ]
null
null
null
RAWDATA_DIR = '/staging/as/skchoudh/rna-seq-datasets/single/ornithorhynchus_anatinus/SRP007412' OUT_DIR = '/staging/as/skchoudh/rna-seq-output/ornithorhynchus_anatinus/SRP007412' CDNA_FA_GZ = '/home/cmb-panasas2/skchoudh/genomes/ornithorhynchus_anatinus/cdna/Ornithorhynchus_anatinus.OANA5.cdna.all.fa.gz' CDNA_IDX = '/home/cmb-panasas2/skchoudh/genomes/ornithorhynchus_anatinus/cdna/Ornithorhynchus_anatinus.OANA5.cdna.all.kallisto.index'
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051ead77d256fe11805dc474f5b972978b2ae452
82
py
Python
neverlose/models/base/response.py
neverlosecc/api-wrapper
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
[ "MIT" ]
2
2021-03-29T17:14:17.000Z
2021-05-15T03:42:44.000Z
neverlose/models/base/response.py
neverlosecc/api-wrapper
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
[ "MIT" ]
null
null
null
neverlose/models/base/response.py
neverlosecc/api-wrapper
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
[ "MIT" ]
null
null
null
from pydantic import BaseModel class BaseResponse(BaseModel): success: bool
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056c60b80c24239c4e8e076bda83bcf6add55bb3
146
py
Python
cats/admin.py
jiz148/django-tutorial
6471bfe1f4e94fd1e7da1531ae1247804deb7871
[ "MIT" ]
null
null
null
cats/admin.py
jiz148/django-tutorial
6471bfe1f4e94fd1e7da1531ae1247804deb7871
[ "MIT" ]
null
null
null
cats/admin.py
jiz148/django-tutorial
6471bfe1f4e94fd1e7da1531ae1247804deb7871
[ "MIT" ]
null
null
null
from django.contrib import admin from .models import Breed, Cat # Register your models here. admin.site.register(Breed) admin.site.register(Cat)
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0.155172
0.293103
0
0
0
0
0
0
0
0
0
0.116438
146
6
33
24.333333
0.899225
0.178082
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
e95375b4801be688246f48392ae31678a7ad67eb
85
py
Python
django_api_example/tasks/admin.py
amrox/django-api-example
6c68e43078bb5e858ddea84d44a943ec9d7808b4
[ "MIT" ]
17
2015-03-31T20:23:08.000Z
2021-06-08T00:46:57.000Z
django_api_example/tasks/admin.py
amrox/django-api-example
6c68e43078bb5e858ddea84d44a943ec9d7808b4
[ "MIT" ]
null
null
null
django_api_example/tasks/admin.py
amrox/django-api-example
6c68e43078bb5e858ddea84d44a943ec9d7808b4
[ "MIT" ]
4
2015-05-18T14:24:52.000Z
2022-02-18T06:52:52.000Z
from models import Task from django.contrib import admin admin.site.register(Task)
14.166667
32
0.811765
13
85
5.307692
0.692308
0
0
0
0
0
0
0
0
0
0
0
0.129412
85
5
33
17
0.932432
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
e98768fa403a6351fffcd3895fcaaa6f9f3d3b5b
75
py
Python
iterate_task.py
Nivratti/bing_image_downloader
9b30d07a2e8733fb255ab6b27499870b942b97c5
[ "MIT" ]
null
null
null
iterate_task.py
Nivratti/bing_image_downloader
9b30d07a2e8733fb255ab6b27499870b942b97c5
[ "MIT" ]
null
null
null
iterate_task.py
Nivratti/bing_image_downloader
9b30d07a2e8733fb255ab6b27499870b942b97c5
[ "MIT" ]
null
null
null
import os, sys import shutil from pathlib import Path import pandas as pd
12.5
24
0.8
13
75
4.615385
0.769231
0
0
0
0
0
0
0
0
0
0
0
0.186667
75
5
25
15
0.983607
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
e9b230b9bb624aa2a11c31674f9c3d58de29814a
129
py
Python
truffletopia/__init__.py
wesleybeckner/truffletopia
574caf24b41126d3d71c45b49cfd44820c42fa7e
[ "MIT" ]
null
null
null
truffletopia/__init__.py
wesleybeckner/truffletopia
574caf24b41126d3d71c45b49cfd44820c42fa7e
[ "MIT" ]
null
null
null
truffletopia/__init__.py
wesleybeckner/truffletopia
574caf24b41126d3d71c45b49cfd44820c42fa7e
[ "MIT" ]
null
null
null
from __future__ import absolute_import, division, print_function from .version import __version__ from .truffletopia import *
32.25
65
0.829457
15
129
6.466667
0.6
0
0
0
0
0
0
0
0
0
0
0
0.131783
129
3
66
43
0.866071
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
1
0
1
0.333333
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
75669275652b7c8d3e3d8a169edb423121ebe99f
157
py
Python
env/lib/python3.8/site-packages/liststyle/admin.py
angels101/practice-django-framework-api-
0a888c75126940c33bc7afc14b8d1496c586512f
[ "MIT" ]
null
null
null
env/lib/python3.8/site-packages/liststyle/admin.py
angels101/practice-django-framework-api-
0a888c75126940c33bc7afc14b8d1496c586512f
[ "MIT" ]
null
null
null
env/lib/python3.8/site-packages/liststyle/admin.py
angels101/practice-django-framework-api-
0a888c75126940c33bc7afc14b8d1496c586512f
[ "MIT" ]
null
null
null
from django.contrib.admin.views.main import ChangeList class ListStyleAdminMixin(object): def get_row_css(self, obj, index): return ''
22.428571
54
0.694268
19
157
5.631579
1
0
0
0
0
0
0
0
0
0
0
0
0.216561
157
6
55
26.166667
0.869919
0
0
0
0
0
0
0
0
0
0
0
0
1
0.25
false
0
0.25
0.25
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
0
1
1
0
0
5
7580078c7f20a034097af3f07e2e70b94dbdfbb3
1,592
py
Python
implementations/general/danbooru_portrait.py
wonwizard/animeface
b022f500803278733a4bdf911feaff884fa3a5db
[ "MIT" ]
2
2021-05-04T06:14:42.000Z
2022-02-28T10:55:39.000Z
implementations/general/danbooru_portrait.py
wonwizard/animeface
b022f500803278733a4bdf911feaff884fa3a5db
[ "MIT" ]
null
null
null
implementations/general/danbooru_portrait.py
wonwizard/animeface
b022f500803278733a4bdf911feaff884fa3a5db
[ "MIT" ]
null
null
null
import random import glob from .dataset_base import Image, ImageXDoG, make_default_transform class DanbooruPortraitDataset(Image): '''Danbooru Portrait Dataset ''' def __init__(self, image_size, transform=None, num_images=None): if transform is None: transform = make_default_transform(image_size, 1.2) super().__init__(transform) if num_images is not None: assert 0 < num_images <= len(self.images) and isinstance(num_images, int) random.shuffle(self.images) self.images = self.images[:num_images] def _load(self): image_paths = glob.glob('/usr/src/data/danbooru/portraits/portraits/*') return image_paths class XDoGDanbooruPortraitDataset(ImageXDoG): '''Image + XDoG Danbooru Portrait Dataset ''' def __init__(self, image_size, transform=None, num_images=None): if transform is None: transform = make_default_transform(image_size, 1.2, hflip=False) super().__init__(transform) if num_images is not None: assert 0 < num_images <= len(self.images) and isinstance(num_images, int) random.shuffle(self.images) self.images = self.images[:num_images] self.xdogs = [path.replace('portraits/portraits', 'portraits/xdog') for path in self.images] def _load(self): image_paths = glob.glob('/usr/src/data/danbooru/portraits/portraits/*') xdog_paths = [path.replace('portraits/portraits', 'portraits/xdog') for path in image_paths] return image_paths, xdog_paths
39.8
104
0.670226
195
1,592
5.235897
0.261538
0.088149
0.054848
0.078355
0.761998
0.761998
0.761998
0.761998
0.761998
0.662096
0
0.00487
0.226131
1,592
39
105
40.820513
0.823864
0.043342
0
0.62069
0
0
0.102258
0.058433
0
0
0
0
0.068966
1
0.137931
false
0
0.103448
0
0.37931
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
75801221ff9e7a3132795404ef76523030d9742b
207
py
Python
vispy/util/ordereddict.py
MatthieuDartiailh/vispy
09d429be361a148b0614a192f56d4070c624072c
[ "BSD-3-Clause" ]
null
null
null
vispy/util/ordereddict.py
MatthieuDartiailh/vispy
09d429be361a148b0614a192f56d4070c624072c
[ "BSD-3-Clause" ]
null
null
null
vispy/util/ordereddict.py
MatthieuDartiailh/vispy
09d429be361a148b0614a192f56d4070c624072c
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- from sys import version_info if version_info[0] > 2 or version_info[1] >= 7: from collections import OrderedDict else: from ..ext.py24_ordereddict import OrderedDict # noqa
25.875
58
0.710145
30
207
4.766667
0.666667
0.230769
0
0
0
0
0
0
0
0
0
0.04142
0.183575
207
7
59
29.571429
0.804734
0.125604
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
0.6
0
0.6
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
7598d0d7b7e570296f576ef7af7b186ea87cf570
91
py
Python
app/train.py
jennyluciav/aws-ml-lambda-tf
c28b45a408d87592639ced9976c9313faa2dc265
[ "MIT" ]
null
null
null
app/train.py
jennyluciav/aws-ml-lambda-tf
c28b45a408d87592639ced9976c9313faa2dc265
[ "MIT" ]
null
null
null
app/train.py
jennyluciav/aws-ml-lambda-tf
c28b45a408d87592639ced9976c9313faa2dc265
[ "MIT" ]
2
2021-06-23T00:31:09.000Z
2021-06-24T23:43:05.000Z
from model import ModelWrapper model_wrapper = ModelWrapper() model_wrapper.train()
15.166667
31
0.769231
10
91
6.8
0.6
0.5
0.705882
0
0
0
0
0
0
0
0
0
0.164835
91
5
32
18.2
0.894737
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0.333333
0
0.333333
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
75dc33110a02a0ef796412ef1a1bc2f67fe6b1d3
264
py
Python
python/anyascii/_data/_2d3.py
casept/anyascii
d4f426b91751254b68eaa84c6cd23099edd668e6
[ "ISC" ]
null
null
null
python/anyascii/_data/_2d3.py
casept/anyascii
d4f426b91751254b68eaa84c6cd23099edd668e6
[ "ISC" ]
null
null
null
python/anyascii/_data/_2d3.py
casept/anyascii
d4f426b91751254b68eaa84c6cd23099edd668e6
[ "ISC" ]
null
null
null
b=' Zong Dao Ai Wei'
264
264
0.049242
5
264
2.6
1
0
0
0
0
0
0
0
0
0
0
0
0.939394
264
1
264
264
0.8125
0
0
0
0
0
0.981132
0
0
0
0
0
0
1
0
false
0
0
0
0
0
1
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
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
f938fcd839377220797a8b450c9e5308dd773c1a
17
py
Python
file9.py
karwinski/QA-and-Git
ec927de5dfb1de62cf46c112b45c751b64e3ccde
[ "MIT" ]
1
2017-12-18T16:01:29.000Z
2017-12-18T16:01:29.000Z
file9.py
karwinski/QA-and-Git
ec927de5dfb1de62cf46c112b45c751b64e3ccde
[ "MIT" ]
null
null
null
file9.py
karwinski/QA-and-Git
ec927de5dfb1de62cf46c112b45c751b64e3ccde
[ "MIT" ]
null
null
null
print("file9");
5.666667
15
0.588235
2
17
5
1
0
0
0
0
0
0
0
0
0
0
0.066667
0.117647
17
2
16
8.5
0.6
0
0
0
0
0
0.3125
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
f953b5021b2b6a337a4070803427b71b6970b12d
506
py
Python
arrow/commands/cmd_cannedkeys.py
GMOD/python-apollo3
c1c47e985d95c8995374f6daa5c2e52b6d94ee0d
[ "MIT" ]
5
2017-06-27T19:41:57.000Z
2021-06-05T13:36:11.000Z
arrow/commands/cmd_cannedkeys.py
galaxy-genome-annotation/python-apollo
1257e050ee3fc0a7f7ab8a8c780aefee5c8143f8
[ "MIT" ]
28
2017-07-24T15:10:37.000Z
2021-09-03T11:56:35.000Z
arrow/commands/cmd_cannedkeys.py
MoffMade/python-apollo
3cc61458cf5c20bd44fde656b8364417b915cfb8
[ "MIT" ]
10
2017-05-10T19:13:44.000Z
2021-08-09T04:52:33.000Z
import click from arrow.commands.cannedkeys.add_key import cli as add_key from arrow.commands.cannedkeys.delete_key import cli as delete_key from arrow.commands.cannedkeys.get_keys import cli as get_keys from arrow.commands.cannedkeys.show_key import cli as show_key from arrow.commands.cannedkeys.update_key import cli as update_key @click.group() def cli(): pass cli.add_command(add_key) cli.add_command(delete_key) cli.add_command(get_keys) cli.add_command(show_key) cli.add_command(update_key)
26.631579
66
0.83004
87
506
4.597701
0.218391
0.1125
0.2125
0.3375
0.225
0
0
0
0
0
0
0
0.096838
506
18
67
28.111111
0.875274
0
0
0
0
0
0
0
0
0
0
0
0
1
0.071429
true
0.071429
0.428571
0
0.5
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
1
1
0
0
0
0
5
f959b18bf8f141da5514d2eca241d1779bf440aa
183
py
Python
by-session/ta-921/j3/func1.py
amiraliakbari/sharif-mabani-python
5d14a08d165267fe71c28389ddbafe29af7078c5
[ "MIT" ]
2
2015-04-29T20:59:35.000Z
2018-09-26T13:33:43.000Z
by-session/ta-921/j3/func1.py
amiraliakbari/sharif-mabani-python
5d14a08d165267fe71c28389ddbafe29af7078c5
[ "MIT" ]
null
null
null
by-session/ta-921/j3/func1.py
amiraliakbari/sharif-mabani-python
5d14a08d165267fe71c28389ddbafe29af7078c5
[ "MIT" ]
null
null
null
def print1(): print 'A' print 'B' def print2(): print 'a' print 'b' def print3(): print '1' print '2' print1() print3() print3() print2()
10.166667
14
0.47541
22
183
3.954545
0.409091
0.137931
0.252874
0.275862
0.344828
0
0
0
0
0
0
0.077586
0.36612
183
17
15
10.764706
0.672414
0
0
0.153846
0
0
0.036145
0
0
0
0
0
0
0
null
null
0
0
null
null
1
1
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
1
0
0
0
0
0
0
1
0
5
f966d81b1806e8b4a6364af7ea00ea9df1539d63
84
py
Python
lib_path.py
MarcDorval/libtclpy
57ae2356eb75930880cdf86afedc28b1fbf3b21c
[ "BSD-3-Clause" ]
null
null
null
lib_path.py
MarcDorval/libtclpy
57ae2356eb75930880cdf86afedc28b1fbf3b21c
[ "BSD-3-Clause" ]
null
null
null
lib_path.py
MarcDorval/libtclpy
57ae2356eb75930880cdf86afedc28b1fbf3b21c
[ "BSD-3-Clause" ]
null
null
null
import os import sys print('"' + os.path.dirname(sys.executable) + '\libs"', end='')
28
63
0.654762
12
84
4.583333
0.75
0
0
0
0
0
0
0
0
0
0
0
0.107143
84
3
63
28
0.733333
0
0
0
0
0
0.082353
0
0
0
0
0
0
1
0
true
0
0.666667
0
0.666667
0.333333
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
f97128d64d845512ce1bd9e6c7216eb277c18aa8
304
py
Python
src/telliot_core/queries/__init__.py
QuintusTheFifth/telliot-core
e22bc3b98d368fa91528f4a273ef26eddfefacaf
[ "MIT" ]
9
2021-12-15T07:03:34.000Z
2022-03-30T20:16:45.000Z
src/telliot_core/queries/__init__.py
QuintusTheFifth/telliot-core
e22bc3b98d368fa91528f4a273ef26eddfefacaf
[ "MIT" ]
76
2021-11-11T10:06:11.000Z
2022-03-30T18:50:48.000Z
src/telliot_core/queries/__init__.py
QuintusTheFifth/telliot-core
e22bc3b98d368fa91528f4a273ef26eddfefacaf
[ "MIT" ]
7
2021-12-17T03:39:23.000Z
2022-03-29T08:53:43.000Z
""" TODO: Remove these imports. They only remain to avoid breaking telliot-feed-examples, until it starts importing from the api module. """ from telliot_core.queries.legacy_query import LegacyRequest from telliot_core.queries.price.spot_price import SpotPrice __all__ = ["LegacyRequest", "SpotPrice"]
38
69
0.802632
41
304
5.756098
0.756098
0.09322
0.127119
0.186441
0
0
0
0
0
0
0
0
0.115132
304
7
70
43.428571
0.877323
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0
0
0
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1
0
1
0
0
5
f974a663db18cecee8c23c312f965b9577d0926c
138
py
Python
nipype/workflows/fmri/spm/__init__.py
abelalez/nipype
878271bd906768f11c4cabd04e5d1895551ce8a7
[ "Apache-2.0" ]
8
2019-05-29T09:38:30.000Z
2021-01-20T03:36:59.000Z
nipype/workflows/fmri/spm/__init__.py
abelalez/nipype
878271bd906768f11c4cabd04e5d1895551ce8a7
[ "Apache-2.0" ]
12
2021-03-09T03:01:16.000Z
2022-03-11T23:59:36.000Z
nipype/workflows/fmri/spm/__init__.py
abelalez/nipype
878271bd906768f11c4cabd04e5d1895551ce8a7
[ "Apache-2.0" ]
2
2017-09-23T16:22:00.000Z
2019-08-01T14:18:52.000Z
# -*- coding: utf-8 -*- from .preprocess import (create_spm_preproc, create_vbm_preproc, create_DARTEL_template)
34.5
64
0.637681
15
138
5.466667
0.8
0.317073
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0
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0.009804
0.26087
138
3
65
46
0.794118
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null
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0
0
1
0
1
0
0
0
0
5
f978b14364d8c517a6d9cd9d38638bde9ecebe1d
123
py
Python
xmstring/strcmp.py
xmake-io/pxmake
c5ca995e1afa840d54b513e8b2f193de463a3606
[ "Apache-2.0" ]
1
2021-08-15T21:26:10.000Z
2021-08-15T21:26:10.000Z
xmstring/strcmp.py
xmake-io/pxmake
c5ca995e1afa840d54b513e8b2f193de463a3606
[ "Apache-2.0" ]
null
null
null
xmstring/strcmp.py
xmake-io/pxmake
c5ca995e1afa840d54b513e8b2f193de463a3606
[ "Apache-2.0" ]
null
null
null
from xmtrace import xmtrace @xmtrace def xm_string_strcmp(lua, s1, s2): return -1 if s1 < s2 else 1 if s2 < s1 else 0
20.5
49
0.699187
24
123
3.5
0.625
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0
0
0
0
0
0
0
0
0
0.094737
0.227642
123
5
50
24.6
0.789474
0
0
0
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0
0
0
0
0
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0
0
1
0.25
false
0
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0.25
0.75
0
1
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0
null
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null
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1
0
0
0
1
1
0
0
5
f9a57de9c4f49f9b5d19dbffa6ae161831da7e3a
50
py
Python
python/testData/completion/asName/a.after.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
2
2019-04-28T07:48:50.000Z
2020-12-11T14:18:08.000Z
python/testData/completion/asName/a.after.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
173
2018-07-05T13:59:39.000Z
2018-08-09T01:12:03.000Z
python/testData/completion/asName/a.after.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
2
2020-03-15T08:57:37.000Z
2020-04-07T04:48:14.000Z
import importSource importSource.arguments_vector
16.666667
29
0.92
5
50
9
0.8
0
0
0
0
0
0
0
0
0
0
0
0.06
50
3
29
16.666667
0.957447
0
0
0
0
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0
true
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0
0
0
1
0
1
0
1
0
0
5
dddc930346967d49b4034f2aa9f7cbd23747df27
189
py
Python
atopa/teacher/admin.py
clbravo/atopa_app
99c17bd83b0564635c284c46df11fcbfb00fc64b
[ "MIT" ]
null
null
null
atopa/teacher/admin.py
clbravo/atopa_app
99c17bd83b0564635c284c46df11fcbfb00fc64b
[ "MIT" ]
10
2020-06-06T00:49:41.000Z
2021-12-22T18:13:00.000Z
atopa/teacher/admin.py
clbravo/atopa_app
99c17bd83b0564635c284c46df11fcbfb00fc64b
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib import admin from . import models # Register your models here. admin.site.register(models.UserProfile)
21
39
0.772487
25
189
5.64
0.68
0
0
0
0
0
0
0
0
0
0
0.006098
0.132275
189
8
40
23.625
0.853659
0.253968
0
0
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0
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0
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1
0
true
0
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0
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null
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0
1
0
1
0
1
0
0
5
dde004d0ba6d779419d5fdf5d45b7a95ec31c29d
83
py
Python
python/settings.py
ucla-hci/journal
14a6e065ed135f7fdaec6dbd9f762a058da877f9
[ "MIT" ]
1
2019-11-17T21:55:00.000Z
2019-11-17T21:55:00.000Z
python/settings.py
ucla-hci/journal
14a6e065ed135f7fdaec6dbd9f762a058da877f9
[ "MIT" ]
null
null
null
python/settings.py
ucla-hci/journal
14a6e065ed135f7fdaec6dbd9f762a058da877f9
[ "MIT" ]
null
null
null
API_USER_NAME="apikey" API_PASSWORD="qTmPPPacTaWbnPrN-_bUSi1r2I_NH2VZIdEGaURRmwJW"
27.666667
59
0.891566
9
83
7.666667
0.888889
0
0
0
0
0
0
0
0
0
0
0.037037
0.024096
83
2
60
41.5
0.814815
0
0
0
0
0
0.60241
0.53012
0
0
0
0
0
1
0
false
0.5
0
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0
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1
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0
null
0
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0
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1
null
0
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0
0
0
0
1
0
0
0
0
0
5
ddee08c86195f4c39728ba9a46d1f15ab2daa4da
42
py
Python
aulas Zero/print.py
haller218/PythonZero
b6dd1650d127eb2f985a316d86160cefbfd42bda
[ "MIT" ]
null
null
null
aulas Zero/print.py
haller218/PythonZero
b6dd1650d127eb2f985a316d86160cefbfd42bda
[ "MIT" ]
null
null
null
aulas Zero/print.py
haller218/PythonZero
b6dd1650d127eb2f985a316d86160cefbfd42bda
[ "MIT" ]
null
null
null
print ("Ola") print ("Mundo") print ("!")
10.5
15
0.547619
5
42
4.6
0.6
0
0
0
0
0
0
0
0
0
0
0
0.142857
42
3
16
14
0.638889
0
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0
0.214286
0
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0
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0
true
0
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1
1
0
null
0
0
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0
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1
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null
0
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0
0
0
1
0
0
0
0
1
0
5
ddfdc87c467d6bc4897bb6015baf9212cfaeb0f1
106
py
Python
trext/datamodules/__init__.py
sergevkim/TextTranslation
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
[ "MIT" ]
1
2020-11-08T18:24:46.000Z
2020-11-08T18:24:46.000Z
trext/datamodules/__init__.py
sergevkim/TextTranslation
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
[ "MIT" ]
null
null
null
trext/datamodules/__init__.py
sergevkim/TextTranslation
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
[ "MIT" ]
null
null
null
from .de_en_datamodule import DeEnDataModule from .de_en_buckets_datamodule import DeEnBucketsDataModule
26.5
59
0.896226
13
106
6.923077
0.615385
0.133333
0.177778
0
0
0
0
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0
0
0.084906
106
3
60
35.333333
0.927835
0
0
0
0
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0
0
0
1
0
true
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1
0
1
0
0
null
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1
0
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null
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1
0
1
0
0
5
348b6be9ac56470b9a3334ff7a6de7b5a9e1285f
162
py
Python
src/pram/model/__init__.py
momacs/pram
d2de43ea447d13a65d814f781ec86889754f76fe
[ "BSD-3-Clause" ]
10
2019-01-18T19:11:54.000Z
2022-03-16T08:39:36.000Z
src/pram/model/__init__.py
momacs/pram
d2de43ea447d13a65d814f781ec86889754f76fe
[ "BSD-3-Clause" ]
2
2019-02-19T15:10:44.000Z
2019-02-26T04:26:24.000Z
src/pram/model/__init__.py
momacs/pram
d2de43ea447d13a65d814f781ec86889754f76fe
[ "BSD-3-Clause" ]
3
2019-02-19T15:11:08.000Z
2021-08-20T11:51:04.000Z
from .model import Model, Solver, MCSolver, ODESolver from .epi import SEIRModelParams, SEI2RModelParams, SISModel, SIRModel, SIRSModel, SEIRModel, SEQIHRModel
54
107
0.814815
17
162
7.764706
0.823529
0
0
0
0
0
0
0
0
0
0
0.006993
0.117284
162
2
108
81
0.916084
0
0
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true
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1
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null
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null
0
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0
1
0
1
0
0
5
34d1125590425c3436ea6fb24117cb4ce1bb0de8
1,959
py
Python
tests/cli/test_utils.py
fabianSorn/widgetmark
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
[ "MIT" ]
null
null
null
tests/cli/test_utils.py
fabianSorn/widgetmark
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
[ "MIT" ]
null
null
null
tests/cli/test_utils.py
fabianSorn/widgetmark
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
[ "MIT" ]
null
null
null
import widgetmark from widgetmark.cli.cli_view import _get_bar_color, Color # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bar Graph printing ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ class ColorTestsUseCase(widgetmark.UseCase): backend = widgetmark.GuiBackend.QT goal = 50.0 minimum = 40.0 tolerance = 0.1 repeat = 1 def setup_widget(self): return None def operate(self): pass def test_color_yellow(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=43.4, ) assert _get_bar_color(result) == Color.YELLOW def test_color_min_yellow(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=36, ) assert _get_bar_color(result) == Color.YELLOW def test_color_green(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=47.4, ) assert _get_bar_color(result) == Color.GREEN def test_color_min_green(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=45, ) assert _get_bar_color(result) == Color.GREEN def test_color_bigger_than_goal(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=64.4, ) assert _get_bar_color(result) == Color.GREEN def test_color_red(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=21.2, ) assert _get_bar_color(result) == Color.RED def test_color_zero(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=0.0, ) assert _get_bar_color(result) == Color.RED def test_negative(): result = widgetmark.UseCaseResult( use_case=ColorTestsUseCase(), operations_per_second=-5.4, ) assert _get_bar_color(result) == Color.RED
23.047059
79
0.665135
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1,959
5.570136
0.262443
0.043867
0.080422
0.207961
0.760357
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0.760357
0.73355
0.73355
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0
0.018893
0.216437
1,959
84
80
23.321429
0.783062
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0.166667
false
0.016667
0.033333
0.016667
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0
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null
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1
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1
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null
0
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0
0
0
0
0
0
0
0
0
5
551c9806114b5c6873e3e49edd4b00ce5daa117e
60
py
Python
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
steerapi/webdnn
1df51cc094e5a528cfd3452c264905708eadb491
[ "MIT" ]
1
2021-04-09T15:55:35.000Z
2021-04-09T15:55:35.000Z
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
steerapi/webdnn
1df51cc094e5a528cfd3452c264905708eadb491
[ "MIT" ]
null
null
null
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
steerapi/webdnn
1df51cc094e5a528cfd3452c264905708eadb491
[ "MIT" ]
null
null
null
from webdnn.backend.webgpu.attributes import lstm_optimized
30
59
0.883333
8
60
6.5
1
0
0
0
0
0
0
0
0
0
0
0
0.066667
60
1
60
60
0.928571
0
0
0
0
0
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0
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0
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0
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1
0
true
0
1
0
1
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1
0
0
null
0
0
0
0
0
0
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0
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0
0
1
0
0
0
0
0
0
0
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null
0
0
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0
0
0
1
0
1
0
1
0
0
5
9b3f64063634694081ef26d6048b7aa5d8e76b4e
38
py
Python
Lezione 1/ciao.py
pietro2356/CorsoCrittografiaAFP
57c8de876abf8dce3e96f39b543e48a498079de4
[ "MIT" ]
1
2022-01-13T13:22:38.000Z
2022-01-13T13:22:38.000Z
Lezione 1/ciao.py
pietro2356/CorsoCrittografiaAFP
57c8de876abf8dce3e96f39b543e48a498079de4
[ "MIT" ]
null
null
null
Lezione 1/ciao.py
pietro2356/CorsoCrittografiaAFP
57c8de876abf8dce3e96f39b543e48a498079de4
[ "MIT" ]
null
null
null
def ciao(): print("Hello") ciao()
9.5
18
0.552632
5
38
4.2
0.8
0
0
0
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0
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0.210526
38
4
19
9.5
0.7
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0.333333
true
0
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0.333333
0.333333
1
1
0
null
0
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null
0
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1
1
0
0
0
0
0
0
5
9b58fcca622e93bbeef7ecd5a43576355d1e06f6
902
py
Python
applications/view/admin/__init__.py
wangyuan02605/webcloud
e57a2713125b751ee8bb8da29b789e2044e789aa
[ "MIT" ]
5
2021-12-13T14:52:08.000Z
2022-03-15T08:59:32.000Z
applications/view/admin/__init__.py
wangyuan02605/webcloud
e57a2713125b751ee8bb8da29b789e2044e789aa
[ "MIT" ]
null
null
null
applications/view/admin/__init__.py
wangyuan02605/webcloud
e57a2713125b751ee8bb8da29b789e2044e789aa
[ "MIT" ]
1
2022-01-21T04:43:58.000Z
2022-01-21T04:43:58.000Z
from flask import Flask from applications.view.admin.admin_log import admin_log from applications.view.admin.dict import admin_dict from applications.view.admin.index import admin_bp from applications.view.admin.file import admin_file from applications.view.admin.power import admin_power from applications.view.admin.role import admin_role from applications.view.admin.user import admin_user from applications.view.admin.monitor import admin_monitor_bp from applications.view.admin.task import admin_task def register_admin_views(app: Flask): app.register_blueprint(admin_bp) app.register_blueprint(admin_user) app.register_blueprint(admin_file) app.register_blueprint(admin_monitor_bp) app.register_blueprint(admin_log) app.register_blueprint(admin_power) app.register_blueprint(admin_role) app.register_blueprint(admin_dict) app.register_blueprint(admin_task)
37.583333
60
0.834812
130
902
5.546154
0.161538
0.199723
0.249653
0.312067
0.149792
0
0
0
0
0
0
0
0.100887
902
23
61
39.217391
0.889026
0
0
0
0
0
0
0
0
0
0
0
0
1
0.05
false
0
0.5
0
0.55
0.45
0
0
0
null
0
1
1
0
0
0
0
0
0
0
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0
0
0
0
0
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0
null
0
0
0
0
0
0
0
0
1
0
1
1
0
5
9b6700af21394488c2381cff198f5f35bf35e99a
82
py
Python
ws/handler/event/appliance/__init__.py
fabaff/automate-ws
a9442f287692787e3f253e1ff23758bec8f3902e
[ "MIT" ]
null
null
null
ws/handler/event/appliance/__init__.py
fabaff/automate-ws
a9442f287692787e3f253e1ff23758bec8f3902e
[ "MIT" ]
1
2021-12-21T11:34:47.000Z
2021-12-21T11:34:47.000Z
ws/handler/event/appliance/__init__.py
fabaff/automate-ws
a9442f287692787e3f253e1ff23758bec8f3902e
[ "MIT" ]
1
2021-12-21T10:10:13.000Z
2021-12-21T10:10:13.000Z
from ws.handler.event.appliance import event, light, sound, sprinkler, thermostat
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0.817073
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1
0
0
5
9b716b17ccaf2199e470ad98f6cc402bc67c4b70
90
py
Python
modoboa/core/checks/__init__.py
HarshCasper/modoboa
a00baa0593107992f545ee3e89cd4346b9615a96
[ "0BSD" ]
1,602
2016-12-15T14:25:34.000Z
2022-03-31T16:49:25.000Z
modoboa/core/checks/__init__.py
sebageek/modoboa
57f5d57ea60a57e8dcac970085dfc07082481fc6
[ "0BSD" ]
1,290
2016-12-14T15:39:05.000Z
2022-03-31T13:49:09.000Z
modoboa/core/checks/__init__.py
sebageek/modoboa
57f5d57ea60a57e8dcac970085dfc07082481fc6
[ "0BSD" ]
272
2016-12-22T11:58:18.000Z
2022-03-17T15:57:24.000Z
# Import these to force registration of checks from . import settings_checks # NOQA:F401
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0.788889
13
90
5.384615
0.846154
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0.166667
90
2
47
45
0.893333
0.6
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0
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1
0
0
null
0
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0
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0
0
1
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0
0
0
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null
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0
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0
0
0
1
0
1
0
1
0
0
5
9b8d29dc80fd2145ebde1c69bcc20726150589e9
51
py
Python
venv/lib/python3.9/site-packages/__init__.py
lyushher/YBrowser
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
[ "MIT" ]
9
2021-07-25T22:45:52.000Z
2021-11-13T03:39:05.000Z
venv/lib/python3.9/site-packages/__init__.py
lyushher/YBrowser
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
[ "MIT" ]
null
null
null
venv/lib/python3.9/site-packages/__init__.py
lyushher/YBrowser
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
[ "MIT" ]
null
null
null
from . import scraper from .browser import Browser
17
28
0.803922
7
51
5.857143
0.571429
0
0
0
0
0
0
0
0
0
0
0
0.156863
51
2
29
25.5
0.953488
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
fd3721e576688b548e98250d3e7be4c3ebadbee6
72
py
Python
bibletext/models/__init__.py
richardbolt/django-bibletext
c060bb54e2a55795509f7b73301faf2df4b2d27d
[ "BSD-3-Clause" ]
4
2015-09-09T02:22:56.000Z
2021-02-12T03:13:10.000Z
bibletext/models/__init__.py
richardbolt/django-bibletext
c060bb54e2a55795509f7b73301faf2df4b2d27d
[ "BSD-3-Clause" ]
null
null
null
bibletext/models/__init__.py
richardbolt/django-bibletext
c060bb54e2a55795509f7b73301faf2df4b2d27d
[ "BSD-3-Clause" ]
2
2016-03-05T11:25:19.000Z
2021-04-20T18:30:37.000Z
from bibles import * from kjv import KJV from scripture import Scripture
24
31
0.833333
11
72
5.454545
0.454545
0
0
0
0
0
0
0
0
0
0
0
0.152778
72
3
31
24
0.983607
0
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0
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0
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0
0
1
0
true
0
1
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1
0
1
0
0
null
0
0
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0
0
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0
0
0
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1
0
0
0
0
0
0
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0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
5
fd5d681f700ed90ccfaa53fb97f8bd759a847060
426
py
Python
LoopStructural/datasets/__init__.py
vpicavet/LoopStructural
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
[ "MIT" ]
null
null
null
LoopStructural/datasets/__init__.py
vpicavet/LoopStructural
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
[ "MIT" ]
null
null
null
LoopStructural/datasets/__init__.py
vpicavet/LoopStructural
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
[ "MIT" ]
null
null
null
from ._base import load_claudius from ._base import load_grose2017 from ._base import load_grose2018 from ._base import load_grose2019 from ._base import load_laurent2016 from ._base import load_noddy_single_fold from ._base import load_intrusion from ._base import normal_vector_headers from ._base import strike_dip_headers from ._base import value_headers from ._base import load_unconformity from ._base import load_duplex
35.5
41
0.861502
64
426
5.296875
0.328125
0.283186
0.495575
0.477876
0
0
0
0
0
0
0
0.042216
0.110329
426
12
42
35.5
0.852243
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0
0
0
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0
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0
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0
0
0
1
0
true
0
1
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1
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0
0
0
null
1
1
1
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0
0
0
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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
fd5f2d186c1e64084a9639f212943b6f1f6cabe0
62
py
Python
experiments/char_rnn/pt_rnn/__init__.py
slyubomirsky/relay-bench-1
abe5a262ee7ded76748130d0fcfbc80e570311c1
[ "Apache-2.0" ]
7
2019-10-03T22:41:18.000Z
2020-05-31T18:52:15.000Z
experiments/char_rnn/pt_rnn/__init__.py
slyubomirsky/relay-bench-1
abe5a262ee7ded76748130d0fcfbc80e570311c1
[ "Apache-2.0" ]
14
2019-10-18T19:13:53.000Z
2021-09-08T01:36:37.000Z
experiments/char_rnn/pt_rnn/__init__.py
slyubomirsky/relay-bench-1
abe5a262ee7ded76748130d0fcfbc80e570311c1
[ "Apache-2.0" ]
4
2019-10-03T21:34:03.000Z
2022-02-23T10:29:49.000Z
from .char_rnn_generator import RNN from .util import samples
20.666667
35
0.83871
10
62
5
0.7
0
0
0
0
0
0
0
0
0
0
0
0.129032
62
2
36
31
0.925926
0
0
0
0
0
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1
0
true
0
1
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1
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1
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0
null
0
0
0
0
0
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0
0
0
0
0
0
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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
b5e025e90ae5e4b9d0af22158f36b82768e39a2d
124
py
Python
evennia/contrib/tutorials/talking_npc/__init__.py
davidrideout/evennia
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
[ "BSD-3-Clause" ]
null
null
null
evennia/contrib/tutorials/talking_npc/__init__.py
davidrideout/evennia
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
[ "BSD-3-Clause" ]
null
null
null
evennia/contrib/tutorials/talking_npc/__init__.py
davidrideout/evennia
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
[ "BSD-3-Clause" ]
null
null
null
""" Talking NPC - Griatch 2011, grungies1138 2016 """ from .talking_npc import CmdTalk, TalkingCmdSet, TalkingNPC # noqa
17.714286
67
0.741935
14
124
6.5
0.857143
0.21978
0
0
0
0
0
0
0
0
0
0.115385
0.16129
124
6
68
20.666667
0.759615
0.41129
0
0
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1
0
true
0
1
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1
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1
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0
null
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null
0
0
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0
0
1
0
1
0
0
0
0
5
b5e69500503f975c9deb2984c54cc343c38a65d2
8,471
py
Python
parser/team23/grammar/parsetab.py
wendychamale/tytus
e5e6d9349f609360370edcfbb65b8c93b21f1bab
[ "MIT" ]
null
null
null
parser/team23/grammar/parsetab.py
wendychamale/tytus
e5e6d9349f609360370edcfbb65b8c93b21f1bab
[ "MIT" ]
null
null
null
parser/team23/grammar/parsetab.py
wendychamale/tytus
e5e6d9349f609360370edcfbb65b8c93b21f1bab
[ "MIT" ]
null
null
null
# parsetab.py # This file is automatically generated. Do not edit. # pylint: disable=W,C,R _tabversion = '3.10' _lr_method = 'LALR' _lr_signature = 'leftIGUALDADDESIGUALDADleftMAYORMENORMAYORIGUALMENORIGUALleftSUMARESTAleftMULTIPLICACIONDIVISIONleftPAR_ABREPAR_CIERRALLAVE_ABRELLAVE_CIERRACADENA DECIMAL DESIGUALDAD DIVISION ELSE ENTERO ID IF IGUALDAD IMPRIMIR LLAVE_ABRE LLAVE_CIERRA MAYOR MAYORIGUAL MENOR MENORIGUAL MULTIPLICACION PAR_ABRE PAR_CIERRA PUNTOCOMA RESTA SUMA WHILEinit : instruccionesinstrucciones : instrucciones instruccioninstrucciones : instruccion instruccion : imprimir_\n | if_statement\n | while_statementexpresion_ : expresion_ SUMA expresion_\n | expresion_ RESTA expresion_\n | expresion_ MULTIPLICACION expresion_\n | expresion_ DIVISION expresion_\n | expresion_ IGUALDAD expresion_\n | expresion_ DESIGUALDAD expresion_\n | expresion_ MAYOR expresion_\n | expresion_ MENOR expresion_\n | expresion_ MAYORIGUAL expresion_\n | expresion_ MENORIGUAL expresion_\n | expif_statement : IF PAR_ABRE expresion_ PAR_CIERRA statement else_statementelse_statement : ELSE statement\n | ELSE if_statement\n | while_statement : WHILE PAR_ABRE expresion_ PAR_CIERRA statementstatement : LLAVE_ABRE instrucciones LLAVE_CIERRA\n | LLAVE_ABRE LLAVE_CIERRAimprimir_ : IMPRIMIR PAR_ABRE expresion_ PAR_CIERRA PUNTOCOMAexp : primitivoprimitivo : ENTEROprimitivo : DECIMALprimitivo : CADENAprimitivo : varsvars : ID' _lr_action_items = {'IMPRIMIR':([0,2,3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[7,7,-3,-4,-5,-6,-2,-25,-21,7,-22,-18,7,-24,-19,-20,-23,]),'IF':([0,2,3,4,5,6,10,37,48,49,50,51,52,53,54,55,56,57,],[8,8,-3,-4,-5,-6,-2,-25,-21,8,-22,-18,8,8,-24,-19,-20,-23,]),'WHILE':([0,2,3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[9,9,-3,-4,-5,-6,-2,-25,-21,9,-22,-18,9,-24,-19,-20,-23,]),'$end':([1,2,3,4,5,6,10,37,48,50,51,54,55,56,57,],[0,-1,-3,-4,-5,-6,-2,-25,-21,-22,-18,-24,-19,-20,-23,]),'LLAVE_CIERRA':([3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[-3,-4,-5,-6,-2,-25,-21,54,-22,-18,57,-24,-19,-20,-23,]),'PAR_ABRE':([7,8,9,],[11,12,13,]),'ENTERO':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[17,17,17,17,17,17,17,17,17,17,17,17,17,]),'DECIMAL':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[18,18,18,18,18,18,18,18,18,18,18,18,18,]),'CADENA':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[19,19,19,19,19,19,19,19,19,19,19,19,19,]),'ID':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[21,21,21,21,21,21,21,21,21,21,21,21,21,]),'PAR_CIERRA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[24,-17,-26,-27,-28,-29,-30,-31,35,36,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'SUMA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[25,-17,-26,-27,-28,-29,-30,-31,25,25,-7,-8,-9,-10,25,25,25,25,25,25,]),'RESTA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[26,-17,-26,-27,-28,-29,-30,-31,26,26,-7,-8,-9,-10,26,26,26,26,26,26,]),'MULTIPLICACION':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[27,-17,-26,-27,-28,-29,-30,-31,27,27,27,27,-9,-10,27,27,27,27,27,27,]),'DIVISION':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[28,-17,-26,-27,-28,-29,-30,-31,28,28,28,28,-9,-10,28,28,28,28,28,28,]),'IGUALDAD':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[29,-17,-26,-27,-28,-29,-30,-31,29,29,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'DESIGUALDAD':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[30,-17,-26,-27,-28,-29,-30,-31,30,30,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'MAYOR':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[31,-17,-26,-27,-28,-29,-30,-31,31,31,-7,-8,-9,-10,31,31,-13,-14,-15,-16,]),'MENOR':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[32,-17,-26,-27,-28,-29,-30,-31,32,32,-7,-8,-9,-10,32,32,-13,-14,-15,-16,]),'MAYORIGUAL':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[33,-17,-26,-27,-28,-29,-30,-31,33,33,-7,-8,-9,-10,33,33,-13,-14,-15,-16,]),'MENORIGUAL':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[34,-17,-26,-27,-28,-29,-30,-31,34,34,-7,-8,-9,-10,34,34,-13,-14,-15,-16,]),'PUNTOCOMA':([24,],[37,]),'LLAVE_ABRE':([35,36,52,],[49,49,49,]),'ELSE':([48,54,57,],[52,-24,-23,]),} _lr_action = {} for _k, _v in _lr_action_items.items(): for _x,_y in zip(_v[0],_v[1]): if not _x in _lr_action: _lr_action[_x] = {} _lr_action[_x][_k] = _y del _lr_action_items _lr_goto_items = {'init':([0,],[1,]),'instrucciones':([0,49,],[2,53,]),'instruccion':([0,2,49,53,],[3,10,3,10,]),'imprimir_':([0,2,49,53,],[4,4,4,4,]),'if_statement':([0,2,49,52,53,],[5,5,5,56,5,]),'while_statement':([0,2,49,53,],[6,6,6,6,]),'expresion_':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[14,22,23,38,39,40,41,42,43,44,45,46,47,]),'exp':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[15,15,15,15,15,15,15,15,15,15,15,15,15,]),'primitivo':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[16,16,16,16,16,16,16,16,16,16,16,16,16,]),'vars':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[20,20,20,20,20,20,20,20,20,20,20,20,20,]),'statement':([35,36,52,],[48,50,55,]),'else_statement':([48,],[51,]),} _lr_goto = {} for _k, _v in _lr_goto_items.items(): for _x, _y in zip(_v[0], _v[1]): if not _x in _lr_goto: _lr_goto[_x] = {} _lr_goto[_x][_k] = _y del _lr_goto_items _lr_productions = [ ("S' -> init","S'",1,None,None,None), ('init -> instrucciones','init',1,'p_init','execute.py',125), ('instrucciones -> instrucciones instruccion','instrucciones',2,'p_instrucciones_lista','execute.py',129), ('instrucciones -> instruccion','instrucciones',1,'p_instrucciones_instruccion','execute.py',134), ('instruccion -> imprimir_','instruccion',1,'p_instruccion','execute.py',138), ('instruccion -> if_statement','instruccion',1,'p_instruccion','execute.py',139), ('instruccion -> while_statement','instruccion',1,'p_instruccion','execute.py',140), ('expresion_ -> expresion_ SUMA expresion_','expresion_',3,'p_expresion_','execute.py',144), ('expresion_ -> expresion_ RESTA expresion_','expresion_',3,'p_expresion_','execute.py',145), ('expresion_ -> expresion_ MULTIPLICACION expresion_','expresion_',3,'p_expresion_','execute.py',146), ('expresion_ -> expresion_ DIVISION expresion_','expresion_',3,'p_expresion_','execute.py',147), ('expresion_ -> expresion_ IGUALDAD expresion_','expresion_',3,'p_expresion_','execute.py',148), ('expresion_ -> expresion_ DESIGUALDAD expresion_','expresion_',3,'p_expresion_','execute.py',149), ('expresion_ -> expresion_ MAYOR expresion_','expresion_',3,'p_expresion_','execute.py',150), ('expresion_ -> expresion_ MENOR expresion_','expresion_',3,'p_expresion_','execute.py',151), ('expresion_ -> expresion_ MAYORIGUAL expresion_','expresion_',3,'p_expresion_','execute.py',152), ('expresion_ -> expresion_ MENORIGUAL expresion_','expresion_',3,'p_expresion_','execute.py',153), ('expresion_ -> exp','expresion_',1,'p_expresion_','execute.py',154), ('if_statement -> IF PAR_ABRE expresion_ PAR_CIERRA statement else_statement','if_statement',6,'p_if_instr','execute.py',170), ('else_statement -> ELSE statement','else_statement',2,'p_else_instr','execute.py',174), ('else_statement -> ELSE if_statement','else_statement',2,'p_else_instr','execute.py',175), ('else_statement -> <empty>','else_statement',0,'p_else_instr','execute.py',176), ('while_statement -> WHILE PAR_ABRE expresion_ PAR_CIERRA statement','while_statement',5,'p_while_instr','execute.py',184), ('statement -> LLAVE_ABRE instrucciones LLAVE_CIERRA','statement',3,'p_statement','execute.py',188), ('statement -> LLAVE_ABRE LLAVE_CIERRA','statement',2,'p_statement','execute.py',189), ('imprimir_ -> IMPRIMIR PAR_ABRE expresion_ PAR_CIERRA PUNTOCOMA','imprimir_',5,'p_imprimir_instr','execute.py',194), ('exp -> primitivo','exp',1,'p_exp_primitivo','execute.py',198), ('primitivo -> ENTERO','primitivo',1,'p_exp_entero','execute.py',202), ('primitivo -> DECIMAL','primitivo',1,'p_exp_decimal','execute.py',207), ('primitivo -> CADENA','primitivo',1,'p_exp_cadena','execute.py',211), ('primitivo -> vars','primitivo',1,'p_exp_variables','execute.py',215), ('vars -> ID','vars',1,'p_exp_id','execute.py',219), ]
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b5eee5f9113d468d36f5b2aecd6fe752b7b17cb7
30
py
Python
python/class_calling_itself.py
robotlightsyou/test
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
[ "MIT" ]
2
2019-05-26T15:09:34.000Z
2021-09-12T08:01:23.000Z
python/class_calling_itself.py
robotlightsyou/test
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
[ "MIT" ]
null
null
null
python/class_calling_itself.py
robotlightsyou/test
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
[ "MIT" ]
1
2021-04-11T20:28:21.000Z
2021-04-11T20:28:21.000Z
class Test: TEST = Test()
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bd17baed38f738943c0c1803e928c48e0e9aa364
267
py
Python
tests/context.py
Pythonimous/pyml
3ecb86140501bf278e46102f8873d2b0228a94f5
[ "BSD-3-Clause" ]
null
null
null
tests/context.py
Pythonimous/pyml
3ecb86140501bf278e46102f8873d2b0228a94f5
[ "BSD-3-Clause" ]
null
null
null
tests/context.py
Pythonimous/pyml
3ecb86140501bf278e46102f8873d2b0228a94f5
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- import sys import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) print(sys.path[0]) # TODO: разберись с https://github.com/navdeep-G/samplemod/commit/48f4c8dba40cb2fe03a74a7a4d7d979892601ddc import pyml
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5
bd1aad8a273c362fb4fb0317d78380a2f4d87464
47
py
Python
skanalytics/reporting/exception.py
jimmyskull/skanalytics
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
[ "MIT" ]
null
null
null
skanalytics/reporting/exception.py
jimmyskull/skanalytics
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
[ "MIT" ]
null
null
null
skanalytics/reporting/exception.py
jimmyskull/skanalytics
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
[ "MIT" ]
null
null
null
class ReportingException(Exception): pass
11.75
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0
5
bd1e617956a494811e97cf195d3cd3f79fb2669d
25,141
py
Python
bts/models/regression.py
benlau6/hierarchy-bayesian-modeling-time-series-sensor
b30f405f865daf973e59a99f24281cd49baac7df
[ "MIT" ]
null
null
null
bts/models/regression.py
benlau6/hierarchy-bayesian-modeling-time-series-sensor
b30f405f865daf973e59a99f24281cd49baac7df
[ "MIT" ]
null
null
null
bts/models/regression.py
benlau6/hierarchy-bayesian-modeling-time-series-sensor
b30f405f865daf973e59a99f24281cd49baac7df
[ "MIT" ]
1
2021-08-02T06:20:14.000Z
2021-08-02T06:20:14.000Z
import pandas as pd import seaborn as sns import matplotlib.pyplot as plt import numpy as np import statsmodels.api as sm import pymc3 as pm import theano.tensor as tt import arviz as az from scipy import stats as sts import warnings import abc warnings.simplefilter(action="ignore", category=FutureWarning) class BayesModel(metaclass=abc.ABCMeta): def __init__(self, y, t, dt, num_samples=1000, num_burnin=2000, threshold_t=7): self.model = pm.Model() self.y = y self.t = t self.dt = dt self.N = y.shape[0] self.threshold_t = threshold_t self.num_samples = num_samples self.num_burnin = num_burnin self.trace = [] self.ppc = [] @classmethod def from_df(cls, df, target, num_samples=1000, num_burnin=2000, threshold_t=24): fig, axes = plt.subplots(1, 2, figsize=(16, 4)) # check difference sns.scatterplot(data=df, x=df.index, y=df[target], ax=axes[0]) axes[0].set_title('pre-preprocessing') # preprocessing #self.df = self.df.assign(week=self.df.index.isocalendar().week) #self.df[target] = self.df.groupby(['week'])[target].transform(lambda x: x.clip(x.quantile(0.05), x.quantile(0.95))) #self.df = self.df.drop(['week'], axis=1) df = df.resample('h').mean().dropna() # check difference sns.scatterplot(data=df, x=df.index, y=df.columns[0], ax=axes[1]) axes[1].set_title('post-preprocessing') #fig.autofmt_xdate(rotation=90) #axes[0].set_xticks(axes[0].get_xticks()[::2]) #axes[1].set_xticks(axes[1].get_xticks()[::2]) fig.tight_layout() y = df.values.flatten() dt = df.index t = cls.dt2t(dt) return cls(y, t, dt, num_samples=num_samples, num_burnin=num_burnin, threshold_t=threshold_t) @classmethod def from_csv(cls, path, index, target, unique_cols, unique_vals, num_samples=1000, num_burnin=2000, threshold_t=24): df = pd.read_csv(path, usecols=[index, *unique_cols, target]) for col, val in zip(unique_cols, unique_vals): mask = df[col] == val df = df[mask] df = df.drop(unique_cols, axis=1) df[index] = pd.to_datetime(df[index]) df = df.set_index(index) return cls.from_df(df, target, num_samples=num_samples, num_burnin=num_burnin, threshold_t=threshold_t) @staticmethod def sample_data(N=100, sp_loc=0.7, mu_1=1440, mu_2=1445, beta_1=0.03, beta_2=0.1, sigma_1=0.3, sigma_2=0.6): N = N sp = int(N*sp_loc) t = np.arange(0, N) eps_1 = np.random.normal(0, sigma_1, sp) eps_2 = np.random.normal(0, sigma_2, N-sp) y_1 = mu_1+beta_1*t[:sp] + eps_1 y_2 = mu_2+beta_2*(t[sp:]-sp) + eps_2 y = np.concatenate((y_1, y_2)) start = pd.to_datetime('2021-06-01') dt = start + pd.TimedeltaIndex(t, unit='hour') _, ax = plt.subplots(figsize=(12, 6)) sns.scatterplot(y=y, x=dt, ax=ax) plt.show() return y, t, dt @staticmethod def dt2t(dt): return ((dt - dt[0]).total_seconds().astype(int)//3600).values def t2dt(self, t): # t to datetime return self.dt[0] + pd.Timedelta(hours=t) def fit(self): with self.model: self.trace = pm.sample(self.num_samples, tune=self.num_burnin, return_inferencedata=True) def _get_posterior_parm(self, arr, parm, val_type='float', stats='mean'): N = len(arr) if stats == 'median': #arr = np.round(trace['switch'][samples//2:]).astype(int) #counts = np.bincount(arr) #switchpoint_post = np.argmax(counts) parm_p = np.median(arr[parm][N//2:]) elif stats == 'mean': parm_p = np.mean(arr[parm][N//2:]) if val_type == 'int': parm_p = np.round(parm_p).astype(int) return parm_p def plot_trace(self): with self.model: pm.plot_trace(self.trace) plt.show() @abc.abstractmethod def define_model(self): return NotImplemented @abc.abstractmethod def plot_posterior_predictive(self): return NotImplemented #def plot_linear_model(self): # with self.model: # switchpoint_post = self._get_posterior_parm(self.trace, 'switch', val_type='int') # mu_1_post = self._get_posterior_parm(self.trace, 'mu_1') # mu_2_post = self._get_posterior_parm(self.trace, 'mu_2') # beta_1_post = self._get_posterior_parm(self.trace, 'beta_1') # beta_2_post = self._get_posterior_parm(self.trace, 'beta_2') # sigma_1_post = self._get_posterior_parm(self.trace, 'sigma_1') # sigma_2_post = self._get_posterior_parm(self.trace, 'sigma_2') # sigma_sensor_post = self._get_posterior_parm(self.trace, 'sigma_sensor') # y1_post = mu_1_post+beta_1_post*self.t[:switchpoint_post] # y2_post = mu_2_post+beta_2_post*(self.t[switchpoint_post:]-switchpoint_post) # y_post = np.concatenate((y1_post, y2_post)) # sns.scatterplot(data=self.y) # plt.plot(range(switchpoint_post), y1_post, color='red') # plt.plot(range(switchpoint_post, self.t), y2_post, color='red') # plt.fill_between(range(switchpoint_post), y1_post-2*(sigma_1_post+sigma_sensor_post), y1_post+2*(sigma_1_post+sigma_sensor_post), alpha=.3) # plt.fill_between(range(switchpoint_post, self.N), y2_post-2*(sigma_2_post+sigma_sensor_post), y2_post+2*(sigma_2_post+sigma_sensor_post), alpha=.3) # plt.axvline(x=switchpoint_post, ls='--', c='blue') # plt.title(f'RMSE: {rmse:.2f}') # plt.show() class BaseLineModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) coeff_std = np.nanstd(np.diff(clipped_y, n=1, axis=0)) y_mean = np.nanmean(self.y) y_std = np.nanstd(self.y) with self.model: # intercept mu_ = pm.Normal("y_mu", mu=y_mean, sigma=y_std) # coefficient beta_ = pm.HalfNormal('y_beta', sigma=coeff_std) # error term sigma_ = pm.HalfNormal("sigma_", sigma=y_std*2, testval=y_std) nu = pm.Gamma('nu', alpha=2, beta=0.1) # likelihood y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*self.t, sigma=sigma_, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs"]) xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1)) mu_pp = (self.ppc["y_mu"][:,None] + self.ppc["y_beta"][:,None] * xs) mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show() class SwitchPointBasicModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0)) late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0)) early_p50 = np.nanquantile(self.y[:self.N//2], 0.5) late_p50 = np.nanquantile(self.y[self.N//2:], 0.5) early_std = np.nanstd(self.y[:self.N//2]) late_std = np.nanstd(self.y[self.N//2:]) sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75)))) sensor_std = np.nanstd(self.y) with self.model: # switch, weight, time multiplier with coefficient switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2) w = pm.math.sigmoid(2*(self.t-switchpoint)) t_ = (1-w)*self.t + w*(self.t-switchpoint) # intercept mu_1 = pm.Normal("mu_1", mu=early_p50, sigma=early_std) mu_2 = pm.Normal("mu_2", mu=late_p50, sigma=late_std) mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2) # error term #sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu) #sigma_sensor = sensor_std sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std) sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std) sigma_ = pm.Deterministic("y_sigma", (1-w)*(sigma_1) + w*(sigma_2)) nu = pm.Gamma('nu', alpha=2, beta=0.1) # likelihood y_obs = pm.StudentT("obs", nu=nu, mu=mu_, sigma=sigma_, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "obs", "switch"]) mu_pp = (self.ppc["y_mu"]) mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int') sp_hpd = az.hdi(self.ppc['switch']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint') ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD') ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey') ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show() class SwitchPointModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0)) late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0)) early_p10 = np.nanquantile(self.y[:self.N//2], 0.1) late_p10 = np.nanquantile(self.y[self.N//2:], 0.1) early_std = np.nanstd(self.y[:self.N//2]) late_std = np.nanstd(self.y[self.N//2:]) sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75)))) sensor_std = np.nanstd(self.y) with self.model: # switch, weight, time multiplier with coefficient switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2) w = pm.math.sigmoid(2*(self.t-switchpoint)) t_ = (1-w)*self.t + w*(self.t-switchpoint) # intercept mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std) mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std) mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2) # coefficient beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std) beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std) beta_ = pm.Deterministic("y_beta", (1-w)*beta_1 + w*beta_2) # error term sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu) sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std) sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std) sigma_ = pm.Deterministic("y_sigma", (1-w)*(sigma_1+sigma_sensor) + w*(sigma_2+sigma_sensor)) nu = pm.Gamma('nu', alpha=2, beta=0.1) # likelihood y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"]) xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1)) xs_mask = xs - self.ppc['switch'][:,None] > 0 for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']): x[mask] = x[mask] - switchpoint mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs) mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int') sp_hpd = az.hdi(self.ppc['switch']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint') ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD') ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey') ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show() class SwitchPointNonCenteredModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0)) late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0)) early_p10 = np.nanquantile(self.y[:self.N//2], 0.1) late_p10 = np.nanquantile(self.y[self.N//2:], 0.1) early_std = np.nanstd(self.y[:self.N//2]) late_std = np.nanstd(self.y[self.N//2:]) sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75)))) sensor_std = np.nanstd(self.y) with self.model: # switch, weight, time multiplier with coefficient switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2) w = pm.math.sigmoid(2*(self.t-switchpoint)) t_ = (1-w)*self.t + w*(self.t-switchpoint) # intercept mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std) mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std) mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2) # coefficient beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std) beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std) beta_ = pm.Deterministic("y_beta", (1-w)*beta_1 + w*beta_2) # error term sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu) sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std) sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std) sigma_ = pm.Deterministic("y_sigma", (1-w)*sigma_1+sigma_sensor + w*sigma_2+sigma_sensor) nu = pm.Gamma('nu', alpha=2, beta=0.1) # likelihood y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"]) xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1)) xs_mask = xs - self.ppc['switch'][:,None] > 0 for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']): x[mask] = x[mask] - switchpoint mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs) mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int') sp_hpd = az.hdi(self.ppc['switch']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint') ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD') ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey') ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show() class SwitchPointDiscreteModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0)) late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0)) early_p10 = np.nanquantile(self.y[:self.N//2], 0.1) late_p10 = np.nanquantile(self.y[self.N//2:], 0.1) early_std = np.nanstd(self.y[:self.N//2]) late_std = np.nanstd(self.y[self.N//2:]) sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75)))) sensor_std = np.nanstd(self.y) with self.model: # switch, weight, time multiplier with coefficient switchpoint = pm.DiscreteUniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2) t_ = pm.math.switch(self.t<switchpoint, self.t, self.t-switchpoint) # to be examine, for multiple change point #w1 = pm.math.sigmoid(2*(t-sp1)) #w2 = pm.math.sigmoid(2*(t-sp2)) #t_ = (1-w1)*t + w1*((1-w2)*(t-sp1) + w2*(t-sp2)) # intercept mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std) mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std) mu_ = pm.Deterministic("y_mu", pm.math.switch(self.t<switchpoint, mu_1, mu_2)) # coefficient beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std) beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std) beta_ = pm.Deterministic("y_beta", pm.math.switch(self.t<switchpoint, beta_1, beta_2)) # error term sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu) sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std) sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std) sigma_ = pm.math.switch(self.t<switchpoint, sigma_1+sigma_sensor, sigma_2+sigma_sensor) nu = pm.Gamma('nu', alpha=2, beta=0.1) # likelihood y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"]) xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1)) xs_mask = xs - self.ppc['switch'][:,None] > 0 for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']): x[mask] = x[mask] - switchpoint mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs) mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int') sp_hpd = az.hdi(self.ppc['switch']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint') ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD') ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey') ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show() class GaussianProcessModel(BayesModel): def define_model(self): clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9))) early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0)) late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0)) early_p10 = np.nanquantile(self.y[:self.N//2], 0.1) late_p10 = np.nanquantile(self.y[self.N//2:], 0.1) early_std = np.nanstd(self.y[:self.N//2]) late_std = np.nanstd(self.y[self.N//2:]) sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75)))) sensor_std = np.nanstd(self.y) with self.model: ## intercept #sigma_ = pm.HalfNormal("sigma_", sigma=early_std*2, testval=early_std) #mu_drift = pm.Normal('mu_drift', mu=early_p10, sigma=early_std) #mu_ = pm.GaussianRandomWalk('mu_', mu=mu_drift, sd=sigma_, shape=self.y.shape[0]) # ## error term # # #nu = pm.Gamma('nu', alpha=2, beta=0.1) ## likelihood #y_obs = pm.StudentT("obs", nu=nu, mu=mu_, sigma=sigma_sensor, observed=self.y) sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu) sigma_ = pm.HalfCauchy('sigma_', beta=self.y.std()) mu_drift = pm.Normal('mu_drift', mu=self.y.mean(), sigma=self.y.std()) mu_ = pm.GaussianRandomWalk('y_mu', mu=mu_drift, sd=sigma_, shape=self.y.size) nu = pm.Gamma('nu', alpha=2, beta=0.1) y_obs = pm.StudentT('obs', mu=mu_, sigma=sigma_sensor, nu=nu, observed=self.y) def plot_posterior_predictive(self): with self.model: self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "obs"]) mu_pp = self.ppc["y_mu"] mu_hpd = az.hdi(mu_pp) obs_hpd = az.hdi(self.ppc['obs']) _, ax = plt.subplots(figsize=(16, 8)) ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data") ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD") ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y") ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD") ax.set_xlabel("datetime") ax.set_ylabel("y") ax.set_title("Continous Posterior predictive checks") ax.legend(ncol=2, fontsize=10) plt.show()
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bd2a7d45db7d5b2e8ab5865988a10638d3564d86
1,404
py
Python
restrain_jit/becython/stack_vm_instructions.py
thautwarm/restrain-jit
f76b3e9ae8a34d2eef87a42cc87197153f14634c
[ "MIT" ]
116
2019-09-18T15:43:09.000Z
2022-02-18T15:28:08.000Z
restrain_jit/becython/stack_vm_instructions.py
thautwarm/restrain-jit
f76b3e9ae8a34d2eef87a42cc87197153f14634c
[ "MIT" ]
6
2019-09-18T16:12:49.000Z
2021-02-03T13:01:42.000Z
restrain_jit/becython/stack_vm_instructions.py
thautwarm/restrain-jit
f76b3e9ae8a34d2eef87a42cc87197153f14634c
[ "MIT" ]
8
2019-09-19T07:15:05.000Z
2022-01-19T19:40:10.000Z
from enum import Enum, auto as _auto import abc import typing as t from dataclasses import dataclass from restrain_jit.becython.representations import * class Instr: pass @dataclass(frozen=True, order=True) class A: lhs:t.Optional[str] rhs:Instr pass @dataclass(frozen=True, order=True) class SetLineno(Instr): lineno:int pass @dataclass(frozen=True, order=True) class App(Instr): f:Repr args:t.List[Repr] pass @dataclass(frozen=True, order=True) class Ass(Instr): reg:Reg val:Repr pass @dataclass(frozen=True, order=True) class Load(Instr): reg:Reg pass @dataclass(frozen=True, order=True) class Store(Instr): reg:Reg val:Repr pass @dataclass(frozen=True, order=True) class JmpIf(Instr): label:object cond:Repr pass @dataclass(frozen=True, order=True) class JmpIfPush(Instr): label:object cond:Repr leave:Repr pass @dataclass(frozen=True, order=True) class Jmp(Instr): label:object pass @dataclass(frozen=True, order=True) class Label(Instr): label:object pass @dataclass(frozen=True, order=True) class Peek(Instr): offset:int pass @dataclass(frozen=True, order=True) class Return(Instr): val:Repr pass @dataclass(frozen=True, order=True) class Push(Instr): val:Repr pass @dataclass(frozen=True, order=True) class Pop(Instr): pass
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bd2d42a708e8e77cb927260a1b2aad36ae2e30fb
157
py
Python
src/yeelight_atmosphere/exception.py
NikSavilov/yeelight-atmosphere
8860c2869380be50a6305b5b2aa77ed3636145d3
[ "MIT" ]
null
null
null
src/yeelight_atmosphere/exception.py
NikSavilov/yeelight-atmosphere
8860c2869380be50a6305b5b2aa77ed3636145d3
[ "MIT" ]
7
2021-11-13T13:07:21.000Z
2021-11-19T16:30:37.000Z
src/yeelight_atmosphere/exception.py
NikSavilov/yeelight-atmosphere
8860c2869380be50a6305b5b2aa77ed3636145d3
[ "MIT" ]
null
null
null
""" Exceptions module. """ from yeelight import BulbException class BulbConnectionLostException(BulbException): """ Raises when connection is lost """
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1f9eb83ee3e0121409cacbc36d536559eb3d4a5c
124
py
Python
scripts/tnaCompile.py
j-vm/feup-tne-PowerTAC
036c88485d538b2e127ea285e4df79107b891611
[ "MIT" ]
null
null
null
scripts/tnaCompile.py
j-vm/feup-tne-PowerTAC
036c88485d538b2e127ea285e4df79107b891611
[ "MIT" ]
null
null
null
scripts/tnaCompile.py
j-vm/feup-tne-PowerTAC
036c88485d538b2e127ea285e4df79107b891611
[ "MIT" ]
null
null
null
from runAgent import compile_and_move AGENT_NAME = "temporaryName" VERSION = "1.7.0" compile_and_move(AGENT_NAME, VERSION)
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1f9fc3ad20a682d3e8eaa70d5cafa1a8aab35dcb
44
py
Python
xknx/config/entries/__init__.py
onkelbeh/xknx
b7c7427b77b1a709aef8e25b39bbbb62ace6f708
[ "MIT" ]
1
2020-12-27T13:54:34.000Z
2020-12-27T13:54:34.000Z
xknx/config/entries/__init__.py
onkelbeh/xknx
b7c7427b77b1a709aef8e25b39bbbb62ace6f708
[ "MIT" ]
1
2021-02-17T23:54:32.000Z
2021-02-17T23:54:32.000Z
xknx/config/entries/__init__.py
mielune/xknx
57c248c386f2ae150d983f72a5a8da684097265d
[ "MIT" ]
null
null
null
"""Support for dedicated config entries."""
22
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0.727273
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6.4
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1
44
44
0.820513
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null
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true
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0
0
0
0
5
1fa24983c75083741e7b2aac162d627c70b7f1e5
507
py
Python
solution/emas_initializer.py
Hoobie/pyage-styblinski-tang
aaf703c8eb95d8c18d414cf194425f7e59712481
[ "MIT" ]
null
null
null
solution/emas_initializer.py
Hoobie/pyage-styblinski-tang
aaf703c8eb95d8c18d414cf194425f7e59712481
[ "MIT" ]
null
null
null
solution/emas_initializer.py
Hoobie/pyage-styblinski-tang
aaf703c8eb95d8c18d414cf194425f7e59712481
[ "MIT" ]
null
null
null
from random import uniform from pyage.core.emas import EmasAgent from solution.genotype import VectorGenotype def emas_initializer(energy=10, size=100, lowerbound=0.0, upperbound=1.0): agents = {} for i in range(size): agent = EmasAgent(VectorGenotype(uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound)), energy) agents[agent.get_address()] = agent return agents
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6.333333
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0.355263
0.355263
0.355263
0.355263
0.355263
0.355263
0
0.020737
0.143984
507
13
215
39
0.854839
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0.111111
false
0
0.333333
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0.555556
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null
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0
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0
1
0
1
0
0
5
1fcd2371b504b06fcff4f6e9230b94a608473994
83
py
Python
reverse_client/exceptions.py
tchar/webshell-client
29612488cf7ef59fa67db732a10c3396407ff154
[ "MIT" ]
1
2021-12-07T22:17:18.000Z
2021-12-07T22:17:18.000Z
reverse_client/exceptions.py
tchar/webshell-client
29612488cf7ef59fa67db732a10c3396407ff154
[ "MIT" ]
null
null
null
reverse_client/exceptions.py
tchar/webshell-client
29612488cf7ef59fa67db732a10c3396407ff154
[ "MIT" ]
null
null
null
class ShellException(Exception): pass class ShellInternalInterrupt(Exception): pass
41.5
45
0.86747
8
83
9
0.625
0.361111
0
0
0
0
0
0
0
0
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0
0.060241
83
2
45
41.5
0.923077
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0
true
1
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null
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1
1
0
0
0
0
0
5
1fffea70af558ca7f3b9320b2339855c0907564b
147
py
Python
models/__init__.py
uncleguanghui/bitcoin_toolkit
c5898d841201ccd3271adee43f7d116e6333e0d8
[ "MIT" ]
null
null
null
models/__init__.py
uncleguanghui/bitcoin_toolkit
c5898d841201ccd3271adee43f7d116e6333e0d8
[ "MIT" ]
1
2020-10-12T01:52:50.000Z
2021-06-22T10:29:10.000Z
models/__init__.py
uncleguanghui/bitcoin_toolkit
c5898d841201ccd3271adee43f7d116e6333e0d8
[ "MIT" ]
1
2021-03-26T15:18:26.000Z
2021-03-26T15:18:26.000Z
from .address import Address from .transaction import Transaction from .output import Output from .block import Block from .bitcoin import Bitcoin
24.5
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147
6.1
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147
5
37
29.4
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1
0
0
5
95040a6c4d7516bdc20c7152e850557e8d61e336
335
py
Python
aux/protocol/http/auth/basic.py
bischjer/auxiliary
e42d8a4af43c9bd4d816c03edc2465640635b46b
[ "BSD-3-Clause" ]
null
null
null
aux/protocol/http/auth/basic.py
bischjer/auxiliary
e42d8a4af43c9bd4d816c03edc2465640635b46b
[ "BSD-3-Clause" ]
null
null
null
aux/protocol/http/auth/basic.py
bischjer/auxiliary
e42d8a4af43c9bd4d816c03edc2465640635b46b
[ "BSD-3-Clause" ]
null
null
null
from base64 import b64encode class BasicAuthenticator(object): def __init__(self, credentials): self.credentials = credentials def __call__(self): return {"Basic":"%s" % b64encode(b'%s%s' % (self.credentials.username, self.credentials.password))}
22.333333
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335
6.1
0.6
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0.325373
335
14
82
23.928571
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0.285714
false
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0.142857
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1
0
1
1
0
0
5
951be236b64c7d5d013f60ecefdb39cfffafbc12
275
py
Python
src/infi/pyutils/exceptions.py
jasonjorge/infi.asi
78a4c34a421102f99b959a659cf7303804627d9b
[ "BSD-3-Clause" ]
1
2022-02-12T20:30:55.000Z
2022-02-12T20:30:55.000Z
src/infi/pyutils/exceptions.py
jasonjorge/infi.asi
78a4c34a421102f99b959a659cf7303804627d9b
[ "BSD-3-Clause" ]
5
2015-11-08T14:50:42.000Z
2020-06-23T14:42:33.000Z
src/infi/pyutils/exceptions.py
jasonjorge/infi.asi
78a4c34a421102f99b959a659cf7303804627d9b
[ "BSD-3-Clause" ]
4
2015-02-22T09:06:59.000Z
2022-02-12T20:30:55.000Z
class ReflectionException(Exception): pass class SignatureException(ReflectionException): pass class MissingArguments(SignatureException): pass class UnknownArguments(SignatureException): pass class InvalidKeywordArgument(ReflectionException): pass
16.176471
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0.796364
20
275
10.95
0.4
0.164384
0.246575
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0.149091
275
16
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17.1875
0.935897
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0.5
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true
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1
null
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null
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0
1
1
0
0
0
0
0
5
1f118ac1da09f3b1bd1fd5332ec578e95fb3d4b3
569
py
Python
ts/nni_manager/test/core/dummy_tuner.py
dutxubo/nni
c16f4e1c89b54b8b80661ef0072433d255ad2d24
[ "MIT" ]
9,680
2019-05-07T01:42:30.000Z
2022-03-31T16:48:33.000Z
ts/nni_manager/test/core/dummy_tuner.py
dutxubo/nni
c16f4e1c89b54b8b80661ef0072433d255ad2d24
[ "MIT" ]
1,957
2019-05-06T21:44:21.000Z
2022-03-31T09:21:53.000Z
ts/nni_manager/test/core/dummy_tuner.py
dutxubo/nni
c16f4e1c89b54b8b80661ef0072433d255ad2d24
[ "MIT" ]
1,571
2019-05-07T06:42:55.000Z
2022-03-31T03:19:24.000Z
# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from nni.tuner import Tuner class DummyTuner(Tuner): def generate_parameters(self, parameter_id): return 'unit-test-parm' def generate_multiple_parameters(self, parameter_id_list): return ['unit-test-param1', 'unit-test-param2'] def receive_trial_result(self, parameter_id, parameters, value): pass def receive_customized_trial_result(self, parameter_id, parameters, value): pass def update_search_space(self, search_space): pass
27.095238
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0.720562
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569
5.549296
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0.13198
0.152284
0.126904
0.243655
0.243655
0.243655
0.243655
0.243655
0
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0.004357
0.193322
569
20
80
28.45
0.854031
0.119508
0
0.25
1
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0.092369
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1
0.416667
false
0.25
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null
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0
1
0
1
0
1
1
0
0
5
1f418e87211666ae0b6509dc62fb065f7fbfe1a6
143
py
Python
tests/test_KSS/conftest.py
bigdata-ustc/EduSim
849eed229c24615e5f2c3045036311e83c22ea68
[ "MIT" ]
18
2019-11-11T03:45:35.000Z
2022-02-09T15:31:51.000Z
tests/test_KSS/conftest.py
ghzhao78506/EduSim
cb10e952eb212d8a9344143f889207b5cd48ba9d
[ "MIT" ]
3
2020-10-23T01:05:57.000Z
2021-03-16T12:12:24.000Z
tests/test_KSS/conftest.py
bigdata-ustc/EduSim
849eed229c24615e5f2c3045036311e83c22ea68
[ "MIT" ]
6
2020-06-09T21:32:00.000Z
2022-03-12T00:25:18.000Z
# coding: utf-8 # 2019/11/27 @ tongshiwei import pytest import gym @pytest.fixture(scope="module") def env(): return gym.make('KSS-v2')
13
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4.409091
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143
10
32
14.3
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true
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0
1
1
1
0
0
5
1f6fb393f1484ef291228861383ed7ead9e5064a
125
py
Python
cvk/admin.py
cvk007/ML_Model
8437257cc84c7a0ac42e7b6728431494f145882b
[ "MIT" ]
null
null
null
cvk/admin.py
cvk007/ML_Model
8437257cc84c7a0ac42e7b6728431494f145882b
[ "MIT" ]
null
null
null
cvk/admin.py
cvk007/ML_Model
8437257cc84c7a0ac42e7b6728431494f145882b
[ "MIT" ]
null
null
null
from django.contrib import admin from cvk.models import feedback admin.site.register(feedback) # Register your models here.
20.833333
32
0.816
18
125
5.666667
0.666667
0
0
0
0
0
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0
0
0
0
0.12
125
5
33
25
0.927273
0.208
0
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true
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0.666667
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null
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null
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0
0
0
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1
0
1
0
1
0
0
5
1f91234660d31d0847e1385fb79af761fe686ebe
92
py
Python
binlog2sql/binlog2sql/__init__.py
sivarki/hjarnuc
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
[ "Apache-2.0" ]
2
2021-05-27T04:07:25.000Z
2021-09-03T02:56:39.000Z
binlog2sql/binlog2sql/__init__.py
sivarki/hjarnuc
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
[ "Apache-2.0" ]
null
null
null
binlog2sql/binlog2sql/__init__.py
sivarki/hjarnuc
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
[ "Apache-2.0" ]
1
2019-02-20T01:27:46.000Z
2019-02-20T01:27:46.000Z
''' binlog2sql: Parse MySQL binlog to SQL you want. ''' from .binlog2sql import Binlog2sql
13.142857
35
0.73913
12
92
5.666667
0.833333
0
0
0
0
0
0
0
0
0
0
0.038961
0.163043
92
6
36
15.333333
0.844156
0.51087
0
0
0
0
0
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true
0
1
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1
0
1
0
0
null
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0
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0
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1
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0
0
0
0
null
0
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0
1
0
1
0
1
0
0
5
2f23033c3fba81b64d632f9fb1e2b5038a6f48a8
56
py
Python
aif360/sklearn/detectors/__init__.py
IBM/AIF-360
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
[ "Apache-2.0" ]
982
2018-09-12T17:19:11.000Z
2020-07-13T21:26:24.000Z
aif360/sklearn/detectors/__init__.py
IBM/AIF-360
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
[ "Apache-2.0" ]
109
2018-09-12T20:39:43.000Z
2020-07-09T20:12:00.000Z
aif360/sklearn/detectors/__init__.py
IBM/AIF-360
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
[ "Apache-2.0" ]
335
2018-09-13T15:35:09.000Z
2020-07-06T10:56:12.000Z
from aif360.sklearn.detectors.detectors import bias_scan
56
56
0.892857
8
56
6.125
0.875
0
0
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56
1
56
56
0.867925
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true
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0
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0
1
0
1
0
0
5
2f77e1f6726adb94470778c88030cfacfb7bd000
2,218
py
Python
webscrape/application/utils.py
kmvicky/webscrape
92ca9100e21de276ed8470621e1e3a7a6495d54d
[ "MIT" ]
null
null
null
webscrape/application/utils.py
kmvicky/webscrape
92ca9100e21de276ed8470621e1e3a7a6495d54d
[ "MIT" ]
null
null
null
webscrape/application/utils.py
kmvicky/webscrape
92ca9100e21de276ed8470621e1e3a7a6495d54d
[ "MIT" ]
null
null
null
"""Get a list of Messages from the user's mailbox. """ from apiclient import errors def ListMessagesMatchingQuery(service, user_id, query=''): """List all Messages of the user's mailbox matching the query. Args: service: Authorized Gmail API service instance. user_id: User's email address. The special value "me" can be used to indicate the authenticated user. query: String used to filter messages returned. Eg.- 'from:user@some_domain.com' for Messages from a particular sender. Returns: List of Messages that match the criteria of the query. Note that the returned list contains Message IDs, you must use get with the appropriate ID to get the details of a Message. """ try: response = service.users().messages().list(userId=user_id,q=query).execute() messages = [] if 'messages' in response: messages.extend(response['messages']) while 'nextPageToken' in response: page_token = response['nextPageToken'] response = service.users().messages().list(userId=user_id, q=query,pageToken=page_token).execute() messages.extend(response['messages']) return messages except Exception as e: print ('An error occurred:', e) def ListMessagesWithLabels(service, user_id, label_ids=[]): """List all Messages of the user's mailbox with label_ids applied. Args: service: Authorized Gmail API service instance. user_id: User's email address. The special value "me" can be used to indicate the authenticated user. label_ids: Only return Messages with these labelIds applied. Returns: List of Messages that have all required Labels applied. Note that the returned list contains Message IDs, you must use get with the appropriate id to get the details of a Message. """ try: response = service.users().messages().list(userId=user_id,labelIds=label_ids).execute() messages = [] if 'messages' in response: messages.extend(response['messages']) while 'nextPageToken' in response: page_token = response['nextPageToken'] response = service.users().messages().list(userId=user_id,labelIds=label_ids,pageToken=page_token).execute() messages.extend(response['messages']) return messages except Exception as e: print ('An error occurred:',e)
34.123077
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0.732394
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2,218
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34.123077
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0
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0
0
0
0
0
0
0
0
0
5
2f8c52b08dd940f71291f75f34451e3b26091852
17
py
Python
z/Zhpy.py
wenzzai/hello-world
e94109a7f48df4c689442e1c1af7d39878d5b3dd
[ "MIT" ]
2
2021-12-06T17:56:37.000Z
2022-01-21T01:44:16.000Z
z/Zhpy.py
wenzzai/hello-world
e94109a7f48df4c689442e1c1af7d39878d5b3dd
[ "MIT" ]
2
2022-03-01T10:57:53.000Z
2022-03-01T12:45:49.000Z
z/Zhpy.py
wenzzai/hello-world
e94109a7f48df4c689442e1c1af7d39878d5b3dd
[ "MIT" ]
1
2022-03-16T00:20:21.000Z
2022-03-16T00:20:21.000Z
印出 'Hello World'
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2f959305098809716563348d572e9232723091f6
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py
Python
tests/not_imported_directly.py
mike0sv/pyjackson
87d2bffa03703ed6b5dabf8098b37f92a067531a
[ "Apache-2.0" ]
20
2019-09-20T15:14:42.000Z
2020-08-05T09:59:30.000Z
tests/not_imported_directly.py
mike0sv/pyjackson
87d2bffa03703ed6b5dabf8098b37f92a067531a
[ "Apache-2.0" ]
null
null
null
tests/not_imported_directly.py
mike0sv/pyjackson
87d2bffa03703ed6b5dabf8098b37f92a067531a
[ "Apache-2.0" ]
1
2020-08-13T11:29:36.000Z
2020-08-13T11:29:36.000Z
from tests.conftest import RootClass class ChildClass(RootClass): def __init__(self, field: str): self.field = field
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c80aef2f1462bbf20cb3140ddf058accfde16214
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py
Python
app/models/exceptions/ResponseErrorCodeNotZero.py
luisalvesmartins/TAPO-P100
02bc929a87bbe4681739b14a716f6cef2b159fd1
[ "MIT" ]
null
null
null
app/models/exceptions/ResponseErrorCodeNotZero.py
luisalvesmartins/TAPO-P100
02bc929a87bbe4681739b14a716f6cef2b159fd1
[ "MIT" ]
1
2021-06-23T09:21:40.000Z
2021-07-02T17:21:12.000Z
app/models/exceptions/ResponseErrorCodeNotZero.py
luisalvesmartins/TAPO-P100
02bc929a87bbe4681739b14a716f6cef2b159fd1
[ "MIT" ]
null
null
null
class ResponseErrorCodeNotZero(Exception): pass
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5
c8125710bba645f59eb48a24cefd8a3f0d6f42a2
290
py
Python
plotplayer/helpers/__init__.py
Jman420/plotplayer
3a224fc38c2825c4166e7534970a792f0e96bd84
[ "Apache-2.0" ]
null
null
null
plotplayer/helpers/__init__.py
Jman420/plotplayer
3a224fc38c2825c4166e7534970a792f0e96bd84
[ "Apache-2.0" ]
7
2018-06-20T19:44:45.000Z
2022-03-11T23:18:57.000Z
plotplayer/helpers/__init__.py
Jman420/plotplayer
3a224fc38c2825c4166e7534970a792f0e96bd84
[ "Apache-2.0" ]
2
2018-04-08T14:36:13.000Z
2018-06-20T19:41:42.000Z
""" PlotPlayer Helpers Subpackage contains various generic miscellaneous modules and methods to ease development. Public Modules: * file_helper - Contains methods for interacting with the local file system * ui_helper - Contains methods for providing generic UI elements & dialogs """
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c8197d1e970c3ca29e165a8d3c59fa019e53b65d
163
py
Python
yolox/models/__init__.py
kadirnar/yolox-lite
a493db0ac636eb507c3511fd24c974a9698c07f5
[ "MIT" ]
null
null
null
yolox/models/__init__.py
kadirnar/yolox-lite
a493db0ac636eb507c3511fd24c974a9698c07f5
[ "MIT" ]
1
2022-03-02T23:30:42.000Z
2022-03-02T23:30:42.000Z
yolox/models/__init__.py
kadirnar/yolox-lite
a493db0ac636eb507c3511fd24c974a9698c07f5
[ "MIT" ]
null
null
null
from .darknet import CSPDarknet, Darknet from .yolo_fpn import YOLOFPN from .yolo_head import YOLOXHead from .yolo_pafpn import YOLOPAFPN from .yolox import YOLOX
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c84cc384ad4a2967c2f453ccd06f349d762753cb
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py
Python
dexplo/_date_funcs.py
dexplo/dexplo
2a522437d3bf848260f9772e7a8f705f534c2e2c
[ "BSD-3-Clause" ]
78
2018-01-25T21:07:17.000Z
2020-11-07T00:19:13.000Z
dexplo/_date_funcs.py
dexplo/dexplo
2a522437d3bf848260f9772e7a8f705f534c2e2c
[ "BSD-3-Clause" ]
null
null
null
dexplo/_date_funcs.py
dexplo/dexplo
2a522437d3bf848260f9772e7a8f705f534c2e2c
[ "BSD-3-Clause" ]
8
2018-04-15T15:28:51.000Z
2022-03-22T10:37:54.000Z
import numpy as np from ._libs import math as _math from . import _utils def max_date(arr, axis, **kwargs): return arr.max(axis=axis) def min_date(arr, axis, **kwargs): return arr.min(axis=axis) def any_date(arr, axis, **kwargs): return (~np.isnat(arr)).sum(axis=axis) > 0 def all_date(arr, axis, **kwargs): return (~np.isnat(arr)).sum(axis=axis) == arr.shape[0] def argmax_date(arr, axis, **kwargs): return arr.argmax(axis=axis) def argmin_date(arr, axis, **kwargs): return arr.argmin(axis=axis) def count_date(arr, axis, **kwargs): return (~np.isnat(arr)).sum(axis=axis) def cummax_date(arr, axis, **kwargs): return np.maximum.accumulate(arr, axis=axis) def cummin_date(arr, axis, **kwargs): return np.minimum.accumulate(arr, axis=axis) def nunique_date(arr, axis, **kwargs): return _math.nunique_int(arr.view('int64'), axis=axis) def mode_date(arr, axis, **kwargs): kind = arr.dtype.kind return _math.mode_int(arr.view('int64'), axis=axis, **kwargs).astype(_utils._DT[kind]) ## These below will only work for timedeltas def sum_date(arr, axis, **kwargs): return arr.sum(axis=axis) def median_date(arr, axis, **kwargs): return np.median(arr, axis=axis) def mean_date(arr, axis, **kwargs): return arr.mean(axis=axis) def prod_date(arr, axis, **kwargs): return arr.prod(axis=axis) def cumsum_date(arr, axis, **kwargs): return np.cumsum(arr, axis=axis) def cumprod_date(arr, axis, **kwargs): return np.cumprod(arr, axis=axis)
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5
c075f6f9782cffb89e911a35c252107b2eae4de7
98
py
Python
website/apps/message/admin.py
jivanyan/salesior
9787b15befb3e39a3e848407bb58fa14d4cafde5
[ "CC0-1.0" ]
3
2015-07-15T07:01:29.000Z
2020-03-29T09:12:39.000Z
message/admin.py
28harishkumar/Social-website-django
0b72ce34241112b87921ef095f6f47d4f958117c
[ "MIT" ]
null
null
null
message/admin.py
28harishkumar/Social-website-django
0b72ce34241112b87921ef095f6f47d4f958117c
[ "MIT" ]
null
null
null
from django.contrib import admin from message.models import Message admin.site.register(Message)
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5
c082cc0125c3c58ef3a6d42897bf2a1b3f3369f9
87
py
Python
tests/test_datafellows.py
redwardstern/datafellows
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
[ "BSD-2-Clause" ]
null
null
null
tests/test_datafellows.py
redwardstern/datafellows
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
[ "BSD-2-Clause" ]
null
null
null
tests/test_datafellows.py
redwardstern/datafellows
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
[ "BSD-2-Clause" ]
null
null
null
import datafellows def test_main(): assert datafellows # use your library here
12.428571
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5
c093e79b3adf01a892c36384fd42ad77534ad2e3
70
py
Python
src/introducao/02_investigando_objeto.py
SamuelPossamai/material_auxilio_conceitos_python
44c15e72f7409441fe0db38288dac782f0cbc94d
[ "MIT" ]
1
2022-02-08T23:39:11.000Z
2022-02-08T23:39:11.000Z
src/introducao/02_investigando_objeto.py
SamuelPossamai/material_auxilio_conceitos_python
44c15e72f7409441fe0db38288dac782f0cbc94d
[ "MIT" ]
null
null
null
src/introducao/02_investigando_objeto.py
SamuelPossamai/material_auxilio_conceitos_python
44c15e72f7409441fe0db38288dac782f0cbc94d
[ "MIT" ]
null
null
null
a = [] print(type(a)) #help(a) #print(dir(a)) #print(type(type(a)))
8.75
21
0.557143
13
70
3
0.384615
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5
c0c645b898c215fd0ff4330d52973dd491756d2e
83
py
Python
photo/qt/__init__.py
RKrahl/photo-tools
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
[ "Apache-2.0" ]
null
null
null
photo/qt/__init__.py
RKrahl/photo-tools
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
[ "Apache-2.0" ]
46
2016-01-03T15:11:18.000Z
2020-05-09T19:46:03.000Z
photo/qt/__init__.py
RKrahl/photo-tools
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
[ "Apache-2.0" ]
null
null
null
"""GUI elements based on PySide. """ from photo.qt.imageViewer import ImageViewer
16.6
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5
c0d4615478ccd32c4548c6aa9237b615a0a673b2
179
py
Python
scrywarden/config/__init__.py
chasebrewsky/scrywarden
c6a5a81d14016ca58625df68594ef52dd328a0dd
[ "MIT" ]
1
2020-12-13T00:49:51.000Z
2020-12-13T00:49:51.000Z
scrywarden/config/__init__.py
chasebrewsky/scrywarden
c6a5a81d14016ca58625df68594ef52dd328a0dd
[ "MIT" ]
null
null
null
scrywarden/config/__init__.py
chasebrewsky/scrywarden
c6a5a81d14016ca58625df68594ef52dd328a0dd
[ "MIT" ]
null
null
null
"""Module containing utilities for retrieving configuration values.""" from .base import Config, parse_config from .settings import Setting, SettingDict, SettingList, SettingKey
35.8
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0.815642
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179
7.25
0.85
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4
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44.75
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1
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1
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5
8d07d3f580b31f92cbba7b8a08c4e771700df290
838
py
Python
metrics.py
sy2616/DATA
8d2314b23c9757c8f54a85a01b451aaa29054912
[ "Apache-2.0" ]
2
2020-08-08T02:02:04.000Z
2020-12-22T09:12:09.000Z
metrics.py
sy2616/DATA
8d2314b23c9757c8f54a85a01b451aaa29054912
[ "Apache-2.0" ]
null
null
null
metrics.py
sy2616/DATA
8d2314b23c9757c8f54a85a01b451aaa29054912
[ "Apache-2.0" ]
null
null
null
import numpy as np def accuracy_score(y_true,y_predict): assert y_true.shape[0]==y_predict.shape[0],\ 'the size of y_true must be equal to the sze of y_predict' return sum(y_true==y_predict)/len(y_true) def mean_squared_error(y_ture,y_predict): assert len(y_ture)==len(y_predict),\ 'the size of y_ture must be equal to the size of y_predict' return np.sum((y_ture-y_predict)**2)/len(y_ture) def root_mean_squared_error(y_ture,y_predict): return squr(mean_squared_error(y_ture,y_predict)) def mean_absolute_error(y_ture,y_predict): assert len(y_ture)==len(y_predict),\ 'the size of y_ture must be equal to the size of y_predict' return np.sum(np.absolute(y_ture-y_predict))/len(y_ture) def r2_score(y_ture,y_predict): return 1-mean_squared_error(y_ture,y_predict)/np.var(y_ture)
38.090909
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838
3.518519
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0.182456
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0.515789
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838
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0
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0
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0
0
0
1
1
0
0
5
2391e837f9b052eff281141e801abf009da64583
671
py
Python
urllib/Cookie/CookieBasic.py
pengchenyu111/SpiderLearning
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
[ "Apache-2.0" ]
3
2020-11-21T13:13:46.000Z
2020-12-03T05:43:32.000Z
urllib/Cookie/CookieBasic.py
pengchenyu111/SpiderLearning
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
[ "Apache-2.0" ]
null
null
null
urllib/Cookie/CookieBasic.py
pengchenyu111/SpiderLearning
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
[ "Apache-2.0" ]
1
2020-12-03T05:43:53.000Z
2020-12-03T05:43:53.000Z
import http.cookiejar, urllib.request # 获取百度返回的Cookie cookie = http.cookiejar.CookieJar() handler = urllib.request.HTTPCookieProcessor(cookie) opener = urllib.request.build_opener(handler) response = opener.open('http://www.baidu.com') print('------http://www.baidu.com--------') for item in cookie: print(item.name + '=' + item.value) # 返回自己服务器的Cookie print('------http://127.0.0.1:5000/writeCookie--------') cookie = http.cookiejar.CookieJar() handler = urllib.request.HTTPCookieProcessor(cookie) opener = urllib.request.build_opener(handler) response = opener.open('http://127.0.0.1:5000/writeCookie') for item in cookie: print(item.name + '=' + item.value)
33.55
59
0.716841
85
671
5.635294
0.329412
0.135699
0.079332
0.11691
0.80167
0.80167
0.80167
0.705637
0.705637
0.551148
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0.032787
0.090909
671
19
60
35.315789
0.752459
0.041729
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0.666667
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false
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0.066667
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0.066667
0.266667
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null
0
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1
1
1
1
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null
0
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0
0
0
0
0
0
0
0
5
23e0e5c7fea788ff45d3c2a315d2f89bd63c1dfe
60
py
Python
lampy/std/__init__.py
Lgneous/Lampy
a009a81b6e55d4203928899e8043b533c02aeba2
[ "MIT" ]
6
2018-12-22T08:08:58.000Z
2019-03-02T05:00:03.000Z
lampy/std/__init__.py
Lgneous/FPython
a009a81b6e55d4203928899e8043b533c02aeba2
[ "MIT" ]
2
2019-03-19T06:01:43.000Z
2019-03-19T06:04:28.000Z
lampy/std/__init__.py
Lgneous/Ignite
a009a81b6e55d4203928899e8043b533c02aeba2
[ "MIT" ]
null
null
null
from .std import * from . import std __all__ = std.__all__
12
21
0.716667
9
60
3.888889
0.444444
0.342857
0
0
0
0
0
0
0
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0
0.2
60
4
22
15
0.729167
0
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false
0
0.666667
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0.666667
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1
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null
0
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0
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0
0
1
0
1
0
0
5
23f105d45171de16e7e0052b26eaace18c9605f4
99
py
Python
opsdroid/connector/gitlab/__init__.py
jacobtomlinson/ops-bot
8b20dd634467097e2dc75af2371e7dec4bbb8960
[ "Apache-2.0" ]
1
2017-08-26T18:31:53.000Z
2017-08-26T18:31:53.000Z
opsdroid/connector/gitlab/__init__.py
jacobtomlinson/ops-bot
8b20dd634467097e2dc75af2371e7dec4bbb8960
[ "Apache-2.0" ]
8
2022-03-01T13:43:05.000Z
2022-03-05T22:51:43.000Z
opsdroid/connector/gitlab/__init__.py
jacobtomlinson/ops-bot
8b20dd634467097e2dc75af2371e7dec4bbb8960
[ "Apache-2.0" ]
null
null
null
"""Import Gitlab connector.""" from .connector import ConnectorGitlab, GitlabPayload # noqa: F401
33
67
0.767677
10
99
7.6
0.8
0
0
0
0
0
0
0
0
0
0
0.034483
0.121212
99
2
68
49.5
0.83908
0.363636
0
0
0
0
0
0
0
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0
0
0
1
0
true
0
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1
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null
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0
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0
0
null
0
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0
0
1
0
1
0
1
0
0
5
9b01b69e4c671d941ba1f641562338ea1f95bffc
272
py
Python
CursoEmVideo/Aula16/ex074.py
lucashsouza/Desafios-Python
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
[ "MIT" ]
null
null
null
CursoEmVideo/Aula16/ex074.py
lucashsouza/Desafios-Python
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
[ "MIT" ]
null
null
null
CursoEmVideo/Aula16/ex074.py
lucashsouza/Desafios-Python
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
[ "MIT" ]
null
null
null
from random import randint n1, n2, n3, n4, n5 = randint(0, 9), randint(0, 9), randint(0, 9), randint(0, 9), randint(0, 9) tup = n1, n2, n3, n4, n5 print(f'Os valores sorteados foram {tup}') print(f'O maior número é {max(tup)}') print(f'O menor número é {min(tup)}')
38.857143
95
0.636029
53
272
3.264151
0.471698
0.231214
0.260116
0.369942
0.375723
0.260116
0.260116
0.260116
0.260116
0.260116
0
0.089286
0.176471
272
6
96
45.333333
0.683036
0
0
0
0
0
0.323308
0
0
0
0
0
0
1
0
false
0
0.166667
0
0.166667
0.5
0
0
0
null
1
1
1
0
0
0
0
0
0
0
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0
0
1
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0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
0
5
9b03c418cf867f922121599295a41f604e1a4153
66
py
Python
Python/List Comprehension One Liner.py
RDxR10/Hacktoberfest-2020-FizzBuzz
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
[ "Unlicense" ]
80
2020-10-01T00:32:34.000Z
2021-01-08T21:56:09.000Z
Python/List Comprehension One Liner.py
RDxR10/Hacktoberfest-2020-FizzBuzz
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
[ "Unlicense" ]
672
2020-09-30T22:53:47.000Z
2020-11-01T12:39:59.000Z
Python/List Comprehension One Liner.py
RDxR10/Hacktoberfest-2020-FizzBuzz
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
[ "Unlicense" ]
618
2020-09-30T22:21:12.000Z
2020-10-31T21:28:06.000Z
[print("Fizz"*(i%3==0)+"Buzz"*(i%5==0) or i) for i in range(101)]
33
65
0.545455
16
66
2.25
0.75
0
0
0
0
0
0
0
0
0
0
0.118644
0.106061
66
1
66
66
0.491525
0
0
0
0
0
0.121212
0
0
0
0
0
0
1
0
true
0
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1
0
0
null
0
0
0
0
0
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0
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0
1
0
0
0
0
0
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null
0
0
0
0
0
0
1
0
0
0
0
1
0
5
9b17fd77dd376b476ec261f14257b37156a30df7
46
py
Python
src/kvt/callbacks/__init__.py
Ynakatsuka/nishika-22
72994cab16486b3a26686642ad72a29b6761b46d
[ "BSD-2-Clause" ]
4
2022-02-01T05:04:53.000Z
2022-02-02T04:16:31.000Z
src/kvt/callbacks/__init__.py
Ynakatsuka/nishika-22
72994cab16486b3a26686642ad72a29b6761b46d
[ "BSD-2-Clause" ]
null
null
null
src/kvt/callbacks/__init__.py
Ynakatsuka/nishika-22
72994cab16486b3a26686642ad72a29b6761b46d
[ "BSD-2-Clause" ]
null
null
null
# flake8: noqa from .autoclip import AutoClip
15.333333
30
0.782609
6
46
6
0.833333
0
0
0
0
0
0
0
0
0
0
0.025641
0.152174
46
2
31
23
0.897436
0.26087
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
1
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1
0
1
1
0
null
0
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null
0
0
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0
1
0
1
0
0
0
0
5
9b211b29391623a5a5c9e80c905e1bd3f8caec2b
130
py
Python
facturador/usuario/admin.py
crodriguezud/Facturador
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
[ "Apache-2.0" ]
null
null
null
facturador/usuario/admin.py
crodriguezud/Facturador
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
[ "Apache-2.0" ]
9
2020-06-05T17:25:18.000Z
2022-03-11T23:15:36.000Z
facturador/usuario/admin.py
crodriguezud/Facturador
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
[ "Apache-2.0" ]
null
null
null
from django.contrib import admin from .models import Usuario, Cliente admin.site.register(Usuario) admin.site.register(Cliente)
18.571429
36
0.815385
18
130
5.888889
0.555556
0.169811
0.320755
0
0
0
0
0
0
0
0
0
0.1
130
6
37
21.666667
0.905983
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
f1ab6c6b62a01a77b6086426a9a429f459997497
92
py
Python
src/utils/sqlite.py
dasoncheng/intelligence
dd5af83c8071025c2934037b40b985aab98726d8
[ "Apache-2.0" ]
null
null
null
src/utils/sqlite.py
dasoncheng/intelligence
dd5af83c8071025c2934037b40b985aab98726d8
[ "Apache-2.0" ]
null
null
null
src/utils/sqlite.py
dasoncheng/intelligence
dd5af83c8071025c2934037b40b985aab98726d8
[ "Apache-2.0" ]
null
null
null
import sqlite3 conn = sqlite3.connect('test.db') def get_sqlite_name(): return "sdf"
11.5
33
0.695652
13
92
4.769231
0.923077
0
0
0
0
0
0
0
0
0
0
0.026316
0.173913
92
7
34
13.142857
0.789474
0
0
0
0
0
0.108696
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
f1ad9efa89fdfcdf813173f61899dad148e554c3
80
py
Python
SSB.py
niazi911/ssb
c73171ae563ead3b3946cc1e1ba792221bd0f7be
[ "Apache-2.0" ]
null
null
null
SSB.py
niazi911/ssb
c73171ae563ead3b3946cc1e1ba792221bd0f7be
[ "Apache-2.0" ]
null
null
null
SSB.py
niazi911/ssb
c73171ae563ead3b3946cc1e1ba792221bd0f7be
[ "Apache-2.0" ]
null
null
null
print(' Project is under maintinace, wait for update. Thanks for patience')
26.666667
77
0.7375
11
80
5.363636
0.909091
0
0
0
0
0
0
0
0
0
0
0
0.1875
80
2
78
40
0.907692
0
0
0
0
0
0.85
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
f1d1d4d5ab39826c929d0e4e26595e2384bcc209
150
py
Python
watson/mail/backends/__init__.py
watsonpy/watson-mail
8e40b5786970845ec56a6f93134908236ad0612c
[ "BSD-3-Clause" ]
null
null
null
watson/mail/backends/__init__.py
watsonpy/watson-mail
8e40b5786970845ec56a6f93134908236ad0612c
[ "BSD-3-Clause" ]
1
2017-07-16T21:37:37.000Z
2017-07-20T07:52:57.000Z
watson/mail/backends/__init__.py
watsonpy/watson-mail
8e40b5786970845ec56a6f93134908236ad0612c
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- from watson.mail.backends.sendmail import Sendmail from watson.mail.backends.smtp import SMTP __all__ = ('Sendmail', 'SMTP')
25
50
0.726667
20
150
5.25
0.55
0.190476
0.266667
0.419048
0
0
0
0
0
0
0
0.007576
0.12
150
5
51
30
0.787879
0.14
0
0
0
0
0.094488
0
0
0
0
0
0
1
0
false
0
0.666667
0
0.666667
0
1
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
0
0
0
5
f1ec104b912a2d888cc3fd26d47d277687eee222
35
py
Python
combat/__init__.py
afrendeiro/combat
1f7d0bbcd221c9f35feff68855f6a697f3626df1
[ "MIT" ]
2
2019-10-29T02:24:38.000Z
2021-02-14T00:54:06.000Z
combat/__init__.py
afrendeiro/combat
1f7d0bbcd221c9f35feff68855f6a697f3626df1
[ "MIT" ]
null
null
null
combat/__init__.py
afrendeiro/combat
1f7d0bbcd221c9f35feff68855f6a697f3626df1
[ "MIT" ]
1
2019-08-06T10:39:39.000Z
2019-08-06T10:39:39.000Z
from .combat import combat combat
8.75
26
0.8
5
35
5.6
0.6
0
0
0
0
0
0
0
0
0
0
0
0.171429
35
3
27
11.666667
0.965517
0
0
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1
0
true
0
0.5
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0
null
0
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null
0
0
0
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0
0
1
0
1
0
0
0
0
5
f1f109aec1120f5711128a43f68ebf400a0dbf26
2,490
py
Python
itests/fe/group_leave_test.py
aneeq009/merou
7a87b43aaf64244932fa460842132a2d9329e704
[ "Apache-2.0" ]
58
2017-05-26T06:46:24.000Z
2022-03-25T20:55:51.000Z
itests/fe/group_leave_test.py
aneeq009/merou
7a87b43aaf64244932fa460842132a2d9329e704
[ "Apache-2.0" ]
74
2017-06-16T17:48:37.000Z
2022-03-28T23:09:54.000Z
itests/fe/group_leave_test.py
aneeq009/merou
7a87b43aaf64244932fa460842132a2d9329e704
[ "Apache-2.0" ]
43
2017-05-20T22:11:51.000Z
2022-03-25T00:24:56.000Z
from __future__ import annotations from typing import TYPE_CHECKING import pytest from selenium.common.exceptions import NoSuchElementException from itests.pages.groups import GroupLeavePage, GroupViewPage from itests.setup import frontend_server from tests.url_util import url if TYPE_CHECKING: from py.path import LocalPath from selenium.webdriver import Chrome from tests.setup import SetupTest def test_leave(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None: with setup.transaction(): setup.add_user_to_group("gary@a.co", "some-group") with frontend_server(tmpdir, "gary@a.co") as frontend_url: browser.get(url(frontend_url, "/groups/some-group")) view_page = GroupViewPage(browser) assert view_page.find_member_row("gary@a.co") view_page.click_leave_button() leave_page = GroupLeavePage(browser) assert leave_page.subheading == "Leave (some-group)" leave_page.submit() assert browser.current_url.endswith("/groups/some-group?refresh=yes") with pytest.raises(NoSuchElementException): view_page.find_member_row("gary@a.co") def test_leave_as_owner(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None: with setup.transaction(): setup.add_user_to_group("gary@a.co", "some-group", role="owner") setup.add_user_to_group("zorkian@a.co", "some-group", role="np-owner") with frontend_server(tmpdir, "gary@a.co") as frontend_url: browser.get(url(frontend_url, "/groups/some-group")) view_page = GroupViewPage(browser) assert view_page.find_member_row("gary@a.co") view_page.click_leave_button() leave_page = GroupLeavePage(browser) leave_page.submit() assert browser.current_url.endswith("/groups/some-group?refresh=yes") with pytest.raises(NoSuchElementException): view_page.find_member_row("gary@a.co") def test_leave_as_last_owner(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None: with setup.transaction(): setup.add_user_to_group("gary@a.co", "some-group", role="owner") setup.add_user_to_group("zorkian@a.co", "some-group", role="manager") with frontend_server(tmpdir, "gary@a.co") as frontend_url: browser.get(url(frontend_url, "/groups/some-group")) view_page = GroupViewPage(browser) with pytest.raises(NoSuchElementException): view_page.click_leave_button()
36.086957
91
0.709237
325
2,490
5.215385
0.212308
0.021239
0.041298
0.041298
0.759882
0.750442
0.723304
0.723304
0.723304
0.723304
0
0
0.17751
2,490
68
92
36.617647
0.827637
0
0
0.625
0
0
0.128916
0.024096
0
0
0
0
0.104167
1
0.0625
false
0
0.208333
0
0.270833
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
7b23b226e9bff7da94f752eccf83139ff0fd1c94
38
py
Python
src/api_status_monitor/producer/apireaders/__init__.py
jjaakola/bang-a-gong
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
[ "MIT" ]
null
null
null
src/api_status_monitor/producer/apireaders/__init__.py
jjaakola/bang-a-gong
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
[ "MIT" ]
null
null
null
src/api_status_monitor/producer/apireaders/__init__.py
jjaakola/bang-a-gong
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
[ "MIT" ]
null
null
null
from .apireaders import create_reader
19
37
0.868421
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38
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0
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0
0
0
0
0
0
1
0
1
0
0
0
0
5
9e9b51bb50690dc800299983ef26d995a8f80761
411
py
Python
Aula34/aula34.py
marcelabbc07/TrabalhosPython
91734d13110e4dee12a532dfd7091e36394a6449
[ "MIT" ]
null
null
null
Aula34/aula34.py
marcelabbc07/TrabalhosPython
91734d13110e4dee12a532dfd7091e36394a6449
[ "MIT" ]
null
null
null
Aula34/aula34.py
marcelabbc07/TrabalhosPython
91734d13110e4dee12a532dfd7091e36394a6449
[ "MIT" ]
null
null
null
#WEB from flask import Flask pessoa_controller=PessoaController() app=Flask (__name__) @app.route('/') def inicio(): return render_template('index.html',titulo_app='nome') @app.route('/Listar') def listar(): return render_template('listar.html',titulo_app='nome',lista=pessoas) @app.route('/Cadastrar') def cadastrar(): return render_template('cadastrar.html',titulo_app='nome') app.run(debug=True)
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14
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0
1
1
0
0
5
9ebfcd12d3dcb80174c64733789ecc5fa030a75d
43
py
Python
geofree/__init__.py
phygitalism/geometry-free-view-synthesis
00dc639c98dfb9246bee0009649c5be8f8b58e1e
[ "MIT" ]
241
2021-04-16T01:09:06.000Z
2022-03-28T13:24:21.000Z
geofree/__init__.py
phygitalism/geometry-free-view-synthesis
00dc639c98dfb9246bee0009649c5be8f8b58e1e
[ "MIT" ]
12
2021-04-21T17:24:31.000Z
2021-11-18T08:42:31.000Z
geofree/__init__.py
phygitalism/geometry-free-view-synthesis
00dc639c98dfb9246bee0009649c5be8f8b58e1e
[ "MIT" ]
13
2021-04-22T09:59:22.000Z
2022-01-22T00:31:19.000Z
from geofree.util import pretrained_models
21.5
42
0.883721
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43
6.166667
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43
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0
0
0
5
7b47a4815a00fc5bb0ff73fadd94a6a91d25ed0d
101
py
Python
__init__.py
areebbeigh/minja
698704c9816909eab144ed81e347e4e697b2493c
[ "BSD-3-Clause" ]
2
2020-03-29T17:43:54.000Z
2020-07-06T05:53:17.000Z
__init__.py
areebbeigh/minja
698704c9816909eab144ed81e347e4e697b2493c
[ "BSD-3-Clause" ]
null
null
null
__init__.py
areebbeigh/minja
698704c9816909eab144ed81e347e4e697b2493c
[ "BSD-3-Clause" ]
null
null
null
__version__ = '0.1' from minja.environment import Environment from minja.utils import Markup, escape
25.25
41
0.811881
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101
5.571429
0.714286
0.230769
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0.022472
0.118812
101
3
42
33.666667
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1
0
false
0
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null
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null
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0
0
0
0
1
0
1
0
0
5
7b83f30bb59de365a0e1edda4bdf7622f316180f
239
py
Python
pyhtmlgui/lib/__init__.py
dirk-attraktor/pyHtmlGui
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
[ "MIT" ]
null
null
null
pyhtmlgui/lib/__init__.py
dirk-attraktor/pyHtmlGui
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
[ "MIT" ]
null
null
null
pyhtmlgui/lib/__init__.py
dirk-attraktor/pyHtmlGui
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
[ "MIT" ]
null
null
null
from .eventset import EventSet from .weakfunctionreferences import WeakFunctionReferences from .browser import Browser from .observable import Observable from .observableDict import ObservableDict from .observableList import ObservableList
39.833333
58
0.878661
24
239
8.75
0.333333
0
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0.096234
239
6
59
39.833333
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1
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1
0
1
0
0
5
c8b9f04ccae9a02c38fedb657079c890af0c24db
148
py
Python
study_management/context_processors.py
jdkizer9/ls2_app
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
[ "Apache-2.0" ]
null
null
null
study_management/context_processors.py
jdkizer9/ls2_app
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
[ "Apache-2.0" ]
7
2020-02-05T04:57:01.000Z
2022-02-10T06:51:23.000Z
study_management/context_processors.py
jdkizer9/ls2_app
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
[ "Apache-2.0" ]
null
null
null
from . import settings def application_version_processor(requests): return { 'application_version': settings.APPLICATION_VERSION, }
24.666667
60
0.743243
14
148
7.571429
0.642857
0.509434
0
0
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0
0
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0
0
0
0
0.182432
148
6
61
24.666667
0.876033
0
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0
0
0
0.127517
0
0
0
0
0
0
1
0.2
false
0
0.2
0.2
0.6
0
1
0
0
null
1
0
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0
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0
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0
0
0
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0
0
1
0
0
0
0
0
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0
0
0
0
null
0
0
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0
0
0
0
0
1
1
0
0
5
c8ce06bbd5b1f46a97ae6d58c317a668b279f3f4
94
py
Python
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
NeonOcean/Order
7e7cbdb26e98bb276c7b27cedc75164634e64148
[ "CC-BY-4.0" ]
null
null
null
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
NeonOcean/Order
7e7cbdb26e98bb276c7b27cedc75164634e64148
[ "CC-BY-4.0" ]
null
null
null
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
NeonOcean/Order
7e7cbdb26e98bb276c7b27cedc75164634e64148
[ "CC-BY-4.0" ]
null
null
null
from __future__ import annotations from NeonOcean.S4.Order import Loading Loading.LoadAll()
15.666667
38
0.829787
12
94
6.166667
0.75
0
0
0
0
0
0
0
0
0
0
0.012048
0.117021
94
5
39
18.8
0.879518
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
7406e864d672d5c9521f4b1ceb78c7fd1649f17e
771
py
Python
tests/end_to_end/scenarios/simple_channel_list.py
norayr/biboumi
805671032d25ee6ce09ed75e8a385c04e9563cdd
[ "Zlib" ]
68
2015-01-29T21:07:37.000Z
2022-03-20T14:48:07.000Z
tests/end_to_end/scenarios/simple_channel_list.py
norayr/biboumi
805671032d25ee6ce09ed75e8a385c04e9563cdd
[ "Zlib" ]
5
2016-10-24T18:34:30.000Z
2021-08-31T13:30:37.000Z
tests/end_to_end/scenarios/simple_channel_list.py
norayr/biboumi
805671032d25ee6ce09ed75e8a385c04e9563cdd
[ "Zlib" ]
13
2015-12-11T15:19:05.000Z
2021-08-31T13:24:35.000Z
from scenarios import * scenario = ( scenarios.multiple_channels_join.scenario, send_stanza("<iq from='{jid_one}/{resource_one}' id='id1' to='{irc_server_one}' type='get'><query xmlns='http://jabber.org/protocol/disco#items'/></iq>"), expect_stanza("/iq[@type='result']/disco_items:query", "/iq/disco_items:query/rsm:set/rsm:count[text()='3']", "/iq/disco_items:query/rsm:set/rsm:first", "/iq/disco_items:query/rsm:set/rsm:last", "/iq/disco_items:query/disco_items:item[@jid='#foo%{irc_server_one}']", "/iq/disco_items:query/disco_items:item[@jid='#bar%{irc_server_one}']", "/iq/disco_items:query/disco_items:item[@jid='#baz%{irc_server_one}']"), )
51.4
158
0.613489
104
771
4.317308
0.394231
0.244989
0.233853
0.227171
0.454343
0.454343
0.454343
0.280624
0.2049
0.2049
0
0.00319
0.18677
771
14
159
55.071429
0.712919
0
0
0
0
0.083333
0.657588
0.546044
0
0
0
0
0
1
0
false
0
0.083333
0
0.083333
0
0
0
0
null
1
1
1
0
0
0
0
0
0
0
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0
0
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0
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0
1
1
null
0
0
0
0
0
0
0
0
0
0
0
0
0
5
cdd0d0f81539165312fe95ceaae7b681d772f4fa
1,953
py
Python
test/test_reporting_api.py
cvent/octopus-deploy-api-client
0e03e842e1beb29b132776aee077df570b88366a
[ "Apache-2.0" ]
null
null
null
test/test_reporting_api.py
cvent/octopus-deploy-api-client
0e03e842e1beb29b132776aee077df570b88366a
[ "Apache-2.0" ]
null
null
null
test/test_reporting_api.py
cvent/octopus-deploy-api-client
0e03e842e1beb29b132776aee077df570b88366a
[ "Apache-2.0" ]
null
null
null
# coding: utf-8 """ Octopus Server API No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501 OpenAPI spec version: 2019.6.7+Branch.tags-2019.6.7.Sha.aa18dc6809953218c66f57eff7d26481d9b23d6a Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import octopus_deploy_swagger_client from octopus_deploy_client.reporting_api import ReportingApi # noqa: E501 from octopus_deploy_swagger_client.rest import ApiException class TestReportingApi(unittest.TestCase): """ReportingApi unit test stubs""" def setUp(self): self.api = octopus_deploy_client.reporting_api.ReportingApi() # noqa: E501 def tearDown(self): pass def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder(self): """Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder """ pass def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder_spaces(self): """Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder_spaces """ pass def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder(self): """Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder """ pass def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder_spaces(self): """Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder_spaces """ pass if __name__ == '__main__': unittest.main()
33.101695
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0.794675
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1,953
5.904564
0.282158
0.082221
0.112439
0.168658
0.664793
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0.621223
0.567814
0.567814
0.567814
0
0.028829
0.147465
1,953
58
137
33.672414
0.825826
0.443932
0
0.25
1
0
0.007759
0
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1
0.3
false
0.25
0.25
0
0.6
0
0
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null
0
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0
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1
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1
0
0
1
0
0
5
cdf8cf181de16d25fec7ec5f36dca963d64cde05
37
py
Python
sample/__init__.py
PARC-Consulting/Kafka_LogProducer
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
[ "BSD-2-Clause" ]
null
null
null
sample/__init__.py
PARC-Consulting/Kafka_LogProducer
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
[ "BSD-2-Clause" ]
null
null
null
sample/__init__.py
PARC-Consulting/Kafka_LogProducer
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
[ "BSD-2-Clause" ]
null
null
null
from core import checklog checklog()
12.333333
25
0.810811
5
37
6
0.8
0
0
0
0
0
0
0
0
0
0
0
0.135135
37
3
26
12.333333
0.9375
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
0.5
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0.5
0
1
1
0
null
0
0
0
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0
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0
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0
0
1
0
1
0
0
0
0
5
cdfc6122f82b969f0d55910d2bfb128e971cf675
75
py
Python
connectwise/service/boardstatuses/__init__.py
punkrokk/connectwise-rest-api-python
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
[ "Apache-2.0" ]
7
2017-01-24T06:41:47.000Z
2021-04-16T17:34:43.000Z
connectwise/service/boardstatuses/__init__.py
punkrokk/connectwise-rest-api-python
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
[ "Apache-2.0" ]
2
2019-10-30T21:32:59.000Z
2019-11-01T18:56:39.000Z
connectwise/service/boardstatuses/__init__.py
punkrokk/connectwise-rest-api-python
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
[ "Apache-2.0" ]
7
2017-10-17T18:41:18.000Z
2019-11-12T20:02:14.000Z
from connectwise.service.boardstatuses.get import get_boardstatuses as get
37.5
74
0.88
10
75
6.5
0.7
0
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75
75
0.942029
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true
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0
1
0
1
0
0
5
a804e1bf7b6242c8104960f730eeb0232923fe93
196
py
Python
tests/test_module.py
gadomski/noaa-climate-normals
2047cd62efa11b231bb97a78c94fa56d2d44c864
[ "Apache-2.0" ]
null
null
null
tests/test_module.py
gadomski/noaa-climate-normals
2047cd62efa11b231bb97a78c94fa56d2d44c864
[ "Apache-2.0" ]
null
null
null
tests/test_module.py
gadomski/noaa-climate-normals
2047cd62efa11b231bb97a78c94fa56d2d44c864
[ "Apache-2.0" ]
null
null
null
import unittest import stactools.noaa_climate_normals class TestModule(unittest.TestCase): def test_version(self): self.assertIsNotNone(stactools.noaa_climate_normals.__version__)
19.6
72
0.806122
22
196
6.772727
0.636364
0.174497
0.268456
0.362416
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0.127551
196
9
73
21.777778
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0.2
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0
1
0
0
0
0
5
b5588e2cf5b9951af48d825fa2f0a363304a8470
99
py
Python
flaskProject/configuration.py
SoerenMLS/SecretSanta
f75242c824851f5f323c6353d9c79e643292b041
[ "MIT" ]
null
null
null
flaskProject/configuration.py
SoerenMLS/SecretSanta
f75242c824851f5f323c6353d9c79e643292b041
[ "MIT" ]
null
null
null
flaskProject/configuration.py
SoerenMLS/SecretSanta
f75242c824851f5f323c6353d9c79e643292b041
[ "MIT" ]
null
null
null
from os import environ class Config: SECRET_KEY = environ.get('SECRET_KEY') or 'development'
16.5
59
0.737374
14
99
5.071429
0.785714
0.253521
0
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0
0
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b5710b5feb5db8d208c0e8aaa3cb85b8d0e1d30b
136
py
Python
ocommerce/store_app/admin.py
vanedta36/golf
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
[ "bzip2-1.0.6" ]
null
null
null
ocommerce/store_app/admin.py
vanedta36/golf
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
[ "bzip2-1.0.6" ]
null
null
null
ocommerce/store_app/admin.py
vanedta36/golf
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
[ "bzip2-1.0.6" ]
null
null
null
from django.contrib import admin from .models import Product # Register your models here. #admin zenithjr admin.site.register(Product)
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b592574da69913806ede857ffe480ea028dab81a
382
py
Python
cashflows/__init__.py
hagarciag/cashflows
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
[ "MIT" ]
54
2017-10-15T09:30:35.000Z
2022-03-18T22:54:41.000Z
cashflows/__init__.py
hagarciag/cashflows
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
[ "MIT" ]
2
2020-10-29T21:27:31.000Z
2021-09-18T23:51:34.000Z
cashflows/__init__.py
hagarciag/cashflows
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
[ "MIT" ]
22
2017-02-15T16:27:56.000Z
2021-12-19T01:34:00.000Z
from cashflows.analysis import * from cashflows.tvmm import * from cashflows.bond import * from cashflows.common import * from cashflows.currency import * from cashflows.depreciation import * from cashflows.rate import * from cashflows.inflation import * from cashflows.loan import * from cashflows.savings import * from cashflows.taxing import * from cashflows.utilityfun import *
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a908749aec9baacaa0e70c2f6c4ab0dc03e60705
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py
Python
tvdb_api/client/__init__.py
h3llrais3r/tvdbapi-v2-client
1210df9dd5869ccc5b63149b1b80630310a14f40
[ "MIT" ]
2
2021-01-24T07:45:22.000Z
2021-11-15T11:29:25.000Z
tvdb_api/client/__init__.py
h3llrais3r/tvdb_api_v2
1210df9dd5869ccc5b63149b1b80630310a14f40
[ "MIT" ]
null
null
null
tvdb_api/client/__init__.py
h3llrais3r/tvdb_api_v2
1210df9dd5869ccc5b63149b1b80630310a14f40
[ "MIT" ]
1
2020-05-07T10:16:15.000Z
2020-05-07T10:16:15.000Z
# coding: utf-8 from .tvdb_client import TvdbClient
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py
Python
cmt/__init__.py
mwtoews/pymt
81a8469b0d0d115d21186ec1d1c9575690d51850
[ "MIT" ]
38
2017-06-30T17:10:53.000Z
2022-01-05T07:38:03.000Z
cmt/__init__.py
mwtoews/pymt
81a8469b0d0d115d21186ec1d1c9575690d51850
[ "MIT" ]
96
2017-04-04T18:52:41.000Z
2021-11-01T21:30:48.000Z
cmt/__init__.py
mwtoews/pymt
81a8469b0d0d115d21186ec1d1c9575690d51850
[ "MIT" ]
15
2017-05-23T15:40:16.000Z
2021-06-14T21:30:28.000Z
import sys import pymt sys.modules["cmt"] = pymt
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a99ed6f6f9b3861c1cd431b083c9a71cde91be84
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py
Python
histogrammar/__init__.py
sbrugman/histogrammar-python
33cb32a01c2eb1a72d0978c65850e03101548c69
[ "Apache-2.0" ]
30
2016-09-25T16:36:06.000Z
2021-07-20T09:09:09.000Z
histogrammar/__init__.py
sbrugman/histogrammar-python
33cb32a01c2eb1a72d0978c65850e03101548c69
[ "Apache-2.0" ]
15
2016-07-26T19:41:31.000Z
2021-02-07T16:30:11.000Z
histogrammar/__init__.py
sbrugman/histogrammar-python
33cb32a01c2eb1a72d0978c65850e03101548c69
[ "Apache-2.0" ]
8
2016-09-19T20:48:37.000Z
2021-02-07T15:00:24.000Z
# flake8: noqa #!/usr/bin/env python # Copyright 2016 DIANA-HEP # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from histogrammar.defs import Factory, Container from histogrammar.primitives.average import Average from histogrammar.primitives.bag import Bag from histogrammar.primitives.bin import Bin from histogrammar.primitives.categorize import Categorize from histogrammar.primitives.centrallybin import CentrallyBin from histogrammar.primitives.collection import Collection, Branch, Index, Label, UntypedLabel from histogrammar.primitives.count import Count from histogrammar.primitives.deviate import Deviate from histogrammar.primitives.fraction import Fraction from histogrammar.primitives.irregularlybin import IrregularlyBin from histogrammar.primitives.minmax import Minimize, Maximize from histogrammar.primitives.select import Select from histogrammar.primitives.sparselybin import SparselyBin from histogrammar.primitives.stack import Stack from histogrammar.primitives.sum import Sum from histogrammar.convenience import Histogram from histogrammar.convenience import SparselyHistogram from histogrammar.convenience import Profile from histogrammar.convenience import SparselyProfile from histogrammar.convenience import ProfileErr from histogrammar.convenience import SparselyProfileErr from histogrammar.convenience import TwoDimensionallyHistogram from histogrammar.convenience import TwoDimensionallySparselyHistogram # handy monkey patch functions for pandas and spark dataframes import histogrammar.dfinterface
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