index int64 | repo_name string | branch_name string | path string | content string | import_graph string |
|---|---|---|---|---|---|
1,493 | tanmesh/cat-and-dog | refs/heads/master | /img_cla.py | import numpy as np
from keras.layers import Activation
from keras.layers import Conv2D
from keras.layers import Dense
from keras.layers import Flatten
from keras.layers import MaxPooling2D
from keras.models import Sequential
from keras_preprocessing.image import ImageDataGenerator
from sklearn.model_selection import tr... | {"/img_cla.py": ["/prepare_data.py"]} |
1,494 | tanmesh/cat-and-dog | refs/heads/master | /prepare_data.py | import os
import re
import cv2
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [atoi(c) for c in re.split('(\d+)', text)]
def prepare_data(list_of_images_path, img_width, img_height):
x = [] # images as arrays
y = [] # labels
for image_path in list... | {"/img_cla.py": ["/prepare_data.py"]} |
1,507 | yueyoum/bulk_create_test | refs/heads/master | /myapp/admin.py | from django.contrib import admin
from import_export import resources
from import_export.admin import ImportExportModelAdmin
from myapp.models import TestModel
class ResourceTestModel_1(resources.ModelResource):
class Meta:
model = TestModel
def before_import(self, *args, **kwargs):
self._met... | {"/myapp/admin.py": ["/myapp/models.py"], "/set_random_data.py": ["/myapp/models.py"]} |
1,508 | yueyoum/bulk_create_test | refs/heads/master | /myapp/models.py | from __future__ import unicode_literals
from django.db import models
class TestModel(models.Model):
id = models.IntegerField(primary_key=True)
f1 = models.CharField(max_length=255)
f2 = models.IntegerField()
f3 = models.TextField()
f4 = models.IntegerField()
class Meta:
db_table = 't... | {"/myapp/admin.py": ["/myapp/models.py"], "/set_random_data.py": ["/myapp/models.py"]} |
1,509 | yueyoum/bulk_create_test | refs/heads/master | /myapp/migrations/0001_initial.py | # -*- coding: utf-8 -*-
# Generated by Django 1.9.6 on 2016-06-20 09:52
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='TestMod... | {"/myapp/admin.py": ["/myapp/models.py"], "/set_random_data.py": ["/myapp/models.py"]} |
1,510 | yueyoum/bulk_create_test | refs/heads/master | /set_random_data.py | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Author: Wang Chao <yueyoum@gmail.com>
Filename: set_random_data.py
Date created: 2016-06-20 17:45:27
Description:
"""
import os
import sys
import uuid
import random
import pymysql
pymysql.install_as_MySQLdb()
os.environ.setdefault("DJANGO_SETTINGS_MODU... | {"/myapp/admin.py": ["/myapp/models.py"], "/set_random_data.py": ["/myapp/models.py"]} |
1,511 | yueyoum/bulk_create_test | refs/heads/master | /mytest1/middleware.py | # -*- coding: utf-8 -*-
"""
Author: Wang Chao <yueyoum@gmail.com>
Filename: middleware.py
Date created: 2016-06-20 18:11:01
Description:
"""
import time
class TimeMeasureRequestMiddleware(object):
def process_request(self, request):
request._time_measure_star_at = time.time()
class TimeMea... | {"/myapp/admin.py": ["/myapp/models.py"], "/set_random_data.py": ["/myapp/models.py"]} |
1,512 | UshshaqueBarira/Data-Analysis | refs/heads/main | /DecisionTree_heartattack.py | #!/usr/bin/env python
# coding: utf-8
# In[7]:
import pandas as pd
import seaborn as sns
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn import metrics
from sklearn.tree import DecisionTreeClassifier
# In[49]:
heart=pd.read_csv("./heart.csv")
heart.head()
# In[50]:
sns.se... | {"/DecisionTree_heartattack.py": ["/seaborn.py"], "/Decision Tree_Titanic.py": ["/seaborn.py"]} |
1,513 | UshshaqueBarira/Data-Analysis | refs/heads/main | /Decision Tree_Titanic.py | #!/usr/bin/env python
# coding: utf-8
# In[3]:
#titanic data set is all manipulated thus we have an accuracy level of 1.0 that is 100 matching as trained and test data
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn import metrics... | {"/DecisionTree_heartattack.py": ["/seaborn.py"], "/Decision Tree_Titanic.py": ["/seaborn.py"]} |
1,514 | UshshaqueBarira/Data-Analysis | refs/heads/main | /seaborn.py | #!/usr/bin/env python
# coding: utf-8
# In[10]:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib.pyplot', '% inline')
# In[11]:
sns.get_dataset_names()
# In[12]:
attention=sns.load_dataset('attention')
attention.head()
# I... | {"/DecisionTree_heartattack.py": ["/seaborn.py"], "/Decision Tree_Titanic.py": ["/seaborn.py"]} |
1,515 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /models/mylosses.py | # -*- coding: utf-8 -*-
import numpy as np
from torch.nn.modules import loss
from torch.nn import functional as F
import torch
from torch.autograd import Variable
class RelMAELoss(loss._Loss):
r"""Creates a criterion that measures the mean squared error between
`n` elements in the input `x` and target `y`.
... | {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,516 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /data/icvl_dataset.py | import os.path
import random
import torchvision.transforms as transforms
import torch
# import torch.nn.functional as F
from data.base_dataset import BaseDataset
from data.image_folder import make_dataset_from_dir_list
from PIL import Image, ImageOps
import h5py
import numpy as np
import spectral
from tqdm import tqdm
... | {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,517 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /data/aligned_dataset.py | import os.path
import random
import torchvision.transforms as transforms
import torch
from data.base_dataset import BaseDataset
from data.image_folder import make_dataset
from PIL import Image
| {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,518 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /eval/evaluation.py | # Evaluation script for the NTIRE 2018 Spectral Reconstruction Challenge
#
# * Provide input and output directories as arguments
# * Validation files should be found in the '/ref' subdirectory of the input dir
# * Input validation files are expected in the v7.3 .mat format
import h5py as h5py
import numpy as np
impor... | {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,519 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /eval/select_model.py | # -*- coding: utf-8 -*-
import pandas as pd
import os
import sacred
import glob
from sacred import Experiment
ex = Experiment('rename_to_samename')
@ex.config
def config():
results_home_dir = os.path.abspath('/home/aitor/dev/adv_rgb2hs_pytorch/results')
@ex.automain
def select_model(results_home_dir):
res_dir... | {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,520 | liuhongbo830117/ntire2018_adv_rgb2hs | refs/heads/master | /util/spectral_color.py | # -*- coding: utf-8 -*-
import os
import numpy as np
from colour.plotting import *
import colour
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from skimage.color import colorconv
from spectral import *
### to avoid importing pyresources.assemple data
def dim_ordering_tf2th(img_list_ndarray):... | {"/data/icvl_dataset.py": ["/util/spectral_color.py"]} |
1,536 | lonce/dcn_soundclass | refs/heads/master | /testPickledModel.py | """
eg
python testPickledModel.py logs.2017.04.28/mtl_2.or_channels.epsilon_1.0/state.pickle
"""
import tensorflow as tf
import numpy as np
import pickledModel
from PIL import TiffImagePlugin
from PIL import Image
# get args from command line
import argparse
FLAGS = None
VERBOSE=False
# -----------------------... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,537 | lonce/dcn_soundclass | refs/heads/master | /utils/ESC50_Convert.py | import os
import numpy as np
import matplotlib.pyplot as plt
# https://github.com/librosa/librosa
import librosa
import librosa.display
import scipy
from PIL import TiffImagePlugin
from PIL import Image
import tiffspect
# Set some project parameters
K_SR = 22050
K_FFTSIZE = 512 # also used for window length where th... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,538 | lonce/dcn_soundclass | refs/heads/master | /trainedModel.py | #
#
#Morgans great example code:
#https://blog.metaflow.fr/tensorflow-how-to-freeze-a-model-and-serve-it-with-a-python-api-d4f3596b3adc
#
# GitHub utility for freezing graphs:
#https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py
#
#https://www.tensorflow.org/api_docs/python/tf/g... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,539 | lonce/dcn_soundclass | refs/heads/master | /testTrainedModel.py | """
eg
python testModel.py logs.2017.04.28/mtl_2.or_channels.epsilon_1.0/my-model.meta logs.2017.04.28/mtl_2.or_channels.epsilon_1.0/checkpoints/
"""
import tensorflow as tf
import numpy as np
import trainedModel
from PIL import TiffImagePlugin
from PIL import Image
# get args from command line
import argparse
FL... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,540 | lonce/dcn_soundclass | refs/heads/master | /style_transfer.py |
""" An implementation of the paper "A Neural Algorithm of Artistic Style"
by Gatys et al. in TensorFlow.
Author: Chip Huyen (huyenn@stanford.edu)
Prepared for the class CS 20SI: "TensorFlow for Deep Learning Research"
For more details, please read the assignment handout:
http://web.stanford.edu/class/cs20si/assignmen... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,541 | lonce/dcn_soundclass | refs/heads/master | /pickledModel.py | #
#
#Morgans great example code:
#https://blog.metaflow.fr/tensorflow-how-to-freeze-a-model-and-serve-it-with-a-python-api-d4f3596b3adc
#
# GitHub utility for freezing graphs:
#https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py
#
#https://www.tensorflow.org/api_docs/python/tf/g... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,542 | lonce/dcn_soundclass | refs/heads/master | /DCNSoundClass.py | """
"""
import tensorflow as tf
import numpy as np
import spectreader
import os
import time
import math
import pickledModel
# get args from command line
import argparse
FLAGS = None
# ------------------------------------------------------
# get any args provided on the command line
parser = argparse.ArgumentParser(f... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,543 | lonce/dcn_soundclass | refs/heads/master | /utils/Centroid2ndaryClassMaker.py | import os
import re
import numpy as np
import math
import tiffspect
import librosa
import librosa.display
import matplotlib.pyplot as plt
K_SPECTDIR = '/home/lonce/tflow/DATA-SETS/ESC-50-spect'
k_soundsPerClass=125 # must divide the total number of sounds evenly!
#============================================
def... | {"/testPickledModel.py": ["/pickledModel.py"], "/testTrainedModel.py": ["/trainedModel.py"], "/style_transfer.py": ["/pickledModel.py"]} |
1,544 | acheng6845/PuzzleSolver | refs/heads/master | /PADCompleter.py | __author__ = 'Aaron'
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5 import QtWidgets, QtCore, QtGui
class PADCompleter(QCompleter):
def __init__(self):
super().__init__()
self.prefix = ''
self.model = None
def _set_model_(self, model):
... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,545 | acheng6845/PuzzleSolver | refs/heads/master | /Calculator_Screen.py | __author__ = 'Aaron'
# Class Description:
# Create framework for the split screens used in PAD_GUI
# import necessary files
import os
import json
from functools import partial
from PyQt5.QtWidgets import (QLabel, QWidget, QHBoxLayout,
QFrame, QSplitter, QStyleFactory,
... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,546 | acheng6845/PuzzleSolver | refs/heads/master | /PAD_GUI.py | __author__ = 'Aaron'
# import necessary files
from PyQt5 import PyQt5
import sys
from PyQt5.QtWidgets import (QApplication, QWidget, QHBoxLayout,
QFrame, QSplitter, QStyleFactory,
QMainWindow, QStackedWidget)
from PyQt5.QtCore import Qt
from PADScreen import P... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,547 | acheng6845/PuzzleSolver | refs/heads/master | /PAD_Monster.py | __author__ = 'Aaron'
# Class Description:
# Our Monster Class where we hold all of the Monster's stats and calculate the values needed with those stats
import os
import json
class PADMonster:
def __init__(self):
# initialize the Class's stats
# _max, _min, and _scale are used for when the mon... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,548 | acheng6845/PuzzleSolver | refs/heads/master | /PADScreen.py | __author__ = 'Aaron'
from Calculator_Screen import CalculatorScreen
from Board_Screen import BoardScreen
from PAD_Monster import PADMonster
from PAD_Team import PADTeam
from PyQt5.QtWidgets import (QVBoxLayout, QHBoxLayout, QWidget, QPushButton, QSplitter, QAction,
QFileDialog, QMainWindow... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,549 | acheng6845/PuzzleSolver | refs/heads/master | /PAD_Team.py | __author__ = 'Aaron'
import os
from PAD_Monster import PADMonster
class PADTeam:
def __init__(self, team):
"""
Initializes the PADTeam Class.
:param team: an array containing 6 PADMonster Classes
"""
# self.team = [PADMonster() for monster in range(6)] -> how the team shoul... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,550 | acheng6845/PuzzleSolver | refs/heads/master | /Board_Screen.py | __author__ = 'Aaron'
from PyQt5.QtWidgets import (QVBoxLayout, QWidget, QLabel, QGridLayout, QSplitter,
QPushButton, QHBoxLayout)
from PyQt5.QtCore import Qt, QMimeData
from PyQt5.QtGui import QPixmap, QDrag
import os
from PAD_Monster import PADMonster
from PAD_Team import PADTeam
from func... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,551 | acheng6845/PuzzleSolver | refs/heads/master | /image_updater.py | __author__ = 'Aaron'
# Class Description:
# Update our monsters.txt file and our images folder
from urllib3 import urllib3
import shutil
import os
import json
class image_updater():
def __init__(self):
# update monsters.txt here:
self.json_file = open(os.path.realpath('./monsters.txt'), 'r')... | {"/Calculator_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"], "/PAD_GUI.py": ["/PADScreen.py"], "/PADScreen.py": ["/Calculator_Screen.py", "/Board_Screen.py", "/PAD_Monster.py", "/PAD_Team.py"], "/PAD_Team.py": ["/PAD_Monster.py"], "/Board_Screen.py": ["/PAD_Monster.py", "/PAD_Team.py"]} |
1,574 | vanya2143/ITEA-tasks | refs/heads/master | /hw-2/task_2.py | """
2. Написать декоратор log, который будет выводить на экран все аргументы,
которые передаются вызываемой функции.
@log
def my_sum(*args):
return sum(*args)
my_sum(1,2,3,1) - выведет "Функция была вызвана с - 1, 2, 3, 1"
my_sum(22, 1) - выведет "Функция была вызвана с - 22, 1"
"""
def log(func):
def wrappe... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,575 | vanya2143/ITEA-tasks | refs/heads/master | /hw-1/task_3.py | """
Реализовать алгоритм бинарного поиска на python.
На вход подается упорядоченный список целых чисел, а так же элемент,
который необходимо найти и указать его индекс,
в противном случае – указать что такого элемента нет в заданном списке.
"""
def search_item(some_list, find_item):
some_list.sort()
list_leng... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,576 | vanya2143/ITEA-tasks | refs/heads/master | /hw-6/task_2.py | # 2. Используя модуль unittests написать тесты: сложения двух матриц, умножения матрицы и метод transpose
import unittest
from .task_1 import Matrix, MatrixSizeError
class TestMatrix(unittest.TestCase):
def setUp(self) -> None:
self.matrix_1 = Matrix([[1, 2, 9], [3, 4, 0], [5, 6, 4]])
self.matrix... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,577 | vanya2143/ITEA-tasks | refs/heads/master | /hw-1/task_1.py | """
1. Определить количество четных и нечетных чисел в заданном списке.
Оформить в виде функции, где на вход будет подаваться список с целыми числами.
Результат функции должен быть 2 числа, количество четных и нечетных соответственно.
"""
def list_check(some_list):
even_numb = 0
not_even_numb = 0
for e... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,578 | vanya2143/ITEA-tasks | refs/heads/master | /hw-3/task_1.py | """
Реализовать некий класс Matrix, у которого:
1. Есть собственный конструктор, который принимает в качестве аргумента - список списков,
копирует его (то есть при изменении списков, значения в экземпляре класса не должны меняться).
Элементы списков гарантированно числа, и не пустые.
2. Метод size без аргументов, кото... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,579 | vanya2143/ITEA-tasks | refs/heads/master | /hw-6/task_1.py | """
1. Реализовать подсчёт елементов в классе Matrix с помощью collections.Counter.
Можно реализовать протоколом итератора и тогда будет такой вызов - Counter(maxtrix).
Либо сделать какой-то метод get_counter(), который будет возвращать объект Counter и подсчитывать все элементы
внутри матрицы. Какой метод - ваш выбор.... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,580 | vanya2143/ITEA-tasks | refs/heads/master | /hw-4/task_1.py | """
К реализованному классу Matrix в Домашнем задании 3 добавить следующее:
1. __add__ принимающий второй экземпляр класса Matrix и возвращающий сумму матриц,
если передалась на вход матрица другого размера - поднимать исключение MatrixSizeError
(по желанию реализовать так, чтобы текст ошибки содержал размерность 1 и 2... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,581 | vanya2143/ITEA-tasks | refs/heads/master | /hw-7/task_1.py | """
Сделать скрипт, который будет делать GET запросы на следующие ресурсы:
"http://docs.python-requests.org/",
"https://httpbin.org/get",
"https://httpbin.org/",
"https://api.github.com/",
"https://example.com/",
"https://www.python.org/",
"https://www.google.com.ua/",
"https://regex101.... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,582 | vanya2143/ITEA-tasks | refs/heads/master | /hw-1/task_2.py | """
Написать функцию, которая принимает 2 числа.
Функция должна вернуть сумму всех элементов числового ряда между этими двумя числами.
(если подать 1 и 5 на вход, то результат должен считаться как 1+2+3+4+5=15)
"""
def all_numbers_sum(num1, num2):
return sum([num for num in range(num1, num2 + 1)])
if __name__ =... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,583 | vanya2143/ITEA-tasks | refs/heads/master | /hw-5/task_1.py | # Реализовать пример использования паттерна Singleton
from random import choice
# Генератор событий
def gen_events(instance, data, count=2):
for i in range(count):
event = choice(data)
instance.add_event(f'Event-{event}-{i}', event)
# Singleton на примере списка событий
class EventsMeta(type):
... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,584 | vanya2143/ITEA-tasks | refs/heads/master | /hw-2/task_1.py | """
1. Написать функцию, которая будет принимать на вход натуральное число n,
и возращать сумму его цифр. Реализовать используя рекурсию
(без циклов, без строк, без контейнерных типов данных).
Пример: get_sum_of_components(123) -> 6 (1+2+3)
"""
def get_sum_of_components_two(n):
return 0 if not n else n % 10 + get... | {"/hw-6/task_2.py": ["/hw-6/task_1.py"]} |
1,586 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/migrations/0006_auto_20210209_1401.py | # Generated by Django 3.1.6 on 2021-02-09 14:01
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('WebMovies', '0005_auto_20210209_0759'),
]
operations = [
migrations.AlterField(
model_name='additionalinfo',
name='g... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,587 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/apps.py | from django.apps import AppConfig
class WebmoviesConfig(AppConfig):
name = 'WebMovies'
| {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,588 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/migrations/0003_movie_description.py | # Generated by Django 3.1.6 on 2021-02-04 08:22
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('WebMovies', '0002_auto_20210204_0806'),
]
operations = [
migrations.AddField(
model_name='movie',
name='description'... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,589 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/migrations/0004_auto_20210204_0835.py | # Generated by Django 3.1.6 on 2021-02-04 08:35
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('WebMovies', '0003_movie_description'),
]
operations = [
migrations.AddField(
model_name='movie',
name='imdb_rating',... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,590 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/views.py | from django.shortcuts import get_object_or_404, render, redirect
from django.http import HttpResponse
from WebMovies.models import Movie
from .forms import MovieForm
from django.contrib.auth.decorators import login_required
def all_movies(request):
movies_all = Movie.objects.all()
return render(request, "movi... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,591 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/migrations/0005_auto_20210209_0759.py | # Generated by Django 3.1.6 on 2021-02-09 07:59
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('WebMovies', '0004_auto_20210204_0835'),
]
operations = [
migrations.CreateModel(
name='Addition... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,592 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/admin.py | from django.contrib import admin
from .models import AdditionalInfo, Movie
# Register your models here.
# admin.site.register(Movie)
@admin.register(Movie)
class MovieAdmin(admin.ModelAdmin):
# fields = ["Title", "Description", "Year"]
# exclude = ["Description"]
list_display = ["title", "imdb_rating", "... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,593 | Kw4dr4t/WebMovies | refs/heads/master | /WebMovies/models.py | from django.db import models
class AdditionalInfo(models.Model):
GENRES = {
(0, "Other"),
(1, "Action"),
(2, "Animation"),
(3, "Comedy"),
(4, "Crime"),
(5, "Drama"),
(6, "Experimental"),
(7, "Fantasy"),
(8, "Historical"),
(9, "Horror"... | {"/WebMovies/views.py": ["/WebMovies/models.py"], "/WebMovies/admin.py": ["/WebMovies/models.py"]} |
1,597 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /main.py | import gym
from Brain import SACAgent
from Common import Play, Logger, get_params
import numpy as np
from tqdm import tqdm
import mujoco_py
def concat_state_latent(s, z_, n):
z_one_hot = np.zeros(n)
z_one_hot[z_] = 1
return np.concatenate([s, z_one_hot])
if __name__ == "__main__":
params = get_param... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,598 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Brain/replay_memory.py | import random
from collections import namedtuple
Transition = namedtuple('Transition', ('state', 'z', 'done', 'action', 'next_state'))
class Memory:
def __init__(self, buffer_size, seed):
self.buffer_size = buffer_size
self.buffer = []
self.seed = seed
random.seed(self.seed)
... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,599 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Brain/model.py | from abc import ABC
import torch
from torch import nn
from torch.nn import functional as F
from torch.distributions import Normal
def init_weight(layer, initializer="he normal"):
if initializer == "xavier uniform":
nn.init.xavier_uniform_(layer.weight)
elif initializer == "he normal":
nn.init.... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,600 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Common/logger.py | import time
import numpy as np
import psutil
from torch.utils.tensorboard import SummaryWriter
import torch
import os
import datetime
import glob
class Logger:
def __init__(self, agent, **config):
self.config = config
self.agent = agent
self.log_dir = self.config["env_name"][:-3] + "/" + d... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,601 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Common/__init__.py | from .config import get_params
from .play import Play
from .logger import Logger | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,602 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Common/config.py | import argparse
def get_params():
parser = argparse.ArgumentParser(
description="Variable parameters based on the configuration of the machine or user's choice")
parser.add_argument("--env_name", default="BipedalWalker-v3", type=str, help="Name of the environment.")
parser.add_argument("--interva... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,603 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Common/play.py | # from mujoco_py.generated import const
from mujoco_py import GlfwContext
import cv2
import numpy as np
import os
GlfwContext(offscreen=True)
class Play:
def __init__(self, env, agent, n_skills):
self.env = env
self.agent = agent
self.n_skills = n_skills
self.agent.set_policy_net_... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,604 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Brain/agent.py | import numpy as np
from .model import PolicyNetwork, QvalueNetwork, ValueNetwork, Discriminator
import torch
from .replay_memory import Memory, Transition
from torch import from_numpy
from torch.optim.adam import Adam
from torch.nn.functional import log_softmax
class SACAgent:
def __init__(self,
... | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,605 | eric-z-lin/DIAYN-PyTorch | refs/heads/main | /Brain/__init__.py | from .agent import SACAgent | {"/main.py": ["/Brain/__init__.py", "/Common/__init__.py"], "/Common/__init__.py": ["/Common/config.py", "/Common/play.py", "/Common/logger.py"], "/Brain/agent.py": ["/Brain/model.py", "/Brain/replay_memory.py"], "/Brain/__init__.py": ["/Brain/agent.py"]} |
1,606 | KimGyuri875/TIL | refs/heads/master | /Django/bbsApp_ORM practice/views.py | from django.shortcuts import render, redirect
from .models import *
# Create your views here.
# select * from table;
# -> modelName.objects.all()
# select * from table where id = xxxx;
# -> modelName.objects.get(id = xxxx)
# -> modelName.objects.filter(id = xxxx)
# select * from table where id = xxxx and ... | {"/Django/bbsApp_ORM practice/views.py": ["/Django/bbsApp_ORM practice/models.py"]} |
1,607 | KimGyuri875/TIL | refs/heads/master | /Django/bbsApp_ORM practice/urls.py | from django.contrib import admin
from django.urls import path, include
from bbsApp import views
urlpatterns = [
path('index/', views.index, name='index'),
path('login/', views.loginProc, name='login'),
path('registerForm/', views.registerForm, name='registerForm'),
path('register/', views.r... | {"/Django/bbsApp_ORM practice/views.py": ["/Django/bbsApp_ORM practice/models.py"]} |
1,608 | KimGyuri875/TIL | refs/heads/master | /Django/bbsApp_ORM practice/models.py | from django.db import models
# Create your models here.
#class is table
class BbsUserRegister(models.Model) :
user_id = models.CharField(max_length=50)
user_pwd = models.CharField(max_length=50)
user_name = models.CharField(max_length=50)
def __str__(self):
return self.user_id +" , "... | {"/Django/bbsApp_ORM practice/views.py": ["/Django/bbsApp_ORM practice/models.py"]} |
1,617 | jeremw264/SheetsUnlockerExcel | refs/heads/master | /model/unlockSheet.py | from model.log import Log
import os
import re
class UnlockSheet:
def __init__(self, pathZip):
self.pathZip = pathZip
self.sheetsPath = []
self.searchSheetPath()
def unlock(self):
for path in self.sheetsPath:
data = ""
Log().writteLog("Read xl/workshee... | {"/model/unlockSheet.py": ["/model/log.py"], "/main.py": ["/model/log.py", "/model/unlockSheet.py"]} |
1,618 | jeremw264/SheetsUnlockerExcel | refs/heads/master | /main.py | import zipfile
import shutil
import os
from model.log import Log
from model.unlockSheet import UnlockSheet
filePath = "filePath"
if __name__ == "__main__":
Log().writteLog("Launch Program on " + filePath)
try:
zipPath = filePath[: len(filePath) - 4] + "zip"
os.rename(filePath, zipPath)
... | {"/model/unlockSheet.py": ["/model/log.py"], "/main.py": ["/model/log.py", "/model/unlockSheet.py"]} |
1,619 | jeremw264/SheetsUnlockerExcel | refs/heads/master | /model/log.py | from datetime import datetime
class Log:
def __init__(self) -> None:
self.path = "log/log.txt"
def writteLog(self, str, level=0):
now = datetime.now()
if level == 1:
levelMsg = "[Warning] "
elif level == 2:
levelMsg = "[Error] "
else:
... | {"/model/unlockSheet.py": ["/model/log.py"], "/main.py": ["/model/log.py", "/model/unlockSheet.py"]} |
1,628 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/__init__.py | from .aws_lambda import xmlabs_lambda_handler
| {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,629 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/aws_lambda/handler.py | from .config import xmlabs_settings
from .env import get_environment
from functools import wraps
def xmlabs_lambda_handler(fn):
@wraps(fn)
def wrapped(*args, **kwargs):
env, config = None , None
try:
env = get_environment(*args, **kwargs)
if not env:
rai... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,630 | xmlabs-io/xmlabs-python | refs/heads/master | /tests/test_aws_lambda_settings.py | import pytest
from xmlabs.aws_lambda.config import settings
def test_xmlabs_aws_lambda_config():
"""Assert Settings"""
assert settings
| {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,631 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/aws_lambda/__init__.py | from .handler import xmlabs_lambda_handler
| {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,632 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/aws_lambda/env.py | import os
import logging
logger = logging.getLogger()
def get_environment(event, context=None):
valid_envs = ["stage", "prod", "dev"]
env = None
# default_env = os.getenv("DEFAULT_ENV", "dev")
default_env = os.getenv("APP_ENV", os.getenv("DEFAULT_ENV", "dev"))
override_env = os.getenv("ENV")
... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,633 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/dynaconf/aws_ssm_loader.py | import boto3
import logging
import requests
from functools import lru_cache
from dynaconf.utils.parse_conf import parse_conf_data
logger = logging.getLogger()
IDENTIFIER = 'aws_ssm'
def load(obj, env=None, silent=True, key=None, filename=None):
"""
Reads and loads in to "obj" a single key or all keys from ... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,634 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/dynaconf/aws_ec2_userdata_loader.py | from .base import ConfigSource
import logging
import requests
logger = logging.getLogger()
class ConfigSourceAwsEc2UserData(ConfigSource):
def load(self):
if self._running_in_ec2():
#TODO: fetch EC2 USERDATA
raise Exception("ConfigSourceEC2UserData Load Unimplemented")
... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,635 | xmlabs-io/xmlabs-python | refs/heads/master | /example/aws_lambda/app.py | from xmlabs.aws_lambda import lambda_handler
@lambda_handler
def main(event, context, config):
print(config.STRIPE_API_SECRET_KEY)
pass
if __name__ == "__main__":
main({"headers":{"X-Environment": "dev"}}, {})
main({"headers":{"X-Environment": "prod"}}, {})
main({"headers":{"X-Environment": "dev"}... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,636 | xmlabs-io/xmlabs-python | refs/heads/master | /tests/test_aws_lambda_integration.py |
import pytest
from xmlabs import xmlabs_lambda_handler
@xmlabs_lambda_handler
def lambda_handler(event, context, config):
assert(config)
def test_lambda_handler():
lambda_handler({},{})
| {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,637 | xmlabs-io/xmlabs-python | refs/heads/master | /xmlabs/aws_lambda/config.py | from dynaconf import Dynaconf
from dynaconf.constants import DEFAULT_SETTINGS_FILES
LOADERS_FOR_DYNACONF = [
'dynaconf.loaders.env_loader', #Inorder to configure AWS_SSM_PREFIX we need to load it from environment
'xmlabs.dynaconf.aws_ssm_loader',
'dynaconf.loaders.env_loader', #Good to load environment las... | {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,638 | xmlabs-io/xmlabs-python | refs/heads/master | /tests/test_dynaconf.py | from dynaconf import Dynaconf
def test_dynaconf_settingsenv():
settingsenv = Dynaconf(environments=True)
assert settingsenv
def test_dynaconf_settings():
settings = Dynaconf()
assert settings
| {"/xmlabs/__init__.py": ["/xmlabs/aws_lambda/__init__.py"], "/xmlabs/aws_lambda/handler.py": ["/xmlabs/aws_lambda/config.py", "/xmlabs/aws_lambda/env.py"], "/tests/test_aws_lambda_settings.py": ["/xmlabs/aws_lambda/config.py"], "/xmlabs/aws_lambda/__init__.py": ["/xmlabs/aws_lambda/handler.py"], "/example/aws_lambda/ap... |
1,639 | Omrigan/essay-writer | refs/heads/master | /emotions.py | mat = [
'сука', "блять", "пиздец", "нахуй", "твою мать", "епта"]
import random
import re
# strong_emotions = re.sub('[^а-я]', ' ', open('strong_emotions').read().lower()).split()
def process(txt, ch):
words = txt.split(" ")
nxt = words[0] + ' '
i = 1
while i < len(words) - 1:
if words[i ... | {"/essay.py": ["/emotions.py"]} |
1,640 | Omrigan/essay-writer | refs/heads/master | /essay.py | #!/usr/bin/python3
import re
import random
import pymorphy2
import json
import emotions
from plumbum import cli
morph = pymorphy2.MorphAnalyzer()
codes = {
'n': 'nomn',
'g': 'gent',
'd': 'datv',
'ac': 'accs',
'a': 'ablt',
'l': 'loct'
}
keywords = set(open('keywords.txt').read().replace(' ', '... | {"/essay.py": ["/emotions.py"]} |
1,642 | sudo-dax/PythonScript_NmapToMacchange | refs/heads/master | /macch.py | #!/usr/bin/python
#Library
import os
import subprocess
import collections
import socket
import subnet
# Clear Screen
subprocess.call('clear', shell=True)
# Get Subnet
adapter = subnet.get_adapter_names()[-1]
Subnet = subnet.get_subnets(adapter)[0]
# Start Network Scan
print(f'Scanning {adapter} Network for Devices... | {"/macch.py": ["/subnet.py"]} |
1,643 | sudo-dax/PythonScript_NmapToMacchange | refs/heads/master | /scan.py | #!/usr/bin/python
#Library
import os
import subprocess
import socket
# Clear Screen
subprocess.call('clear', shell=True)
# Get Subnet
adapter = subnet.get_adapter_names()[-1]
Subnet = subnet.get_subnets(adapter)[0]
print(f'Scanning {adapter} Network for Devices')
print(' ')
# Start Network Scan
print('Scannig Netw... | {"/macch.py": ["/subnet.py"]} |
1,644 | sudo-dax/PythonScript_NmapToMacchange | refs/heads/master | /subnet.py | """
Some helper functions to get adapter names and ipv4 subnets on that adapter
"""
import ipaddress
import ifaddr
def compressed_subnet(host, bits):
"""
Given an ip and number of bits, (e.g. 10.0.3.1, 8), returns the compressed
subnet mask (10.0.0.0/8)
"""
net_string = '{host}/{bits}'.format(hos... | {"/macch.py": ["/subnet.py"]} |
1,675 | estebanfloresf/testcases | refs/heads/master | /testcases/spiders/createTestCase.py | # -*- coding: utf-8 -*-
import scrapy
from scrapy.utils.project import get_project_settings
from ..items import TestCasesItem
from scrapy.loader import ItemLoader
class createTestCaseSpider(scrapy.Spider):
name = "createTestCase"
settings = get_project_settings()
http_user = settings.get('HTTP_USER')
... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,676 | estebanfloresf/testcases | refs/heads/master | /testcases/spiders/testSpider.py | # -*- coding: utf-8 -*-
import scrapy
from scrapy import Request
from scrapy.utils.project import get_project_settings
from ..items import TestCasesItem, Responsive, Requirements
from scrapy.spidermiddlewares.httperror import HttpError
from twisted.internet.error import DNSLookupError
from twisted.internet.error import... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,677 | estebanfloresf/testcases | refs/heads/master | /utils/generateTC.py | from openpyxl import load_workbook
#import the pandas library and aliasing as pd and numpy as np
import pandas as pd
import numpy as np
import os
class createTestCase():
def __init__(self):
self.dir_path = os.path.dirname(os.path.realpath(__file__))
self.wb = load_workbook(self.dir_path+... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,678 | estebanfloresf/testcases | refs/heads/master | /utils/readTestCases.py | from openpyxl import load_workbook
import re
import json
class readFile():
def __init__(self):
path = 'C:\\Users\\Esteban.Flores\\Documents\\1 Verndale\\2 Projects\\GE-GeneralElectric\\GE TestCases\\0942-(QA) Course Registration Module.xlsx'
self.wb = load_workbook(path, data_only=True)
sel... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,679 | estebanfloresf/testcases | refs/heads/master | /utils/readFiles.py | import os
import re
path = os.chdir('C://Users//503025052//Documents//GE//GE TestCases')
filenames = os.listdir(path)
for index,filename in enumerate(filenames):
try:
extension = os.path.splitext(filename)[1][1:]
if(extension=='xlsx'):
number =re.findall(r'\d+', str(filename))
... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,680 | estebanfloresf/testcases | refs/heads/master | /testcases/items.py | # -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
import scrapy
class TestCasesItem(scrapy.Item):
component = scrapy.Field()
requirements = scrapy.Field()
responsive = scrapy.Field()
pass
class Requ... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,681 | estebanfloresf/testcases | refs/heads/master | /testcases/variables.py | USER='Esteban.Flores'
PASS='estebanFS10' | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,682 | estebanfloresf/testcases | refs/heads/master | /testcases/main.py | from scrapy import cmdline
import os
import inspect
import logging
path = os.path.abspath(os.path.join(os.path.dirname(
os.path.realpath(__file__)), os.pardir)) # script directory
# To generate the verified labels from the input excel (uncomment line below)
# os.system('python '+path+'\\utils\\generateTC.py')
... | {"/testcases/spiders/createTestCase.py": ["/testcases/items.py"], "/testcases/spiders/testSpider.py": ["/testcases/items.py"]} |
1,725 | shikharbahl/multiworld | refs/heads/master | /multiworld/envs/pygame/__init__.py | from gym.envs.registration import register
import logging
LOGGER = logging.getLogger(__name__)
_REGISTERED = False
def register_custom_envs():
global _REGISTERED
if _REGISTERED:
return
_REGISTERED = True
LOGGER.info("Registering multiworld pygame gym environments")
register(
id=... | {"/multiworld/envs/mujoco/__init__.py": ["/multiworld/envs/mujoco/cameras.py"]} |
1,726 | shikharbahl/multiworld | refs/heads/master | /multiworld/envs/mujoco/__init__.py | import gym
from gym.envs.registration import register
import logging
LOGGER = logging.getLogger(__name__)
_REGISTERED = False
def register_custom_envs():
global _REGISTERED
if _REGISTERED:
return
_REGISTERED = True
LOGGER.info("Registering multiworld mujoco gym environments")
"""
R... | {"/multiworld/envs/mujoco/__init__.py": ["/multiworld/envs/mujoco/cameras.py"]} |
1,727 | shikharbahl/multiworld | refs/heads/master | /multiworld/envs/mujoco/cameras.py | import numpy as np
def create_sawyer_camera_init(
lookat=(0, 0.85, 0.3),
distance=0.3,
elevation=-35,
azimuth=270,
trackbodyid=-1,
):
def init(camera):
camera.lookat[0] = lookat[0]
camera.lookat[1] = lookat[1]
camera.lookat[2] = lookat[2]
came... | {"/multiworld/envs/mujoco/__init__.py": ["/multiworld/envs/mujoco/cameras.py"]} |
1,734 | vltanh/CaNet | refs/heads/master | /visualize.py | import torchvision.transforms as tvtf
from PIL import Image
import argparse
import torch
from torch import nn
from torch.utils.data import DataLoader
import torch.nn.functional as F
import torchvision
import numpy as np
import matplotlib.pyplot as plt
from one_shot_network import Res_Deeplab
from utils import load_resn... | {"/visualize.py": ["/one_shot_network.py", "/utils.py"], "/val.py": ["/utils.py", "/one_shot_network.py"], "/one_shot_network.py": ["/utils.py"], "/train.py": ["/utils.py", "/one_shot_network.py"]} |
1,735 | vltanh/CaNet | refs/heads/master | /val.py | from torch.utils import data
import torch.optim as optim
import torch.backends.cudnn as cudnn
import os.path as osp
from utils import *
import time
import torch.nn.functional as F
import tqdm
import random
import argparse
from dataset_mask_train import Dataset as Dataset_train
from dataset_mask_val import Dataset as Da... | {"/visualize.py": ["/one_shot_network.py", "/utils.py"], "/val.py": ["/utils.py", "/one_shot_network.py"], "/one_shot_network.py": ["/utils.py"], "/train.py": ["/utils.py", "/one_shot_network.py"]} |
1,736 | vltanh/CaNet | refs/heads/master | /utils.py | import torchvision
import os
import torch
import torch.nn as nn
from pylab import plt
import numpy as np
def convert_image_np(inp):
"""Convert a Tensor to numpy image."""
inp = inp.numpy().transpose((1, 2, 0))
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
inp = std *... | {"/visualize.py": ["/one_shot_network.py", "/utils.py"], "/val.py": ["/utils.py", "/one_shot_network.py"], "/one_shot_network.py": ["/utils.py"], "/train.py": ["/utils.py", "/one_shot_network.py"]} |
1,737 | vltanh/CaNet | refs/heads/master | /one_shot_network.py | import torch.nn as nn
import torch
import numpy as np
import torch.nn.functional as F
import math
from utils import convert_image_np
# code of dilated convolution part is referenced from https://github.com/speedinghzl/Pytorch-Deeplab
affine_par = True
class Bottleneck(nn.Module):
expansion = 4
def __init__... | {"/visualize.py": ["/one_shot_network.py", "/utils.py"], "/val.py": ["/utils.py", "/one_shot_network.py"], "/one_shot_network.py": ["/utils.py"], "/train.py": ["/utils.py", "/one_shot_network.py"]} |
1,738 | vltanh/CaNet | refs/heads/master | /train.py | from torch.utils import data
import torch.optim as optim
import torch.backends.cudnn as cudnn
import os.path as osp
from utils import *
import time
import torch.nn.functional as F
import tqdm
import random
import argparse
from dataset_mask_train import Dataset as Dataset_train
from dataset_mask_val import Dataset as Da... | {"/visualize.py": ["/one_shot_network.py", "/utils.py"], "/val.py": ["/utils.py", "/one_shot_network.py"], "/one_shot_network.py": ["/utils.py"], "/train.py": ["/utils.py", "/one_shot_network.py"]} |
1,741 | pt657407064/shippoTracking | refs/heads/master | /generator.py | import threading
from time import sleep
import shippo
class generator:
shippo.api_key = "shippo_test_a0159d5cfb4013f15b4db6360f5be757edb6a2d4"
def __init__(self,fromname,fromaddress,fromcity,fromstate,fromcountry,fromzipcode,fromemail,fromphone,
toname,toaddress,tocity,tostate,tocountr... | {"/main.py": ["/generator.py"]} |
1,742 | pt657407064/shippoTracking | refs/heads/master | /main.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file '.\etherousUI.ui'
#
# Created by: PyQt5 UI code generator 5.8.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QMessageBox
from generator import generator
cla... | {"/main.py": ["/generator.py"]} |
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