content stringlengths 5 1.05M |
|---|
# -*- coding: future_fstrings -*-
from fabric.context_managers import cd
from fabric.operations import run
from fabric.state import env
def __task_clean_releases():
with cd(env.release_path):
releases = env.get("keep_releases") or 5
releases_count = int(releases) if str(releases).isdigit() else 5... |
import re
import random
import aiohttp
from fuzzywuzzy import fuzz
import logging
from . import config
from skybeard.beards import BeardChatHandler
logger = logging.getLogger(__name__)
async def get_key():
return BeardChatHandler.key
BOT_JSON = None
async def get_me():
global BOT_JSON
if not BOT_JS... |
# coding: utf-8
"""A tornado based Jupyter lab server."""
# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
# TODO: import base server app
import os
from jupyter_core.paths import jupyter_config_path, jupyter_path
from notebook.notebookapp import NotebookApp
from tra... |
# Copyright 2021 The Cirq Developers
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... |
# project/server/models.py
import datetime
from project.server import app, db, bcrypt
class User(db.Model):
__tablename__ = "users"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
email = db.Column(db.String(255), unique=True, nullable=False)
password = db.Column(db.String(255), ... |
from django.contrib import admin
from .models import Patient
from .forms import PatientAdminForm
# Register your models here.
class PatientAdmin(admin.ModelAdmin):
form = PatientAdminForm
list_display = ['user','created', 'last_updated', 'cart_code']
readonly_fields = ['created', 'last_updated']
admin.sit... |
import numpy as np
# make any plots not use display
from matplotlib import use
use('Agg')
import matplotlib.pyplot as plt
# used for ECDF
import statsmodels.api as sm
from selection.algorithms.lasso import instance
from selection.algorithms.forward_step import forward_step, info_crit_stop, data_carving_IC
from sel... |
import csv
import os
import tempfile
import pytest
from topo_processor.metadata.csv_loader.csv_loader import read_csv
def test_read_csv() -> None:
metadata_path = os.path.join(os.getcwd(), "test_data", "historical_aerial_photos_metadata.csv")
metadata = read_csv(metadata_path, "raw_filename", "sufi")
a... |
import pytest
from flask import g, session
from app.db import get_db
@pytest.mark.parametrize(('username', 'password', 'message'), (
('', '', b'Incorrect username.'),
('test', '', b'Incorrect password.'),
('test', 'test', b'Ok.'),
))
def test_login(client, username, password, message):
response = clie... |
from PyQt5.QtSql import QSqlDatabase, QSqlQuery
import pymysql
from datetime import date
import time
class LinkDatabaseInMysql:
def __init__(self, username, pass_word):
self.connection = pymysql.connect(
host='localhost',
port=3306,
user=username,
password=p... |
import json
from time import sleep
import blessed
import requests
from blessed.keyboard import Keystroke
from modules.game import Game
from modules.game_data import GameData
Bounds = tuple[int, int, int, int]
RenderableCoordinate = tuple[int, int, str]
def _lies_within_bounds(bounds: Bounds, point: tuple[int, int]... |
from .base import *
DEBUG = True
TEMPLATE_DEBUG = True
ADMINS = ()
MANAGERS = ADMINS
SECRET_KEY = 'TEST'
COINS_BASE_URL = 'https://coins.ph'
COINS_API_KEY = "09Wvsxce4IVBYfW1yIn4OnvlstObgTXNEeV0i7jY"
COINS_SECRET = "8PLwxbZpB3nW2N7kqRaIfkgja5kLTMO6VYUaJMLQ3Aea2yfv4K"
# For testing in sandbox
# COINS_BASE_URL = '... |
'''
This file provides a basic framework for a live demo. In this case the
demo is for face and eye detection.
Copyright David S. Bolme
Created on Jul 9, 2011
@author: bolme
'''
import pyvision as pv
import cv
from pyvision.face.CascadeDetector import CascadeDetector
from pyvision.face.FilterEyeLocator import Filt... |
# This class is used to implement a stack which in turn is used to implement LRU
class Stack:
# Default constructor
def __init__(self):
self.items = []
# Function used to push an item on to the stack
def push(self, item):
self.items.append(item)
# Function used to remov... |
from rest_framework.generics import ListAPIView
from rest_framework.permissions import IsAuthenticated
from notifications.models import Notification
from .serializers import NotificationSerializer
class NotificationListAPIView(ListAPIView):
"""
View that returns notification list of a single user.
"""
... |
from maya import cmds
from PySide2 import QtWidgets, QtGui, QtCore
from ncachefactory.optionvars import (
RANGETYPE_OPTIONVAR, CACHE_BEHAVIOR_OPTIONVAR, VERBOSE_OPTIONVAR,
VERBOSE_OPTIONVAR, SAMPLES_EVALUATED_OPTIONVAR, SAMPLES_SAVED_OPTIONVAR,
ensure_optionvars_exists)
BLENDMODE_LABELS = (
"Clear all... |
#import skimage.io as io
#import matplotlib.pyplot as plt
import numpy as np
from sklearn.metrics import f1_score, precision_score, recall_score, accuracy_score
def read_img(img_path):
img = io.imread(img_path)
return img
def save_img(img_path, np_array):
io.imsave(img_path, np_array)
def extract_patches(outpu... |
from transformers import RobertaTokenizer, RobertaModel, RobertaConfig
import torch
import os
class EmbeddingGenerator:
''' A class which generates embeddings for text and saves them to data/tensors/ '''
def __init__(self):
self.config = RobertaConfig.from_pretrained("roberta-base")
self.confi... |
import asyncio
import datetime
import json
import logging
from pathlib import Path
import discord
from discord.ext import commands
# https://discordapp.com/oauth2/authorize?client_id=500165490753404938&scope=bot&permissions=8
# APPROVED SERVERS:
# Fooeyy Official - 476519720380792834
def config_load():
with op... |
def number_generator():
yield 0
yield 1
yield 2
# for i in number_generator():
# print(i)
g = number_generator()
# print(dir(g))
print(next(g))
print(next(g))
print(next(g))
def one_generator():
yield 1
return 'return에 지정한 값'
try:
g = one_generator()
next(g)
next(g)
except ... |
# coding: utf-8
"""Набор конструкция для работы с уровнем моделей."""
import os
import simplejson as json
import sqlalchemy
from sqlalchemy.exc import IntegrityError
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.inspection import inspect
from sqlalchemy.orm.properties import ColumnProperty
from sqlal... |
from process import wordlist
import itertools
import time
import os
import re
ALPHABET = '23456789abcdefghjkmnpqrstuvwxyz'
def main():
blacklist_all = wordlist.dict_by_length()
blacklist = blacklist_all[3].union(blacklist_all[4]).union(blacklist_all[5])
combinations = get_combinations(3)
tick = time.t... |
'''
Created on 13.06.2016
@author: Fabian Reiber
@version: 1.0
'''
class NoFingerprintException(Exception):
def __str__(self, *args, **kwargs):
return Exception.__str__(self, *args, **kwargs)
#
# a = NoFingerprintException('Blaa')
# print('test:', a.args[0])
# raise a
|
#!/usr/bin/python
import sys, os, platform
import configparser
from executely.constants import Java
class AppConfiguration(object):
def __init__(self, app_path):
if (not os.path.exists(app_path)):
raise Exception('The app folder "%s" does not exist!' % app_path)
config = conf... |
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# 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 appli... |
#!/usr/bin/env python3
from pathlib import Path
from typing import Any, Dict
import jinja2
from aiohttp import web
from aiohttp_jinja2 import setup as jinja2_setup, template
from aiohttp_session import SimpleCookieStorage, get_session, setup as session_setup
from aiohttp_oauth2.client.app import oauth2_app
from func... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# VideoColorSpace for Dreambox-Enigma2
#
# Coded by cmikula (c)2012
# Support: www.i-have-a-dreambox.com
#
# This plugin is licensed under the Creative Commons
# Attribution-NonCommercial-ShareAlike 3.0 Unported
# License. To view a copy of this license, visit
# http://c... |
from nextcord.ext.commands.errors import CheckFailure
class NotConnectedToVoice(CheckFailure):
"""User not connected to any voice channel"""
pass
class PlayerNotConnected(CheckFailure):
"""Player not connected"""
pass
class MustBeSameChannel(CheckFailure):
"""Player and user not in same chan... |
import numpy as np
from collections import defaultdict
from formulagen.formula import as_str
from formulagen.formula import as_tree
from formulagen.formula import gen_formula_tree
from formulagen.formula import Unit
from formulagen.formula import Node
def count():
return defaultdict(int)
class TreeGram:
... |
from data_detective_airflow.operators.extractors.db_dump import DBDump
from data_detective_airflow.operators.extractors.python_dump import PythonDump
from data_detective_airflow.operators.extractors.request_dump import RequestDump
from data_detective_airflow.operators.extractors.s3_dump import S3Dump
from data_detectiv... |
import os
from pydub.utils import make_chunks
from pydub import AudioSegment
chunk_size = 60000 #millisecs
ragas = ['Kapi',
'Mayamalavagowla',
'Harikambhoji',
'Kharaharapriya',
'Nattai',
'Bilahari',
'Charukesi',
'Abheri',
'Kamas',
'B... |
# ===============================================================================
# Program : iterative_vasp_run.py
# Author : Hyeongseon Park
# must be run in the main_dataset directory!!
# This code iteratively runs "vasp_run.sh" using "qsub" command in super-computing
# server in NURION (by KISTI)
# =========... |
# Copyright 2017 Google Inc. All Rights Reserved.
#
# 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 a... |
# Copyright (c) 2015-2022 Vector 35 Inc
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, ... |
from django.shortcuts import redirect
from .models import HouseMembership
def house_required(function=None):
def wrapper(request, *args, **kwargs):
user = request.user
try:
currentHouse = HouseMembership.objects.get(user=user, currentHouse=True)
except HouseMembership.DoesNotExist:
currentHouse = None
... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import os.path
sys.path.append(os.path.join(os.getcwd(), '.'))
sys.path.append(os.path.join(os.getcwd(), '..'))
|
import json
import os
import argparse
from shutil import copy, SameFileError
import logging
from tqdm import tqdm
from PIL import Image
from pathlib import Path
from odm_report_shot_coverage.models.reconstruction import parse_reconstruction
from odm_report_shot_coverage.models.shot import Boundaries
Image.MAX_IMAGE_... |
class Solution:
def containsNearbyDuplicate(self, nums: List[int], k: int) -> bool:
dic = {}
for i, x in enumerate(nums):
if x in dic:
if abs(dic[x] - i) <= k:
return True
dic[x] = i
return False
|
def main(parameters):
'''
Gets al ist of users at a certain location
NOTE: not implemented yet
'''
answer = {
'text': 'This feature is not yet implemented.',
'markdown': 'This feature is not yet implemented.',
'file': None
}
return answer |
from jinja2 import Environment, FileSystemLoader, select_autoescape, meta, Template
from sql_gen.template_source import TemplateSource
from sql_gen.prompter import Prompter
from sql_gen.filter_loader import load_filters
from sql_gen_app import run_app
##main
def main():
run_app()
if __name__ == '__main__':
m... |
from pymongo import MongoClient
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"-u", "--mongo_url", default="localhost", dest = "u"
)
parser.add_argument(
"-d", "--mongo_db", default="pmc", dest = "d"
)
parser.add_argument(... |
from .python_package_template import PythonPackageTemplate
|
# -*- coding: utf-8 -*-
from hcloud.core.domain import BaseDomain, DomainIdentityMixin
class Location(BaseDomain, DomainIdentityMixin):
"""Location Domain
:param id: int
ID of location
:param name: str
Name of location
:param description: str
Description of location
... |
# import inspect
# import os
#
#
# def test_rules_imported():
# """
# Проверяем что все правила импортированны в __init__
# :return:
# """
# import policy
#
# members = inspect.getmembers(policy, inspect.ismodule)
# modules_imported = set(name for name, _ in members)
#
# # Берем все файл... |
class Piece:
def __init__(self, name, *, is_white: bool = True):
self.name = name
self.is_white = is_white
self.color = 'white' if is_white else 'black'
self.has_moved = False
def find_piece(self, board):
position = None
for row in board:
for cell in ... |
import re
import os
import json
from ts import Simbolo
from storageManager import jsonMode as jsonMode
from tabla_errores import *
from columna import *
import math
import numpy as np
from random import random
class TypeChecker():
'Esta clase representa el type checker para la comprobación de tipos'
def __i... |
from django import forms
from django.forms import formset_factory
from .models import Category,Measure,IngPrice
class RecipeForm(forms.Form):
name = forms.CharField(
label="Recipe name",
required=True,
widget=forms.TextInput(
attrs={
'placeholder':"Enter Recipe... |
import tensorflow as tf
flags = tf.app.flags
FLAGS = flags.FLAGS
flags.DEFINE_integer('hidden3', 64, 'Number of units in hidden layer 3.')
flags.DEFINE_integer('discriminator_out', 0, 'discriminator_out.')
flags.DEFINE_float('discriminator_learning_rate', 0.001, 'Initial learning rate.')
flags.DEFINE_float('learning_... |
from django.db.models.signals import pre_save,post_save
from .mysingal import action
def pre_save_func(sender,**kwargs):
print(sender)
print(kwargs)
print(kwargs.get("instance"))
# pre_save.connect(pre_save_func)
post_save.connect(pre_save_func)
def my_action_func(sender,**kwargs):
pr... |
import os
import shutil
import hdbscan
from math import isclose
import numpy as np
from sklearn.metrics import adjusted_rand_score
from oolearning import *
from tests.TestHelper import TestHelper
from tests.TimerTestCase import TimerTestCase
# noinspection PyMethodMayBeStatic, PyUnresolvedReferences
class Unsuperv... |
# 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 t... |
from .module import Module
from .pipeline import Pipeline
from .pipeline import PipelineNode
from .module import Module2
from .pipeline import Pipeline2
from .pipeline import Node |
# CloudKit Helper
#
#
# Based off the following
# - CloudKitCatalog (c) 2016, Apple
# - PyCloudKit. Created on 09.02.2016 (c) 2015 Andreas Schulz
# - requests-cloudkit Copyright 2016 Lionheart Software LLC
from __future__ import print_function
import ecdsa
import base64
import hashlib
import datetime
import sys
im... |
#!/usr/bin/env python
import sys
from PyQt5 import QtGui, QtWidgets, QtCore
#create class for QPix map that just changes picture based on button pressest
class WindowScreen(QtWidgets.QWidget):
def __init__(self):
super().__init__()
self.string_of_commands = ''
self.setWindowTitle("Traject... |
# automatically generated by the FlatBuffers compiler, do not modify
# namespace: graph
class ExecutionMode(object):
SEQUENTIAL = 0
STRICT = 1
AUTO = 2
|
import sys
from setuptools import setup
VERSION = '0.0.1'
DESCRIPTION = 'WRITE SOMETHING INTELLIGENT HERE!'
CLASSIFIERS = ['Development status :: 3 - Alpha',
'Intended Audience :: Ay250 grader',
'Topic :: Software Development :: Libraries :: Python Modules',
'License :: OS... |
from dataclasses import dataclass
from enum import Enum
from typing import Optional, List, Sequence, Any
import numpy as np
from tabulate import tabulate
from pyqumo.matrix import str_array
from pyqumo.random import CountableDistribution, Distribution
from pyqumo.sim.helpers import build_statistics, FiniteFifoQueue, \... |
import logging
from .traderbot import TraderBot
import json
import config
class MockMarket(object):
def __init__(self, name, fee=0, cny_balance=3000., btc_balance=10.,
persistent=True):
self.name = name
self.filename = "traderbot-sim-" + name + ".json"
self.cny_balance = c... |
import numpy as np
import cv2
camera = cv2.VideoCapture(0)
# determine upper and lower HSV limits for (my) skin tones
lower = np.array([0, 100, 0], dtype="uint8")
upper = np.array([50,255,255], dtype="uint8")
while (True):
ret, frame = camera.read()
if not ret:
continue
# switch to HSV
hsv = ... |
"""3. Longest Substring Without Repeating Characters
https://leetcode.com/problems/longest-substring-without-repeating-characters/
Given a string, find the length of the longest substring without repeating
characters.
Example 1:
Input: "abcabcbb"
Output: 3
Explanation: The answer is "abc", with the length of 3.
Ex... |
import os
import pickle
import operator
from . import config
from . import lib
from .profanity_rater import profanity_severity_rating
from .spam_rater import spam_severity_rating
from .short_content_rater import short_content_severity_rating
from .keyword_stuffing_rater import keyword_stuffing_severity_rating, find_stu... |
from solutions.CHK import checkout_solution
from unittest import TestCase
class TestSum(TestCase):
def test_chkE(self):
self.assertEqual(checkout_solution.checkout('BBE'), 85)
def test_chkEE(self):
self.assertEqual(checkout_solution.checkout('BBEE'), 110)
def test_chkABCDE(self):
... |
# -*- coding: utf-8 -*-
"""Synteny (genome order) operations."""
# standard library imports
import sys
from itertools import combinations
# from os.path import commonprefix as prefix
from pathlib import Path
# third-party imports
import dask.bag as db
import networkx as nx
import numpy as np
import pandas as pd
from ... |
import unittest
from jina.executors.encoders.nlp.transformer import TransformerTFEncoder, TransformerTorchEncoder
from tests.unit.executors.encoders.nlp import NlpTestCase
class PytorchTestCase(NlpTestCase):
def _get_encoder(self, metas):
return TransformerTorchEncoder(
pretrained_model_name_... |
from os.path import join
from celery import Celery
from flask import Flask
from flask_assets import Environment as FlaskAssets, Bundle
from flask_migrate import Migrate
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config.from_object('config.Config')
app.secret_key = app.config['SECRET_KEY']
ce... |
"""
Code to make an exploratory plot of the output of a box extraction.
"""
from lo_tools import Lfun, zfun
from lo_tools import plotting_functions as pfun
import xarray as xr
import matplotlib.pyplot as plt
import numpy as np
import sys
from cmocean import cm
import pandas as pd
Ldir = Lfun.Lstart()
# choose the fi... |
import numpy as np
# most basic functions
def sigmoid(x):
"""sigmoid function"""
return 1/(1+np.exp(-x))
def sigmoid_gradient(x):
"""gradient of sigmoid function"""
return x * (1-x)
def tanh(x):
"""tanh function"""
return np.tanh(x)
def tanh_gradient(x):
"""gradient of tanh function"... |
#!/usr/bin/env python
import sys
if sys.version_info.major == 3:
import exodus3 as exo
else:
import exodus2 as exo
import os.path
import numpy as np
f = sys.argv[-1]
if not os.path.isfile(f) or not (len(sys.argv) == 2):
print "usage: {0} <filename>".format(sys.argv[0])
exit
e = exo.exodus(f,"r")
dim ... |
# The MIT License (MIT)
#
# Copyright (c) 2020 Huimao Chen
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modif... |
import torch
import torch.nn as nn
import torch.nn.functional as F
class Generator(nn.Module):
def __init__(self):
super(Generator, self).__init__()
self.linear_z = nn.Linear(100, 200)
self.linear_y = nn.Linear(10, 1000)
self.linear = nn.Linear(1200, 784)
# "In our generat... |
import os,sys,time
from Tkinter import *
from PIL import Image, ImageTk
import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BCM)
GPIO.setup(8, GPIO.IN, pull_up_down=GPIO.PUD_UP)
def RunPlaylist():
hdmi.destroy()
path = '/home/pi/Desktop/majestic-pi/current.txt'
file = open(path... |
from csvhandler import *
import logging
class DataFeed(object):
def __init__(self, instrument):
self.feed = None
self.subscribe_to_price_feed_for_instrument(instrument)
def n_day_moving_avg(self, instrument, date, price, n):
'''
trading, not calendar, day average
'''
j = -1
for i ... |
from Crypto import Random
from Crypto.Cipher import AES
from Crypto.Hash import SHA256
def get_key(
password: str
) -> bytes:
"""Generates an encryption key based on the password provided."""
key = SHA256.new(password.encode()).digest()
return key
def encrypt(
key: bytes,
source: bytes
) ->... |
from .dataset import split, deploy, deploy_and_split
from .generic import *
class DatasetCreator:
''' Create a dataset from a string.
dataset_cmd (str):
Command to execute.
ex: "ImageList('path/to/list.txt')"
Returns:
instanciated dataset.
'''
def __init__(self, globs):
... |
class Logger:
enable_logging = True
def __init__(self, owning_class):
self.owning_class_name = type(owning_class).__name__
def warning(self, message):
self.log("Warning: " + message)
def log(self, message):
if (Logger.enable_logging):
print(self.owning_class_name +... |
def bezout(a, b):
"""returns u, v such as au+bv = pgcd(a,b)"""
if b == 0:
return (1, 0)
else:
(u, v) = bezout(b, a % b)
return (v, u - (a // b) * v)
def chinese_theorem_inv(modulo_list):
"""
Returns (x, n1*...*nk) such as
x mod mk = ak for all k, with
modulo_list =... |
import unittest
from mock import patch
from bbpyp.ll_combinator.defer import Defer
@patch('test.TestContext', create=True)
class TestDefer(unittest.TestCase):
def test_defer_initialized_as_expected(self, test_context):
expected_parser_factory = test_context.parser_factory
parser = Defer(test_co... |
from dataclasses import dataclass, field
from typing import Optional
from bindings.csw.angle_type import AngleType
from bindings.csw.vector import Vector
__NAMESPACE__ = "http://www.opengis.net/gml"
@dataclass
class DirectionVectorType:
"""
Direction expressed as a vector, either using components, or using a... |
class TestPolicy:
def test_view_policy(self, lenses_conn):
result = lenses_conn.ViewPolicy()
assert type(result) is list
def test_set_policy(self, lenses_conn):
result = lenses_conn.SetPolicy("test_policy","All","HIGH","test_category",["test_field"])
policies = lenses_conn.View... |
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Abstract class for utilities that upload to and download from object stores."""
import abc
import pathlib
from typing import Callable, Optional, Union
__all__ = ['ObjectStore', 'ObjectStoreTransientError']
class ObjectStoreTransien... |
import os
import os.path as osp
import click
from prettytable import PrettyTable
import pandas as pd
from he import colors
from he.config import *
from he.experiment import Experiment
from he.util import ExclusivePersistentObject
class Workspace:
"""HE Workspace"""
def __init__(self):
experiments_fi... |
"""
Initialization module.
"""
|
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib import rc
from matplotlib import rcParams
from matplotlib import style
# https://stackoverflow.com/questions/15814635/prettier-default-plot-colors-in-matplotlib
# http://seaborn.pydata.org/tutorial/color_palettes.html
#import seaborn a... |
from nacl.utils import random
from nacl.secret import SecretBox
from nacl.pwhash.argon2i import kdf
class TestRule4c:
def __init__(self):
self.g_salt1 = b"1234567812345678"
self.g_salt2 = bytes("1234567812345678", "utf8")
self.nonce = b"123456781234567812345678" # 24 byte
def p_examp... |
### This is a script to get fragments using Murcko method ###
import os
import pandas as pd
import rdkit
from rdkit import Chem
from rdkit.Chem.Scaffolds import MurckoScaffold as Murcko
from rdkit.Chem import AllChem
import numpy as np
import ast
def get_fragments(insmiles):
"""Get core and sidechains using Murcko... |
"""This module contains utilities for docstrings parsers."""
from __future__ import annotations
from ast import PyCF_ONLY_AST
from contextlib import suppress
from typing import TYPE_CHECKING, Callable
from griffe.agents.nodes import get_annotation
from griffe.expressions import Expression, Name
from griffe.logger im... |
from decimal import Decimal
import numpy as np
import matplotlib.pyplot as plt
from scipy import io
from scipy.optimize import minimize
def cofi_costfunc(params, Y, R, num_users, num_movies,
num_features, lambda_):
# 还原参数
X = params[:num_movies *
num_features].reshape(num_mov... |
import glob
import subprocess
import sys
from multiprocessing import Pool
FILES_DIR = '/tmp/credo/parts'
CORES = 4
def run_file(fn):
print('Start compressing: %s' % fn)
sp = subprocess.Popen(["xz", "-9e", fn])
sp.wait()
print('... finish compressing: %s' % fn)
def main():
# list all files in IN... |
# MenuTitle: Copy Paths To All Layers
for layer in Glyphs.font.selectedLayers:
g = layer.parent
paths = [p.copy() for p in layer.paths]
for l in g.layers:
if layer == l:
continue
l.shapes = []
for p in paths:
l.paths.append(p.copy())
l.width = layer.width |
from toolz.functoolz import curry
from sympy.core.function import Function
NAN = Function('NAN')
Missing = Function('Missing')
NaNProtect = Function('NaNProtect')
Expit = Function('Expit')
# def call_method_or_dispatch(method_name, dispatcher):
# def _call_method_or_dispatch(estimator, *args, **kwargs):
# ... |
from datetime import datetime
from abc import ABCMeta, abstractmethod
from typing import List
from domain.entry import Entry
class EntryRepository(metaclass=ABCMeta):
@abstractmethod
def get_all_entries(self, url: str) -> List[Entry]:
raise NotImplementedError
@abstractmethod
def get_until_l... |
from scrabbler.scrabbler import Game
# from dqn.dqn_scrabble_helpers import DQNScrabbleHelpers
import random
import copy
class Simulation:
# LETTERS = ("AAAAAAAAAB"
# "BCCDDDDEEE"
# "EEEEEEEEEF"
# "FGGGHHIIII"
# "IIIIIJKLLL"
# "LMMNNNNNNO"
... |
print([123, 'das'] * 2 ) |
# -*- coding: utf-8 -*-
import unittest
import psycopg2
import mock
from pgclient.exceptions import ErrorsRegistry as registry, PgClientError
class ErrorsRegistryTest(unittest.TestCase):
def test_registry(self):
from psycopg2 import errorcodes
codes = {k: v for k, v in errorcodes.__dict__.items()
... |
import torchdiffeq
import torch
import torch.utils.data
import torch.nn as nn
import numpy as np
import transformer.Constants as Constants
from transformer.Layers import EncoderLayer, DecoderLayer
from transformer.Modules import ScaledDotProductAttention
from transformer.Models import (
Decoder, get_attn_key_pad_ma... |
import data_preparation
def main(file):
data_preparation.save_data(file)
file = '../data/viirs-snpp_2016_Australia.csv'
main(file) |
import requests
class ImportApi:
""" import french products from api openfoodfact"""
def __init__(self):
self._page = None
self._page_size = None
self._actual_request = None
self._status_code = None
self._imported_file = None
@property
def page(self):
... |
import cv2
import random
import itertools
import numpy as np
from skimage.measure import compare_mse
def random_drop(img, ws, ratio):
h, w = img.shape[:2]
drop_map = np.zeros((h, w))
img_drop = img.copy()
for i, j in itertools.product(range(h // ws), range(w // ws)):
drop_index = random.sample... |
import numpy as np
import matplotlib.pyplot as plt
import os
import itertools
import bayesiantests as bt
import matplotlib.pyplot as plt
import seaborn as snb
import scipy.io as sio
# Define set that stores names of results files.
res_list = []
# Define path to folder containing results.
RESULTS_FOLDER = '../resul... |
# -*- coding: utf-8 -*-
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.callbacks import ModelCheckpoint
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from sklearn.... |
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