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550f5ad4fef77d5795db0393ae0701f679143e72 | #!/usr/bin/env python
# @HEADER
# ************************************************************************
#
# TriBITS: Tribal Build, Integrate, and Test System
# Copyright 2013 Sandia Corporation
#
# Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
# the U.S. Govern... | [
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4fa9d16f979acf3edce05a209e1c6636e50fc315 | from jox_api import label_image, Mysql, Utils
from jox_config import api_base_url
import json
class Menu:
def __init__(self):
self.mysqlClass = Mysql.MySQL()
self.timeClass = Utils.Time()
def get_menu(self, type, openid):
try:
if type == "mine":
self.sql = ... | [
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e5e012e40a71dee9f4dbd9913590aef125b758df | from classes.Board import Board
class Visualiser:
coordinate_map = ("a", "b", "c", "d", "e", "f", "g", "h")
__dimensions = 8
def __init__(self):
self.map = []
self.__build_map()
def __build_map(self):
"""
Creates the array of the battlefield. Should never be used for ... | [
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27e9e63338d422b5fca6f7a67fa3d255602a3358 | from abstract_class_V import V
import torch
import torch.nn as nn
class V_test_abstract(V):
def __init__(self):
super(V_test_abstract, self).__init__()
def V_setup(self, y, X, nu):
self.explicit_gradient = False
self.need_higherorderderiv = True
self.dim = X.shape[1]
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d0a3f332e04627eb275168972bd92cd1ea9b9447 | from board.ttt import TTT
from mctsai.mcts import MCTS
import unittest
# skip = [0, 1]
skip = [0]
class TestTTT(unittest.TestCase):
def test_mcts(self):
if 0 in skip:
print("Skipping ai self-play")
return
ttt = TTT()
for i in range(1000):
mcts = MCTS(t... | [
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f85a703b47d981397ed6048e941030a3fbee7b6d | # -*- coding: utf-8 -*-
# Generated by Django 1.9.8 on 2018-04-27 08:05
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("talk", "0023_auto_20180207_1121"),
]
operations = [
migrations.AddField(
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f8d815bcdc74452b66a1b3b33bf0fbe976e728c8 | # This is a sample Python script.
# Press Shift+F10 to execute it or replace it with your code.
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
import tensorflow as tf
from tensorflow.keras import datasets, layers, models
import matplotlib.pyplot as plt
import numpy ... | [
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ef85f94282bfd7c9491c4e28bab61aaab5c792a5 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'src/ui_LibraryTab.ui'
#
# Created: Tue Jun 9 21:46:41 2015
# by: PyQt5 UI code generator 5.4
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Tab(object):
def setupUi(s... | [
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8c8bbbc682889c8d79c893f27def76ad70e8bf8d | DATABASE_NAME = "user_db"
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9d904225afd4f4d0cf338ae16f031f8ab41639ad | # -*- coding=utf-8 -*-
from mako.template import Template
from xblock.fragment import Fragment
from .lookup import TemplateLookup # xblock_ifmo.lookup
from .utils import deep_update
class FragmentMakoChain(Fragment):
"""
Класс, позволяющий последовательно оборачивать экземпляры Fragment друг в
друга.
... | [
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... |
8cc0393082448bb8f61068b5c96e89ef3aee77ed | # coding: utf-8
import logging
from threading import Thread
from ldap import SCOPE_BASE
from seafevents.ldap_syncer.ldap_conn import LdapConn
from seafevents.ldap_syncer.utils import bytes2str, add_group_uuid_pair
from seaserv import get_group_dn_pairs
logger = logging.getLogger(__name__)
def migrate_dn_pairs(set... | [
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47... |
eb853e430b996a81dc2ef20c320979a3e04d956a | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
import hashlib
import re
from datetime import datetime
import gevent
import requests
import scrapy
from gevent.pool import Pool
from lxml import etree
from scrapy.http import HtmlResponse
from sqlalchemy import create_engine, func
from sqlalchemy.orm import sessionmaker
... | [
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5... |
bc4684d255a46427f708d8ce8bda2e12fb8c8ffe | # -*- coding: utf-8 -*-
from route4me import Route4Me
API_KEY = "11111111111111111111111111111111"
def main():
r4m = Route4Me(API_KEY)
route = r4m.route
response = route.get_routes(limit=1, offset=0)
if isinstance(response, dict) and "errors" in response.keys():
print(". ".join(response["err... | [
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d015a1b27a3a9e7f5e6614da752137064000b905 | #!/usr/bin/env python3
"""Transfer learning with xception"""
import tensorflow.keras as K
from GPyOpt.methods import BayesianOptimization
import pickle
import os
import numpy as np
class my_model:
"""A model bassed on xception"""
def make_model(self, param):
"""makes the model"""
self.lr = p... | [
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ef6f55bf27982f53441215da6822cfcdc80706a5 | # -*- coding: utf-8 -*-
__author__ = "Yun"
__project__ = "DjangoBookTest2"
# from django.template import Template, Context
# from django.template.loader import get_template
# from django.http import HttpResponse
from django.shortcuts import render_to_response
import datetime
def current_datetime(request):
# now ... | [
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... |
e616d14827beaa08ab08219421cbf7990cf163fd | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.constant.ParamConstants import *
from alipay.aop.api.domain.InsureAdmitDTO import InsureAdmitDTO
class AlipayInsSceneEcommerceInsureCheckModel(object):
def __init__(self):
self._insure_admit_dto_list = None
self._partne... | [
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c4ca4b5c77c3c912b44a4853be30298ec845c4fd | # str
owog = "Delger"
# len()- urt
# lower()- jijigruuleh
# upper()- tomruulah
# capitalize()- ehnii useg tomruulah
# replace()- temdegt solih
print(owog.find("e"))
print(owog.count("e"))
print(owog[2:10])
a = 21
b = 21
if a > b:
print("a too ih")
elif a == b:
print("tentsuu")
else:
print("b too ih")
... | [
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050e2207ac7331444d39305869c4b25bcbc53907 | import pandas as pd
from sklearn.preprocessing import MinMaxScaler
# loading data from CSV
training_data_df = pd.read_csv("sales_data_training.csv")
test_data_df = pd.read_csv("sales_data_test.csv")
# scaler
scaler = MinMaxScaler(feature_range=(0, 1))
# scale both inputs and outputs
scaled_training = scaler.fit_tran... | [
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21b295e28a7e4443ea116df1b22ff5074dca955a | n = int(input("nhap gia tri"))
for i in range(1, n + 1):
print(i)
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93737e4c409d0efb1ae2263cb60d4b03d9aad0d8 | import os
import shutil
import argparse
ap = argparse.ArgumentParser()
ap.add_argument("-D", "--dir", required=False, help="Directory to sort")
args = vars(ap.parse_args())
if args["dir"] == None:
DIR = os.getcwd()
elif os.path.exists(args["dir"]):
DIR = args["dir"]
for file in os.listdir(DIR):
if not os... | [
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b5611c668a40e1735c92d6d00867885023ad713f | target = []
with open("IntegerArray.txt", "r") as f:
target = f.readlines()
for x in range(len(target)):
target[x] = int(target[x])
def f(A):
if len(A) == 1:
return 0
else:
rightStart = len(A) // 2
leftArray = A[0:rightStart]
righArray = A[rightStart:]
B, b = co... | [
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68b967ecf18d576758cf05e889919944cfc34dcd | """
generalised behaviour for actors and vacancies
"""
from mesa import Agent
from random import shuffle
import numpy as np
class Entity(Agent):
"""
superclass for vacancy and actor agents
not intended to be used on its own, but to inherit its methods to multiple other agents
"""
def __init__(se... | [
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46babde9c26a944c9d29121b6bbf89a32f242a81 | import simple_draw as sd
import random
# sd.resolution = (1400, 900)
# Prepare data for the sun function
def sun_prepare(xpoint, ypoint, radius, color, angle):
delta_list = []
radius_list = []
for delta in range(0, 360, angle):
delta_list.append(delta)
radius_list.append(random.randint(r... | [
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e736991f364ba9ff709348e4b1f612b1e9673281 | from flask import *
app = Flask(__name__)
from app import views
from app import admin_views
from app import usr_reg
from app import cookie
from app import db_connect
| [
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18d3f58048b7e5d792eb2494ecc62bb158ac7407 | from flask import Flask
from flask import render_template
from flask import make_response
import json
from lib import powerswitch
app = Flask(__name__)
@app.route("/")
def hello_world():
return render_template("index.html")
@app.route("/on/")
def on():
state = powerswitch.on()
return json.dumps(state... | [
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869284fa531a93c1b9812ed90a560d0bb2f87e97 | # fonction pour voir quel est le plus grand entre l'energie limite et l'enerve potentiel
def ep(m, h, el, g=9.8):
E = m * h * g
if E < el:
print("le plus grand est : el")
else:
print("le plus grand est : E")
ep(3, 4, 5)
# fontion fibonaci 0 1 1 2 3 5 8 13
def fibonaci(n):
for i in r... | [
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d126efa91b964a3a374d546bb860b39ae26dfa22 | """A tiny example binary for the native Python rules of Bazel."""
import unittest
from bazel_tutorial.examples.py.lib import GetNumber
from bazel_tutorial.examples.py.fibonacci.fib import Fib
class TestGetNumber(unittest.TestCase):
def test_ok(self):
self.assertEqual(GetNumber(), 42)
def test_fib(se... | [
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e582787a912f479830ed99575b2c6adb8088b4e5 | from flask import Flask, request
from flask import jsonify
from preprocessing import QueryProcessor
from flask_cors import CORS
app = Flask(__name__)
CORS(app)
qp = QueryProcessor()
@app.route("/search_general", methods=["POST"])
def query():
message = None
searchQuery = request.json["searchQuery"]
resul... | [
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f8bf7e2d8f06bbd00f04047153833c07bf483fd3 | from django.apps import AppConfig
class PyrpgConfig(AppConfig):
name = "PyRPG"
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48677d73f6489ce789884a9dff5d50c23f47d8b3 | __author__ = "simon.hughes"
from sklearn.feature_extraction import DictVectorizer
from WindowFeatures import compute_middle_index
from collections import Counter
class WindowFeatureExtractor(object):
"""
A simple wrapper class that takes a number of window based feature extractor
functions and applies th... | [
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47c1ad4bd1ceffa38eef467ea8eb59dbd2fc2ebb | from packet import Packet
from packetConstructor import PacketConstructor
import threading
import time
class PacketSender:
"""
Packet represents a simulated UDP packet.
"""
# The next seq num for sent packets
seq_num = 0
# The next seq num for acks that we're waiting for
next_seq_num = 0
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24cdbbadc8ff1c7ad5d42eeb518cb6c2b34724a2 | from openfermion import QubitOperator, FermionOperator
from openfermion.transforms import jordan_wigner
from src.utils import QasmUtils, MatrixUtils
from src.ansatz_elements import AnsatzElement, DoubleExchange
import itertools
import numpy
class EfficientDoubleExchange(AnsatzElement):
def __init__(self, qubit_... | [
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2843845848747c723d670cd3a5fcb7127153ac7e | from flask import Flask
from sim.toggle import ToggleSensor
from sim.sensor import Sensor
app = Flask(__name__)
sensors = [
ToggleSensor(id="s-01", description="lampadina"),
ToggleSensor(id="s-02", description="lampadina"),
ToggleSensor(id="s-03", description="allarme atomico"),
ToggleSensor(id="s-04... | [
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f5bd41f4aaff616a332d80ec44c364ffc91c58f0 | # %load q03_skewness_log/build.py
from scipy.stats import skew
import pandas as pd
import numpy as np
data = pd.read_csv("data/train.csv")
# Write code here:
def skewness_log(df):
df["SalePrice_New"] = np.log(df["SalePrice"])
df["GrLivArea_New"] = np.log(df["GrLivArea"])
skewed_slPri = skew(df["SalePrice... | [
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d65f858c3ad06226b83d2627f6d38e03eae5b36c | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Phase transition module"""
import utils
import datetime
import itertools
import numpy as np
import recovery as rec
import sampling as smp
import graphs_signals as gs
import pathos.multiprocessing as mp
from tqdm import tqdm
## MAIN FUNCTIONS ##
def grid_evaluati... | [
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f97a892e6e0aa258ad917c4a73a66e89b0dc3253 | # coding: utf-8
# In[1]:
import sys
sys.path.extend(["detection", "train"])
# from detection folder
from MtcnnDetector import MtcnnDetector
from detector import Detector
from fcn_detector import FcnDetector
# from train folder
from model_factory import P_Net, R_Net, O_Net
import config as config
from preprocess.uti... | [
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df40b0628d6a180a98cd385145ee7c65ecb78256 | import os
import tensorflow as tf
import torch
from tqdm import tqdm
from glob import glob
import numpy as np
from collections.abc import Iterable
from utils.hparams import HParam
# from utils.audio import Audio
# import librosa
# python encoder_inference.py --in_dir training_libri_mel/train/ --gpu_str 5
# python tfre... | [
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ed7b29a4d7f3a48884434373418c3528f2f397ac | #!/usr/bin/python3
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" # or any {'0', '1', '2'
os.environ["KERAS_BACKEND"] = "tensorflow"
import numpy as np
import sys
from util import load_model
from keras.preprocessing.text import hashing_trick
from keras.preprocessing.sequence import pad_sequences
from southpar... | [
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b6d8a918659f733919fe3bb4be9037e36ad32386 | import queue
import sys
import logging
from superai.common import InitLog
logger = logging.getLogger(__name__)
# 2维到1维
def hwToidx(x: int, y: int, weight: int):
return y * weight + x
# 1维到2维
def idxTohw(idx, weight: int):
return [idx % weight, idx // weight]
# 10x10 cell idx 到 [x,y]
def idxToXY(idx, cel... | [
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7930bb813bd546747c7c65b661900939f5ba93f1 | user_input = input() # abv>1>1>2>2asdasd
exploded_str = user_input
for n in range(len(user_input)):
explosion_strength = 0
if user_input[n] == ">":
explosion_strength += int(user_input[n + 1])
if user_input[n + explosion_strength] != ">":
exploded_str = user_input[:n] + user_input[... | [
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c6cf085330f47ffb139c5acc91d91e9758f5396a | from page_objects import PageObject, PageElement
class MainPage(PageObject):
level_menu_opened = False
level_menu_created = False
css_input = PageElement(css="input.input-strobe")
level_text_span = PageElement(css="span.level-text")
instruction_h2 = PageElement(css="h2.order")
enter_button = P... | [
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c2ddf31bce4a5f3ae2b0d5455bbc9942f92bff40 | import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
from keras.models import load_model
from utils import resize_to_fit, clear_chunks, stack_windows
from imutils import paths
import numpy as np
import imutils
import cv2 as cv2
import pickle
from tqdm import tqdm
c1_correct = 0
c2_correct = 0
c3_correct = 0
c4_correct... | [
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75e6554ea3c327c87a2a65710a7f1d55e9933bb0 | # Author: BeiYu
# Github: https://github.com/beiyuouo
# Date : 2021/2/21 21:57
# Description:
__author__ = "BeiYu"
from utils.init_env import set_seed
from utils.options import *
import os
import logging
import torch
from torch import nn
from torch import optim
from torch.optim.lr_scheduler import MultiStepLR
from ... | [
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58f3b8c5470c765c81f27d39d9c28751a8c2b719 | """Ex026 Faça um programa que leia uma frase pelo teclado e mostre:
Quantas vezes aparece a letra "A".
Em que posição ela aparece a primeira vez.
Em que posição ela aparece pela última vez."""
frase = str(input("Digite uma frase: ")).strip().lower()
n_a = frase.count("a")
f_a = frase.find("a") + 1
l_a = frase.rfind("a... | [
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d83f2d9bb25a46bc7344b420ce65bf729165e6b9 | from django.apps import AppConfig
class FosAppConfig(AppConfig):
name = "fos_app"
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d2b05c5653ca6c6b7219f6c0393e81c9425b5977 | """
HLS: Check if Twin Granule Exists
"""
from typing import Dict
import os
import re
import boto3
from botocore.errorfactory import ClientError
from datetime import date
s3 = boto3.client("s3")
bucket = os.getenv("SENTINEL_INPUT_BUCKET", None)
print(bucket)
if bucket is None:
raise Exception("No Input Bucket set... | [
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c73a199d1c1c1867f3d53ceebf614bc9b65c0d5e | from django.contrib import admin
from ticket.models import Ticket, UserTicket, AuxiliaryTicket
@admin.register(Ticket)
class TicketAdmin(admin.ModelAdmin):
pass
@admin.register(AuxiliaryTicket)
class AuxiliaryTicketAdmin(admin.ModelAdmin):
pass
@admin.register(UserTicket)
class UserTicketAdmin(admin.Mode... | [
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e564e0d05c3c0e60f356422722803df510d9dd0b | import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.metrics import precision_score, recall_score, f1_score
from scipy.optimize import fsolve
import numba
from numba import njit, jit
#
@jit(parallel=True)
def conventional_te... | [
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9bc13c608c079cbf23ed04f29edd1fd836214cde | from rest_framework import viewsets, mixins
from .models import Comment, Post
from .serializer import CommentSerializer, PostSerializer, AllCommentSerializer
class PostViewSet(viewsets.ModelViewSet):
serializer_class = PostSerializer
queryset = Post.objects.all()
class CommentViewSet(viewsets.GenericViewSet... | [
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b11e2837d3ba9c14770b8039186a2175adc41ea1 | from .server import CanvasServer
try:
from .jupyter import JupyterCanvas, create_jupyter_canvas
HAS_JUPYTER = True
except:
HAS_JUPYTER = False
JupyterCanvas = None # type: ignore
def http_server(file: str = None, host: str = "localhost", port: int = 5050) -> CanvasServer:
"""Creates a new HTTP ... | [
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2da7892722afde5a6f87e3bd6d5763c895ac96c9 | import json
import os
import ipdb
from tqdm import tqdm
import argparse
from os import listdir
from os.path import isfile, join
import pickle
import joblib
from collections import Counter
from shutil import copyfile
import networkx as nx
import spacy
import nltk
import numpy as np
nltk.download("stopwords")
nltk_stopw... | [
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e38ae7f91deed1be00e60b7516210ea1feefe23e | import sys
import os
from configparser import ConfigParser
import logging
from mod_argparse import setup_cli
from checkers.IndexFile import DocumentIndex, ProgressNoteIndex
from checkers import source_files
from utilities import write_to_file, strip # , write_to_db_isok
# import pandas as pd
logger = logging.getLogge... | [
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069338b188f3cf16357b2502cbb3130b69918bd9 | from .cli import cli
if __name__ == "__main__":
exit(cli.main(prog_name="htmap"))
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8c539dbbb762717393b9a71ddca8eb3872890854 | import re
import os
import pandas as pd
instruments_file = os.path.abspath("instruments.csv")
input_names_file = os.path.abspath("names.txt")
output_names_file = os.path.abspath("names.csv")
inst_name_file = os.path.abspath("name_instrument.csv")
reg_ex = "; |, |\\*|\n"
name_header = ["first_name", "last_name"]
def ... | [
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0db0daf9bea254cffaec1280cd13b2d70368cd94 | import numpy.random as rnd
import numpy as np
B = 100000
N1 = 50
N2 = 50
p1mle = 0.3
p2mle = 0.4
taumle = p2mle - p1mle
estimate = []
for i in range(B):
p1 = 0.0
for j in range(N1):
if rnd.uniform(0, 1) < p1mle:
p1 += 1
p1 /= N1
p2 = 0.0
for j in range(N2):
if rnd.u... | [
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a90b7e44cc54d4f96a13e5e6e2d15b632d3c4983 | import random
import string
import steembase
import struct
import steem
from time import sleep
from time import time
from steem.transactionbuilder import TransactionBuilder
from steembase import operations
from steembase.transactions import SignedTransaction
from resultthread import MyThread
from charm.toolbox.pairingg... | [
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ee80169afd4741854eff8619822a857bbf757575 | """
Created on 27 Mar 2015
@author: Jon
"""
import matplotlib.pyplot as plt
from numerical_functions import Timer
import numerical_functions.numba_funcs.indexing as indexing
import numpy as np
import unittest
class Test(unittest.TestCase):
def test_take(self):
x = np.linspace(0, 100)
idx = np.ra... | [
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ce6dba2f682b091249f3bbf362bead4b95fee1f4 | """
.. currentmodule:: jotting
.. automodule:: jotting.book
:members:
.. automodule:: jotting.to
:members:
.. automodule:: jotting.read
:members:
.. automodule:: jotting.style
:members:
"""
from .book import book
from . import style, to, read, dist
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bf8bbeb408cb75af314ef9f3907456036e731c0b | def solution(S):
# write your code in Python 3.6
# Definitions
log_sep = ","
num_sep = "-"
time_sep = ":"
# Initialization
from collections import defaultdict
# defaultdict initialize missing key to default value -> 0
bill = defaultdict(int)
total = defaultdict(int)
calls = ... | [
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... |
35ae9c86594b50bbe4a67d2cc6b20efc6f6fdc64 | # 配置我们文件所在目录的搜寻环境
import os, sys
# 第一步先拿到当前文件的路径
file_path = os.path.abspath(__file__)
# 第二步 根据这个路径去拿到这个文件所在目录的路径
dir_path = os.path.dirname(file_path)
# 第三步:讲这个目录的路径添加到我们的搜寻环境当中
sys.path.append(dir_path)
# 第四步,动态设置我们的setting文件
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "gulishop.settings")
# 第五步,让设置好的环境初始化生效
imp... | [
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"#",
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... |
d34159536e860719094a36cfc30ffb5fcae72a9a | # API End Points by Mitul
import urllib.error, urllib.request, urllib.parse
import json
target = "http://py4e-data.dr-chuck.net/json?"
local = input("Enter location: ")
url = target + urllib.parse.urlencode({"address": local, "key": 42})
print("Retriving", url)
data = urllib.request.urlopen(url).read()
print("Retrive... | [
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c382b298cce8d7045d6ce8a84f90b3800dba7717 | # Generated by Django 3.0.7 on 2020-06-15 15:26
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("products", "0003_auto_20200615_1225"),
]
operations = [
migrations.AlterField(
model_name="product",
name="harmonizac... | [
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3372d98ff91d90558a87293d4032820b1662d60b | from django.conf.urls import patterns, url
from riskDashboard2 import views
urlpatterns = patterns(
"",
# url(r'getdata', views.vulnData, name='getdata'),
url(r"appmanagement", views.appmanagement, name="appmanagement"),
url(r"^.*", views.index, name="index"),
)
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0465e33d65c2ce47ebffeec38db6908826bf4934 | people = 20
cats = 30
dogs = 15
if people < cats:
print("Too many cats")
elif people > cats:
print("Not many cats")
else:
print("we cannnot decide")
| [
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5ddfeb49c16a7452c99126f1a837f3c0bed0ec10 | import requests
from urllib.parse import urlparse
from bs4 import BeautifulSoup
import re
import datetime
import random
pages = set()
# Retrieve a list of all Internal links foound on a page.
def getInternalLinks(bs, includeUrl):
includeUrl = f"{urlparse(includeUrl).scheme}://{urlparse(includeUrl).netloc}"
i... | [
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1e1f918ba24f5a5f13b9b01289ebfda65bae572d | def warshall_floyd(N):
INF = 10**20
path = [[INF for _ in range(N + 1)] for _ in range(N + 1)]
graph = get_graph()
for i in range(N + 1):
path[i][i] = 0
for g in graph:
x = g[0]
y = g[1]
l = g[2]
path[x][y] = path[y][x] = l
for start in range(N + 1):
... | [
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04538cc5c9c68582cc9aa2959faae2d7547ab2ee | try:
import xml.etree.cElementTree as ET
except ImportError:
import xml.etree.ElementTree as ET
import data_helpers
def write_to_file(file, line):
file.write(line + "\n")
def cat_map():
catmap = {}
id = 1
f = open("cat")
cat = set([s.strip() for s in list(f.readlines())])
for i in ca... | [
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631323e79f4fb32611d7094af92cff8f923fa996 | #!/bin/python3
def word_ladder(start_word, end_word, dictionary_file="words5.dict"):
"""
Returns a list satisfying the following properties:
1. the first element is `start_word`
2. the last element is `end_word`
3. elements at index i and i+1 are `_adjacent`
4. all elements are entries in the... | [
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0a528fb7fe4a318af8bd3111e8d67f6af6bd7416 | from typing import Tuple
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def lcaDeepestLeaves(self, root: TreeNode) -> TreeNode:
_, lca = self.get_lca(root, 0)
return lca
def get_lca(self, node: TreeNode, dep... | [
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371762a6e3f8b8ed14742a70a709da224ae6712b | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import random
"""
检查图数据和结构或者链表数据结构中是否存在环
https://www.youtube.com/watch?v=YKE4Vd1ysPI
"""
def get_all_edge(graph):
result = []
for k, v in graph.items():
for i in v:
if sorted((k, i)) not in result:
result.append(sorted((k, ... | [
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7f7ebc6d3d69fbb19071c63a9ab235ad01f1d414 | import sys
sys.path.append("..")
import helpers
helpers.mask_busy_gpus(wait=False)
import nltk
import numpy as np
nltk.download("brown")
nltk.download("universal_tagset")
data = nltk.corpus.brown.tagged_sents(tagset="universal")
all_tags = ["#EOS#", "#UNK#", "ADV", "NOUN", "ADP", "PRON", "DET", ".", "PRT", "VERB"... | [
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8698aedc5c8671f46c73898a7188440254b79bbf | from abc import abstractmethod
class Environment:
@abstractmethod
def __init__(self, agent):
pass
@abstractmethod
def execute_step(self, n=1):
pass
@abstractmethod
def execute_all(self):
pass
@abstractmethod
def set_delay(self, delay):
pass
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1be510e6715d21e814c48fe05496704e9a65d554 | from end import Client
c = Client()
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6b727cdfc684db4ba919cd5390fe45de43a806fe | import glob
import xarray as xr
from model_diagnostics import *
data_root = "../data/synthetic/standard/"
var_list = ["hs", "dp", "spr", "fp", "dir", "t0m1"]
eke = 0.01
##########################
output = []
diagnostic_functions = [basic_stats]
for var in var_list:
grid_files = glob.glob(data_root + "gridded/*%s*... | [
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c66f4ee5719f764c8c713c23815302c00b6fb9af | import os
from cs50 import SQL
from flask import Flask, flash, redirect, render_template, request, session
from flask_session import Session
from tempfile import mkdtemp
from werkzeug.exceptions import default_exceptions, HTTPException, InternalServerError
from werkzeug.security import check_password_hash, generate_pa... | [
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097a87f7f1346e5db1599e59680232912348aef7 | # -*- coding:utf-8 -*-
from odoo import api, models, fields, _
class hrsalaryRule(models.Model):
_inherit = "hr.salary.rule"
is_tax_fdfp = fields.Boolean("Est un impôt FDFP")
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a126b1775ffe1ba1aebc288ce17fac8ada0b0756 | import cv2
import numpy as np
import pandas as pd
import tkinter as tk
import random
from tkinter import *
from tkinter import ttk
from tkinter import messagebox
from tkinter import Scale, Tk
from tkinter.ttk import Notebook
refPt = []
PtBGR = []
r = []
g = []
b = []
refPt = []
Serial = []
PtBGR = []
r1 = []
r2 = []
r... | [
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dca36de5556b120b8b93eac0ad7b971ad735d907 | import numpy as np
def GradientDescent(f, gradf, x0, epsilon, num_iter, line_search, disp=False, callback=None, **kwargs):
x = x0.copy()
iteration = 0
opt_arg = {"f": f, "grad_f": gradf}
for key in kwargs:
opt_arg[key] = kwargs[key]
while True:
gradient = -gradf(x)
alpha = ... | [
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4711adcc7c95993ec13b9d06fa674aa064f79bfd | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(torch.nn.Module):
def __init__(self, layer_sizes=[256, 128, 2], dropout_prob=None, device=None):
super(Net, self).__init__()
self.device = device
if dropout_prob is not None and dropout_prob > 0.5:
pr... | [
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3479276d4769518aa60dcd4e1bb41a8a1a7d6517 | import os
from multiprocessing import Pool
import glob
import click
import logging
import pandas as pd
from src.resampling.resampling import Resampler
# Default paths
path_in = "data/hecktor_nii/"
path_out = "data/resampled/"
path_bb = "data/bbox.csv"
@click.command()
@click.argument("input_folder", type=click.Pat... | [
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d5beff74e3746c77cbaf6b8233b822ed1a86701e | # Generated by Django 2.2.2 on 2021-01-23 04:11
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("task", "0022_taskrecycle_create_date"),
]
operations = [
migrations.RemoveField(
model_name="ansibleextravars",
name="playboo... | [
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77763f501c6776969d2594f987e5d7ab7d4377fb | import time
from PyQt5.QtCore import (
QThread,
)
from common import attach_common
from database_downloader import DatabaseDownload
from ai_list_memorize import MemorizeList
from ai_list_morpheme import MorphemeList
from ai_list_ngram import NgramList
from ai_list_none import NoneList
from ai_bot_memorize import Me... | [
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d6a760774b45454c959c2932d7b28deee7f81872 | # SPDX-License-Identifier: Apache-2.0
# Licensed to the Ed-Fi Alliance under one or more agreements.
# The Ed-Fi Alliance licenses this file to you under the Apache License, Version 2.0.
# See the LICENSE and NOTICES files in the project root for more information.
import json
from typing import Dict
from pandas import... | [
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bd3b1263d7d657fe2edd3c7198f63821a3d1d1e5 | import random
from . import WaiterInterface
class RandomIPv4Waiter(WaiterInterface):
"""
HostPortWaiter which generates random ipv4 adresses
"""
def __init__(self, options):
self.ports = options["ports"]
self.limit_generate = options.get("limit_generate", -1)
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d2c31d9c3cc66b43966cfd852582539d4e4bea17 | from selenium import webdriver
import time
import datetime
import os
import openpyxl as vb
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.common.action_chains import ActionChains
def deconnexion(Chrome):
"""登陆"""
"""初始化"""
global web, actions
web = webdriver.Chrome(C... | [
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213ab22a269abc8180524462a8966e5d929ef7d1 | import os
import json
import codecs
import markdown
from flask import current_app
def get_json_file(filename, lang="en"):
"""
Get the contents of a JSON file.
"""
filepath = os.path.join(current_app.config["APP_PATH"], "data", filename)
with open(filepath, "r") as f:
return json.loads(... | [
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398263b65fd98003f27020e46ae38e913dc5dd45 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "Brice Chou"
import os
import lib
import sys
import time
import getopt
import training
try:
import cv2
import h5py
except Exception as e:
error_info = "Please install h5py/cv2 tools first. Error: {}.\n".format(e)
print("\033[0;31m%s\033[0m" ... | [
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86ca94820c05b3f63f4a733b6d1fa7eb9dea6a5d | # generated from catkin/cmake/template/order_packages.context.py.in
source_root_dir = "/home/songsong/image_transport_ws/src"
whitelisted_packages = "".split(";") if "" != "" else []
blacklisted_packages = "".split(";") if "" != "" else []
underlay_workspaces = (
"/home/songsong/image_transport_ws/devel;/home/songs... | [
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1f27b697985c7417e6d8d978703175a415c6c57d | import math
r = float(input())
p = int(input())
obim = 2 * r * math.pi
ukupanPut = p * obim
# centimetre pretvaramo u metre
ukupanPut = ukupanPut * 0.01
print("%.2f" % ukupanPut)
| [
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71a9c9b8f47dcfbecc154c44d5a72ddbd852145a | def randomizer(n, garrafa_vidro, lata_metal, copo_plastico, bola_papel, maça_organico):
lixos = [garrafa_vidro, lata_metal, copo_plastico, bola_papel, maça_organico]
return lixos[n]
| [
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02e711dfc122007c74949cd9f86e2aeb9d334871 | import numpy as np
class Adaline:
def __init__(self, eta=0.0001, n_iter=2000):
self.eta = eta
self.n_iter = n_iter
self.error = []
def fit(self, X, Y):
X = np.hstack((np.ones((X.shape[0], 1)), X))
self.w = np.random.uniform(-1, 1, (X.shape[1], 1))
for n in rang... | [
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6bf1d410a33e3b2535e39e4f8c5c7f8278b3de67 | from PIL import Image
from src import urbandictionary_api
from src.card.cardDrawer import CardDrawer
from src.card.cardModel import CardModel
from src.repository import Repository
from src.urbandictionary_api import get_random_word
def save_card(word, image_path, filepath="data/cards/", filename=None):
"""Функци... | [
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a096e811e50e25e47a9b76b1f813c51f4307bbfe | import django_filters
from .models import Drinks, Brand
class DrinkFilter(django_filters.FilterSet):
BRAND_CHOICES = tuple((brand.name, brand.name) for brand in Brand.objects.all())
name = django_filters.CharFilter(lookup_expr="icontains")
price_lt = django_filters.NumberFilter(field_name="price", lookup_... | [
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3ea42e7ad5301314a39bf522280c084342cd18c5 | from flask import render_template, request, Response
from flask.views import MethodView, View
from flask.views import View
from repo import ClassifierRepo
from services import PredictDigitService
from settings import CLASSIFIER_STORAGE
class IndexView(View):
def dispatch_request(self):
return render_tem... | [
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0c97569c77fb3598d83eba607960328bb2134dd2 | from __future__ import print_function, division
import os
from os.path import exists, join, basename, dirname
from os import makedirs
import numpy as np
import datetime
import time
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
from lib.dataloader import DataLoader
from lib.im_pair_dat... | [
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a65dfca1773c1e4101ebfb953e0f617a2c345695 | def merge(self, intervals):
intervals.sort()
arr = []
for i in intervals:
if len(arr) == 0 or arr[-1][1] < i[0]:
arr.append(i)
else:
arr[-1][1] = max(arr[-1][1], i[1])
return arr
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49005500b299ca276f663fe8431bb955e5585bbd | import Net
import mnist_parser
import numpy as np
# To use this model it is required to download the MNIST database
# The donwloaded base is then needet parse to numpy using mnist_parser.parse_to_npy method
# The files genetared using mnist_parser.parse_to_npy are then loaded using np.load
in_values = np.load("MNIST/m... | [
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219929d52b5f1a0690590e83b41d2b4f0b2b3a51 | list = [3, 1, 2, 5, 4, 7, 6]
def sort(list):
for i in range(len(list) - 1):
if list[i] > list[i + 1]:
a = list[i]
list[i] = list[i + 1]
list[i + 1] = a
print(list)
sort(list)
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e884ce5878de75afe93085e2310b4b8d5953963a | """
Created on 13 Dec 2016
@author: hpcosta
"""
# https://www.hackerrank.com/challenges/backreferences-to-failed-groups
regex = r"^\d{2}(-?)\d{2}\1\d{2}\1\d{2}$" # Do not delete 'r'.
import re
print(str(bool(re.search(regex, raw_input()))).lower())
# Task
#
# You have a test string S.
# Your task is to write a r... | [
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302accfd5001a27c7bbe6081856d43dbec704168 | import asyncio
import logging
import random
from aiogram.dispatcher import FSMContext
from aiogram.types import ContentTypes, Message, CallbackQuery
from aiogram.utils.exceptions import BotBlocked
import keyboards
from data.config import ADMINS, ADMIN_CHAT_ID
from keyboards.inline.activate_menu import active_menu_cal... | [
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33,
35,
42,
1,
5,
9,
13,
14,
19,
26,
34,
39,
40,
48,
49,
58,
63,
1,
5,
9,
13,
14,
19,
20,
30,
37,
41,
48,
1,
1,
7,
16,
17,
1,
5,
10,
11,
17,
24,
3... |
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