text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>IT',
url = 'https://github.com/muntashir/taskrelay',
author = 'https://github.com/muntashir',
packages = [''],
install_requires = ['websockets']
)<|fim_prefix|># repo: muntashir/taskrelay path: /python/setup.py
from setuptools import setup
setup(
name = 'taskrelay',
version = '0.... | code_fim | medium | {
"lang": "python",
"repo": "muntashir/taskrelay",
"path": "/python/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muntashir/taskrelay path: /python/setup.py
from setuptools import setup
setup(
name = 'taskrelay',
version = '0.1.0<|fim_suffix|>thub.com/muntashir',
packages = [''],
install_requires = ['websockets']
)<|fim_middle|>',
description = 'A library to run tasks on remote servers',... | code_fim | medium | {
"lang": "python",
"repo": "muntashir/taskrelay",
"path": "/python/setup.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Check for our .git/packed-refs' file since a `git gc` may have run
# https://git-scm.com/book/en/v2/Git-Internals-Maintenance-and-Data-Recovery
packed_file = os.path.join(path, ".git", "packed-refs")
if os.path.exists(packed_file):
with open(packed_file) as fh... | code_fim | hard | {
"lang": "python",
"repo": "SpongePowered/SpongeAuth",
"path": "/spongeauth/spongeauth/settings/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if head.startswith("ref: "):
head = head[5:]
revision_file = os.path.join(path, ".git", *head.split("/"))
else:
return head
else:
revision_file = os.path.join(path, ".git", "refs", "heads", head)
if not os.path.exists(revision_file):
... | code_fim | hard | {
"lang": "python",
"repo": "SpongePowered/SpongeAuth",
"path": "/spongeauth/spongeauth/settings/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SpongePowered/SpongeAuth path: /spongeauth/spongeauth/settings/utils.py
"""
Copyright (c) 2015 Functional Software, Inc and individual contributors.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following con... | code_fim | hard | {
"lang": "python",
"repo": "SpongePowered/SpongeAuth",
"path": "/spongeauth/spongeauth/settings/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MihneaS/ckanext-inventory path: /ckanext/inventory/controllers/inventory_entry.py
import unicodecsv
from cStringIO import StringIO
from ckan.plugins.toolkit import (
c, check_access, NotAuthorized, abort, get_action, render, request,
redirect_to, _, response)
from ckan import model
from... | code_fim | hard | {
"lang": "python",
"repo": "MihneaS/ckanext-inventory",
"path": "/ckanext/inventory/controllers/inventory_entry.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return render('inventory/entry/edit.html')
def read(self, organization_name, inventory_entry_id):
context = {'model': model,
'session': model.Session,
'user': c.user or c.author}
c.entries = get_action('inventory_entry_list_items')(
... | code_fim | hard | {
"lang": "python",
"repo": "MihneaS/ckanext-inventory",
"path": "/ckanext/inventory/controllers/inventory_entry.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ### Custom methods
def is_live(self, obj):
"""
This shows WHICH object will be the live object.
Returns True/False.
This is used in the default list_display.
"""
most_appropriate_object = get_appropriate_object_from_model(self.model)
... | code_fim | hard | {
"lang": "python",
"repo": "WGBH/django-model-gatekeeper",
"path": "/gatekeeper/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WGBH/django-model-gatekeeper path: /gatekeeper/admin.py
from django.contrib import admin
from django.utils.safestring import mark_safe
import pytz
from datetime import datetime
from .utils import get_appropriate_object_from_model
def is_in_the_future(dt):
"""
Is this (UTC) date/time valu... | code_fim | hard | {
"lang": "python",
"repo": "WGBH/django-model-gatekeeper",
"path": "/gatekeeper/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # then find end
nEndOfSilence = nNumFirstSample*self.nNbrChannel # init of the loop
while( nEndOfSilence < len(self.data) ):
#nFirstSilenceIndex = np.argmax( np.abs(self.data[nEndOfSilence:])<=nLimit )
nFirstSilenceIndex = findFirstFalseV... | code_fim | hard | {
"lang": "python",
"repo": "laboratoriumDIBRIS/caresses-opensource",
"path": "/CAHRIM/ActionsLib/NAOqi_apps/asr2/lib/abcdk/sound/wav.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: laboratoriumDIBRIS/caresses-opensource path: /CAHRIM/ActionsLib/NAOqi_apps/asr2/lib/abcdk/sound/wav.py
e.write( struct.pack( "I", 16 ) )
file.write( struct.pack( "h", 1) ) # self.nWaveTypeFormat
file.write( struct.pack( "h", self.nNbrChannel) )
file.write( struct.pack( "i"... | code_fim | hard | {
"lang": "python",
"repo": "laboratoriumDIBRIS/caresses-opensource",
"path": "/CAHRIM/ActionsLib/NAOqi_apps/asr2/lib/abcdk/sound/wav.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LeoWshington/Exercicios_CursoEmVideo_Python path: /ex081.py
valores = list()
cont = 0
while True:
n = float(input('Digite um valor: '))
valores.append(n)
op = str(input('Deseja continuar [S/N]? ')).strip()[0]
cont += 1
if op in 'Nn':
break
print(f'{"~" * 30}')
valo... | code_fim | medium | {
"lang": "python",
"repo": "LeoWshington/Exercicios_CursoEmVideo_Python",
"path": "/ex081.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ')
print('O numero 5 aparece na(s) ', end='')
for pos, v in enumerate(valores):
if v == 5:
print(f'{pos + 1}ª ', end='')
print(' posição(es).')<|fim_prefix|># repo: LeoWshington/Exercicios_CursoEmVideo_Python path: /ex081.py
valores = list()
cont = 0
while True:
n = float(input('Digite ... | code_fim | medium | {
"lang": "python",
"repo": "LeoWshington/Exercicios_CursoEmVideo_Python",
"path": "/ex081.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def set_all_data(self):
self.get_name()
self.get_id()
self.get_description()
self.get_class()
self.get_exits()
self.get_attributes()
#simple test to verify working so far
if __name__ == '__main__':
from xmlroom import room_xml_pa... | code_fim | hard | {
"lang": "python",
"repo": "tehologist/x-venture",
"path": "/old/lib/xmlroom.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tehologist/x-venture path: /old/lib/xmlroom.py
from xml.dom import minidom
"""This is parser, which parses XML room files and returns data to create classes
for use within the mud."""
class room_xml_parse:
def __init__(self, dom):
self.name = ""
self.id = 0
self.descri... | code_fim | hard | {
"lang": "python",
"repo": "tehologist/x-venture",
"path": "/old/lib/xmlroom.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_attributes(self):
try:
var = self.dom.getElementsByTagName("attributes")[0]
except IndexError:
return 0
var = var.getElementsByTagName("label")
var2 = {}
for elements in var:
for items in elements.childNodes:
... | code_fim | hard | {
"lang": "python",
"repo": "tehologist/x-venture",
"path": "/old/lib/xmlroom.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_poem.py
#calss header
class _POEM():
def __init__(self,):
<|fim_suffix|> self.specie = 'nouns'
def run(self, obj1 = [], obj2 = []):
return self.jsondata<|fim_middle|> self.name = "POEM"
self.definitions = [u'a piece of writing in which th... | code_fim | hard | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_poem.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Mahedros/jbc path: /block.py
import hashlib
import os
import json
import utils
from config import *
class Block(object):
def __init__(self, dictionary):
'''
We're looking for index, timestamp, data, prev_hash, nonce
'''
for key, value in dictionary.items()... | code_fim | hard | {
"lang": "python",
"repo": "Mahedros/jbc",
"path": "/block.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def to_dict(self):
info = {}
info['index'] = str(self.index)
info['timestamp'] = str(self.timestamp)
info['prev_hash'] = str(self.prev_hash)
info['hash'] = str(self.hash)
info['data'] = str(self.data).replace("'", '"')
info['nonce'] = str(self.no... | code_fim | hard | {
"lang": "python",
"repo": "Mahedros/jbc",
"path": "/block.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.Height=self.Length=self.Width=0
print("Please set the values of Height, Width, and Length for Prism", self.Id)
print("No value can not be under 1.")
while self.Height < 1:
self.Height=int(input("Height: "))
if self.Height < 1:
pr... | code_fim | hard | {
"lang": "python",
"repo": "ThomasMorrissey/Chapter_8_Supp",
"path": "/Challenge_2.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ThomasMorrissey/Chapter_8_Supp path: /Challenge_2.py
#! usr/bin/python3
# Program Name: Challenge_2.py
# Author: Thomas Morrissey
# Date Written: 2-18-2015
# Pusedocode:
# This challenge is about creating three different prisms and adding attributes for each prism.
# I accomplished this by cr... | code_fim | hard | {
"lang": "python",
"repo": "ThomasMorrissey/Chapter_8_Supp",
"path": "/Challenge_2.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> Prism0=Prism(0)
Prism1=Prism(1)
Prism2=Prism(2)
print("Welcome to Challenge_2.py!")
print("The goal of this program is to create three different prisms with the following parimeters: width, length, height, volume, perimter, and surface area.")
Prism0.GetLengthHeightWidth()
Pris... | code_fim | hard | {
"lang": "python",
"repo": "ThomasMorrissey/Chapter_8_Supp",
"path": "/Challenge_2.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.asyncio
@pytest.mark.usefixtures('ignore_unawaited_request')
async def test_twitter_req_to_http_req_post():
tr = TwitterRequest("POST", "http://url.com/", "service", "family")
async with aiohttp.ClientSession() as session:
req = twitter_req_to_http_req(session, app_cred, clien... | code_fim | hard | {
"lang": "python",
"repo": "jbn/brittle_wit",
"path": "/tests/unit_tests/executors/test_twitter_req_to_http_req.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jbn/brittle_wit path: /tests/unit_tests/executors/test_twitter_req_to_http_req.py
import aiohttp
import pytest
from brittle_wit_core import TwitterRequest, AppCredentials, ClientCredentials
from brittle_wit.executors import twitter_req_to_http_req
from tests.helpers import *
<|fim_suffix|>
# --... | code_fim | medium | {
"lang": "python",
"repo": "jbn/brittle_wit",
"path": "/tests/unit_tests/executors/test_twitter_req_to_http_req.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RxJellyBot/Jelly-Bot path: /tests/unit/game_pkchess/character/obj.py
from game.pkchess.character import Character
from game.pkchess.utils.character import get_character_template
from tests.base import TestCase
<|fim_suffix|> self.assertEqual(chara.template, template)
self.assertEq... | code_fim | medium | {
"lang": "python",
"repo": "RxJellyBot/Jelly-Bot",
"path": "/tests/unit/game_pkchess/character/obj.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class TestCharacter(TestCase):
def test_character_from_template(self):
template = get_character_template("Nearnox")
chara = Character(template)
self.assertEqual(chara.template, template)
self.assertEqual(chara.name, template.name)
self.assertEqual(chara.HP, t... | code_fim | medium | {
"lang": "python",
"repo": "RxJellyBot/Jelly-Bot",
"path": "/tests/unit/game_pkchess/character/obj.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_convert_data_to_klass_instances(self):
self.assertIsInstance(self.apilist[0], rainforest.apibits.ApiResource)
self.assertEqual(self.fake_resource, self.apilist[0].json)<|fim_prefix|># repo: rainforestapp/rainforest-python path: /rainforest/test/test_api_list.py
import rainfor... | code_fim | hard | {
"lang": "python",
"repo": "rainforestapp/rainforest-python",
"path": "/rainforest/test/test_api_list.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rainforestapp/rainforest-python path: /rainforest/test/test_api_list.py
import rainforest
import unittest
class TestApiList(unittest.TestCase):
def setUp(self):
<|fim_suffix|> def test_convert_data_to_klass_instances(self):
self.assertIsInstance(self.apilist[0], rainforest.apibits... | code_fim | hard | {
"lang": "python",
"repo": "rainforestapp/rainforest-python",
"path": "/rainforest/test/test_api_list.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wuxiuzhi738/openspeech path: /openspeech/modules/additive_attention.py
# MIT License
#
# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Soft... | code_fim | hard | {
"lang": "python",
"repo": "wuxiuzhi738/openspeech",
"path": "/openspeech/modules/additive_attention.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
dim (int): dimension of model
Inputs: query, key, value
- **query** (batch_size, q_len, hidden_dim): tensor containing the output features from the decoders.
- **key** (batch, k_len, d_model): tensor containing projection vector for encoders.
- **value** (bat... | code_fim | hard | {
"lang": "python",
"repo": "wuxiuzhi738/openspeech",
"path": "/openspeech/modules/additive_attention.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: barberscore/barberscore-api path: /project/apps/adjudication/migrations/0025_outcome_printed.py
# Generated by Django 2.2.27 on 2022-05-30 22:19
from django.db import migrations, models
<|fim_suffix|> dependencies = [
('adjudication', '0024_auto_20220530_1454'),
]
operation... | code_fim | easy | {
"lang": "python",
"repo": "barberscore/barberscore-api",
"path": "/project/apps/adjudication/migrations/0025_outcome_printed.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='outcome',
name='printed',
field=models.BooleanField(default=True, help_text='\n Show this outcome on the OSS.'),
),
]<|fim_prefix|># repo: barberscore/barberscore-api path: /project/apps... | code_fim | medium | {
"lang": "python",
"repo": "barberscore/barberscore-api",
"path": "/project/apps/adjudication/migrations/0025_outcome_printed.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
NewNode tests behavior of lndmanage under a blank new node without any
channels.
"""
network_definition = test_graphs_paths['empty_graph']
def graph_test(self):
self.assertEqual(0, len(self.master_node_graph_view))
def test_empty(self):
# LND interface of ... | code_fim | medium | {
"lang": "python",
"repo": "bitromortac/lndmanage",
"path": "/test/test_lndmanage.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bitromortac/lndmanage path: /test/test_lndmanage.py
""" Integration tests for lndmanage."""
import asyncio
from test.testing_common import test_graphs_paths, TestNetwork
class NewNode(TestNetwork):
"""
NewNode tests behavior of lndmanage under a blank new node without any
channels.... | code_fim | medium | {
"lang": "python",
"repo": "bitromortac/lndmanage",
"path": "/test/test_lndmanage.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stdiorion/competitive-programming path: /contests_atcoder/abc159/abc159_f.py
from collections import defaultdict
MOD = 998244353
n, s = map(int, input().split())
a = list(map(int, input().split()))
for <|fim_suffix|> dp[l][a[l]] = 1
for i in range(l + 1, n):
dp[i][]<|fim_middle|>l i... | code_fim | medium | {
"lang": "python",
"repo": "stdiorion/competitive-programming",
"path": "/contests_atcoder/abc159/abc159_f.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> dp[l][a[l]] = 1
for i in range(l + 1, n):
dp[i][]<|fim_prefix|># repo: stdiorion/competitive-programming path: /contests_atcoder/abc159/abc159_f.py
from collections import defaultdict
MOD = 998244353
n, s = map(int, input().split())
a = list(map(int, input().split()))
for <|fim_middle|>l i... | code_fim | medium | {
"lang": "python",
"repo": "stdiorion/competitive-programming",
"path": "/contests_atcoder/abc159/abc159_f.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DBXhhh/VGCN-PyTorch path: /main.py
import os
import time
import argparse
import torch
import math
import numpy as np
import cv2
import torch.optim as optim
import torch.optim.lr_scheduler as LS
from torch.autograd import Variable
from torchvision import models
import scipy.io as scio
from scipy i... | code_fim | hard | {
"lang": "python",
"repo": "DBXhhh/VGCN-PyTorch",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def train(epoch, iteration):
model.train()
# scheduler.step()
end = time.time()
log = [0 for _ in range(1)]
for batch_idx, batch in enumerate(train_loader):
data, label, _, A, wimg = batch
data = Variable(data.cuda())
label = Variable(label.cuda())
A = ... | code_fim | hard | {
"lang": "python",
"repo": "DBXhhh/VGCN-PyTorch",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
model.eval()
log = 0
score_list = []
label_list = []
name_list = []
for batch_idx, batch in enumerate(test_loader):
data, label, imgname, A, wimg = batch
data = Variable(data.cuda())
label = Variable(label.cuda())
A = Variable(A.cuda())
wim... | code_fim | hard | {
"lang": "python",
"repo": "DBXhhh/VGCN-PyTorch",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #-----------------------------------------------------
#PLOT DATA SAMPLES
#-----------------------------------------------------
title = ""
x_title = "Longitude"
y_title = "Latitude"
x_axis = lon_list
y_axis = lat_list
color_list = color_list
filename = "doc/visualization/plot.png"
fig = plt.f... | code_fim | hard | {
"lang": "python",
"repo": "urbanoanderson/ufpe-graduation-thesis",
"path": "/src/thesis/experiments/visualization.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: urbanoanderson/ufpe-graduation-thesis path: /src/thesis/experiments/visualization.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
import sys
import argparse
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
#Custom Classes
sys.dont_write_bytecode = True
from modules.erb ... | code_fim | hard | {
"lang": "python",
"repo": "urbanoanderson/ufpe-graduation-thesis",
"path": "/src/thesis/experiments/visualization.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> user_defined_parameters = {
"base_reward": base_reward,
"min_other_merchants": min_other_merchants,
"token": "0x999999cf1046e68e36E1aA2E0E07105eDDD1f08E",
"duration": 43200,
}
return user_defined_parameters<|fim_prefix|># repo: cardstack/cardstack path: /packag... | code_fim | hard | {
"lang": "python",
"repo": "cardstack/cardstack",
"path": "/packages/cardpay-reward-programs/streamlit/views/min_other_merchants_paid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_user_defined_parameters():
s = st.expander(label="User defined parameters", expanded=True)
min_other_merchants = s.number_input(
"Min Other Merchants", value=1, step=1, min_value=0, max_value=20
)
base_reward = s.number_input(
"Base reward", value=5, step=1, min_val... | code_fim | medium | {
"lang": "python",
"repo": "cardstack/cardstack",
"path": "/packages/cardpay-reward-programs/streamlit/views/min_other_merchants_paid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cardstack/cardstack path: /packages/cardpay-reward-programs/streamlit/views/min_other_merchants_paid.py
import streamlit as st
from cardpay_reward_programs.rules import MinOtherMerchantsPaid
def get_rule_class():
<|fim_suffix|> user_defined_parameters = {
"base_reward": base_reward,
... | code_fim | hard | {
"lang": "python",
"repo": "cardstack/cardstack",
"path": "/packages/cardpay-reward-programs/streamlit/views/min_other_merchants_paid.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Azure/azure-cli path: /src/azure-cli/azure/cli/command_modules/appservice/_github_oauth.py
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt i... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/appservice/_github_oauth.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def load_github_token_from_cache(cmd, repo):
repo = repo_url_to_name(repo)
secret_store = _get_github_token_secret_store(cmd)
cache = secret_store.load()
if isinstance(cache, list):
for entry in cache:
if isinstance(entry, dict) and repo in entry.get("repos", []):
... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/appservice/_github_oauth.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> repo = repo_url_to_name(repo)
secret_store = _get_github_token_secret_store(cmd)
cache = secret_store.load()
if isinstance(cache, list):
for entry in cache:
if isinstance(entry, dict) and repo in entry.get("repos", []):
return entry.get("value")
re... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/appservice/_github_oauth.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> lista[index], lista[min_index] = lista[min_index], lista[index]<|fim_prefix|># repo: EDAII/Lista2_JoaoVitor_JoaoPedro path: /algoritmos_python/selection_sort.py
def selection_sort(lista):
"""
Realiza ordenacao utilizando selection sort
lista: Vetor de inteiros
"""
for index in... | code_fim | medium | {
"lang": "python",
"repo": "EDAII/Lista2_JoaoVitor_JoaoPedro",
"path": "/algoritmos_python/selection_sort.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EDAII/Lista2_JoaoVitor_JoaoPedro path: /algoritmos_python/selection_sort.py
def selection_sort(lista):
"""
Realiza ordenacao utilizando selection sort
lista: Vetor de inteiros
"""
for index in range(0, len(lista)):
min_index = index
<|fim_suffix|> lista[index],... | code_fim | medium | {
"lang": "python",
"repo": "EDAII/Lista2_JoaoVitor_JoaoPedro",
"path": "/algoritmos_python/selection_sort.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#
# Derive state #################################################################
def player(n_moves):
if n_moves % 2 == 0:
return ch_x
else:
return ch_o
def player_str(n_moves):
if player(n_moves) == ch_x:
return 'X'
else:
return 'O'
def turn(game):
... | code_fim | hard | {
"lang": "python",
"repo": "whtahy/prototypes",
"path": "/tictactoe-ext/src/game.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def player_str(n_moves):
if player(n_moves) == ch_x:
return 'X'
else:
return 'O'
def turn(game):
return 1 + len(game.history) - (winner(game) or tie(game))
def tie(game):
return len(game.history) == board_rows * board_cols
def winner(game):
def check(coords):
... | code_fim | hard | {
"lang": "python",
"repo": "whtahy/prototypes",
"path": "/tictactoe-ext/src/game.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: whtahy/prototypes path: /tictactoe-ext/src/game.py
# Released under CC0:
# Summary: https://creativecommons.org/publicdomain/zero/1.0/
# Legal Code: https://creativecommons.org/publicdomain/zero/1.0/legalcode.txt
from config import *
#
# Game state ############################################... | code_fim | hard | {
"lang": "python",
"repo": "whtahy/prototypes",
"path": "/tictactoe-ext/src/game.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def auth_user(username, password):
"""Return wihether user `username` exists with password `password`"""
db, c = config.start_db()
c.execute(
'SELECT pass_hash, salt FROM users WHERE username=? LIMIT 1',
(username,)
)
result = c.fetchone()
config.end_db(db)
if ... | code_fim | hard | {
"lang": "python",
"repo": "dkeriazisStuy/Bourbon-Chocolate_Blog",
"path": "/util/accounts.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def auth_user(username, password):
"""Return wihether user `username` exists with password `password`"""
db, c = config.start_db()
c.execute(
'SELECT pass_hash, salt FROM users WHERE username=? LIMIT 1',
(username,)
)
result = c.fetchone()
config.end_db(db)
if r... | code_fim | hard | {
"lang": "python",
"repo": "dkeriazisStuy/Bourbon-Chocolate_Blog",
"path": "/util/accounts.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dkeriazisStuy/Bourbon-Chocolate_Blog path: /util/accounts.py
import sqlite3 # Enable control of an sqlite database
import csv # Facilitates CSV I/O
import os
import hashlib
import hmac
import util.config as config
def create_table():
"""Creates the SQLite database 'users'"""
db, c = c... | code_fim | hard | {
"lang": "python",
"repo": "dkeriazisStuy/Bourbon-Chocolate_Blog",
"path": "/util/accounts.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rishabhdutta/pylith path: /playpen/finitestrain/plot_soln.py
import h5py
geom = "topo"
# Finite strain
sim = "%s-finite" % geom
filename = "output/%s-domain.h5" % sim
h5 = h5py.File(filename, "r")
dispF = h5['vertex_fields/displacement'][:]
timeF = h5['time'][:,0,0]
h5.close()
filename = "out... | code_fim | medium | {
"lang": "python",
"repo": "rishabhdutta/pylith",
"path": "/playpen/finitestrain/plot_soln.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from pyre.units.time import year
timeF /= year.value
timeI /= year.value
import pylab
iPt = 1
pylab.subplot(2,1,1)
pylab.plot(timeF, dispF[:,iPt,1], 'r-', timeI, dispI[:,iPt,1], 'b--')
pylab.subplot(2,1,2)
pylab.plot(timeF, vstrainF[:,:], 'r-', timeI, vstrainI[:,:], 'b--')
pylab.show()<|fim_prefix|># r... | code_fim | hard | {
"lang": "python",
"repo": "rishabhdutta/pylith",
"path": "/playpen/finitestrain/plot_soln.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not asyncio.iscoroutinefunction(coro_func):
raise TypeError(f'Annotated functions should be coroutines. Use \'async def\'.')
for event in event_types:
if event not in allowed_events:
raise RuntimeError(f'Event {eve... | code_fim | hard | {
"lang": "python",
"repo": "sousa-andre/lcu-driver",
"path": "/lcu_driver/events/managers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Match registered websocket events and create a task with each handler"""
for event in connector.ws.registered_uris:
if event['uri'] == data['uri'] or (
event['uri'].endswith('/') and data['uri'].startswith(event['uri'])
):
if d... | code_fim | hard | {
"lang": "python",
"repo": "sousa-andre/lcu-driver",
"path": "/lcu_driver/events/managers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sousa-andre/lcu-driver path: /lcu_driver/events/managers.py
import asyncio
from abc import ABC
from typing import Union, Callable, Awaitable, Iterable
from lcu_driver.events.responses import WebsocketEventResponse
class ConnectorEventManager(ABC):
"""Connector Events Manager Base Class"""
... | code_fim | hard | {
"lang": "python",
"repo": "sousa-andre/lcu-driver",
"path": "/lcu_driver/events/managers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> datatype = 'dask' if use_dask else 'pandas'
if gridded:
datatype = 'xarray'
gridded_data = True
if kind == 'rgb':
if 'bands' in kwds:
other_dims = [kwds['bands']]
else:
... | code_fim | hard | {
"lang": "python",
"repo": "SmartDataProject/hvplot",
"path": "/hvplot/converter.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SmartDataProject/hvplot path: /hvplot/converter.py
gridded = True
else:
kind = 'hist'
datatype = 'dask' if use_dask else 'pandas'
if gridded:
datatype = 'xarray'
gridded_data = True
... | code_fim | hard | {
"lang": "python",
"repo": "SmartDataProject/hvplot",
"path": "/hvplot/converter.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> import xarray as xr
data = self.data if data is None else data
z = z or self.kwds.get('z')
x = x or self.x
y = y or self.y
if not (x and y):
x, y = list(data.dims)[::-1]
if not z:
z = list(data.data_vars)[0] if isinstance(dat... | code_fim | hard | {
"lang": "python",
"repo": "SmartDataProject/hvplot",
"path": "/hvplot/converter.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rapidsai/xgboost path: /demo/rmm_plugin/rmm_mgpu_with_dask.py
import xgboost as xgb
from sklearn.datasets import make_classification
import dask
from dask.distributed import Client
from dask_cuda import LocalCUDACluster
<|fim_suffix|> X, y = make_classification(n_samples=10000, n_informative=... | code_fim | medium | {
"lang": "python",
"repo": "rapidsai/xgboost",
"path": "/demo/rmm_plugin/rmm_mgpu_with_dask.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> X, y = make_classification(n_samples=10000, n_informative=5, n_classes=3)
# In pratice one should prefer loading the data with dask collections instead of using
# `from_array`.
X = dask.array.from_array(X)
y = dask.array.from_array(y)
dtrain = xgb.dask.DaskDMatrix(client, X, label=... | code_fim | medium | {
"lang": "python",
"repo": "rapidsai/xgboost",
"path": "/demo/rmm_plugin/rmm_mgpu_with_dask.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tomturner/django-datatables path: /django/examples/migrations/0004_person_title.py
# Generated by Django 2.2.5 on 2020-12-16 14:05
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.AddField(
model_nam... | code_fim | medium | {
"lang": "python",
"repo": "tomturner/django-datatables",
"path": "/django/examples/migrations/0004_person_title.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('examples', '0003_tags'),
]
operations = [
migrations.AddField(
model_name='person',
name='title',
field=models.IntegerField(choices=[(0, 'Mr'), (1, 'Mrs'), (2, 'Miss')], null=True),
),
]<|fim_prefix|># repo: to... | code_fim | easy | {
"lang": "python",
"repo": "tomturner/django-datatables",
"path": "/django/examples/migrations/0004_person_title.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>m.save(os.path.join('results', 'Colormaps_2.html'))
m
#
# def my_color_function(feature):
# """Maps low values to green and hugh values to red."""
# if unemployment_dict[feature['id']] > 6.5:
# return '#ff0000'
# else:
# return '#008000'
#
# m = folium.Map([43, -1... | code_fim | hard | {
"lang": "python",
"repo": "sduprey/open_data_platform",
"path": "/python_dashboard/python_visualization.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sduprey/open_data_platform path: /python_dashboard/python_visualization.py
import os
import folium
import pickle
import json
import pandas as pd
import branca.colormap as cm
from collections import defaultdict
print(folium.__version__)
#us_states = os.path.join('..\\example\\data'... | code_fim | hard | {
"lang": "python",
"repo": "sduprey/open_data_platform",
"path": "/python_dashboard/python_visualization.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if apo:
eu = 1 + e
ed = 1 - e
else:
eu = 1 - e
ed = 1 + e
aux_m = max(m1, m2)
m2 = min(m1, m2)
m1 = aux_m
aux_p = a * eu / M
a... | code_fim | hard | {
"lang": "python",
"repo": "Gianuzzi/circumbinary-disc",
"path": "/libs/stars.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Gianuzzi/circumbinary-disc path: /libs/stars.py
from __future__ import print_function
from sys import exit
from numpy import all, any, sum, cos, sin, pi, sqrt
from numpy import array, newaxis, ndarray
from numpy import empty, full, where
from numpy import transpose, unique
from libs.const impo... | code_fim | hard | {
"lang": "python",
"repo": "Gianuzzi/circumbinary-disc",
"path": "/libs/stars.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Print Final Result
openLines(1,"-")
result = randomize(age,sign,street,color,hometown)+" from "+hometown
#Display and Save Result
print(result)
file = open("name.txt", "w")
file.write(str(result))
file.close()<|fim_prefix|># repo: ianpetrarca/python_examples path: /nick_name.py
# Python Project: Nic... | code_fim | hard | {
"lang": "python",
"repo": "ianpetrarca/python_examples",
"path": "/nick_name.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ianpetrarca/python_examples path: /nick_name.py
# Python Project: Nick NAME GENERATOR
# CLI Goals: Generate A Nick Name From a User's Data
# Python Topics:
# - If Statement
# - Writing To Files
# - Lists
# - Functions
# Sample Data:
# - Broadway
# - 25
# - Purple
# - 5
# - Brooklyn
... | code_fim | hard | {
"lang": "python",
"repo": "ianpetrarca/python_examples",
"path": "/nick_name.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> names.append(sign),names.append(street),names.append(color)
sampling = random.sample(names,k=2) #return random choice
return age + " " + sampling[1] + " " + sampling[0][0]
#Print Final Result
openLines(1,"-")
result = randomize(age,sign,street,color,hometown)+" from "+hometown
#Display a... | code_fim | medium | {
"lang": "python",
"repo": "ianpetrarca/python_examples",
"path": "/nick_name.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NKM-ML/LLC_Membranes path: /Ben_Manuscripts/transport/figures/msd_bar_chart.py
#!/usr/bin/env python
import matplotlib.pyplot as plt
import sqlite3 as sql
import numpy as np
import names
connection = sql.connect("../../../LLC_Membranes/timeseries/msd.db")
crsr = connection.cursor()
restrict_by_... | code_fim | hard | {
"lang": "python",
"repo": "NKM-ML/LLC_Membranes",
"path": "/Ben_Manuscripts/transport/figures/msd_bar_chart.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if time_averaged:
ordered_md = np.argsort(md_tamsd)[::-1]
md_tamsd = md_tamsd[ordered_md]
md_tamsd_lower = md_tamsd_lower[ordered_md]
md_tamsd_upper = md_tamsd_upper[ordered_md]
#mw = mw[ordered_md]
else:
ordered_md = np.argsort(md_msd)[::-1]
md_msd = md_msd[ordered_md]
md_msd_lower = md_msd_low... | code_fim | hard | {
"lang": "python",
"repo": "NKM-ML/LLC_Membranes",
"path": "/Ben_Manuscripts/transport/figures/msd_bar_chart.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> failing_navet_responses = [
OrderedDict([
(u'OfficialAddress', OrderedDict([(u'Address2', u'\xd6RGATAN 79 LGH 10'),
(u'PostalCode', u'12345'),
(u'City', u'LANDET')]))
... | code_fim | hard | {
"lang": "python",
"repo": "SUNET/eduid-idproofing-letter",
"path": "/src/idproofing_letter/tests/test_pdf.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SUNET/eduid-idproofing-letter path: /src/idproofing_letter/tests/test_pdf.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import unittest
from collections import OrderedDict
from idproofing_letter import pdf
# We need to add Navet responses that we fail to handle
__author__ ... | code_fim | hard | {
"lang": "python",
"repo": "SUNET/eduid-idproofing-letter",
"path": "/src/idproofing_letter/tests/test_pdf.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
failing_navet_responses = [
OrderedDict([
(u'OfficialAddress', OrderedDict([(u'Address2', u'\xd6RGATAN 79 LGH 10'),
(u'PostalCode', u'12345'),
(u'City', u'LANDET')]))
... | code_fim | hard | {
"lang": "python",
"repo": "SUNET/eduid-idproofing-letter",
"path": "/src/idproofing_letter/tests/test_pdf.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def create_demo_accounts():
Account.objects.all().delete()
# Create some rows
Account.objects.create(year="2004", sales=1000,
expenses=400, ceo="Welch")
Account.objects.create(year="2005", sales=1170,
expenses=460, ceo="Jobs")
Acco... | code_fim | hard | {
"lang": "python",
"repo": "aburan28/django-graphos",
"path": "/demo_project/demo/utils.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aburan28/django-graphos path: /demo_project/demo/utils.py
import pymongo
from .models import Account
DB_HOST = ["localhost"]
DB_PORT = 27017
def get_db(db_name):
DB_HOST = ["localhost"]
DB_PORT = 27017
db = pymongo.Connection(DB_HOST, DB_PORT)[db_name]
return db
def get_mon... | code_fim | hard | {
"lang": "python",
"repo": "aburan28/django-graphos",
"path": "/demo_project/demo/utils.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>candlestick_data = [['Mon', 20, 28, 38, 45],
['Tue', 31, 38, 55, 66],
['Wed', 50, 55, 77, 80],
['Thu', 77, 77, 66, 50],
['Fri', 68, 66, 22, 15]]
mongo_series_object_1 = [[440, 39],
[488, 29.25],
... | code_fim | hard | {
"lang": "python",
"repo": "aburan28/django-graphos",
"path": "/demo_project/demo/utils.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mdeff/ntds_2016 path: /project/reports/breast_cancer/models.py
"""
This module contains the function to run the cnn model
"""
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import collections
import cnn
import utils
from timeit import default_timer as timer
from sklea... | code_fim | hard | {
"lang": "python",
"repo": "mdeff/ntds_2016",
"path": "/project/reports/breast_cancer/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # second convolutional layer
KERNEL_2_SIZE = (5,5)
KERNEL_2_NUM = 32
MAXPOOL_2_SIZE = (3,3)
if strides=='conv':
KERNEL_2_STRIDE = (2,2)
MAXPOOL_2_STRIDE = (1,1)
elif strides=='pool':
KERNEL_2_STRIDE = (1,1)
MAXPOOL_2_STRIDE = (2,2)
else:
... | code_fim | hard | {
"lang": "python",
"repo": "mdeff/ntds_2016",
"path": "/project/reports/breast_cancer/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: laume/dlai path: /dlai/mlai.py
import tensorflow as tf
from tensorflow import keras
import pandas as pd
def plot_history(history, contains, skip=0):
df = pd.DataFrame(history.history)
df[list(df.filter(regex=contains))].iloc[skip:].plot()
def categorical_fit_transform(df, cat_cols):
... | code_fim | hard | {
"lang": "python",
"repo": "laume/dlai",
"path": "/dlai/mlai.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def continuous_fit_transform(df, cont_cols):
df = df.copy()
cont_features_map = {}
df[cont_cols] = df[cont_cols].astype(float)
for cont_col in cont_cols:
cont_features_map[cont_col] = {
"mean": df[cont_col].mean(),
"std": df[cont_col].std(),
}
... | code_fim | hard | {
"lang": "python",
"repo": "laume/dlai",
"path": "/dlai/mlai.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>With ``matplotlib>=3.4``, a keyword argument ``transform`` can be given.
Particularly when `ax.transTernaryAxes` is given, a line fixed to the
triangle can be added by giving the first and the second arguments in the
barycentric coordinates.
"""
import matplotlib.pyplot as plt
import mpltern
ax = plt.sub... | code_fim | hard | {
"lang": "python",
"repo": "yuzie007/mpltern",
"path": "/examples/introductory/axline.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yuzie007/mpltern path: /examples/introductory/axline.py
"""
======
AxLine
======
An infinitely long straight line can be added using ``ax.axline`` in a similar
way as Matplotlib. This may be helpful, e.g., for adding an isoproportion line.
.. note::
<|fim_suffix|>ax.axline(
[1.0, 0.0, 0.0]... | code_fim | hard | {
"lang": "python",
"repo": "yuzie007/mpltern",
"path": "/examples/introductory/axline.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert 0 not in solveset_real(sin(x)/x, x)
assert 0 not in solveset_complex((exp(x) - 1)/x, x)
@XFAIL
def test_solve_trig_simplified():
n = Dummy('n')
assert dumeq(solveset_real(sin(x), x),
imageset(Lambda(n, n*pi), S.Integers))
assert dumeq(solveset_real(cos(x), x),
... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/solvers/tests/test_solveset.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sympy/sympy path: /sympy/solvers/tests/test_solveset.py
):
n = Dummy('n')
assert dumeq(solveset_complex(2**x + 4**x, x),imageset(
Lambda(n, I*(2*n*pi + pi)/log(2)), S.Integers))
assert solveset_complex(x**z*y**z - 2, z) == FiniteSet(
log(2)/(log(x) + log(y)))
asse... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/solvers/tests/test_solveset.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert solveset_real(LambertW(2*x) - y) == FiniteSet(
y*exp(y)/2)
@XFAIL
def test_other_lambert():
a = Rational(6, 5)
assert solveset_real(x**a - a**x, x) == FiniteSet(
a, -a*LambertW(-log(a)/a)/log(a))
@_both_exp_pow
def test_solveset():
f = Function('f')
raises(Va... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/solvers/tests/test_solveset.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EDAII/Arvores_RB-Tree_Lista_04 path: /No.py
# No e Cores
PRETO = 'PRETO'
VERMELHO = 'VERMELHO'
NIL = 'NIL'
class No:
def __init__(self, valor, cor, pai, esquerda=None, direita=None):
self.valor = valor
self.cor = cor
self.pai = pai
self.esquerda = esquerda
... | code_fim | medium | {
"lang": "python",
"repo": "EDAII/Arvores_RB-Tree_Lista_04",
"path": "/No.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.cor == NIL and self.cor == other.cor:
return True
if self.pai is None or other.pai is None:
pais_iguais = self.pai is None and other.pai is None
else:
pais_iguais = self.pai.valor == other.pai.valor and self.pai.cor == other.pai.cor
... | code_fim | medium | {
"lang": "python",
"repo": "EDAII/Arvores_RB-Tree_Lista_04",
"path": "/No.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.cor == NIL:
return 0
return sum([int(self.esquerda.cor != NIL), int(self.direita.cor != NIL)])<|fim_prefix|># repo: EDAII/Arvores_RB-Tree_Lista_04 path: /No.py
# No e Cores
PRETO = 'PRETO'
VERMELHO = 'VERMELHO'
NIL = 'NIL'
class No:
def __init__(self, valor, cor,... | code_fim | hard | {
"lang": "python",
"repo": "EDAII/Arvores_RB-Tree_Lista_04",
"path": "/No.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sasasagagaga/Code-examples path: /Python 2 & 3/some ML examples/linear models/multiclass.py
class MulticlassStrategy:
def __init__(self, classifier, mode, **kwargs):
"""
Инициализация мультиклассового классификатора
classifier - базовый бинарный классификат... | code_fim | hard | {
"lang": "python",
"repo": "sasasagagaga/Code-examples",
"path": "/Python 2 & 3/some ML examples/linear models/multiclass.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def predict(self, X):
"""
Выдача предсказаний классификатором
"""
if self.mode == 'one_vs_all':
probs = [classifier.predict_proba(X)[:, 1] for classifier in self.classifiers]
return np.argmax(probs, axis=0)
else:
pred = np.zer... | code_fim | hard | {
"lang": "python",
"repo": "sasasagagaga/Code-examples",
"path": "/Python 2 & 3/some ML examples/linear models/multiclass.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: edkirk30/django-notifications path: /notifications/migrations/0009_notification_full_screen_datetime.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.4 on 2018-06-05 22:20
from __future__ import unicode_literals
<|fim_suffix|> operations = [
migrations.AddField(
model... | code_fim | medium | {
"lang": "python",
"repo": "edkirk30/django-notifications",
"path": "/notifications/migrations/0009_notification_full_screen_datetime.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='notification',
name='full_screen_datetime',
field=models.DateTimeField(blank=True, null=True),
),
]<|fim_prefix|># repo: edkirk30/django-notifications path: /notifications/migrations/0009_notificat... | code_fim | medium | {
"lang": "python",
"repo": "edkirk30/django-notifications",
"path": "/notifications/migrations/0009_notification_full_screen_datetime.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> config_expression = snippet_config_language_pb2.Expression(
string_value="hello world"
)
node = libcst_utils.convert_expression(config_expression)
expected_node = libcst.SimpleString(value='"hello world"')
assert node.deep_equals(expected_node), (node, expected_node)
def tes... | code_fim | hard | {
"lang": "python",
"repo": "googleapis/gapic-generator-python",
"path": "/tests/unit/configurable_snippetgen/test_libcst_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_convert_py_dict():
key_value_pairs = [("key1", "value1"), ("key2", "value2")]
node = libcst_utils.convert_py_dict(key_value_pairs)
expected_node = libcst.Dict(
[
libcst.DictElement(
libcst.SimpleString('"key1"'), libcst.SimpleString('"value1"')
... | code_fim | hard | {
"lang": "python",
"repo": "googleapis/gapic-generator-python",
"path": "/tests/unit/configurable_snippetgen/test_libcst_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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