text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: gvx/generate-html path: /tests/test_comments.py
from generate_html import comment, fragment, render_html, tag
from typing import Iterator
<|fim_suffix|> assert render_html(simple_comment()) == '<!-- hi -->'
def test_comment_doesnt_escape() -> None:
assert render_html(comment_doesnt_esc... | code_fim | hard | {
"lang": "python",
"repo": "gvx/generate-html",
"path": "/tests/test_comments.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @keyword
def foo(self):
self.info('foo')
@keyword
def bar(self, arg):
self.info(arg)<|fim_prefix|># repo: HelioGuilherme66/robotframework-seleniumlibrary path: /utest/test/api/my_lib.py
from SeleniumLibrary.base import LibraryComponent, keyword
<|fim_middle|>class my_li... | code_fim | easy | {
"lang": "python",
"repo": "HelioGuilherme66/robotframework-seleniumlibrary",
"path": "/utest/test/api/my_lib.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HelioGuilherme66/robotframework-seleniumlibrary path: /utest/test/api/my_lib.py
from SeleniumLibrary.base import LibraryComponent, keyword
<|fim_suffix|>
@keyword
def foo(self):
self.info('foo')
@keyword
def bar(self, arg):
self.info(arg)<|fim_middle|>
class my_l... | code_fim | easy | {
"lang": "python",
"repo": "HelioGuilherme66/robotframework-seleniumlibrary",
"path": "/utest/test/api/my_lib.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.info(arg)<|fim_prefix|># repo: HelioGuilherme66/robotframework-seleniumlibrary path: /utest/test/api/my_lib.py
from SeleniumLibrary.base import LibraryComponent, keyword
<|fim_middle|>
class my_lib(LibraryComponent):
@keyword
def foo(self):
self.info('foo')
@keyword
... | code_fim | medium | {
"lang": "python",
"repo": "HelioGuilherme66/robotframework-seleniumlibrary",
"path": "/utest/test/api/my_lib.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Network size
Kappa : float
Mean degree of the ensemble
Returns
----------
Mu2 : float
Expected algebraic connectivity of the ensemble.
"""
Mu2 = Kappa - ( 2*Kappa*(1.0 - (Kappa/N))*math.log(N) )**0.5 + (( (Kappa*(1.0 - (Kappa/N)))/math.log(N) )**0.5)*( math.log( (2*math.pi*math.l... | code_fim | hard | {
"lang": "python",
"repo": "MGarrod1/rgg_ensemble_analysis",
"path": "/rgg_ensemble_analysis/Analytic_Functions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
Parameters
-----------
N : int
Network size
Kappa : float
Mean degree of the ensemble
d: int
Dimension of the embedding space
Returns
---------
Mu2 : float
Approximate value of the algebraic connectivity.
"""
Mu2 = (1.0/6.0)*( (math.pi/(N**(1.0/d)) )**2 )*( ( Kappa ... | code_fim | hard | {
"lang": "python",
"repo": "MGarrod1/rgg_ensemble_analysis",
"path": "/rgg_ensemble_analysis/Analytic_Functions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MGarrod1/rgg_ensemble_analysis path: /rgg_ensemble_analysis/Analytic_Functions.py
"""
Contains functions which evaluate the analytic approximation of the
algebraic connectivity of graphs.
"""
#Import standard python modules:
import numpy as np
import itertools
import math
import scipy
from s... | code_fim | hard | {
"lang": "python",
"repo": "MGarrod1/rgg_ensemble_analysis",
"path": "/rgg_ensemble_analysis/Analytic_Functions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: healthwhale/streamlit-quill path: /streamlit_quill/__init__.py
import os
import streamlit.components.v1 as components
_RELEASE = True
if not _RELEASE:
_st_quill = components.declare_component("streamlit_quill", url="http://localhost:3001")
else:
parent_dir = os.path.dirname(os.path.absp... | code_fim | hard | {
"lang": "python",
"repo": "healthwhale/streamlit-quill",
"path": "/streamlit_quill/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if not _RELEASE:
import streamlit as st
st.sidebar.title(":computer: Quill Editor")
placeholder = st.sidebar.text_input("Placeholder", "Some placeholder text")
html = st.sidebar.checkbox("Return HTML", False)
read_only = st.sidebar.checkbox("Read only", False)
content = st_quill... | code_fim | hard | {
"lang": "python",
"repo": "healthwhale/streamlit-quill",
"path": "/streamlit_quill/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robsonzagrejr/random_prime_number path: /prng/blum_blum_shub.py
# Implementation of Blum Blum Shub
# Copyright (c) 2021 Robson Zagre Júnior
from src.utils import (
_random_int
)
# x(i+1) = x(i)² Mod M
# coprime are values that factorized in primes dont shared a same divisor
# (If p and q ar... | code_fim | hard | {
"lang": "python",
"repo": "robsonzagrejr/random_prime_number",
"path": "/prng/blum_blum_shub.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> random_number = 0
while random_number.bit_length() < n_bits:
# Generate next value in serie
x = pow(x,2,M)
# Join least significant bit of serie with random_number
random_number <<= 1
random_number |= (x & 1)
return random_number
# Generate a ranfom ... | code_fim | hard | {
"lang": "python",
"repo": "robsonzagrejr/random_prime_number",
"path": "/prng/blum_blum_shub.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return random_number
# Generate a ranfom integer with 32 bits
def gen_int(size=32):
global random_seed, x, M
if random_seed:
_set_random_seed()
random_number = 0
# Execute just by size of int (not garantee that number will have size bits)
for _ in range(0, size):
... | code_fim | hard | {
"lang": "python",
"repo": "robsonzagrejr/random_prime_number",
"path": "/prng/blum_blum_shub.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rustytwilight/sandypi path: /server/utils/buffered_timeout.py
from threading import Thread, Lock
import time
# this thread calls a function after a timeout but only if the "update" method is not called before that timeout expires
class BufferTimeout(Thread):
def __init__(self, timeout_delta... | code_fim | hard | {
"lang": "python",
"repo": "rustytwilight/sandypi",
"path": "/server/utils/buffered_timeout.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, timeout_delta, function, group=None, target=None, name=None, args=(), kwargs=None):
super(BufferTimeout, self).__init__(group=group, target=target, name=name)
self.name = "buffered_timeout"
self.timeout_delta = timeout_delta
self.callback = function
... | code_fim | hard | {
"lang": "python",
"repo": "rustytwilight/sandypi",
"path": "/server/utils/buffered_timeout.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ii_dist = final_mesh[:len(ii)]
jj_dist = final_mesh[len(jj):]
sources = np.stack([ii, jj]).transpose().astype(np.int32)
targets = np.stack([ii_dist, jj_dist]).transpose().astype(np.int32)
# Define path to save results
out_distord = '{out_dir}/ebsd_distord.{index}.png'.format(out_d... | code_fim | hard | {
"lang": "python",
"repo": "MLmicroscopy/distortions",
"path": "/src/distord.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # turn floating mesh into integer one (pixels are integer!)
mesh_int = np.array(solutions, dtype=np.int32)
# prepare data for multi-threading
scores = []
for s in mesh_int:
ii_dist = s[:len(ii)]
jj_dist = s[len(jj):]
sources = ... | code_fim | hard | {
"lang": "python",
"repo": "MLmicroscopy/distortions",
"path": "/src/distord.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MLmicroscopy/distortions path: /src/distord.py
import numpy as np
import os
import cv2
from distutils.util import strtobool
from matplotlib import pyplot as plt, cm
import argparse
from misc.tools import compute_score, apply_distortion
from ang.write_core_ang import Ang
from ang.phase import P... | code_fim | hard | {
"lang": "python",
"repo": "MLmicroscopy/distortions",
"path": "/src/distord.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>server_msg, address = sock.recvfrom(1024)
print('收到服务端消息',server_msg.decode())
sock.close()<|fim_prefix|># repo: panshen083/RUN path: /install/Hardware control.hcl
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import socket
import time
sock = socket.socket(type=socket.SOCK_DGRAM) ... | code_fim | hard | {
"lang": "python",
"repo": "panshen083/RUN",
"path": "/install/Hardware control.hcl",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: panshen083/RUN path: /install/Hardware control.hcl
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import socket
import time
sock = socket.socket(type=socket.SOCK_DGRAM) #创建Socket接口
sock.sendto('RELAY-SCAN_DEVICE-NOW'.encode(),('192.168.1.210', 4196)) #发送初始化命令1
<|fim_s... | code_fim | medium | {
"lang": "python",
"repo": "panshen083/RUN",
"path": "/install/Hardware control.hcl",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Wen-Tian-Pineapple/RL-template path: /run_breakout.py
"""
Example of an efficiently implemented RL model
in a 2D environment. This example uses the Atari
game breakout.
"""
import numpy as np
import gym
import time
from mpi4py import MPI
import heapq
import tensorflow as tf
from models import T... | code_fim | hard | {
"lang": "python",
"repo": "Wen-Tian-Pineapple/RL-template",
"path": "/run_breakout.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> batch_train_data = [datum[0] for datum in batch_data]
batch_reward_data = [datum[1] for datum in batch_data]
train_data.extend(batch_train_data)
all_rewards.extend(batch_reward_data)
else:
comm.gather(worker(model... | code_fim | hard | {
"lang": "python",
"repo": "Wen-Tian-Pineapple/RL-template",
"path": "/run_breakout.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skyhigh8591/VocationalTraining_LearningCode path: /Program_RPI_IOT_code/Python/1750.py
#!/home/pi/RPI_IOT/Python
#-*- coding: UTF-8 -*-
import smbus
import time
DEVICE =0x23
POWER_DOWN =0x00
POWER_ON =0x01
RESET =0x07
<|fim_suffix|> return((data[1]+(256*data[0]))/1.2)
def readLight(... | code_fim | hard | {
"lang": "python",
"repo": "skyhigh8591/VocationalTraining_LearningCode",
"path": "/Program_RPI_IOT_code/Python/1750.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def readLight(addr=DEVICE):
data=bus.read_i2c_block_data(addr,ONE_TIME_HIGH_RES_MODE_1)
return convertToNumber(data)
def main():
while True:
print "Light Level :"+str(readLight())+" 1x"
time.sleep(1)
if __name__=="__name__":
main()<|fim_prefix|># repo: skyhigh8591/VocationalTraining_LearningCode... | code_fim | hard | {
"lang": "python",
"repo": "skyhigh8591/VocationalTraining_LearningCode",
"path": "/Program_RPI_IOT_code/Python/1750.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sydnimeyer/PFCH-Final-2021 path: /GlobKwdArticle.py
import xml.etree.ElementTree as etree
import glob
import pandas as pd
keywords = []
#creating structure for Pandas dataframe
df_cols = ['Keywords']
rows = []
<|fim_suffix|># # creating rows for data for Pandas DataFrame
rows.append({'Keywords... | code_fim | hard | {
"lang": "python",
"repo": "sydnimeyer/PFCH-Final-2021",
"path": "/GlobKwdArticle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># # creating rows for data for Pandas DataFrame
rows.append({'Keywords': keywords})
out_df = pd.DataFrame(rows, columns=df_cols)
out_df.to_csv('kwdglob_keywords.csv', index=False)<|fim_prefix|># repo: sydnimeyer/PFCH-Final-2021 path: /GlobKwdArticle.py
import xml.etree.ElementTree as etree
import glob
... | code_fim | hard | {
"lang": "python",
"repo": "sydnimeyer/PFCH-Final-2021",
"path": "/GlobKwdArticle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open(file) as xmlfile:
tree = etree.parse(file)
root = tree.getroot()
# #defining tree structure
article_meta = tree.find('front').find('article-meta')
# #setting keywords text
for keyword in article_meta.findall('.//kwd-group/kwd'):
keywords.append(... | code_fim | medium | {
"lang": "python",
"repo": "sydnimeyer/PFCH-Final-2021",
"path": "/GlobKwdArticle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cms-sw/cmssw path: /L1Trigger/Configuration/python/customise_l1GtEmulatorFromRaw.py
#
# customization fragment to run L1 GT emulator starting from a RAW file
#
# V.M. Ghete 2010-06-09
import FWCore.ParameterSet.Config as cms
def customise(process):
<|fim_suffix|> #
# customization o... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/L1Trigger/Configuration/python/customise_l1GtEmulatorFromRaw.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if printL1TriggerReport == True :
from L1Trigger.Configuration.L1Trigger_custom import customiseL1TriggerReport
process=customiseL1TriggerReport(process)
process.SimL1Emulator_L1TriggerReport = cms.Sequence(process.SimL1Emulator*process.l1GtTrigReport)
process.... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/L1Trigger/Configuration/python/customise_l1GtEmulatorFromRaw.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>router = routers.SimpleRouter()
router.register('plan-tags', PlanTagViewSet, basename='plan-tags')
router.register('plan-costs', PlanCostViewSet, basename='plan-costs')
router.register('planlist-details', PlanListDetailViewSet, basename='planlist-details')
router.register('planlist', PlanListViewSet, base... | code_fim | medium | {
"lang": "python",
"repo": "ydaniels/drf-django-flexible-subscriptions",
"path": "/subscriptions_api/urls.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ydaniels/drf-django-flexible-subscriptions path: /subscriptions_api/urls.py
from rest_framework import routers
from .views import PlanTagViewSet, PlanCostViewSet, PlanListDetailViewSet, \
PlanListViewSet, SubscriptionPlanViewSet, SubscriptionTransactionViewSet, \
UserSubscriptionViewSet
... | code_fim | medium | {
"lang": "python",
"repo": "ydaniels/drf-django-flexible-subscriptions",
"path": "/subscriptions_api/urls.py",
"mode": "psm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|> initial = True
dependencies = [
('playlist', '0010_playlist_type'),
]
operations = [
migrations.CreateModel(
name='Weekly',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
... | code_fim | medium | {
"lang": "python",
"repo": "gasbarroni8/best-channels",
"path": "/django_base/weekly_channels/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gasbarroni8/best-channels path: /django_base/weekly_channels/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.2 on 2017-08-10 04:02
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
<|fim_suffix|> i... | code_fim | medium | {
"lang": "python",
"repo": "gasbarroni8/best-channels",
"path": "/django_base/weekly_channels/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def teardown_function():
"""Executed at the end of the current test suite"""
# Force module reload as the default test settings have been restored
importlib.reload(defaults)<|fim_prefix|># repo: openfun/marion path: /src/marion/marion/tests/test_defaults.py
"""Tests for the marion applicatio... | code_fim | hard | {
"lang": "python",
"repo": "openfun/marion",
"path": "/src/marion/marion/tests/test_defaults.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Executed at the end of the current test suite"""
# Force module reload as the default test settings have been restored
importlib.reload(defaults)<|fim_prefix|># repo: openfun/marion path: /src/marion/marion/tests/test_defaults.py
"""Tests for the marion application defaults"""
import imp... | code_fim | hard | {
"lang": "python",
"repo": "openfun/marion",
"path": "/src/marion/marion/tests/test_defaults.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openfun/marion path: /src/marion/marion/tests/test_defaults.py
"""Tests for the marion application defaults"""
import importlib
from pathlib import Path
from marion import defaults
<|fim_suffix|> """Test marion.defaults overrides with settings definition"""
settings.MARION_DOCUMENT_IS... | code_fim | medium | {
"lang": "python",
"repo": "openfun/marion",
"path": "/src/marion/marion/tests/test_defaults.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def from_pretrained(cls, *args, **kw):
kw["_fast_init"] = False
return super().from_pretrained(*args, **kw)
@classmethod
def from_pretrained_question_encoder_generator(
cls,
question_encoder_pretrained_model_name_or_path=None,
generator... | code_fim | hard | {
"lang": "python",
"repo": "quantapix/qnarre",
"path": "/qnarre/prep/config/rag.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if "config" not in kw_question_encoder:
from ..auto.configuration_auto import AutoConfig
question_encoder_config, kw_question_encoder = AutoConfig.from_pretrained(
question_encoder_pretrained_model_name_or_path,
**kw_ques... | code_fim | hard | {
"lang": "python",
"repo": "quantapix/qnarre",
"path": "/qnarre/prep/config/rag.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: quantapix/qnarre path: /qnarre/prep/config/rag.py
# Copyright 2022 Quantapix 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 at
#
# http:... | code_fim | hard | {
"lang": "python",
"repo": "quantapix/qnarre",
"path": "/qnarre/prep/config/rag.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def sanitize_webscrape_name(name):
""" Sanitizes webscrape powerplant names by removing unwanted
strings (listed in blacklist), applying lower case, and deleting
trailing whitespace.
Parameters
----------
name: str
webscrape plant name
Returns
-------
name: s... | code_fim | hard | {
"lang": "python",
"repo": "arfc/transition-scenarios",
"path": "/scripts/merge_coordinates.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: arfc/transition-scenarios path: /scripts/merge_coordinates.py
from fuzzywuzzy import fuzz
import numpy as np
import pandas as pd
import sqlite3 as sql
import sys
if len(sys.argv) < 3:
print('Usage: python merge_coordinates.py [pris_link] [webscrape_link]')
def cursor(file_name):
""" Co... | code_fim | hard | {
"lang": "python",
"repo": "arfc/transition-scenarios",
"path": "/scripts/merge_coordinates.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def save_output(pris):
""" Saves updated PRIS database as 'reactors_pris_2016.csv'
Parameters
----------
pris: pd.DataFrame
updated PRIS database with latitude and longitude info
Returns
-------
"""
pris.to_csv('reactors_pris_2016.csv',
index=Fals... | code_fim | hard | {
"lang": "python",
"repo": "arfc/transition-scenarios",
"path": "/scripts/merge_coordinates.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.eval()
self.define_extras(self.args.batch_size)
test_loss = 0
correct = 0
for data, target in test_loader:
if self.args.cuda:
data, target = data.cuda(), target.cuda()
target = Variable(target)
target_ = targe... | code_fim | hard | {
"lang": "python",
"repo": "BalintMagyar4/soft-decision-tree",
"path": "/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def train_(self, train_loader, epoch):
t = time.time()
self.train()
self.define_extras(self.args.batch_size)
for batch_idx, (data, target) in enumerate(train_loader):
correct = 0
if self.args.cuda:
data, target = data.cuda(), tar... | code_fim | hard | {
"lang": "python",
"repo": "BalintMagyar4/soft-decision-tree",
"path": "/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BalintMagyar4/soft-decision-tree path: /model.py
import os
import time
import scipy.misc
import numpy as np
import pickle
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
import time
class InnerNode():
def... | code_fim | hard | {
"lang": "python",
"repo": "BalintMagyar4/soft-decision-tree",
"path": "/model.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self):
self.times = []
self.values = []
def clear(self):
self.times = []
self.values = []
def to_dict(self):
# Ensure times are a python list
times = self.times if type(self.times) is list else list(self.times)
... | code_fim | medium | {
"lang": "python",
"repo": "gjfelix/BlenderNEURON",
"path": "/blenderneuron/activity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gjfelix/BlenderNEURON path: /blenderneuron/activity.py
try:
import numpy as np
numpy_available = True
from blenderneuron.blender.utils import rdp
except:
numpy_available = False
class Activity:
def __init__(self):
<|fim_suffix|> def to_dict(self):
# E... | code_fim | medium | {
"lang": "python",
"repo": "gjfelix/BlenderNEURON",
"path": "/blenderneuron/activity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print('Loading gitGrab.json...')
with open(basedir+'/gitGrab.json', 'rt') as fd:
gitgrabs = sorted(json.loads(fd.read()), key=lambda x:-x['stars'])
ngrabs = len(gitgrabs)
lastds = 0
downfd = None
for i, gitgrab in enumerate(gitgrabs):
ds = 1 + i//maxprojects
if... | code_fim | hard | {
"lang": "python",
"repo": "nokia/code-compass",
"path": "/scripts/create_crawl_scripts.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nokia/code-compass path: /scripts/create_crawl_scripts.py
#!/usr/bin/env python
# Copyright (C) 2019, Nokia
# Licensed under the BSD 3-Clause License
import json
import os
import sys
basedir = sys.argv[1] if len(sys.argv) > 1 else '../datasets/python'
maxprojects=10000
gitclone = False
wit... | code_fim | hard | {
"lang": "python",
"repo": "nokia/code-compass",
"path": "/scripts/create_crawl_scripts.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TrendingTechnology/pyZscaler path: /pyzscaler/zpa/posture_profiles.py
from box import BoxList
from restfly.endpoint import APIEndpoint
class PostureProfilesAPI(APIEndpoint):
def list_profiles(self):
"""
Returns a list of all configured posture profiles.
Returns:
... | code_fim | medium | {
"lang": "python",
"repo": "TrendingTechnology/pyZscaler",
"path": "/pyzscaler/zpa/posture_profiles.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_profile(self, profile_id: str):
"""
Returns information on the specified posture profiles.
Args:
profile_id (str):
The unique identifier for the posture profiles.
Returns:
:obj:`dict`: The resource record for the posture... | code_fim | hard | {
"lang": "python",
"repo": "TrendingTechnology/pyZscaler",
"path": "/pyzscaler/zpa/posture_profiles.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
:obj:`dict`: The resource record for the posture profiles.
Examples:
>>> pprint(zpa.posture_profiles.get_profile('2342342342344433'))
"""
return self._get(f"posture/{profile_id}")<|fim_prefix|># repo: TrendingTechnology/pyZscaler path: /... | code_fim | medium | {
"lang": "python",
"repo": "TrendingTechnology/pyZscaler",
"path": "/pyzscaler/zpa/posture_profiles.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if help_ or len(argv) == 1:
dalton_help()
if version: # :todo: displays version number
pass
if license_:
click.echo(mit_license())<|fim_prefix|># repo: periodicaidan/dalton-cli path: /dalton.py
"""
File: dalton.py
Purpose: The root-command for the program, shows app i... | code_fim | hard | {
"lang": "python",
"repo": "periodicaidan/dalton-cli",
"path": "/dalton.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: periodicaidan/dalton-cli path: /dalton.py
"""
File: dalton.py
Purpose: The root-command for the program, shows app information
"""
from sys import argv
import click
from app_info import mit_license
from help_menus import dalton_help
<|fim_suffix|> if help_ or len(argv) == 1:
dalto... | code_fim | hard | {
"lang": "python",
"repo": "periodicaidan/dalton-cli",
"path": "/dalton.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@click.group("dalton", invoke_without_command=True)
@click.option("--version", is_flag=True, default=False)
@click.option("--license", "license_", is_flag=True, default=False)
@click.option("--help", "-h", "help_", is_flag=True, default=False)
def dalton(help_, version, license_):
if help_ or len(arg... | code_fim | medium | {
"lang": "python",
"repo": "periodicaidan/dalton-cli",
"path": "/dalton.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: henrikmidtiby/PorpoiseTracker path: /tracked_object.py
class MarkObject:
def __init__(self, name, color, marking, data, from_video, log_file, fov_file):
self.video = from_video
self.log_file = log_file<|fim_suffix|>or
self.marking = marking
self.data = data
... | code_fim | medium | {
"lang": "python",
"repo": "henrikmidtiby/PorpoiseTracker",
"path": "/tracked_object.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>or
self.marking = marking
self.data = data
self.hide = False<|fim_prefix|># repo: henrikmidtiby/PorpoiseTracker path: /tracked_object.py
class MarkObject:
def __init__(self, name, color, marking, data, from_video, lo<|fim_middle|>g_file, fov_file):
self.video = from_vi... | code_fim | medium | {
"lang": "python",
"repo": "henrikmidtiby/PorpoiseTracker",
"path": "/tracked_object.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yuenliou/leetcode path: /40-combination-sum-ii.py
#!/usr/local/bin/python3.7
# -*- coding: utf-8 -*-
from typing import List
class Solution:
def combinationSum2(self, candidates: List[int], target: int) -> List[List[int]]:
"""
什么时候使用 used 数组，什么时候使用 begin 变量
有些朋友可能会疑惑什... | code_fim | hard | {
"lang": "python",
"repo": "yuenliou/leetcode",
"path": "/40-combination-sum-ii.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>所有数字（包括目标数）都是正整数。
解集不能包含重复的组合。
示例 1:
输入: candidates = [10,1,2,7,6,1,5], target = 8,
所求解集为:
[
[1, 7],
[1, 2, 5],
[2, 6],
[1, 1, 6]
]
示例 2:
输入: candidates = [2,5,2,1,2], target = 5,
所求解集为:
[
[1,2,2],
[5]
]
来源：力扣（LeetCode）
链接：https://leetcode-cn.com/problems/combination-sum-ii
著作权归领扣网络所有。商业转... | code_fim | hard | {
"lang": "python",
"repo": "yuenliou/leetcode",
"path": "/40-combination-sum-ii.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alaindet/learn-python path: /courses/complete-python/web-scraping/books-scraper/pages/all_books_page.py
from bs4 import BeautifulSoup
from re import search
from locators.all_books_page import AllBooksPageLocators
from parsers.book import BookParser
class AllBooksPage:
def __init__(self, pag... | code_fim | medium | {
"lang": "python",
"repo": "alaindet/learn-python",
"path": "/courses/complete-python/web-scraping/books-scraper/pages/all_books_page.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pager_content = self.soup.select_one(AllBooksPageLocators.PAGER).string
pattern = 'Page [0-9]+ of ([0-9]+)'
matches = search(pattern, pager_content)
pages = int(matches.group(1))
return pages<|fim_prefix|># repo: alaindet/learn-python path: /courses/complete-python... | code_fim | medium | {
"lang": "python",
"repo": "alaindet/learn-python",
"path": "/courses/complete-python/web-scraping/books-scraper/pages/all_books_page.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>file = open('travel_plans.txt', 'r')
first_chars = file.read(33)
print(first_chars)
# 8. Challenge: Using the file school_prompt.txt, if the character ‘p’ is in a word, then add the word to a list called p_words.
file = open('school_prompt.txt', 'r')
p_words = []
for line in file:
words = line.split... | code_fim | hard | {
"lang": "python",
"repo": "Salman42Sabir/Python3-Programming-Specialization",
"path": "/course_2_assessment_1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Salman42Sabir/Python3-Programming-Specialization path: /course_2_assessment_1.py
# 1. The textfile, travel_plans.txt, contains the summer travel plans for someone with some commentary.
# Find the total number of characters in the file and save to the variable num.
file = open("travel_plans.txt")... | code_fim | hard | {
"lang": "python",
"repo": "Salman42Sabir/Python3-Programming-Specialization",
"path": "/course_2_assessment_1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>file = open('school_prompt.txt', 'r')
p_words = []
for line in file:
words = line.split()
for word in words:
if "p" not in word:
continue
p_words.append(word)
print(p_words)<|fim_prefix|># repo: Salman42Sabir/Python3-Programming-Specialization path: /course_2_assessmen... | code_fim | hard | {
"lang": "python",
"repo": "Salman42Sabir/Python3-Programming-Specialization",
"path": "/course_2_assessment_1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ioannispapadogeo/Flood_protection path: /Model/problem_formulation_2.py
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 21 17:34:11 2018
@author: ciullo
"""
from __future__ import (unicode_literals, print_function, absolute_import,
division)
from ema_workbench import (Mo... | code_fim | hard | {
"lang": "python",
"repo": "ioannispapadogeo/Flood_protection",
"path": "/Model/problem_formulation_2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> outcomes.append(ScalarOutcome('Total Investment Costs',
variable_name=['{}_Dike Investment Costs'.format(dike)
for dike in function.dikelist] + ['RfR Total Costs'] + ['Expected Evacuation Costs'],
function... | code_fim | hard | {
"lang": "python",
"repo": "ioannispapadogeo/Flood_protection",
"path": "/Model/problem_formulation_2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Override to print a readable string presentation of your object
# below is a dynamic way of doing this without explicity constructing the string manually
return ', '.join(['{key}={value}'.format(key=key, value=self.__dict__.get(key)) for key in self.__dict__])
class Order(... | code_fim | hard | {
"lang": "python",
"repo": "dutraa/alpaca1",
"path": "/data/alpaca_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dutraa/alpaca1 path: /data/alpaca_data.py
user
boolean
User setting. If true, the account is not allowed to place orders.
trading_blocked
boolean
If true, the account is not allowed to place orders.
transfers_blocked
boolean
If true,... | code_fim | hard | {
"lang": "python",
"repo": "dutraa/alpaca1",
"path": "/data/alpaca_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> now = pd.Timestamp.now(tz=timezone)
nextOpen = self.next_open
if( now.day == nextOpen.day and
now.hour == nextOpen.hour - hour and
now.minute == nextOpen.minute - minute and
now.second == nextOpen.second - second):
return True... | code_fim | hard | {
"lang": "python",
"repo": "dutraa/alpaca1",
"path": "/data/alpaca_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ApiResponse
"""
return self._request(fill_query_params(kwargs.pop('path'), campaignId), params=kwargs)
@sp_endpoint('/v2/sp/campaigns/{}', method='DELETE')
def delete_campaign(self, campaignId, **kwargs) -> ApiResponse:
r"""
delete_campaign(self, camp... | code_fim | hard | {
"lang": "python",
"repo": "saleweaver/python-amazon-ad-api",
"path": "/ad_api/api/sp/campaigns.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: saleweaver/python-amazon-ad-api path: /ad_api/api/sp/campaigns.py
from ad_api.base import Client, sp_endpoint, fill_query_params, ApiResponse
class Campaigns(Client):
@sp_endpoint('/v2/sp/campaigns', method='POST')
def create_campaigns(self, **kwargs) -> ApiResponse:
r"""
... | code_fim | hard | {
"lang": "python",
"repo": "saleweaver/python-amazon-ad-api",
"path": "/ad_api/api/sp/campaigns.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
return self._request(kwargs.pop('path'), params=kwargs)
@sp_endpoint('/v2/sp/campaigns/{}', method='GET')
def get_campaign(self, campaignId, **kwargs) -> ApiResponse:
r"""
get_campaign(self, campaignId, **kwargs) -> ApiResponse
Gets a campaign specif... | code_fim | hard | {
"lang": "python",
"repo": "saleweaver/python-amazon-ad-api",
"path": "/ad_api/api/sp/campaigns.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thatdeep/urnn path: /utils/optimizations.py
import theano
import lasagne
import theano.tensor as T
import numpy as np
from collections import OrderedDict
def clipped_gradients(gradients, gradient_clipping):
clipped_grads = [T.clip(g, -gradient_clipping, gradient_clipping)
... | code_fim | hard | {
"lang": "python",
"repo": "thatdeep/urnn",
"path": "/utils/optimizations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Stochastic Gradient Descent (SGD) updates
Generates update expressions of the form:
* ``param := param - learning_rate * gradient``
Parameters
----------
loss_or_grads : symbolic expression or list of expressions
A scalar loss expression, or a list of gradient expression... | code_fim | hard | {
"lang": "python",
"repo": "thatdeep/urnn",
"path": "/utils/optimizations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CyberZHG/keras-adaptive-softmax path: /keras_adaptive_softmax/softmax.py
from tensorflow import keras
from tensorflow.keras import backend as K
__all__ = ['AdaptiveSoftmax']
class AdaptiveSoftmax(keras.layers.Layer):
"""Turns dense vectors into probabilities.
# Arguments
input... | code_fim | hard | {
"lang": "python",
"repo": "CyberZHG/keras-adaptive-softmax",
"path": "/keras_adaptive_softmax/softmax.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return input_shape[0][:-1] + (self.output_dim,)
def call(self, inputs, **kwargs):
embeddings = inputs[1:1 + (self.cluster_num + 1)]
projections = inputs[1 + (self.cluster_num + 1):]
inputs = inputs[0]
if self.div_val == 1:
if self.embed_dim != self.... | code_fim | hard | {
"lang": "python",
"repo": "CyberZHG/keras-adaptive-softmax",
"path": "/keras_adaptive_softmax/softmax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Ident(ctypes.Structure):
_fields_ = [
("nsid", ctypes.c_uint32),
("nst", ctypes.c_uint8),
("type", ctypes.c_uint8),
("_pad0", ctypes.c_uint8),
("be_attr", BackendAttributes),
("_pad", ctypes.c_uint8 * 38),
("uri", ctypes.c_char * 320),
... | code_fim | medium | {
"lang": "python",
"repo": "SuhoSon/xNVMe",
"path": "/pyxnvme/xnvme/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SuhoSon/xNVMe path: /pyxnvme/xnvme/__init__.py
"""
xNVMe libraries for Python
Wrapping the shared version of xNVMe
"""
import ctypes
import time
import sys
import os
XNVME_SHARED_LIB_FN = "libxnvme-shared.so"
CAPI = None
if CAPI is None:
CAPI = ctypes.cdll.LoadLibrary(XNVME_SHARED_... | code_fim | hard | {
"lang": "python",
"repo": "SuhoSon/xNVMe",
"path": "/pyxnvme/xnvme/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_display = ['key', 'format_value', 'createtime', 'updatetime']
admin.site.site_title = '数据存储'
admin.site.site_header = '数据存储'
admin.site.register(Data, AdminData)<|fim_prefix|># repo: Today-to-Lsp/pythonanywhere path: /DataStorage/DataStorage/admin.py
from django.contrib import admin
from DataS... | code_fim | easy | {
"lang": "python",
"repo": "Today-to-Lsp/pythonanywhere",
"path": "/DataStorage/DataStorage/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Today-to-Lsp/pythonanywhere path: /DataStorage/DataStorage/admin.py
from django.contrib import admin
from DataStorage.models import Data
# Register your models here.
<|fim_suffix|>admin.site.site_title = '数据存储'
admin.site.site_header = '数据存储'
admin.site.register(Data, AdminData)<|fim_middle|>cl... | code_fim | medium | {
"lang": "python",
"repo": "Today-to-Lsp/pythonanywhere",
"path": "/DataStorage/DataStorage/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: colibris-framework/colibris path: /colibris/authorization/role.py
from .base import AuthorizationBackend
# A permission is defined as the role of an account.
#
# The optional ordering defines a relation between roles; this allows specifying e.g. "admin" as required permission
# and assuming th... | code_fim | hard | {
"lang": "python",
"repo": "colibris-framework/colibris",
"path": "/colibris/authorization/role.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.role_field = role_field
self.order = order or [] # lower first, e.g. ["readonly", "regular", "admin"]
super().__init__(**kwargs)
def get_role(self, account):
return getattr(account, self.role_field)
def get_actual_permissions(self, account, method, path):
... | code_fim | medium | {
"lang": "python",
"repo": "colibris-framework/colibris",
"path": "/colibris/authorization/role.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class LeastMedianSquaresResults(NamedTuple):
slope: float
intercept: float
def least_median_squares(x, y, max_iter: int = 100):
check_consistent_length(x, y)
if x.ndim == 2:
if x.shape[1] == 1:
x = x.flatten()
else:
raise ValueError('x must be 1-d... | code_fim | hard | {
"lang": "python",
"repo": "EdgarTeixeira/dsul",
"path": "/dsul/linear_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EdgarTeixeira/dsul path: /dsul/linear_model.py
from typing import NamedTuple
from warnings import warn
import numpy as np
from scipy.optimize import basinhopping, minimize
from sklearn.base import BaseEstimator, RegressorMixin
from sklearn.utils import check_consistent_length, check_scalar, chec... | code_fim | hard | {
"lang": "python",
"repo": "EdgarTeixeira/dsul",
"path": "/dsul/linear_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with pytest.raises(TypeError):
# pretrained mast be a str or None
model = DetectoRS_ResNet(
**detectorrs_cfg, pretrained=['Pretrained'], init_cfg=None)
model.init_weights()<|fim_prefix|># repo: alldatacenter/alldata path: /ai/mmdetection/tests/test_models/test_back... | code_fim | hard | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/tests/test_models/test_backbones/test_detectors_resnet.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alldatacenter/alldata path: /ai/mmdetection/tests/test_models/test_backbones/test_detectors_resnet.py
# Copyright (c) OpenMMLab. All rights reserved.
import pytest
from mmdet.models.backbones import DetectoRS_ResNet
def test_detectorrs_resnet_backbone():
detectorrs_cfg = dict(
dept... | code_fim | hard | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/tests/test_models/test_backbones/test_detectors_resnet.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with pytest.raises(KeyError):
# init_cfg must contain the key `type`
DetectoRS_ResNet(
**detectorrs_cfg,
pretrained=None,
init_cfg=dict(checkpoint='Pretrained'))
with pytest.raises(AssertionError):
# init_cfg only support initialize pret... | code_fim | medium | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/tests/test_models/test_backbones/test_detectors_resnet.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertRendered('{% load fiber_tags %}{% fiber_version %}', str(fiber.__version__))<|fim_prefix|># repo: swdreams/django-fiber path: /testproject/fiber_test/tests/test_templatetags/test_fiber_version.py
import fiber
from django.test import SimpleTestCase
from ...test_util import RenderMixin
... | code_fim | medium | {
"lang": "python",
"repo": "swdreams/django-fiber",
"path": "/testproject/fiber_test/tests/test_templatetags/test_fiber_version.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: swdreams/django-fiber path: /testproject/fiber_test/tests/test_templatetags/test_fiber_version.py
import fiber
from django.test import SimpleTestCase
from ...test_util import RenderMixin
<|fim_suffix|> self.assertRendered('{% load fiber_tags %}{% fiber_version %}', str(fiber.__version__))... | code_fim | medium | {
"lang": "python",
"repo": "swdreams/django-fiber",
"path": "/testproject/fiber_test/tests/test_templatetags/test_fiber_version.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlexanderUstinovv/medical_test path: /medical_test/forms.py
from typing import List
from collections import namedtuple
import django.forms as forms
from django.forms.fields import Field
FLOAT_FILED = 'float_field'
STRING_FIELD = 'string_field'
INTEGER_FIELD = 'integer_field'
field_generators... | code_fim | hard | {
"lang": "python",
"repo": "AlexanderUstinovv/medical_test",
"path": "/medical_test/forms.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_field(field_description: FormFieldDescription) -> Field:
field_function = field_generators.get(field_description.field_type)
return field_function(field_description.label,
field_description.measurement)
def get_form(descriptions: List[FormFieldDescription]) -> ... | code_fim | hard | {
"lang": "python",
"repo": "AlexanderUstinovv/medical_test",
"path": "/medical_test/forms.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
def get_field(field_description: FormFieldDescription) -> Field:
field_function = field_generators.get(field_description.field_type)
return field_function(field_description.label,
field_description.measurement)
def get_form(descriptions: List[FormFieldDescrip... | code_fim | hard | {
"lang": "python",
"repo": "AlexanderUstinovv/medical_test",
"path": "/medical_test/forms.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: InnoFang/algo-set path: /LeetCode/0442. Find All Duplicates in an Array/solution.py
"""
28 / 28 test cases passed.
Runtime: 96 ms
Memory Usage: 21.1 MB
"""
class Solution:
<|fim_suffix|> ans = []
for num in nums:
num = abs(num)
if nums[num - 1] < 0:
... | code_fim | medium | {
"lang": "python",
"repo": "InnoFang/algo-set",
"path": "/LeetCode/0442. Find All Duplicates in an Array/solution.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ans = []
for num in nums:
num = abs(num)
if nums[num - 1] < 0:
ans.append(num)
else:
nums[num - 1] *= -1
return ans<|fim_prefix|># repo: InnoFang/algo-set path: /LeetCode/0442. Find All Duplicates in an Array/solu... | code_fim | medium | {
"lang": "python",
"repo": "InnoFang/algo-set",
"path": "/LeetCode/0442. Find All Duplicates in an Array/solution.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>gtail.core.blocks.TextBlock(label='Answer', required=True)), ('bullet_image', wagtail.images.blocks.ImageChooserBlock(label='Bullet image', required=False)), ('more_info_url', wagtail.core.blocks.URLBlock(help_text='A link to be followed for more information on that question, feature or product', label='U... | code_fim | hard | {
"lang": "python",
"repo": "thclark/wagtail_site_sections",
"path": "/wagtail_site_sections/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thclark/wagtail_site_sections path: /wagtail_site_sections/migrations/0001_initial.py
# Generated by Django 2.1.4 on 2019-05-24 17:16
from django.db import migrations, models
import django.db.models.deletion
import wagtail.core.blocks
import wagtail.core.fields
import wagtail.embeds.blocks
impor... | code_fim | hard | {
"lang": "python",
"repo": "thclark/wagtail_site_sections",
"path": "/wagtail_site_sections/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: desihub/desispec path: /bin/desi_proc_joint_fit
#!/usr/bin/env python
# small time jitter so MPI parallel imports don't hit the disk simultaneously
import time
import random
time.sleep(2*random.random())
<|fim_suffix|> args = proc_joint_fit.parse()
sys.exit(proc_joint_fit.main(args))<|fi... | code_fim | medium | {
"lang": "python",
"repo": "desihub/desispec",
"path": "/bin/desi_proc_joint_fit",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> args = proc_joint_fit.parse()
sys.exit(proc_joint_fit.main(args))<|fim_prefix|># repo: desihub/desispec path: /bin/desi_proc_joint_fit
#!/usr/bin/env python
# small time jitter so MPI parallel imports don't hit the disk simultaneously
import time
import random
time.sleep(2*random.random())
<|fi... | code_fim | medium | {
"lang": "python",
"repo": "desihub/desispec",
"path": "/bin/desi_proc_joint_fit",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if discipline not in self._marks[student]:
self._marks[student][discipline] = {}
self._marks[student][discipline] = mark
return Response(201, 'Created')
def send_response(self, conn, resp):
wfile = conn.makefile('wb')
status_line = f'HTTP/1.1 {res... | code_fim | hard | {
"lang": "python",
"repo": "EgorovM/ITMO_ICT_WebDevelopment_2021-2022",
"path": "/students/K33402/Prokhorov_Nikolay/LR1/task3/task3_server.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EgorovM/ITMO_ICT_WebDevelopment_2021-2022 path: /students/K33402/Prokhorov_Nikolay/LR1/task3/task3_server.py
import argparse
import json
import socket
from email.parser import Parser
from functools import lru_cache
from urllib.parse import parse_qs, urlparse
class HTTPError(Exception):
def ... | code_fim | hard | {
"lang": "python",
"repo": "EgorovM/ITMO_ICT_WebDevelopment_2021-2022",
"path": "/students/K33402/Prokhorov_Nikolay/LR1/task3/task3_server.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cbare/Etudes path: /python/big_tree.py
import random
EMPTY = tuple()
NUM_PROJECTS = 1000
class Folder:
def __init__(self, id, children=None):
<|fim_suffix|>
class Sequence:
def __init__(self, i=100001):
self.starting_value = i
self.i = i
def __next__(self):
t... | code_fim | medium | {
"lang": "python",
"repo": "cbare/Etudes",
"path": "/python/big_tree.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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