text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> statistics = {}
rankList = {}
# status == 1 mean Accepted
for submission in submissionList:
status = submission.status
if status != 1: status = 0
user_pid = (submission.user, submission.pid)
if statistics.has_key(user_pid):
statistics[user_pid] =... | code_fim | hard | {
"lang": "python",
"repo": "haihua-sysu/onlinejudge",
"path": "/web/contest/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> context = {'contest': contest, 'submissionList': submissionList}
return render_to_response('contest_submission.html', context, context_instance = RequestContext(request))
def solvedCount(val):
return val[1]
def SCORE(val):
return val[1]
def showOIStanding(request, cid):
res = canSho... | code_fim | hard | {
"lang": "python",
"repo": "haihua-sysu/onlinejudge",
"path": "/web/contest/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tensorflow/datasets path: /tensorflow_datasets/translate/mtnt/mtnt.py
# coding=utf-8
# Copyright 2023 The TensorFlow Datasets Authors.
#
# 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 ... | code_fim | hard | {
"lang": "python",
"repo": "tensorflow/datasets",
"path": "/tensorflow_datasets/translate/mtnt/mtnt.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> pair = f'{self.builder_config.src_lang}-{self.builder_config.dst_lang}'
return {
'train': self._generate_examples(path / f'MTNT/train/train.{pair}.tsv'),
'test': self._generate_examples(path / f'MTNT/test/test.{pair}.tsv'),
'valid': self._generate_examples(path / f'MTNT/val... | code_fim | hard | {
"lang": "python",
"repo": "tensorflow/datasets",
"path": "/tensorflow_datasets/translate/mtnt/mtnt.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Yields examples."""
with epath.Path(path).open() as f:
reader = csv.reader(f, delimiter='\t')
for row in reader:
if len(row) < 3:
logging.info('skipped row %s', row)
continue
key = hashlib.md5(','.join(row[0:3]).encode('utf-8')).hexdigest()
... | code_fim | hard | {
"lang": "python",
"repo": "tensorflow/datasets",
"path": "/tensorflow_datasets/translate/mtnt/mtnt.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __lt__(self, other):
if not isinstance(other, self.__class__):
return NotImplemented
return self.sort_key < other.sort_key
@property
def sort_key(self):
return (self.controller_num, self.channel, self.enclosure_id, self.target_id)
@property
... | code_fim | hard | {
"lang": "python",
"repo": "asciiphil/perc-status",
"path": "/perc-status",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asciiphil/perc-status path: /perc-status
""" Returns a string containing the binary representation of the given
integer. COUNT represents the number of digits that should be in the
output. If omitted, as few digits will be used as possible."""
if count == 0:
count = int(math... | code_fim | hard | {
"lang": "python",
"repo": "asciiphil/perc-status",
"path": "/perc-status",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asciiphil/perc-status path: /perc-status
'--omreport', default='omreport',
help='Location of the omreport program, if not in $PATH.')
option_parser.add_option('-c', '--controller', type='int',
help='Specific controller number to query. Default is... | code_fim | hard | {
"lang": "python",
"repo": "asciiphil/perc-status",
"path": "/perc-status",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>rec = musicbrainzngs.get_recording_by_id('9abfbf0b-ef05-4dfc-9177-17cc42dd3feb',includes=['artists','releases'])
track = rec['recording']
album = track['release-list'][0]['title']
artist = track['artist-credit-phrase']<|fim_prefix|># repo: rawdlite/mopidy-remote path: /tests/library_test.py
from __future... | code_fim | hard | {
"lang": "python",
"repo": "rawdlite/mopidy-remote",
"path": "/tests/library_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rawdlite/mopidy-remote path: /tests/library_test.py
from __future__ import unicode_literals
import datetime
import sys
sys.path.append('../mopidy_remote')
from library import RemoteLibrary
import musicbrainzngs
<|fim_suffix|>lib = RemoteplayLibrary(config)
musicbrainzngs.set_useragent('mopidy-he... | code_fim | medium | {
"lang": "python",
"repo": "rawdlite/mopidy-remote",
"path": "/tests/library_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> data = get_only_updated_values(instance, data)
if len(data) == 0:
return None
res = update_in_db(instance, data)
if res != 'updated':
set_session_var('errors', str(res))
return None
else:
set_session_var('success', ... | code_fim | hard | {
"lang": "python",
"repo": "ai-transparent/transparentai-ui",
"path": "/transparentai_ui/app/controllers/controller_class.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ai-transparent/transparentai-ui path: /transparentai_ui/app/controllers/controller_class.py
from flask import render_template, request, redirect, url_for, session
from flask_babel import _
from ..utils import set_session_var, check_if_session_var_exists
from ..utils.db import add_in_db, update_i... | code_fim | hard | {
"lang": "python",
"repo": "ai-transparent/transparentai-ui",
"path": "/transparentai_ui/app/controllers/controller_class.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yhz61010/jquery path: /build/downloadapi_for_exist_file.py
#!/usr/bin/python
# -*- coding: UTF-8 -*-
import codecs
import os,sys,re,time;
filename = r"../jQueryAPI.en_US.xml"
fileread = o<|fim_suffix|>Query Object Instances",filer,0); #替换stra 为 strb
sub = re.sub(r'(<entry.*?)(>)',r'\1 filename... | code_fim | medium | {
"lang": "python",
"repo": "yhz61010/jquery",
"path": "/build/downloadapi_for_exist_file.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ead.close();
fileok = open(filename,'w', encoding='utf-8');
fileok.write(sub);
fileok.close();
print(filename,'Replace successful.')<|fim_prefix|># repo: yhz61010/jquery path: /build/downloadapi_for_exist_file.py
#!/usr/bin/python
# -*- coding: UTF-8 -*-
import codecs
import os,sys,re,time;
filename = ... | code_fim | medium | {
"lang": "python",
"repo": "yhz61010/jquery",
"path": "/build/downloadapi_for_exist_file.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name="study",
name="coi_reported",
field=models.PositiveSmallIntegerField(
choices=[
(4, "---"),
(0, "Authors report they have no COI"),
(... | code_fim | hard | {
"lang": "python",
"repo": "shapiromatron/hawc",
"path": "/hawc/apps/study/migrations/0011_auto_20190416_2035.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shapiromatron/hawc path: /hawc/apps/study/migrations/0011_auto_20190416_2035.py
# Generated by Django 1.11.15 on 2019-04-17 01:35
from django.conf import settings
from django.db import migrations, models
def update_choices(apps, schema_editor):
if settings.HAWC_FLAVOR == "EPA":
app... | code_fim | hard | {
"lang": "python",
"repo": "shapiromatron/hawc",
"path": "/hawc/apps/study/migrations/0011_auto_20190416_2035.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hisahi/Nanibgal path: /application/view/feed.py
MSGS_PER_PAGE = 25
# (request.args, msgs_func, *func_args) -> (msgs, offset, next_page, prev_page)
def compute_pages(args, msgs_func, *func_args):
try:
before = max(0, int(args.get("b", None)))
except:
before = None
try... | code_fim | hard | {
"lang": "python",
"repo": "hisahi/Nanibgal",
"path": "/application/view/feed.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>f newest_id <= prev_page:
prev_page = None
else:
prev_page = None
if len(msgs) > MSGS_PER_PAGE:
next_page = msgs[MSGS_PER_PAGE]["id"]
msgs = msgs[:MSGS_PER_PAGE]
return msgs, next_page, prev_page<|fim_prefix|># repo: hisahi/Nanibgal path: /applicati... | code_fim | hard | {
"lang": "python",
"repo": "hisahi/Nanibgal",
"path": "/application/view/feed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: airbus-cert/regrippy path: /regrippy/plugins/mndmru.py
from regrippy import BasePlugin, PluginResult, mactime
class Plugin(BasePlugin):
"""Reads 'Map Network Drive MRU' key (Most Recently Used remote drives)"""
__REGHIVE__ = "NTUSER.DAT"
def run(self):
<|fim_suffix|> order ... | code_fim | medium | {
"lang": "python",
"repo": "airbus-cert/regrippy",
"path": "/regrippy/plugins/mndmru.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(
mactime(
name=f"{self.guess_username()}\t{result.value_data}", mtime=result.mtime
)
)<|fim_prefix|># repo: airbus-cert/regrippy path: /regrippy/plugins/mndmru.py
from regrippy import BasePlugin, PluginResult, mactime
class Plugin(BasePlugin... | code_fim | medium | {
"lang": "python",
"repo": "airbus-cert/regrippy",
"path": "/regrippy/plugins/mndmru.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for letter in order.value():
res = PluginResult(key=key, value=values[letter])
yield res
def display_human(self, result):
print(result.value_data)
def display_machine(self, result):
print(
mactime(
name=f"{self.guess_use... | code_fim | hard | {
"lang": "python",
"repo": "airbus-cert/regrippy",
"path": "/regrippy/plugins/mndmru.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bzaczynski/ogre path: /tests/pdf/test_canvas.py
m ipsum', 10, 10), places=2)
def test_should_return_cursor_position_of_longest_line_of_text(self):
canvas = Canvas()
canvas.font.size_pts = 6
self.assertAlmostEqual(76.24, canvas.text(self.TEXT, 10, 10), places=2)
d... | code_fim | hard | {
"lang": "python",
"repo": "bzaczynski/ogre",
"path": "/tests/pdf/test_canvas.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertAlmostEqual(34.58, x, places=2)
mock_obj.assert_called_once_with(28.34645669291339, 805.543307086614)
mock_obj.return_value.textLine.assert_has_calls([
mock.call('Lorem'),
mock.call('ipsum'),
mock.call('dolor sit'),
mock.c... | code_fim | hard | {
"lang": "python",
"repo": "bzaczynski/ogre",
"path": "/tests/pdf/test_canvas.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bzaczynski/ogre path: /tests/pdf/test_canvas.py
nvas.Canvas.setTitle')
def test_should_update_metadata(self,
mock_set_title,
mock_set_subject,
mock_set_keywords,
... | code_fim | hard | {
"lang": "python",
"repo": "bzaczynski/ogre",
"path": "/tests/pdf/test_canvas.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> eps = guess_epsilon.epsilon()
ret = eps.to_log10(10, 0.1)
assert_almost_equal(ret[0], 1.0, 0.01)
assert_almost_equal(ret[1], 0.01, 0.001)
def test_obs_to_log():
eps = guess_epsilon.epsilon()
obs = {'dnu': [10.0, 0.1],
'numax': [100.0, 1.0],
'teff': [4000.0, 1... | code_fim | hard | {
"lang": "python",
"repo": "darthoctopus/PBjam",
"path": "/pbjam/tests/test_epsilon_guess.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: darthoctopus/PBjam path: /pbjam/tests/test_epsilon_guess.py
from __future__ import division, print_function
import pytest
import numpy as np
from numpy.testing import (assert_almost_equal, assert_array_equal,
assert_allclose)
from pbjam import guess_epsilon
def test_... | code_fim | hard | {
"lang": "python",
"repo": "darthoctopus/PBjam",
"path": "/pbjam/tests/test_epsilon_guess.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def name(self):
return self._name
@property
def dtype(self):
return dtypes.int64
@property
def is_reparameterized(self):
return False
def batch_shape(self, name="batch_shape"):
with ops.name_scope(self.name):
return array_ops.identity(self._batch_shape, nam... | code_fim | hard | {
"lang": "python",
"repo": "agrawalnishant/tensorflow",
"path": "/tensorflow/contrib/distributions/python/ops/categorical.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agrawalnishant/tensorflow path: /tensorflow/contrib/distributions/python/ops/categorical.py
# Copyright 2016 Google Inc. 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 c... | code_fim | hard | {
"lang": "python",
"repo": "agrawalnishant/tensorflow",
"path": "/tensorflow/contrib/distributions/python/ops/categorical.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Sample `n` observations from the Categorical distribution.
Args:
n: 0-D. Number of independent samples to draw for each distribution.
seed: Random seed (optional).
name: A name for this operation (optional).
Returns:
An `int64` `Tensor` with shape `[n, batch_shape... | code_fim | hard | {
"lang": "python",
"repo": "agrawalnishant/tensorflow",
"path": "/tensorflow/contrib/distributions/python/ops/categorical.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Cap-n-Proud/Bailey_2 path: /units/easy_driver_test.py
# 31 dir
# 33 steps
import time
import random
import Easy_Driver as es
import RPi.GPIO as GPIO
en = 19
step = 21
dir = 23
en = 26
step = 24
dir = 22
<|fim_suffix|>motor_A.set_speed(speed)
# while i < 1000:
#
# motor_A.step()
#
# ... | code_fim | hard | {
"lang": "python",
"repo": "Cap-n-Proud/Bailey_2",
"path": "/units/easy_driver_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>motor_A.set_speed(speed)
# while i < 1000:
#
# motor_A.step()
#
# i += 1
#
# motor_A.disable()
print("all finished")
motor_A.print_info()
motor_A.set_target(90)
i = 0
while i < 1000:
motor_A.step_to_target()
# print(round(motor_A.steps_to_go(), 2), motor_A.current_pos)
i += 1<|fim_... | code_fim | hard | {
"lang": "python",
"repo": "Cap-n-Proud/Bailey_2",
"path": "/units/easy_driver_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> cate = [path + x for x in os.listdir(path) if os.path.isdir(path + x)]
cate.sort()
record = getrecord(record_path)
label = getlabel(label_path)
for idx, folder in enumerate(cate):
L = len([name for name in os.listdir(folder) if os.path.isfile(os.path.join(folder, name))])
... | code_fim | hard | {
"lang": "python",
"repo": "githubhjx/Deep-Learning",
"path": "/pythonFilep/pain_cut.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: githubhjx/Deep-Learning path: /pythonFilep/pain_cut.py
# This is a Pain Dataset cut program
# Created by JiaxuHan at 2018/11/19
import os
import glob
import shutil
record_path = '/home/s2/data/Pain/records.txt'
label_path = '/home/s2/data/Pain/label.txt'
img_path = '/home/s2/data/Pain/79/'
o... | code_fim | hard | {
"lang": "python",
"repo": "githubhjx/Deep-Learning",
"path": "/pythonFilep/pain_cut.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for idx, folder in enumerate(cate):
L = len([name for name in os.listdir(folder) if os.path.isfile(os.path.join(folder, name))])
temp = glob.glob(folder + '/*.png')
temp.sort()
for i, j in zip(range(0, len(record[idx]), 2), range(1, len(record[idx]), 2)):
l... | code_fim | hard | {
"lang": "python",
"repo": "githubhjx/Deep-Learning",
"path": "/pythonFilep/pain_cut.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>result = nfa.match(args.regex, args.text)
if args.verbose:
if result == False:
print("The text " + args.text + \
" does not match the regular expression " + args.regex)
else:
print("The text " + args.text + \
" matches the regular expression " + args.re... | code_fim | hard | {
"lang": "python",
"repo": "charlieconneely/regex_nfa",
"path": "/runner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if args.verbose:
if result == False:
print("The text " + args.text + \
" does not match the regular expression " + args.regex)
else:
print("The text " + args.text + \
" matches the regular expression " + args.regex)
elif args.quiet:
print(str(result)... | code_fim | medium | {
"lang": "python",
"repo": "charlieconneely/regex_nfa",
"path": "/runner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: charlieconneely/regex_nfa path: /runner.py
# Charlie Conneely
# Runner program
import argparse
import nfa
parser = argparse.ArgumentParser()
group = parser.add_mutually_exclusive_group()
<|fim_suffix|>if args.verbose:
if result == False:
print("The text " + args.text + \
... | code_fim | hard | {
"lang": "python",
"repo": "charlieconneely/regex_nfa",
"path": "/runner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self):
super(refinement, self).__init__()
self.conv1 = nn.Sequential(
nn.Conv2d(4, 64, 3, stride=1, padding=1),
nn.ReLU()
)
self.conv2 = nn.Sequential(
nn.Conv2d(64, 64, 3, stride=1, padding=1),
nn.ReLU()
... | code_fim | hard | {
"lang": "python",
"repo": "wyk0517/image-matting-experiment",
"path": "/model/part_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wyk0517/image-matting-experiment path: /model/part_model.py
# -*- coding: utf-8 -*-
import torch.nn as nn
import torch
import torch.nn.functional as F
from base import BaseModel
import torchvision.models as models
def architecture_transform(model, backbone=models.vgg16(pretrained=True)):
# ... | code_fim | hard | {
"lang": "python",
"repo": "wyk0517/image-matting-experiment",
"path": "/model/part_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class refinement(nn.Module):
def __init__(self):
super(refinement, self).__init__()
self.conv1 = nn.Sequential(
nn.Conv2d(4, 64, 3, stride=1, padding=1),
nn.ReLU()
)
self.conv2 = nn.Sequential(
nn.Conv2d(64, 64, 3, stride=1, padding=... | code_fim | hard | {
"lang": "python",
"repo": "wyk0517/image-matting-experiment",
"path": "/model/part_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ggirlk/python-bigO-calculator path: /tests/test_compare.py
from bigO import bigO
from bigO import algorithm
def test_run():
lib = bigO()
result = lib.compare(algorithm.bubbleSort, algorithm.insertSort, "reversed", 5000)
result = lib.compare(
algorithm.insertSort, algorithm.... | code_fim | hard | {
"lang": "python",
"repo": "ggirlk/python-bigO-calculator",
"path": "/tests/test_compare.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_all():
lib = bigO()
result = lib.compare(
algorithm.quickSortHoare, algorithm.quickSortHeap, "all", 50000
)
result = lib.compare(algorithm.insertSort, algorithm.bubbleSort, "all", 5000)
print(result)
result = lib.compare(algorithm.quickSortHoare, algorithm.inser... | code_fim | hard | {
"lang": "python",
"repo": "ggirlk/python-bigO-calculator",
"path": "/tests/test_compare.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> lib.compare(algorithm.bubbleSort, algorithm.insertSort, "reversed", 16)
lib.compare(algorithm.insertSort, algorithm.selectionSort, "reversed", 16)
lib.compare(algorithm.bubbleSort, algorithm.selectionSort, "reversed", 16)
def test_all():
lib = bigO()
result = lib.compare(
alg... | code_fim | hard | {
"lang": "python",
"repo": "ggirlk/python-bigO-calculator",
"path": "/tests/test_compare.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: STAR-TIDES/kb path: /star_tides/core/actions/create_project_action.py
'''star_tides.core.actions.create_project_action
'''
from marshmallow.exceptions import ValidationError
from star_tides.services.databases.mongo.schemas.project_schema import ProjectSchema
from star_tides.services.databases.mo... | code_fim | hard | {
"lang": "python",
"repo": "STAR-TIDES/kb",
"path": "/star_tides/core/actions/create_project_action.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.project = project
def run(self):
if self.project.id is not None:
raise InvalidParamError('Expected project not to have ID.')
schema = {}
try:
schema = ProjectSchema().load(self.project._asdict())
except ValidationError as e:
... | code_fim | medium | {
"lang": "python",
"repo": "STAR-TIDES/kb",
"path": "/star_tides/core/actions/create_project_action.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return operator
def taper_clifford(self, operator: PauliSumOp) -> OperatorBase:
"""This method operates the second part of the tapering.
This function assumes that the input operators have already been transformed using
:meth:`convert_clifford`. The redundant qubits du... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/opflow/primitive_ops/tapered_pauli_sum_op.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 1ucian0/qiskit-terra path: /qiskit/opflow/primitive_ops/tapered_pauli_sum_op.py
t],
tapering_values: Optional[List[int]] = None,
tol: float = 1e-14,
):
"""
Args:
symmetries: the list of Pauli objects representing the Z_2 symmetries
sq_pa... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/opflow/primitive_ops/tapered_pauli_sum_op.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 1ucian0/qiskit-terra path: /qiskit/opflow/primitive_ops/tapered_pauli_sum_op.py
class TaperedPauliSumOp(PauliSumOp):
"""Deprecated: Class for PauliSumOp after tapering"""
@deprecate_func(
since="0.24.0",
additional_msg="For code migration guidelines, visit https://qisk... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/opflow/primitive_ops/tapered_pauli_sum_op.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ArthurGorgonio/suggestclasses path: /core/tests/test_sugestao.py
import django
django.setup()
from django.contrib.auth.models import User
from core.bo.sevices import get_estrutura_by_id
from core.bo.turma import get_sugestao_turmas, carrega_turmas_horario, carrega_sugestao_turmas, \
converte... | code_fim | hard | {
"lang": "python",
"repo": "ArthurGorgonio/suggestclasses",
"path": "/core/tests/test_sugestao.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().setUpClass()
print('\nSugestaoTests')
criar_dados()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
remover_dados()
def test_get_sugestao(self):
estrutura = get_estrutura_by_id(999999999)
sugestao1 = SugestaoTurma.o... | code_fim | hard | {
"lang": "python",
"repo": "ArthurGorgonio/suggestclasses",
"path": "/core/tests/test_sugestao.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cdeil/astrometric_checks path: /test_pointing.py
"""Checks of the pointing table from HESS.
"""
from gammapy.data import PointingInfo
def check_pointing_info():
pointing_info = PointingInfo.read('hess_event_list.fits')
print(pointing_info)
# Check altaz coordinates from HESS softwa... | code_fim | medium | {
"lang": "python",
"repo": "cdeil/astrometric_checks",
"path": "/test_pointing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>START:
Time: 2004-01-21T19:50:02.184(TT)
Time: 53025.826414166666 MJD (TT)
RADEC: 83.6333 24.5144 deg
ALTAZ: 11.2043 41.3792 deg
END:
Time: 2004-01-21T20:16:28.184(TT)
Time: 53025.844770648146 MJD (TT)
RADEC: 83.6333 24.5144 deg
ALTAZ: 3.18474 42.1431 deg
sky_diff: 697.907arcsec 697.909arcsec
a... | code_fim | hard | {
"lang": "python",
"repo": "cdeil/astrometric_checks",
"path": "/test_pointing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
END:
Time: 2004-01-21T20:16:28.184(TT)
Time: 53025.844770648146 MJD (TT)
RADEC: 83.6333 24.5144 deg
ALTAZ: 3.18474 42.1431 deg
sky_diff: 697.907arcsec 697.909arcsec
az_diff: 911.484arcsec 939.596arcsec
alt_diff: -137.97arcsec -40.2693arcsec
time diff: 0h01m00.7656s 0h01m02.6397s
"""
if __na... | code_fim | hard | {
"lang": "python",
"repo": "cdeil/astrometric_checks",
"path": "/test_pointing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HelloKuki/autoupdateServer path: /apkinfo/urls.py
from django.conf.urls import url
from django.contrib import admin
<|fim_suffix|>urlpatterns = [
url(r'^createAppInfo', views.createAppInfo.as_view()),
url(r'^uploadAppIcon', views.uploadAppIcon.as_view()),
url(r'^uploadApkFile', views... | code_fim | easy | {
"lang": "python",
"repo": "HelloKuki/autoupdateServer",
"path": "/apkinfo/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = [
url(r'^createAppInfo', views.createAppInfo.as_view()),
url(r'^uploadAppIcon', views.uploadAppIcon.as_view()),
url(r'^uploadApkFile', views.uploadApkFile.as_view()),
url(r'^explainApk', views.explainApk.as_view()),
url(r'^releaseVersion', views.releaseVersion.as_view()),... | code_fim | easy | {
"lang": "python",
"repo": "HelloKuki/autoupdateServer",
"path": "/apkinfo/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='Leave',
fields=[
('id',models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False, verbose_name='ID')),
],
),
migrations.CreateModel(
name='... | code_fim | hard | {
"lang": "python",
"repo": "Iamdavidonuh/REQAP",
"path": "/activities/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Iamdavidonuh/REQAP path: /activities/migrations/0001_initial.py
# Generated by Django 3.0.4 on 2020-04-15 21:39
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
import uuid
class Migration(migrations.Migrati... | code_fim | hard | {
"lang": "python",
"repo": "Iamdavidonuh/REQAP",
"path": "/activities/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: googleapis/python-bigtable path: /tests/unit/test_row_merger.py
import os
from itertools import zip_longest
from typing import List
import proto
import pytest
from google.cloud.bigtable.row_data import PartialRowsData, PartialRowData, InvalidChunk
from google.cloud.bigtable_v2.types.bigtable im... | code_fim | hard | {
"lang": "python",
"repo": "googleapis/python-bigtable",
"path": "/tests/unit/test_row_merger.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with pytest.raises(InvalidChunk):
_process_chunks(
ReadRowsResponse.CellChunk(
row_key=b"a",
family_name="f",
qualifier=b"q",
timestamp_micros=1000,
value_size=2,
value=b"v",
... | code_fim | hard | {
"lang": "python",
"repo": "googleapis/python-bigtable",
"path": "/tests/unit/test_row_merger.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ccr5/BlackJack path: /tests/review.py
import unittest
import bot
import cards
import dealer
import deck
import players
class TestBlackJack(unittest.TestCase):
# Bot unittests
def bot_play_game(self):
npc = bot.Bot('test', 100)
npc.hand.append(["Aces", [1, 11], "A"], ["T... | code_fim | medium | {
"lang": "python",
"repo": "ccr5/BlackJack",
"path": "/tests/review.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> npc = deck.Deck()
result = npc.create_deck()
self.assertEqual(len(result), 52)
def deck_shuffle_deck(self):
npc = deck.Deck()
result1 = npc.create_deck()
result2 = npc.shuffle_deck()
self.assertEqual(len(result1), len(result2))
if __name__ == ... | code_fim | hard | {
"lang": "python",
"repo": "ccr5/BlackJack",
"path": "/tests/review.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # build dic2
l1=random.sample(nameObj, n2)
l2=random.sample(nameNonObj, n2)
if (verbose >= 2):
print 'dic2: ', l1, l2
dic2[name] = l1
for i in l1:
nameObj.remove(i)
for (k, i) in l2:
if not (dic2.has_key(k)):
dic2[k]=[]
dic2[k].append... | code_fim | hard | {
"lang": "python",
"repo": "baaslaawe/speaker-recognition-2",
"path": "/split.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: baaslaawe/speaker-recognition-2 path: /split.py
# -*- coding: utf-8 -*-
from __future__ import division #division en flottants par défaut
import random
#Split the dictionary into 3 disjoint dictionaries
#A dictionary is balanced if the number of name's objects is roughly equal to the number of n... | code_fim | hard | {
"lang": "python",
"repo": "baaslaawe/speaker-recognition-2",
"path": "/split.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if(t == 0):
loop = False
else:
pt = p
loop1 = True
print(f'Progressão finalizada com {counter} termos mostrados')<|fim_prefix|># repo: henriquekirchheck/Curso-em-Video-Python path: /desafio/desafio062.py
print('=====================')
print(' 10 Termos de um PA')
pr... | code_fim | medium | {
"lang": "python",
"repo": "henriquekirchheck/Curso-em-Video-Python",
"path": "/desafio/desafio062.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: henriquekirchheck/Curso-em-Video-Python path: /desafio/desafio062.py
print('=====================')
print(' 10 Termos de um PA')
print('=====================')
loop = True
loop1 = True
p = int(input('Primeiro Termo: '))
pt = p
r = int(input('Razão: '))
t = 10
counter = 0
while(loop == True):
... | code_fim | medium | {
"lang": "python",
"repo": "henriquekirchheck/Curso-em-Video-Python",
"path": "/desafio/desafio062.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#erorr
error = 0
for i in range(0, len(reproducedAnalog)):
error += int(math.fabs(reproducedAnalog[i] - samples[i]))
print("Level, Analog, Digital: ",levelsOfSamples)
print("Digital Form: ",digitalForm)
print("Reproduced Analog: ",reproducedAnalog)
print("Total Error: ",error)<|fim_prefix|># repo: ol... | code_fim | hard | {
"lang": "python",
"repo": "olagalal/multimedia-tasks",
"path": "/quantization.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: olagalal/multimedia-tasks path: /quantization.py
import math
# samples = [550, 600, -100, 150, -300, 900, 0, 850]
# bitLevel = 2
samples = []
bitLevel = 0
userInput = input("Enter samples: ")
temp = ""
for i in range(0, len(userInput)):
if userInput[i] == " ":
samples += [int(temp... | code_fim | hard | {
"lang": "python",
"repo": "olagalal/multimedia-tasks",
"path": "/quantization.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: atniptw/shiny-robot path: /Sportz/killersports/killersportsteam.py
from datetime import date
import requests
BASE_URL = "http://api.sportsdatabase.com/nfl/query.json"
class KillerSportsTeam:
def __init__(self, team, season):
self.team = team
self.season = season
def ge... | code_fim | medium | {
"lang": "python",
"repo": "atniptw/shiny-robot",
"path": "/Sportz/killersports/killersportsteam.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> query = "division@team={0} and season={1}".format(self.team, self.season)
payload = {"output": "json", "api_key": "guest", "sdql": query}
result = requests.get(BASE_URL, params=payload)
jsonResult = self._format_string_to_JSON(result.text)
return jsonResult['groups... | code_fim | hard | {
"lang": "python",
"repo": "atniptw/shiny-robot",
"path": "/Sportz/killersports/killersportsteam.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return jsonResult['groups'][0]['columns'][0][0]
def get_team_opponent(self, week):
return self._get_game_parameter("o:team", week)
def _get_game_parameter(self, parameter, week):
query = "{0}@team={1} and season={2} and week={3}".format(parameter, self.team, self.season, ... | code_fim | hard | {
"lang": "python",
"repo": "atniptw/shiny-robot",
"path": "/Sportz/killersports/killersportsteam.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>m
from .pso import ParticleSwarmOptimization
from .sa import SimulatedAnnealing
from .two_opt import TwoOpt<|fim_prefix|># repo: shubhampachori12110095/tsp-solvers path: /tsp_solvers/methods/__init__.py
from .aco import AntColonyOptimization
from .ga impor<|fim_middle|>t GeneticAlgorithm
from .lp import ... | code_fim | easy | {
"lang": "python",
"repo": "shubhampachori12110095/tsp-solvers",
"path": "/tsp_solvers/methods/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shubhampachori12110095/tsp-solvers path: /tsp_solvers/methods/__init__.py
from .aco import AntColonyOptimization
from .ga impor<|fim_suffix|> import SimulatedAnnealing
from .two_opt import TwoOpt<|fim_middle|>t GeneticAlgorithm
from .lp import LinearIntegerProgram
from .pso import ParticleSwarmOp... | code_fim | medium | {
"lang": "python",
"repo": "shubhampachori12110095/tsp-solvers",
"path": "/tsp_solvers/methods/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data['supervisors'] = data['supervisors'].apply(split_entry)
data['keywords'] = data['keywords'].apply(split_entry)
data['skills'] = data.apply(
lambda row: {
'required': split_entry(row['required_skills']),
'preferred': split_entry(row['preferred_skills']) }, ... | code_fim | hard | {
"lang": "python",
"repo": "guillep/pharo-project-proposals",
"path": "/converter/XLS2JSON/convert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guillep/pharo-project-proposals path: /converter/XLS2JSON/convert.py
import pandas as pd
DIR = '../../website/data/'
FILE_IN = DIR + 'ideas.xlsx'
FILE_OUT = 'ideas.json'
def split_entry(string):
return [each.strip() for each in string.split(',')]
<|fim_suffix|> data['skills'] = data.a... | code_fim | hard | {
"lang": "python",
"repo": "guillep/pharo-project-proposals",
"path": "/converter/XLS2JSON/convert.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data['skills'] = data.apply(
lambda row: {
'required': split_entry(row['required_skills']),
'preferred': split_entry(row['preferred_skills']) }, axis=1)
data['size'] = data['size'].apply(lambda x: x.split()[0])
data['difficulty'] = data['difficulty'].apply(lamb... | code_fim | hard | {
"lang": "python",
"repo": "guillep/pharo-project-proposals",
"path": "/converter/XLS2JSON/convert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OPI-PIB/jupyter-edx-grader-xblock path: /xblock_jupyter_graded/config.py
"""Application config"""
# Root directory where nbgrader data will be stored in EdX
EDX_ROOT = "/var/www/nbgrader/courses/"
<|fim_suffix|># nbgrader directory names - these are the default names nbgrader expects
# but coul... | code_fim | medium | {
"lang": "python",
"repo": "OPI-PIB/jupyter-edx-grader-xblock",
"path": "/xblock_jupyter_graded/config.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># nbgrader directory names - these are the default names nbgrader expects
# but could be mofied in nbgrader config and those reflected here if so desired
RELEASE = "release"
SOURCE = "source"
SUBMITTED = "submitted"
AUTOGRADED = "autograded"
FEEDBACK = "feedback"<|fim_prefix|># repo: OPI-PIB/jupyter-edx-g... | code_fim | medium | {
"lang": "python",
"repo": "OPI-PIB/jupyter-edx-grader-xblock",
"path": "/xblock_jupyter_graded/config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aio-libs/aiopg path: /tests/test_pool.py
import asyncio
from unittest import mock
import pytest
from psycopg2.extensions import TRANSACTION_STATUS_INTRANS
import aiopg
from aiopg.connection import TIMEOUT, Connection
from aiopg.pool import Pool
async def test_create_pool(create_pool):
poo... | code_fim | hard | {
"lang": "python",
"repo": "aio-libs/aiopg",
"path": "/tests/test_pool.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> conn1, conn2, conn3 = await asyncio.gather(fut1, fut2, fut3)
assert 3 == pool.size
assert 0 == pool.freesize
assert {conn1, conn2, conn3} == pool._used
pool.release(conn1)
assert 3 == pool.size
assert 1 == pool.freesize
assert {conn2, conn3} == pool._used
pool.release... | code_fim | hard | {
"lang": "python",
"repo": "aio-libs/aiopg",
"path": "/tests/test_pool.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> res = CommandBlock()
res += self
res += arg
return res
def __iadd__(self, arg):
if arg is None:
return self
if isinstance(arg, str):
self.__commands.extend(arg.split('\n'))
return self
try:
self.__... | code_fim | hard | {
"lang": "python",
"repo": "serl/topoblocktest",
"path": "/lib/bash.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: serl/topoblocktest path: /lib/bash.py
import os
import re
import subprocess
from tempfile import NamedTemporaryFile
class CommandBlock:
__timeout_re = re.compile(r"\s+timeout\s+.*?(\d+)")
@classmethod
def root_check(cls):
return cls() + 'if [ $EUID -ne 0 ]; then echo "root ... | code_fim | hard | {
"lang": "python",
"repo": "serl/topoblocktest",
"path": "/lib/bash.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: idkwim/CryptoAttacks path: /CryptoAttacks/tests/test_Hash.py
#!/usr/bin/env python
from __future__ import print_function
from CryptoAttacks.Hash import *
import hashlib
def test_sha1():
print("Test: sha1")
for x in range(30):
tmp = random_str(random.randint(0, 256))
as... | code_fim | hard | {
"lang": "python",
"repo": "idkwim/CryptoAttacks",
"path": "/CryptoAttacks/tests/test_Hash.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_length_extension():
print("Test length extension sha1")
for x in range(30):
secret = random_str(random.randint(0, 130))
new_message = random_str(random.randint(0, 130))
old_hash = sha1(secret)
new_hash, new_data = length_extension(old_hash, len(secret), ne... | code_fim | hard | {
"lang": "python",
"repo": "idkwim/CryptoAttacks",
"path": "/CryptoAttacks/tests/test_Hash.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Test length extension md4")
for x in range(30):
secret = random_str(random.randint(0, 130))
new_message = random_str(random.randint(0, 130))
old_hash = md4(secret)
new_hash, new_data = length_extension(old_hash, len(secret), new_message, type='md4')
a... | code_fim | hard | {
"lang": "python",
"repo": "idkwim/CryptoAttacks",
"path": "/CryptoAttacks/tests/test_Hash.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> secret_type = "Azure SAS Token"
denylist = [
re.compile(r"(?=.*sv=*)(?=.*&se=*)(?=.*&sig=[\%0-9a-zA-Z]{20})"),
]<|fim_prefix|># repo: flecoqui/azure-detect-secrets path: /pipelines/detect-secrets/plugins/azuresas.py
# ------------------------------------------------------------------... | code_fim | medium | {
"lang": "python",
"repo": "flecoqui/azure-detect-secrets",
"path": "/pipelines/detect-secrets/plugins/azuresas.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: flecoqui/azure-detect-secrets path: /pipelines/detect-secrets/plugins/azuresas.py
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# lic... | code_fim | medium | {
"lang": "python",
"repo": "flecoqui/azure-detect-secrets",
"path": "/pipelines/detect-secrets/plugins/azuresas.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tuetschek/GEM-metrics path: /gem_metrics/bleu.py
#!/usr/bin/env python3
from .metric import ReferencedMetric
import sacrebleu
from itertools import zip_longest
<|fim_suffix|> ref_streams = list(zip_longest(*references.untokenized))
bleu = sacrebleu.corpus_bleu(predictions.untoken... | code_fim | medium | {
"lang": "python",
"repo": "tuetschek/GEM-metrics",
"path": "/gem_metrics/bleu.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def compute(self, predictions, references):
ref_streams = list(zip_longest(*references.untokenized))
bleu = sacrebleu.corpus_bleu(predictions.untokenized, ref_streams, lowercase=True)
return {'bleu': bleu.score}<|fim_prefix|># repo: tuetschek/GEM-metrics path: /gem_metrics/ble... | code_fim | medium | {
"lang": "python",
"repo": "tuetschek/GEM-metrics",
"path": "/gem_metrics/bleu.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aladshaw3/cats path: /scripts/python/labview_processing/specific_data_scripts/PureFuels_data_processing.py
out (C)', 'P tup in (bar)', 'P top out (bar)', 'NH3 (3000,300)', 'CO (500,10000)', 'Ethanol (1000,10000)', 'CH4 (250,3000)']
# methylisobutylketone
if base_folder == "MIBK":
... | code_fim | hard | {
"lang": "python",
"repo": "aladshaw3/cats",
"path": "/scripts/python/labview_processing/specific_data_scripts/PureFuels_data_processing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> run.append(readCoOptimaFile(folder+"/"+run_name, folder+"/"+bypass_name))
avg_run = readCoOptimaFile(folder+"/"+run_name, folder+"/"+bypass_name)
bypass_name = "20170804-CPTMA-MalibuTWC-SGDI-30k-2Pentaone-5Cramp-lambda0_999-bp-2"
run_name = "20170804-CPTMA-MalibuTWC-SGD... | code_fim | hard | {
"lang": "python",
"repo": "aladshaw3/cats",
"path": "/scripts/python/labview_processing/specific_data_scripts/PureFuels_data_processing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nihirsingh29/HCRSimPY path: /HCRSimPY/light_schedules/__init__.py
#This will load in some functions to the nam<|fim_suffix|>ghtSchedule import *
from ..plots import *
from ..utils import *
from ..models import *<|fim_middle|>espace when the
#package is loaded
from .Li | code_fim | easy | {
"lang": "python",
"repo": "nihirsingh29/HCRSimPY",
"path": "/HCRSimPY/light_schedules/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>rom ..utils import *
from ..models import *<|fim_prefix|># repo: nihirsingh29/HCRSimPY path: /HCRSimPY/light_schedules/__init__.py
#This will load in some functions to the namespace when the
#package is loaded
from .Li<|fim_middle|>ghtSchedule import *
from ..plots import *
f | code_fim | easy | {
"lang": "python",
"repo": "nihirsingh29/HCRSimPY",
"path": "/HCRSimPY/light_schedules/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def parse_variable(parsed_tokens):
return Variable(parsed_tokens[0])<|fim_prefix|># repo: SeerZero/synet path: /synet/translation/variable.py
class Variable:
def __init__(self, name):
self.name = name
self.is_variable = True
self.is_constant = False
if self.name == '_':
self.wil... | code_fim | hard | {
"lang": "python",
"repo": "SeerZero/synet",
"path": "/synet/translation/variable.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SeerZero/synet path: /synet/translation/variable.py
class Variable:
def __init__(self, name):
self.name = name
self.is_variable = True
self.is_constant = False
if self.name == '_':
self.wildcard = True
else:
self.wildcard = False
def __str__(self):
r... | code_fim | medium | {
"lang": "python",
"repo": "SeerZero/synet",
"path": "/synet/translation/variable.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> comments_map = {}
root_header = None
root_comment = None
for comment in self.comments():
dot()
if root_header is None or root_header.object_id != comment.nid:
root_comment = Comment.objects.get_or_create_root_comment(self.node_ctype, comment.nid)[0]
update_comments_header(Comment, in... | code_fim | hard | {
"lang": "python",
"repo": "LinuxOSsk/Shakal-NG",
"path": "/blackhole/management/commands/import_blackhole.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def sync_comment(self):
comments_map = {}
root_header = None
root_comment = None
for comment in self.comments():
dot()
if root_header is None or root_header.object_id != comment.nid:
root_comment = Comment.objects.get_or_create_root_comment(self.node_ctype, comment.nid)[0]
update_co... | code_fim | hard | {
"lang": "python",
"repo": "LinuxOSsk/Shakal-NG",
"path": "/blackhole/management/commands/import_blackhole.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LinuxOSsk/Shakal-NG path: /blackhole/management/commands/import_blackhole.py
# -*- coding: utf-8 -*-
import subprocess
import sys
from collections import namedtuple
from datetime import datetime
from os import path
import pytz
from django.conf import settings
from django.contrib.contenttypes.mod... | code_fim | hard | {
"lang": "python",
"repo": "LinuxOSsk/Shakal-NG",
"path": "/blackhole/management/commands/import_blackhole.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def stem(word):
"""
stemming = tìm dạng gốc của từ
ví dụ:
từ = ["tổ chức", "tổ chức", "tổ chức"]
words = [gốc (w) cho w trong từ]
-> ["organ", "organ", "organ"]
"""
return stemmer.stem(word.lower())
def bag_of_words(tokenized_sentence, words):
"""
trả về mảng các... | code_fim | medium | {
"lang": "python",
"repo": "Lanh2208/android",
"path": "/python_fun/chatbot-gui/nltk_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
trả về mảng các từ:
1 cho mỗi từ đã biết tồn tại trong câu, 0 nếu không
thí dụ:
câu = ["xin chào", "như thế nào", "là", "bạn"]
words = ["xin chào", "xin chào", "tôi", "bạn", "tạm biệt", "cảm ơn", "tuyệt"]
bog = [0, 1, 0, 1, 0, 0, 0]
"""
# ngắt từng từ
sentence_w... | code_fim | hard | {
"lang": "python",
"repo": "Lanh2208/android",
"path": "/python_fun/chatbot-gui/nltk_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lanh2208/android path: /python_fun/chatbot-gui/nltk_utils.py
import numpy as np
#NLTK là gì? NLTK là một thư viện python tiêu chuẩn với các chức năng và tiện ích được tạo sẵn để dễ sử dụng và triển khai. Nó là một trong những thư viện được sử dụng nhiều nhất để xử lý ngôn ngữ tự nhiên và ngôn ngữ... | code_fim | hard | {
"lang": "python",
"repo": "Lanh2208/android",
"path": "/python_fun/chatbot-gui/nltk_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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