text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> create_dir(OUTPUT_DIR)
soup = get_soup(SOURCE, session)
link = soup.find('div', {'id': 'divid'}).find('div')['ng-include'].replace('\'', '')
link = PARENT_SOURCES[1] + link
soup = get_soup(link, session)
file_url = PARENT_SOURCES[0] + soup.find_all('a')[0]['href'][2:]
zip_filen... | code_fim | medium | {
"lang": "python",
"repo": "themousepotato/unscrapulous",
"path": "/unscrapulous/scrapers/sebi_debarred_bse.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> alias = {
'PAN': 'PAN No.',
'Name': 'Scrip Name /Entity',
'AddedDate': 'Date of Order '
}
write_to_db(conn, os.path.join(OUTPUT_DIR, OUTPUT_FILE), SOURCE, alias)<|fim_prefix|># repo: themousepotato/unscrapulous path: /unscrapulous/scrapers/sebi_debarred_bse.py
#!/usr/b... | code_fim | hard | {
"lang": "python",
"repo": "themousepotato/unscrapulous",
"path": "/unscrapulous/scrapers/sebi_debarred_bse.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: estebango/coding-skills-sample-code path: /coding202-parsing-json/get-cmx-json.py
from urllib.request import Request, urlopen
import json
<|fim_suffix|>jsonObject = json.loads(responseString)
print(json.dumps(jsonObject, sort_keys=True, indent=4))
response.close()<|fim_middle|>req = Request('h... | code_fim | hard | {
"lang": "python",
"repo": "estebango/coding-skills-sample-code",
"path": "/coding202-parsing-json/get-cmx-json.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(json.dumps(jsonObject, sort_keys=True, indent=4))
response.close()<|fim_prefix|># repo: estebango/coding-skills-sample-code path: /coding202-parsing-json/get-cmx-json.py
from urllib.request import Request, urlopen
import json
req = Request('https://devnetapi.cisco.com/sandbox/mse/api/config/v1/ma... | code_fim | medium | {
"lang": "python",
"repo": "estebango/coding-skills-sample-code",
"path": "/coding202-parsing-json/get-cmx-json.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.linkedlist.isempty()
def display(self):
self.linkedlist.display()<|fim_prefix|># repo: aashishogale/DataStructurePrograms-Python- path: /com/bridgelabz/utility/queue.py
from com.bridgelabz.utility.linkedlist import LinkedList
class Queue:
linkedlist=LinkedList... | code_fim | hard | {
"lang": "python",
"repo": "aashishogale/DataStructurePrograms-Python-",
"path": "/com/bridgelabz/utility/queue.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aashishogale/DataStructurePrograms-Python- path: /com/bridgelabz/utility/queue.py
from com.bridgelabz.utility.linkedlist import LinkedList
class Queue:
linkedlist=LinkedList()
def enqueue(self,item):
self.linkedlist.addatEnd(item)
return
def dequeue(se... | code_fim | medium | {
"lang": "python",
"repo": "aashishogale/DataStructurePrograms-Python-",
"path": "/com/bridgelabz/utility/queue.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = 'name'
users_repo = mock.Mock()
users_repo.update.return_value = User(id=id, name=name, roles=mock.Mock())
request = UpdateUserRequest(id=None)
action = UpdateUserAction(repo=users_repo)
response = action.execute(request)
assert bool(response) is False
assert not ... | code_fim | hard | {
"lang": "python",
"repo": "Himon-SYNCRAFT/taskplus",
"path": "/tests/core/actions/update_user/test_update_user_action.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Himon-SYNCRAFT/taskplus path: /tests/core/actions/update_user/test_update_user_action.py
from unittest import mock
from taskplus.core.actions import UpdateUserAction, UpdateUserRequest
from taskplus.core.domain import User
from taskplus.core.shared.response import ResponseFailure
def test_upda... | code_fim | hard | {
"lang": "python",
"repo": "Himon-SYNCRAFT/taskplus",
"path": "/tests/core/actions/update_user/test_update_user_action.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> action = UpdateUserAction(repo=users_repo)
response = action.execute(request)
assert bool(response) is False
assert users_repo.update.called
assert response.value == {
'type': ResponseFailure.SYSTEM_ERROR,
'message': 'Exception: {}'.format(error_message)
}<|fim_pre... | code_fim | hard | {
"lang": "python",
"repo": "Himon-SYNCRAFT/taskplus",
"path": "/tests/core/actions/update_user/test_update_user_action.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@bottle.post("/pobrisi-udelezenca/")
def pobrisi_udelezenca():
print(dict(bottle.request.forms))
indeks = bottle.request.forms.getunicode("indeks")
skupina = moj_model.aktualna_skupina
udelezenec = skupina.udelezenci[int(indeks)]
Skupina.zbrisi_udelezenca(skupina, udelezenec)
moj_... | code_fim | hard | {
"lang": "python",
"repo": "nikapavlic/razdelitev-stroskov",
"path": "/spletni_vmesnik2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nikapavlic/razdelitev-stroskov path: /spletni_vmesnik2.py
import bottle
from model import Model, Skupina, Udelezenec
IME_DATOTEKE = "stanje.json"
try:
moj_model = Model.preberi_iz_datoteke(IME_DATOTEKE)
except FileNotFoundError:
moj_model = Model()
@bottle.get("/")
def osnovna_stran():... | code_fim | hard | {
"lang": "python",
"repo": "nikapavlic/razdelitev-stroskov",
"path": "/spletni_vmesnik2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@bottle.post("/pobrisi-placilo/")
def pobrisi_placilo():
print(dict(bottle.request.forms))
indeks = bottle.request.forms.getunicode("indeks")
skupina = moj_model.aktualna_skupina
udelezenec = skupina.udelezenci[int(indeks)]
print(dict(bottle.request.forms))
st = bottle.request.for... | code_fim | hard | {
"lang": "python",
"repo": "nikapavlic/razdelitev-stroskov",
"path": "/spletni_vmesnik2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rho2/alpyro_msgs path: /alpyro_msgs/actionlib/testrequestresult.py
from alpyro_msgs import RosMessage, boolean, int32
<|fim_suffix|> __msg_typ__ = "actionlib/TestRequestResult"
__msg_def__ = "aW50MzIgdGhlX3Jlc3VsdApib29sIGlzX3NpbXBsZV9zZXJ2ZXIKCg=="
__md5_sum__ = "61c2364524499c7c5017e2f3fc... | code_fim | easy | {
"lang": "python",
"repo": "rho2/alpyro_msgs",
"path": "/alpyro_msgs/actionlib/testrequestresult.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> the_result: int32
is_simple_server: boolean<|fim_prefix|># repo: rho2/alpyro_msgs path: /alpyro_msgs/actionlib/testrequestresult.py
from alpyro_msgs import RosMessage, boolean, int32
class TestRequestResult(RosMessage):
<|fim_middle|> __msg_typ__ = "actionlib/TestRequestResult"
__msg_def__ = "aW... | code_fim | medium | {
"lang": "python",
"repo": "rho2/alpyro_msgs",
"path": "/alpyro_msgs/actionlib/testrequestresult.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kidkid168/yarppg path: /test/processors/test_processor.py
import numpy as np
import pytest
from yarppg.rppg.processors import Processor
def test_spatial_pooling():
frame = np.ones((10, 10, 3))
proc = Processor()
for i in range(10):
proc.spatial_pooling(i*frame, append_rgb=T... | code_fim | medium | {
"lang": "python",
"repo": "kidkid168/yarppg",
"path": "/test/processors/test_processor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert np.isnan(proc.calculate(None))
@pytest.mark.filterwarnings("ignore")
def test_moving_average():
assert np.isnan(Processor.moving_average_update(None, [], 1))
assert np.isnan(Processor.moving_average_update(None, [np.nan]*3, 2))
assert Processor.moving_average_update(None, range(5)... | code_fim | hard | {
"lang": "python",
"repo": "kidkid168/yarppg",
"path": "/test/processors/test_processor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.c = nn.Conv3d(
in_channels = self.num_filters//self.expansion_ratio,
out_channels = self.num_filters,
kernel_size = 1,
stride = 1,
padding = 0,
bias = False
)
... | code_fim | hard | {
"lang": "python",
"repo": "hrb518/EssentialMC2",
"path": "/papers/pytorch-video-understanding/models/module_zoo/branches/r2d3d_branch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hrb518/EssentialMC2 path: /papers/pytorch-video-understanding/models/module_zoo/branches/r2d3d_branch.py
#!/usr/bin/env python3
# Copyright (C) Alibaba Group Holding Limited.
""" R2D3D branch. """
import torch
import torch.nn as nn
from models.base.base_blocks import BaseBranch, Base... | code_fim | hard | {
"lang": "python",
"repo": "hrb518/EssentialMC2",
"path": "/papers/pytorch-video-understanding/models/module_zoo/branches/r2d3d_branch.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def forward(self, x):
if self.transformation == 'simple_block':
x = self.a(x)
x = self.a_bn(x)
x = self.a_relu(x)
x = self.b(x)
x = self.b_bn(x)
return x
elif self.transformation == 'bottleneck':
... | code_fim | hard | {
"lang": "python",
"repo": "hrb518/EssentialMC2",
"path": "/papers/pytorch-video-understanding/models/module_zoo/branches/r2d3d_branch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shruti1421/scona path: /scona/__init__.py
"""
scona
=====
scona is a Python package for the analysis
of structural covariance brain networks.
Website (including documentation)::
http://whitakerlab.github.io/scona
Source::
https://github.com/WhitakerLab/scona
Bug reports::
https://git... | code_fim | medium | {
"lang": "python",
"repo": "shruti1421/scona",
"path": "/scona/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from scona.wrappers import *
from scona.visualisations_helpers import *
import scona.datasets
from scona import *<|fim_prefix|># repo: shruti1421/scona path: /scona/__init__.py
"""
scona
=====
scona is a Python package for the analysis
of structural covariance brain networks.
Website (including docume... | code_fim | medium | {
"lang": "python",
"repo": "shruti1421/scona",
"path": "/scona/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pricem14pc/eq-questionnaire-runner path: /app/routes/session.py
from datetime import datetime, timezone
from flask import Blueprint, g, jsonify, redirect, request
from flask import session as cookie_session
from flask import url_for
from flask_login import login_required, logout_user
from marshm... | code_fim | hard | {
"lang": "python",
"repo": "pricem14pc/eq-questionnaire-runner",
"path": "/app/routes/session.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@session_blueprint.route("/sign-out", methods=["GET"])
def get_sign_out():
"""
Signs the user out of eQ and redirects to the log out url.
"""
log_out_url = get_survey_config().account_service_log_out_url
# Check for GET as we don't want to log out for HEAD requests
if request.met... | code_fim | hard | {
"lang": "python",
"repo": "pricem14pc/eq-questionnaire-runner",
"path": "/app/routes/session.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: silky/Geothon path: /Create Spatial File/Vector/create_wkt_multiline.py
#!/usr/bin/env python
'''
Project: Geothon (https://github.com/MBoustani/Geothon)
File: Vector/create_wkt_multiline.py
Description: This code creates a wkt multi lines from some points
Author: Maziyar... | code_fim | hard | {
"lang": "python",
"repo": "silky/Geothon",
"path": "/Create Spatial File/Vector/create_wkt_multiline.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>latitudes = [50, 51, 52, 53]
longitudes = [100, 110, 120, 130]
elevation = 0
#Create multilines
multi_lines = ogr.Geometry(ogr.wkbMultiLineString)
#Create first line
#define first line geometry
line_1 = ogr.Geometry(ogr.wkbLineString)
#add points into first line geometry
line_1.AddPoint(longitudes[0], l... | code_fim | medium | {
"lang": "python",
"repo": "silky/Geothon",
"path": "/Create Spatial File/Vector/create_wkt_multiline.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Create multilines
multi_lines = ogr.Geometry(ogr.wkbMultiLineString)
#Create first line
#define first line geometry
line_1 = ogr.Geometry(ogr.wkbLineString)
#add points into first line geometry
line_1.AddPoint(longitudes[0], latitudes[0], elevation)
line_1.AddPoint(longitudes[1], latitudes[1], elevation... | code_fim | medium | {
"lang": "python",
"repo": "silky/Geothon",
"path": "/Create Spatial File/Vector/create_wkt_multiline.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andydevs/todo-flask path: /models.py
"""
To-Do list application
Author: Anshul Kharbanda
Created: 11 - 10 - 2017
"""
from bson.objectid import ObjectId
from flask_wtf import FlaskForm
from wtforms import StringField
class TodoForm(FlaskForm):
"""
Form for updating To-Do's
Author: ... | code_fim | hard | {
"lang": "python",
"repo": "andydevs/todo-flask",
"path": "/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def save(self, db):
"""
Saves to mongo database
:param db: the mongo database to save to
"""
# Create new if no id is given
if self._id is None:
self.collection(db).insert_one(
document={'text': self.text})
# Else up... | code_fim | hard | {
"lang": "python",
"repo": "andydevs/todo-flask",
"path": "/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Else update old
else:
self.collection(db).update_one(
filter={'_id': ObjectId(self._id)},
update={'$set': {'text': self.text}})
def delete(self, db):
"""
Deletes the todo from the database
:param db: the database t... | code_fim | hard | {
"lang": "python",
"repo": "andydevs/todo-flask",
"path": "/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sniner/rp-recorder path: /rprecorder/recorder.py
import logging
import pathlib
import re
import threading
from datetime import datetime, timedelta, time
from typing import Union
import urllib3
from rprecorder import cuesheet
log = logging.getLogger(__name__)
def _parse_meta(metastr:str):
... | code_fim | hard | {
"lang": "python",
"repo": "sniner/rp-recorder",
"path": "/rprecorder/recorder.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def record(
station:str,
streamurl:str,
streamtype:str,
target_dir:pathlib.Path,
end_time:datetime=None,
cue_sheet:bool=False,
track_list:bool=True,
):
def read_block(conn, blocksize):
data = b""
while len(data)<blocksize:... | code_fim | hard | {
"lang": "python",
"repo": "sniner/rp-recorder",
"path": "/rprecorder/recorder.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Calculating the feature tensor.
:param args: Arguments object.
:param graph: NetworkX graph.
:return target_matrices: Target tensor.
"""
index_1 = [edge[0] for edge in graph.edges()]
index_2 = [edge[1] for edge in graph.edges()]
values = [1 for edge in graph.edges()... | code_fim | medium | {
"lang": "python",
"repo": "kexinxin/Defect",
"path": "/GraphEmbedding/attentionWalk/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kexinxin/Defect path: /GraphEmbedding/attentionWalk/utils.py
import json
import numpy as np
import pandas as pd
import networkx as nx
from tqdm import tqdm
from scipy import sparse
from texttable import Texttable
def read_graph(graph_path):
"""
Method to read graph and create a target ma... | code_fim | hard | {
"lang": "python",
"repo": "kexinxin/Defect",
"path": "/GraphEmbedding/attentionWalk/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: plotdevice/plotdevice path: /tests/module.py
import os
import unittest
from . import PlotDeviceTestCase, reference
from subprocess import check_output, STDOUT
from plotdevice import *
sdist_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
class ModuleTests(PlotDeviceTestCase):... | code_fim | hard | {
"lang": "python",
"repo": "plotdevice/plotdevice",
"path": "/tests/module.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._image = 'module/cli.png'
plod_bin = '%s/app/plotdevice'%sdist_path
script = '%s/tests/_in/cli.pv'%sdist_path
output = '%s/tests/_out/%s'%(sdist_path, self._image)
check_output([plod_bin, script, '--export', output], stderr=STDOUT, cwd=sdist_path)
self.... | code_fim | hard | {
"lang": "python",
"repo": "plotdevice/plotdevice",
"path": "/tests/module.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
# this is a recovered parser
self.particle_class = HydODclRecoveredDataParticle
# no config for this parser, pass in empty dict
super(HydODclParser, self).__init__({},
stream_handle,
... | code_fim | hard | {
"lang": "python",
"repo": "oceanobservatories/mi-instrument",
"path": "/mi/dataset/parser/hyd_o_dcl.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: oceanobservatories/mi-instrument path: /mi/dataset/parser/hyd_o_dcl.py
"""
@package mi.dataset.parser
@file mi-dataset/mi/dataset/parser/hyd_o_dcl.py
@author Emily Hahn
@brief Parser for the hydrogen series o instrument through a dcl
"""
__author__ = 'Emily Hahn'
__license__ = 'Apache 2.0'
impor... | code_fim | hard | {
"lang": "python",
"repo": "oceanobservatories/mi-instrument",
"path": "/mi/dataset/parser/hyd_o_dcl.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> particle = self._extract_sample(self.particle_class,
None,
data_match,
port_timestamp=port_timestamp,
... | code_fim | hard | {
"lang": "python",
"repo": "oceanobservatories/mi-instrument",
"path": "/mi/dataset/parser/hyd_o_dcl.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(answer_word) ==0 or len(masked_word)==0:
raise InvalidWordException('Those words are invalid!')
if len(answer_word) is not len(masked_word):
raise InvalidWordException('Those words are invalid!')
if len(character) > 1:
raise InvalidGuessedLetterException('also w... | code_fim | hard | {
"lang": "python",
"repo": "joetynan/itp-u4-c2-hangman-game",
"path": "/hangman/game.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joetynan/itp-u4-c2-hangman-game path: /hangman/game.py
from .exceptions import *
import random
# Complete with your own, just for fun :)
LIST_OF_WORDS = ['book','view','quill','interrupt','macabre','marked','snakes','zephyr','behave','drum','blood','plucky']
def _get_random_word(list):
if ... | code_fim | hard | {
"lang": "python",
"repo": "joetynan/itp-u4-c2-hangman-game",
"path": "/hangman/game.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>params=json.loads(data) #type = kind of command
ctype = params['type']
jpurl = params['p1']#for ctype 'access' jpurl = ip
enurl = params['p2']#for ctype 'access' enurl = country
produceid = params['p3']
version = params['p4']
modeid = params['p5']
submodeid = params['p6']
menuid = params['p7']
mac=params... | code_fim | medium | {
"lang": "python",
"repo": "iamundeathbird/Apache-cgi-for-qr-reader",
"path": "/qrcodeprocess.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iamundeathbird/Apache-cgi-for-qr-reader path: /qrcodeprocess.py
#!/usr/bin/python3
import json
import sys
from databaseprolib import databaseProcess
from geolite2 import geolite2 as geo# geolite2 is the lib to get location of ip address
print ("Content-Type: text/html\n\n")
# connect to the data... | code_fim | medium | {
"lang": "python",
"repo": "iamundeathbird/Apache-cgi-for-qr-reader",
"path": "/qrcodeprocess.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_dau_filtering(self):
sign_up_action, person = self._create_events()
with freeze_time('2020-01-02'):
Event.objects.create(team=self.team, event='sign up', distinct_id='someone_else')
with freeze_time('2020-01-04'):
action_response = self.client.... | code_fim | hard | {
"lang": "python",
"repo": "pulmonesxavier/posthog",
"path": "/posthog/api/test/test_action.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulmonesxavier/posthog path: /posthog/api/test/test_action.py
r": "div > button",
"url": "/signup",
"isNew": 'asdf'
}]
}, content_type='application/json', HTTP_ORIGIN='http://testserver').json()
action = Action.objects.get()
self... | code_fim | hard | {
"lang": "python",
"repo": "pulmonesxavier/posthog",
"path": "/posthog/api/test/test_action.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._create_events()
# automatically sets first day as first day of any events
with freeze_time('2020-01-04'):
action_response = self.client.get('/api/action/trends/?date_from=all').json()
event_response = self.client.get('/api/action/trends/?date_from=all&... | code_fim | hard | {
"lang": "python",
"repo": "pulmonesxavier/posthog",
"path": "/posthog/api/test/test_action.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>string = input()
ans = permutations(string)
for s in ans:
print(s)<|fim_prefix|># repo: jarvis-1805/DSAwithPYTHON path: /Recursions/Recursions 3/Return_Permutations_of_a_String.py
'''
Return Permutations of a String
Given a string, find and return all the possible permutations of the input string.
... | code_fim | hard | {
"lang": "python",
"repo": "jarvis-1805/DSAwithPYTHON",
"path": "/Recursions/Recursions 3/Return_Permutations_of_a_String.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jarvis-1805/DSAwithPYTHON path: /Recursions/Recursions 3/Return_Permutations_of_a_String.py
'''
Return Permutations of a String
Given a string, find and return all the possible permutations of the input string.
Note : The order of permutations are not important.
Sample Input :
abc
Sample Outp... | code_fim | medium | {
"lang": "python",
"repo": "jarvis-1805/DSAwithPYTHON",
"path": "/Recursions/Recursions 3/Return_Permutations_of_a_String.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> output = []
for i in temp:
for j in range(len(i)+1):
smallString = i[:j] + string[0] + i[j:]
output.append(smallString)
return output
string = input()
ans = permutations(string)
for s in ans:
print(s)<|fim_prefix|># repo: jarvis-1805/DSAwithPYTHON pa... | code_fim | hard | {
"lang": "python",
"repo": "jarvis-1805/DSAwithPYTHON",
"path": "/Recursions/Recursions 3/Return_Permutations_of_a_String.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
module = __import__('courant.core.assets.filter.%s' % name,
{}, {}, [''])
except ImportError:
raise ValueError('Filter "%s" is not valid' % name)
return module<|fim_prefix|># repo: din982/Courant-News path: /courant/core/assets/filter/__in... | code_fim | easy | {
"lang": "python",
"repo": "din982/Courant-News",
"path": "/courant/core/assets/filter/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: din982/Courant-News path: /courant/core/assets/filter/__init__.py
# Assets can be filtered through one or multiple filters, modifying their
# contents (think minification, compression).
<|fim_suffix|> try:
module = __import__('courant.core.assets.filter.%s' % name,
... | code_fim | easy | {
"lang": "python",
"repo": "din982/Courant-News",
"path": "/courant/core/assets/filter/__init__.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def run_spamp(request_json):
"""
The base formulation for "pamp". Typically used for unconstrained facility location or job assignment.
This creates a light weight way to solve the p-median problem.
The same input requirements hold as for "run_pamp"
#TODO: consolidate formulatio... | code_fim | hard | {
"lang": "python",
"repo": "fhk/link_src",
"path": "/link/solve/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fhk/link_src path: /link/solve/main.py
"""
Run the main solver interface
"""
import os
from link.solve.util import (
geojson_to_graph,
make_prox_graph,
make_assi_graph,
make_tb_objects,
match_solution,
create_geojson,
make_o_graph,
... | code_fim | hard | {
"lang": "python",
"repo": "fhk/link_src",
"path": "/link/solve/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = Task
fields = ['name']<|fim_prefix|># repo: djworth/pugip-todo path: /todo/forms.py
from django.forms import Form, CharField, ModelForm
from todo.models import Task
<|fim_middle|>class TodoForm(ModelForm):
class Meta:
| code_fim | easy | {
"lang": "python",
"repo": "djworth/pugip-todo",
"path": "/todo/forms.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: djworth/pugip-todo path: /todo/forms.py
from django.forms import Form, CharField, ModelForm
from todo.models import Task
<|fim_suffix|> class Meta:
model = Task
fields = ['name']<|fim_middle|>class TodoForm(ModelForm):
| code_fim | easy | {
"lang": "python",
"repo": "djworth/pugip-todo",
"path": "/todo/forms.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kenpkz/gcp-continuous-compliance-demo path: /continuous-compliance-demo-scc/cloudfunction_remedy.py
import json
import base64
import google.auth
import google.auth.transport.requests
from google.cloud import compute_v1
def ssh_remedy(event, context):
<|fim_suffix|>
"""
Copy and paste these modul... | code_fim | hard | {
"lang": "python",
"repo": "kenpkz/gcp-continuous-compliance-demo",
"path": "/continuous-compliance-demo-scc/cloudfunction_remedy.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
Copy and paste these modules for the requirements.txt
google-auth
google-cloud-compute
"""<|fim_prefix|># repo: kenpkz/gcp-continuous-compliance-demo path: /continuous-compliance-demo-scc/cloudfunction_remedy.py
import json
import base64
import google.auth
import google.auth.transport.requests
from... | code_fim | hard | {
"lang": "python",
"repo": "kenpkz/gcp-continuous-compliance-demo",
"path": "/continuous-compliance-demo-scc/cloudfunction_remedy.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> _inherit = "mail.thread"
@api.model
def mailgun_fetch_message(self, message_url):
api_key = self.env["ir.config_parameter"].sudo().get_param("mailgun.apikey")
res = requests.get(
message_url,
headers={"Accept": "message/rfc2822"},
auth=("api... | code_fim | medium | {
"lang": "python",
"repo": "SDIsl/mail-addons",
"path": "/mailgun/models/mail_thread.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SDIsl/mail-addons path: /mailgun/models/mail_thread.py
import logging
import requests
from odoo import api, models
_logger = logging.getLogger(__name__)
<|fim_suffix|> @api.model
def mailgun_fetch_message(self, message_url):
api_key = self.env["ir.config_parameter"].sudo().get... | code_fim | medium | {
"lang": "python",
"repo": "SDIsl/mail-addons",
"path": "/mailgun/models/mail_thread.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> api_key = self.env["ir.config_parameter"].sudo().get_param("mailgun.apikey")
res = requests.get(
message_url,
headers={"Accept": "message/rfc2822"},
auth=("api", api_key),
verify=False,
)
self.message_process(False, res.json()... | code_fim | medium | {
"lang": "python",
"repo": "SDIsl/mail-addons",
"path": "/mailgun/models/mail_thread.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rakshith291/ResNet_Tensorflow path: /main.py
from model import ResNet
from data import DataGenerator
from tensorflow.keras.layers import Layer
<|fim_suffix|> data = DataGenerator()
train_gen = data.train_data('path')
valid_gen = data.test_data('/path')
model = ResNet(3)
print(... | code_fim | easy | {
"lang": "python",
"repo": "rakshith291/ResNet_Tensorflow",
"path": "/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> data = DataGenerator()
train_gen = data.train_data('path')
valid_gen = data.test_data('/path')
model = ResNet(3)
print(ResNet(3).model().summary())
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=["accuracy"])
model.fit_generator(train_gen, validation_d... | code_fim | easy | {
"lang": "python",
"repo": "rakshith291/ResNet_Tensorflow",
"path": "/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Validate that the provided email is not considered a "burner"
domain, e.g. someone not interested in committing and contributing to
the community or the ability to recover their account."""
if '@' not in email:
return
email, domain = email.split('@')
try:
BurnerD... | code_fim | medium | {
"lang": "python",
"repo": "NDevox/website",
"path": "/app/marketing/validators.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NDevox/website path: /app/marketing/validators.py
from django.forms import ValidationError
from django.utils.translation import gettext as _
<|fim_suffix|>def validate_not_burner_domain(email: str):
"""Validate that the provided email is not considered a "burner"
domain, e.g. someone not... | code_fim | medium | {
"lang": "python",
"repo": "NDevox/website",
"path": "/app/marketing/validators.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Create rules file
build_config_cmake(cmake_opts=["-DBUILD_PYTHON=ON"])
install_usr_dir_to_package("usr/include", "dev")
install_usr_dir_to_package("usr/CMake", "dev")
install_usr_dir_to_package("usr/lib/python2.7", "python")
build_config["configure"].append(
"echo 'add_definitions(\"-std=gnu++11\")'... | code_fim | hard | {
"lang": "python",
"repo": "ulikoehler/deb-buildscripts",
"path": "/deb-opengv.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Create the changelog (no messages - dummy)
create_dummy_changelog()
# Create rules file
build_config_cmake(cmake_opts=["-DBUILD_PYTHON=ON"])
install_usr_dir_to_package("usr/include", "dev")
install_usr_dir_to_package("usr/CMake", "dev")
install_usr_dir_to_package("usr/lib/python2.7", "python")
build_con... | code_fim | medium | {
"lang": "python",
"repo": "ulikoehler/deb-buildscripts",
"path": "/deb-opengv.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ulikoehler/deb-buildscripts path: /deb-opengv.py
#!/usr/bin/env python3
from deblib import *
# General config
set_name("libopengv")
set_homepage("https://github.com/laurentkneip/opengv")
#Download it
git_clone("https://github.com/laurentkneip/opengv.git")
set_version("1.0", gitcount=True)
add_ver... | code_fim | hard | {
"lang": "python",
"repo": "ulikoehler/deb-buildscripts",
"path": "/deb-opengv.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ascend/ModelZoo-PyTorch path: /PyTorch/dev/cv/image_classification/DeepLab-CRF_ID1873_for_PyTorch/hubconf.py
#!/usr/bin/env python
# coding: utf-8
#
# BSD 3-Clause License
#
# Copyright (c) 2017 xxxx
# All rights reserved.
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Redistribution and use i... | code_fim | hard | {
"lang": "python",
"repo": "Ascend/ModelZoo-PyTorch",
"path": "/PyTorch/dev/cv/image_classification/DeepLab-CRF_ID1873_for_PyTorch/hubconf.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert pretrained in model_dict, list(model_dict.keys())
expected = model_dict[pretrained][1]
error_message = "Expected: n_classes={}".format(expected)
assert n_classes == expected, error_message
model_url = model_url_root + model_dict[pretrained][0]
state_... | code_fim | hard | {
"lang": "python",
"repo": "Ascend/ModelZoo-PyTorch",
"path": "/PyTorch/dev/cv/image_classification/DeepLab-CRF_ID1873_for_PyTorch/hubconf.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from torch.hub import load_state_dict_from_url
import torch.npu
import os
NPU_CALCULATE_DEVICE = 0
if os.getenv('NPU_CALCULATE_DEVICE') and str.isdigit(os.getenv('NPU_CALCULATE_DEVICE')):
NPU_CALCULATE_DEVICE = int(os.getenv('NPU_CALCULATE_DEVICE'))
if torch.npu.current_device() != NPU_CALCULATE_DEVIC... | code_fim | hard | {
"lang": "python",
"repo": "Ascend/ModelZoo-PyTorch",
"path": "/PyTorch/dev/cv/image_classification/DeepLab-CRF_ID1873_for_PyTorch/hubconf.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self,
to_ckpt,
index,
is_latest = False):
ckpt_str = 'latest_' if is_latest else ''
ckpt_loc = os.path.join(self.checkpoint_dir, '{}{}.pth'.format(ckpt_str, index))
# remove the previous if it is the latest
if is_latest:
for fnam... | code_fim | hard | {
"lang": "python",
"repo": "kshen6/byol-pytorch",
"path": "/research_tools/store/writer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kshen6/byol-pytorch path: /research_tools/store/writer.py
'''
Class for writing experimental logs.
'''
import pandas as pd
import os
import pickle
from datetime import datetime
from ..utils.metric import create_metric
import torch
from .dir_utils import get_latest_run_id
class ExperimentLogWr... | code_fim | hard | {
"lang": "python",
"repo": "kshen6/byol-pytorch",
"path": "/research_tools/store/writer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # remove the previous if it is the latest
if is_latest:
for fname in os.listdir(self.checkpoint_dir):
if 'latest_' in fname:
os.remove(os.path.join(self.checkpoint_dir, fname))
torch.save(to_ckpt, ckpt_loc)
def save_tensor(self,... | code_fim | hard | {
"lang": "python",
"repo": "kshen6/byol-pytorch",
"path": "/research_tools/store/writer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# In[6]:
# Lets further clean up the list to seperate Usernames from age
# Use list comprehension to replace the last brace ")" with empty "" in member_found above
member_found_replaced = [x.replace(")", "") for x in member_found] # replaces ")" by ""
print (member_found_replaced)
# In[... | code_fim | hard | {
"lang": "python",
"repo": "forum2k9/Nairaland-Christmas-Birthday",
"path": "/Nairaland_Xmas_Birthdays.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: forum2k9/Nairaland-Christmas-Birthday path: /Nairaland_Xmas_Birthdays.py
# coding: utf-8
# The original blog post for this notebook is at: https://umar-yusuf.blogspot.com.ng/2016/12/nairaland-christmas-birthday-analyzed.html
# In[1]:
# import the libraries we are going to use
# libraries for S... | code_fim | hard | {
"lang": "python",
"repo": "forum2k9/Nairaland-Christmas-Birthday",
"path": "/Nairaland_Xmas_Birthdays.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
member_found_replaced = [x.replace(")", "") for x in member_found] # replaces ")" by ""
print (member_found_replaced)
# In[7]:
# Now split "member_found_replaced" based on '(' between the usernames and age
# we use for loop to loop through each item of the "member_found_replaced" list abov... | code_fim | hard | {
"lang": "python",
"repo": "forum2k9/Nairaland-Christmas-Birthday",
"path": "/Nairaland_Xmas_Birthdays.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: virtuNat/aoc-12020 path: /src-python/day17.py
#!/usr/bin/env python
import numpy as np
from scipy.signal import correlate
from aoc import get_input
def automata(grid, dims):
grid = np.pad(np.expand_dims(grid, tuple(range(2, dims))), 6)
mask = np.ones((3,) * dims, dtype=int)
mask[(1,)... | code_fim | medium | {
"lang": "python",
"repo": "virtuNat/aoc-12020",
"path": "/src-python/day17.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(automata(grid, 3)) # 1
print(automata(grid, 4)) # 2
if __name__ == '__main__':
main()<|fim_prefix|># repo: virtuNat/aoc-12020 path: /src-python/day17.py
#!/usr/bin/env python
import numpy as np
from scipy.signal import correlate
from aoc import get_input
def automata(grid, dims):
<|fi... | code_fim | hard | {
"lang": "python",
"repo": "virtuNat/aoc-12020",
"path": "/src-python/day17.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> grid = np.pad(np.expand_dims(grid, tuple(range(2, dims))), 6)
mask = np.ones((3,) * dims, dtype=int)
mask[(1,)*dims] = 0
for _ in range(6):
conv = correlate(grid, mask, 'same')
grid[(conv < 2) | (conv > 3)] = 0
grid[conv == 3] = 1
return grid.sum()
def main():
... | code_fim | medium | {
"lang": "python",
"repo": "virtuNat/aoc-12020",
"path": "/src-python/day17.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> buttons = [
Color.button_secondary(cancel, focus_map='button_secondary focus')
]
return Pile(buttons)
def build_menuable_items(self):
""" Builds a list of bundles available to install
"""
cols = []
for bundle in app.bundles:
... | code_fim | hard | {
"lang": "python",
"repo": "conjure-up/conjure-up",
"path": "/conjureup/ui/views/variant.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self._w.body.focus_position == 2:
self._w.body.focus_position = 4
else:
self._w.body.focus_position = 2
def keypress(self, size, key):
if key in ['tab', 'shift tab']:
self._swap_focus()
return super().keypress(size, key)
def ... | code_fim | hard | {
"lang": "python",
"repo": "conjure-up/conjure-up",
"path": "/conjureup/ui/views/variant.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: conjure-up/conjure-up path: /conjureup/ui/views/variant.py
from __future__ import unicode_literals
from ubuntui.ev import EventLoop
from ubuntui.utils import Color, Padding
from ubuntui.widgets.buttons import menu_btn, quit_btn
from urwid import Columns, Filler, Pile, Text, WidgetWrap
from conj... | code_fim | hard | {
"lang": "python",
"repo": "conjure-up/conjure-up",
"path": "/conjureup/ui/views/variant.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SamueleMeta/optimal_is path: /examples/util.py
"""Running utilities."""
import importlib
import yaml
from gym.envs import registry
from rllib.environment import GymEnvironment
from rllib.util.training.agent_training import evaluate_agent, train_agent
from rllib.util.utilities import RewardTrans... | code_fim | hard | {
"lang": "python",
"repo": "SamueleMeta/optimal_is",
"path": "/examples/util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Train agent."""
train_agent(
agent=agent,
environment=environment,
num_episodes=args.num_train,
max_steps=args.max_steps,
eval_frequency=args.eval_frequency,
print_frequency=args.print_frequency,
render=args.render_train,
)
def evalu... | code_fim | hard | {
"lang": "python",
"repo": "SamueleMeta/optimal_is",
"path": "/examples/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LucaMalavolta/PyORBIT path: /pyorbit/pyorbit_results.py
import pyorbit
import argparse
import sys
def pyorbit_results():
# print 'This program is being run by itself'
parser = argparse.ArgumentParser(prog='PyORBIT_GetResults.py', description='PyDE+emcee runner')
parser.add_argument... | code_fim | hard | {
"lang": "python",
"repo": "LucaMalavolta/PyORBIT",
"path": "/pyorbit/pyorbit_results.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if args.all_corners is not False:
plot_dictionary['full_correlation'] = True
plot_dictionary['common_corner'] = True
plot_dictionary['dataset_corner'] = True
if args.noacf is not False:
plot_dictionary['print_acf'] = False
plot_dictionary['plot_acf'] = Fals... | code_fim | hard | {
"lang": "python",
"repo": "LucaMalavolta/PyORBIT",
"path": "/pyorbit/pyorbit_results.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Parameters
----------
x_tst: features of testing data
model: trained learning model
"""
predictions = model.predict(x_tst)
return predictions
def write_output(predictions):
order = np.arange(1, 81)
order.shape = (80, 1)
predictions.shape = (80, 1)
pred = np... | code_fim | hard | {
"lang": "python",
"repo": "aycagokdag/BrainNet-ML-ToolBox",
"path": "/Team 11/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
The method predicts labels for testing data samples by using trained learning model.
Parameters
----------
x_tst: features of testing data
model: trained learning model
"""
predictions = model.predict(x_tst)
return predictions
def write_output(predictions):
... | code_fim | hard | {
"lang": "python",
"repo": "aycagokdag/BrainNet-ML-ToolBox",
"path": "/Team 11/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aycagokdag/BrainNet-ML-ToolBox path: /Team 11/main.py
"""
Target Problem:
---------------
* A classifier for the diagnosis of Autism Spectrum Disorder (ASD)
Proposed Solution (Machine Learning Pipeline):
----------------------------------------------
* SelectKBest Algorithm -> Adaptive Boosting ... | code_fim | hard | {
"lang": "python",
"repo": "aycagokdag/BrainNet-ML-ToolBox",
"path": "/Team 11/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tejasmanohar/viper path: /viper/optimizer.py
from viper.parser.parser_utils import LLLnode
from viper.utils import LOADED_LIMIT_MAP
def get_int_at(args, pos, signed=False):
value = args[pos].value
if isinstance(value, int):
o = value
elif value == "mload" and args[pos].args... | code_fim | hard | {
"lang": "python",
"repo": "tejasmanohar/viper",
"path": "/viper/optimizer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def optimize(node):
argz = [optimize(arg) for arg in node.args]
if node.value in arith and int_at(argz, 0) and int_at(argz, 1):
left, right = get_int_at(argz, 0), get_int_at(argz, 1)
calcer, symb = arith[node.value]
new_value = calcer(left, right)
if argz[0].annota... | code_fim | hard | {
"lang": "python",
"repo": "tejasmanohar/viper",
"path": "/viper/optimizer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> clusteredBars.xTickLabels = ["A", "B", "C", "D", "E"]
plot = Plot()
plot.add(clusteredBars)
plot.hasLegend()
plot.save(self.imageName)
ImageComparisonTestCase.register(ClusteredBarsTest)
if __name__ == "__main__":
test = ClusteredBarsTest("testImageCompariso... | code_fim | hard | {
"lang": "python",
"repo": "alexras/boomslang",
"path": "/tests/test_clusteredbars.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alexras/boomslang path: /tests/test_clusteredbars.py
#!/usr/bin/env python
from boomslang import Bar, ClusteredBars, Plot
import unittest
from ImageComparisonTestCase import ImageComparisonTestCase
class ClusteredBarsTest(ImageComparisonTestCase, unittest.TestCase):
def __init__(self, testCa... | code_fim | hard | {
"lang": "python",
"repo": "alexras/boomslang",
"path": "/tests/test_clusteredbars.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> bar1 = Bar()
bar1.xValues = range(5)
bar1.yValues = [2, 4, 6, 8, 10]
bar1.color = "red"
bar1.label = "Red Cluster"
bar2 = Bar()
bar2.xValues = range(5)
bar2.yValues = [3, 12, 4, 8, 14]
bar2.color = "blue"
bar2.label = "Blue C... | code_fim | medium | {
"lang": "python",
"repo": "alexras/boomslang",
"path": "/tests/test_clusteredbars.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Royelrani/OVOS-local-backend path: /ovos_local_backend/backend/device.py
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | code_fim | hard | {
"lang": "python",
"repo": "Royelrani/OVOS-local-backend",
"path": "/ovos_local_backend/backend/device.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> token = request.json["state"]
device = {"uuid": "AnonDevice",
"expires_at": time.time() + 72000,
"accessToken": token,
"refreshToken": token}
return nice_json(device)
@app.route("/" + API_VERSION + "/device/<uuid>/message",... | code_fim | hard | {
"lang": "python",
"repo": "Royelrani/OVOS-local-backend",
"path": "/ovos_local_backend/backend/device.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gkskillz/karenanderic path: /web/app/models.py
from google.appengine.ext import ndb
class Invitation(ndb.Model):
code = ndb.StringProperty()
@classmethod
def query_code(cls, code):
return cls.query(cls.code == code).get()
class Guest(ndb.Model):
first_name = ndb.Strin... | code_fim | hard | {
"lang": "python",
"repo": "gkskillz/karenanderic",
"path": "/web/app/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for rsvp in self.guest_rsvps:
if rsvp.rsvp == NO_RSVP:
continue
if rsvp.is_extra and not rsvp.name:
continue
if rsvp.meal_choice is None:
return False
return True
def add_empty_extras(self, location):
... | code_fim | hard | {
"lang": "python",
"repo": "gkskillz/karenanderic",
"path": "/web/app/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: afmsaif/Exploiting-Cascaded-Ensemble-of-Features-for-the-Detection-of-Tuberculosis-from-Chest-Radiographs path: /inceptionv3.py
#from keras.preprocessing import image
from tensorflow.keras.models import Model
#from keras.layers import Dense, GlobalAveragePooling2D
#from keras import backend as K... | code_fim | hard | {
"lang": "python",
"repo": "afmsaif/Exploiting-Cascaded-Ensemble-of-Features-for-the-Detection-of-Tuberculosis-from-Chest-Radiographs",
"path": "/inceptionv3.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>model.compile(loss='binary_crossentropy',
optimizer=opt,
metrics= METRICS,
)
datagen.fit(X_train)
datagen_val.fit(X_val)
#model.fit(X_train, y_train, batch_size= 50, epochs=200, validation_... | code_fim | hard | {
"lang": "python",
"repo": "afmsaif/Exploiting-Cascaded-Ensemble-of-Features-for-the-Detection-of-Tuberculosis-from-Chest-Radiographs",
"path": "/inceptionv3.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main(argv):
parser = argparse.ArgumentParser(description='Xpath Eval Function')
parser.add_argument('-f','--file', help='XML file', required=True)
parser.add_argument('-x','--xpath', help='Xpath Query', required=True)
args = vars(parser.parse_args())
res = xpath_eval(args['file'], ... | code_fim | hard | {
"lang": "python",
"repo": "dadhichmohit/notes",
"path": "/scripts/xpath.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.