text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> def generator(self, data_dir, tmp_dir, is_training):
# In this test problem, we assume that the data is in tmp_dir/ocr/ in
# files names 0.png, 0.txt, 1.png, 1.txt and so on until num_examples.
num_examples = 2
ocr_dir = os.path.join(tmp_dir, "ocr/")
tf.logging.info("Looking for OCR ... | code_fim | hard | {
"lang": "python",
"repo": "yyht/BERT",
"path": "/t2t_bert/utils/tensor2tensor/data_generators/ocr.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# moonlight channel
# calc current brightness of the moon
# percentage is max_moonlight_percentage times moonlight_brightness in percent
if not channel['manual'] and channel['moonlight']:
print(" moonlight channel")
# create moonlight object using t... | code_fim | hard | {
"lang": "python",
"repo": "isnuryusuf/ReefLight",
"path": "/reeflight.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# normal channel (new percentage calculated via interpolation of the data_points)
if not channel['manual'] and not channel['moonlight']:
# normal channel
# new percentage updated via linear interpolation of the data_points
print(" regular channel")
... | code_fim | hard | {
"lang": "python",
"repo": "isnuryusuf/ReefLight",
"path": "/reeflight.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: isnuryusuf/ReefLight path: /reeflight.py
from flask import Flask, request, render_template
import json
import time
import datetime
import paho.mqtt.client as mqtt
import pylunar
import threading
import math
server = Flask(__name__)
settings_file = "settings.json"
#
# save, load and print the ... | code_fim | hard | {
"lang": "python",
"repo": "isnuryusuf/ReefLight",
"path": "/reeflight.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert isinstance(node, ast.Name)
return node.id<|fim_prefix|># repo: mugwort-rc/pyqtpp path: /pyqtpp/util.py
# -*- coding: utf-8 -*-
import ast
def attr2list(node):
prefix = []
assert isinstance(node, ast.Attribute)
if isinstance(node.value, ast.Attribute):
prefix = attr2li... | code_fim | easy | {
"lang": "python",
"repo": "mugwort-rc/pyqtpp",
"path": "/pyqtpp/util.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mugwort-rc/pyqtpp path: /pyqtpp/util.py
# -*- coding: utf-8 -*-
import ast
def attr2list(node):
<|fim_suffix|> assert isinstance(node, ast.Name)
return node.id<|fim_middle|> prefix = []
assert isinstance(node, ast.Attribute)
if isinstance(node.value, ast.Attribute):
pr... | code_fim | hard | {
"lang": "python",
"repo": "mugwort-rc/pyqtpp",
"path": "/pyqtpp/util.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> type
A shortened string of the platform name.
typeLong
An enlongated string of the platform name.
membershipTypeID
The numerical value of the platform.
"""
def __init__(self, membershipType):
self._conversion = {
1: ["xb", "xbox", 1],
... | code_fim | medium | {
"lang": "python",
"repo": "TheTimebike/destiny.py",
"path": "/destiny/platform.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheTimebike/destiny.py path: /destiny/platform.py
class Platform:
"""Represents membershipType data given back by the API in a more user-friendly format.
Can be created any time by passing a numerical membershipType value. IE: 1, 2 or 3
<|fim_suffix|> self._conversion = {
... | code_fim | hard | {
"lang": "python",
"repo": "TheTimebike/destiny.py",
"path": "/destiny/platform.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _read_lines(fn):
# NC_000007.13 RefSeq cDNA_match 50344265 50344518 254 + . ID=aln58042;Target=NM_001220765.2 1 254 +;gap_count=0;identity=0.0691326;idty=1;num_ident=428;num_mismatch=0;pct_coverage=6.91326;pct_identity_gap=100;pct_identity_ungap=100;score=254
# NC_000002.11 RefSeq... | code_fim | hard | {
"lang": "python",
"repo": "simexin/uta",
"path": "/sbin/ncbi-parse-gff",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def convert_exon_data(opts, exon_recs):
"""return (TxInfo,ExonSet) tuple for given exon record data"""
er0 = exon_recs[0]
ti = TxInfo(ac=er0["tx_ac"],
origin=opts.origin,
hgnc=None,
cds_se_i=None,
exons_se_i=";".join(
... | code_fim | hard | {
"lang": "python",
"repo": "simexin/uta",
"path": "/sbin/ncbi-parse-gff",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simexin/uta path: /sbin/ncbi-parse-gff
#!/usr/bin/env python
"""Write exonsets and txinfo files from NCBI GFF alignments, as obtained from
ftp://ftp.ncbi.nlm.nih.gov/refseq/H_sapiens/alignments/
This service appeared in April 2015 and is due to update weekly.
See uta.formats for a description o... | code_fim | hard | {
"lang": "python",
"repo": "simexin/uta",
"path": "/sbin/ncbi-parse-gff",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ckreutz/open-aid-data path: /openaid.py
'a')
link = 'recipient_country/' + country + '/' + year
input = sitemap(link)
sitemap_file.write(input)
sitemap_file.close()
year = int(year)
position = query_db('SELECT id from crs_donortop where recipientcode = {0}'.format(countr... | code_fim | hard | {
"lang": "python",
"repo": "ckreutz/open-aid-data",
"path": "/openaid.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@app.route('/sectors/<year>/')
def show_schwerpunkte(year):
var = {'year': year}
sitemap_file = open('sitemap.xml', 'a')
link = 'sectors/' + year
input = sitemap(link)
sitemap_file.write(input)
sitemap_file.close()
entries = []
if year == ... | code_fim | hard | {
"lang": "python",
"repo": "ckreutz/open-aid-data",
"path": "/openaid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> recipient_countries = []
for row in query_db('select round(sum(usd_disbursement * 1000000)) as main_value, recipientname, recipientcode, count(id) as activities from crs where donorcode = {0} and Year = {1} group by recipientname order by main_value desc limit 10'.format(donor, year)):
... | code_fim | hard | {
"lang": "python",
"repo": "ckreutz/open-aid-data",
"path": "/openaid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: StanleyCruvinel/mlrun path: /tests/test_sqldb.py
# Copyright 2019 Iguazio
#
# 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... | code_fim | hard | {
"lang": "python",
"repo": "StanleyCruvinel/mlrun",
"path": "/tests/test_sqldb.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> runs = list(db.list_runs(uid=uid, iter=True))
assert 5 == len(runs), 'iter=True'
def test_schedules(db: sqldb.SQLDB):
count = 7
for i in range(count):
data = {'i': i}
db.store_schedule(data)
scheds = list(db.list_schedules())
assert count == len(scheds), 'wrong n... | code_fim | hard | {
"lang": "python",
"repo": "StanleyCruvinel/mlrun",
"path": "/tests/test_sqldb.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> db.store_artifact('k1', {}, '1', tag='t1', project='p1')
db.store_artifact('k1', {}, '2', tag='t2', project='p1')
db.store_artifact('k1', {}, '2', tag='t2', project='p2')
tags = db.list_artifact_tags('p1')
assert {'t1', 't2'} == set(tags), 'bad tags'
def test_list_artifact_date(db: ... | code_fim | hard | {
"lang": "python",
"repo": "StanleyCruvinel/mlrun",
"path": "/tests/test_sqldb.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jiazhizhong/bk-log path: /apps/feature_toggle/plugins/base.py
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-LOG 蓝鲸日志平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-LOG 蓝鲸日志平台 is licensed under the MIT... | code_fim | hard | {
"lang": "python",
"repo": "jiazhizhong/bk-log",
"path": "/apps/feature_toggle/plugins/base.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @abstractmethod
def action(self):
"""
trigger action if need at update config
must try any exception
"""
pass
@register
class DummyFeatureToggle(FeatureToggleBase):
target = "dummy"
def set_status(self, param: dict) -> dict:
return param
... | code_fim | hard | {
"lang": "python",
"repo": "jiazhizhong/bk-log",
"path": "/apps/feature_toggle/plugins/base.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>append(int(line))
line = f.readline()
line = line.strip('\n')
f.close()
c.sort()
len1 = int(len(c)/2)
print(c[len1])<|fim_prefix|># repo: ioyy900205/PyTorch_mess-around path: /txt_read.py
f = open("/home/liuliang/data.txt")
line = f.readline()
line <|fim_middle|>= line.strip('\n')
c = []
while l... | code_fim | medium | {
"lang": "python",
"repo": "ioyy900205/PyTorch_mess-around",
"path": "/txt_read.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ioyy900205/PyTorch_mess-around path: /txt_read.py
f = open("/home/liuliang/data.txt")
line = f.readline()
line = line.strip('\n')
c = []
while line:
# print(line)
c.<|fim_suffix|>p('\n')
f.close()
c.sort()
len1 = int(len(c)/2)
print(c[len1])<|fim_middle|>append(int(line))
line = f.re... | code_fim | medium | {
"lang": "python",
"repo": "ioyy900205/PyTorch_mess-around",
"path": "/txt_read.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jordan-Kowal/discord-dice-roller path: /discord_dice_roller/cogs/utility.py
"""Cog for utility commands like clean up or about"""
# Built-in
import time
# Third-party
from discord.ext import commands
# Application
from utils.cog import ImprovedCog
from utils.embed import create_embed, create_e... | code_fim | hard | {
"lang": "python",
"repo": "Jordan-Kowal/discord-dice-roller",
"path": "/discord_dice_roller/cogs/utility.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _should_delete(self, msg, ctx):
"""
Predicate to choose which message to delete in the `purge` API
:param Message msg: Any discord message we are reading through
:param Context ctx: The command call context
:return: Whether the message should be deleted
... | code_fim | hard | {
"lang": "python",
"repo": "Jordan-Kowal/discord-dice-roller",
"path": "/discord_dice_roller/cogs/utility.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muzudho/openpyxl-practice path: /read_cell.py
import openpyxl as xl
# Book
wb = xl.load_workbook('test-data/test-data.xlsx')
# Sheet
ws = wb['Test1']
<|fim_suffix|># Cell value
print(f'cell(value={c3.value})')<|fim_middle|># Cell
c3 = ws['C3']
| code_fim | easy | {
"lang": "python",
"repo": "muzudho/openpyxl-practice",
"path": "/read_cell.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Cell value
print(f'cell(value={c3.value})')<|fim_prefix|># repo: muzudho/openpyxl-practice path: /read_cell.py
import openpyxl as xl
# Book
wb = xl.load_workbook('test-data/test-data.xlsx')
<|fim_middle|># Sheet
ws = wb['Test1']
# Cell
c3 = ws['C3']
| code_fim | easy | {
"lang": "python",
"repo": "muzudho/openpyxl-practice",
"path": "/read_cell.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muzudho/openpyxl-practice path: /read_cell.py
import openpyxl as xl
<|fim_suffix|># Cell value
print(f'cell(value={c3.value})')<|fim_middle|># Book
wb = xl.load_workbook('test-data/test-data.xlsx')
# Sheet
ws = wb['Test1']
# Cell
c3 = ws['C3']
| code_fim | medium | {
"lang": "python",
"repo": "muzudho/openpyxl-practice",
"path": "/read_cell.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if line.end == 0:
return
pos = line.end
while line.buffer[pos - 1] in string.whitespace and pos > line.start:
pos -= 1
if pos != line.end and line.buffer[pos] in ' \t':
yield LintProblem(line.line_no, pos - line.start + 1,
'trailing spaces... | code_fim | medium | {
"lang": "python",
"repo": "jennahung/infra_project-config",
"path": "/jenkins/scripts/yamllint.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jennahung/infra_project-config path: /jenkins/scripts/yamllint.py
#!/usr/bin/env python
import sys
import yaml
import string
from yamllint.linter import LintProblem
if len(sys.argv) < 2:
print 'Missing file to lint'
sys.exit(1)
ID = 'trailing-spaces'
TYPE = 'line'
def check(conf, line... | code_fim | medium | {
"lang": "python",
"repo": "jennahung/infra_project-config",
"path": "/jenkins/scripts/yamllint.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class TestManager(models.Manager):
def for_user(self, user):
return self.get_query_set().filter(Q(website__users__id=user.pk) | Q(website__groups__users__id=user.pk))<|fim_prefix|># repo: randomknowledge/mwt path: /mwt/managers.py
from django.db import models
from django.db.models.query_util... | code_fim | hard | {
"lang": "python",
"repo": "randomknowledge/mwt",
"path": "/mwt/managers.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: randomknowledge/mwt path: /mwt/managers.py
from django.db import models
from django.db.models.query_utils import Q
from . import constants
from .utils.time import get_tznow
class RunScheduleManager(models.Manager):
def pending(self):
qset = self.get_query_set().filter(paused=False)
... | code_fim | hard | {
"lang": "python",
"repo": "randomknowledge/mwt",
"path": "/mwt/managers.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ltoscano/Y-Flow path: /tools/trec2trecs.py
import argparse
import os
import io
import re
def output_doc(text, filename):
with open(filename, 'wt') as fout:
for line in text:
fout.write(line)
def trecs2trec(filename, output_dir, lowercase=False):
<|fim_suffix|> files =... | code_fim | hard | {
"lang": "python",
"repo": "ltoscano/Y-Flow",
"path": "/tools/trec2trecs.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open(filename) as fin:
print(filename)
for line in fin:
line.strip()
if '<DOC>' in line: ## begin a document
text = [line]
elif '</DOC>' in line:
text.append(line)
output_doc(text, os.path.join(out... | code_fim | medium | {
"lang": "python",
"repo": "ltoscano/Y-Flow",
"path": "/tools/trec2trecs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if clean:
green_print("Clean")
# Return the porcelain status of a submodule project
@memoized
def submodule_status(self, sub):
path = self.sub_folder(sub)
command = ["git", "-C", path, "status", "--porcelain", "--branch"]
status = exec_command(com... | code_fim | hard | {
"lang": "python",
"repo": "wichtounet/pm",
"path": "/pm/scm/git.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wichtounet/pm path: /pm/scm/git.py
#=======================================================================
# Copyright (c) 2014 Baptiste Wicht
# Distributed under the terms of the MIT License.
# (See accompanying file LICENSE or copy at
# http://opensource.org/licenses/MIT)
#===================... | code_fim | hard | {
"lang": "python",
"repo": "wichtounet/pm",
"path": "/pm/scm/git.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> path = self.sub_folder(sub)
command = ["git", "-C", path, "status", "--porcelain", "--branch"]
status = exec_command(command)
return status
def find_detached_source_branch(self, path):
command = ["git", "-C", path, "for-each-ref",
"--forma... | code_fim | hard | {
"lang": "python",
"repo": "wichtounet/pm",
"path": "/pm/scm/git.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: watrt/micropython-mgui path: /mgui/dev/ssd1306pygame.py
try:
import framebuf
except ImportError:
from . import framebuf
from sys import exit
from multiprocessing import Process, Queue, Array
# from pygame.time import wait
from pygame import locals as L
from pygame import display as pyg_d... | code_fim | hard | {
"lang": "python",
"repo": "watrt/micropython-mgui",
"path": "/mgui/dev/ssd1306pygame.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> req = RefreshRequest()
req.action = signal
req.value = value
req.rect = rect
req.data = data
if self.__main_process:
if self.__screen == None:
return
self.__request_list.append(req)
else:
if self.__... | code_fim | hard | {
"lang": "python",
"repo": "watrt/micropython-mgui",
"path": "/mgui/dev/ssd1306pygame.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Setup robots.txt
path("robots.txt", TemplateView.as_view(template_name="robots.txt", content_type="text/plain"))
]
if settings.PGS_ON_CURATION_SITE:
# e.g.: /stats/
urlpatterns.append(path('stats/', views.stats, name='Stats'))
# e.g.: /releases/
urlpatterns.append(path('release... | code_fim | hard | {
"lang": "python",
"repo": "PGScatalog/PGS_Catalog",
"path": "/catalog/urls.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # e.g.: /labs
path('labs/', views.LabsView.as_view(), name="Labs"),
# Setup URL used to warmup the Django app in the Google App Engine
path('_ah/warmup', views.warmup, name="Warmup"),
# Setup robots.txt
path("robots.txt", TemplateView.as_view(template_name="robots.txt", content_t... | code_fim | hard | {
"lang": "python",
"repo": "PGScatalog/PGS_Catalog",
"path": "/catalog/urls.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PGScatalog/PGS_Catalog path: /catalog/urls.py
from django.conf import settings
from django.urls import path
from django.views.generic.base import RedirectView, TemplateView
from django.views.decorators.cache import cache_page
from . import views
# Seconds * Minutes
cache_time = 60 * 60
urlpatt... | code_fim | hard | {
"lang": "python",
"repo": "PGScatalog/PGS_Catalog",
"path": "/catalog/urls.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return cls(
item.get(DynamoDbClient.GITHUB_HANDLE_KEY, {}).get("S", ""),
item.get(DynamoDbClient.USER_ID_KEY, {}).get("S", ""),
)
@staticmethod
def _get_custom_field_value(custom_field: dict):
if custom_field["type"] == "text":
return cu... | code_fim | medium | {
"lang": "python",
"repo": "isabella232/SGTM",
"path": "/src/sync_users/sgtm_user.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.domain_user_id = domain_user_id
@classmethod
def from_dynamodb_item(cls, item: dict) -> SgtmUser:
return cls(
item.get(DynamoDbClient.GITHUB_HANDLE_KEY, {}).get("S", ""),
item.get(DynamoDbClient.USER_ID_KEY, {}).get("S", ""),
)
@staticmeth... | code_fim | medium | {
"lang": "python",
"repo": "isabella232/SGTM",
"path": "/src/sync_users/sgtm_user.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: isabella232/SGTM path: /src/sync_users/sgtm_user.py
"""
Class representing a "User" for SGTM, which comprises of a Github handle and an
Asana domain user id. In practice, these should be actual developers in your
organization that are contributing to your repository, which have an Asana
account a... | code_fim | medium | {
"lang": "python",
"repo": "isabella232/SGTM",
"path": "/src/sync_users/sgtm_user.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: praekeltfoundation/nurseconnect-registration path: /seaworthy/fixtures.py
import pytest
from seaworthy.containers.postgresql import PostgreSQLContainer
from seaworthy.definitions import ContainerDefinition
NCREG_IMAGE = pytest.config.getoption("--ncreg-image")
<|fim_suffix|> super().__i... | code_fim | medium | {
"lang": "python",
"repo": "praekeltfoundation/nurseconnect-registration",
"path": "/seaworthy/fixtures.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
postgresql_container = PostgreSQLContainer("postgresql")
f = postgresql_container.pytest_clean_fixtures("postgresql_container")
postgresql_fixture, clean_postgresql_fixture = f
ncreg_container = NCRegContainer(
"nurseconnect_registration", postgresql_container.database_url()
)
ncreg_fixture = ncreg_... | code_fim | hard | {
"lang": "python",
"repo": "praekeltfoundation/nurseconnect-registration",
"path": "/seaworthy/fixtures.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(f"\nO Jogador {jogador['Nome']} jogou {len(jogador['Gols'])} partidas.")
for item, valor in enumerate(jogador['Gols']):
print(f'Na partida {item+1} fez {valor} gols')
print(f"Foi um total de {jogador['Total de Gols']} gols.")<|fim_prefix|># repo: matheusguerreiro/python path: /Python/19 - 093 -... | code_fim | medium | {
"lang": "python",
"repo": "matheusguerreiro/python",
"path": "/Python/19 - 093 - cadastro de jogador de futebol.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: matheusguerreiro/python path: /Python/19 - 093 - cadastro de jogador de futebol.py
# Aula 19 (Dicionários)
from time import sleep
jogador = {}
gols = []
jogador['Nome'] = str(input('Nome do Jogador: '))
totalGols = 0
quantidadePartidas = int(input('Quantas partidas ele Jogou? '))
for c in rang... | code_fim | medium | {
"lang": "python",
"repo": "matheusguerreiro/python",
"path": "/Python/19 - 093 - cadastro de jogador de futebol.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlexKyuu/collective-intelligence path: /recommendations.py
# coding=utf-8
from math import sqrt
critics = {
'Lisa Rose': {
'Lady in the Water': 2.5,
'Snakes on the Plane': 3.5,
'Just My Luck': 3.0,
'Superman Returns': 3.5,
'You, Me and Dupree': 2.5,
... | code_fim | hard | {
"lang": "python",
"repo": "AlexKyuu/collective-intelligence",
"path": "/recommendations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> user_rattings = prefs[user]
scores = {}
total_sim = {}
# 循环遍历由当前用户评分的物品
for (item, rating) in user_rattings.items():
# 循环遍历与当前物品相近的物品
for (similarity, item2) in item_match[item]:
# 如果该用户已经对当前物品做过评价, 则将其忽略
if item2 in user_rattings: continue
... | code_fim | hard | {
"lang": "python",
"repo": "AlexKyuu/collective-intelligence",
"path": "/recommendations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nocproject/noc path: /vc/migrations/0018_vc_state.py
# ---------------------------------------------------------------------
# VRF, Prefix, IP state
# ---------------------------------------------------------------------
# Copyright (C) 2007-2019 The NOC Project
# See LICENSE for details
# ------... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/vc/migrations/0018_vc_state.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Migration(BaseMigration):
depends_on = [("main", "0043_default_resourcestates")]
def migrate(self):
# Create .state
ResourceState = self.db.mock_model(
model_name="ResourceState", db_table="main_resourcestate"
)
self.db.add_column(
"v... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/vc/migrations/0018_vc_state.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gdikov/vae-playground path: /playground/models/networks/encoder.py
'add', 'concatenate' and 'product' are available.")
standard_normal_sampler.arguments = {'seed': config['seed'], 'noise_dim': noise_dim, 'mode': noise_mode}
for i, inp in enumerate(inputs):
noise_inpu... | code_fim | hard | {
"lang": "python",
"repo": "gdikov/vae-playground",
"path": "/playground/models/networks/encoder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class StandardConjointEncoder(object):
"""
A StandardConjointEncoder parametrises an arbitrary latent distribution given two (or more) datasets,
by partially sharing the latent vector between two (or more) encoders:
Data_1 Data_2
| ... | code_fim | hard | {
"lang": "python",
"repo": "gdikov/vae-playground",
"path": "/playground/models/networks/encoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> latent_factors = []
for i, (a, v) in enumerate(zip(coefficients, noise_basis_vectors)):
latent_factors.append(Multiply(name='enc_elemwise_coeff_vecs_mult_{}'.format(i))([a, v]))
latent_factors = Add(name='enc_add_weighted_vecs')(latent_factors)
latent_factors = ... | code_fim | hard | {
"lang": "python",
"repo": "gdikov/vae-playground",
"path": "/playground/models/networks/encoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
mprre = MultiPulseRadarRangeEquation()
mprre.main()<|fim_prefix|># repo: djfish1/RadarToolbox path: /MultiPulseRadarRangeEquation.py
import math
import RadarRangeEquation
class MultiPulseRadarRangeEquation(RadarRangeEquation.RadarRangeEquation):
<|fim_middle|>
def __init... | code_fim | medium | {
"lang": "python",
"repo": "djfish1/RadarToolbox",
"path": "/MultiPulseRadarRangeEquation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: djfish1/RadarToolbox path: /MultiPulseRadarRangeEquation.py
import math
import RadarRangeEquation
class MultiPulseRadarRangeEquation(RadarRangeEquation.RadarRangeEquation):
def __init__(self):
<|fim_suffix|>if __name__ == '__main__':
mprre = MultiPulseRadarRangeEquation()
mprre.main()<|fi... | code_fim | medium | {
"lang": "python",
"repo": "djfish1/RadarToolbox",
"path": "/MultiPulseRadarRangeEquation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Export data from a python engine, data= (engname, onames), result=None
EXPORT = 'Export'
#Import data from a file, data=(), result=None
IMPORT = 'Import'<|fim_prefix|># repo: tito2016/Python-Project path: /PythonToolkit-14.04.04/ptk_lib/core_tools/fileio/fileio_messages.py
"""
Message types for th... | code_fim | medium | {
"lang": "python",
"repo": "tito2016/Python-Project",
"path": "/PythonToolkit-14.04.04/ptk_lib/core_tools/fileio/fileio_messages.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tito2016/Python-Project path: /PythonToolkit-14.04.04/ptk_lib/core_tools/fileio/fileio_messages.py
"""
Message types for the FileIO tool
"""
#Addressed messages sent to 'FileIO'
#Open the file(s) using the fileio system, data=filenames, result=None
OPEN = 'Open'
<|fim_suffix|>#Import ... | code_fim | medium | {
"lang": "python",
"repo": "tito2016/Python-Project",
"path": "/PythonToolkit-14.04.04/ptk_lib/core_tools/fileio/fileio_messages.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lsmo-epfl/aiida-lsmo path: /aiida_lsmo/calcfunctions/working_cap.py
# -*- coding: utf-8 -*-
"""Calcfunctions to compute working capacities for different gasses."""
from math import sqrt
from aiida.engine import calcfunction
from aiida.orm import Dict
def get_molec_uc_to_mg_g(isot_dict):
""... | code_fim | hard | {
"lang": "python",
"repo": "lsmo-epfl/aiida-lsmo",
"path": "/aiida_lsmo/calcfunctions/working_cap.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # conversion factors form mol/kg to cm3STP/cm3 and wt%
conv1 = isot_dict['conversion_factor_molec_uc_to_cm3stp_cm3'] / isot_dict['conversion_factor_molec_uc_to_mol_kg'] # pylint: disable=line-too-long
conv2 = get_molec_uc_to_mg_g(isot_dict) / isot_dict['conversion_factor_molec_uc_... | code_fim | hard | {
"lang": "python",
"repo": "lsmo-epfl/aiida-lsmo",
"path": "/aiida_lsmo/calcfunctions/working_cap.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('home', '0010_auto_20200822_0327'),
]
operations = [
migrations.AlterField(
model_name='siparis',
name='kisi_say',
field=models.IntegerField(default=1, verbose_name='Kisi Say'),
),
]<|fim_prefix|># rep... | code_fim | medium | {
"lang": "python",
"repo": "nursenyanar/bi-odeme",
"path": "/home/migrations/0011_auto_20200822_0335.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nursenyanar/bi-odeme path: /home/migrations/0011_auto_20200822_0335.py
# Generated by Django 2.1.7 on 2020-08-22 00:35
from django.db import migrations, models
<|fim_suffix|> dependencies = [
('home', '0010_auto_20200822_0327'),
]
operations = [
migrations.A... | code_fim | easy | {
"lang": "python",
"repo": "nursenyanar/bi-odeme",
"path": "/home/migrations/0011_auto_20200822_0335.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sudoguy/dtf_bot path: /base/models/skipped.py
from django.db import models
from .base import BaseModel
class Skipped(BaseModel):
<|fim_suffix|> class Meta:
constraints = [
models.UniqueConstraint(fields=["object_id", "object_type"], name="unique_skipped")
]<|fim_... | code_fim | medium | {
"lang": "python",
"repo": "sudoguy/dtf_bot",
"path": "/base/models/skipped.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> object_id = models.BigIntegerField()
object_type = models.CharField(max_length=255)
class Meta:
constraints = [
models.UniqueConstraint(fields=["object_id", "object_type"], name="unique_skipped")
]<|fim_prefix|># repo: sudoguy/dtf_bot path: /base/models/skipped.py... | code_fim | easy | {
"lang": "python",
"repo": "sudoguy/dtf_bot",
"path": "/base/models/skipped.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> class Meta:
constraints = [
models.UniqueConstraint(fields=["object_id", "object_type"], name="unique_skipped")
]<|fim_prefix|># repo: sudoguy/dtf_bot path: /base/models/skipped.py
from django.db import models
from .base import BaseModel
<|fim_middle|>class Skipped(Base... | code_fim | medium | {
"lang": "python",
"repo": "sudoguy/dtf_bot",
"path": "/base/models/skipped.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Atelier-Developers/atelier-artemisia-processor path: /Processor/utils.py
from gate.input_gate import Input
<|fim_suffix|> for i in range(len(bitstring)):
inps[i].output = 0 if bitstring[i] == "0" else 1
return inps<|fim_middle|>def bits_to_gates(bitstring, inps):
| code_fim | easy | {
"lang": "python",
"repo": "Atelier-Developers/atelier-artemisia-processor",
"path": "/Processor/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(len(bitstring)):
inps[i].output = 0 if bitstring[i] == "0" else 1
return inps<|fim_prefix|># repo: Atelier-Developers/atelier-artemisia-processor path: /Processor/utils.py
from gate.input_gate import Input
<|fim_middle|>def bits_to_gates(bitstring, inps):
| code_fim | easy | {
"lang": "python",
"repo": "Atelier-Developers/atelier-artemisia-processor",
"path": "/Processor/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return fun(expx(x), *fargs, **fkwargs)
# Transform the final result
result = minimizer(new_fun, logx(x0), jac=new_jac, bounds=bounds,
**minimizer_kwargs)
result['x'] = expx(result['x'])
return result
return new_minimizer
de... | code_fim | hard | {
"lang": "python",
"repo": "lizhangzhan/revrand",
"path": "/revrand/optimize/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lizhangzhan/revrand path: /revrand/optimize/base.py
nums=[5, 3]).shape
(2, 15)
>>> candidate_start_points_lattice([(-1, 1.5), (-1.5, 3), (0, 5)],
... nums=[5, 10, 9]) # doctest: +ELLIPSIS
array([[-1. , -1. , -1. , ..., 1.5 , 1.5 , ... | code_fim | hard | {
"lang": "python",
"repo": "lizhangzhan/revrand",
"path": "/revrand/optimize/base.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if bounds is None:
return sgd(fun, x0, data, bounds=bounds, eval_obj=eval_obj,
**sgd_kwargs)
logx, expx, gradx, bounds = logtrick_gen(bounds)
if bool(eval_obj):
def new_fun(x, *fargs, **fkwargs):
o, g = fun(expx(x), ... | code_fim | hard | {
"lang": "python",
"repo": "lizhangzhan/revrand",
"path": "/revrand/optimize/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: graphistry/pygraphistry path: /graphistry/tests/test_ArrowFileUploader.py
import pandas as pd, pyarrow as pa, unittest
from graphistry.arrow_uploader import ArrowUploader
from graphistry.ArrowFileUploader import (
ArrowFileUploader,
DF_TO_FILE_ID_CACHE,
MemoizedFileUpload,
Wrappe... | code_fim | hard | {
"lang": "python",
"repo": "graphistry/pygraphistry",
"path": "/graphistry/tests/test_ArrowFileUploader.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TestArrowFileUploader_Core(unittest.TestCase):
def test_memoization(self):
afu = ArrowFileUploader(ArrowUploader(token="xx"))
arr = pa.Table.from_pandas(pd.DataFrame({"x": [1, 2, 3]}))
# avoid directly holding references
DF_TO_FILE_ID_CACHE[cache_arr(WrappedTab... | code_fim | medium | {
"lang": "python",
"repo": "graphistry/pygraphistry",
"path": "/graphistry/tests/test_ArrowFileUploader.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jvrsantacruz/ipodio path: /spec/ui/rename_spec.py
# -*- coding: utf-8 -*-
from expects import expect
from mamba import describe, context, before, after
from spec.ui._ipod_helpers import *
from spec.ui._fixture import update_environment
<|fim_suffix|> execution = _.env.run(
*... | code_fim | hard | {
"lang": "python",
"repo": "jvrsantacruz/ipodio",
"path": "/spec/ui/rename_spec.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def should_show_an_error_when_called_without_arguments():
execution = _.env.run(*_.cmd + ['rename'], expect_error=True)
expect(execution.stderr).to.have('Usage')
def should_show_an_error_when_called_with_expression_but_without_replacement():
execution = _.env.run(*_.cmd +... | code_fim | medium | {
"lang": "python",
"repo": "jvrsantacruz/ipodio",
"path": "/spec/ui/rename_spec.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> execution = _.env.run(*_.cmd + ['rename'], expect_error=True)
expect(execution.stderr).to.have('Usage')
def should_show_an_error_when_called_with_expression_but_without_replacement():
execution = _.env.run(*_.cmd + ['rename', _.expression], expect_error=True)
expect(... | code_fim | hard | {
"lang": "python",
"repo": "jvrsantacruz/ipodio",
"path": "/spec/ui/rename_spec.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fmehralian/Image-Caption-Joint-Embedding path: /transfer.py
from data import Data
from settings import config
from iconClasses.model import Model
from loss import PairwiseRankingLoss as Loss
from optimizer import Optimizer
if __name__ == "__main__":
# Load data
data = Data()
data.load_dictio... | code_fim | hard | {
"lang": "python",
"repo": "fmehralian/Image-Caption-Joint-Embedding",
"path": "/transfer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Optimizer
optimizer = Optimizer(model)
# Begin epochs
for epoch in range(config["num_epochs"]):
print("[EPOCH]", epoch+1)
# Process batches
for caption, image_feature, contents in data:
pass
# Pass data through model
caption, image_feature = model(caption, image_feature)
# ... | code_fim | medium | {
"lang": "python",
"repo": "fmehralian/Image-Caption-Joint-Embedding",
"path": "/transfer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Evaluate final model results
model.evaluate(data, save_if_better=True)
# Final evaluation
print("\nFinal evaluation:")
model.evaluate(data, save_if_better=True)
print("\n[SCRIPT] complete")<|fim_prefix|># repo: fmehralian/Image-Caption-Joint-Embedding path: /transfer.py
from data imp... | code_fim | hard | {
"lang": "python",
"repo": "fmehralian/Image-Caption-Joint-Embedding",
"path": "/transfer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmenezesgabriel/tick_track path: /tick_track/src/models/base.py
from peewee import Model, DatabaseProxy
<|fim_suffix|>class BaseModel(Model):
"""
Class responsible to create database connection.
"""
class Meta:
# Indicates in which database the tables it will be created
... | code_fim | easy | {
"lang": "python",
"repo": "dmenezesgabriel/tick_track",
"path": "/tick_track/src/models/base.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Class responsible to create database connection.
"""
class Meta:
# Indicates in which database the tables it will be created
database = database_proxy<|fim_prefix|># repo: dmenezesgabriel/tick_track path: /tick_track/src/models/base.py
from peewee import Model, Databa... | code_fim | easy | {
"lang": "python",
"repo": "dmenezesgabriel/tick_track",
"path": "/tick_track/src/models/base.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> NINDIRECT = 512
def __init__(self, idisk):
self._NINDIRECT = IndirectInodeDisk.NINDIRECT
self._idisk = idisk
def get_iattr(self, ino):
return self._idisk.get_iattr(ino)
def set_iattr(self, ino, attr):
self._idisk.set_iattr(ino, attr)
def read(self, l... | code_fim | hard | {
"lang": "python",
"repo": "fengjixuchui/hydra",
"path": "/src/yggdrasil/xv6inode.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fengjixuchui/hydra path: /src/yggdrasil/xv6inode.py
import errno
import sys
import time
import argparse
from collections import namedtuple
from stat import S_IFDIR
import cython
if not cython.compiled:
from diskimpl import Allocator, DentryLookup
from waldisk import WALDisk
from disk... | code_fim | hard | {
"lang": "python",
"repo": "fengjixuchui/hydra",
"path": "/src/yggdrasil/xv6inode.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return content
###
#
# Version: 1.1.0
# Date: 2020-04-15
# Author: Yves Vindevogel (vindevoy)
#
# Added logging
#
# Version: 1.0.0
# Date: 2020-04-13
# Author: Yves Vindevogel (vindevoy)
#
# This class was split of the DataLoader class
#
###<|fim_prefix|># repo: vindevoy/cherryblo... | code_fim | hard | {
"lang": "python",
"repo": "vindevoy/cherryblog",
"path": "/src/application/model/codeversion.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def data(self):
content = Content().load_data_settings_yaml(self.__base_dir)
self.__logger.debug('data - content: {0}'.format(content))
return content
###
#
# Version: 1.1.0
# Date: 2020-04-15
# Author: Yves Vindevogel (vindevoy)
#
# Added logging
#
# ... | code_fim | medium | {
"lang": "python",
"repo": "vindevoy/cherryblog",
"path": "/src/application/model/codeversion.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vindevoy/cherryblog path: /src/application/model/codeversion.py
###
#
# Full history: see below
#
# Version: 1.2.0
# Date: 2020-04-17
# Author: Yves Vindevogel (vindevoy)
#
# Features:
# - Caching done outside this class
#
###
import logging
<|fim_suffix|> __base_dir = 'codev... | code_fim | medium | {
"lang": "python",
"repo": "vindevoy/cherryblog",
"path": "/src/application/model/codeversion.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: analuisadev/100-Days-Of-Code path: /day-14.py
import sys
from time import sleep
player = 10
sleep(1)
#Welcome
print ('=' *38)
print ('\033[1;33mWelcome to game I ALREADY and I NEVER!\033[m')
print ('=' *38)
sleep(2)
#Rules
print ('''\033[1;33mRules:
1 ° For every question you ask you lose ... | code_fim | hard | {
"lang": "python",
"repo": "analuisadev/100-Days-Of-Code",
"path": "/day-14.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ever\033[m '))
if q8 == 1:
player = player - 1
elif q8 == 2:
pass
else:
print ('\033[1;31mInvalid answer, Choose between 1 (already) and 2 (NEVER)\033[m ')
sys.exit()
q9 = int(input('\033[1;36mI never immediately regretted having sent a message: 1 - Already 2 - Never\033[m '))
if q9 == 1:
... | code_fim | hard | {
"lang": "python",
"repo": "analuisadev/100-Days-Of-Code",
"path": "/day-14.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> text = request.data
return text
@app.after_request
def add_cors(resp):
resp.headers['Access-Control-Allow-Origin'] = flask.request.headers.get('Origin', '*')
resp.headers['Access-Control-Allow-Credentials'] = True
resp.headers['Access-Control-Allow-Methods'] = 'POST, OPTIONS, GET, PUT... | code_fim | hard | {
"lang": "python",
"repo": "fayllanera/startup",
"path": "/startup_llanera/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> res = spcall('login', (email,password), True)
print res
if 'Error' in str(res[0][0]):
return jsonify({'status': 'error'})
return jsonify({'status': 'ok'})
@app.route('/data', methods=['POST', 'GET'])
def data_post():
text = request.data
return text
@app.after_request
def... | code_fim | medium | {
"lang": "python",
"repo": "fayllanera/startup",
"path": "/startup_llanera/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fayllanera/startup path: /startup_llanera/app.py
from flask import Flask, jsonify, request
from flask.ext.httpauth import HTTPBasicAuth
import sys, flask
import model
app = Flask(__name__)
auth = HTTPBasicAuth()
def spcall(qry, param, commit=False):
<|fim_suffix|>
params = request.get_json(... | code_fim | hard | {
"lang": "python",
"repo": "fayllanera/startup",
"path": "/startup_llanera/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if select == 5 or select == 6: # 프리퀀시 데이터에 자카드 유사도 사용시
Xarr_seq, yTotal_seq, fileNum_seq = gcn_dataprocess.fileRead_Xarr(Normal_seq, Attack_seq, 1)
if select == 5: # 전체
JACCARD_ROW = gcn_jaccard.JaccardSim(Xarr_seq, fileNum, 0)
elif select == 6: # 한행... | code_fim | hard | {
"lang": "python",
"repo": "yanghun-park/Sequenced-based-GCN-deep-learning",
"path": "/kegra/gcn_main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yanghun-park/Sequenced-based-GCN-deep-learning path: /kegra/gcn_main.py
import os, datetime
import numpy as np
import scipy.sparse as sp
import gcn_train
import gcn_dataprocess
import gcn_jaccard
# =================================================================
# ... | code_fim | hard | {
"lang": "python",
"repo": "yanghun-park/Sequenced-based-GCN-deep-learning",
"path": "/kegra/gcn_main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 시퀀스 데이터에 자카드 유사도 사용시
if select == 2: # 전체
JACCARD_ROW = gcn_jaccard.JaccardSim(Xarr, fileNum, 0)
if select == 3: # 한행
JACCARD_ROW = gcn_jaccard.JaccardSim(Xarr, fileNum, 1)
if select == 5 or select == 6: # 프리퀀시 데이터에 자카드 유사도 사용시
Xarr_seq, ... | code_fim | hard | {
"lang": "python",
"repo": "yanghun-park/Sequenced-based-GCN-deep-learning",
"path": "/kegra/gcn_main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: savagej/mlflow-torchserve path: /examples/MNIST/predict.py
import os
from argparse import ArgumentParser
import matplotlib.pyplot as plt
from mlflow.deployments import get_deploy_client
from torchvision import transforms
def predict(parser_args):
plugin = get_deploy_client(parser_args["tar... | code_fim | medium | {
"lang": "python",
"repo": "savagej/mlflow-torchserve",
"path": "/examples/MNIST/predict.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
parser = ArgumentParser(description="MNIST hand written digits classification example")
parser.add_argument(
"--target",
type=str,
default="torchserve",
help="MLflow target (default: torchserve)",
)
parser.add_argument(
... | code_fim | medium | {
"lang": "python",
"repo": "savagej/mlflow-torchserve",
"path": "/examples/MNIST/predict.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> cytoplasm_feature = extract_cell_level_feature(
c,
'Cytoplasm',
tid,
iid,
set(extract_info_dict['cytoplasm_feature_filter_name']),
extract_info_dict['cytoplasm_name']
)
nuclei_feature = extract_cell_level_feat... | code_fim | hard | {
"lang": "python",
"repo": "gitter-lab/pharmaco-image",
"path": "/scripts/extract_median_feature.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Connect the sql db
conn = sqlite3.connect('./{}.sqlite'.format(pid))
c = conn.cursor()
plate_features = []
plate_row_index = []
plate_row_bids = []
# Extract features well by well
for i, r in df.iterrows():
if i == 3:
break
wid = r['Metadata_Well']
features, row_index = extract_f... | code_fim | hard | {
"lang": "python",
"repo": "gitter-lab/pharmaco-image",
"path": "/scripts/extract_median_feature.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gitter-lab/pharmaco-image path: /scripts/extract_median_feature.py
import sqlite3
import pandas as pd
import numpy as np
from sys import argv
from json import load
def extract_cell_level_feature(c, table, tid, iid, filter_names,
validation_names):
"""
Extr... | code_fim | hard | {
"lang": "python",
"repo": "gitter-lab/pharmaco-image",
"path": "/scripts/extract_median_feature.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # print(tf.get_collection(end_points_collection))
end_points.update(
dict([(ep.name, ep) for ep in tf.get_collection(end_points_collection)]))
end_points[ns + '_to_32'] = fcn32
end_points[ns + '_to_16'] = fcn16
end_points[ns + '_to_8'] = fcn8... | code_fim | hard | {
"lang": "python",
"repo": "Mooonside/SEGS",
"path": "/segs/fcn.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Mooonside/SEGS path: /segs/fcn.py
"""
An implementation of Fully Convolution Network
By Yifeng Chen
"""
from re import search
import tensorflow as tf
from backbones.vgg_16 import vgg_16, vgg_arg_scope
from tf_ops.wrap_ops import trans_conv2d, conv2d, tensor_shape
arg_scope = tf.contrib.framewo... | code_fim | hard | {
"lang": "python",
"repo": "Mooonside/SEGS",
"path": "/segs/fcn.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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