text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> """
Sets the version of this Problem.
:param version: The version of this Problem.
:type version: int
"""
self._version = version
@property
def body(self) -> Body:
"""
Gets the body of this Problem.
:return: The body of th... | code_fim | hard | {
"lang": "python",
"repo": "ldev-r3-t4/storage_server",
"path": "/web/swagger_server/models/problem.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>migrate = Migrate(app, db)
manager.add_command("shell", Shell(make_context=make_shell_context))
manager.add_command("db", MigrateCommand)
@manager.command
def test(coverage=False):
"""Run the unit tests."""
if coverage and not os.environ.get('FLASK_COVERAGE'):
import sys
os.envir... | code_fim | hard | {
"lang": "python",
"repo": "zxxlxx/qk_spider",
"path": "/spider.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zxxlxx/qk_spider path: /spider.py
#!/usr/bin/env python
import os
from flask_jwt import JWT
from app.api_1_0.models import InnerResult
from app.datasource.models import OriginData
COV = None
if os.environ.get("FLASK_COVERAGE"):
import coverage
# TODO:here is not understand
COV = c... | code_fim | medium | {
"lang": "python",
"repo": "zxxlxx/qk_spider",
"path": "/spider.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> fin.wintype = int(wtype.get())
fout.wintype = int(wtype.get())
def overlapsfunc():
olaps = int(overlaps.get())
size = int(fftsize.get())
wintype = int(wtype.get())
fin = FFT(snd, size=size, overlaps=olaps, wintype=wintype)
fout = IFFT(real, imag, size=size, overlaps=ol... | code_fim | hard | {
"lang": "python",
"repo": "guibarrette/PyoPlug",
"path": "/ScriptsPresets/NeedWork/CeciliaProblematic/30-SpectralFilter.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|>np.save("Mandelbrot_test_data.npy", mesh)<|fim_prefix|># repo: MateiSarivan/MandelbrotSet path: /tests/generate_test_data.py
import numpy as np
from manset.mandelbrot import divergence_check_naive
x_range = np.linspace(-2.3, 0.7, 20)
y_range = np.linspace(-1.5, 1.5, 20)
<|fim_middle|>mesh = divergence_... | code_fim | medium | {
"lang": "python",
"repo": "MateiSarivan/MandelbrotSet",
"path": "/tests/generate_test_data.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MateiSarivan/MandelbrotSet path: /tests/generate_test_data.py
import numpy as np
from manset.mandelbrot import divergence_check_naive
x_range = np.linspace(-2.3, 0.7, 20)
y_range = np.linspace(-1.5, 1.5, 20)
<|fim_suffix|>np.save("Mandelbrot_test_data.npy", mesh)<|fim_middle|>mesh = divergence_... | code_fim | medium | {
"lang": "python",
"repo": "MateiSarivan/MandelbrotSet",
"path": "/tests/generate_test_data.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xuefenga616/mygit path: /spark/pyspark(by Leaderman git)/1.2.0/examples/sql/spark_sql_cache.py
# coding=utf-8
from pyspark import SparkConf, SparkContext
from pyspark.sql import HiveContext, Row
conf = SparkConf().setAppName("spark_sql_cache")
sc = SparkContext(conf=conf)
hc = HiveContext(sc)... | code_fim | medium | {
"lang": "python",
"repo": "xuefenga616/mygit",
"path": "/spark/pyspark(by Leaderman git)/1.2.0/examples/sql/spark_sql_cache.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def printRows(rows):
for row in rows:
print row
datas = hc.sql("select * from temp_mytable").collect()
printRows(datas)
datas = hc.sql("select col1 from temp_mytable").collect()
printRows(datas)
# hc.uncacheTable("temp_mytable")
sc.stop()<|fim_prefix|># repo: xuefenga616/mygit path: /s... | code_fim | medium | {
"lang": "python",
"repo": "xuefenga616/mygit",
"path": "/spark/pyspark(by Leaderman git)/1.2.0/examples/sql/spark_sql_cache.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for movie in movieList:
yield {
'title': movie.xpath('//div[contains(@class, "info")]/div[contains(@class, "hd")]/a/span[@class="title"][1]/text()').extract_first(),
'img': movie.xpath('//div[@class="pic"]/a/img/@src').extract_first()
}
... | code_fim | medium | {
"lang": "python",
"repo": "iamMarkchu/spider",
"path": "/spider/spiders/movie.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iamMarkchu/spider path: /spider/spiders/movie.py
# -*- coding: utf-8 -*-
import scrapy
class MovieSpider(scrapy.Spider):
name = 'movie'
allowed_domains = ['movie.douban.com']
start_urls = ['http://movie.douban.com/top250']
<|fim_suffix|> # 下一页逻辑
nextPage = response.x... | code_fim | hard | {
"lang": "python",
"repo": "iamMarkchu/spider",
"path": "/spider/spiders/movie.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> track = track_info.tracks[trackname]
TL.load_tracks([trackname])
this_looper = TL.tracks[trackname]
thtr=this_looper.tr
main_core_list = nar(this_looper.core_list)
main_core_list.sort()
mini_scrubbers={}
for core_id in main_core_list:
print('buddy_centroid',core_id)... | code_fim | medium | {
"lang": "python",
"repo": "dcollins4096/p19_newscripts",
"path": "/analysis_pipe/buddy_centroid.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dcollins4096/p19_newscripts path: /analysis_pipe/buddy_centroid.py
from starter2 import *
import buddy_hair
reload(buddy_hair)
import find_other_cores
reload(find_other_cores)
import track_loader as TL
<|fim_suffix|> track = track_info.tracks[trackname]
TL.load_tracks([trackname])
... | code_fim | medium | {
"lang": "python",
"repo": "dcollins4096/p19_newscripts",
"path": "/analysis_pipe/buddy_centroid.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Utsavjain4561/Image-Captioning path: /evaluate.py
from numpy import argmax
from pickle import load
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.models import load_model
from nltk.translate.bleu_score import corpus_bleu
def load_d... | code_fim | hard | {
"lang": "python",
"repo": "Utsavjain4561/Image-Captioning",
"path": "/evaluate.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>train_features = load_photo_features('/home/uj/Desktop/Resources/features.pkl',train_data)
print('Photos: %d'%len(train_features))
tokenizer = create_tokenizer(train_descriptions)
vocab_length = len(tokenizer.word_index)+1
print('Vocabulary Size: %d'%vocab_length)
max_length = max_length(train_descripti... | code_fim | hard | {
"lang": "python",
"repo": "Utsavjain4561/Image-Captioning",
"path": "/evaluate.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>train_descriptions = load_descriptions('/home/uj/Desktop/Resources/descriptions.txt',
train_data)
print('Descriptions: %d'%len(train_descriptions))
train_features = load_photo_features('/home/uj/Desktop/Resources/features.pkl',train_data)
print('Photos: %d'%len(train_features))
tokenizer = create_token... | code_fim | hard | {
"lang": "python",
"repo": "Utsavjain4561/Image-Captioning",
"path": "/evaluate.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#n-2 because we using sample data
s_sqr = sse/(len(x)-2)
print('sigma sqr = '+str(s_sqr))
#calculating Variances
s = s_sqr**0.5
sb1 = s/(dem**0.5)
varb1 = sb1**2
print('Var(b1) = '+str(varb1))
varb0 = (s_sqr*ssx)/(len(x)*dem)
print('Var(b0) = '+str(varb0))
#calculating correlation
r_sqr = ssr/sst
prin... | code_fim | hard | {
"lang": "python",
"repo": "ChaosTheLegend/Statistics-HW",
"path": "/HW7/prob3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>varb0 = (s_sqr*ssx)/(len(x)*dem)
print('Var(b0) = '+str(varb0))
#calculating correlation
r_sqr = ssr/sst
print('r^2 = '+str(r_sqr))
plt.plot([min(x),max(x)],[min(y_pred),max(y_pred)])
plt.scatter(x,y)
plt.show()<|fim_prefix|># repo: ChaosTheLegend/Statistics-HW path: /HW7/prob3.py
import openpyxl
from... | code_fim | hard | {
"lang": "python",
"repo": "ChaosTheLegend/Statistics-HW",
"path": "/HW7/prob3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ChaosTheLegend/Statistics-HW path: /HW7/prob3.py
import openpyxl
from pathlib import Path
import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import t
filename = 'datap3.txt'
pt = Path(__file__)
parent = pt.parent
filepath = Path.joinpath(parent,filename)
data = []
f... | code_fim | hard | {
"lang": "python",
"repo": "ChaosTheLegend/Statistics-HW",
"path": "/HW7/prob3.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """[summary]
Verifica si se ha intentado hacer 3 compras en menos de 2 minutos
Args:
lista ([List], optional): [Recibe la lista de violaciones
y agrega una nueva violacion si se cumple la condicion inicial]. Defaults to list_violations.
Returns:
[List]: [Retorna la... | code_fim | hard | {
"lang": "python",
"repo": "kemirandad/Authorizer",
"path": "/Operations/violations_list.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def violation_frequency(lista = list_violations):
"""[summary]
Verifica si se ha intentado hacer 3 compras en menos de 2 minutos
Args:
lista ([List], optional): [Recibe la lista de violaciones
y agrega una nueva violacion si se cumple la condicion inicial]. Defaults to list_vio... | code_fim | hard | {
"lang": "python",
"repo": "kemirandad/Authorizer",
"path": "/Operations/violations_list.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kemirandad/Authorizer path: /Operations/violations_list.py
from Validations.val_account import is_already_initialized
from Validations.val_transaction import status_card, set_disponible, double_transaction, entry_point, time_validation_double, time_validation_frequency
from Entities.violations im... | code_fim | hard | {
"lang": "python",
"repo": "kemirandad/Authorizer",
"path": "/Operations/violations_list.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='pageobjects',
name='content',
field=models.JSONField(max_length=100, verbose_name='Содержание'),
),
]<|fim_prefix|># repo: ShancoVils/web_calc_repos path: /backend/django_web_calculator/web_calcu... | code_fim | medium | {
"lang": "python",
"repo": "ShancoVils/web_calc_repos",
"path": "/backend/django_web_calculator/web_calculator/migrations/0024_alter_pageobjects_content.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShancoVils/web_calc_repos path: /backend/django_web_calculator/web_calculator/migrations/0024_alter_pageobjects_content.py
# Generated by Django 3.2.5 on 2021-09-02 13:39
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='pageobjects',
name='conte... | code_fim | medium | {
"lang": "python",
"repo": "ShancoVils/web_calc_repos",
"path": "/backend/django_web_calculator/web_calculator/migrations/0024_alter_pageobjects_content.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alenzhao/bio_tools path: /utils_plot.py
import pylab, time, os
import numarray, Gnuplot, random
def plotPtLs(pt_ls, titles, g):
r = random.randint(1, 100)
plot_command = "plot 'tmp"
rm_command = 'rm tmp'
for index in xrange(len(pt_ls)):
tmp_suffix = str(r + index)
... | code_fim | hard | {
"lang": "python",
"repo": "alenzhao/bio_tools",
"path": "/utils_plot.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> (n, bins_res1, patches1) = pylab.hist(data1, bins=b)
(n, bins_res2, patches2) = pylab.hist(data2, bins=b)
(n, bins_res3, patches3) = pylab.hist(data3, bins=b)
(n, bins_res4, patches4) = pylab.hist(data4, bins=b)
pylab.setp(patches1, 'facecolor', 'g', 'alpha', .75)
pylab.setp(patche... | code_fim | hard | {
"lang": "python",
"repo": "alenzhao/bio_tools",
"path": "/utils_plot.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_home_url_resolves_home_view(self):
view = resolve('/')
# self.assertEqual(view.func, home)
self.assertEqual(view.func.view_class, BoardListView)
def test_home_view_contains_link_to_topics_page(self):
board_topics_url = reverse('board_topics', kwargs={'pk':... | code_fim | medium | {
"lang": "python",
"repo": "MingruiWang2017/DjangoProject",
"path": "/boards/tests/test_view_home.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MingruiWang2017/DjangoProject path: /boards/tests/test_view_home.py
# encoding: utf-8
"""
@ author: wangmingrui
@ time: 2019/9/30 14:42
@ desc:
"""
from django.test import TestCase
from django.core.urlresolvers import reverse
from django.urls import resolve
<|fim_suffix|>class HomeTests(TestCa... | code_fim | medium | {
"lang": "python",
"repo": "MingruiWang2017/DjangoProject",
"path": "/boards/tests/test_view_home.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in range(0,len(deviceslist)):
print 'current devices:'
print deviceslist[i]
devices.append(mr.waitForConnection(1.0,deviceslist[i]))
thread.start_new_thread(thread_monkey, (devices[i], ) )
time.sleep(15)<|fim_prefix|># repo: icsnju/apt-dm path: /DeviceManagerWeb/apkbat/work_thread.py
im... | code_fim | hard | {
"lang": "python",
"repo": "icsnju/apt-dm",
"path": "/DeviceManagerWeb/apkbat/work_thread.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: icsnju/apt-dm path: /DeviceManagerWeb/apkbat/work_thread.py
import sys,time,datetime,thread,os
from com.android.monkeyrunner import MonkeyRunner as mr
from com.android.monkeyrunner import MonkeyDevice as md
from com.android.monkeyrunner import MonkeyImage as mi
BASE_DIR = os.path.abspath(o... | code_fim | hard | {
"lang": "python",
"repo": "icsnju/apt-dm",
"path": "/DeviceManagerWeb/apkbat/work_thread.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: conyml/Proyecto-Estrellas-Variables path: /Desktop/FINAL-PROYECTO-ESTRELLAS-VARIABLES-master/DASCH Lightcurve info/order_lightcurves_dasch.py
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 10 11:59:55 2019
@author: Alvaro
"""
import os
import pandas as pd
from astropy.coo... | code_fim | hard | {
"lang": "python",
"repo": "conyml/Proyecto-Estrellas-Variables",
"path": "/Desktop/FINAL-PROYECTO-ESTRELLAS-VARIABLES-master/DASCH Lightcurve info/order_lightcurves_dasch.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>j = 0
DASCH_OGLE_match['DASCH ID'] = ''
for i in idx:
DASCH_OGLE_match['DASCH ID'][i] = IDS_DASCH[j]
j+=1
DASCH_OGLE_match.to_csv('DASCH-OGLE-crossmatch.csv', index = False)<|fim_prefix|># repo: conyml/Proyecto-Estrellas-Variables path: /Desktop/FINAL-PROYECTO-ESTRELLAS-VARIABLES-master/DASC... | code_fim | hard | {
"lang": "python",
"repo": "conyml/Proyecto-Estrellas-Variables",
"path": "/Desktop/FINAL-PROYECTO-ESTRELLAS-VARIABLES-master/DASCH Lightcurve info/order_lightcurves_dasch.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#CROSSMATCH de astropy entre IDs de OGLE y DASCH por las coordenadas de cada catalogo.
DASCH_coords = SkyCoord(ras_DASCH,decs_DASCH, unit = [u.hourangle,u.deg])
OGLE_coords = SkyCoord(DASCH_OGLE_match['ra'],DASCH_OGLE_match['dec'],unit=[u.hourangle,u.deg])
idx, d2d, d3d = DASCH_coords.match_to_catalog_sky... | code_fim | hard | {
"lang": "python",
"repo": "conyml/Proyecto-Estrellas-Variables",
"path": "/Desktop/FINAL-PROYECTO-ESTRELLAS-VARIABLES-master/DASCH Lightcurve info/order_lightcurves_dasch.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Quildra/tourney path: /tourney/lib/models/role.py
# -*- coding: utf-8 -*-
from sqlalchemy import Column
from sqlalchemy.types import Unicode, Integer
from sqlalchemy.orm import relationship, backref
from lib.models import Base
__all__ = ['Role']
class Role(Base):
<|fim_suffix|> users = rela... | code_fim | medium | {
"lang": "python",
"repo": "Quildra/tourney",
"path": "/tourney/lib/models/role.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def all(session):
return session.query(Role)<|fim_prefix|># repo: Quildra/tourney path: /tourney/lib/models/role.py
# -*- coding: utf-8 -*-
from sqlalchemy import Column
from sqlalchemy.types import Unicode, Integer
from sqlalchemy.orm import relationship, backref
from lib.... | code_fim | medium | {
"lang": "python",
"repo": "Quildra/tourney",
"path": "/tourney/lib/models/role.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> users = relationship("User", order_by="User.id", backref="user")
@staticmethod
def get_by_id(session, id):
return session.query(Role).filter(Role.id == id).one()
@staticmethod
def all(session):
return session.query(Role)<|fim_prefix|># repo: Quildra/tourney p... | code_fim | medium | {
"lang": "python",
"repo": "Quildra/tourney",
"path": "/tourney/lib/models/role.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: codacy-badger/pythonApps path: /colors/primaryColors.py
def diff(a, b):
return a -b
def simpleColor(r,g,b):
r = int(r)
g = int(g)
b = int(b)
bg = ir = 0
try:
if r > g and r > b:
rg = diff(r,g)
rb = diff(r,b)
if g <... | code_fim | hard | {
"lang": "python",
"repo": "codacy-badger/pythonApps",
"path": "/colors/primaryColors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if r < 65 and g < 65 and bg > 60:
return "BLUE"
rg = diff(r,g)
if g > r:
if bg > rg:
if bg <= 20:
return "TURQOISE"
else:
return "LIGHT B... | code_fim | hard | {
"lang": "python",
"repo": "codacy-badger/pythonApps",
"path": "/colors/primaryColors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rg = diff(r,g)
if g > r:
if bg > rg:
if bg <= 20:
return "TURQOISE"
else:
return "LIGHT BLUE"
else:
if rg <= 20:
if r ... | code_fim | hard | {
"lang": "python",
"repo": "codacy-badger/pythonApps",
"path": "/colors/primaryColors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: johannalbino/course_python_geek_university path: /S13 - Leitura e Escrita em Arquivos/S13E89 - Seek e Cursors.py
"""
Seek e Cursors
seek() -> É utilizado para movimentar o cursor pelo arquivo.
arquivo = open('texto.txt')
print(arquivo.read())
<|fim_suffix|>print(arquivo.read())
# readline() ... | code_fim | hard | {
"lang": "python",
"repo": "johannalbino/course_python_geek_university",
"path": "/S13 - Leitura e Escrita em Arquivos/S13E89 - Seek e Cursors.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>arquivo = open('texto.txt')
print(arquivo.read())
print(arquivo.closed) #Verifica se o arquivo está aberto ou fechado - True: Arquivo fechado / False: Arquivo aberto
arquivo.close()
print(arquivo.closed)<|fim_prefix|># repo: johannalbino/course_python_geek_university path: /S13 - Leitura e Escrita em... | code_fim | hard | {
"lang": "python",
"repo": "johannalbino/course_python_geek_university",
"path": "/S13 - Leitura e Escrita em Arquivos/S13E89 - Seek e Cursors.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>a
from app.models.user import User # noqa
from app.models.chinook import Artist, Employee, Genre, MediaType, Playlist, Album, Customer, Invoice, Track, InvoiceLine<|fim_prefix|># repo: JayGitH/SQLacodegen-FastAPI path: /backend/app/app/db/base.py
# Import all the models, so that Base has them before bei... | code_fim | medium | {
"lang": "python",
"repo": "JayGitH/SQLacodegen-FastAPI",
"path": "/backend/app/app/db/base.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JayGitH/SQLacodegen-FastAPI path: /backend/app/app/db/base.py
# Import all the models, so that Base has them before being
# imported by Alembic
<|fim_suffix|>Employee, Genre, MediaType, Playlist, Album, Customer, Invoice, Track, InvoiceLine<|fim_middle|>from app.db.base_class import Base # noqa
... | code_fim | medium | {
"lang": "python",
"repo": "JayGitH/SQLacodegen-FastAPI",
"path": "/backend/app/app/db/base.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig, ax = plt.subplots()
im, cbar = heatmap(df, c_L, m_L, ax=ax, cmap="YlGn", cbarlabel=val_label)
texts = annotate_heatmap(im, valfmt='{x:'+n_digits+'}', fsize=16)#6)
fig.tight_layout()
#plt.show()
outName = 'punzi_2Dmap_bdt_vs_'+'_trn_'+... | code_fim | hard | {
"lang": "python",
"repo": "hotdrinkbrian/pyplot_template",
"path": "/readPlot/heat_map/punzi_map_stack.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hotdrinkbrian/pyplot_template path: /readPlot/heat_map/punzi_map_stack.py
from sklearn.externals import joblib
import pandas as pd
from hm import *
from matplotlib import pyplot as plt
pth = '/home/hezhiyua/desktop/DeepTop/LLP/Limits/'+'MA/'+'bdt/'
#pth_out = '/beegfs/desy/user/hezhiyua/... | code_fim | hard | {
"lang": "python",
"repo": "hotdrinkbrian/pyplot_template",
"path": "/readPlot/heat_map/punzi_map_stack.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aerocat/CSC394-Project path: /capstone/coursesDB/dataManipulationAndPopulatingDatabase/efficientCourseAlgorithm.py
from coursesDB.dataManipulationAndPopulatingDatabase.databaseRetrieval import *
intro_courses = ["CSC400", "CSC401", "CSC402", "CSC403", "CSC406", "CSC407"]
foundation_courses = ["C... | code_fim | hard | {
"lang": "python",
"repo": "aerocat/CSC394-Project",
"path": "/capstone/coursesDB/dataManipulationAndPopulatingDatabase/efficientCourseAlgorithm.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> quarters = ["Fall", "Winter", "Spring", "Summer"]
if quarter == "Summer":
return "Fall"
else:
return quarters[quarters.index(quarter) + 1]
elective_preference = []
def have_prereqs_for_electives(number, introCourses, current_quarter, classes_per_quarter):
global elective_p... | code_fim | hard | {
"lang": "python",
"repo": "aerocat/CSC394-Project",
"path": "/capstone/coursesDB/dataManipulationAndPopulatingDatabase/efficientCourseAlgorithm.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sergeyyun/utils path: /results_notify.py
import boto3
import os
import json
from configparser import ConfigParser
parser = ConfigParser()
parser.read('config.ini')
def send_email_ses(recipients=None,
sender=None, subject=None, body=None):
ses = boto3.client('ses', region_name=parser.get('c... | code_fim | hard | {
"lang": "python",
"repo": "sergeyyun/utils",
"path": "/results_notify.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> #send the email
send_email_ses (recipients=user_email, sender=parser.get('configuration_variables', 'MAIL_DEFAULT_SENDER'), subject=subject, body=body)
print("Email notification sent")
#delete the message
message.delete()
... | code_fim | hard | {
"lang": "python",
"repo": "sergeyyun/utils",
"path": "/results_notify.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># main loop
try:
while True:
forward(50)
time.sleep(2)
reverse(50)
time.sleep(2)
turn(rspeed= 20, lspeed =50)
time.sleep(2)
turn(rspeed = 50, lspeed = 20)
time.sleep(2)
stopall()
time.sleep(10)
except KeyboardInterrupt:
GPIO.cleanup()<|fim_prefix|># repo: ucs... | code_fim | medium | {
"lang": "python",
"repo": "ucsd-cse-spis-2016/robotics-pizazz",
"path": "/test_motor.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ucsd-cse-spis-2016/robotics-pizazz path: /test_motor.py
# Pizazz Motor Test
# Moves: Forward, Reverse, turn Right, turn Left, Stop - then repeat
# Press Ctrl-C to stop
#
# To check wiring is correct ensure the order of movement as above is correct
# Run using: sudo python motorTest.py
import RP... | code_fim | medium | {
"lang": "python",
"repo": "ucsd-cse-spis-2016/robotics-pizazz",
"path": "/test_motor.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Use pika connection params to set connection details
credentials = pika.PlainCredentials('amqp', 'amqp')
connParams = pika.ConnectionParameters(
host='localhost',
port=5672,
virtual_host='/',
credentials=credentials)
# Create a PikaBusSetup instance with a listener queue, and add the m... | code_fim | hard | {
"lang": "python",
"repo": "hansehe/PikaBus",
"path": "/Examples/consumer_example.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Errors(db.Model):
id = db.Column(UUID, primary_key=True, default=uuid4)
name = db.Column(db.String(50))
description = db.Column(db.String(200))
calculation_id = db.Column(UUID, db.ForeignKey('calculation.id'))<|fim_prefix|># repo: dpPython/dpPython_165 path: /calculation_service/ser... | code_fim | medium | {
"lang": "python",
"repo": "dpPython/dpPython_165",
"path": "/calculation_service/services/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dpPython/dpPython_165 path: /calculation_service/services/models.py
from uuid import uuid4
from sqlalchemy.dialects.postgresql import UUID
from .config import db
<|fim_suffix|>class Errors(db.Model):
id = db.Column(UUID, primary_key=True, default=uuid4)
name = db.Column(db.String(50))
... | code_fim | hard | {
"lang": "python",
"repo": "dpPython/dpPython_165",
"path": "/calculation_service/services/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> id = db.Column(UUID, primary_key=True, default=uuid4)
project_id = db.Column(unique=True)
# result = db.Column(db.Decimal, default=0)
error_relation = db.relation('Errors')
class Errors(db.Model):
id = db.Column(UUID, primary_key=True, default=uuid4)
name = db.Column(db.String(50)... | code_fim | medium | {
"lang": "python",
"repo": "dpPython/dpPython_165",
"path": "/calculation_service/services/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chiachin-yen/Crowd_simulation_py3 path: /entities/obstacles.py
# obstacles for the scene
import pygame
from utils import SIM_COLORS, SCALE
from utils import euclidean_distance, vec2d
class Obstacle(object):
""" Scene obstacles """
def __init__(self, screen, oid, otype, params):
... | code_fim | hard | {
"lang": "python",
"repo": "chiachin-yen/Crowd_simulation_py3",
"path": "/entities/obstacles.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def convert_to_cells(self, grid):
pass
@property
def id(self):
return self._id
@property
def type(self):
return self._type
@property
def params(self):
return (self._params[0] / SCALE, self._params[1] / SCALE, self._params[2] / SCALE, self._pa... | code_fim | hard | {
"lang": "python",
"repo": "chiachin-yen/Crowd_simulation_py3",
"path": "/entities/obstacles.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _line_intersection(self, line, point):
""" Fine the point of intersetion of a line and a point
Line is given as (x1,y1, x2,y2), point (x,y)
based on http://paulbourke.net/geometry/pointlineplane/
"""
den = euclidean_distance((line[0],line[1]), (li... | code_fim | hard | {
"lang": "python",
"repo": "chiachin-yen/Crowd_simulation_py3",
"path": "/entities/obstacles.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>== orange:
print("Orange, no way me too!!")
else:
print("I don't really relate to people with {colour} as colour choice!")
if hobby == code:
print("HelloWorld")
else:
print("GoodbyeWorld")
'''
main()<|fim_prefix|># repo: nei1d0r/python path: /helloworld.py
def main():
print("Nam... | code_fim | hard | {
"lang": "python",
"repo": "nei1d0r/python",
"path": "/helloworld.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nei1d0r/python path: /helloworld.py
def main():
print("Name: {name}\nAge: int{age}\nFavourite Colour: {colour}\nPet name(s): {pet}\nHobbies: {hobby}".format(name = input("What is your name? "),age = int(input("How old are you? ")),colour = input("What is your favourite colour? "),pet = input(... | code_fim | hard | {
"lang": "python",
"repo": "nei1d0r/python",
"path": "/helloworld.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def build(self):
c1 = load(self, os.path.join(self.source_folder, "source.txt"))
c2 = load(self, os.path.join(self.source_folder, "..", "exported.txt"))
save(self, "build.txt", c1 + c2)
def package(self):
copy(self, "... | code_fim | hard | {
"lang": "python",
"repo": "conan-io/conan",
"path": "/conans/test/functional/layout/test_build_system_layout_helpers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (j=="C") or (j=="M") or (j=="Y"):
print("#Color")
game=False
sys.exit()
if game==True:
print("#Black&White")<|fim_prefix|># repo: Social-CodePlat/Comptt-Coding-Solutions path: /Codeforces Problems/Brain's Photos/Brain's Photos.py
import sys
r,c=[int(x) for x i... | code_fim | medium | {
"lang": "python",
"repo": "Social-CodePlat/Comptt-Coding-Solutions",
"path": "/Codeforces Problems/Brain's Photos/Brain's Photos.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Social-CodePlat/Comptt-Coding-Solutions path: /Codeforces Problems/Brain's Photos/Brain's Photos.py
import sys
r,c=[int(x) for x in input().split()]
game=True
arr=[]
for i in range(r):
arr.append(input().split())
for i in arr:
for j in i:
<|fim_suffix|> game=False
sys.... | code_fim | medium | {
"lang": "python",
"repo": "Social-CodePlat/Comptt-Coding-Solutions",
"path": "/Codeforces Problems/Brain's Photos/Brain's Photos.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> game=False
sys.exit()
if game==True:
print("#Black&White")<|fim_prefix|># repo: Social-CodePlat/Comptt-Coding-Solutions path: /Codeforces Problems/Brain's Photos/Brain's Photos.py
import sys
r,c=[int(x) for x in input().split()]
game=True
arr=[]
for i in r<|fim_middle|>ange(r):
arr... | code_fim | medium | {
"lang": "python",
"repo": "Social-CodePlat/Comptt-Coding-Solutions",
"path": "/Codeforces Problems/Brain's Photos/Brain's Photos.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>lse:
print ("I=%.1f J=%.1f"%(fi/10.0,j+(fi/10.0)))<|fim_prefix|># repo: FelipeNunes04/URI path: /1098.py
for i in range(0,22,2):
fi = float(i)
for j in range(1,4):
if((fi/10)==2.0 or (fi/10)==1.0 or (fi/10)=<|fim_middle|>=0.0):
print ("I=%d J=%d"%(i/10,j+int(fi/10)))
e | code_fim | easy | {
"lang": "python",
"repo": "FelipeNunes04/URI",
"path": "/1098.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>=0.0):
print ("I=%d J=%d"%(i/10,j+int(fi/10)))
else:
print ("I=%.1f J=%.1f"%(fi/10.0,j+(fi/10.0)))<|fim_prefix|># repo: FelipeNunes04/URI path: /1098.py
for i in range(0,22,2):
fi = float(i)
for j in rang<|fim_middle|>e(1,4):
if((fi/10)==2.0 or (fi/10)==1.0 or (fi/10)= | code_fim | easy | {
"lang": "python",
"repo": "FelipeNunes04/URI",
"path": "/1098.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FelipeNunes04/URI path: /1098.py
for i in range(0,22,2):
fi = float(i)
for j in range(1,4):
if((fi/10)==2.0 or (fi/10)==1.0 or (fi/10)=<|fim_suffix|>lse:
print ("I=%.1f J=%.1f"%(fi/10.0,j+(fi/10.0)))<|fim_middle|>=0.0):
print ("I=%d J=%d"%(i/10,j+int(fi/10)))
e | code_fim | easy | {
"lang": "python",
"repo": "FelipeNunes04/URI",
"path": "/1098.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Reports(models.Model):
report_name = models.CharField(max_length=255)
report_detail = models.TextField()
due_date = models.DateTimeField()
created_at = models.DateTimeField(auto_now_add=True)
updated_at = models.DateTimeField(auto_now_add=True)
class Report_submitting(models.M... | code_fim | hard | {
"lang": "python",
"repo": "Abdulla-Ydyrys/sdu_beta_web",
"path": "/sdu_beta_web_app/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Abdulla-Ydyrys/sdu_beta_web path: /sdu_beta_web_app/models.py
from django.db import models
from django.contrib.auth.models import AbstractUser
from django.db.models.signals import post_save
from django.dispatch import receiver
from django.core.validators import MaxValueValidator, MinValueValidato... | code_fim | hard | {
"lang": "python",
"repo": "Abdulla-Ydyrys/sdu_beta_web",
"path": "/sdu_beta_web_app/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Report_submitting(models.Model):
SUB_STATUS = (
(0, 'Not Submitted'),
(1, 'Submitted'),
(2, 'Graded'),
)
student_id = models.ForeignKey(Students, on_delete=models.CASCADE)
report_id = models.ForeignKey(Reports, on_delete=models.CASCADE)
references = model... | code_fim | hard | {
"lang": "python",
"repo": "Abdulla-Ydyrys/sdu_beta_web",
"path": "/sdu_beta_web_app/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: acpn/analytcs-challenge path: /challenge/challengeApp/migrations/0001_initial.py
# Generated by Django 3.0.5 on 2020-05-04 05:11
from django.db import migrations, models
import django.db.models.deletion
import jsonfield.fields
class Migration(migrations.Migration):
initial = True
dep... | code_fim | hard | {
"lang": "python",
"repo": "acpn/analytcs-challenge",
"path": "/challenge/challengeApp/migrations/0001_initial.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>, serialize=False, verbose_name='ID')),
('userid', models.IntegerField()),
('logdescription', models.CharField(max_length=500)),
('created', models.DateTimeField(auto_now_add=True)),
('timeresponse', models.CharField(max_length=20, null=True)... | code_fim | hard | {
"lang": "python",
"repo": "acpn/analytcs-challenge",
"path": "/challenge/challengeApp/migrations/0001_initial.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>ields.JSONField(null=True)),
],
),
migrations.CreateModel(
name='AnalyticsViews',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('viewid', models.IntegerField()... | code_fim | hard | {
"lang": "python",
"repo": "acpn/analytcs-challenge",
"path": "/challenge/challengeApp/migrations/0001_initial.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: manasishrotri/DS595CS525-RL-Projects path: /Project1/mdp_dp.py
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 17 20:26:48 2020
RL Project 1: Frozen Lake MDP
@author: Manasi Shrotri
"""
### MDP Value Iteration and Policy Iteration
### Reference: https://web.stanford.edu/class/cs234/assignment1/ind... | code_fim | hard | {
"lang": "python",
"repo": "manasishrotri/DS595CS525-RL-Projects",
"path": "/Project1/mdp_dp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Learn value function and policy by using value iteration method for a given
gamma and environment.
Parameters:
----------
P, nS, nA, gamma:
defined at beginning of file
V: value to be updated
tol: float
Terminate value iteration when
max |val... | code_fim | hard | {
"lang": "python",
"repo": "manasishrotri/DS595CS525-RL-Projects",
"path": "/Project1/mdp_dp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("CUT OF CALCULATOR")
print("Cutt off calculator @nikku ")
x = int(input("Enter your maths mark:"))
y = int(input("enter your physics mark:"))
z = int(input("enter your chemistry mark:"))
average = (y+z)/2+x
print("your cut off is :" )
print(average)<|fim_prefix|># repo: nishanthrg/cutoff... | code_fim | easy | {
"lang": "python",
"repo": "nishanthrg/cutoffcalc",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nishanthrg/cutoffcalc path: /main.py
from flask import Flask
app = Flask(__name__)
<|fim_suffix|>print("Cutt off calculator @nikku ")
x = int(input("Enter your maths mark:"))
y = int(input("enter your physics mark:"))
z = int(input("enter your chemistry mark:"))
average = (y+z)/2+x
p... | code_fim | medium | {
"lang": "python",
"repo": "nishanthrg/cutoffcalc",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print("Cutt off calculator @nikku ")
x = int(input("Enter your maths mark:"))
y = int(input("enter your physics mark:"))
z = int(input("enter your chemistry mark:"))
average = (y+z)/2+x
print("your cut off is :" )
print(average)<|fim_prefix|># repo: nishanthrg/cutoffcalc path: /main.py
from flask i... | code_fim | easy | {
"lang": "python",
"repo": "nishanthrg/cutoffcalc",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> async def disconnect(self):
if self.heartbeat_sender:
self.heartbeat_sender.cancel()
if self.__ws:
await self.__ws.close()
if self.__session:
await self.__session.close()
# Should we close event loop?
async def identify(self):
... | code_fim | hard | {
"lang": "python",
"repo": "Lapis0875/volt.py",
"path": "/volt/gateway.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lapis0875/volt.py path: /volt/gateway.py
import asyncio
import json
from enum import IntEnum, IntFlag, Enum
from random import random
from typing import Final, List
import aiohttp
from volt.events import EventManager
from volt.utils.log import get_logger, DEBUG
from volt.utils.loop_task import ... | code_fim | hard | {
"lang": "python",
"repo": "Lapis0875/volt.py",
"path": "/volt/gateway.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return len(dict(self))
def __contains__(self, item):
if item == self.key_name:
return True
return item in self._data
def iteritems(self):
yield self.key_name, self.key
for k, v in self._data.items():
yield k, v
def items(self):... | code_fim | hard | {
"lang": "python",
"repo": "ArminGruner/redpipe",
"path": "/redpipe/structs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ArminGruner/redpipe path: /redpipe/structs.py
# -*- coding: utf-8 -*-
"""
The Struct is a convenient way to access data in a hash.
Makes it possible to load data from redis as an object and access the fields.
Then store changes back into redis.
"""
from six import add_metaclass
from json.encoder ... | code_fim | hard | {
"lang": "python",
"repo": "ArminGruner/redpipe",
"path": "/redpipe/structs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bluefog-Lib/EastCoastTutorial2021 path: /test/test_notebook.py
import atexit
import functools
import glob
import os
import subprocess
import time
import papermill as pm
import pytest
SKIP_NOTEBOOKS = []
TEST_CWD = os.getcwd()
def _list_all_notebooks():
output = subprocess.check_output(["gi... | code_fim | hard | {
"lang": "python",
"repo": "Bluefog-Lib/EastCoastTutorial2021",
"path": "/test/test_notebook.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@pytest.mark.parametrize("notebook_path", _list_all_notebooks())
def test_notebooks_against_bluefog(notebook_path):
os.environ["TEST_ENV"] = "1"
try:
notebook_file = os.path.basename(notebook_path)
notebook_rel_dir = os.path.dirname(os.path.relpath(notebook_path, "."))
os.... | code_fim | medium | {
"lang": "python",
"repo": "Bluefog-Lib/EastCoastTutorial2021",
"path": "/test/test_notebook.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>X_train, X_test, y_train, y_test = cross_validation.train_test_split(features, labels, test_size=0.3, random_state=42)
clf = tree.DecisionTreeClassifier()
clf.fit(X_train, y_train)
pred = clf.predict(X_test)
print "score",clf.score(X_test, y_test)
print "poi predicted in test set", sum([i for i in pred])
... | code_fim | medium | {
"lang": "python",
"repo": "poindextrose/ud120-projects",
"path": "/evaluation/evaluate_poi_identifier.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>data_dict = pickle.load(open("../final_project/final_project_dataset.pkl", "r") )
### add more features to features_list!
features_list = ["poi", "salary"]
data = featureFormat(data_dict, features_list)
labels, features = targetFeatureSplit(data)
### your code goes here
from sklearn import cross_vali... | code_fim | hard | {
"lang": "python",
"repo": "poindextrose/ud120-projects",
"path": "/evaluation/evaluate_poi_identifier.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: poindextrose/ud120-projects path: /evaluation/evaluate_poi_identifier.py
#!/usr/bin/python
"""
Starter code for the evaluation mini-project.
Start by copying your trained/tested POI identifier from
that which you built in the validation mini-project.
This is the second step tow... | code_fim | medium | {
"lang": "python",
"repo": "poindextrose/ud120-projects",
"path": "/evaluation/evaluate_poi_identifier.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>torch_dataset = Data.TensorDataset(x,y)
loader = DataLoader(dataset=torch_dataset,batch_size=5, num_workers=2)
for epoch in range(3):
for step, (batch_x, batch_y) in enumerate(loader):
prediction = net(batch_x)
loss = loss_func(prediction, batch_y)
optimizer.z... | code_fim | medium | {
"lang": "python",
"repo": "alptkn/Deep-Learning",
"path": "/Basics/batch_train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alptkn/Deep-Learning path: /Basics/batch_train.py
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data as Data
from torch.utils.data import DataLoader
net = nn.Sequential(
nn.Linear(5,1),
nn.ReLU(),
nn.Linear(1, 1))
<|fim_suffix|>for... | code_fim | hard | {
"lang": "python",
"repo": "alptkn/Deep-Learning",
"path": "/Basics/batch_train.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>optimizer = torch.optim.SGD(net.parameters(), lr=0.001)
loss_func = nn.MSELoss()
x = torch.linspace(1,10,10)
y = torch.linspace(10,1,10)
torch_dataset = Data.TensorDataset(x,y)
loader = DataLoader(dataset=torch_dataset,batch_size=5, num_workers=2)
for epoch in range(3):
for step, (batch_x, ... | code_fim | medium | {
"lang": "python",
"repo": "alptkn/Deep-Learning",
"path": "/Basics/batch_train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> print('Your body mass index is ' + bmi(mass,height))
analysis(mass,height)
if __name__ == "__main__":
run()<|fim_prefix|># repo: JDavid550/python_challenges path: /BMI.py
import math
def bmi(mass,height):
bmi=mass/height
bmi=round(bmi,2)
bmi=str(bmi)
return bmi
... | code_fim | hard | {
"lang": "python",
"repo": "JDavid550/python_challenges",
"path": "/BMI.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JDavid550/python_challenges path: /BMI.py
import math
def bmi(mass,height):
bmi=mass/height
bmi=round(bmi,2)
bmi=str(bmi)
return bmi
def analysis(mass,height):
<|fim_suffix|>def run():
while True:
mass=input('Submit your mass in Kg: ')
try:... | code_fim | hard | {
"lang": "python",
"repo": "JDavid550/python_challenges",
"path": "/BMI.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ch9fod/Markets path: /marketsWithCons.py
# coding: utf-8
# In[1]:
from pyomo.environ import *
m = ConcreteModel()
infinity = float('inf')
# In[2]:
# sets
m.B = RangeSet(3, doc='Buses')
m.G = RangeSet(3, doc='Generators')
m.L = RangeSet(2, doc='Loads')
m.dBlocks = RangeSet(4, doc='block bids... | code_fim | hard | {
"lang": "python",
"repo": "ch9fod/Markets",
"path": "/marketsWithCons.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (summation(m.pd) ==
summation(m.pg))
m.meet = Constraint(rule=meet_rule, doc='Blocks demand = Blocks gen')
# -------------------------------------------------------------------------------
def gens_min_rule(model,i):
return (m.u[i]*m.gMin[i] <=
sum(m.pg[i,j] for ... | code_fim | hard | {
"lang": "python",
"repo": "ch9fod/Markets",
"path": "/marketsWithCons.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alokekumardas/MC_QCDTF path: /QCDTF_direct_Mu_lukas_backup.py
from ROOT import TH1F, TFile, TChain, TCanvas, gROOT
import ROOT
import sys
import math
import os
gROOT.SetBatch(True)
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-y", "--year", dest="Year", defaul... | code_fim | hard | {
"lang": "python",
"repo": "alokekumardas/MC_QCDTF",
"path": "/QCDTF_direct_Mu_lukas_backup.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
h41=TH1F("h41","h41",1,0,2)
h41.Sumw2()
tree.Draw("1 >> h41","(passPresel_Mu && nJet>=4 && nBJet>=1 && nPho==0 && nLoosePho==0)*evtWeight*PUweight*muEffWeight*btagWeight_1a*prefireSF")
#tree.Draw("1 >> h41","(passPresel_Mu && nJet>=4 && nBJet>=1 && nPho==0 && nLoosePho==0)*evtWeight*PUweight*muEffWeig... | code_fim | hard | {
"lang": "python",
"repo": "alokekumardas/MC_QCDTF",
"path": "/QCDTF_direct_Mu_lukas_backup.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JaeSeo/basic path: /7.list/3.list_functions_e.py
len 함수
len 함수는, 리스트 안의 원소 개수를 세주는 역할을 합니다.
alphabet = ["a", "b", "c", "d", "e", "f"]
print("리스트의 길이는: %d" % len(alphabet))
리스트의 길이는: 6
원소 추가하기
insert와 append를 사용하여 리스트에 원소를 추가할 수 있습니다.
numbers = []
# 마지막 위치에 5 추가
numbers.append(5)
print(numbers... | code_fim | medium | {
"lang": "python",
"repo": "JaeSeo/basic",
"path": "/7.list/3.list_functions_e.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># 인덱스 3에 있는 값 삭제
del numbers[3]
print(numbers)
# 인덱스 4부터 마지막 값까지 삭제
del numbers[4:]
print(numbers)
[1, 2, 3, 5, 6, 7, 8]
[1, 2, 3, 5]
sorted 함수
sorted 함수는 리스트의 원소들을 오름차순으로 정렬한 새로운 리스트를 리턴해줍니다.
sorted 함수를 이용하여 [8, 6, 2, 4, 5, 7, 1, 3]이라는 리스트를 정렬한 후 출력하면, [1, 2, 3, 4, 5, 6, 7, 8]이 나옵니다.
numbers = [8, 6, ... | code_fim | hard | {
"lang": "python",
"repo": "JaeSeo/basic",
"path": "/7.list/3.list_functions_e.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># 인덱스 0 자리에 0 추가
numbers.insert(0, 0)
print(numbers)
# 인덱스 3 자리에 12 추가
numbers.insert(3, 12)
print(numbers)
[5]
[5, 8]
[5, 8, 10]
[0, 5, 8, 10]
[0, 5, 8, 12, 10]
원소 빼기
del 함수를 사용함으로써 원하는 리스트의 원소를 삭제할 수 있습니다.
numbers = [1, 2, 3, 4, 5, 6, 7, 8]
# 인덱스 3에 있는 값 삭제
del numbers[3]
print(numbers)
# 인덱스 4부터 마지... | code_fim | medium | {
"lang": "python",
"repo": "JaeSeo/basic",
"path": "/7.list/3.list_functions_e.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: l0he1g/tf-exp path: /rnn/r2rt.py
# -*- coding: utf-8 -*-
import tensorflow as tf
def build_graph(vocab_size, state_size=64, batch_size=256, num_classes=6):
# Placeholders
x = tf.placeholder(tf.int32, [batch_size, None]) # [batch_size, num_steps]
seqlen = tf.placeholder(tf.int32, [batch_... | code_fim | hard | {
"lang": "python",
"repo": "l0he1g/tf-exp",
"path": "/rnn/r2rt.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(logits, y))
train_step = tf.train.AdamOptimizer(1e-4).minimize(loss)
return {
'x': x,
'seqlen': seqlen,
'y': y,
'dropout': keep_prob,
'loss': loss,
'ts': train_step,
'preds': preds,
'accuracy': accu... | code_fim | hard | {
"lang": "python",
"repo": "l0he1g/tf-exp",
"path": "/rnn/r2rt.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
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