text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> if self.isSelected() & self.corner_rect().contains(event.pos().toPoint()):
self.setCursor(Qt.SizeFDiagCursor)
else:
self.setCursor(Qt.ArrowCursor)
super().hoverMoveEvent(event)
def mousePressEvent(self, event: QMouseEvent):
""" override mouse P... | code_fim | hard | {
"lang": "python",
"repo": "mdalboni/PySide2-Widgets",
"path": "/widgets/resizable_rect_item.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Sean-Huang65/NLP-tutorial path: /model.py
import torch.nn as nn
import torch
from torch.nn import functional as F
from config import *
class EncoderRNN(nn.Module):
def __init__(self, input_size, hidden_size, n_layers=1, model_name='rnn'):
super(EncoderRNN, self).__init__()
... | code_fim | hard | {
"lang": "python",
"repo": "Sean-Huang65/NLP-tutorial",
"path": "/model.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class biEncoderLSTM(nn.Module):
def __init__(self, input_size, hidden_size, n_layers=1):
super(biEncoderLSTM, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.n_layers = n_layers
self.embedding = nn.Embedding(i... | code_fim | hard | {
"lang": "python",
"repo": "Sean-Huang65/NLP-tutorial",
"path": "/model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, hidden_size, output_size, n_layers=1, dropout_p=0.1, model_name='rnn'):
super(biDecoderLSTM, self).__init__()
# Keep parameters for reference
self.hidden_size = hidden_size
self.output_size = output_size
self.n_layers = n_layers
... | code_fim | hard | {
"lang": "python",
"repo": "Sean-Huang65/NLP-tutorial",
"path": "/model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(f' {fonte.green("Código do aluno:")} {self.codigo}\n'
f' {fonte.green("Nome:")} {self.nome}\n'
f' {fonte.green("Matrícula:")} {self.matricula}\n'
f' {fonte.green("Ano:")} {self.ano}')<|fim_prefix|># repo: senac-repos/Senac_2021-01_ALG2 p... | code_fim | medium | {
"lang": "python",
"repo": "senac-repos/Senac_2021-01_ALG2",
"path": "/Atividades/Atividade2/Classes/AlunoEnsinoMedio.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: senac-repos/Senac_2021-01_ALG2 path: /Atividades/Atividade2/Classes/AlunoEnsinoMedio.py
from Atividades.Atividade2.Classes.Aluno import Aluno
from ClassesAuxiliares.FormatFonts import FormatFonts
fonte = FormatFonts()
<|fim_suffix|> Aluno.__init__(self, codigo, nome, matricula)
s... | code_fim | medium | {
"lang": "python",
"repo": "senac-repos/Senac_2021-01_ALG2",
"path": "/Atividades/Atividade2/Classes/AlunoEnsinoMedio.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>class AlunoEnsinoMedio(Aluno):
def __init__(self, codigo, nome, matricula, ano):
Aluno.__init__(self, codigo, nome, matricula)
self.ano = ano
def imprimir(self):
print(f' {fonte.green("Código do aluno:")} {self.codigo}\n'
f' {fonte.green("Nome:")} {self... | code_fim | medium | {
"lang": "python",
"repo": "senac-repos/Senac_2021-01_ALG2",
"path": "/Atividades/Atividade2/Classes/AlunoEnsinoMedio.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>class PatcherCollection:
def __init__(self):
self.patchers = []
def __enter__(self):
for patcher in self.patchers:
patcher.__enter__()
def __exit__(self, exc_type, exc_value, traceback):
for patcher in self.patchers:
patcher.__exit__(exc_type, ... | code_fim | medium | {
"lang": "python",
"repo": "cloudfoundry/php-buildpack",
"path": "/tests/common/dingus_extension.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __enter__(self):
for patcher in self.patchers:
patcher.__enter__()
def __exit__(self, exc_type, exc_value, traceback):
for patcher in self.patchers:
patcher.__exit__(exc_type, exc_value, traceback)
def add_patcher(self, patcher):
self.patch... | code_fim | medium | {
"lang": "python",
"repo": "cloudfoundry/php-buildpack",
"path": "/tests/common/dingus_extension.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cloudfoundry/php-buildpack path: /tests/common/dingus_extension.py
from dingus import patch
def patches(patch_values):
patcher_collection = PatcherCollection()
for object_path, new_object in patch_values.iteritems():
patcher_collection.add_patcher(patch(object_path, new_object)... | code_fim | hard | {
"lang": "python",
"repo": "cloudfoundry/php-buildpack",
"path": "/tests/common/dingus_extension.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # net.para = x1 * net2.para + x2 * net.para + b
for (k, v) , (k2, v2) in zip( net.collect_params().items() , net2.collect_params().items() ):
v.set_data(v2.data() * x1 + v.data() * x2 + b)
# train
def test():
metric = mx.metric.Accuracy()
for data, label in val_data:
X... | code_fim | hard | {
"lang": "python",
"repo": "bdus/programpractice",
"path": "/mxnet/mnist_semi/semi/train_mt.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bdus/programpractice path: /mxnet/mnist_semi/semi/train_mt.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 14 12:46:58 2018
@author: bdus
baseline:
https://github.com/bdus/programpractice/blob/master/mxnet/mnist_semi/supervised/experiments/finetune/train_finetune.py
me... | code_fim | hard | {
"lang": "python",
"repo": "bdus/programpractice",
"path": "/mxnet/mnist_semi/semi/train_mt.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#net.load_parameters(os.path.join('symbols','para','%s.params'%(modelname)))
# g(x) : stochastic input augmentation function
def g(x):
return x + nd.random.normal(0,stochastic_ratio,shape=x.shape)
# loss function
l_logistic = gloss.SoftmaxCrossEntropyLoss()
l_l2loss = gloss.L2Loss()
metric = mx.me... | code_fim | hard | {
"lang": "python",
"repo": "bdus/programpractice",
"path": "/mxnet/mnist_semi/semi/train_mt.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: freesan44/LeetCode path: /LeetCode_1913.py
class Solution:
def maxProductDifference(self, nums: List[int]) -> int:
<|fim_suffix|>if __name__ == '__main__':
nums = [4,2,5,9,7,4,8]
ret = Solution().maxProductDifference(nums)
print(ret)<|fim_middle|> nums.sort()
# prin... | code_fim | medium | {
"lang": "python",
"repo": "freesan44/LeetCode",
"path": "/LeetCode_1913.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
nums = [4,2,5,9,7,4,8]
ret = Solution().maxProductDifference(nums)
print(ret)<|fim_prefix|># repo: freesan44/LeetCode path: /LeetCode_1913.py
class Solution:
def maxProductDifference(self, nums: List[int]) -> int:
<|fim_middle|> nums.sort()
# prin... | code_fim | medium | {
"lang": "python",
"repo": "freesan44/LeetCode",
"path": "/LeetCode_1913.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tommydenton/tinkering path: /IOT/weatherDisplay/weatherDisplay.py
import os, syslog
import pygame
import time
import datetime
import pywapi
import string
# Weather Icons used with the following permissions:
#
# VClouds Weather Icons
# Created and copyrighted by VClouds - http://vclouds.deviantar... | code_fim | hard | {
"lang": "python",
"repo": "tommydenton/tinkering",
"path": "/IOT/weatherDisplay/weatherDisplay.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sfn = pygame.font.match_font('freemono')
suplargeFont = pygame.font.SysFont( fn, 50)
largeFont = pygame.font.SysFont( fn, 44)
medFont = pygame.font.Font(fn, 20)
smallFont = pygame.font.SysFont( sfn, 18)
supsmallFont = pygame.font.SysFont( sfn, 13)
forcastFont = pygame.font.Font... | code_fim | hard | {
"lang": "python",
"repo": "tommydenton/tinkering",
"path": "/IOT/weatherDisplay/weatherDisplay.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: strogo/lre path: /python/lre/test/test_serialization.py
import unittest
import lre
# Disable preallocated buffer
newlre = lre.LRE(0)
lre.dumps = newlre.pack
lre.loads = newlre.load
class TestOrder(unittest.TestCase):
def testTypes(self):
l1 = [float('-inf'), -10.5, -1, 0, 1, 10.5, ... | code_fim | hard | {
"lang": "python",
"repo": "strogo/lre",
"path": "/python/lre/test/test_serialization.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> l1 = [-0.999, -0.995, -0.8001, -0.1234, 0, 0.1, 0.1, 0.101, 0.801]
l2 = sorted(l1, key=lre.dumps)
self.assertEqual(l1, l2, 'invalid order')
def testSortingString(self):
l1 = [['00', 2], ['000', 3]]
l2 = sorted(l1, key=lre.dumps)
self.assertEqual(l1, l2,... | code_fim | hard | {
"lang": "python",
"repo": "strogo/lre",
"path": "/python/lre/test/test_serialization.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yjs1210/cardcounting path: /tests/test_hand.py
import pytest
import os
import sys
ROOT = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..")
sys.path.append(os.path.join(ROOT, "src"))
from blackjack import Deck, Hand, Cards, HandTypes
def test_hand_basic_functions():
deck = Deck... | code_fim | hard | {
"lang": "python",
"repo": "yjs1210/cardcounting",
"path": "/tests/test_hand.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> hand.delete_card(Cards.ACE)
hand_type, aces, lower_bound, upper_bound = hand.parse_hand()
assert hand_type == HandTypes.HARD
assert lower_bound == 12
assert upper_bound == 12
hand = Hand([Cards.TWO, Cards.TWO])
hand_type, aces, lower_bound, upper_bound = hand.parse_hand()
... | code_fim | hard | {
"lang": "python",
"repo": "yjs1210/cardcounting",
"path": "/tests/test_hand.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def welcome(self,friend):
print(self.name,"的朋友是",friend)
def __gender(self):
print("性别是",self.__sex)<|fim_prefix|># repo: Teddy2007/myturtle path: /Person.py
class Person:
def __init__(self,name,age,sex):
self.name=name
self.age=age
self.__sex="男"
... | code_fim | medium | {
"lang": "python",
"repo": "Teddy2007/myturtle",
"path": "/Person.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Teddy2007/myturtle path: /Person.py
class Person:
def __init__(self,name,age,sex):
<|fim_suffix|> def myage(self):
print("I am",self.age,"years old")
def welcome(self,friend):
print(self.name,"的朋友是",friend)
def __gender(self):
print("性别是",self.__sex)<|fim_... | code_fim | medium | {
"lang": "python",
"repo": "Teddy2007/myturtle",
"path": "/Person.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def myage(self):
print("I am",self.age,"years old")
def welcome(self,friend):
print(self.name,"的朋友是",friend)
def __gender(self):
print("性别是",self.__sex)<|fim_prefix|># repo: Teddy2007/myturtle path: /Person.py
class Person:
def __init__(self,name,age,sex):
... | code_fim | medium | {
"lang": "python",
"repo": "Teddy2007/myturtle",
"path": "/Person.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print sudoku.updateFactor(BOX, 0)
sudoku = sudoku.setVariable(0, 0, 8)
print sudoku.row(0)
print sudoku.updateAllFactors()
print sudoku.updateVariableFactors((1, 2))
print sudoku.getSuccessors()
solveCSP(Sudoku(boardEasy))<|fim_prefix|># repo: Bryanlee99/CS182 path: /sudoku/Testing.py
from sudoku i... | code_fim | easy | {
"lang": "python",
"repo": "Bryanlee99/CS182",
"path": "/sudoku/Testing.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bryanlee99/CS182 path: /sudoku/Testing.py
from sudoku import *
sudoku = Sudoku(boardHard)
sudoku.board
print sudoku.box(0)
<|fim_suffix|>print sudoku.updateFactor(BOX, 0)
sudoku = sudoku.setVariable(0, 0, 8)
print sudoku.row(0)
print sudoku.updateAllFactors()
print sudoku.updateVariab... | code_fim | easy | {
"lang": "python",
"repo": "Bryanlee99/CS182",
"path": "/sudoku/Testing.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> i_code_B_avg = np.mean(np.array(i_code_B), axis=0)
#i_code_B_var = np.sqrt(np.var(np.array(i_code_B), axis=0))
#i_code_B_up = i_code_B_avg + i_code_B_var
#i_code_B_down = i_code_B_avg - i_code_B_var
i_code_B_up = np.ndarray.max(np.array(i_code_B), axis=0)
i_code_B_down = np.nd... | code_fim | hard | {
"lang": "python",
"repo": "kevin105150/EMG_Analysis",
"path": "/analysis_dl.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kevin105150/EMG_Analysis path: /analysis_dl.py
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 6 15:19:18 2021
@author: csyu
"""
import os
import numpy as np
import csv
import dictlearn as dl
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use('Agg')
import tkinter as... | code_fim | hard | {
"lang": "python",
"repo": "kevin105150/EMG_Analysis",
"path": "/analysis_dl.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: duarte28nm/SR1 path: /MMC/server.py
# server.py
import socket
# calcular peso
def CalcI(peso, altura):
if (altura <= 2.5): # altura menor que 2.5m
imc = round(peso / (altura * altura), 1)
return imc
else:
imc = round(peso * 10000 / (altura * altura), 1)
<|fi... | code_fim | medium | {
"lang": "python",
"repo": "duarte28nm/SR1",
"path": "/MMC/server.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># obter o nome da máquina local
host = socket.gethostname()
port = 9999
# vincular à porta
serversocket.bind((host, port))
# enfileira até 5 solicitações
serversocket.listen(5)
while True:
# estabelecer valores
print(entrada)
try:
peso = float(entrada[0])
altura = float(entr... | code_fim | medium | {
"lang": "python",
"repo": "duarte28nm/SR1",
"path": "/MMC/server.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Press the green button in the gutter to run the script.
if __name__ == '__main__':
print_hi('PyCharm')
# See PyCharm help at https://www.jetbrains.com/help/pycharm/<|fim_prefix|># repo: monmokk/pyStudy path: /main.py
# coding=utf-8
# This is a sample Python script.
# Press ⌃R to execute it or ... | code_fim | hard | {
"lang": "python",
"repo": "monmokk/pyStudy",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: monmokk/pyStudy path: /main.py
# coding=utf-8
# This is a sample Python script.
# Press ⌃R to execute it or replace it with your code.
# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.
<|fim_suffix|>
# Press the green button in the gutter to run t... | code_fim | hard | {
"lang": "python",
"repo": "monmokk/pyStudy",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.RenameField(
model_name='review',
old_name='body',
new_name='general_info',
),
migrations.AddField(
model_name='review',
name='payment_methods',
field=models.ManyToManyField(blank=... | code_fim | medium | {
"lang": "python",
"repo": "urosmarolt/dj_blog",
"path": "/blog/migrations/0008_auto_20160507_1744.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: urosmarolt/dj_blog path: /blog/migrations/0008_auto_20160507_1744.py
# -*- coding: utf-8 -*-
# Generated by Django 1.9.6 on 2016-05-07 17:44
from __future__ import unicode_literals
import datetime
from django.db import migrations, models
from django.utils.timezone import utc
class Migration(mi... | code_fim | medium | {
"lang": "python",
"repo": "urosmarolt/dj_blog",
"path": "/blog/migrations/0008_auto_20160507_1744.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> data=codecs.open("data/dict/english.txt",'rb','utf-8')
wordList=data.readlines()
data=codecs.open("data/dict/indon.txt",'rb','utf-8')
indonList=data.readlines()
def start(appid,threadID):
print("======Starting Filtering=======")
msg='Initiate filtering for %s' ... | code_fim | hard | {
"lang": "python",
"repo": "hazimhanif/OpiClass",
"path": "/OpiClass_filter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def isEnglish(wordEng):
if wordEng in map(str.lower,[x.strip("\r\n\t") for x in wordList]):
#print("English: "+wordEnglish)
return 1
return 0
def getReviews(data,threadID,appid):
global english_count
global indon_count
global total_count
... | code_fim | hard | {
"lang": "python",
"repo": "hazimhanif/OpiClass",
"path": "/OpiClass_filter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ultimitech/tranai_site3 path: /tranai/models.py
from django.db import models
from django.core.validators import RegexValidator
from django.utils.translation import gettext_lazy as _
# from rest_framework import serializers
# from django.utils.translation import gettext as _
from django.core.valid... | code_fim | hard | {
"lang": "python",
"repo": "ultimitech/tranai_site3",
"path": "/tranai/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># class TranslationSerializer(serializers.ModelSerializer):
# class Meta:
# model = Translation
# fields = ('id', 'lan', 'tran_title', 'descrip', 'blkc', 'subc', 'senc', 'xcrip', 'li', 'pubdate', 'version', 'document', 'eng_tran')
# class Task(models.Model):
# role =
# attendees = models.Ma... | code_fim | hard | {
"lang": "python",
"repo": "ultimitech/tranai_site3",
"path": "/tranai/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
admin.site.register(Weather)
admin.site.register(UpdateDay)<|fim_prefix|># repo: DollaR84/elrusapps path: /weather/admin.py
from django.contrib import admin
<|fim_middle|># Register your models here.
from .models import Weather
from .models import UpdateDay
| code_fim | medium | {
"lang": "python",
"repo": "DollaR84/elrusapps",
"path": "/weather/admin.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>from .models import Weather
from .models import UpdateDay
admin.site.register(Weather)
admin.site.register(UpdateDay)<|fim_prefix|># repo: DollaR84/elrusapps path: /weather/admin.py
from django.contrib import admin
<|fim_middle|># Register your models here.
| code_fim | easy | {
"lang": "python",
"repo": "DollaR84/elrusapps",
"path": "/weather/admin.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DollaR84/elrusapps path: /weather/admin.py
from django.contrib import admin
<|fim_suffix|>from .models import Weather
from .models import UpdateDay
admin.site.register(Weather)
admin.site.register(UpdateDay)<|fim_middle|># Register your models here.
| code_fim | easy | {
"lang": "python",
"repo": "DollaR84/elrusapps",
"path": "/weather/admin.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>10-mbps", 1), ("speed-100-mbps", 2), ("not-applicable", 3)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: aniDevEthernetCurrentSpeed.setStatus('current')
if mibBuilder.loadTexts: aniDevEthernetCurrentSpeed.setDescription('Displays the current ethernet speed of the device ')
aniDevEthernetCurrentDupl... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/DEVETHERNET-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>t(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("auto-negotiate", 1), ("speed-100mbps-full", 2), ("speed-100mbps-half", 3), ("speed-10mbps-full", 4), ("speed-10mbps-half", 5))).clone('auto-negotiate')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: aniDevEthernetConfigMode.setStatus('current')
if mi... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/DEVETHERNET-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp-with-texts/DEVETHERNET-MIB.py
#
# PySNMP MIB module DEVETHERNET-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/DEVETHERNET-MIB
# Produced by pysmi-0.3.4 at Wed May 1 12:41:52 2019
# On host DAVWANG4-M-... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/DEVETHERNET-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: udaloff22/django_movie path: /testsite/main/migrations/0001_initial.py
# Generated by Django 3.1.5 on 2021-02-12 08:20
import datetime
from django.db import migrations, models
import django.db.models.deletion
import django.db.models.fields
class Migration(migrations.Migration):
initial = ... | code_fim | hard | {
"lang": "python",
"repo": "udaloff22/django_movie",
"path": "/testsite/main/migrations/0001_initial.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>s.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='main.review', verbose_name='Parent')),
],
options={
'verbose_name': 'Review',
'verbose_name_plural': 'Reviews',
},
),
migrations.CreateM... | code_fim | hard | {
"lang": "python",
"repo": "udaloff22/django_movie",
"path": "/testsite/main/migrations/0001_initial.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
硬编码音频素材文件
先暂时这样以后有空再改
"""
super().__init__()
self.VoicesFiles = {
'表演绝活': {
'file': '0.mp3',
'tag': '普通'
},
'iloveyou': {
'file': '1.mp3',
'tag': '卖萌'
... | code_fim | hard | {
"lang": "python",
"repo": "hailong-z/nonebot2_miya",
"path": "/omega_miya/plugins/miya_button/resources/__init__.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hailong-z/nonebot2_miya path: /omega_miya/plugins/miya_button/resources/__init__.py
import os
import random
class Voice(object):
def __init__(self):
self.VoicesFiles = dict()
def get_voice_filepath(self, voice: str) -> str:
plugin_path = os.path.dirname(os.path.abspath(... | code_fim | hard | {
"lang": "python",
"repo": "hailong-z/nonebot2_miya",
"path": "/omega_miya/plugins/miya_button/resources/__init__.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> nodeDF, edgeDF = util.buildCoauthorNodesEdges(authorNet)
nodeDF.to_csv('{0}/{1}_{2}_OneDegreeNodes.csv'.format(resultDir, fileFirstName, fileLastName))
edgeDF.to_csv('{0}/{1}_{2}_OneDegreeEdges.csv'.format(resultDir, fileFirstName, fileLastName))
except Exception a... | code_fim | medium | {
"lang": "python",
"repo": "srhoades10/CollaborationNetworks",
"path": "/citationsAndcollaborations.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: srhoades10/CollaborationNetworks path: /citationsAndcollaborations.py
""" Query pubmed and Arxiv to generate citation/collaboration networks.
Examples herein include Albert-Laszlo Barabasi, my (much sparser) network
Default parameters are to limit the number of citations, and keep to wi... | code_fim | hard | {
"lang": "python",
"repo": "srhoades10/CollaborationNetworks",
"path": "/citationsAndcollaborations.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if ('{0}_{1}_ColabNet.json'.format(fileFirstName, fileLastName) not in os.listdir(resultDir)
or overwrite == True):
with open('{0}/{1}_{2}_Papers.json'.format(resultDir, fileFirstName, fileLastName), 'r') as fin:
authorDict = json.load(fin)
... | code_fim | hard | {
"lang": "python",
"repo": "srhoades10/CollaborationNetworks",
"path": "/citationsAndcollaborations.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>uito perto')
if d>=102:
print('Muito longe')
else:
print('Acertou!')<|fim_prefix|># repo: gabriellaec/desoft-analise-exercicios path: /backup/user_086/ch30_2019_08_21_18_30_32_558782.py
import math
velocidade=float(input('Qual a velocidade da sua jaca? '<|fim_middle|>))
angulo=float(input('Qual é o ân... | code_fim | medium | {
"lang": "python",
"repo": "gabriellaec/desoft-analise-exercicios",
"path": "/backup/user_086/ch30_2019_08_21_18_30_32_558782.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gabriellaec/desoft-analise-exercicios path: /backup/user_086/ch30_2019_08_21_18_30_32_558782.py
import math
velocidade=float(input('Qual a velocidade da sua jaca? '<|fim_suffix|>uito perto')
if d>=102:
print('Muito longe')
else:
print('Acertou!')<|fim_middle|>))
angulo=float(input('Qual é o ân... | code_fim | medium | {
"lang": "python",
"repo": "gabriellaec/desoft-analise-exercicios",
"path": "/backup/user_086/ch30_2019_08_21_18_30_32_558782.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> '))
g=9.8
d=(velocidade**2*math.sin(2*angulo))/g
if d<=98:
print('Muito perto')
if d>=102:
print('Muito longe')
else:
print('Acertou!')<|fim_prefix|># repo: gabriellaec/desoft-analise-exercicios path: /backup/user_086/ch30_2019_08_21_18_30_32_558782.py
import math
velocidade=float(input('Qual a velo... | code_fim | medium | {
"lang": "python",
"repo": "gabriellaec/desoft-analise-exercicios",
"path": "/backup/user_086/ch30_2019_08_21_18_30_32_558782.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BongoHive/magriculture path: /magriculture/fncs/management/commands/fncs_users_find_bad_lengths.py
from django.contrib.auth.models import User
from django.core.management.base import BaseCommand
# Example usage:
# python manage.py fncs_users_find_bad_lengths
class Command(BaseCommand):
<|fim_s... | code_fim | hard | {
"lang": "python",
"repo": "BongoHive/magriculture",
"path": "/magriculture/fncs/management/commands/fncs_users_find_bad_lengths.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> for user in users:
stripped = user.username.replace(' ', '')
length = len(stripped)
if length > expected_length:
self.stdout.write(user.username + '\n')<|fim_prefix|># repo: BongoHive/magriculture path: /magriculture/fncs/management/commands/fnc... | code_fim | hard | {
"lang": "python",
"repo": "BongoHive/magriculture",
"path": "/magriculture/fncs/management/commands/fncs_users_find_bad_lengths.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> help = "Search for too long and too short numbers (+260 numbers only)"
def handle(self, *args, **options):
users = User.objects.filter(username__startswith='+260')
total = len(users)
expected_length = 13
if total == 0:
self.stdout.write('No users start... | code_fim | medium | {
"lang": "python",
"repo": "BongoHive/magriculture",
"path": "/magriculture/fncs/management/commands/fncs_users_find_bad_lengths.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>######################################
# Residual Calculation for least squares
def res(p, y, x):
Gam, Del, Sca = p
y_fit = inversegaussian(x, Gam, Del, Sca)
err = y - y_fit
return err
######################################<|fim_prefix|># repo: hdrake/so_lagrangian_upwelling path: /inver... | code_fim | hard | {
"lang": "python",
"repo": "hdrake/so_lagrangian_upwelling",
"path": "/inversegaussian.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hdrake/so_lagrangian_upwelling path: /inversegaussian.py
import numpy as np
######################################
# Inverse Gaussian (scaled)
def inversegaussian(x, Gamma, Delta, Scaling):
inversegaussian = []
for i in range(x.size):
inversegaussian += [Scaling*(((Gamma**3)/(4 *... | code_fim | medium | {
"lang": "python",
"repo": "hdrake/so_lagrangian_upwelling",
"path": "/inversegaussian.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jankowskipawel/PZ-NETTOM path: /python/script2.py
#!/var/www/html/cgi-enabled/env/bin/python3
from MySQLdb import _mysql
from config import *
import datetime
import math
import random
ram = "1GB"
print("Content-type: text/html\n\n")
print("<html>\n<body>")
print( "<div style=\"width: 100%; font-... | code_fim | hard | {
"lang": "python",
"repo": "jankowskipawel/PZ-NETTOM",
"path": "/python/script2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#data = EmptyToPi(data)
data = EmptyToRandom(data, 1, 10, 1)
data = CiezkiSkrypt(data)
#print(data)
################################
dateend = datetime.datetime.now()
elapsedTime=dateend-datestart
totalTime+=elapsedTime
print(f"<br>Elapsed time (script execution): {elapsedTime} (Started: {datestart}, ... | code_fim | hard | {
"lang": "python",
"repo": "jankowskipawel/PZ-NETTOM",
"path": "/python/script2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def CiezkiSkrypt(dataset):
#dataset = list(dataset)
for row in range(len(dataset)):
dataset[row] = list(dataset[row])
for col in range(len(dataset[row])):
if(isinstance(dataset[row][col], (float))):
dataset[row][col] = math.log((dataset[row][col]**(1/flo... | code_fim | hard | {
"lang": "python",
"repo": "jankowskipawel/PZ-NETTOM",
"path": "/python/script2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_func(self):
return self.request.user.is_staff<|fim_prefix|># repo: codeforamerica/intake path: /user_accounts/base_views.py
from django.contrib.auth.mixins import UserPassesTestMixin
<|fim_middle|>
class StaffOnlyMixin(UserPassesTestMixin):
| code_fim | easy | {
"lang": "python",
"repo": "codeforamerica/intake",
"path": "/user_accounts/base_views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: codeforamerica/intake path: /user_accounts/base_views.py
from django.contrib.auth.mixins import UserPassesTestMixin
class StaffOnlyMixin(UserPassesTestMixin):
<|fim_suffix|> return self.request.user.is_staff<|fim_middle|>
def test_func(self):
| code_fim | easy | {
"lang": "python",
"repo": "codeforamerica/intake",
"path": "/user_accounts/base_views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Robbybp/IDAES-CLC path: /idaes_models/unit/MB_CLC_dynamic/ss_sim.py
"\nH20: ", value(fs.MB_fuel.Gas_M[0,'H2O']), "kg/s",
"\nCH4: ", value(fs.MB_fuel.Gas_M[0,'CH4']), "kg/s")
print("\nOutlet gas: ",
"\nCO2: ", value(fs.MB_fuel.F[1,'CO2']), "mol/s",
... | code_fim | hard | {
"lang": "python",
"repo": "Robbybp/IDAES-CLC",
"path": "/idaes_models/unit/MB_CLC_dynamic/ss_sim.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Robbybp/IDAES-CLC path: /idaes_models/unit/MB_CLC_dynamic/ss_sim.py
"\nFe2O3: ", value(fs.MB_fuel.Solid_M[1,'Fe2O3']), "kg/s",
"\nFe3O4: ", value(fs.MB_fuel.Solid_M[1,'Fe3O4']), "kg/s",
"\nAl: ", value(fs.MB_fuel.Solid_M[1,'Al2O3']), "kg/s")
print("\nOutle... | code_fim | hard | {
"lang": "python",
"repo": "Robbybp/IDAES-CLC",
"path": "/idaes_models/unit/MB_CLC_dynamic/ss_sim.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("\n")
print("----------------------------------------------------------")
print('Total simulation time: ', value(time.time() - ts), " s")
print("----------------------------------------------------------")
# Print some variables
#print_summary_fuel_reactor(flowsheet)
... | code_fim | hard | {
"lang": "python",
"repo": "Robbybp/IDAES-CLC",
"path": "/idaes_models/unit/MB_CLC_dynamic/ss_sim.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print("Tuned: {}".format(clf_.best_params_))
print("Mean of the cv scores is {:.6f}".format(clf_.best_score_))
print("Train Score {:.6f}".format(clf_.score(X_train,y_train)))
print("Test Score {:.6f}".format(clf_.score(X_test,y_test)))
#%%
#Evaluate your result on both train and test set.
#Analyse... | code_fim | hard | {
"lang": "python",
"repo": "egeakyol/GlobalAl-Homework-and-final-project",
"path": "/Homework3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>X_train, X_test, y_train, y_test = train_test_split(data, y ,test_size=0.3, random_state=0)
clf = DecisionTreeClassifier()
#we have to define max_depth to prevent overfitting
clf.fit(X_train,y_train)
print("Train Accuracy of clf:",clf.score(X_train,y_train))
print("Test Accuracy of clf",clf.score... | code_fim | hard | {
"lang": "python",
"repo": "egeakyol/GlobalAl-Homework-and-final-project",
"path": "/Homework3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: egeakyol/GlobalAl-Homework-and-final-project path: /Homework3.py
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 8 00:45:04 2021
@author: Asus
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs
from sklearn.model_selectio... | code_fim | hard | {
"lang": "python",
"repo": "egeakyol/GlobalAl-Homework-and-final-project",
"path": "/Homework3.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
from Adafruit_BNO055 import BNO055
from time import time
from time import sleep
from sensor_msgs.msg import Imu, Temperature, MagneticField
from tf.transformations import quaternion_from_euler
from dynamic_reconfigure.server import Server
from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus... | code_fim | hard | {
"lang": "python",
"repo": "betaupsx86/medbot",
"path": "/bosch_imu_node/scripts/calibrate_bosch_imu.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not bno.begin():
raise RuntimeError('Failed to initialize BNO055! Is the sensor connected?')
# Print system status and self test result.
status, self_test, error = bno.get_system_status()
print('System status: {0}'.format(status))
print('Self test result (0x0F is normal): 0x{0... | code_fim | hard | {
"lang": "python",
"repo": "betaupsx86/medbot",
"path": "/bosch_imu_node/scripts/calibrate_bosch_imu.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: betaupsx86/medbot path: /bosch_imu_node/scripts/calibrate_bosch_imu.py
#!/usr/bin/env python
#####################################################################
# Software License Agreement (BSD License)
#
# Copyright (c) 2016, Michal Drwiega
# All rights reserved.
#
# Redistribution and use i... | code_fim | hard | {
"lang": "python",
"repo": "betaupsx86/medbot",
"path": "/bosch_imu_node/scripts/calibrate_bosch_imu.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aasthaengg/IBMdataset path: /Python_codes/p03273/s197165929.py
h,w=map(int,input().split())
a=[]
data=[0]*w
for i in range(h):
a_=input<|fim_suffix|>ange(w):
if data[j]!=n:
ans.append(a[i][j])
print(*ans,sep='')<|fim_middle|>()
if a_!='.'*w:
a.append(a_)
for j in range(w):... | code_fim | medium | {
"lang": "python",
"repo": "Aasthaengg/IBMdataset",
"path": "/Python_codes/p03273/s197165929.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>ange(w):
if data[j]!=n:
ans.append(a[i][j])
print(*ans,sep='')<|fim_prefix|># repo: Aasthaengg/IBMdataset path: /Python_codes/p03273/s197165929.py
h,w=map(int,input().split())
a=[]
data=[0]*w
for i in range(h):
a_=input()
if a_!='.'*w:
a.append(a_)
for j in range(w):
if a_[j... | code_fim | medium | {
"lang": "python",
"repo": "Aasthaengg/IBMdataset",
"path": "/Python_codes/p03273/s197165929.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>='.':
data[j]+=1
n=len(a)
for i in range(n):
ans=[]
for j in range(w):
if data[j]!=n:
ans.append(a[i][j])
print(*ans,sep='')<|fim_prefix|># repo: Aasthaengg/IBMdataset path: /Python_codes/p03273/s197165929.py
h,w=map(int,input().split())
a=[]
data=[0]*w
for i in range(h):
a_=inp... | code_fim | medium | {
"lang": "python",
"repo": "Aasthaengg/IBMdataset",
"path": "/Python_codes/p03273/s197165929.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_sum():
running_sum = 0
for i in range(2, 10**6+1):
if primes[i] == True:
running_sum += i
sum_[i] = running_sum
get_sum()
for _ in range(T):
N = int(input())
print(sum_[N])<|fim_prefix|># repo: skubatur/euler_prime_sum pa... | code_fim | hard | {
"lang": "python",
"repo": "skubatur/euler_prime_sum",
"path": "/prime_sum.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skubatur/euler_prime_sum path: /prime_sum.py
from bisect import bisect_left
T = int(input())
primes = [True for i in range(10**6+1)]
def get_primes():
p = 2
<|fim_suffix|>def get_sum():
running_sum = 0
for i in range(2, 10**6+1):
if primes[i] == True:
r... | code_fim | hard | {
"lang": "python",
"repo": "skubatur/euler_prime_sum",
"path": "/prime_sum.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.school_name
class HighSchoolStudent(Student):
school_name = "Patrick Henry Hight"
def get_school_name(self):
return 'This is a hight School student'
def get_name_capitalize(self):
original_value = super().get_name_capitalize()
return original_val... | code_fim | medium | {
"lang": "python",
"repo": "jerrylee09/pythonStudentApp",
"path": "/classes.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_school_name(self):
return self.school_name
class HighSchoolStudent(Student):
school_name = "Patrick Henry Hight"
def get_school_name(self):
return 'This is a hight School student'
def get_name_capitalize(self):
original_value = super().get_name_capitaliz... | code_fim | medium | {
"lang": "python",
"repo": "jerrylee09/pythonStudentApp",
"path": "/classes.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jerrylee09/pythonStudentApp path: /classes.py
students = []
class Student:
# static varible
school_name = "Patrick Henry"
def __init__ (self, name, student_id = 1):
self.name = name
self.student = student_id
students.append(self)
def __str__(self):
... | code_fim | hard | {
"lang": "python",
"repo": "jerrylee09/pythonStudentApp",
"path": "/classes.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jionie/Joint-Learning-3-Probalistic-Models path: /CoopNets/main.py
from model import CoopNets
from opts import opts
<|fim_suffix|> opt=opts().parse()
model=CoopNets(opt)
if opt.test:
model.test()
else:
model.train()
if __name__=='__main__':
main()<|fim_middle|... | code_fim | easy | {
"lang": "python",
"repo": "jionie/Joint-Learning-3-Probalistic-Models",
"path": "/CoopNets/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__=='__main__':
main()<|fim_prefix|># repo: jionie/Joint-Learning-3-Probalistic-Models path: /CoopNets/main.py
from model import CoopNets
from opts import opts
def main():
<|fim_middle|> opt=opts().parse()
model=CoopNets(opt)
if opt.test:
model.test()
else:
mo... | code_fim | medium | {
"lang": "python",
"repo": "jionie/Joint-Learning-3-Probalistic-Models",
"path": "/CoopNets/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.category is None:
category = self.categories.all()[0]
return reverse('category_content_detail', args=[CategoryContent.get_path(category), self.slug])<|fim_prefix|># repo: ikresoft/django-category-content path: /category_content/models.py
from django.db import models
fr... | code_fim | hard | {
"lang": "python",
"repo": "ikresoft/django-category-content",
"path": "/category_content/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ikresoft/django-category-content path: /category_content/models.py
from django.db import models
from django.core.urlresolvers import reverse
from django.utils.encoding import force_unicode
from categories.fields import CategoryM2MField
from content.models import Content
from django.utils.transla... | code_fim | medium | {
"lang": "python",
"repo": "ikresoft/django-category-content",
"path": "/category_content/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Third block
flatten = tf.keras.layers.Flatten()(maxpool2)
dense1 = tf.keras.layers.Dense(400, activation='relu',
kernel_initializer='he_uniform')(flatten)
dense2 = tf.keras.layers.Dense(120, activation='relu',
kernel_i... | code_fim | hard | {
"lang": "python",
"repo": "surajkarki66/Image-Classification-Deep-Learning",
"path": "/LeNet-5/Tensorflow/functional_api/model/model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: surajkarki66/Image-Classification-Deep-Learning path: /LeNet-5/Tensorflow/functional_api/model/model.py
import tensorflow as tf
def LeNet5(input_shape=None):
""" Building LeNet-5 Model using Functional API """
input_data = tf.keras.layers.Input(shape=input_shape)
# First block
c... | code_fim | hard | {
"lang": "python",
"repo": "surajkarki66/Image-Classification-Deep-Learning",
"path": "/LeNet-5/Tensorflow/functional_api/model/model.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return render(request,'orderdetails.html',{"dump": objectlist})
def addwishlist(request):
wishlist = wishlistmodel.objects.all()
productid = request.GET['id']
price = request.GET['price']
qty = 1
userid=request.user.id
retval = chekwishproductid(productid,price,userid)
if ... | code_fim | hard | {
"lang": "python",
"repo": "Hariharan1305/E-pharmacy",
"path": "/product/views.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Hariharan1305/E-pharmacy path: /product/views.py
from django.shortcuts import render, redirect
from django.shortcuts import get_list_or_404, get_object_or_404
from django.http import JsonResponse
from .forms import MedicineForm,AddtocartForm,OrderdetailForm,WishlistForm
from django.core import se... | code_fim | hard | {
"lang": "python",
"repo": "Hariharan1305/E-pharmacy",
"path": "/product/views.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmitry-petrov-dev/python-algorithm path: /lesson3/task9.py
# 9. Найти максимальный элемент среди минимальных элементов столбцов матрицы.
from random import randint
<|fim_suffix|>max_element = min_column[0]
for item in min_column[1:]:
if max_element < item:
max_element = item
print(f"... | code_fim | hard | {
"lang": "python",
"repo": "dmitry-petrov-dev/python-algorithm",
"path": "/lesson3/task9.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>max_element = min_column[0]
for item in min_column[1:]:
if max_element < item:
max_element = item
print(f"\nList of minimum values by columns: {min_column}")
print(f"Maximum - {max_element}")<|fim_prefix|># repo: dmitry-petrov-dev/python-algorithm path: /lesson3/task9.py
# 9. Найти максимальн... | code_fim | hard | {
"lang": "python",
"repo": "dmitry-petrov-dev/python-algorithm",
"path": "/lesson3/task9.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>outim=Image.new(fontfile.mode,(width,outy+box[1]))
outim.paste(fontfile,(0,0))
for name,im,x,y in placements:
outim.paste(im,(x,y))
print """ "{}": {{
"x": {},
"y": {},
"w": {},
"h": {}
}},""".format(name,x,y,im.size[0],im.size[1])
outfile=os.path.splitext(sys.argv[1])[0]+'-a... | code_fim | hard | {
"lang": "python",
"repo": "iokaravas/SierraDeathGenerator",
"path": "/tools/portraitpacker.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iokaravas/SierraDeathGenerator path: /tools/portraitpacker.py
import sys,os,glob
from PIL import Image
files = sorted(glob.glob('atlas/*.png'))
fontfile=Image.open(sys.argv[1])
width=fontfile.size[0]
images = {}
for path in files:
im=Image.open(path)
name=os.path.splitext(os.path.basename(path)... | code_fim | hard | {
"lang": "python",
"repo": "iokaravas/SierraDeathGenerator",
"path": "/tools/portraitpacker.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ysu-Wzy/mamlCNN path: /train.py
import torch
import numpy as np
import argparse
from fewshot_re_kit.data_loader import glove_getloader, bert_getloader
from fewshot_re_kit.tokenizer import Berttokenizer, GloveTokenizer, Alberttokenizer
import json
from meta import Meta
import time
import os
from d... | code_fim | hard | {
"lang": "python",
"repo": "ysu-Wzy/mamlCNN",
"path": "/train.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> pred = maml.evaluate(x_spt_one, y_spt_one, x_qry_one).cpu().numpy()
acc = (y_qry_one.numpy() == pred).mean()
accs.append(acc)
accs = np.array(accs).mean(axis=0).astype(np.float16)
l.append(accs)... | code_fim | hard | {
"lang": "python",
"repo": "ysu-Wzy/mamlCNN",
"path": "/train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chaitanya9899/mestro_invoice path: /src/invoice_scripts/kalmar_energi.py
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support.expected_conditions import presence_of_element_located
from selenium.webdriver.common.by import By
from s... | code_fim | hard | {
"lang": "python",
"repo": "chaitanya9899/mestro_invoice",
"path": "/src/invoice_scripts/kalmar_energi.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> table=driver.find_elements_by_xpath('//tbody/tr/td[7]')
print(len(table))
time.sleep(3)
try:
driver.find_element_by_class_name("notification-close").click()
except:
print("no pop element")
x=100
time.sleep(5)
log.job(c... | code_fim | hard | {
"lang": "python",
"repo": "chaitanya9899/mestro_invoice",
"path": "/src/invoice_scripts/kalmar_energi.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if (lst[i]+lst[j]==num):
print("\n(",lst[i],",",lst[j],")")<|fim_prefix|># repo: Aswani-kolloly/luminarPython path: /collections/list_pgm2.py
lst=list()
r=int(input("enter range of list"))
print("Enter elements")
for i in range(0,r):
lst.append(int(input()))
print("\nList\n",lst)... | code_fim | medium | {
"lang": "python",
"repo": "Aswani-kolloly/luminarPython",
"path": "/collections/list_pgm2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aswani-kolloly/luminarPython path: /collections/list_pgm2.py
lst=list()
r=int(input("enter range of list"))
print("Enter elements")
for i in <|fim_suffix|>ter number"))
print("\n 'pairs")
for i in range(0,r):
for j in range(i+1,r):
if (lst[i]+lst[j]==num):
print("\n(",lst[... | code_fim | medium | {
"lang": "python",
"repo": "Aswani-kolloly/luminarPython",
"path": "/collections/list_pgm2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>counter = 1
for code in ptr:
counter += 1
code = int(code[:-1])
#print "code received " , code , " " ,
if code not in dic.keys():
rcvd = previous_char + previous_char[0]
else:
rcvd = dic[code]
#print rcvd
fptr.write(rcvd)
dic[pointer] = previous_char + rcvd[0]
pointer += 1
previous_char ... | code_fim | medium | {
"lang": "python",
"repo": "snehasinghania/compression-algorithms",
"path": "/lzwdecoding.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
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