text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: ericav99/CAT_REU_2019 path: /catvehicle_openai_ros_code/catvehicle_env.py
import rospy
import time
import numpy as np
from geometry_msgs.msg import Twist
from std_msgs.msg import Float64, Float32
from openai_ros import robot_gazebo_env
from nav_msgs.msg import Odometry
class CATVehicleEnv(robot... | code_fim | hard | {
"lang": "python",
"repo": "ericav99/CAT_REU_2019",
"path": "/catvehicle_openai_ros_code/catvehicle_env.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _check_all_systems_ready(self):
"""
Checks that all the sensors, publishers and other simulation systems are
operational.
"""
self._check_all_sensors_ready()
#self._check_joint_states_ready()
self._check_cmd_vel_pub()
... | code_fim | hard | {
"lang": "python",
"repo": "ericav99/CAT_REU_2019",
"path": "/catvehicle_openai_ros_code/catvehicle_env.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _check_distsb_ready(self):
self.distsb = None
rospy.logdebug("Waiting for /catvehicle/distanceEstimatorSteeringBased/dist to be READY...")
while self.distsb is None and not rospy.is_shutdown():
try:
self.distsb = rospy.wait_for_message("/catvehic... | code_fim | hard | {
"lang": "python",
"repo": "ericav99/CAT_REU_2019",
"path": "/catvehicle_openai_ros_code/catvehicle_env.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brockellefson/school path: /Senior Year/Fall Semester/CS432/Project 6/sortingexamples.py
import math
import random
from random import randint
import time
def partition(arr, low, high):
i = (low - 1)
pivot = arr[high]
for j in range(low, high):
if arr[j] <= pivot:
... | code_fim | hard | {
"lang": "python",
"repo": "brockellefson/school",
"path": "/Senior Year/Fall Semester/CS432/Project 6/sortingexamples.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> quickSort(arr, 0, listLength-1)
timeoutend = time.time()
end = timeoutend - timeoutstart
print('quicksort: ' + str(end))
timeoutstart = time.time()
#heapSort(arr)
timeoutend = time.time()
end = timeoutend - timeoutstart
#print('heapsort: ' + str(end))
maxdepth = i... | code_fim | hard | {
"lang": "python",
"repo": "brockellefson/school",
"path": "/Senior Year/Fall Semester/CS432/Project 6/sortingexamples.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JBed/edx-spark path: /Lab_3/lab3.py
long(0)
else:
size = long(match.group(9))
return (Row(
host = match.group(1),
client_identd = match.group(2),
user_id = match.group(3),
date_time = parse_apache_time(match.group(4)),
me... | code_fim | hard | {
"lang": "python",
"repo": "JBed/edx-spark",
"path": "/Lab_3/lab3.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>responseCodeToCountList = responseCodeToCount.take(100)
print 'Found {} response codes'.format(len(responseCodeToCountList))
print 'Response Code Counts: {}'.format(responseCodeToCountList)
assert len(responseCodeToCountList) == 7
assert sorted(responseCodeToCountList) == [(200, 940847), (302, 16244), (3... | code_fim | hard | {
"lang": "python",
"repo": "JBed/edx-spark",
"path": "/Lab_3/lab3.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JBed/edx-spark path: /Lab_3/lab3.py
int(s[0:2]),
int(s[12:14]),
int(s[15:17]),
int(s[18:20]))
def parseApacheLogLine(logline):
""" Parse a line in the Apache Common Log format
Args:
logli... | code_fim | hard | {
"lang": "python",
"repo": "JBed/edx-spark",
"path": "/Lab_3/lab3.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tusharsadhwani/daily_byte path: /p110_birthday_cake.py
"""
You are at a birthday party and are asked to distribute cake to your
guests. Each guess is only satisfied if the size of the piece of cake
they’re given, matches their appetite (i.e. is greater than or equal to
their appetite). Given two ... | code_fim | hard | {
"lang": "python",
"repo": "tusharsadhwani/daily_byte",
"path": "/p110_birthday_cake.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>Ex: Given the following arrays appetite and cake...
appetite = [3, 4, 5], cake = [2], return 0.
"""
def max_guests(appetite: list[int], cake: list[int]) -> int:
"""Returns maximum number of guests you can satisfy"""
guest_count = 0
appetite_index = len(appetite) - 1
cake_index = len(ca... | code_fim | medium | {
"lang": "python",
"repo": "tusharsadhwani/daily_byte",
"path": "/p110_birthday_cake.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>1
return counter
print(persistence(int(input("Num:"))))<|fim_prefix|># repo: Conor12345/challenges-july-2020 path: /CW - 6 - Persisten Bugger.py
def persistence(n):
n = str(n)
counter = 0
while len(n) > 1:
sum = 1
for num in n:
<|fim_middle|> sum *= int(num)
... | code_fim | medium | {
"lang": "python",
"repo": "Conor12345/challenges-july-2020",
"path": "/CW - 6 - Persisten Bugger.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Conor12345/challenges-july-2020 path: /CW - 6 - Persisten Bugger.py
def persistence(n):
n = str(n)
counter = 0
whil<|fim_suffix|>1
return counter
print(persistence(int(input("Num:"))))<|fim_middle|>e len(n) > 1:
sum = 1
for num in n:
sum *= int(num)
... | code_fim | medium | {
"lang": "python",
"repo": "Conor12345/challenges-july-2020",
"path": "/CW - 6 - Persisten Bugger.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wmengyu/spiderDay1 path: /Day2/5-ajax-douban.py
import urllib.request
import urllib.parse
url = 'https://movie.douban.com/typerank?type_name=%E5%8A%A8%E4%BD%9C&type=5&interval_id=100:90&action=&'
headers={
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ... | code_fim | medium | {
"lang": "python",
"repo": "wmengyu/spiderDay1",
"path": "/Day2/5-ajax-douban.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>data = urllib.parse.urlencode(data).encode('utf-8')
#构建路径(get请求)
# url += data
#构建请求(post请求)
req = urllib.request.Request(url=url, data=data, headers=headers)
#发送请求
res = urllib.request.urlopen(req)
# print(res.read().decode('utf-8'))
with open('douban.html', 'wb') as fw:
fw.write(res.read())<|fim_p... | code_fim | medium | {
"lang": "python",
"repo": "wmengyu/spiderDay1",
"path": "/Day2/5-ajax-douban.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keita8723/mypkg path: /scripts/twice.py
#!/usr/bin/env python3
import rospy
from std_msgs.msg import Float32
n = 0
def cb(message):
global n
n = message.data*2
<|fim_suffix|>
rospy.init_node('twice')
sub = rospy.Subscriber('count_up', Float32, cb)
pub = rospy.Publisher('twice', Float3... | code_fim | medium | {
"lang": "python",
"repo": "keita8723/mypkg",
"path": "/scripts/twice.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> global n
n = message.data*2
if n > 100:
n = message.data*3
if n > 300:
n = message.data/5
rospy.init_node('twice')
sub = rospy.Subscriber('count_up', Float32, cb)
pub = rospy.Publisher('twice', Float32, queue_size=1)
rate = rospy.Rate(10)
while not rospy.is_shutdown():... | code_fim | easy | {
"lang": "python",
"repo": "keita8723/mypkg",
"path": "/scripts/twice.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>rospy.init_node('twice')
sub = rospy.Subscriber('count_up', Float32, cb)
pub = rospy.Publisher('twice', Float32, queue_size=1)
rate = rospy.Rate(10)
while not rospy.is_shutdown():
pub.publish(n)
rate.sleep()<|fim_prefix|># repo: keita8723/mypkg path: /scripts/twice.py
#!/usr/bin/env python3
impor... | code_fim | easy | {
"lang": "python",
"repo": "keita8723/mypkg",
"path": "/scripts/twice.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Thorjezar/pythonDemo path: /homework/3.17-4.py
#coding=utf-8
'''
4. 编写程序，完成“名片管理器”项目
需要完成的基本功能：
添加名片
删除名片
修改名片
查询名片
退出系统
程序运行后，除非选择退出系统，否则重复执行功能
'''
#初始化一个名片存储
cards = {}
i = 0
while i == 0:
print("=" * 10 + "欢迎使用名片管理器" + "=" * 10)
print("1.添加名片")
print("2.删除名片")
print("3.修改名片"... | code_fim | hard | {
"lang": "python",
"repo": "Thorjezar/pythonDemo",
"path": "/homework/3.17-4.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> updateId = input("请输入要修改的编号：")
updateId = int(updateId)
info["name"] = input("修改编号%d名片的姓名" % updateId)
info["phonenumber"] = input("修改编号%d名片的电话号" % updateId)
info["wechat"] = input("修改编号%d名片的微信号" % updateId)
c... | code_fim | hard | {
"lang": "python",
"repo": "Thorjezar/pythonDemo",
"path": "/homework/3.17-4.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ankit-w/machine-translation path: /fileprocessor.py
with open("small_vocab_en") as xh:
with open('small_vocab_fr') as yh:
with open("en_fr","w") as zh:
#Read first file
xlines = xh.readlines()
#Read second file
ylines = yh.readlines()
<|fim_suffix|> for i in rang... | code_fim | medium | {
"lang": "python",
"repo": "ankit-w/machine-translation",
"path": "/fileprocessor.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(len(xlines)):
line = ylines[i].strip() + '\t' + xlines[i]
zh.write(line)<|fim_prefix|># repo: ankit-w/machine-translation path: /fileprocessor.py
with open("small_vocab_en") as xh:
with open('small_vocab_fr') as yh:
with open("en_fr","w") as zh:
<|fim_middle|> ... | code_fim | hard | {
"lang": "python",
"repo": "ankit-w/machine-translation",
"path": "/fileprocessor.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Katerina964/study path: /второе вхождение.py
string = input()
substring = 'f'
kst = len(string)
pos = string.fi<|fim_suffix|>2 == -1:
print(pos2)
else:
print(pos2 + pos + 1)<|fim_middle|>nd(substring)
newString = string[pos + 1:]
if pos == -1:
print(-2)
elif pos != -1:
... | code_fim | medium | {
"lang": "python",
"repo": "Katerina964/study",
"path": "/второе вхождение.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>-2)
elif pos != -1:
pos2 = newString.find(substring)
if pos2 == -1:
print(pos2)
else:
print(pos2 + pos + 1)<|fim_prefix|># repo: Katerina964/study path: /второе вхождение.py
string = input()
substring = 'f'
kst = len(string)
pos = string.fi<|fim_middle|>nd(substring)
newStrin... | code_fim | medium | {
"lang": "python",
"repo": "Katerina964/study",
"path": "/второе вхождение.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>SCOPES = ['https://www.googleapis.com/auth/analytics.readonly']
KEY_FILE_LOCATION = os.getenv('GOOGLE_APPLICATION_CREDENTIALS')
if KEY_FILE_LOCATION:
credentials = ServiceAccountCredentials.from_json_keyfile_name(KEY_FILE_LOCATION, SCOPES)
else:
credentials = None
# Cell
def ga_to_df(start_dat... | code_fim | medium | {
"lang": "python",
"repo": "andrewm4894/am4894ga",
"path": "/am4894ga/core.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not view_id:
view_id = os.getenv('GOOGLE_ANALYTICS_VIEW_ID')
qry = {
'dateRanges': [{'startDate': start_date, 'endDate': end_date}],
'metrics': [{'expression': m} for m in metrics],
'dimensions': [{'name': m} for m in dimensions],
}
if filters:
qr... | code_fim | medium | {
"lang": "python",
"repo": "andrewm4894/am4894ga",
"path": "/am4894ga/core.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewm4894/am4894ga path: /am4894ga/core.py
# AUTOGENERATED! DO NOT EDIT! File to edit: 00_core.ipynb (unless otherwise specified).
__all__ = ['SCOPES', 'KEY_FILE_LOCATION', 'ga_to_df']
# Cell
from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredent... | code_fim | medium | {
"lang": "python",
"repo": "andrewm4894/am4894ga",
"path": "/am4894ga/core.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nizarhmain/master_thesis path: /private_data/enclave.py
from ecies.utils import generate_key
from ecies import encrypt, decrypt
import binascii
import coincurve
pub = '0227ffac7d33231086df84e12f0856c0e985c18d3daa2c94c7abcbff9a6aa8b258'
priv = 'ee113297d1fb3c214722aadf59a3d94dff24264ffc5c34b78... | code_fim | hard | {
"lang": "python",
"repo": "nizarhmain/master_thesis",
"path": "/private_data/enclave.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # pub = '0227ffac7d33231086df84e12f0856c0e985c18d3daa2c94c7abcbff9a6aa8b258'
# priv = 'ee113297d1fb3c214722aadf59a3d94dff24264ffc5c34b78c903b36eb1aeca8'
# print(pub)
# pubk = coincurve.PublicKey.from_hex(pub)
# print(coincurve_pubk)
# print(coincurve_privk.secret)
# k = generate_key()
# print(... | code_fim | medium | {
"lang": "python",
"repo": "nizarhmain/master_thesis",
"path": "/private_data/enclave.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zdgriffith/ShowerLLH_scripts path: /run_data/save_hist.py
#!/usr/bin/env python
###########################################################################
# Replacement for save_data.py takes a collection of hdf5 files, and #
# builds desired histograms for rapid plotting ... | code_fim | hard | {
"lang": "python",
"repo": "zdgriffith/ShowerLLH_scripts",
"path": "/run_data/save_hist.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return q
def histWriter(config, file, outfile):
# Bin values
eList = ['p','h','o','f']
decbins = ['0-12','12-24','24-40']
rabins = ['0-60','60-120','120-180','180-240','240-300','300-360']
# Build general list of key names to write
keyList = []
keyList += ['energy','ene... | code_fim | hard | {
"lang": "python",
"repo": "zdgriffith/ShowerLLH_scripts",
"path": "/run_data/save_hist.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># * The states whose winning rates are highly positively correlated with S&P 500 are: OH, WI, OR...
# * The states whose winning rates are highly negatively correlated with S&P 500 are: NM, OK, KS...
# * States such as MD are not likely to be affected by stock market
# In[27]:
pst_merge = pst_cat.reset... | code_fim | hard | {
"lang": "python",
"repo": "AliciaFZhang/Data-Visualization-Trump-s-winning-rate",
"path": "/Data visualization_Trump Winning Rate.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AliciaFZhang/Data-Visualization-Trump-s-winning-rate path: /Data visualization_Trump Winning Rate.py
#!/usr/bin/env python
# coding: utf-8
# # Data Visualization: Trump's Winning Rate
# This report provides detailed facts about Trump's Winning Rate and its correlation between economics indicator... | code_fim | hard | {
"lang": "python",
"repo": "AliciaFZhang/Data-Visualization-Trump-s-winning-rate",
"path": "/Data visualization_Trump Winning Rate.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for src,dst in zip(lcpaths,dstpaths):
dstdir = os.path.dirname(dst)
if not os.path.exists(dstdir):
os.mkdir(dstdir)
try:
shutil.move(src,dst)
print('moved {} -> {}'.format(src,dst))
except FileNotFoundError as e:
if os.pat... | code_fim | hard | {
"lang": "python",
"repo": "lgbouma/cdips",
"path": "/drivers/get_cdips_lc_stats.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SerCharles/SPQRNet path: /src/main.py
'''
Description: Main program used in train and testing my network
Author:Charles Shen
Date:8/22/2020
'''
import numpy as np
import time
import os
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Varia... | code_fim | hard | {
"lang": "python",
"repo": "SerCharles/SPQRNet",
"path": "/src/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> total_dist = 0
total_batch = 0
for i, (partial_shapenet, ground_truth_fine, ground_truth_coarse) in enumerate(data_loader_shapenet_val):
if device:
partial_shapenet = partial_shapenet.to(device)
ground_truth_fine = ground_truth_fine.to(device)
groun... | code_fim | hard | {
"lang": "python",
"repo": "SerCharles/SPQRNet",
"path": "/src/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DanielMevs/Tuple-Input-with-Python path: /tuple_input.py
def input_tuple_lc(prompt, types, sep):
answer_str = input(prompt)
new_list = answer_str.split(sep)
new_tuple = ()
if len(new_list) != len(types):
print("Number of values inputted do not match number of values intend... | code_fim | hard | {
"lang": "python",
"repo": "DanielMevs/Tuple-Input-with-Python",
"path": "/tuple_input.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> new_tuple = new_tuple + (new_object,)
i+=1
return new_tuple
sep = ','
prompt = "Please input a first name, last name, age, ID, and full-time(True or False) separated by '" + sep + "':"
types = (str,str,float,int,bool)
some_tuple = input_tuple(prompt,ty... | code_fim | hard | {
"lang": "python",
"repo": "DanielMevs/Tuple-Input-with-Python",
"path": "/tuple_input.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> except ValueError:
print("Error, incorrect data type inputted")
return ()
new_tuple = new_tuple + (new_object,)
i+=1
return new_tuple
sep = ','
prompt = "Please input a first name, last name, age... | code_fim | hard | {
"lang": "python",
"repo": "DanielMevs/Tuple-Input-with-Python",
"path": "/tuple_input.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leo-bart/mbsim path: /misc/BuildService/scripts/builddocsb.py
#!/usr/bin/python
import subprocess
import glob
subprocess.check_call(["pdflatex", "-halt-on-error", "-file-line-e<|fim_suffix|>-file-line-error", "main.tex"])
subprocess.check_call(["pdflatex", "-halt-on-error", "-file-line-error", ... | code_fim | hard | {
"lang": "python",
"repo": "leo-bart/mbsim",
"path": "/misc/BuildService/scripts/builddocsb.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>-file-line-error", "main.tex"])
subprocess.check_call(["pdflatex", "-halt-on-error", "-file-line-error", "main.tex"])<|fim_prefix|># repo: leo-bart/mbsim path: /misc/BuildService/scripts/builddocsb.py
#!/usr/bin/python
import subprocess
import glob
subprocess.check_call(["pdflatex", "-halt-on-error", "... | code_fim | medium | {
"lang": "python",
"repo": "leo-bart/mbsim",
"path": "/misc/BuildService/scripts/builddocsb.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Om1627/corrcoef path: /students.py
import pandas as pd
import plotly.express as px
import numpy as np
import csv
def getDataSource(data_path):
Days=[]
Marks=[]
with open(data_path) as csv_file:
csv_reader=csv.DictReader(csv_file)
for row in csv_reader:
... | code_fim | medium | {
"lang": "python",
"repo": "Om1627/corrcoef",
"path": "/students.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> data_path="./students.csv"
datasource=getDataSource(data_path)
findCorrelation(datasource)
setup()
plot()<|fim_prefix|># repo: Om1627/corrcoef path: /students.py
import pandas as pd
import plotly.express as px
import numpy as np
import csv
def getDataSource(data_path):
<|fim_m... | code_fim | hard | {
"lang": "python",
"repo": "Om1627/corrcoef",
"path": "/students.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: roholt93/macro-keyboard path: /macro-watcher.py
### Author: Roholt
### 10-2020
from ConfigLoader import ConfigLoader
from KeyboardWatcher import KeyboardWatcher
def main():
settings = ConfigLoader("./config.yml").config
<|fim_suffix|> keyboardWatcher.run()
if __name__ == "__main__":
main... | code_fim | medium | {
"lang": "python",
"repo": "roholt93/macro-keyboard",
"path": "/macro-watcher.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> keyboardWatcher.run()
if __name__ == "__main__":
main()<|fim_prefix|># repo: roholt93/macro-keyboard path: /macro-watcher.py
### Author: Roholt
### 10-2020
from ConfigLoader import ConfigLoader
from KeyboardWatcher import KeyboardWatcher
def main():
settings = ConfigLoader("./config.yml").config... | code_fim | medium | {
"lang": "python",
"repo": "roholt93/macro-keyboard",
"path": "/macro-watcher.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.parametrize("asteroids,station,expected", [
(parse_asteroid_map(
"""###
###
###"""), (1, 1), [((1, 0), 0.0), ((2, 0), 45.0), ((2, 1), 90.0), ((2, 2), 135.0), ((1, 2), 180.0), ((0, 2), 225.0), ((0, 1), 270.0), ((0, 0), 315.0)]),
(parse_asteroid_map(
"""###
... | code_fim | hard | {
"lang": "python",
"repo": "Markus-Ende/adventofcode2019",
"path": "/src/day10/test_monitoring_station.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Markus-Ende/adventofcode2019 path: /src/day10/test_monitoring_station.py
import pytest
from day10.monitoring_station import parse_asteroid_map, can_detect, count_detectable_asteroids, find_best_station, sort_for_laser_round, shoot
from common.io import read
@pytest.mark.parametrize("input,expec... | code_fim | hard | {
"lang": "python",
"repo": "Markus-Ende/adventofcode2019",
"path": "/src/day10/test_monitoring_station.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cohadar/aski path: /тестови/test_aski.py
from aski import двоцифрени
def test0():
assert двоцифрени([64, 65, 66]) == '@AB'
def test1():
assert двоцифрени(list(range(27, 33))) == ''
def test2():
<|fim_suffix|>def test3():
assert двоцифрени([100, 101, 200, 3000]) == ''
def test4... | code_fim | easy | {
"lang": "python",
"repo": "cohadar/aski",
"path": "/тестови/test_aski.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test5():
assert двоцифрени(list(range(0, 27))) == 'defghijklmnopqrstuvwxyz{|}~'<|fim_prefix|># repo: cohadar/aski path: /тестови/test_aski.py
from aski import двоцифрени
def test0():
assert двоцифрени([64, 65, 66]) == '@AB'
def test1():
assert двоцифрени(list(range(27, 33))) == ''
... | code_fim | hard | {
"lang": "python",
"repo": "cohadar/aski",
"path": "/тестови/test_aski.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cgyulay/nfl-play-prediction path: /code/guess.py
import numpy as np
from load_data import load_data
from veltman_format import teams
class PlayCallGame():
def __init__(self):
self.start()
def start(self):
data = load_data('formatted_veltman_pbp_small.pkl', False)
self.train_set... | code_fim | hard | {
"lang": "python",
"repo": "cgyulay/nfl-play-prediction",
"path": "/code/guess.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> quarter = int(row[0])
return '{0}{1} quarter'.format(quarter, self.suffix(quarter))
def format_position(self, row, def_team):
down = int(row[2])
togo = int(row[3])
yardline = int(row[4])
if yardline > 50:
yardline -= 50
yardline_str = 'your own {0} yard line'.format... | code_fim | hard | {
"lang": "python",
"repo": "cgyulay/nfl-play-prediction",
"path": "/code/guess.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> actions = ['ran the ball', 'threw the ball', 'punted the ball', 'kicked a '
'field goal']
return actions[answer]
def select_random(self):
row = np.random.randint(1, len(self.test_set_x))
return self.test_set_x[row], self.test_set_y[row]
def extract_teams(self, row):
off_on... | code_fim | hard | {
"lang": "python",
"repo": "cgyulay/nfl-play-prediction",
"path": "/code/guess.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> r"""
Returns reduced-row echelon form (RREF) and list of pivots.
If the domain is not a field then it will be converted to a field. See
:meth:`rref_den` for the fraction-free version of this routine that
returns RREF with denominator instead.
The domain mu... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/polys/matrices/domainmatrix.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sympy/sympy path: /sympy/polys/matrices/domainmatrix.py
but if
the domain is not a field then it will be converted to a field
at the end and divided by the denominator. This is most efficient
for dense matrices or for matrices with simple denominators.
... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/polys/matrices/domainmatrix.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> rref
RREF without denominator for field domains.
sympy.polys.matrices.sdm.sdm_irref
Sparse implementation of ``method='GJ'``.
sympy.polys.matrices.sdm.sdm_rref_den
Sparse implementation of ``method='FF'`` and ``method='CD'``.
sympy.polys.... | code_fim | hard | {
"lang": "python",
"repo": "sympy/sympy",
"path": "/sympy/polys/matrices/domainmatrix.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: epsdg/mltools path: /models/base_model.py
import numpy as np
import pandas as pd
from .. import utils
from sklearn.preprocessing import scale
from sklearn.impute import SimpleImputer
class BaseModel():
def __init__(self, X_train, y_train, X_test, params_file, folds_lookup,
... | code_fim | hard | {
"lang": "python",
"repo": "epsdg/mltools",
"path": "/models/base_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def evals_df(self):
'''Transform round-by-round metrics from dict to pd.DataFrame'''
parts = []
for pref in ['train', 'val']:
metrics = list(self.evals_out[pref].keys())
columns = {metric: pref + '_' + tag for metric in metrics}
df = pd.DataF... | code_fim | hard | {
"lang": "python",
"repo": "epsdg/mltools",
"path": "/models/base_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> X = np.concatenate([self.X_train.values, self.X_test.values], axis=0)
if fillna:
imputer = SimpleImputer(strategy=fill_with, verbose=1)
self.logger.info(' filling NaN...')
X[X == np.inf] = np.nan
X[X == -np.inf] = np.nan
X = imp... | code_fim | hard | {
"lang": "python",
"repo": "epsdg/mltools",
"path": "/models/base_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skoczen/will path: /will/plugins/friendly/cookies.py
from will.plugin import WillPlugin
from will.decorators import respond_to, periodic, hear, randomly, route, rendered_template, require_settings
class SnickerdoodlesPlugin(WillPlugin):
<|fim_suffix|> self.say(rendered_template("cookies.... | code_fim | medium | {
"lang": "python",
"repo": "skoczen/will",
"path": "/will/plugins/friendly/cookies.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.say(rendered_template("cookies.html", {}), message=message, html=True, )<|fim_prefix|># repo: skoczen/will path: /will/plugins/friendly/cookies.py
from will.plugin import WillPlugin
from will.decorators import respond_to, periodic, hear, randomly, route, rendered_template, require_settings
... | code_fim | medium | {
"lang": "python",
"repo": "skoczen/will",
"path": "/will/plugins/friendly/cookies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@hear("cookies", include_me=False)
def will_likes_cookies(self, message):
self.say(rendered_template("cookies.html", {}), message=message, html=True, )<|fim_prefix|># repo: skoczen/will path: /will/plugins/friendly/cookies.py
from will.plugin import WillPlugin
from will.decorators import... | code_fim | easy | {
"lang": "python",
"repo": "skoczen/will",
"path": "/will/plugins/friendly/cookies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: randy3k/SendCode path: /code_sender/iterm/__init__.py
import os
from ..applescript import osascript
ITERM = os.path.join(os.path.dirname(__file__), "iterm.applescript")
ITERM_BRACKETED = os.path.join(os.path.dirname(__file__), "iterm_bracketed.applescript")
<|fim_suffix|> if bracketed:
... | code_fim | easy | {
"lang": "python",
"repo": "randy3k/SendCode",
"path": "/code_sender/iterm/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if bracketed:
osascript(ITERM_BRACKETED, cmd, str(commit))
else:
osascript(ITERM, cmd, str(commit))<|fim_prefix|># repo: randy3k/SendCode path: /code_sender/iterm/__init__.py
import os
from ..applescript import osascript
<|fim_middle|>ITERM = os.path.join(os.path.dirname(__file__... | code_fim | hard | {
"lang": "python",
"repo": "randy3k/SendCode",
"path": "/code_sender/iterm/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ellmetha/django-machina path: /machina/apps/forum_conversation/migrations/0013_auto_20201220_1745.py
# Generated by Django 3.1.2 on 2020-12-20 22:45
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.AlterField(
... | code_fim | hard | {
"lang": "python",
"repo": "ellmetha/django-machina",
"path": "/machina/apps/forum_conversation/migrations/0013_auto_20201220_1745.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='topic',
name='created',
field=models.DateTimeField(auto_now_add=True, db_index=True, verbose_name='Creation date'),
),
migrations.AlterField(
model_name='topic',
name='... | code_fim | hard | {
"lang": "python",
"repo": "ellmetha/django-machina",
"path": "/machina/apps/forum_conversation/migrations/0013_auto_20201220_1745.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pcoder/dynamicweb path: /datacenterlight/migrations/0014_dclsectionpromopluginmodel.py
# -*- coding: utf-8 -*-
# Generated by Django 1.9.4 on 2018-03-21 19:09
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import djangocms_text_c... | code_fim | hard | {
"lang": "python",
"repo": "pcoder/dynamicweb",
"path": "/datacenterlight/migrations/0014_dclsectionpromopluginmodel.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='DCLSectionPromoPluginModel',
fields=[
('cmsplugin_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE,
parent_link=T... | code_fim | hard | {
"lang": "python",
"repo": "pcoder/dynamicweb",
"path": "/datacenterlight/migrations/0014_dclsectionpromopluginmodel.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/pulumi-google-native path: /sdk/python/pulumi_google_native/certificatemanager/v1/get_certificate_issuance_config.py
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
impo... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-google-native",
"path": "/sdk/python/pulumi_google_native/certificatemanager/v1/get_certificate_issuance_config.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Set of labels associated with a CertificateIssuanceConfig.
"""
return pulumi.get(self, "labels")
@property
@pulumi.getter
def lifetime(self) -> str:
"""
Workload certificate lifetime requested.
"""
return pulumi.get(self, "li... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-google-native",
"path": "/sdk/python/pulumi_google_native/certificatemanager/v1/get_certificate_issuance_config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_certificate_issuance_config(certificate_issuance_config_id: Optional[str] = None,
location: Optional[str] = None,
project: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) ... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-google-native",
"path": "/sdk/python/pulumi_google_native/certificatemanager/v1/get_certificate_issuance_config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def render_to_response(self, context, **response_kwargs):
response_kwargs['content_type'] = self.content_type # standard TemplateView does not offer this!
context['ROOT_URL'] = self.request.build_absolute_uri('/')
context['ROBOTS_TXT_DISALLOW_ALL'] = appsettings.ROBOTS_TXT_DIS... | code_fim | hard | {
"lang": "python",
"repo": "sigmacms/django-fluent-pages",
"path": "/fluent_pages/views/seo.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sigmacms/django-fluent-pages path: /fluent_pages/views/seo.py
from django.views.generic import TemplateView
from fluent_pages import appsettings
class RobotsTxtView(TemplateView):
"""
Exposing a ``robots.txt`` template in the Django project.
Add this view to the ``urls.py``:
.... | code_fim | hard | {
"lang": "python",
"repo": "sigmacms/django-fluent-pages",
"path": "/fluent_pages/views/seo.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> from fluent_pages.views import RobotsTxtView
urlpatterns = [
# ...
url(r'^robots.txt$', RobotsTxtView.as_view()),
]
Naturally, this pattern should not be included
inside :func:`~django.conf.urls.i18n.i18n_patterns` as it should appear at the top l... | code_fim | medium | {
"lang": "python",
"repo": "sigmacms/django-fluent-pages",
"path": "/fluent_pages/views/seo.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|>in"][0](message,commu):
await message.delete()
channs = commu[str(message.channel.category_id)][0].remove(message.channel.id)
await message.channel.delete()<|fim_prefix|># repo: Astremy/CommunityBot path: /commandes/remove_channel.py
infos = {"name":"remove_channel","require":["message","command... | code_fim | medium | {
"lang": "python",
"repo": "Astremy/CommunityBot",
"path": "/commandes/remove_channel.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>annel.category_id)][0].remove(message.channel.id)
await message.channel.delete()<|fim_prefix|># repo: Astremy/CommunityBot path: /commandes/remove_channel.py
infos = {"name":"remove_channel","require":["message","commandes","commu"],"show":<|fim_middle|>2,"use":1}
async def command(message,commande... | code_fim | medium | {
"lang": "python",
"repo": "Astremy/CommunityBot",
"path": "/commandes/remove_channel.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Astremy/CommunityBot path: /commandes/remove_channel.py
infos = {"name":"remove_channel","require":["message","commandes","commu"],"show":<|fim_suffix|>annel.category_id)][0].remove(message.channel.id)
await message.channel.delete()<|fim_middle|>2,"use":1}
async def command(message,commande... | code_fim | medium | {
"lang": "python",
"repo": "Astremy/CommunityBot",
"path": "/commandes/remove_channel.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>Healt_calc(*venkat_data) # UNPACKING ARGUMENT<|fim_prefix|># repo: venkatshukla/Python_Tuts path: /Unpacking Args.py
def Healt_calc(age, apples, cig):
<|fim_middle|> health = (100-age) + apples*2 - (cig*2.8)
print(health)
Healt_calc(22,5,7)
venkat_data = [22,5,7]
Healt_calc(venkat_data[0],venka... | code_fim | medium | {
"lang": "python",
"repo": "venkatshukla/Python_Tuts",
"path": "/Unpacking Args.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: venkatshukla/Python_Tuts path: /Unpacking Args.py
def Healt_calc(age, apples, cig):
<|fim_suffix|>Healt_calc(*venkat_data) # UNPACKING ARGUMENT<|fim_middle|> health = (100-age) + apples*2 - (cig*2.8)
print(health)
Healt_calc(22,5,7)
venkat_data = [22,5,7]
Healt_calc(venkat_data[0],venka... | code_fim | medium | {
"lang": "python",
"repo": "venkatshukla/Python_Tuts",
"path": "/Unpacking Args.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
Healt_calc(22,5,7)
venkat_data = [22,5,7]
Healt_calc(venkat_data[0],venkat_data[1],venkat_data[2])
Healt_calc(*venkat_data) # UNPACKING ARGUMENT<|fim_prefix|># repo: venkatshukla/Python_Tuts path: /Unpacking Args.py
def Healt_calc(age, apples, cig):
<|fim_middle|> health = (100-age) + apples*2 - (... | code_fim | medium | {
"lang": "python",
"repo": "venkatshukla/Python_Tuts",
"path": "/Unpacking Args.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>tall_requires=['gym', 'numpy', 'opencv-python'] # And any other dependencies foo needs
)<|fim_prefix|># repo: x2ever/Smart-Elevator-With-RL path: /gym-building/setup.py
from setuptools import setup
setup(name='gy<|fim_middle|>m_building',
version='0.0.1',
ins | code_fim | easy | {
"lang": "python",
"repo": "x2ever/Smart-Elevator-With-RL",
"path": "/gym-building/setup.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: x2ever/Smart-Elevator-With-RL path: /gym-building/setup.py
from setuptools import setup
setup(name='gym_building',
version='0.0.1',
ins<|fim_suffix|>n'] # And any other dependencies foo needs
)<|fim_middle|>tall_requires=['gym', 'numpy', 'opencv-pytho | code_fim | easy | {
"lang": "python",
"repo": "x2ever/Smart-Elevator-With-RL",
"path": "/gym-building/setup.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alheart/python path: /learn/headfirstpython/chapter4/write.py
#import nester
import pickle
man = []
other = []
try:
data = open('sketch.txt')
for each_line in data:
try:
(role, line_spoken) = each_line.split(':', 1)
line_spoken = line_spoken.strip()
... | code_fim | medium | {
"lang": "python",
"repo": "alheart/python",
"path": "/learn/headfirstpython/chapter4/write.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>try:
with open('man_data.txt', 'wb') as manfile:
pickle.dump(man, manfile)
#nester.print_lol(man, outfile=manfile)
with open('other_data.txt', 'wb') as otherfile:
#nester.print_lol(other, outfile=otherfile)
pickle.dump(other, otherfile)
except IOError:
print('wr... | code_fim | medium | {
"lang": "python",
"repo": "alheart/python",
"path": "/learn/headfirstpython/chapter4/write.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
try:
with open('man_data.txt', 'wb') as manfile:
pickle.dump(man, manfile)
#nester.print_lol(man, outfile=manfile)
with open('other_data.txt', 'wb') as otherfile:
#nester.print_lol(other, outfile=otherfile)
pickle.dump(other, otherfile)
except IOError:
print('w... | code_fim | medium | {
"lang": "python",
"repo": "alheart/python",
"path": "/learn/headfirstpython/chapter4/write.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>for clf,label in zip([clf1,clr2,clf3,sclf],
['KNN',
'Random Forest',
'Naive Bayes',
'StackingClassifier']):
scores_acc=model_selection.cross_val_score(clf,X,y,cv=3,scoring='accuracy')
scores_auc=model_selection.... | code_fim | hard | {
"lang": "python",
"repo": "JoKerDii/Bank-financial-products-ordering-model",
"path": "/bank.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JoKerDii/Bank-financial-products-ordering-model path: /bank.py
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 15 09:23:25 2018
@author: dizhen
"""
import pandas as pd
import numpy as np
from sklearn.datasets import load_iris
from sklearn.pipeline import Pipeline
from sklearn.preprocessing impo... | code_fim | hard | {
"lang": "python",
"repo": "JoKerDii/Bank-financial-products-ordering-model",
"path": "/bank.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> cluster_idxs = cluster_learner.predict(embedding)
centers = cluster_learner.cluster_centers_[cluster_idxs]
dis = (embedding - centers)**2
dis = dis.sum(axis=1)
q_idxs = np.array(
[
np.arange(embedding.shape[0])[cluster_idxs == i][dis[cluster_idxs == i].argmin()]
for i in range(n)
]... | code_fim | hard | {
"lang": "python",
"repo": "wenhao-gao/active_mpnn",
"path": "/query_strategies/kmeans_sampling.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> cluster_learner = KMeans(n_clusters=n)
cluster_learner.fit(embedding)
cluster_idxs = cluster_learner.predict(embedding)
centers = cluster_learner.cluster_centers_[cluster_idxs]
dis = (embedding - centers)**2
dis = dis.sum(axis=1)
q_idxs = np.array(
[
np.arange(embedding.shape[0])[c... | code_fim | hard | {
"lang": "python",
"repo": "wenhao-gao/active_mpnn",
"path": "/query_strategies/kmeans_sampling.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wenhao-gao/active_mpnn path: /query_strategies/kmeans_sampling.py
import numpy as np
from .strategy import Strategy
from sklearn.cluster import KMeans
from dataset.data import MoleculeDataset
class KMeansSampling(Strategy):
<|fim_suffix|> embedding = self.get_embedding(MoleculeDataset(self.da... | code_fim | hard | {
"lang": "python",
"repo": "wenhao-gao/active_mpnn",
"path": "/query_strategies/kmeans_sampling.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def empty_results():
output = open(ALL_RESULTS_FILE, 'wb')
pickle.dump([], output)
output.close()<|fim_prefix|># repo: kkkgabriel/Monocular-Depth-Estimation path: /utils/config.py
'''
# not used, no time yo.
This file stores constants and global configuration variables
'''
import pickle
<|fim_middle... | code_fim | hard | {
"lang": "python",
"repo": "kkkgabriel/Monocular-Depth-Estimation",
"path": "/utils/config.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> output = open(ALL_RESULTS_FILE, 'wb')
pickle.dump([], output)
output.close()<|fim_prefix|># repo: kkkgabriel/Monocular-Depth-Estimation path: /utils/config.py
'''
# not used, no time yo.
This file stores constants and global configuration variables
'''
import pickle
<|fim_middle|># constants
MODELS_... | code_fim | hard | {
"lang": "python",
"repo": "kkkgabriel/Monocular-Depth-Estimation",
"path": "/utils/config.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kkkgabriel/Monocular-Depth-Estimation path: /utils/config.py
'''
# not used, no time yo.
This file stores constants and global configuration variables
'''
import pickle
# constants
MODELS_DIR = 'models/'
MAIN_RESULTS_DIR = 'results/'
ALL_RESULTS_FILE = MAIN_RESULTS_DIR + 'all_results.pkl'
<|fi... | code_fim | hard | {
"lang": "python",
"repo": "kkkgabriel/Monocular-Depth-Estimation",
"path": "/utils/config.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SoloTodo/storescraper path: /storescraper/stores/pontofrio.py
import json
import re
import urllib
from bs4 import BeautifulSoup
from decimal import Decimal
from storescraper.product import Product
from storescraper.store import Store
from storescraper.utils import session_with_proxy, check_ean1... | code_fim | hard | {
"lang": "python",
"repo": "SoloTodo/storescraper",
"path": "/storescraper/stores/pontofrio.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> pricing_data = pricing_data['product']
name = urllib.parse.unquote(pricing_data['fullName'])
sku = pricing_data['idSku']
price = Decimal(pricing_data['salePrice'])
if pricing_data['StockAvailability']:
stock = -1
else:
stock = 0
... | code_fim | hard | {
"lang": "python",
"repo": "SoloTodo/storescraper",
"path": "/storescraper/stores/pontofrio.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> y=self.rating.train.y
if self.regression:
# fit model
m = LinearRegression()
m.fit(self.train_veczr.sign(), y.items);
# get predictions
preds = m.predict(self.valid_veczr.sign())
error = mean_squared_error(self.rating.valid.y.items, preds, squared=False)
print("R... | code_fim | hard | {
"lang": "python",
"repo": "akrahdan/SemEval2021",
"path": "/baseline_model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: akrahdan/SemEval2021 path: /baseline_model.py
from fastai.text import *
import sklearn.feature_extraction.text as sklearn_text
import pickle
from sklearn.linear_model import LogisticRegression, LinearRegression
from sklearn.feature_extraction.text import CountVectorizer
from dataclasses import as... | code_fim | hard | {
"lang": "python",
"repo": "akrahdan/SemEval2021",
"path": "/baseline_model.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # get predictions
preds = m.predict(self.valid_veczr.sign())
valid_labels = [label == yes for label in self.rating.valid.y.items]
# check accuracy
accuracy = (preds==valid_labels).mean()
print(f'Accuracy = {accuracy} for Logistic Regression, with binarized trigram counts from... | code_fim | hard | {
"lang": "python",
"repo": "akrahdan/SemEval2021",
"path": "/baseline_model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mikkokotila/learning-deep-learning path: /predict-with-saved-model.py
from keras.models import model_from_json
import numpy
import os
# SECTION 1 - Load the model
# By now all of this should be pretty clear for you.
# Still, check out the relevant Keras manual entry
# https://keras.io/models/a... | code_fim | hard | {
"lang": "python",
"repo": "mikkokotila/learning-deep-learning",
"path": "/predict-with-saved-model.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>loaded_model.compile(loss='binary_crossentropy', optimizer='rmsprop', metrics=['accuracy'])
score = loaded_model.evaluate(X, Y, verbose=0)
print("%s: %.2f%%" % (loaded_model.metrics_names[1], score[1]*100))
# That's it, it is a simple as that!<|fim_prefix|># repo: mikkokotila/learning-deep-learning path... | code_fim | medium | {
"lang": "python",
"repo": "mikkokotila/learning-deep-learning",
"path": "/predict-with-saved-model.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> vf.nvr = self
vf.channel = cha
vf.nvrId = self.nvrId
vf.mgr = self.mgr
vf.previewSession = self.nvrDll.CLIENT_RealPlay(
self.userSession,
cha - 1,
vf.GetHandle()
)
# 添加到窗口列表
vf.AddToWindowList()
# 实时播放... | code_fim | hard | {
"lang": "python",
"repo": "danny2jenny/rec-client-python",
"path": "/video/NvrDH.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danny2jenny/rec-client-python path: /video/NvrDH.py
'''
大华 NVR 接口
'''
from _ctypes import Structure, byref
from ctypes import c_ubyte, c_int, c_char_p, c_bool
from video.NvrBase import NvrBase
from video.RealPlayer import RealPlayerForm, PtzDir
# 登录用的返回结构体
class NET_DEVICEINFO_Ex(Structure):
... | code_fim | hard | {
"lang": "python",
"repo": "danny2jenny/rec-client-python",
"path": "/video/NvrDH.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
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