blob_id stringlengths 40 40 | language stringclasses 1
value | repo_name stringlengths 5 133 | path stringlengths 2 333 | src_encoding stringclasses 30
values | length_bytes int64 18 5.47M | score float64 2.52 5.81 | int_score int64 3 5 | detected_licenses listlengths 0 67 | license_type stringclasses 2
values | text stringlengths 12 5.47M | download_success bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|---|
7f166fc88eb1bdde3f58e6711e1b420d9070c498 | Python | DenisFeoktistov/CasinoProject | /pythonProject/Состовляющие класса Casino/Interface.py | UTF-8 | 1,129 | 2.53125 | 3 | [] | no_license | from RegistrationWindow import RegistrationWindow
from CasinoWindow import CasinoWindow
from LoginWindow import LoginWindow
class Interface:
def __init__(self):
self.login_window = LoginWindow(self)
self.registration_window = RegistrationWindow(self)
self.casino_window = CasinoWindow(self)... | true |
c698ea5dc43e2f61d1636ff3fbb8582ad966f97d | Python | 3207-Rhims/100days-of-code-challenge | /codechef/sum.py | UTF-8 | 227 | 2.8125 | 3 | [] | no_license | t=int(input())
for i in range(t):
if 1<=t<=1000:
line=input().split(" ")
a,b=line
a=int(a)
b=int(b)
sum=a+b
if 0<=a<=10000 and 0<=a<=10000:
print(sum) | true |
8a8ca7923a0ec1a027a9e07e8ae42448ab94c105 | Python | fredford/maze-generator | /src/maze.py | UTF-8 | 3,308 | 3.6875 | 4 | [] | no_license | import random
from src import cell
RED = (255, 0, 0)
BLUE = (0, 0, 255)
WHITE = (255, 255, 255)
class Maze:
"""Object used to represent a maze and the information needed to specify the dimensions, cells contained, start and finish.
"""
def __init__(self, size, scale):
self.directions = {"above":(0... | true |
d9f99e25b778b0bbca89c7c30fa998de65c9c1ac | Python | nswarner/poker | /hand.py | UTF-8 | 1,061 | 3.859375 | 4 | [] | no_license | #!/usr/bin/python3
from card import Card
from logger import Logger
class Hand:
hand = None
def __init__(self, num_cards = 2):
Logger.log("Hand: Creating a new hand with cards: " + str(num_cards))
self.hand = []
for i in range(0, num_cards):
Logger.log("Hand: Calling add_c... | true |
db0fc827e3e427abd38335ad0d1addf75aa5820d | Python | Kr0n0/tensorflow-metal-osx | /mnist.py | UTF-8 | 1,055 | 2.921875 | 3 | [] | no_license | import tensorflow as tf
from tensorflow import keras
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
y_train = y_train[:1000]
y_test = y_test[:1000]
x_train, x_test = x_train / 255.0, x_test / 255.0
x_train = x_train[:1000].reshape(-1, 28*28)
x_test = x_test[:1000].reshape(-... | true |
e0d7373dee703dc6a82273d0494fe8845fdac89f | Python | dejori/this-and-that | /NaiveBayes/bayes.py | UTF-8 | 5,220 | 3.25 | 3 | [] | no_license | import sys, getopt
import re
import pickle
from sets import Set
from os import listdir
from os.path import isfile, join
class Bayes(object):
def __init__(self, th=.9):
self.tokens = {}
self.pos_count = 0
self.neg_count = 0
def _train_token(self, token, pos):
if token in self.t... | true |
5a75b9d0d143945b0ce3c726977797b319ee538a | Python | lspence40/engineering4notebook | /python/LEDblinkPython.py | UTF-8 | 215 | 2.8125 | 3 | [] | no_license | import RPi.GPIO as GPIO
from time import sleep
GPIO.setmode(GPIO.BCM)
pin = 4
GPIO.setup(pin, GPIO.OUT)
sleep(1)
for i in range(5):
GPIO.output(pin, 1)
sleep(.5)
GPIO.output(pin, 0)
sleep(.5)
GPIO.cleanup()
| true |
5ddfc82dfe44aa966b9c0c01b1913a7b1343f525 | Python | unknownboyy/GUVI | /code16.py | UTF-8 | 174 | 3.203125 | 3 | [] | no_license | for _ in range(int(input())):
n = int(input())
x = int((2*n)**0.5)
if x*(x+1)//2==n:
print('Go On Bob',x)
else:
print('Better Luck Next Time') | true |
2630e21c0ae1861b8a642960c8297b0ebe5c1ce0 | Python | domingoesteban/robolearn | /robolearn/torch/models/transitions/linear_regression.py | UTF-8 | 2,470 | 2.515625 | 3 | [
"BSD-3-Clause"
] | permissive | import torch
import torch.nn as nn
from robolearn.torch.core import PyTorchModule
from robolearn.utils.serializable import Serializable
import robolearn.torch.utils.pytorch_util as ptu
from robolearn.models import Transition
from robolearn.torch.utils.ops.gauss_fit_joint_prior import gauss_fit_joint_prior
class TVLGD... | true |
16d97479b965679a0577708e215d05d34ac07311 | Python | donzucchero/homework_week_2 | /hw_week2_exc2.py | UTF-8 | 848 | 4 | 4 | [] | no_license | def get_grades():
while True:
try:
grade = (int(input('Enter grade(2/3/4/5/6): ')))
if grade in [2,3,4,5,6]:
grades.append(grade)
answer = input("Would you like to add another grade?(y/n): ")
if answer == "n":
b... | true |
83c00da578e7bf8cc3d12c623f3f72f304ca4f5b | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_201/2167.py | UTF-8 | 1,014 | 3.546875 | 4 | [] | no_license | def construct(n):
right = 0
left = 0
if (n % 2 == 0):
# even
right, left = (n//2), max(0, (n//2 - 1))
else:
right, left = (n//2), (n//2)
return right, left
def get_stall(n, m):
if (n == m):
return 0, 0
elif (m == 1):
if (n % 2 == 0):
# even
return (n//2), max(0, (n//2 - 1))
else:
# odd
r... | true |
f1b7429c6e376820133ce069e1bd9e04f74caa6e | Python | THUMNLab/AutoGL | /autogl/datasets/utils/conversion/_to_pyg_dataset.py | UTF-8 | 1,435 | 2.59375 | 3 | [
"Apache-2.0"
] | permissive | import typing as _typing
import torch
import torch_geometric
from autogl.data import Dataset, InMemoryDataset
from autogl.data.graph import GeneralStaticGraph
from autogl.data.graph.utils import conversion
def to_pyg_dataset(
dataset: _typing.Union[Dataset, _typing.Iterable[GeneralStaticGraph]]
) -> Dataset[t... | true |
14321c1252e55e3b5f2ca03c6cc86c92da9f8795 | Python | DeepikaSampangi/Addtnl | /minesweeper.py | UTF-8 | 553 | 3.359375 | 3 | [] | no_license | def mine_sweeper(bombs , n_rows , n_cols):
fields = [[0 for i in range (n_cols)] for j in range (n_rows)]
for bomb_loc in bombs:
(b_rows , b_cols) = bomb_loc
fields[b_rows][b_cols] = -1
r_range = range (b_rows - 1 , b_rows + 2)
c_range = range (b_cols - 1 , b_cols + 2)
... | true |
8af62d2a3e958d39ecd1612dd211a6e71dbb5a35 | Python | Krystiano8686/python_studia | /Zad_cw2/zad5.py | UTF-8 | 247 | 3.984375 | 4 | [] | no_license | # ZAD5
a, b, c = input('Podaj 3 liczby: '), input(), input()
a = float(a)
b = float(b)
c = float(c)
if a <= 10 and a >= 0 and a > b and b > c:
print("Wszystkie warunki zostały spełnione")
else:
print("Warunki nie zostały spełnione")
| true |
fcc68c10fe0694f29db5c638069f0a57d40cde9f | Python | Furricane/Camera | /on_motion_script.py | UTF-8 | 790 | 2.5625 | 3 | [] | no_license | #!/usr/bin/python
#!/usr/bin/env python
import os, sys
sys.path.append('/home/pi/PythonUtilities')
import socketcomm
os.chdir('/home/pi/Camera/') # Change working directory
HostAddress = '192.168.1.92'
HostPort = 44444
def notify_host(host_address, host_port, message):
connectedstatus = False
client, connec... | true |
49a1e99006cdf9db11cde3e11626e18a44521700 | Python | omazhary/dm-oscars | /OscarDataset/dataLoader.py | UTF-8 | 1,654 | 3.203125 | 3 | [
"MIT"
] | permissive | import csv
import numpy as np
from sklearn import preprocessing
#
# converts a csv file to 2D array
def csvToArray(filename):
ret = []
with open(filename) as x:
entryreader = csv.reader(x, delimiter=',')
for row in entryreader:
ret.append(row)
return ret
feat_train = csvToArray... | true |
4166f89ca12e70242ed11f1f03ee78fbab1d371d | Python | kantmp/CAmodule | /getTick.py | UTF-8 | 1,716 | 2.796875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
'''
get the option tick
格式为
gettick tick.csv
'''
import tables as tbl
import os
import tsData
import pandas as pd
import sys
import getopt
#
__version__ = '0.1'
baseurl = os.getcwd()
def openHDFfile(hdf_file):
'''
open the hdf5 file
need in the cwd
'''
try:
fileh... | true |
e432d08da4dfa64cedb982b46c48c3b47977e55d | Python | turovod/Otus | /8_Lesson8/oop/example2-mro-newstyle2.py | UTF-8 | 506 | 3.90625 | 4 | [
"MIT"
] | permissive | """
In Python 2, search path is F, A, X, Y, B.
With Python 3, search path should be : F, A, X, Y, B, Y, X and after removing « bad heads » : F, A, B, Y, X.
"""
class X():
def who_am_i(self):
print("I am a X")
class Y():
def who_am_i(self):
print("I am a Y")
class A(Y, X):
def who_am_i... | true |
dea2f65b6d7baedf2cbff2c73646c677df54d338 | Python | C2SM-RCM/emiproc | /tests/test_country_mask.py | UTF-8 | 501 | 2.59375 | 3 | [
"CC-BY-4.0"
] | permissive | import numpy as np
from emiproc.utilities import compute_country_mask
from emiproc.grids import RegularGrid
def test_create_simple_mask():
arr = compute_country_mask(
RegularGrid(
xmin=47.5,
xmax=58.5,
ymin=7.5,
ymax=12.5,
nx=10,
... | true |
c35343c6a2b725a53966247c10dd080809990177 | Python | mvabf/URI_python | /ex_1061.py | UTF-8 | 745 | 3.390625 | 3 | [] | no_license |
diaInicial = int(input()[4:])
horaInicial, minutoInicial, segundoInicial = map(int,input().split(':'))
diaFinal = int(input()[4:])
horaFinal, minutoFinal, segundoFinal = map(int,input().split(':'))
diaTotal = diaFinal - diaInicial
horaTotal = horaFinal - horaInicial
if horaTotal < 0:
horaTotal += 24
diaTot... | true |
e99a9e53abe8f0329a95508d607c840883abb218 | Python | igenic/deep-rl-ofc-poker | /rlofc/ofc_agent.py | UTF-8 | 1,507 | 3.625 | 4 | [] | no_license | import numpy as np
from treys import Card
street_to_row = {
0: 'front',
1: 'mid',
2: 'back'
}
class OFCAgent(object):
"""An OFC decision maker."""
def place_new_card(self, card, board):
"""Return 0, 1, 2 for front, mid, back."""
pass
class OFCRandomAgent(OFCAgent):
"""Place ... | true |
3560f874cdf6bbddde48a3d8d59e7eb3d4ce7dc7 | Python | starrrr1/traveltimeprediction | /traveltimecalc.py | UTF-8 | 2,332 | 2.75 | 3 | [] | no_license | import sys
import pandas as pd
import datetime
if __name__ == '__main__':
weekend = ['03/07/2015','03/14/2015','03/21/2015','03/28/2015','04/04/2015']
df = pd.read_csv(sys.argv[1])
sortdf = df.sort(['V1','section'])
sortdf['date'] = sortdf['V1'].apply(lambda x: x[:10])
xsortdf =... | true |
1e4be08abc6d7687af8e2009642b2108a46f524c | Python | chrishefele/kaggle-sample-code | /SemiSupervised/analysis/src/col_vals.py | UTF-8 | 2,329 | 2.828125 | 3 | [] | no_license | import sys
INVERT_FLAG = False
INVERT_THRESHOLD = 500000 # if more than this, use nonzero(1+(data+zeros)) vs the data
TRAIN = "/home/chefele/SemiSupervised/download/competition_data/unlabeled_data.svmlight.dat"
TRAIN_LINES = 1000000
line_counter = 0
col_vals = {}
print "Reading:", TRAIN
print "Reading line:",
for ... | true |
1e96763245ab65c1568641a3395421d5d778a65f | Python | olber027/AdventOfCode2020 | /Day_16/Part2.py | UTF-8 | 3,018 | 3.734375 | 4 | [] | no_license | '''
Now that you've identified which tickets contain invalid values, discard those tickets entirely. Use the remaining valid tickets to determine which field is which.
Using the valid ranges for each field, determine what order the fields appear on the tickets. The order is consistent between all tickets: if seat is t... | true |
4a17aa26e827154a3f137dfc3c08159a6723825d | Python | Da1anna/Data-Structed-and-Algorithm_python | /基础知识/动态规划/贪心算法/20.3.17.py | UTF-8 | 5,094 | 4.1875 | 4 | [] | no_license | '''
有一堆石头，每块石头的重量都是正整数。
每一回合，从中选出两块最重的石头，然后将它们一起粉碎。假设石头的重量分别为 x 和 y，且 x <= y。那么粉碎的可能结果如下：
如果 x == y，那么两块石头都会被完全粉碎；
如果 x != y，那么重量为 x 的石头将会完全粉碎，而重量为 y 的石头新重量为 y-x。
最后，最多只会剩下一块石头。返回此石头的重量。如果没有石头剩下，就返回 0。
提示：
1 <= stones.length <= 30
1 <= stones[i] <= 1000
来源：力扣（LeetCode）
链接：https://leetcode-cn.com/problems/last-s... | true |
7211772918339234af209e4cb3785d55b2b57ee5 | Python | NaveenKudari/Assignment_6 | /Assignment_6.2.py | UTF-8 | 228 | 3.265625 | 3 | [] | no_license |
# coding: utf-8
# In[38]:
list1=[3,21,98,203,17,9]
mean = sum(list1)/sum([1 for i in list1])
value=0
for i in list1:
value+=(i-mean)**2
variance=value/(sum([1 for i in list1])-1)
print("variance is:"+" "+str(variance))
| true |
5ca048990621fc4c4d3872a071665349439c583d | Python | yaohongyi/identify_ui_test | /operate/operate_tool.py | UTF-8 | 12,637 | 2.640625 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding:utf-8 -*-
# 都君丨大魔王
import time
from selenium.webdriver import ActionChains
from public import api
from page_object.tool_page import ToolPage
from page_object.case_page import CasePage
class OperateTool:
def __init__(self, browser):
self.browser = browser
self.too... | true |
3a9f8e1c8f83185ce82b022d74d09428e6078fc3 | Python | liliangqi/person_search_triplet | /__init__.py | UTF-8 | 579 | 2.671875 | 3 | [
"MIT"
] | permissive | # -----------------------------------------------------
# Initial Settings for Taining and Testing SIPN
#
# Author: Liangqi Li
# Creating Date: Apr 14, 2018
# Latest rectified: Apr 14, 2018
# -----------------------------------------------------
import time
import functools
def clock_non_return(func):
@functools.... | true |
35cf46b77bf570c28ae3edcdc42615112bcec1d5 | Python | atharrison/python-adventofcode2020 | /day15/day15.py | UTF-8 | 944 | 3.53125 | 4 | [
"MIT"
] | permissive | import copy
class Day15:
# started 0:12 after
def __init__(self, data):
self.data = data
self.iterations = 2021
def solve_part1(self):
turn_lookup = {}
for idx, val in enumerate(self.data):
turn_lookup[val] = idx + 1
print(turn_lookup)
# first... | true |
c483b4457c9cc8807e03406750b987d727c517aa | Python | saiprasadvk/pythonprogram | /workout/perimeter of a circle.py | UTF-8 | 591 | 4.4375 | 4 | [] | no_license | Write a Python class named Circle constructed by a radius and two methods which will compute the area and the perimeter of a circle
Ans::
class circle:
def __init__(self,radius):
self.radius = radius
def perimeter(self):
a = 3.14*(self.radius)**2
print("Area of a circle",a)
... | true |
389b4cc1a23e9c787a31e515472804751350aa16 | Python | nathanielanozie/anozie_tools | /py/na_addToLayer.py | UTF-8 | 2,688 | 2.953125 | 3 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | ##@file na_addToLayer.py Tools to find Maya scene transforms and put them into a display Layer.
#@note ex put all the transforms in group1 into layer1.
#@code import na_addToLayer as na @endcode
#@code na.addToLayer( 'group1', ['transform'], 'layer1' ) @endcode
#
#@author Nathaniel Anozie
import maya.cmds as cmds
imp... | true |
d3b37b9c6fe2a92e7936560463b4035cd335f410 | Python | ideaqiwang/leetcode | /Array/39_CombinationSum.py | UTF-8 | 1,516 | 3.78125 | 4 | [] | no_license | '''
39. Combination Sum
Given an array of distinct integers candidates and a target integer target, return a list of all unique combinations of candidates where the chosen numbers sum to target. You may return the combinations in any order.
The same number may be chosen from candidates an unlimited number of times. Tw... | true |
5d26ac68e18555fecc365914261f24fc61a9567e | Python | imaginechen/EzaPython | /Email/SendEmail.py | UTF-8 | 838 | 2.890625 | 3 | [] | no_license | import smtplib
from email.mime.text import MIMEText
# third-part smtp service
mail_host = "applesmtp.126.com" # SMTP server
mail_user = "eric_python_auto@126.com" # user name
mail_pass = "qijzxcqj00838488" # passcode
sender = 'eric_python_auto@126.com' # sender
receivers = ['imaginechen@126.com', 'eric_python... | true |
252d7096d8b2d216e97b575de5f52c522c57f50d | Python | dung-ngviet/LeetD | /LeetCode/DP/55/55.py | UTF-8 | 1,722 | 3.625 | 4 | [] | no_license | from typing import List
# class Solution:
# def canJump(self, nums: List[int]) -> bool:
# max = 0
# for i in range(0, len(nums)):
# if i > max: return False
# num = nums[i]
# if i + num > max: max = i + num
# if max > len(nums): return True
# r... | true |
b6903c86f398377444a9bb1812e662a7dac24f96 | Python | linxumelon/examplifier | /netStat.py | UTF-8 | 3,464 | 2.765625 | 3 | [] | no_license | import psutil
import time
import socket
def get_global_stat():
stats = psutil.net_io_counters(pernic=False, nowrap=True)
bytes_sent = stats.bytes_sent
bytes_recv = stats.bytes_recv
packets_sent = stats.packets_sent
packets_recv = stats.packets_recv
errin = stats.errin # total number of errors... | true |
b3d743e915b7e2909f8260a7fa08fc556f8d14a5 | Python | poke53280/ml_mercari | /Train_Index_Group.py | UTF-8 | 1,388 | 2.984375 | 3 | [] | no_license |
import pandas as pd
import numpy as np
id = [0,0,1,1,3, 0]
d = [3,3,4,5,6, 3]
s = [4,4,4,4,4, 4]
ix = [7,2, 0, 3, 1, 4]
t = ['A', 'B', 'C', 'D', 'E', 'C']
df = pd.DataFrame({'id': id, 'd' : d, 's': s, 'idx': ix, 't':t})
df
# Group by id, d, s. Check t ordering.
df_grouped = df.groupby(['id', 'd', 's'])
for gr... | true |
921d77f26ae0b97b936a7fbba071677d281dfcae | Python | Felienne/spea | /Python files/39 Week 7 - About Sets/06 test_set_have_arithmetic_operators/78855_01_code.step.py | UTF-8 | 500 | 3.5 | 4 | [] | no_license | #
class AboutSets(unittest.TestCase):
def test_set_have_arithmetic_operators(self):
beatles = {'John', 'Ringo', 'George', 'Paul'}
dead_musicians = {'John', 'George', 'Elvis', 'Tupac', 'Bowie'}
great_musicians = beatles | dead_musicians
self.assertEqual(__, great_musicians)
... | true |
2dfdab9376b8740407e15a91d1987f8adaa5ede9 | Python | adamr2/dhutil | /dhutil/mongo_utils.py | UTF-8 | 1,077 | 2.515625 | 3 | [
"MIT"
] | permissive | """Python based utilities for the registration system."""
import os
import json
from urllib.parse import quote_plus
from functools import lru_cache
import pymongo
CRED_DIR_PATH = os.path.expanduser('~/.datahack/')
CRED_FNAME = 'mongodb_credentials.json'
def _get_credentials():
fpath = os.path.join(CRED_DIR_PA... | true |
4d1426383b3bb6382e8245a214c533032ea84e64 | Python | Kaynelua/SUSH-SpectralSensor | /SpectralSensor.py | UTF-8 | 2,404 | 2.765625 | 3 | [] | no_license | import smbus
from I2C import write,read
import time
import math
import numpy as np
import bitstring as bs
class SpectralSensor:
def __init__(self):
self.bus = smbus.SMBus(1)
self.gain(2)
# Set sensor gain
def gain(self,level):
if(level >=0 and level <=3):
reg = read(self.bus,0x07)
reg = reg & 0xCF
... | true |
b076a489b8bda48899060faa8a055a05bea1da6a | Python | pthorn/eor-filestore | /eor_filestore/images/image_ops.py | UTF-8 | 3,162 | 2.765625 | 3 | [] | no_license | # coding: utf-8
import os
import errno
import math
from io import BytesIO
from PIL import Image
from ..exceptions import FileException, NotAnImageException
import logging
log = logging.getLogger(__name__)
def get_image_format(file_obj):
ext = os.path.splitext(file_obj.filename)[1]
if ext.lower() in('.gif... | true |
d28617d064b72c5690830654683948626338d579 | Python | anastasia1002/my-labs | /lab8/lab8.1(2).py | UTF-8 | 288 | 3.140625 | 3 | [] | no_license | x=float(input("x="))
y=float(input("y="))
z=float(input("z="))
def get_max(x,z):
if x>z:
return x
else:
return y
sum=x+y
dob=x*y
def get_max(sum,dob):
if sum>dob:
return sum
else:
return dob
u=max(x,z)+max(x+y,x*y)/max(x+y,x*y)**2
print(u)
| true |
a3c1d031f338227dd66c79bd2fc8c694275a139a | Python | georgetown-cset/ai-definitions-for-policymaking | /tests/test_query.py | UTF-8 | 2,386 | 2.53125 | 3 | [] | no_license | import pytest
from google.api_core.exceptions import NotFound
from google.cloud import bigquery
from bq import query, create_client
from settings import DATASET, PROJECT_ID
TOY_QUERY = """select * from unnest(array<struct<x int64, y string>>[(1, 'foo'), (3, 'bar')])"""
ALT_TOY_QUERY = """select * from unnest(array<st... | true |
0e6bc8babd9029fa1737979a87c7e8fdf99fa068 | Python | covid-maps/covid-maps | /scripts/database_helper.py | UTF-8 | 292 | 2.828125 | 3 | [] | no_license | from sqlalchemy import create_engine
def load_engine(db_url):
print('Connecting to the PostgreSQL database...')
return create_engine(db_url, echo=False)
def close_connection(session):
if session is not None:
session.close()
print('Database connection closed.')
| true |
2cb83902d515adff0d8599e261579aa60d507e13 | Python | ahmedhussiien/Disaster-Response-NLP-Pipeline | /data/process_data.py | UTF-8 | 3,693 | 3.0625 | 3 | [] | no_license | # load, clean and save the datasets
import pandas as pd
from sqlalchemy import create_engine
import argparse
CATEGORIES_DEFAULT_FILENAME = './data/categories.csv'
MESSAGES_DEFAULT_FILENAME = './data/messages.csv'
DATABASE_DEFAULT_FILENAME = './data/labeled_messages_db.sqlite3'
TABLE_NAME = 'labeled_messages'
def lo... | true |
432eda01889a1c14e18a28e61fecb57a1b84dbd9 | Python | sedasugur/homeworks | /Learning from Data/HW1/lfd_1.py | UTF-8 | 4,716 | 2.75 | 3 | [] | no_license | # -*- coding: utf-8 -*-
#Seda SUGUR 150160130
import random
iter_num=1000
learning_rate=0.01
m=[]
sum_x=0
sum_y=0
m.append([])
m.append([])
with open('./regression_data.txt','r') as file:
file.readline()
a=0
lines=file.readlines()
for line in lines:
for word in line.split()... | true |
c3647b2d8d7b5716d148060078d9f7ee5481c324 | Python | ArtskydJ/project-euler | /020_FactorialDigitSum.py | UTF-8 | 188 | 2.875 | 3 | [] | no_license | from math import *
import string
#from string import *
n=factorial(100)
s=format(n)
sTemp="hi"
x=0
for i in range(len(s)):
sTemp=str.index(s,i)
x+=int(sTemp)
print(x)
| true |
5ede18c830281d936688bc7f3ff8f8e721b92607 | Python | torenunez/ud120-projects | /datasets_questions/explore_enron_data.py | UTF-8 | 2,080 | 2.9375 | 3 | [] | no_license | #!/usr/bin/python
"""
Starter code for exploring the Enron dataset (emails + finances);
loads up the dataset (pickled dict of dicts).
The dataset has the form:
enron_data["LASTNAME FIRSTNAME MIDDLEINITIAL"] = { features_dict }
{features_dict} is a dictionary of features associated with that pers... | true |
abbf03ffe895b458704d292d01142d6e09504d2c | Python | Ackermannn/MyLeetcode | /src/edu/neu/xsz/leetcode/lcof/lcof37/Main.py | UTF-8 | 2,089 | 3.875 | 4 | [] | no_license | #! usr/bin/env python3
from queue import Queue
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string.
:type roo... | true |
002af52aaabfbf3869840413fae4dcb4d9dc39fd | Python | LamThanhNguyen/HackerEarth-Solutions | /Fitting-Circles.py | UTF-8 | 142 | 3.46875 | 3 | [] | no_license | t = int(input())
for i in range(t):
a,b = map(int,input().split())
if(a >= b):
print(a//b)
elif(a<b):
print(b//a) | true |
f83143318388cad3273a0eb9cf962565c96da736 | Python | thomasgauvin/LeetcodePractice | /leetcode-reverse-integer.py | UTF-8 | 446 | 2.859375 | 3 | [] | no_license | def reverse(x: int) -> int:
negative = False
if x < 0:
negative = True
x = 0 - x
x = str(x)
result = ""
for i in x:
result = i+result
result = int(result)
if negative:
result = -result
if result > 2**31-2 or result < -2**31:
result = 0
print(r... | true |
c0eba7eb46ded6dc70201840d15bfd63b86e06b4 | Python | onaio/tasking | /tests/models/test_locations.py | UTF-8 | 1,092 | 3.0625 | 3 | [
"Apache-2.0"
] | permissive | """
Test for Location model
"""
from django.test import TestCase
from model_mommy import mommy
class TestLocations(TestCase):
"""
Test class for Location models
"""
def test_location_model_str(self):
"""
Test the str method on Location model with Country Defined
"""
n... | true |
74ba6bab32b06a88d5c6f938b47627a808154a96 | Python | Chandan-CV/school-lab-programs | /Program2.py | UTF-8 | 542 | 4.59375 | 5 | [] | no_license | #Program 2
#Write a program to accept 2 numbers and interchange the values without using a temporary variable
#Name : Adeesh Devanand
#Date of Execution: July 17, 2020
#Class 11
a = int(input("Enter first number"))
b = int(input("Enter second number"))
a = a + b
b = a - b
a = a - b
print("Interchanged value of the fir... | true |
8169cca045bb096d8d290bae52a99ed0f07b93e0 | Python | posuna19/pythonBasicCourse | /course2/week5/W5_01_arrange_name_test.py | UTF-8 | 881 | 3.859375 | 4 | [] | no_license | import unittest
from W5_01_arrange_name import rearrange_name
class TestRearrange(unittest.TestCase):
def test_basic(self):
#Arrange
username = "Lovecale, Ada"
expectedName = "Ada Lovecale"
#Act
resultName = rearrange_name(username)
#Assert
self.assertEqual(... | true |
9fd8e94a89212556fce1cb300a2627e72d611c5f | Python | dfarache/hackerrank | /loveLetterMistery/loveLetter.py | UTF-8 | 460 | 3.71875 | 4 | [] | no_license | def apply_changes(string):
number_of_changes = 0
length = len(string)
low = 0
high = length-1
for index in range(int(length/2)):
number_of_changes += abs(ord(string[low]) - ord(string[high]))
high -= 1
low += 1
print(number_of_changes)
def calculate_answers():
for i... | true |
ef0dfd16468612e3f77bd995b10213dc22e43d3f | Python | anuragvij264/covid-social-distancing-scoring | /api/api_utils.py | UTF-8 | 1,086 | 2.53125 | 3 | [] | no_license | from torchvision import transforms
from PIL import Image
import numpy as np
import torch
from model import CSRNet
transform = transforms.Compose([
transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225]),
])
def gen_img_cou... | true |
4caf73f8a532f644161ac8ed84aa0f7bef99093a | Python | fanonwue/ScannerTool | /SmtpConfig.py | UTF-8 | 738 | 2.625 | 3 | [
"MIT"
] | permissive | class SmtpConfig:
def __init__(self, host: str, port: int, username: str, password: str, starttls: bool, mail_from: str):
self.host = host
self.port = port
self.username = username
self.password = password
self.starttls = starttls
if not mail_from:
mail_f... | true |
83bd2e6837094aa9cb7eeeb6261058ea5c0c7dc3 | Python | YaojieLu/LAI_optimization | /MDP_class.py | UTF-8 | 4,541 | 3.015625 | 3 | [] | no_license |
"""
We define an Markov Decision Process.
We represent a policy as a dictionary of {state: action} pairs.
"""
import numpy as np
def Ef(dL, gs, L, slope, dt):
""" Given leaf area and stomatal conductance, return whole-plant transpiration """
return slope*(L+dL)*gs*dt
def gsmax_sf(dL, L, s, slope, dt):
"... | true |
b1808f3ebe9420e737934a10f91b39d09a152a5a | Python | LuizaM21/Learn_python | /Python_server_testing/Genios_threads.py | UTF-8 | 1,306 | 2.828125 | 3 | [] | no_license | from timeit import default_timer as timer
import bs4
import urllib.request
import ConfigData as config_data
from multiprocessing import Process
from Python_files_manipulation.CSVManipulation import CSVManipulation as csv_manipulation
conf_data = config_data.ConfigData.get_instance()
cube_types_file = conf_data.get_va... | true |
b842b98dbbaabbd5a0f1a66ffe0246e88d5e1255 | Python | Charlie-Ren/ML5525 | /hw1-logistic.py | UTF-8 | 3,524 | 2.796875 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
# In[39]:
import numpy as np, pandas as pd
from matplotlib import pyplot as pl
feat=pd.read_csv("IRISFeat.csv",header=None)
label=pd.read_csv("IRISlabel.csv",header=None)
idx=np.random.permutation(feat.index)# shuffle
X_shuffle=feat.reindex(idx).to_numpy()
y_shuffle=label.reinde... | true |
3503bb1b4bf94a92d8df3bae82e7f3ad34eed40a | Python | 0xfirefist/cryptopals | /l1-basics/chal4.py | UTF-8 | 718 | 3.484375 | 3 | [] | no_license | # Detect single-character XOR
from pprint import pprint
from chal3 import decrypt
# filter list based on printable character
def filter(decryptedList):
for decryptedString in decryptedList:
for c in decryptedString:
if c>126 :
return True
return False
# this will return a ... | true |
da07b99cb2bf9fd29fbd1ca213723ed82149c405 | Python | m-niemiec/space-impact | /ship.py | UTF-8 | 2,189 | 3.546875 | 4 | [] | no_license | import pygame
from settings import Settings
class Ship:
"""A class to manage the ship."""
def __init__(self, si_game):
"""Initialize the ship and set its starting positon."""
self.screen = si_game.screen
self.screen_rect = si_game.screen.get_rect()
self.settings = S... | true |
456de6a70ade0e55c29d1c631b1dd33447409582 | Python | dapr/python-sdk | /dapr/actor/runtime/context.py | UTF-8 | 4,721 | 2.546875 | 3 | [
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | permissive | # -*- coding: utf-8 -*-
"""
Copyright 2023 The Dapr Authors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | true |
269996c00984e84d54e9f0dd8f40e42de2e75cc2 | Python | tehzeebb1/Project104 | /read.py | UTF-8 | 136 | 2.6875 | 3 | [] | no_license | import csv
with open('height-weight.csv',newline='') as f:
reader=csv.reader(f)
file_data=list(reader)
print(file_data) | true |
869b66d8ac7825c08fa0c22ecf20cf0753744dab | Python | wills201/Challenge-Probs | /mergeindex.py | UTF-8 | 535 | 3.28125 | 3 | [] | no_license | l1 = [1,7,3,4,9,3,8,6,8,9]
l2 = [0,3,8,6,8,4,7,6,8,9]
def mergeindex(l1,l2):
idx = 0
while idx < len(l1):
idx += 1
if l1[idx:] == l2[idx:]:
return idx
def mergeindex2(l1,l2):
idx = 0
while idx < len(l1):
idx += 1
if l1[idx] == l2[idx]:
if l1[-1] ... | true |
79ea7ac1fa5080ff2626a47bdbcad600254570c3 | Python | TemistoclesZwang/HackerRank_e_URI | /URI judgeOnline/1771.py | UTF-8 | 3,119 | 3.40625 | 3 | [] | no_license | class Numero:
CLASSEB = list (range(1,16))
CLASSEI = list (range(16,31))
CLASSEN = list (range(31,46))
CLASSEG = list (range(46,61))
CLASSEO = list (range(61,76))
def __init__(self, numero, classe):
self.numero = numero
self.classe = classe
def vali... | true |
27dabaf21b0d96fb3ed72f62a63167969d8ce239 | Python | john-hewitt/cs229-head-tracking | /util.py | UTF-8 | 13,590 | 2.828125 | 3 | [] | no_license | import csv
import json
import os
import numpy as np
import sklearn as sk
import re
import cnn
# globals
mos = [0, 2, 6, 12]
exps = ['R', 'N1', 'N2', 'P1', 'P2']
# file naming conventions
id_reg = '[a-z]{2}[0-9]{5}'
mo_reg = '(((2)|(6)|(12))mo)?'
exp_reg = '((n1)|(n2)|(r)|(p1)|(p2))'
tfname_reg = r'tracking_{}{}{}\.t... | true |
7a88241a3037fbdf8e159972c08c6162dda7e3ca | Python | stefanct/avr-lib | /scripts/timers.py | UTF-8 | 5,130 | 2.546875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os, sys, math, argparse, time
from cdecimal import Decimal
from prettytable import PrettyTable
from common import *
def main(*args):
global verbose, long_width, timer_width, param_width, timer
# docs: http://docs.python.org/dev/library/argparse.html#argparse.Argu... | true |
1f39440ee996093565fb96452af0b457958c451b | Python | jasonyu0100/General-Programs | /2018 Programs/Dynamic Programming/WoodCutter/test.py | UTF-8 | 859 | 2.828125 | 3 | [] | no_license | with open('input.txt') as f:
length = float(f.readline())
positions = list(map(float,f.readline().strip().split()))
cache = {}
def woodCutter(positions, cost, start, end, sequence):
if (start,end) in cache:
return cache[(start,end)]
allCuts = {}
cutCost = (end - start)
for cut in positions:
if start < cut a... | true |
21846fd3aeac2362aa4e46ea2dda5052997aef38 | Python | bagherhussaini/matrix-multiplication-algorithms-runtime-comparison-python | /src/main.py | UTF-8 | 5,310 | 3.171875 | 3 | [] | no_license | from time import time
import numpy as np
import pandas as pd
import xlsxwriter
def main():
n = [2 ** i for i in range(2, 10)]
log = pd.DataFrame(index=[],
columns=['N', 'Normal_Multiplication_Time', 'Divide_and_Conquer_Time', 'Strassen_Time'])
normal_multiplication_durat... | true |
ba48a58445f113708babc1f9247d9b8d50b38921 | Python | Vincent105/python | /04_The_Path_of_Python/05_if/ch5_01_if.py | UTF-8 | 85 | 3.953125 | 4 | [] | no_license | age = input('請輸入年齡：')
if (int(age) < 18):
print('You are too young.') | true |
97d62992639a42ee5dbd7effd7c610e406635a04 | Python | glasnt/emojificate | /tests/test_graphemes.py | UTF-8 | 530 | 2.828125 | 3 | [
"BSD-3-Clause"
] | permissive | import pytest
from emojificate.filter import emojificate
def valid(emoji, title, fuzzy=False):
parsed = emojificate(emoji)
assert emoji in parsed
assert 'alt="{}'.format(emoji) in parsed
assert title in parsed
if not fuzzy:
assert 'aria-label="Emoji: {}'.format(title) in parsed
def tes... | true |
916768ecaf5ee6442a9c206c7c5557f2817bf2a7 | Python | auretsky1/BasicPuzzleGame | /PuzzleGraphics.py | UTF-8 | 7,969 | 3.546875 | 4 | [] | no_license | """ This class will be responsible for drawing the cubes to the game screen and updating the highlighting in accordance
with which ones are on and off as well as where the user's mouse is located. These changes can be called as functions
by an outside module or class with the relevant data needed to make a chan... | true |
ff5c4826288f3f2ad76efbde8ba7a3aacbba34f9 | Python | Kamilos1337/pp1 | /03-FileHandling/18.py | UTF-8 | 181 | 3.53125 | 4 | [] | no_license | tablica = []
with open("03-FileHandling/numbers.txt", 'r') as tekst:
for line in tekst:
tablica.append(int(line))
tablica.sort()
for n in tablica:
print(n, end=' ')
| true |
df1f8bfde2f60756578ee51d21c69cd47e07e9b7 | Python | dolphingarlic/seniorrobotics2018 | /test.py | UTF-8 | 831 | 2.625 | 3 | [] | no_license | from src.robot import Robot
from time import sleep
ROBOT = Robot()
print("Started")
ROBOT.follow_until_next_node()
sleep(10)
ROBOT.stop()
print("Stopped")
'''
for i in range(40):
print("L:"+str(ROBOT.left_colour_sensor.reflected_light_intensity))
print("R:"+str(ROBOT.right_colour_sensor.reflected_light_intens... | true |
a2e14e94527a98bfa95424959cfbd5111e4ad6c5 | Python | pirobtumen/pymediator | /test/test_mediator.py | UTF-8 | 1,598 | 2.90625 | 3 | [
"BSD-3-Clause"
] | permissive | from pymediator import Event, EventHandler, Mediator
def test_base_event():
assert Event.EVENT_NAME is ''
def test_base_event_handler():
handler = EventHandler()
res = handler.handle(Event())
assert res is None
def test_mediator_register_event():
test_event_name = 'test_event'
test_mediato... | true |
1d774ffbb52a1629ea6a0d97d74b2672973e5865 | Python | iCodeIN/competitive-programming-5 | /leetcode/Two-Pointers/permutation-in-string.py | UTF-8 | 1,134 | 3.046875 | 3 | [] | no_license | from itertools import permutations
class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
if len(s1) > len(s2):
print('here')
return False
di = {}
for i in s1:
di[i] = di.get(i, 0) + 1
ls1 = len(s1)
di_sliding = {}
for ... | true |
dd15cc73c67fcc5a97e2ee77a7339d6f866dffa1 | Python | CatalystOfNostalgia/hoot | /server/hoot/emotion_processing/compound_emotions.py | UTF-8 | 427 | 2.53125 | 3 | [
"MIT"
] | permissive | from enum import Enum
from enum import unique
@unique
class CompoundEmotion(Enum):
"""
Represents all possible compound emotions.
"""
optimism = 1
frustration = 2
aggressiveness = 3
anxiety = 4
frivolity = 5
disapproval = 6
rejection = 7
awe = 8
love = 9
envy = 10... | true |
882973f64b9e2f292aaa052a78d88e4e744a4f34 | Python | alan-yjzhang/AIProjectExamples1 | /HW2/part1-convnet/modules/max_pool.py | UTF-8 | 3,554 | 2.796875 | 3 | [] | no_license | import numpy as np
class MaxPooling:
'''
Max Pooling of input
'''
def __init__(self, kernel_size, stride):
self.kernel_size = kernel_size
self.stride = stride
self.cache = None
self.dx = None
self.mask = None
def forward(self, x):
'''
Forward... | true |
024d3e1d7a83f8a2f7e10ad7e349e892e100b646 | Python | vdrhtc/Two-qubit-AT-paper | /Pictures/Plotting/StationaryPlot.py | UTF-8 | 7,639 | 2.59375 | 3 | [] | no_license | import pickle
from numpy import *
import matplotlib
from matplotlib import ticker, colorbar as clb, patches
matplotlib.use('Qt5Agg')
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
class StationaryPlot:
def __init__(self):
with open("stationary.p... | true |
8fe8f2b0f369781c4ce0b68602c09eb5f39eb147 | Python | abhijit26110709/python | /decsitree_iris.py | UTF-8 | 1,564 | 3.546875 | 4 | [
"MIT"
] | permissive | #!/usr/bin/env python
# coding: utf-8
# In[ ]:
from sklearn.datasets import load_iris
import matplotlib.pyplot as plt
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score
# In[3]:
# now loading IRIS data only
iris=load_iris()
# In[4]:
dir(iris) #exploring variable
# In... | true |
3ac7a45f1c93cbd04c8aa60fa845a050a822f114 | Python | NilsJPWerner/autoDocstring | /src/test/integration/python_test_files/file_2_output.py | UTF-8 | 524 | 2.96875 | 3 | [
"MIT"
] | permissive | from typing import Union, List, Generator, Tuple, Dict
def function(
arg1: int,
arg2: Union[List[str], Dict[str, int], Thing],
kwarg1: int = 1
) -> Generator[Tuple[str, str]]:
"""_summary_
:param arg1: _description_
:type arg1: int
:param arg2: _description_
:type arg2: Union[List[str... | true |
bc712597c75c5f664f6a5c323f5aa183087917dd | Python | uniqxh/tensorflow | /pdes.py | UTF-8 | 1,714 | 2.578125 | 3 | [] | no_license | #!/usr/bin/python
import tensorflow as tf
import numpy as np
from PIL import Image
from cStringIO import StringIO
import images2gif
#from IPython.display import clear_output, Image, display
images = []
def DisplayArray(a, fmt='jpeg', rng=[0,1]):
a = (a-rng[0])/float(rng[1] - rng[0])*255
a = np.uint8(np.clip(a, ... | true |
68328f531f700bbf47394c47ef61c901de83237b | Python | achalddave/maskrcnn-benchmark | /maskrcnn_benchmark/utils/parallel/pool_context.py | UTF-8 | 1,860 | 3.015625 | 3 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | import multiprocessing as mp
from collections.abc import Iterable
_PoolWithContext_context = None
def _PoolWithContext_init(initializer, init_args):
global _PoolWithContext_context
_PoolWithContext_context = {}
if init_args is None:
initializer(context=_PoolWithContext_context)
else:
... | true |
aed2c42eb01432869b16ea8df0495672658a1b46 | Python | linhuaxin93/LearnPython | /matplotilb/matplotlib_05.py | UTF-8 | 557 | 3.484375 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.family'] = 'SimHei'
plt.rcParams['axes.unicode_minus'] = False
#随机x,y各十个散点图
plt.subplot(2,2,1)
x = np.random.rand(10)
y = np.random.rand(10)
plt.scatter(x, y)
#柱形图
plt.subplot(2,2,2)
x = np.arange(1, 6)
y = np.array([13, 15, 1... | true |
1af27c27ffeee246f5ec3b69728e96329eeb31f6 | Python | gilReyes/SaphireSQL | /Programming Languages/syntaxAnalyzerworking.py | UTF-8 | 954 | 2.546875 | 3 | [] | no_license | import ply.yacc as yacc
#Getting the token
from lexicalAnalyzer import tokens
var = [[]]
resultQueries = []
tracker = 0
def p_expression_table(p):
'expression : ID ASSIGNMENT LB ID RB LP IDS RP EOL'
var[tracker].insert( 0, p[4])
#print('entering table')
def p_expression_ids(p):
'''IDS : IDS SEPARATO... | true |
93cab0e0b143889fefbf1875811a0afc84383416 | Python | khawajaosama/Algebra_Python | /algebra_4.py | UTF-8 | 2,376 | 3.1875 | 3 | [] | no_license | #Dot Product
from collections import defaultdict
def dot(v,w):
return sum([v_i*w_i
for v_i,w_i in zip(v,w)])
print (dot([1,2,3],[4,5,6]))
#Vector Product
def vector_product(v,w):
adder = defaultdict(int)
for n_1,v_i in enumerate(v):
for n_2,w_i in enumerate(w):
if (n_1!=n... | true |
9f8ef20552481f3811825e97136d7f15fcd30567 | Python | dawnonme/Eureka | /main/leetcode/466.py | UTF-8 | 1,897 | 3.609375 | 4 | [] | no_license | class Solution:
def getMaxRepetitions(self, s1: str, n1: int, s2: str, n2: int) -> int:
# hashtable to store the patterns
patterns = {}
# pointers on s1 and s2
p1, p2 = 0, 0
# number of occurance of s1 and s2 so far
c1, c2 = 1, 0
# execute the loop when num... | true |
752a66e25c86d705c8267dff31778a729bdea21f | Python | iotrusina/M-Eco-WP3-package | /xsafar13/locations/filters/filter_allc_forload | UTF-8 | 563 | 2.640625 | 3 | [] | no_license | #!/usr/bin/python
f1 = open("allCountries","r")
while True:
line = f1.readline()
if line == '':
f1.close()
break
sp = line.split(" ")
if (sp[6] == "P"):
print sp[2] + "\t" + sp[4] + "\t" + sp[5] + "\t" + sp[0] + "\t" + sp[7] + "\t" + sp[8] + "\t" + sp[14]
if (sp[6] == "L") and (sp[7] == "RGN"... | true |
d2466f2cd469e19567cafcc62b34b5cd32aacd37 | Python | DDR7707/Final-450-with-Python | /Dynamic Programming/453.Longest Alternating Subsequence.py | UTF-8 | 678 | 4.125 | 4 | [] | no_license | def LAS(arr, n):
# "inc" and "dec" initialized as 1
# as single element is still LAS
inc = 1
dec = 1
# Iterate from second element
for i in range(1,n):
if (arr[i] > arr[i-1]):
# "inc" changes iff "dec"
# changes
inc = dec ... | true |
50c12377804a67e387707bb55931766e8aaa591f | Python | SaurabhThube/Competitive-Programming-Templates | /FastExpo.py | UTF-8 | 141 | 3.21875 | 3 | [] | no_license | def FastExpo(x,y,mod):
res=1
while(y>0):
if y&1:
res=(res*x)%mod
x=(x*x)%mod
y/=2
return res
| true |
61ba73b0485e119a918e282f88308ee7704e51ef | Python | tonmoy50/Bangla-Sign-Language-Detection | /Model/d.py | UTF-8 | 721 | 3.96875 | 4 | [] | no_license | import math
# Function to check
# palindrome
def isPalindrome(s):
left = 0
right = len(s) - 1
while (left <= right):
if (s[left] != s[right]):
return False
left = left + 1
right = right - 1
return True
# Function to calculate
# the sum of... | true |
5d96e42ed110d4d14db6d9513d4f7ec19fa08509 | Python | programmer-666/Codes | /Python/Tensorflow/tnf1.py | UTF-8 | 2,295 | 3.09375 | 3 | [
"MIT"
] | permissive | import pandas as pd
import seaborn as sb
import matplotlib.pyplot as plt
import tensorflow as wtf
from tensorflow.keras.models import Sequential # çalışılacak katmanları belirtir
from tensorflow.keras.layers import Dense # modele katmanları eklemek için
from sklearn.model_selection import train_test_split
from sklearn.... | true |
6a5c06800c91495b5fe95c83d72abac65fa3afd9 | Python | Shobhit05/Hackerranksolutions | /Python/mobileno.py | UTF-8 | 161 | 2.96875 | 3 | [] | no_license | N=int(input())
a=[]
for i in range(0,N):
c=raw_input()
c=c[-10:]
a.append(c)
a.sort()
for j in a:
print("+91"+" "+j[:5]+" " +j[-5:])
| true |
19fb562b91c7094da27b52527eeb2a5cc5773677 | Python | jesusalvador2911/AdmonODatos | /2.13/2.13.py | UTF-8 | 242 | 2.53125 | 3 | [] | no_license | import pickle
nombre = "Bartolo"
apellido = "Andropolis"
edad = 20
soltero = False
salario =8523.20
registro= [nombre, apellido,edad,soltero,salario]
archivo = open("ArchivoX.txt","wb")
pickle.dump(registro,archivo)
archivo.colse()
| true |
51de96aff7508305f260cf886de56c2f5d33a9c0 | Python | RevansChen/online-judge | /Codewars/8kyu/5-without-numbers/Python/test.py | UTF-8 | 118 | 2.5625 | 3 | [
"MIT"
] | permissive | # Python - 3.6.0
test.describe('Basic test')
test.it('Should return 5')
test.assert_equals(unusual_five(), 5, 'lol')
| true |
9d19104c37108c01e35bf007c449fd0a5033cedf | Python | geyang/plan2vec | /plan2vec/scratch/td_lambda.py | UTF-8 | 2,449 | 2.921875 | 3 | [] | no_license | import numpy as np
from params_proto.neo_proto import ParamsProto
class Args(ParamsProto):
gamma = 0.9
lam = 0.9
T = 20
N = 20 # truncation for TD(λ)
def td_lambda():
el_rewards = np.zeros(Args.T)
el_states = np.zeros(Args.T)
# We fix the G_t to the left side, and focus
# on comput... | true |
effd2e6a01eb9a715eb2ca287d00fa134fdf2474 | Python | CCALITA/CNNthings | /week10/10_3.py | UTF-8 | 1,982 | 3.015625 | 3 | [] | no_license | import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
boston_housing=tf.keras.datasets.boston_housing
(train_x,train_y),(test_x,test_y)=boston_housing.load_data()
#数据归一化处理
x_train=(train_x-train_x.min(axis=0))/(train_x.max(axis=0)-train_x.min(axis=0))
x_test=(test_x-test_x.min(axis=0))/(test_x... | true |
42e0bbba8ed554a6b5f49904383bc057e6c7d6c5 | Python | PaulB99/Tessa | /new/lines.py | UTF-8 | 7,707 | 3.390625 | 3 | [] | no_license | # Imports
import cv2
import matplotlib.pyplot as plt
import numpy as np
import scipy.ndimage
import scipy.stats
# Line class
class Line(object):
vertical_threshold = 30
def __init__(self, m, b, center, min_x, max_x, min_y, max_y):
'''
m: slope
b: y-intercept
center: cente... | true |
4e5369318ad362551632d48abfa4e4f0f23782d3 | Python | 401-python-final/wheres_my_bus_backend | /api_caller/views.py | UTF-8 | 11,512 | 2.875 | 3 | [] | no_license | from django.shortcuts import render
from django.http import HttpResponse, JsonResponse
from rest_framework.views import APIView
#import speech_recognition as sr
import requests
import time
import json
with open('bus_routes/finalRoutesAndIds.json') as all_routes:
route_data = json.load(all_routes)
print(route... | true |
bce12d9ab605840040a770164a47bc653c32c599 | Python | samuxiii/prototypes | /aigym/cartpole/cartpole.py | UTF-8 | 4,104 | 3.359375 | 3 | [
"MIT"
] | permissive | import os
import random
import gym
import numpy as np
from collections import deque
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from time import sleep
class Agent:
def __init__(self):
self.memory = []
self.epsilon = 1.0 #exploration rate
... | true |