code stringlengths 10 2.58M | original_code stringlengths 3 3.18M | original_language stringclasses 1
value | source stringclasses 7
values |
|---|---|---|---|
function generate_excerpt self
begin
if not call is_editable
begin
raise call Unauthorized string Editing is not allowed
end
if not call can_generate_excerpt
begin
raise call Forbidden string Generating excerpt is not allowed in this state.
end
try
begin
call generate_excerpt title=form at string excerpt_title
end
exce... | def generate_excerpt(self):
if not self.context.model.is_editable():
raise Unauthorized("Editing is not allowed")
if not self.agenda_item.can_generate_excerpt():
raise Forbidden('Generating excerpt is not allowed in this state.')
try:
self.agenda_item.genera... | Python | nomic_cornstack_python_v1 |
from gensim.models.keyedvectors import KeyedVectors
import numpy as np
import networkx as nx
import random
import math
import os
import io
import Constant
comment Path a carpeta con los embeddings
set EMBEDDING_FOLDER = EMBEDDING_FOLDER
class CrossMatchTestClass
begin
comment Resultados
set _RESULT = RESULTS_FOLDER / s... | from gensim.models.keyedvectors import KeyedVectors
import numpy as np
import networkx as nx
import random
import math
import os
import io
import Constant
# Path a carpeta con los embeddings
EMBEDDING_FOLDER = Constant.EMBEDDING_FOLDER
class CrossMatchTestClass:
# Resultados
_RESULT = Constant.RESULTS_FOL... | Python | zaydzuhri_stack_edu_python |
function is_integer j
begin
return not integer 2 * j % 2
end function | def is_integer(j):
return not(int(2*j)%2) | Python | nomic_cornstack_python_v1 |
function test_image filename x_size=350 y_size=350
begin
comment Create image and loop over all pixels
set im = call new string RGB tuple x_size y_size
set pixels = load im
for i in range x_size
begin
for j in range y_size
begin
set x = call remap_interval i 0 x_size - 1 1
set y = call remap_interval j 0 y_size - 1 1
c... | def test_image(filename, x_size=350, y_size=350):
# Create image and loop over all pixels
im = Image.new("RGB", (x_size, y_size))
pixels = im.load()
for i in range(x_size):
for j in range(y_size):
x = remap_interval(i, 0, x_size, -1, 1)
y = remap_interval(j, 0, y_size, -1... | Python | nomic_cornstack_python_v1 |
function b_vs_r r t=0.97
begin
set min_b = log 1 - t / log 1 - 0.95 ^ r
return min_b
end function | def b_vs_r(r, t=.97):
min_b = (np.log(1-t))/(np.log(1-.95**r))
return min_b | Python | nomic_cornstack_python_v1 |
comment -*- coding:UTF-8 -*-
function display_message
begin
string 显示本章学习的内容
print string Yor‘ll learn the 'function'.
end function
call display_message | # -*- coding:UTF-8 -*-
def display_message():
"""显示本章学习的内容"""
print("Yor‘ll learn the 'function'.")
display_message() | Python | zaydzuhri_stack_edu_python |
import math
from random import random as rand
from math import pi as pi
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
set fig = figure
set ax = call add_subplot 111 projection=string 3d
set X = list
set Y = list
set Z = list
set T = list
function plateMotion x y z delta ... | import math
from random import random as rand
from math import pi as pi
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X=[]
Y=[]
Z=[]
T=[]
def plateMotion(x,y,z,delta,n,tstep):
n=float(n)
delta=float(delta)... | Python | zaydzuhri_stack_edu_python |
import random
comment Define lists of words
set adjectives = list string happy string sad string tired string excited string bored
set nouns = list string day string night string morning string afternoon string evening
set verbs = list string went string ate string slept string worked string studied
comment Generate a ... | import random
# Define lists of words
adjectives = ['happy', 'sad', 'tired', 'excited', 'bored']
nouns = ['day', 'night', 'morning', 'afternoon', 'evening']
verbs = ['went', 'ate', 'slept', 'worked', 'studied']
# Generate a random sentence
sentence = random.choice(adjectives) + ' ' + random.choice(nouns) + ' ' + random... | Python | jtatman_500k |
import pandas as pd
import os
from sklearn.utils import shuffle
function xlsx_to_csv_pd excel_path csv_path
begin
set data_xls = call read_excel excel_path encoding=string utf-8
set labels = data_xls at string cluster_name
set label_uni = unique
set num_class = size
print num_class
set label_map = dictionary comprehens... | import pandas as pd
import os
from sklearn.utils import shuffle
def xlsx_to_csv_pd(excel_path,csv_path):
data_xls = pd.read_excel(excel_path,encoding='utf-8')
labels = data_xls['cluster_name']
label_uni = labels.unique()
num_class = label_uni.size
print(num_class)
label_map = {label: ind for ind, label in enumera... | Python | zaydzuhri_stack_edu_python |
function to_list bits
begin
set positions = list
for r in range 8
begin
for c in range 8
begin
set mask = call pos_mask r c
if bits ? mask > 0
begin
append positions call Position r c
end
end
end
return positions
end function | def to_list(bits: int) -> list[Position]:
positions = []
for r in range(8):
for c in range(8):
mask = pos_mask(r, c)
if bits & mask > 0:
positions.append(Position(r, c))
return positions | Python | nomic_cornstack_python_v1 |
comment !/usr/bin/python
comment -*- coding: UTF-8 -*-
string 1、学习怎样使用python中的“with”
string 2、demo：一个商店，例如沃尔玛，要求建立一个信息系统，这个系统可以查询到商店的员工信息和商品信息。 每个员工有一些像id、name、age等这样的信息，每个商品也要求有一些属性信息。当用户打开系统，他们可以 查询员工和商品信息。用户输入id，系统就返回员工或者商品的信息。 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
"""
1、学习怎样使用python中的“with”
"""
"""
2、demo：一个商店，例如沃尔玛，要求建立一个信息系统，这个系统可以查询到商店的员工信息和商品信息。
每个员工有一些像id、name、age等这样的信息，每个商品也要求有一些属性信息。当用户打开系统，他们可以
查询员工和商品信息。用户输入id，系统就返回员工或者商品的信息。
""" | Python | zaydzuhri_stack_edu_python |
function zip arrays depth_limit=none
begin
import awkward
import vector
import vector.backends.awkward
if not is instance arrays dict
begin
raise call TypeError string argument passed to vector.zip must be a dictionary
end
set tuple is_momentum dimension names columns = call _check_names arrays list keys arrays
set beh... | def zip(arrays: dict[str, typing.Any], depth_limit: int | None = None) -> typing.Any:
import awkward
import vector
import vector.backends.awkward
if not isinstance(arrays, dict):
raise TypeError("argument passed to vector.zip must be a dictionary")
is_momentum, dimension, names, columns =... | Python | nomic_cornstack_python_v1 |
function convert_dict_of_lists_to_df time_dict
begin
return call DataFrame time_dict
end function | def convert_dict_of_lists_to_df(time_dict):
return pd.DataFrame(time_dict) | Python | nomic_cornstack_python_v1 |
class Humano
begin
string Esta es la clase Humano exige atributos nombreEntrada: Hace referencia al nombre del usuario edadEntrada: Hace referencia al edad del usuario estaturaEntrada: Hace referencia al estatura del usuario Tiene las siguientes acciones: *hablar(mensaje): dado un mensaje lo muestra en pantalla *mostra... | class Humano ():
'''
Esta es la clase Humano exige atributos
nombreEntrada: Hace referencia al nombre del usuario
edadEntrada: Hace referencia al edad del usuario
estaturaEntrada: Hace referencia al estatura del usuario
Tiene las siguientes acciones:
*hablar(mensaje):
... | Python | zaydzuhri_stack_edu_python |
comment -*- coding: utf-8 -*-
string LearningFluentyPython.Delegate ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Delegate.py :copyright: (c) 2018 by Raymond. :last modified by 2018-07-03 15:35:41
class Proxy
begin
function __init__ self obj
begin
set _obj = obj
end function
function __getattr__ self name
begin
return get attribute _... | # -*- coding: utf-8 -*-
"""
LearningFluentyPython.Delegate
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Delegate.py
:copyright: (c) 2018 by Raymond.
:last modified by 2018-07-03 15:35:41
"""
class Proxy:
def __init__(self, obj):
self._obj = obj
def __getattr__(self, name):
return get... | Python | zaydzuhri_stack_edu_python |
function Mean_Radius ClusterResults
begin
return mean np list comprehension call average Size95X weights=Members for CR in ClusterResults
end function | def Mean_Radius(ClusterResults):
return np.mean([np.ma.average(CR.Size95X, weights=CR.Members) for CR in ClusterResults]) | Python | nomic_cornstack_python_v1 |
function _input_expr self match base
begin
set tokens = parse self call group 0
set segments = eval tokens
return base % call _set_regex *segments
end function | def _input_expr(self, match, base):
tokens = self.parse(match.group(0))
segments = self.eval(tokens)
return base % _set_regex(*segments) | Python | nomic_cornstack_python_v1 |
import random
import discord
import json
from discord.ext import commands
from random import randint
comment <== you can change this
set Defualt_bot_prefix = string /
comment your token
set token = string
set client = call Bot command_prefix=Defualt_bot_prefix
decorator event
comment This will tell if the bot is ready... | import random
import discord
import json
from discord.ext import commands
from random import randint
Defualt_bot_prefix = '/' # <== you can change this
token = '' # your token
client = commands.Bot(command_prefix=Defualt_bot_prefix)
#This will tell if the bot is ready or not:
# All events for the bot
@c... | Python | zaydzuhri_stack_edu_python |
comment -*- coding: utf-8 -*-
string Created on Sat Nov 25 20:40:23 2017 @author: vpx365
import os
from os.path import isdir , isfile , join
from pathlib import Path
import pandas as pd
comment Math
import numpy as np
import math
from scipy.fftpack import fft
from scipy import signal
from scipy.io import wavfile
from s... | # -*- coding: utf-8 -*-
"""
Created on Sat Nov 25 20:40:23 2017
@author: vpx365
"""
import os
from os.path import isdir, isfile, join
from pathlib import Path
import pandas as pd
# Math
import numpy as np
import math
from scipy.fftpack import fft
from scipy import signal
from scipy.io import wavfile
from sklearn.de... | Python | zaydzuhri_stack_edu_python |
function reset_bd
begin
call delete_many dict
end function | def reset_bd() -> None:
COLLECTION.delete_many({}) | Python | nomic_cornstack_python_v1 |
function plot_isoline self level=0.0 n=none tri_alpha=0
begin
set hv = call ensure_holoviews
if n == - 1
begin
set plot = call Path list
end
else
begin
set plot = plot n=n tri_alpha=tri_alpha
end
if is instance level Iterable
begin
for lvl in level
begin
set plot = plot * call plot_isoline level=lvl n=- 1
end
return pl... | def plot_isoline(self, level=0.0, n=None, tri_alpha=0):
hv = ensure_holoviews()
if n == -1:
plot = hv.Path([])
else:
plot = self.plot(n=n, tri_alpha=tri_alpha)
if isinstance(level, Iterable):
for lvl in level:
plot = plot * self.plot_i... | Python | nomic_cornstack_python_v1 |
function test
begin
import unittest
set tests = call discover string tests
run tests
end function | def test():
import unittest
tests = unittest.TestLoader().discover('tests')
unittest.TextTestRunner(verbosity=2).run(tests) | Python | nomic_cornstack_python_v1 |
function actions self actions
begin
if actions is none
begin
raise call ValueError string Invalid value for `actions`, must not be `None`
end
set _actions = actions
end function | def actions(self, actions):
if actions is None:
raise ValueError("Invalid value for `actions`, must not be `None`")
self._actions = actions | Python | nomic_cornstack_python_v1 |
function type self
begin
return __type
end function | def type(self) -> Union[AssetType, str]:
return self.__type | Python | nomic_cornstack_python_v1 |
function Nu X x
begin
return length list comprehension 1 for v in X if v > x
end function | def Nu(X, x):
return len([1 for v in X if v > x]) | Python | nomic_cornstack_python_v1 |
function fails self model
begin
function _fail_dict msg treatment
begin
return dict string error_code _error_code ; string inconsistent_variables _var_names ; string error_message msg ; string treatment name
end function
for treatment in call treatments
begin
if call _is_defined_for_all model treatment
begin
set amount... | def fails(self, model):
def _fail_dict(msg, treatment):
return {
'error_code': self._error_code,
'inconsistent_variables': self._var_names,
'error_message': msg,
'treatment': treatment.name
... | Python | nomic_cornstack_python_v1 |
function execute context log
begin
try
begin
comment Don't run if there were errors or if this is a dry run
set ok_to_run = true
set dry = false
comment return codes from all runs
set ret = list
comment assume the worst
set return_code = 1
if length gear_dict at string errors > 0
begin
set ok_to_run = false
append ret... | def execute(context, log):
try:
# Don't run if there were errors or if this is a dry run
ok_to_run = True
dry = False
ret = [] # return codes from all runs
return_code = 1 # assume the worst
if len(context.gear_dict['errors']) > 0:
ok_to_run = False
... | Python | nomic_cornstack_python_v1 |
function filtered_rows filename operation thread stage
begin
set data = list
for row in call filter_lines filename operation thread stage
begin
append data row
end
return data
end function | def filtered_rows(filename, operation, thread, stage):
data = []
for row in filter_lines(filename, operation, thread, stage):
data.append(row)
return data | Python | nomic_cornstack_python_v1 |
function compute_decorr_time sfreq data
begin
set n_channels = shape at 0
set decorrelation_times = call empty tuple n_channels
for j in range n_channels
begin
set _acf = call _unbiased_autocorr data at tuple j slice : :
set zc = diff np call sign _acf != 0
if any zc
begin
set decorr_time = argument maximum zc + 1
se... | def compute_decorr_time(sfreq, data):
n_channels = data.shape[0]
decorrelation_times = np.empty((n_channels,))
for j in range(n_channels):
_acf = _unbiased_autocorr(data[j, :])
zc = np.diff(np.sign(_acf)) != 0
if np.any(zc):
decorr_time = np.argmax(zc) + 1
dec... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
comment plots SNR for cross-correlation functions with steadily growing window lengths
comment starting at 32 seconds (one file) and ending in somewhat around 73 files merged (40 mins)
import numpy as np
import csv
import matplotlib.pyplot as plt
import datetime
from obspy import UTCDateTi... | # -*- coding: utf-8 -*-
# plots SNR for cross-correlation functions with steadily growing window lengths
# starting at 32 seconds (one file) and ending in somewhat around 73 files merged (40 mins)
import numpy as np
import csv
import matplotlib.pyplot as plt
import datetime
from obspy import UTCDateTime
from matplot... | Python | zaydzuhri_stack_edu_python |
function addTask self script taskId clearMemory=true
begin
return run script taskId clearMemory
end function | def addTask(self, script:str, taskId:int, clearMemory:bool = True):
return self.pool.run(script, taskId, clearMemory) | Python | nomic_cornstack_python_v1 |
function calcular_PuntosClave_Descriptores imagen sigma=1.6 num_intervalos=3 assumed_blur=0.5 ancho_borde_imagen=5
begin
set imagen = as type imagen string float32
set imagen_base = call generar_Imagen_Base imagen sigma assumed_blur
set numero_octavas = call calcular_Numero_Octavas shape
set kernels_gaussianos = call g... | def calcular_PuntosClave_Descriptores(imagen, sigma=1.6, num_intervalos=3, assumed_blur=0.5, ancho_borde_imagen=5):
imagen = imagen.astype('float32')
imagen_base = generar_Imagen_Base(imagen, sigma, assumed_blur)
numero_octavas = calcular_Numero_Octavas(imagen_base.shape)
kernels_gaussianos = generar_Ke... | Python | nomic_cornstack_python_v1 |
import numpy as np
import matplotlib
import matplotlib.pyplot as pyplot
import collections
import scipy
import scipy.stats
import scipy.fftpack
import struct
import subprocess
from fractions import gcd
from wave import open as open_wave
import warnings
try
begin
from IPython.display import Audio
end
except any
begin
wa... | import numpy as np
import matplotlib
import matplotlib.pyplot as pyplot
import collections
import scipy
import scipy.stats
import scipy.fftpack
import struct
import subprocess
from fractions import gcd
from wave import open as open_wave
import warnings
try:
from IPython.display import Audio
except:
warnings... | Python | zaydzuhri_stack_edu_python |
function get_daily_goals self surface dates
begin
set iterator = call order_by string day
return list comprehension list day average * DJU_TO_KWH * KWH_TO_EUROS * surface for x in iterator
end function | def get_daily_goals(self, surface, dates):
iterator = DjuDay.objects.filter(day__in=dates).order_by('day')
return [
[x.day, x.average * DJU_TO_KWH * KWH_TO_EUROS * surface] for x in iterator
] | Python | nomic_cornstack_python_v1 |
function clear_flair_templates self subreddit is_link=false
begin
string Clear flair templates for the given subreddit. :returns: The json response from the server.
set data = dict string r call text_type subreddit ; string flair_type if expression is_link then string LINK_FLAIR else string USER_FLAIR
return call reque... | def clear_flair_templates(self, subreddit, is_link=False):
"""Clear flair templates for the given subreddit.
:returns: The json response from the server.
"""
data = {'r': six.text_type(subreddit),
'flair_type': 'LINK_FLAIR' if is_link else 'USER_FLAIR'}
return s... | Python | jtatman_500k |
function asteriscos n
begin
set a = n * string string *
return a
end function
set a = call asteriscos n
print a | def asteriscos (n):
a=n*str("*")
return a
a=asteriscos(n)
print(a) | Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/env python3
string Переиндексирует объявления и URL-ы Вход: URL вьюдира или файл «id_file» с id-шниками (перед id гудса должен быть дефис) Выход: ничего (переиндексированные объявления) Нужно помнить, что farpost.ru отдает максимум 180 страниц вьюдира. Если объявлений >9000, то их нужно разбить на час... | #!/usr/bin/env python3
'''
Переиндексирует объявления и URL-ы
Вход: URL вьюдира или файл «id_file» с id-шниками (перед id гудса должен быть дефис)
Выход: ничего (переиндексированные объявления)
Нужно помнить, что farpost.ru отдает максимум 180 страниц вьюдира. Если объявлений >9000, то их нужно разбить на части (напр... | Python | zaydzuhri_stack_edu_python |
comment Developed By : NIRANJAN KUMAR G S
comment From : INDIA
comment Email : niranjan4@outlook.in
comment Updated date : 12/sep/2017
from requests import get
from bs4 import BeautifulSoup
import pandas as pd
import re
import matplotlib.pyplot as plt
comment this is not complete code contact 7019832930
class Webscrape... | # Developed By : NIRANJAN KUMAR G S
# From : INDIA
# Email : niranjan4@outlook.in
# Updated date : 12/sep/2017
from requests import get
from bs4 import BeautifulSoup
import pandas as pd
import re
import matplotlib.pyplot as plt
### this is not complete code contact 7019832930
class Webscraper:
def __init__(self, u... | Python | zaydzuhri_stack_edu_python |
function process cls target
begin
set result : List at Attr = list
for attr in attrs
begin
set pos = find collections result attr
set existing = if expression pos > - 1 then result at pos else none
if not existing
begin
append result attr
end
else
if not is_attribute or is_enumeration
begin
set help = help or help
set... | def process(cls, target: Class):
result: List[Attr] = []
for attr in target.attrs:
pos = collections.find(result, attr)
existing = result[pos] if pos > -1 else None
if not existing:
result.append(attr)
elif not (attr.is_attribute or attr.i... | Python | nomic_cornstack_python_v1 |
function snyder_opt self structure
begin
string Calculates Snyder's optical sound velocity (in SI units) Args: structure: pymatgen structure object Returns: Snyder's optical sound velocity (in SI units)
set nsites = num_sites
set volume = volume
set num_density = 1e+30 * nsites / volume
return 1.66914e-23 * call long_v... | def snyder_opt(self, structure):
"""
Calculates Snyder's optical sound velocity (in SI units)
Args:
structure: pymatgen structure object
Returns: Snyder's optical sound velocity (in SI units)
"""
nsites = structure.num_sites
volume = structure.volum... | Python | jtatman_500k |
set x = input
print upper x at 0 + x at slice 1 : : | x = input()
print(x[0].upper() + x[1:])
| Python | zaydzuhri_stack_edu_python |
import pickle
import pygame
from game.player.player import Player
from game.environment.board import Board
from game.player.bullets import ActiveBullets
from game.player.health_bar import HealthBar
from game.environment.directions import Direction
from game.bots.ai_bot import AI_bot
import numpy as np
function run_trai... | import pickle
import pygame
from game.player.player import Player
from game.environment.board import Board
from game.player.bullets import ActiveBullets
from game.player.health_bar import HealthBar
from game.environment.directions import Direction
from game.bots.ai_bot import AI_bot
import numpy as np
def run_train_A... | Python | zaydzuhri_stack_edu_python |
function multiplication number1 number2
begin
return number1 * number2
end function | def multiplication(number1, number2):
return number1 * number2 | Python | nomic_cornstack_python_v1 |
try
begin
import os
import json
import io
import urllib.request
from robobrowser import RoboBrowser
import html
end
except Exception as err
begin
print format string Error 101:Import failed {0} err
exit 101
end
set fromusr = string
set tousr = string
set topsd = string
set b = call RoboBrowser parser=string html.par... | try:
import os
import json
import io
import urllib.request
from robobrowser import RoboBrowser
import html
except Exception as err:
print("Error 101:Import failed {0}".format(err))
exit(101)
fromusr=""
tousr=""
topsd=""
b=RoboBrowser(parser="html.parser")
def getURL... | Python | zaydzuhri_stack_edu_python |
import numpy as np
function kdists matrix k=7 ix=none
begin
string Returns the k-th nearest distances, row-wise, as a column vector
set ix = ix or call kindex matrix k
return T
end function
function kindex matrix k
begin
string Returns indices to select the kth nearest neighbour
set ix = tuple array range length matrix... | import numpy as np
def kdists(matrix, k=7, ix=None):
""" Returns the k-th nearest distances, row-wise, as a column vector """
ix = ix or kindex(matrix, k)
return matrix[ix][np.newaxis].T
def kindex(matrix, k):
""" Returns indices to select the kth nearest neighbour"""
ix = (np.arange(len(matrix... | Python | zaydzuhri_stack_edu_python |
function plot_emoji_heatmap df size=tuple 20 5 agg=string from axs=none
begin
set df_smiley = call agg list string count __custom_smiley_aggregator
set ls_smiley = list
for x in call itertuples
begin
for tuple smiley count in _2
begin
append ls_smiley tuple Index smiley count
end
end
set df_smiley_reduced = call DataF... | def plot_emoji_heatmap(df, size=(20, 5), agg='from', axs=None):
df_smiley = df.groupby(agg)['emojis'].agg(['count', __custom_smiley_aggregator])
ls_smiley = []
for x in df_smiley.itertuples():
for smiley, count in x._2:
ls_smiley.append((x.Index, smiley, count))
df_smiley_reduced = p... | Python | nomic_cornstack_python_v1 |
comment !/usr/bin/python3
comment -*- coding: utf-8 -*-
import unittest
from q import Casier as CasierStudent
from Casier import *
from Biere import *
import random as rd
seed 2019
set nom_biere = list string Jupiler string leffe string Chimay
function generateCasier min_value max_value
begin
set instances = list compr... | #!/usr/bin/python3
# -*- coding: utf-8 -*-
import unittest
from q import Casier as CasierStudent
from Casier import *
from Biere import *
import random as rd
rd.seed(2019)
nom_biere=["Jupiler","leffe","Chimay"]
def generateCasier(min_value,max_value):
instances=[[] for i in range(5)]
for i in range(5):
... | Python | zaydzuhri_stack_edu_python |
function _params_slice_for_W_zero self params_type
begin
return call _general_params_slice nemf
end function | def _params_slice_for_W_zero(self, params_type):
return self._general_params_slice(self.nemf) | Python | nomic_cornstack_python_v1 |
import datetime
import argparse
import re
import json
import time
import math
import numpy as np
function parse_deviation log_name limit=0
begin
string Create JSON files in ./dumps directory: 1) log_clients_diff_{lines parsed}.json -- Time difference between requests 2) log_clients_mean_{lines parsed}.json -- Mean valu... | import datetime
import argparse
import re
import json
import time
import math
import numpy as np
def parse_deviation(log_name: str, limit=0) -> None:
"""
Create JSON files in ./dumps directory:
1) log_clients_diff_{lines parsed}.json
-- Time difference between requests
2) log_clients_mean_{l... | Python | zaydzuhri_stack_edu_python |
import time
from tinydb import TinyDB , Query
class DatabaseManager
begin
string A class representing an object used to interact with a local database, to keep track of visitors interacting with the robot
set __db : TinyDB
function __init__ self
begin
comment Initialize the database
set __db = call TinyDB string ./visi... | import time
from tinydb import TinyDB, Query
class DatabaseManager():
"""
A class representing an object used to interact with a local database, to keep track of visitors interacting with the robot
"""
__db: TinyDB
def __init__(self):
# Initialize the database
self.__db = TinyDB... | Python | zaydzuhri_stack_edu_python |
comment Time: O(n)
comment Space: O(n)
string Given a singly linked list where elements are sorted in ascending order, convert it to a height balanced BST. For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every node never differ by more than 1. Exampl... | # Time: O(n)
# Space: O(n)
"""
Given a singly linked list where elements are sorted in ascending order, convert it to a height balanced BST.
For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every
node never differ by more than 1.
Example:
G... | Python | zaydzuhri_stack_edu_python |
function get_node_connection self client_settings node
begin
set tuple settings timeout = value
set cache_key = tuple node client_settings
if cache_key not in __connection_cache
begin
set __connection_cache at cache_key = call ClickhousePool host_name port __user __password __database client_settings=settings send_rece... | def get_node_connection(
self, client_settings: ClickhouseClientSettings, node: ClickhouseNode,
) -> ClickhousePool:
settings, timeout = client_settings.value
cache_key = (node, client_settings)
if cache_key not in self.__connection_cache:
self.__connection_cache[cache_k... | Python | nomic_cornstack_python_v1 |
function fix_continuity self continuity
begin
return call fix_continuity self continuity
end function | def fix_continuity(self, continuity):
return fix_continuity(self, continuity) | Python | nomic_cornstack_python_v1 |
function del_tags self tags
begin
string remove a tag or tags from a symbol Parameters ---------- tags : str or [str,] Tags to be removed
comment SQLA Adding a SymbolTag object, feels awkward/uneccessary.
comment Should I be implementing this functionality a different way?
if is instance tags tuple str unicode
begin
se... | def del_tags(self, tags):
""" remove a tag or tags from a symbol
Parameters
----------
tags : str or [str,]
Tags to be removed
"""
# SQLA Adding a SymbolTag object, feels awkward/uneccessary.
# Should I be implementing this functiona... | Python | jtatman_500k |
import random
set sentence = string ManchesterMetropolitanUniversity0123456789|{_@&
set size = length sentence
set passwords = list
set orderedNumbers = list
set charList = list sentence | import random
sentence = 'ManchesterMetropolitanUniversity0123456789|{_@&'
size = len(sentence)
passwords = []
orderedNumbers = []
charList = list(sentence) | Python | zaydzuhri_stack_edu_python |
function setName self name createNamespace=string False
begin
pass
end function | def setName(self, name, createNamespace='False'):
pass | Python | nomic_cornstack_python_v1 |
function next_collatz n
begin
if n <= 1
begin
raise call ValueError string eular14.next_collatz: n must be a positive integer larger than 1!
end
else
if n % 2 == 0
begin
return n // 2
end
else
begin
return 3 * n + 1
end
end function | def next_collatz(n):
if n <= 1:
raise ValueError('eular14.next_collatz: n must be a positive integer larger than 1!')
elif n % 2 == 0:
return n // 2
else:
return (3 * n) + 1 | Python | nomic_cornstack_python_v1 |
function deserialize_model_instance self model_class
begin
return call from_dictionary request_body
end function | def deserialize_model_instance(self, model_class):
return model_class.from_dictionary(self.request_body) | Python | nomic_cornstack_python_v1 |
from tkinter import *
import random
from tkinter import messagebox
function load_card_images card_list
begin
set suits = list string heart string diamond string club string spade
set face_cards = list string king string queen string jack
if TkVersion >= 8.6
begin
set extension = string png
end
else
begin
set extension ... | from tkinter import *
import random
from tkinter import messagebox
def load_card_images(card_list):
suits = ['heart', 'diamond', 'club', 'spade']
face_cards= ['king', 'queen', 'jack']
if TkVersion >= 8.6:
extension = 'png'
else:
extension = 'ppm'
for suit in suits:
... | Python | zaydzuhri_stack_edu_python |
function oauth2_auth_url redirect_uri=none client_id=none base_url=OH_BASE_URL
begin
if not client_id
begin
set client_id = call getenv string OHAPI_CLIENT_ID
if not client_id
begin
raise call SettingsError string Client ID not provided! Provide client_id as a parameter, or set OHAPI_CLIENT_ID in your environment.
end
... | def oauth2_auth_url(redirect_uri=None, client_id=None, base_url=OH_BASE_URL):
if not client_id:
client_id = os.getenv('OHAPI_CLIENT_ID')
if not client_id:
raise SettingsError(
"Client ID not provided! Provide client_id as a parameter, "
"or set OHAPI_CLIEN... | Python | nomic_cornstack_python_v1 |
for number in numbers
begin
if number not in number_counts
begin
set number_counts at number = 0
end
set number_counts at number = number_counts at number + 1
end
for tuple number count in items number_counts
begin
print string { number } - { count } times
end | for number in numbers:
if number not in number_counts:
number_counts[number] = 0
number_counts[number] += 1
for number, count in number_counts.items():
print(f"{number} - {count} times") | Python | zaydzuhri_stack_edu_python |
import sys
function strToInt s
begin
set s = strip s
if not s
begin
return 0
end
set index = 0
set symbol = true
if s at index == string -
begin
set symbol = false
set index = index + 1
end
set result = 0
while index < length s
begin
set num = s at index - string 0
if num < 0 or num > 9
begin
return 0
end
set result = ... | import sys
def strToInt(s):
s = s.strip()
if not s: return 0
index = 0
symbol = True
if s[index] == '-':
symbol = False
index += 1
result = 0
while index < len(s):
num = s[index] - '0'
if num < 0 or num > 9:
return 0
result = result * 10 + num
if result > sys.max:
retu... | Python | zaydzuhri_stack_edu_python |
from pages.google_home import GoogleHome
from tests.base_test import BaseTest
class TestGoogleSearch extends BaseTest
begin
function setup_method self method
begin
call get_driver method
set google_home = call GoogleHome driver
call visit
end function
function teardown_method self _
begin
call quit_driver
end function
... | from pages.google_home import GoogleHome
from tests.base_test import BaseTest
class TestGoogleSearch(BaseTest):
def setup_method(self, method):
self.get_driver(method)
self.google_home = GoogleHome(self.driver)
self.google_home.visit()
def teardown_method(self, _):
self.quit_d... | Python | zaydzuhri_stack_edu_python |
import unittest
import numpy.testing as npt
import pb.ball
class TestBall extends TestCase
begin
function testGetPhantomPos self
begin
comment H <-- B
set ball = call Ball 1 0 0.5
set pos = call get_phantom_pos tuple 0 0
call assert_almost_equal pos tuple 2 0
comment H
comment ^
comment |
comment B
set ball = call Ball... | import unittest
import numpy.testing as npt
import pb.ball
class TestBall(unittest.TestCase):
def testGetPhantomPos(self):
# H <-- B
ball = pb.ball.Ball(1,0,0.5)
pos = ball.get_phantom_pos((0,0))
npt.assert_almost_equal(pos, (2,0))
# H
# ^
# |
# B
... | Python | zaydzuhri_stack_edu_python |
import json
from collections import defaultdict
import csv
from pathlib import Path
set business_data = list
set review_data = list
comment Path where Rishabh's data is stored
print string Reading Business JSON
for line_business in open string D:\Courses\18755\yelp_dataset\yelp_academic_dataset_business.json string r... | import json
from collections import defaultdict
import csv
from pathlib import Path
business_data = []
review_data = []
# Path where Rishabh's data is stored
print("Reading Business JSON")
for line_business in open('D:\Courses\\18755\yelp_dataset\yelp_academic_dataset_business.json', 'r', encoding="utf8"):
... | Python | zaydzuhri_stack_edu_python |
comment -*- coding:utf-8 -*-
import xlsxwriter
comment read file, 按行创建一个列表
set f0 = open string hall0.txt string r encoding=string utf-8
set content_list0 = list comprehension i for i in f0 if string mag in i
close f0
set f1 = open string hall1.txt string r encoding=string utf-8
set content_list1 = list comprehension i... | # -*- coding:utf-8 -*-
import xlsxwriter
# read file, 按行创建一个列表
f0 = open('hall0.txt', 'r', encoding='utf-8')
content_list0 = [i for i in f0 if 'mag' in i]
f0.close()
f1 = open('hall1.txt', 'r', encoding='utf-8')
content_list1 = [i for i in f1 if 'mag' in i]
f1.close()
# 创建一个excel
workbook = xlsxwriter.Workbook("hal... | Python | zaydzuhri_stack_edu_python |
function gandiva_node_set_adjust self cur_time jobs
begin
set total_gpu_demands = 0
set nl_gpu_demands = dictionary
set nl_gpu_occupied = dictionary
for tuple num_gpu node_list in items node_g
begin
set total_jobs = 0
set occupied_gpus = 0
for node_set in node_list
begin
set total_jobs = total_jobs + length node_set at... | def gandiva_node_set_adjust(self, cur_time, jobs):
total_gpu_demands = 0
nl_gpu_demands = dict()
nl_gpu_occupied = dict()
for num_gpu, node_list in self.node_g.items():
total_jobs = 0
occupied_gpus = 0
for node_set in node_list:
... | Python | nomic_cornstack_python_v1 |
string Shared functions/constructs are here.
from torch.optim import SGD , lr_scheduler
import torch.nn.functional as F
from torch import nn
function pretrain_optimizers parameters momentum weight_decay lr lars=true
begin
string If using the LARS optimizer, cosine decay schedule is used. This is a simpler scheduler, dr... | '''
Shared functions/constructs are here.
'''
from torch.optim import SGD, lr_scheduler
import torch.nn.functional as F
from torch import nn
def pretrain_optimizers(parameters, momentum, weight_decay, lr, lars=True):
'''
If using the LARS optimizer, cosine decay schedule is used.
This is a simpler... | Python | zaydzuhri_stack_edu_python |
from manim import *
class SquareToCircle extends Scene
begin
function construct self
begin
set circle = call Circle
set square = call Square
set triangle = call Triangle
set text = call Text string Alice
set p1 = list - 1 - 1 0
set p2 = list 1 - 1 0
set p3 = list 1 1 0
set p4 = list - 1 1 0
set a = call append_points c... | from manim import *
class SquareToCircle(Scene):
def construct(self):
circle = Circle()
square = Square()
triangle = Triangle()
text = Text("Alice")
p1 = [-1, -1, 0]
p2 = [1, -1, 0]
p3 = [1,1, 0]
p4 = [-1, 1, 0]
a = Line(p1, p2).append_po... | Python | zaydzuhri_stack_edu_python |
function predictions model x_train y_train x_test y_test
begin
comment Train the model on training data.
fit model x_train y_train
comment Use the model to predict the test set.
set y_pred = predict model x_test
comment Create a confusion matrix and write to file.
set cm_df = call DataFrame call confusion_matrix y_test... | def predictions(model, x_train, y_train, x_test, y_test):
# Train the model on training data.
model.fit(x_train, y_train)
# Use the model to predict the test set.
y_pred = model.predict(x_test)
# Create a confusion matrix and write to file.
cm_df = pd.DataFrame(metrics.confusion_matrix... | Python | nomic_cornstack_python_v1 |
comment Without Lambda
function high_marks n
begin
if n >= 60
begin
return true
end
end function
set result = list filter high_marks a
print result
print type result
print
comment With Lambda
set result = list filter lambda n -> n >= 60 a
print result
print type result | # Without Lambda
def high_marks(n):
if n >= 60:
return True
result = list(filter(high_marks,a))
print(result)
print(type(result))
print()
# With Lambda
result = list(filter(lambda n : (n>=60),a))
print(result)
print(type(result))
| Python | zaydzuhri_stack_edu_python |
function getInputSpecification cls
begin
set inputSpecification = call getInputSpecification
call addSub call parameterInputFactory string costID contentType=StringType
call addSub call parameterInputFactory string valueID contentType=StringType
return inputSpecification
end function | def getInputSpecification(cls):
inputSpecification = super(ParetoFrontier, cls).getInputSpecification()
inputSpecification.addSub(InputData.parameterInputFactory('costID' , contentType=InputTypes.StringType))
inputSpecification.addSub(InputData.parameterInputFactory('valueID', contentType=InputTypes.StringT... | Python | nomic_cornstack_python_v1 |
function map_objects cls all_objects
begin
comment Do the object mapping
for obj in all_objects
begin
comment Add the Object to its respective dictionary
if id_
begin
set id_objects at id_ = obj
end
else
if idref and idref not in idref_objects
begin
set idref_objects at idref = list obj
end
else
if idref and idref in i... | def map_objects(cls, all_objects):
# Do the object mapping
for obj in all_objects:
# Add the Object to its respective dictionary
if obj.id_:
cls.id_objects[obj.id_] = obj
elif obj.idref and obj.idref not in cls.idref_objects:
cls.idref_... | Python | nomic_cornstack_python_v1 |
function func
begin
set user_input = input string Enter a string:
set vowels = list string a string e string i string o string u
set vowel_count = 0
set consonant_count = 0
for char in user_input
begin
if lower char in vowels
begin
set vowel_count = vowel_count + 1
end
else
if is alpha char
begin
set consonant_count = ... | def func():
user_input = input("Enter a string: ")
vowels = ['a', 'e', 'i', 'o', 'u']
vowel_count = 0
consonant_count = 0
for char in user_input:
if char.lower() in vowels:
vowel_count += 1
elif char.isalpha():
consonant_count += 1
print("The number of vow... | Python | greatdarklord_python_dataset |
import numpy as np
import cv2
function count_non_singleton_dimension array
begin
set array_shape = shape
set nsd_numerosity = sum generator expression 1 for i in array_shape if i > 1
return nsd_numerosity
end function
function filter1d_x volume kernel border_type=BORDER_REFLECT_101
begin
if length shape != 3
begin
rais... | import numpy as np
import cv2
def count_non_singleton_dimension(array):
array_shape = array.shape
nsd_numerosity = sum(1 for i in array_shape if i > 1)
return nsd_numerosity
def filter1d_x(volume, kernel, border_type = cv2.BORDER_REFLECT_101):
if len(volume.shape) != 3:
raise ValueError("T... | Python | zaydzuhri_stack_edu_python |
function test_range_check
begin
set filter_ = range 2 4 false true
assert not call check 2
assert call check 3
assert call check 4
assert string filter_ == string >2,<=4
set filter_ = range 2 none true true
assert not call check 1
assert call check 2
assert string filter_ == string >=2
set filter_ = range 2 none false ... | def test_range_check() -> None:
filter_ = Range(2, 4, False, True)
assert not filter_.check(2)
assert filter_.check(3)
assert filter_.check(4)
assert str(filter_) == ">2,<=4"
filter_ = Range(2, None, True, True)
assert not filter_.check(1)
assert filter_.check(2)
assert str(filter_)... | Python | nomic_cornstack_python_v1 |
comment Interview Scheduling Problem
from constraint import Problem
from constraint import AllDifferentConstraint
set problem = call Problem
comment The possible appointment times are 1, 2, 3 or 4
comment There are four applicants: Ali, Bob, Cyl, and Dan
comment Ali is busy from 2 to 3
call addVariable string Ali list ... | # Interview Scheduling Problem
from constraint import Problem
from constraint import AllDifferentConstraint
problem = Problem()
# The possible appointment times are 1, 2, 3 or 4
# There are four applicants: Ali, Bob, Cyl, and Dan
problem.addVariable('Ali',[1,3,4])# Ali is busy from 2 to 3
problem.addVariable('Dan',[... | Python | zaydzuhri_stack_edu_python |
import sys
import numpy as np
import scipy.sparse.linalg
from conditions import Neumann
from helpers import central_difference
from integrate import integrate
from interpolate import calculate_poisson_derivatives , interpolate
from nonuniform import has_uniform_steps , liu_coefficients
from refine import refine_after ,... | import sys
import numpy as np
import scipy.sparse.linalg
from .conditions import Neumann
from .helpers import central_difference
from .integrate import integrate
from .interpolate import calculate_poisson_derivatives, interpolate
from .nonuniform import has_uniform_steps, liu_coefficients
from .refine import refine_a... | Python | zaydzuhri_stack_edu_python |
for c in tuple 2 n
begin
if n % c == 0 and n != c
begin
set cont = cont + 1
end
end
if cont == 0
begin
print string Numero primo
end
else
if cont != 0
begin
print string Numero não é primo
end | for c in (2, n):
if n % c == 0 and n != c:
cont = cont + 1
if cont == 0:
print('Numero primo')
elif cont != 0:
print('Numero não é primo')
| Python | zaydzuhri_stack_edu_python |
from django.test import TestCase
comment Create your tests here.
set a = list 1 2 3
set b = string 1
set c = 1
print iterate a
print iterate b | from django.test import TestCase
# Create your tests here.
a=[1,2,3]
b='1'
c=1
print(iter(a))
print(iter(b))
| Python | zaydzuhri_stack_edu_python |
from itertools import permutations
from math import sqrt
function is_prime num
begin
if num < 2
begin
return false
end
for i in range 2 integer square root num + 1
begin
if num % i == 0
begin
return false
end
end
return true
end function
function find_prime_permutations num
begin
set num_str = string num
set digits = l... | from itertools import permutations
from math import sqrt
def is_prime(num):
if num < 2:
return False
for i in range(2, int(sqrt(num)) + 1):
if num % i == 0:
return False
return True
def find_prime_permutations(num):
num_str = str(num)
digits = [int(d) for d in num_str]
... | Python | jtatman_500k |
comment -*- coding: utf-8 -*-
from __future__ import unicode_literals
from datetime import datetime
from pattern.en import singularize
import sys
comment sys.path.insert(0,"I:\Projects\finderbuddy")
comment sys.path.insert(0,"C:\Users\aman_AV\Desktop\Finder_Buddy\finder_Buddy")
comment from msgbox import threshold
from... | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from datetime import datetime
from pattern.en import singularize
import sys
#sys.path.insert(0,"I:\Projects\finderbuddy")
#sys.path.insert(0,"C:\Users\aman_AV\Desktop\Finder_Buddy\finder_Buddy")
#from msgbox import threshold
from .logic_adapter import Logi... | Python | zaydzuhri_stack_edu_python |
import matplotlib.pyplot as plt
function get_insights data
begin
print string Getting insights from KPIs!
comment Purchase By Type: ONEOFF_ONLY, INSTALLMENTS_ONLY, BOTH_ONEOFF_INSTALL, NONE_ONEOFF_INSTALL
comment This KPI is done here because of it's none number value and later is dropped
set data at string PURCHASE_TY... | import matplotlib.pyplot as plt
def get_insights(data):
print("Getting insights from KPIs!")
# Purchase By Type: ONEOFF_ONLY, INSTALLMENTS_ONLY, BOTH_ONEOFF_INSTALL, NONE_ONEOFF_INSTALL
# This KPI is done here because of it's none number value and later is dropped
data["PURCHASE_... | Python | zaydzuhri_stack_edu_python |
for i in item
begin
if i != temp
begin
set rs = rs + i
end
set temp = i
end
print rs | for i in item:
if i != temp:
rs += i
temp = i
print(rs) | Python | zaydzuhri_stack_edu_python |
function integral_tangential p_i p_j
begin
function func s
begin
return - xc - xa - sin beta * s * sin beta + yc - ya + cos beta * s * cos beta / xc - xa - sin beta * s ^ 2 + yc - ya + cos beta * s ^ 2
end function
return call quad lambda s -> call func s 0.0 length at 0
end function | def integral_tangential(p_i, p_j):
def func(s):
return ( (-(p_i.xc-(p_j.xa-math.sin(p_j.beta)*s))*math.sin(p_i.beta)
+(p_i.yc-(p_j.ya+math.cos(p_j.beta)*s))*math.cos(p_i.beta))
/((p_i.xc-(p_j.xa-math.sin(p_j.beta)*s))**2
+(p_i.yc-(p_j.ya+math.cos(p_j.bet... | Python | nomic_cornstack_python_v1 |
function create_list_node Admonition
begin
set list_node = type lower __name__ + string list_node tuple generic_list_node General Element dict
return list_node
end function | def create_list_node(Admonition):
list_node = type(
Admonition.__name__.lower()+'list_node',
(generic_list_node, nodes.General, nodes.Element),
{}
)
return list_node | Python | nomic_cornstack_python_v1 |
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
set mnist = call read_data_sets string data/MNIST/ one_hot=true
comment mnist data setinde işlem yapmayı sağlayan kütüphane.
comment Bu kodla mnisti indirerek işlem yapmaya hazır hale getiriyoruz.
comment labeller one hot olarak istendi ... | import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist= input_data.read_data_sets("data/MNIST/", one_hot=True)
#mnist data setinde işlem yapmayı sağlayan kütüphane.
# Bu kodla mnisti indirerek işlem yapmaya hazır hale getiriyoruz.
#labeller one hot olarak istendi yani 10 uzunluğunda ve... | Python | zaydzuhri_stack_edu_python |
function run self
begin
info string Update the Infos of the Router( + string id + string ) ... 1
call connect_with_remote_system
try
begin
comment Model
set model = call _get_router_model
comment MAC
set mac = call _get_router_mac
comment SSID
set ssid = call _get_router_ssid
comment NetworkInterfaces
set interfaces = ... | def run(self):
Logger().info("Update the Infos of the Router(" + str(self.router.id) + ") ...", 1)
self.network_ctrl.connect_with_remote_system()
try:
# Model
self.router.model = self._get_router_model()
# MAC
self.router.mac = self._get_router_mac... | Python | nomic_cornstack_python_v1 |
function run_one_iteration self current_state current_log_pdf
begin
comment Start the loop over nsamples - this code uses the parallel version of the stretch algorithm
set all_inds = array range nchains
set inds = all_inds % 2
set accept_vec = zeros tuple nchains
comment Separate the full ensemble into two sets, use on... | def run_one_iteration(self, current_state, current_log_pdf):
# Start the loop over nsamples - this code uses the parallel version of the stretch algorithm
all_inds = np.arange(self.nchains)
inds = all_inds % 2
accept_vec = np.zeros((self.nchains, ))
# Separate the full ensemble i... | Python | nomic_cornstack_python_v1 |
function export_model_to_pb model_name_or_path export_path inputs outputs
begin
set gpu_config = call ConfigProto
set allow_growth = true
set sess = call Session config=gpu_config
set saver = call Saver
if is directory path model_name_or_path
begin
set ckpt_file = call latest_checkpoint model_name_or_path
if ckpt_file ... | def export_model_to_pb(model_name_or_path, export_path,
inputs: dict, outputs: dict):
gpu_config = tf.ConfigProto()
gpu_config.gpu_options.allow_growth = True
sess = tf.Session(config=gpu_config)
saver = tf.train.Saver()
if os.path.isdir(model_name_or_path):
ckpt_file... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
string Created on Wed Nov 14 06:27:57 2018 @author: Charan
import pandas as pd
set transactions = call DataFrame
set customerProfile = call DataFrame
function inititalizeTransaction_df
begin
global transactions
print string Initalizing the Kitty Bank
set dict2 = dict string Custid list 101... | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 14 06:27:57 2018
@author: Charan
"""
import pandas as pd
transactions = pd.DataFrame()
customerProfile = pd.DataFrame()
def inititalizeTransaction_df():
global transactions
print('Initalizing the Kitty Bank')
dict2 = {'Custid':[101,102,103,10... | Python | zaydzuhri_stack_edu_python |
set white = string #FFFFFF
set nordred = string #BF616A
set nordorange = string #D08770
set nordyellow = string #EBCB8B
set nordgreen = string #A3BE8C
set nordmagenta = string #B48EAD
set darkblack = string #2e3440
set nordblack = string #3b4252
set mediumblack = string #434c5e
set brightblack = string #4c566a
set nord... | white = '#FFFFFF'
nordred = '#BF616A'
nordorange = '#D08770'
nordyellow = '#EBCB8B'
nordgreen = '#A3BE8C'
nordmagenta = '#B48EAD'
darkblack = '#2e3440'
nordblack = '#3b4252'
mediumblack = '#434c5e'
brightblack = '#4c566a'
nordwhite = '#d8dee9'
brigherwhite = '#e5e9f0'
brightestwhite = '#eceff4'
nordcyan = '#8fbcbb... | Python | zaydzuhri_stack_edu_python |
function post_on_hastebin content
begin
set post = post string https://hastebin.com/documents data=encode content
return string string https://hastebin.com/ + json post at string key
end function | def post_on_hastebin(content: str) -> str:
post = requests.post("https://hastebin.com/documents", data=content.encode())
return str("https://hastebin.com/" + post.json()["key"]) | Python | nomic_cornstack_python_v1 |
function __init__ self master loop=none
begin
if loop is none
begin
set loop = call get_event_loop
end
set loop = loop
set master = master
comment Dict with sockets as keys and boolean indicating mute as values
set all_sockets = dict
set commands = dict string help send_help ; string raw enable_raw ; string unraw disa... | def __init__(self, master, loop=None):
if loop is None:
loop = asyncio.get_event_loop()
self.loop = loop
self.master = master
# Dict with sockets as keys and boolean indicating mute as values
self.all_sockets = {}
self.commands = {
'help': self.s... | Python | nomic_cornstack_python_v1 |
function send self destiny subject context send_image=false img=string
begin
try
begin
if length server > 1
begin
set server = server at 1
end
if length server == 0
begin
set server = server at 0
end
if send_image
begin
set img_data = read open img string rb
set message = call MIMEMultipart
set message at string subjec... | def send(self, destiny, subject, context, send_image=False, img=""):
try:
if len(self.server) > 1:
server = self.server[1]
if len(self.server) == 0:
server = self.server[0]
if send_image:
img_data = open(img, 'rb').read()
... | Python | nomic_cornstack_python_v1 |
function build_ibb_graph_from ea_source sourcenode reachgraph
begin
set flowgraph = call create_flowgraph_from 4465616
call add_disasm_lines_to_flowgraph flowgraph
call write_VCG_File string C:\test.vcg
end function | def build_ibb_graph_from( ea_source, sourcenode, reachgraph ):
flowgraph = create_flowgraph_from( 0x4423D0 )
add_disasm_lines_to_flowgraph( flowgraph )
flowgraph.write_VCG_File("C:\\test.vcg") | Python | nomic_cornstack_python_v1 |
function fight self opponent
begin
if health - call getDamage > 0
begin
set health = health - call getDamage
print string attack failed. Remaining Health: health
return false
end
else
begin
print string successful attack
return true
end
end function | def fight(self, opponent):
if(self.health - opponent.getDamage() > 0):
self.health -= opponent.getDamage()
print("attack failed. Remaining Health: ", self.health)
return False
else:
print("successful attack")
return True | Python | nomic_cornstack_python_v1 |
comment !/usr/bin/env python
comment -*- coding: utf-8 -*-
comment @Date : 2020-03-15 06:41:38
comment @Author : mutudeh (josephmathone@gmail.com)
comment @Link : ${link}
comment @Version : $Id$
import os
class Solution extends object
begin
function findRadius self houses heaters
begin
string :type houses: List[int] :t... | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date : 2020-03-15 06:41:38
# @Author : mutudeh (josephmathone@gmail.com)
# @Link : ${link}
# @Version : $Id$
import os
class Solution(object):
def findRadius(self, houses, heaters):
"""
:type houses: List[int]
:type heaters: List[int]
... | Python | zaydzuhri_stack_edu_python |
function run_call self expanded unexpanded
begin
if not expanded
begin
return call errormessage string Needs an object id to call
end
comment Michel@DC: you should factor the object out of this eval and
comment validate it with
comment SecurityManager.checkPermission('View', object).
comment Also, 'eval' without an nam... | def run_call(self, expanded, unexpanded) :
if not expanded :
return self.errormessage("Needs an object id to call")
# Michel@DC: you should factor the object out of this eval and
# validate it with
# SecurityManager.checkPermission('View', object).
# Also, 'eval' without an namespace qualifying 'in'
... | Python | nomic_cornstack_python_v1 |
comment !/usr/bin/env python3
from typing import List
import numpy as np
from estimator.models.data_container_base import DataContainer
from estimator.models.gaussian_noise import GaussianNoiseModel
from estimator.models.line import LineModel
class RecordedData extends DataContainer
begin
function __init__ self noise s... | #!/usr/bin/env python3
from typing import List
import numpy as np
from estimator.models.data_container_base import DataContainer
from estimator.models.gaussian_noise import GaussianNoiseModel
from estimator.models.line import LineModel
class RecordedData(DataContainer):
def __init__(self, noise: GaussianNoiseMo... | Python | zaydzuhri_stack_edu_python |
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