code stringlengths 10 2.58M | original_code stringlengths 3 3.18M | original_language stringclasses 1
value | source stringclasses 7
values |
|---|---|---|---|
comment -*- coding: utf-8 -*-
string Created on Wed May 26 20:23:22 2021 @author: calle Alejandro Calderon will work on this script
import pandas as pd
import time
comment Read tables as dataframes
comment file = os.path.join("..", "data", "Data Model Generated Network-13.xlsm")
function read_data_rfep folder_path dict... | # -*- coding: utf-8 -*-
"""
Created on Wed May 26 20:23:22 2021
@author: calle
Alejandro Calderon will work on this script
"""
import pandas as pd
import time
#Read tables as dataframes
#file = os.path.join("..", "data", "Data Model Generated Network-13.xlsm")
def read_data_rfep(folder_path, dict_tables_name, is_to_g... | Python | zaydzuhri_stack_edu_python |
function evaluate_model model X_test Y_test label_names
begin
set Y_pred = predict model X_test
comment Calculate classification report
set metrics = call classification_report Y_test Y_pred target_names=label_names output_dict=true
comment Create dataframe, tanspose it
set metrics_df = T
print metrics_df
end function | def evaluate_model(model, X_test, Y_test, label_names):
Y_pred = model.predict(X_test)
# Calculate classification report
metrics = classification_report(
Y_test, Y_pred,
target_names=label_names,
output_dict=True,
)
# Create data... | Python | nomic_cornstack_python_v1 |
function remove self idxs
begin
import utool as ut
set keep_idxs = call index_complement idxs length self
return call take keep_idxs
end function | def remove(self, idxs):
import utool as ut
keep_idxs = ut.index_complement(idxs, len(self))
return self.take(keep_idxs) | Python | nomic_cornstack_python_v1 |
set list = list 1 6 2 8 4 9
set max_index = index list max list
comment Output: 4
print max_index | list = [1, 6, 2, 8, 4, 9]
max_index = list.index(max(list))
print(max_index) # Output: 4
| Python | flytech_python_25k |
string AUTHOR: Micah Braun PROJECT NAME: test_run.py (for waterregulation modules) DATE CREATED: 10/19/2018 LAST-UPDATED: 10/29/2018 PURPOSE: Lesson 6 DESCRIPTION: Unittests for Pump, Sensor, Controller, and Decider classes and their modules to check for proper functionality.
import unittest
from unittest.mock import M... | """
AUTHOR: Micah Braun
PROJECT NAME: test_run.py (for waterregulation modules)
DATE CREATED: 10/19/2018
LAST-UPDATED: 10/29/2018
PURPOSE: Lesson 6
DESCRIPTION: Unittests for Pump, Sensor, Controller,
and Decider classes and their modules to check for
proper functionality.
"""
import unittest
from unittest.mock import ... | Python | zaydzuhri_stack_edu_python |
string Starter code for logistic regression model to solve OCR task with MNIST in TensorFlow MNIST dataset: yann.lecun.com/exdb/mnist/
import os
set environ at string TF_CPP_MIN_LOG_LEVEL = string 2
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
import time
comment... | """
Starter code for logistic regression model to solve OCR task
with MNIST in TensorFlow
MNIST dataset: yann.lecun.com/exdb/mnist/
"""
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
import time
# Def... | Python | zaydzuhri_stack_edu_python |
import numpy as np
from scipy.spatial.distance import pdist
string 马氏距离python实现
function mashi_distance_by_python x y
begin
string 纯python实现
comment 马氏距离要求样本数要大于维数，否则无法求协方差矩阵
comment 此处进行转置，表示10个样本，每个样本2维
set X = vertical stack list x y
set XT = T
comment 两个维度之间协方差矩阵
set S = call cov X
comment 协方差矩阵的逆矩阵
set SI = call i... | import numpy as np
from scipy.spatial.distance import pdist
"""
马氏距离python实现
"""
def mashi_distance_by_python(x, y):
"""
纯python实现
"""
# 马氏距离要求样本数要大于维数，否则无法求协方差矩阵
# 此处进行转置，表示10个样本，每个样本2维
X = np.vstack([x, y])
XT = X.T
S = np.cov(X) # 两个维度之间协方差矩阵
SI = np.linalg.inv(S) # 协方差矩阵的逆矩阵... | Python | zaydzuhri_stack_edu_python |
function bool2int x
begin
set y = 0
for tuple i j in enumerate x
begin
set y = y + j ? i
end
return y
end function | def bool2int(x):
y = 0
for i,j in enumerate(x):
y += j<<i
return y | Python | nomic_cornstack_python_v1 |
from django.db import models
comment Create your models here.
string Documentation for this module: This module of django contains all tables of the databse .
class user extends Model
begin
string user data of the people interacting with the bot
set mobile = call CharField max_length=250 default=string NULL
set fbid = ... | from django.db import models
# Create your models here.
"""
Documentation for this module:
This module of django contains all tables of the databse .
"""
class user(models.Model):
"""user data of the people interacting with the bot """
mobile = models.CharField(max_length = 250 , default = 'NULL')
fbi... | Python | zaydzuhri_stack_edu_python |
function striding_windows arr batch_num=200
begin
set batches = list
for di in range length arr - batch_num + 1
begin
set window = arr at slice di : di + batch_num :
print di window
append batches window
end
return array batches
end function | def striding_windows(arr: list, batch_num=200) -> np.array:
batches = []
for di in range(len(arr) - batch_num + 1):
window = arr[di:di + batch_num]
print(di, window)
batches.append(window)
return np.array(batches) | Python | nomic_cornstack_python_v1 |
comment Helper for some tests
import sys
import fileinput
from insurance import Data
set dataset = data
load dataset stdin
comment Find customers that chose a weirdo product
set n = 0
for customer in values customers
begin
if not did_choose_browsed_plan
begin
print customer_id
set n = n + 1
end
end
print
print string %... | # Helper for some tests
import sys
import fileinput
from insurance import Data
dataset = Data()
dataset.load(sys.stdin)
# Find customers that chose a weirdo product
n = 0
for customer in dataset.customers.values():
if not customer.did_choose_browsed_plan:
print(customer.customer_id)
n += 1
print()
print("%d... | Python | zaydzuhri_stack_edu_python |
string This program mediates between the AI instructions and the game itself through stdin and stdout
import sys
import subprocess
class Manager
begin
set ai = string
set game_name = string
set best = 0
function __init__ self game ai gens=50
begin
set gens = gens
set game_name = game
end function
function openAI self... | """
This program mediates between the AI instructions and the game itself through stdin and stdout
"""
import sys
import subprocess
class Manager:
ai = ""
game_name = ""
best = 0
def __init__(self, game, ai, gens=50):
self.gens = gens
self.game_name = game
def openAI(self):
... | Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/env python3
from tkinter.filedialog import asksaveasfilename
from tkinter.filedialog import askopenfilename
from tkinter import *
import alsaaudio , wave , threading
class PiAudio extends Tk
begin
function __init__ self
begin
call __init__ self
set nom_carte = string sysdefault:CARD=U0x46d0x825
set fi... | #!/usr/bin/env python3
from tkinter.filedialog import asksaveasfilename
from tkinter.filedialog import askopenfilename
from tkinter import *
import alsaaudio, wave, threading
class PiAudio(Tk):
def __init__(self):
Tk.__init__(self)
self.nom_carte = 'sysdefault:CARD=U0x46d0x825'
self.fichier... | Python | zaydzuhri_stack_edu_python |
from tweepy import Stream
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
import socket
import sys
import json
comment Twitter consumer key, consumer secret, access token, access secret
set ACCESS_TOKEN = string 741468980-hirgAI1iuJr8RyLlWS4zX86YsFVTsvnH84cNw4ND
set ACCESS_SECRET = string Fc... | from tweepy import Stream
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
import socket
import sys
import json
# Twitter consumer key, consumer secret, access token, access secret
ACCESS_TOKEN = '741468980-hirgAI1iuJr8RyLlWS4zX86YsFVTsvnH84cNw4ND'
ACCESS_SECRET = 'FcUyRls8TBRQkloHTiWMqxzt1... | Python | zaydzuhri_stack_edu_python |
comment CS B551 Fall 2017, Assignment #3
comment (Based on skeleton code by D. Crandall)
string Title: To find POS tags of every word of a given sentence using hidden Markov model. We have implemented this using three techniques viz. a. Simple Naive Bayes Algorithm b. Variable Elimination (Forward-Backward algorithm) c... | ###################################
# CS B551 Fall 2017, Assignment #3
#
#
# (Based on skeleton code by D. Crandall)
#
#
####
"""
Title: To find POS tags of every word of a given sentence using hidden Markov model.
We have implemented this using three techniques viz.
a. Simple Naive Bayes Algorithm
b. Variable Elimin... | Python | zaydzuhri_stack_edu_python |
set tuple m n = split input
set tuple m n = tuple integer m integer n
set m = m ? n
set n = m ? n
set m = m ? n
print m n | m,n=input().split()
m,n=int(m),int(n)
m=m^n
n=m^n
m=m^n
print(m,n)
| Python | zaydzuhri_stack_edu_python |
class MaxStack
begin
function __init__ self
begin
set __stack = list
end function
function push self x
begin
append __stack x
end function
function pop self
begin
if length __stack != 0
begin
pop __stack
end
end function
function getMax self
begin
if length __stack == 0
begin
return - 1
end
return max __stack
end func... | class MaxStack:
def __init__(self):
self.__stack=[]
def push(self, x: int):
self.__stack.append(x)
def pop(self) -> None:
if len(self.__stack)!=0:
self.__stack.pop()
def getMax(self):
if len(self.__stack)==0:
return -1
... | Python | zaydzuhri_stack_edu_python |
import tensorflow as tf
function dice_loss prediction label class_num
begin
comment softmax processing
set softmax_prediction = softmax logits=prediction
set ground_truth = call one_hot indices=label depth=class_num
set loss = 0
comment unique = len(tf.unique(label))
for i in range class_num
begin
set i_prediction = so... | import tensorflow as tf
def dice_loss(prediction, label, class_num):
# softmax processing
softmax_prediction = tf.nn.softmax(logits=prediction)
ground_truth = tf.one_hot(indices=label, depth=class_num)
loss = 0
# unique = len(tf.unique(label))
for i in range(class_num):
i_prediction = ... | Python | zaydzuhri_stack_edu_python |
from queue import PriorityQueue as pq
from copy import deepcopy
class Node
begin
function __init__ self mat move height parent=none
begin
set mat = mat
set move = move
set parent = parent
set height = height
end function
comment makes nodes comparable
function __lt__ self other
begin
return 0
end function
function zero... | from queue import PriorityQueue as pq
from copy import deepcopy
class Node():
def __init__(self, mat, move,height,parent=None):
self.mat = mat
self.move = move
self.parent = parent
self.height=height
def __lt__(self,other): #makes nodes comparable
return 0
de... | Python | zaydzuhri_stack_edu_python |
import unittest
from model.model import to_uppercase
from unittest import TestCase
class ModelTest extends TestCase
begin
function test_uppercase self
begin
assert equal call to_uppercase string abc string ABC
end function
end class
if __name__ == string __main__
begin
call main
end | import unittest
from ..model.model import to_uppercase
from unittest import TestCase
class ModelTest(TestCase):
def test_uppercase(self):
self.assertEqual(to_uppercase('abc'), 'ABC')
if __name__ == '__main__':
unittest.main()
| Python | zaydzuhri_stack_edu_python |
function has_negatives a
begin
string YOUR CODE HERE
comment Dictionary for values
set vals = dict
comment Iterate through numbers in a
for num in a
begin
comment Check if the absolute value of num is in vals
if absolute num in vals
begin
comment Increment the value associated with abs(a)
set vals at absolute num = va... | def has_negatives(a):
"""
YOUR CODE HERE
"""
# Dictionary for values
vals = {}
# Iterate through numbers in a
for num in a:
# Check if the absolute value of num is in vals
if abs(num) in vals:
# Increment the value associated with abs(a)
vals[abs(num)... | Python | zaydzuhri_stack_edu_python |
import numpy as np
from numpy import array
from keras.models import Sequential , Model
from keras.layers import Dense , LSTM , Input
function split_sequence sequence n_steps
begin
set tuple x y = tuple list list
comment 10
for i in range length sequence
begin
comment 0+4=4/// 6+4
set end_ix = i + n_steps
if end_ix > le... | import numpy as np
from numpy import array
from keras.models import Sequential,Model
from keras.layers import Dense, LSTM, Input
def split_sequence(sequence, n_steps):
x,y = list(), list()
for i in range(len(sequence)): #10
end_ix = i + n_steps #0+4=4/// 6+4
if end_ix > len(sequence)-1... | Python | zaydzuhri_stack_edu_python |
import torch
import torch.nn as nn
import torch.nn.functional as F
class LSTMNet extends Module
begin
string model built with 2 lstm layers
function __init__ self params device
begin
call __init__
comment ! https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM
comment initilize h0, c0 (num_layers * num_directions, batc... | import torch
import torch.nn as nn
import torch.nn.functional as F
class LSTMNet(nn.Module):
"""
model built with 2 lstm layers
"""
def __init__(self, params, device):
super(LSTMNet, self).__init__()
#! https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM
# initilize h0, c... | Python | zaydzuhri_stack_edu_python |
function test_reset_channel backend
begin
set original_backend = call get_backend
call set_backend backend
set initial_rho = call random_density_matrix 3
set c = call Circuit 3 density_matrix=true
add c call ResetChannel 0 p0=0.2 p1=0.2
set final_rho = call c copy np initial_rho
set dtype = dtype
set collapsed_rho = re... | def test_reset_channel(backend):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_rho = utils.random_density_matrix(3)
c = models.Circuit(3, density_matrix=True)
c.add(gates.ResetChannel(0, p0=0.2, p1=0.2))
final_rho = c(np.copy(initial_rho))
dtype = initial_r... | Python | nomic_cornstack_python_v1 |
from gsapi import *
from gsapi.MathUtils import PatternMarkov
import random
import copy
import logging
set markovLog = call getLogger string gsapi.GSStyle.GSMarkovStyle
class GSMarkovStyle extends GSStyle
begin
string compute sa style based on markov chains Args: order: order used for markov computation numSteps: numbe... | from gsapi import *
from gsapi.MathUtils import PatternMarkov
import random
import copy
import logging
markovLog = logging.getLogger('gsapi.GSStyle.GSMarkovStyle')
class GSMarkovStyle(GSStyle):
""" compute sa style based on markov chains
Args:
order: order used for markov computation
numSteps: number of steps... | Python | zaydzuhri_stack_edu_python |
function recreatedb
begin
call drop_all
call create_all
end function | def recreatedb():
db.drop_all()
db.create_all() | Python | nomic_cornstack_python_v1 |
function delete_asset self asset_id asset_type
begin
return call asset asset_id asset_type=asset_type action=string DELETE
end function | def delete_asset(self, asset_id, asset_type):
return self.asset(asset_id, asset_type=asset_type, action='DELETE') | Python | nomic_cornstack_python_v1 |
function send_email date result
begin
set message = call MIMEMultipart string alternative none list call MIMEText result string html
set message at string Subject = string net_syslog for { date }
set message at string From = FROM
set message at string To = TO
with call SMTP SERVER as server
begin
call sendmail FROM TO ... | def send_email(date, result):
message = MIMEMultipart("alternative", None, [MIMEText(result, 'html')])
message['Subject'] = f"net_syslog for {date}"
message['From'] = FROM
message['To'] = TO
with smtplib.SMTP(SERVER) as server:
server.sendmail(FROM, TO, message.as_string()) | Python | nomic_cornstack_python_v1 |
from datetime import datetime
set d = input
set a = string parse time d string %dth %b %Y
print strip string a string 00:00:00 | from datetime import datetime
d=input()
a=datetime.strptime(d,"%dth %b %Y")
print(str(a).strip('00:00:00')) | Python | zaydzuhri_stack_edu_python |
import unittest
from transparencia_api.crawler.remuneracao_camara.remuneracao_camara_model import RemuneracaoCamaraModel
class RemuneracaoCamaraModelTest extends TestCase
begin
function setUp self
begin
set remuneracaoModel = call RemuneracaoCamaraModel
set dado = list string ABEL YOSHINOBU TAIRA string ANALISTA TEC.LE... | import unittest
from transparencia_api.crawler.remuneracao_camara.remuneracao_camara_model import RemuneracaoCamaraModel
class RemuneracaoCamaraModelTest(unittest.TestCase):
def setUp(self):
self.remuneracaoModel = RemuneracaoCamaraModel()
self.dado = ["ABEL YOSHINOBU TAIRA", "ANALISTA TEC.LEG-DE... | Python | zaydzuhri_stack_edu_python |
function get_function_path_and_options function
begin
comment Try to pop the options off whatever they passed in.
set options = get attribute function string _async_options none
return tuple call reference_to_path function options
end function | def get_function_path_and_options(function):
# Try to pop the options off whatever they passed in.
options = getattr(function, '_async_options', None)
return reference_to_path(function), options | Python | nomic_cornstack_python_v1 |
from bs4 import BeautifulSoup
import requests
function get_repos uri
begin
set r = get requests uri
set soup = call BeautifulSoup text string html.parser
set table = table
for row in find all table string tr at slice 1 : :
begin
set column = find all row string td at 0
yield string %s%s % tuple uri a at string href
e... | from bs4 import BeautifulSoup
import requests
def get_repos(uri):
r = requests.get(uri)
soup = BeautifulSoup(r.text, "html.parser")
table = soup.table
for row in table.find_all('tr')[1:]:
column = row.find_all('td')[0]
yield "%s%s" % (uri, column.a['href'])
| Python | zaydzuhri_stack_edu_python |
function delete_all_refresh_tokens self user_id
begin
set keys = keys redis_db string * { user_id } *
if keys
begin
delete *keys
end
end function | def delete_all_refresh_tokens(self, user_id: str):
keys = redis_db.keys(f"*{user_id}*")
if keys:
redis_db.delete(*keys) | Python | nomic_cornstack_python_v1 |
function find_max_consecutive_vowels s max_count=0 max_substrings=list count=0 substring=string
begin
if s == string
begin
if count > max_count
begin
set max_count = count
set max_substrings = list substring
end
else
if count == max_count and count > 0
begin
append max_substrings substring
end
return tuple max_count ... | def find_max_consecutive_vowels(s, max_count=0, max_substrings=[], count=0, substring=""):
if s == "":
if count > max_count:
max_count = count
max_substrings = [substring]
elif count == max_count and count > 0:
max_substrings.append(substring)
return max_c... | Python | greatdarklord_python_dataset |
import datetime
function print_human_readable_date
begin
set days = list string Monday string Tuesday string Wednesday string Thursday string Friday string Saturday string Sunday
set months = list string January string February string March string April string May string June string July string August string September ... | import datetime
def print_human_readable_date():
days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']
today = datetime.date.today()
... | Python | jtatman_500k |
import pandas as pd , numpy as np , copy
from sklearn.feature_selection import SelectKBest , f_classif
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split , GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.ensemble import RandomForestClassifier
from sklearn... | import pandas as pd, numpy as np, copy
from sklearn.feature_selection import SelectKBest, f_classif
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.ensemble import RandomForestClassifier
from sklearn imp... | Python | zaydzuhri_stack_edu_python |
function make_plots self indices=none hardcopy=false hardcopydir=string . hardcopyprefix=string hardcopytype=string png
begin
for tuple i E in enumerate experiments
begin
if indices == none or i in indices
begin
call show_plot hardcopy hardcopydir hardcopyprefix hardcopytype
end
end
end function | def make_plots(self,indices=None,hardcopy=False,hardcopydir='.',hardcopyprefix='',hardcopytype='png'):
for (i,E) in enumerate(self.experiments):
if(indices==None) or (i in indices):
E.show_plot(hardcopy,hardcopydir,hardcopyprefix,hardcopytype) | Python | nomic_cornstack_python_v1 |
set protein1 = string msrslllrfllfllllpplp
set protein2 = string MSRSLLLRFLLFLLLLPPLP
set protein3 = string MSRSLLLRFLLFLLLLPPLP
set list1 = list string L | protein1 = "msrslllrfllfllllpplp"
protein2 = "MSRSLLLRFLLFLLLLPPLP"
protein3 = "MSRSLLLRFLLFLLLLPPLP"
list1=["L"]
| Python | zaydzuhri_stack_edu_python |
comment contoh penggunaan modul getpass
import getpass
set password = call getpass | # contoh penggunaan modul getpass
import getpass
password = getpass.getpass() | Python | zaydzuhri_stack_edu_python |
function assays self
begin
return _assay_queryset
end function | def assays(self):
return self._assay_queryset | Python | nomic_cornstack_python_v1 |
string Replay each URL on a list through the replay proxy, and gather results.
import argparse
import threading
import time
from pyvirtualdisplay import Display
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.common.exceptions import UnexpectedAlertPresentException
f... | """Replay each URL on a list through the replay proxy, and gather results."""
import argparse
import threading
import time
from pyvirtualdisplay import Display
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.common.exceptions import UnexpectedAlertPresentException
... | Python | zaydzuhri_stack_edu_python |
function serialize self writer
begin
if not writer
begin
raise call TypeError string writer cannot be null.
end
call serialize writer
call write_object_value string emailSettings email_settings
call write_int_value string workflowScheduleIntervalInHours workflow_schedule_interval_in_hours
end function | def serialize(self,writer: SerializationWriter) -> None:
if not writer:
raise TypeError("writer cannot be null.")
super().serialize(writer)
writer.write_object_value("emailSettings", self.email_settings)
writer.write_int_value("workflowScheduleIntervalInHours", self.workflow_... | Python | nomic_cornstack_python_v1 |
function IPban message
begin
if lower call GetArg 0 == string list
begin
if not ipbans
begin
call Reply string Nobody is currently IP banned
end
else
begin
call Reply string List of currently banned IPs: + join string , ipbans
end
end
else
if call GetArg 1
begin
set action = lower call GetArg 0
if action == string remo... | def IPban(message):
if message.GetArg(0).lower() == "list":
if not ipbans:
message.Reply("Nobody is currently IP banned")
else:
message.Reply("List of currently banned IPs: " + ", ".join(ipbans))
elif message.GetArg(1):
action = message.GetArg(0).lower()
if action == "remove":
ipbans.discard(message.... | Python | nomic_cornstack_python_v1 |
function get_bullet self paragraph
begin
try
begin
set pPr = next call iterfind call qn string w:pPr
set numPr = next call iterfind call qn string w:numPr
set numId = attrib at call qn string w:val
set ilvl = attrib at call qn string w:val
try
begin
set numFmt = numId2numFmts at string numId at integer ilvl
end
except ... | def get_bullet(self, paragraph: EtreeElement) -> str:
try:
pPr = next(paragraph.iterfind(qn("w:pPr")))
numPr = next(pPr.iterfind(qn("w:numPr")))
numId = next(numPr.iterfind(qn("w:numId"))).attrib[qn("w:val")]
ilvl = next(numPr.iterfind(qn("w:ilvl"))).attrib[qn("w:... | Python | nomic_cornstack_python_v1 |
function scatter self *args **kwargs
begin
set cls = call _make_class ScatterVisual _default_marker=pop kwargs string marker none
return call _add_item cls *args keyword kwargs
end function | def scatter(self, *args, **kwargs):
cls = _make_class(ScatterVisual,
_default_marker=kwargs.pop('marker', None),
)
return self._add_item(cls, *args, **kwargs) | Python | nomic_cornstack_python_v1 |
function fix_bulkrename self
begin
set bulkrename_cls = call get_command string bulkrename
if not bulkrename_cls
begin
return
end
set editor = call getenv string EDITOR
if not editor
begin
set editor = string nvim
end
set code = call dedent get source execute
set code = replace code string def execute string def bulkre... | def fix_bulkrename(self):
bulkrename_cls = self.commands.get_command('bulkrename')
if not bulkrename_cls:
return
editor = os.getenv('EDITOR')
if not editor:
editor = 'nvim'
code = textwrap.dedent(inspect.getsource(bulkrename_cls.execute))
code = ... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
string Created on Wed Sep 26 21:49:19 2018 @author: Rafiya
import numpy as np
import scipy as sp
comment one option for a 2D convolution library
import scipy.signal
import cv2
import matplotlib.pyplot as plt
from os import path
import seam_carving as sc
comment img = cv2.imread("sample_ima... | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 26 21:49:19 2018
@author: Rafiya
"""
import numpy as np
import scipy as sp
import scipy.signal # one option for a 2D convolution library
import cv2
import matplotlib.pyplot as plt
from os import path
import seam_carving as sc
### img = cv2.imread("sample_image.png",... | Python | zaydzuhri_stack_edu_python |
function rget dict_object path_list
begin
try
begin
return reduce lambda d k -> d at k path_list dict_object
end
except KeyError
begin
return dict_object
end
end function | def rget(dict_object, path_list):
try:
return reduce(lambda d, k: d[k], path_list, dict_object)
except KeyError:
return dict_object | Python | nomic_cornstack_python_v1 |
string 개요: continue문 작성자: 진상영 작성일: 2021.03.22 내용: continue문은 반복문의 시작 지점으로 제어의 흐름 변경 - while문 : 조건식 이동 실행 - for문 : 반복가능객체 이동 나머지 실행
comment fruits = ['사과', '감귤']
comment count = 3
comment while count > 0:
comment fruit = input('어떤 과일을 저장할까요?>>> ')
comment if fruit in fruits:
comment print('동일한 과일이 있습니다.')
comment contin... | '''
개요: continue문
작성자: 진상영
작성일: 2021.03.22
내용: continue문은 반복문의 시작 지점으로 제어의 흐름 변경
- while문 : 조건식 이동 실행
- for문 : 반복가능객체 이동 나머지 실행
'''
# fruits = ['사과', '감귤']
# count = 3
#
# while count > 0:
# fruit = input('어떤 과일을 저장할까요?>>> ')
# if fruit in fruits:
# print('동일한 과일이 있습니다.')
# continue
# fruit... | Python | zaydzuhri_stack_edu_python |
for i in range integer input
begin
set n = integer input
set l = list map int split input
while length l != 2
begin
set r = sorted l
remove l r at 1
remove r r at 1
end
print string l at 0 + string + string l at 1
end | for i in range(int(input())):
n = int(input())
l = list(map(int,input().split()))
while len(l) != 2:
r = sorted(l)
l.remove(r[1])
r.remove(r[1])
print(str(l[0]) + " " + str(l[1]))
| Python | zaydzuhri_stack_edu_python |
import re
set text = string Hello, my cell is (770) 555-1234
set phoneNumRegex = compile string (\(\d\d\d\)) (\d\d\d-\d\d\d\d)
set match = search text
print match
print call group 0
print call group 1
print call group 2
print call group | import re
text = "Hello, my cell is (770) 555-1234"
phoneNumRegex = re.compile(r'(\(\d\d\d\)) (\d\d\d-\d\d\d\d)')
match = phoneNumRegex.search(text)
print(match)
print(match.group(0))
print(match.group(1))
print(match.group(2))
print(match.group())
| Python | zaydzuhri_stack_edu_python |
function SqueezeNet include_top=true input_shape=none weights=string imagenet input_tensor=none pooling=none classes=1000 **kwargs
begin
if weights not in set literal string imagenet none
begin
raise call ValueError string The `weights` argument should be either `None` (random initialization) or `imagenet` (pre-trainin... | def SqueezeNet(include_top=True,
input_shape=None,
weights='imagenet',
input_tensor=None,
pooling=None,
classes=1000,
**kwargs):
if weights not in {'imagenet', None}:
raise ValueError('The `weights` argument should be... | Python | nomic_cornstack_python_v1 |
function get_param_groups core selection=string kep
begin
if selection == string all
begin
set selection = string kep_binary_gr_pm_spin_pos_noise_dm_chrom_dmx_fd
end
set kep_pars = list string PB string PBDOT string T0 string A1 string OM string E string ECC string EPS1 string EPS2 string EPS1DOT string EPS2DOT string ... | def get_param_groups(core, selection="kep"):
if selection == "all":
selection = "kep_binary_gr_pm_spin_pos_noise_dm_chrom_dmx_fd"
kep_pars = [
"PB",
"PBDOT",
"T0",
"A1",
"OM",
"E",
"ECC",
"EPS1",
"EPS2",
"EPS1DOT",
"... | Python | nomic_cornstack_python_v1 |
function typecheck values nans=list
begin
set types = list
for v in values
begin
if v == none
begin
append types TYPE_EMPTY
end
else
begin
try
begin
set test = integer v
append types TYPE_INTEGER
end
except any
begin
try
begin
set test = decimal lower v
append types TYPE_FLOAT
end
except any
begin
append types TYPE_ST... | def typecheck(values, nans=[]):
types = []
for v in values:
if v == None:
types.append(TYPE_EMPTY)
else:
try:
test = int(v)
types.append(TYPE_INTEGER)
except:
try:
test = float(v.lower())
... | Python | nomic_cornstack_python_v1 |
string Save models to saved_models folder
function save_model model model_name
begin
set model_json = to json model
with open string saved_models\ + model_name + string .json string w as json_file
begin
write json_file model_json
end
comment serialize weights to HDF5
call save_weights string saved_models\ + model_name ... | """
Save models to saved_models folder
"""
def save_model(model, model_name):
model_json = model.to_json()
with open("saved_models\\" + model_name + ".json", "w") as json_file:
json_file.write(model_json)
# serialize weights to HDF5
model.save_weights("saved_models\\" + model_name+ ".h5")
pr... | Python | zaydzuhri_stack_edu_python |
import pandas as pd
import numpy as np
from datetime import datetime
import pytz
from math import ceil
import matplotlib.pyplot as plt
from matplotlib import cm
import seaborn as sns
call set_style string white
function get_data_from_csv
begin
return read csv string ../data/USvideos.csv
end function
function delete_dup... | import pandas as pd
import numpy as np
from datetime import datetime
import pytz
from math import ceil
import matplotlib.pyplot as plt
from matplotlib import cm
import seaborn as sns
sns.set_style("white")
def get_data_from_csv():
return pd.read_csv("../data/USvideos.csv")
def delete_duplicates(df):
df = ... | Python | zaydzuhri_stack_edu_python |
function cast obj
begin
return call itkAdaptiveHistogramEqualizationImageFilterISS2_cast obj
end function | def cast(obj: 'itkLightObject') -> "itkAdaptiveHistogramEqualizationImageFilterISS2 *":
return _itkAdaptiveHistogramEqualizationImageFilterPython.itkAdaptiveHistogramEqualizationImageFilterISS2_cast(obj) | Python | nomic_cornstack_python_v1 |
import math
import torch
from torch.nn import functional as F
from networks import eta_to_gamma , get_eta_scale
function unsqueeze_x_as_y x y
begin
if ndim == ndim
begin
return x
end
assert size x 0 == size y 0
return view x - 1 *[1] * (y.ndim - 1)
end function
class GaussianDiffusion
begin
function __init__ self num_t... | import math
import torch
from torch.nn import functional as F
from networks import eta_to_gamma, get_eta_scale
def unsqueeze_x_as_y(x, y):
if x.ndim == y.ndim:
return x
assert x.size(0) == y.size(0)
return x.view(-1, *([1, ] * (y.ndim-1)) )
class GaussianDiffusion:
def __init__(
sel... | Python | zaydzuhri_stack_edu_python |
comment bot.py
import os
import datetime
comment from datetime import datetime
import discord
from dotenv import load_dotenv
from discord.ext import commands
import json
import asyncio
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from... | # bot.py
import os
import datetime
#from datetime import datetime
import discord
from dotenv import load_dotenv
from discord.ext import commands
import json
import asyncio
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.web... | Python | zaydzuhri_stack_edu_python |
comment -*- coding=UTF-8 -*-
string author:hamioo date:2018/1/23 describle:循环遍历 describle:循环遍历
for i in range 1 20 3
begin
if i == 16
begin
break
end
end | # -*- coding=UTF-8 -*-
"""
author:hamioo
date:2018/1/23
describle:循环遍历
describle:循环遍历
"""
for i in range(1, 20, 3):
if i== 16:
break | Python | zaydzuhri_stack_edu_python |
function analyze_build_main bin_dir from_build_command
begin
set parser = call create_parser from_build_command
set args = call parse_args
call validate parser args from_build_command
comment setup logging
call initialize_logging verbose
debug string Parsed arguments: %s args
with call report_directory output keep_empt... | def analyze_build_main(bin_dir, from_build_command):
parser = create_parser(from_build_command)
args = parser.parse_args()
validate(parser, args, from_build_command)
# setup logging
initialize_logging(args.verbose)
logging.debug('Parsed arguments: %s', args)
with report_directory(args.out... | Python | nomic_cornstack_python_v1 |
comment 주어진 튜플 (1,2,3,4,5,6,7,8,9,10)의 앞 항목 절반과 뒤 항목 절반을 출력하는 프로그램을 작성하십시오.
set tu = tuple 1 2 3 4 5 6 7 8 9 10
print tu at slice 0 : 5 :
print tu at slice 5 : 11 : | # 주어진 튜플 (1,2,3,4,5,6,7,8,9,10)의 앞 항목 절반과 뒤 항목 절반을 출력하는 프로그램을 작성하십시오.
tu = (1,2,3,4,5,6,7,8,9,10)
print(tu[0:5])
print(tu[5:11])
| Python | zaydzuhri_stack_edu_python |
function query_api term location
begin
set bearer_token = call obtain_bearer_token API_HOST TOKEN_PATH
set response = search bearer_token term location
set businesses = get response string businesses
if not businesses
begin
print format string No businesses for {0} in {1} found. term location
return
end
set business_id... | def query_api(term, location):
bearer_token = obtain_bearer_token(API_HOST, TOKEN_PATH)
response = search(bearer_token, term, location)
businesses = response.get('businesses')
if not businesses:
print(u'No businesses for {0} in {1} found.'.format(term, location))
return
business_... | Python | nomic_cornstack_python_v1 |
from collections import Counter
set tuple N M = map int split input
set primes = list
set d = 2
while d ^ 2 <= M
begin
if M % d == 0
begin
set M = M // d
append primes d
end
else
begin
set d = d + 1
end
end
if M != 1
begin
append primes M
end
set cnt = counter primes
function choose n k
begin
import math
return call f... | from collections import Counter
N,M = map(int,input().split())
primes = []
d = 2
while d**2<=M:
if M % d == 0:
M //= d
primes.append(d)
else:
d += 1
if M != 1:
primes.append(M)
cnt = Counter(primes)
def choose(n,k):
import math
return math.factorial(n)//(math.factorial(n-k... | Python | zaydzuhri_stack_edu_python |
function swt X wtf=string d4 nlevels=string conservative RetainVJ=false
begin
comment Get a valid wavelet transform filter coefficients struct.
set wtf_s = call wtfilter wtf
set wtfname = Name
set gt = g
set ht = h
set L = L
comment ensure X is a numpy array
set X = array X
if length shape > 1
begin
raise call ValueErr... | def swt(X, wtf='d4', nlevels='conservative', RetainVJ=False):
# Get a valid wavelet transform filter coefficients struct.
wtf_s = wtfilter(wtf)
wtfname = wtf_s.Name
gt = wtf_s.g
ht = wtf_s.h
L = wtf_s.L
# ensure X is a numpy array
X = np.array(X)
if len(X.shape)>1:
rais... | Python | nomic_cornstack_python_v1 |
function test_post_apost self
begin
set url = string http://blog/postcreate/
set data = dict string title string new idea ; string text string Notre Dame Cathedral rebuilt in 5 years
set request = post url data
call force_authenticate request user=user token=token
set response = call call as_view request
assert status_... | def test_post_apost(self):
url = 'http://blog/postcreate/'
data = {'title': 'new idea', 'text':'Notre Dame Cathedral rebuilt in 5 years'}
request = self.factory.post(url, data)
force_authenticate(request, user=self.user, token=self.token)
response = PostCreation.as_view()(request... | Python | nomic_cornstack_python_v1 |
function _apply_replacement error found_file file_lines
begin
set fixed_lines = file_lines
set fixed_lines at line - 1 = replacement
set concatenated_fixed_lines = join string fixed_lines
comment Only fix one error at a time
seek found_file 0
write found_file concatenated_fixed_lines
call truncate
end function | def _apply_replacement(error, found_file, file_lines):
fixed_lines = file_lines
fixed_lines[error[1].line - 1] = error[1].replacement
concatenated_fixed_lines = "".join(fixed_lines)
# Only fix one error at a time
found_file.seek(0)
found_file.write(concatenated_fixed_lines)
found_file.trunc... | Python | nomic_cornstack_python_v1 |
for n in nums
begin
if n > 4
begin
append twice n * 2
end
end
set twice = list comprehension n * 2 for n in nums if n > 4 | for n in nums:
if n > 4:
twice.append(n * 2)
twice = [n * 2 for n in nums if n > 4]
| Python | zaydzuhri_stack_edu_python |
set name = string alice wonderland
comment 문자열의 수를 알려줌.
length name
comment name[-10]과 같음.
print name at 6
comment 문자열은 immutable하기 때문에 변형이 안됨.
set name at 0 = string A
comment 6번째 열부터 12열전까지 출력-'wonder'문자열이 출력됨.
name at slice 6 : 12 :
comment 위와 같으 결과가 나옴.
name at slice - 10 : 12 :
comment 계산방향이 왼쪽부터 오른쪽 순서이기 때문에 왼쪽... | name='alice wonderland'
len(name)# 문자열의 수를 알려줌.
print(name[6]) #name[-10]과 같음.
name[0]='A'#문자열은 immutable하기 때문에 변형이 안됨.
name[6:12] #6번째 열부터 12열전까지 출력-'wonder'문자열이 출력됨.
name[-10:12] #위와 같으 결과가 나옴.
name[12:9]# 계산방향이 왼쪽부터 오른쪽 순서이기 때문에 왼쪽이 오른쪽보다 작아야함.
name[ : 5] #숫자칸이 비어있으면 0으로 계산.
name[12 : ] #생략된 부분이 len(name)이라고 생각.(문자열... | Python | zaydzuhri_stack_edu_python |
function left self
begin
return integer round _box at 0
end function | def left(self):
return int(round(self._box[0])) | Python | nomic_cornstack_python_v1 |
for i in range e
begin
set arr = list map int split right strip input
append G at arr at 0 arr at 1
append GR at arr at 1 arr at 0
end
for i in G
begin
sort i
end
for i in GR
begin
sort i
end
class prop
begin
function __init__ self u
begin
set u = u
set flag = false
set t1 = - 1
set t2 = - 1
end function
end class
clas... | for i in range(e):
arr=list(map(int,input().rstrip().split()))
G[arr[0]].append(arr[1])
GR[arr[1]].append(arr[0])
for i in G:
i.sort()
for i in GR:
i.sort()
class prop:
def __init__(self,u):
self.u=u
self.flag=False
self.t1=-1
self.t2=-1
class DFS:
def __init__(self,G):
self.graph=[]
for i in G:
s... | Python | zaydzuhri_stack_edu_python |
import pandas as pd
import os
set DATA_DIRECTORY = string Data + sep
set GI = read csv string Dataset S2 - Averaged E-MAP one allele per gene.csv header=none
set GS = read csv string Dataset S3 - S.pombe Similarity Scores.csv header=none
set output_name_GI = string gene_interactions
set output_name_GS = string gene_sim... | import pandas as pd
import os
DATA_DIRECTORY = "Data" + os.sep
GI = pd.read_csv("Dataset S2 - Averaged E-MAP one allele per gene.csv", header=None)
GS = pd.read_csv("Dataset S3 - S.pombe Similarity Scores.csv", header=None)
output_name_GI = "gene_interactions"
output_name_GS = "gene_similarity"
output_name_combined ... | Python | zaydzuhri_stack_edu_python |
import csv
import matplotlib.pyplot as plt
import requests
import pandas as pd
from config2 import api_key
from pprint import pprint
function make_df city_list
begin
comment We will be making a list of dictionaries that we will eventually turn into our dataframe
set dict_list = list
comment Loops through every city in... | import csv
import matplotlib.pyplot as plt
import requests
import pandas as pd
from config2 import api_key
from pprint import pprint
def make_df(city_list):
#We will be making a list of dictionaries that we will eventually turn into our dataframe
dict_list = []
#Loops through every city in the p... | Python | zaydzuhri_stack_edu_python |
function get_session_keys conn pairing_data
begin
set headers = dict string Content-Type string application/pairing+tlv8
comment Step #1 ios --> accessory (send verify start Request) (page 47)
set ios_key = call Key25519
set request_tlv = call encode_list list tuple kTLVType_State M1 tuple kTLVType_PublicKey pubkey
cal... | def get_session_keys(conn, pairing_data):
headers = {
'Content-Type': 'application/pairing+tlv8'
}
#
# Step #1 ios --> accessory (send verify start Request) (page 47)
#
ios_key = py25519.Key25519()
request_tlv = TLV.encode_list([
(TLV.kTLVType_State, TLV.M1),
(TLV.k... | Python | nomic_cornstack_python_v1 |
function test_thin
begin
set s = call SED string 1 wave_type=string nm flux_type=string fphotons
set bp = call Bandpass join path datapath string LSST_r.dat string nm
set flux = call calculateFlux bp
print string Original number of bandpass samples = length wave_list
for err in list 0.01 0.001 0.0001 1e-05
begin
print ... | def test_thin():
s = galsim.SED('1', wave_type='nm', flux_type='fphotons')
bp = galsim.Bandpass(os.path.join(datapath, 'LSST_r.dat'), 'nm')
flux = s.calculateFlux(bp)
print("Original number of bandpass samples = ",len(bp.wave_list))
for err in [1.e-2, 1.e-3, 1.e-4, 1.e-5]:
print("Test err = ... | Python | nomic_cornstack_python_v1 |
function __create_preference_file
begin
try
begin
comment creates file
set pref_file = open call get_preference_file string w
comment creates the data structure
set data = dict
set data at string cache_manager_cache_path = string
set data at string cache_manager_model_group = string
set data at string cache_manager_... | def __create_preference_file():
try:
# creates file
pref_file = open(get_preference_file(), "w")
# creates the data structure
data = {}
data["cache_manager_cache_path"] = ""
data["cache_manager_model_group"] = ""
data["cache_manager_unload_rigs"] = 1
... | Python | nomic_cornstack_python_v1 |
function load_image self image_id
begin
comment Load image
set image = call imread image_info at image_id at string path
comment If grayscale. Convert to RGB for consistency.
if ndim != 3
begin
set image = call gray2rgb as type image / 65535 * 255 uint8
end
comment If has an alpha channel, remove it for consistency
if ... | def load_image(self, image_id):
# Load image
image = skimage.io.imread(self.image_info[image_id]['path'])
# If grayscale. Convert to RGB for consistency.
if image.ndim != 3:
image = skimage.color.gray2rgb((image / 65535 * 255).astype(np.uint8))
# If has an alpha chann... | Python | nomic_cornstack_python_v1 |
function get_exchangeable_nodes self n
begin
set parent = parent_node
set tuple a b = random sample call child_nodes 2
if parent_node is none
begin
if rooted
begin
set tuple c d = random sample call child_nodes 2
end
else
begin
set tuple c d = random sample call sister_nodes 2
end
end
else
begin
set c = random choice c... | def get_exchangeable_nodes(self, n):
parent = n.parent_node
a, b = random.sample(n.child_nodes(), 2)
if parent.parent_node is None:
if self.tree.rooted:
c, d = random.sample(n.sister_nodes()[0].child_nodes(), 2)
else:
c, d = random.sample(n... | Python | nomic_cornstack_python_v1 |
function access_token self
begin
return get attribute top string _assist_access_token none
end function | def access_token(self):
return getattr(_app_ctx_stack.top, "_assist_access_token", None) | Python | nomic_cornstack_python_v1 |
import torch
import numpy as np
import matplotlib.pyplot as plt
from model import Generator
if __name__ == string __main__
begin
string Load generator checkpoint, then generate a single image
set generator = call Generator
load state dict generator load torch string generator.pth
set device = if expression call is_avai... | import torch
import numpy as np
import matplotlib.pyplot as plt
from model import Generator
if __name__ == '__main__':
"""
Load generator checkpoint, then generate a single image
"""
generator = Generator()
generator.load_state_dict(torch.load('generator.pth'))
device = torch.device('cuda') ... | Python | zaydzuhri_stack_edu_python |
from django.test import TestCase
from datetime import datetime
from errors.models import Error
from errors.forms import ErrorForm
from projects.models import Project
class ErrorFormTestCase extends TestCase
begin
function test_error_form_should_use_error_model self
begin
string ErrorForm should use Error model for form... | from django.test import TestCase
from datetime import datetime
from errors.models import Error
from errors.forms import ErrorForm
from projects.models import Project
class ErrorFormTestCase(TestCase):
def test_error_form_should_use_error_model(self):
'''
ErrorForm should use Error model for form ... | Python | zaydzuhri_stack_edu_python |
function append self val
begin
if vals and vals at - 1 at 0 == val at 0
begin
if vals at - 1 at 2 == val at 1 and vals at - 1 at 4 == val at 3
begin
set res = tuple vals at - 1 at 0 vals at - 1 at 1 val at 2 vals at - 1 at 3 val at 4
set vals = vals at slice : - 1 :
end
else
begin
raise call ValueError string Element... | def append(self, val):
if self.vals and self.vals[-1][0] == val[0]:
if self.vals[-1][2] == val[1] and self.vals[-1][4] == val[3]:
res = (self.vals[-1][0], self.vals[-1][1],
val[2], self.vals[-1][3], val[4])
self.vals = self.vals[:-1]
... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
string Created on Tue Feb 13 13:52:25 2018 @author: Data Scientist 1
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime , date , time , timedelta
import pandas as pd
import numpy as np
import ConfigParser
from scipy.interpolate im... | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 13 13:52:25 2018
@author: Data Scientist 1
"""
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, date, time, timedelta
import pandas as pd
import numpy as np
import ConfigParser
from scipy.interpolate import U... | Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/env python3
comment -*- coding: utf-8 -*-
string https://leetcode.com/problems/redundant-connection/description/ In this problem, a tree is an *undirected graph* that is connected and has no cycles. The given input is a graph that started as a tree with N nodes (with distinct values 1, 2, ..., N), wit... | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
https://leetcode.com/problems/redundant-connection/description/
In this problem,
a tree is an *undirected graph* that is connected and has no cycles.
The given input is a graph that started as a tree with N nodes
(with distinct values 1, 2, ..., N), with one additi... | Python | zaydzuhri_stack_edu_python |
function is_develop self spec
begin
return name in dev_specs
end function | def is_develop(self, spec):
return spec.name in self.dev_specs | Python | nomic_cornstack_python_v1 |
import random
import disjointSet
import matplotlib.pyplot as plt
class BiGraph
begin
string An undirected binomial random graph
function __init__ self
begin
string Graph constructor
set graph = dict
end function
function Binomial self n p
begin
string Generate and return an instance of a binomial random graph
set L = ... | import random
import disjointSet
import matplotlib.pyplot as plt
class BiGraph:
'''An undirected binomial random graph'''
def __init__(self):
'''Graph constructor'''
self.graph={}
def Binomial(self, n, p):
'''Generate and return an instance of a binomial random graph'''
L=[]
for i in range(n):
for... | Python | zaydzuhri_stack_edu_python |
import os
function file_merger dir
begin
set files = list directory dir
set full_text = string
print length files
for file in files
begin
with open format string {}/{} dir file as f
begin
set full_text = full_text + join string read lines f
end
end
with open format string {}_merge.txt dir string w as f
begin
write f ... | import os
def file_merger(dir):
files = os.listdir(dir)
full_text = ''
print(len(files))
for file in files:
with open('{}/{}'.format(dir,file)) as f:
full_text += ''.join(f.readlines())
with open('{}_merge.txt'.format(dir), 'w') as f:
f.write(full_text)
return f... | Python | zaydzuhri_stack_edu_python |
function Get self interface prop
begin
set my_prop = call __getattribute__ prop
return my_prop
end function | def Get(self, interface, prop):
my_prop = self.__getattribute__(prop)
return my_prop | Python | nomic_cornstack_python_v1 |
class DomainSearch
begin
function __init__ self
begin
string This still needs a bit of modifications :param phagesProteins: protein function and sequences, as provided in NCBI. Each phage ID has every protein represented with a dicionary with keys as protein IDs :param phageDomains: for each phage and each of it's prot... | class DomainSearch:
def __init__(self):
'''
This still needs a bit of modifications
:param phagesProteins: protein function and sequences, as provided in NCBI. Each phage ID has every protein represented with a dicionary with keys as protein IDs
:param phageDomains: for each phage and each of it's proteins, a... | Python | zaydzuhri_stack_edu_python |
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from mpl_toolkits.mplot3d import Axes3D
from sklearn.ensemble import IsolationForest
from visualize.helper import plot_hyperplane , plot_subplots
if __name__ == string __main__
begin
set fig = figure
set gs = call GridSpec 3 8 fig
from sklearn.dat... | import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from mpl_toolkits.mplot3d import Axes3D
from sklearn.ensemble import IsolationForest
from visualize.helper import plot_hyperplane, plot_subplots
if __name__ == '__main__':
fig = plt.figure()
gs = GridSpec(3, 8, fig)
from sklearn.dat... | Python | zaydzuhri_stack_edu_python |
class Estudiante extends object
begin
set db = none
decorator classmethod
comment Crear estudiante
function create cls apellido nombre fecha_nac localidad_id nivel_id domicilio genero_id escuela_id tipo_doc_id numero tel barrio_id lugar_nac responsable
begin
set sql = string INSERT INTO `estudiante`(`apellido`, `nombre... | class Estudiante(object):
db = None
#Crear estudiante
@classmethod
def create(cls, apellido, nombre, fecha_nac, localidad_id, nivel_id, domicilio, genero_id, escuela_id, tipo_doc_id, numero, tel, barrio_id, lugar_nac, responsable):
sql = """
INSERT INTO `estudiante`(`apellido`, `nombre... | Python | zaydzuhri_stack_edu_python |
function empty self
begin
return not call qsize
end function | def empty(self):
return not self.qsize() | Python | nomic_cornstack_python_v1 |
function cb_toggled self cb
begin
set config at string Setup at check_boxes at call objectName = string call isChecked
comment TODO: When initially loading config, clear certain checkbox values in it
write config
end function | def cb_toggled(self, cb):
GLB.config['Setup'][self.check_boxes[cb.objectName()]] = str(cb.isChecked())
GLB.config.write() # TODO: When initially loading config, clear certain checkbox values in it | Python | nomic_cornstack_python_v1 |
comment How To Read Global Variables From Local
function spam
begin
print eggs
end function
set eggs = 42
call spam
print eggs
print string eggs needed:
set eggs = input
call spam | #How To Read Global Variables From Local
def spam():
print(eggs)
eggs = 42
spam()
print(eggs)
print("eggs needed:")
eggs = input()
spam()
| Python | zaydzuhri_stack_edu_python |
function solve s
begin
set split_arr = list
set split_str = string
for ch in s
begin
if ch in string aeiou
begin
append split_arr split_str
set split_str = string
end
else
begin
set split_str = split_str + ch
end
end
return max map lambda item -> sum generator expression ordinal ch - 96 for ch in item split_arr
end ... | def solve(s):
split_arr = []
split_str = ''
for ch in s:
if ch in 'aeiou':
split_arr.append(split_str)
split_str = ''
else:
split_str += ch
return max(map(lambda item: sum(ord(ch) - 96 for ch in item), split_arr)) | Python | zaydzuhri_stack_edu_python |
function look vertices viewpoints direction=none up=none
begin
assert ndim == 3
if direction is none
begin
set direction = call as_tensor list 0 0 1 dtype=float32
end
if up is none
begin
set up = call as_tensor list 0 1 0 dtype=float32
end
if is instance viewpoints list or is instance viewpoints tuple
begin
set viewpoi... | def look(vertices, viewpoints, direction=None, up=None):
assert (vertices.ndim == 3)
if direction is None:
direction = torch.as_tensor([0, 0, 1], dtype=torch.float32)
if up is None:
up = torch.as_tensor([0, 1, 0], dtype=torch.float32)
if isinstance(viewpoints, list) or isinstance(viewp... | Python | nomic_cornstack_python_v1 |
comment 讀取檔案
set data = list
set count = 0
with open string reviews.txt string r as f
begin
for line in f
begin
append data line
set count = count + 1
if count % 100000 == 0
begin
print length data
end
end
end
print string 檔案讀取完了,總共有 length data string 筆資料
comment 文字記數
comment word_count 字典
set wc = dict
for d in dat... | # 讀取檔案
data = []
count = 0
with open('reviews.txt', 'r') as f:
for line in f:
data.append(line)
count += 1
if count % 100000 == 0:
print(len(data))
print('檔案讀取完了,總共有', len(data), '筆資料')
# 文字記數
wc = {} # word_count 字典
for d in data:
words = d.split()
for word in words:
if word in wc:
wc[word] += 1
e... | Python | zaydzuhri_stack_edu_python |
function calendar request username=none year=none month=none
begin
set context = dict
set tuple is_owner user = call check_access user username
set year = if expression year then integer year else year
set month = if expression month then integer month else month
set tuple current_workout schedule = call get_current_w... | def calendar(request, username=None, year=None, month=None):
context = {}
is_owner, user = check_access(request.user, username)
year = int(year) if year else datetime.date.today().year
month = int(month) if month else datetime.date.today().month
(current_workout, schedule) = Schedule.objects.get_cu... | Python | nomic_cornstack_python_v1 |
import cv2
import sys
import logging as log
import datetime as dt
from time import sleep
import PIL
from PIL import Image
from Predict import PredictClass
set cascPath = string haarcascade_frontalface_default.xml
set faceCascade = call CascadeClassifier cascPath
call basicConfig filename=string webcam.log level=INFO
se... | import cv2
import sys
import logging as log
import datetime as dt
from time import sleep
import PIL
from PIL import Image
from Predict import PredictClass
cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)
log.basicConfig(filename='webcam.log', level=log.INFO)
video_capture... | Python | zaydzuhri_stack_edu_python |
function show_deaths self db_session
begin
set deaths = call _get_current_deaths db_session
set total_deaths = call _get_total_deaths db_session
call _add_to_chat_queue format string Current Boss Deaths: {}, Total Deaths: {} deaths total_deaths
end function | def show_deaths(self, db_session):
deaths = self._get_current_deaths(db_session)
total_deaths = self._get_total_deaths(db_session)
self._add_to_chat_queue("Current Boss Deaths: {}, Total Deaths: {}".format(deaths, total_deaths)) | Python | nomic_cornstack_python_v1 |
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