uroybd

use std::collections::HashMap;

pub fn read_lines(filename: String) -> Vec<String> {
    let content: Vec<String> = fs::read_to_string(filename)
        .expect("Invalid File")
        .split('\n')
        .map(|s| s.to_string())
        .collect();
    return content;
}

uroybd

import sys
largest_by_far = sys.float_info.min
smallest_by_far = sys.float_info.max

while True:
    value = input("Enter Numbers: ")
    if value == "done":
        break
    try:
        fvalue = float(value)

uroybd

import csv

MY_DICT = {"a": "a definition"} # assuming this is your dict
data = list(MY_DICT.items())

with open('glossary.txt', 'w') as gfile:
  writer = csv.writer(gfile, delimiter="\t")
  writer.writerows(data)

uroybd

Keybase proof

I hereby claim:

• I am uroybd on github.
• I am uroybd (https://keybase.io/uroybd) on keybase.
• I have a public key ASDAvqxhvhTXcjkzLfpaldu_T9EmLDU80ej4KEkZY2MyQAo

To claim this, I am signing this object:

uroybd

var bengaliUnitRegex = /([অ-হড়-য়](্[অ-হড়-য়])+|[অ-হড়-য়]্|[অ-হড়-য়])[া-ৌ]*[ঁঃং]*|ৎ|[০-৯]| /g;
// You can match with str.mathc(rg) and it will yield units as array. Example:
var testText = "আদর্শলিপি";
testText.match(bengaliUnitRegex);

// > ["আ", "দ", "র্শ", "লি", "পি"]

uroybd

class Case:
    """A Class to simulate case behavior in a more compact way.

    Optionaly, default value and a conditional function can be passed.
    cases and **kwargs are for flexibility since you can't have nothing
    but string keys in kwargs. They both get combined in a single switch.

    Return value for switches can be either a value or callable.
    
    Stupid thingy, I know right! :D

uroybd

import pandas as pd

def check_equal(lst):
    if lst[0] != " ":
        return lst[1:] == lst[:-1]
    else:
        return False

def if_win(board):
    for i in range(3):

uroybd

import csv
from requests import post
from functools import reduce
from bs4 import BeautifulSoup

def soup_to_dict(dt):
    """Job html soup to dictionary"""
    
    main_site = 'http://jobs.bdjobs.com/'
    data_dict = {};

uroybd

from copy import deepcopy

# Datastructure: [{'r': int, 'c': int, 'd': boolean, 'v': int, 'p': vecotor of int}.....]

def related(case, unit, data):
    grider = [[1,2,3], [4,5,6], [7,8,9]]
    for g in grider:
        if unit['c'] in g:
            cols = g
        if unit['r'] in g:

uroybd

def verdict(P1,P2,C1,C2,M,N):
    if (M + N) % 2 == 0:
	v = 'PAR'
    else:
	v = 'IMPAR'
    if C1 == v:
	return P1
    else:
	return P2