Nasdin

#!/usr/bin/env bash

set -euo pipefail

DESCRIPTION="Convert an input file of {csv, parquet, json} format to {csv, parquet, json} format using Polars"
VERBOSE=false

usage() {
  echo "Usage: $0 <input_file> -f <output_format> [-o <output_file>] [-v]"
  echo "  <input_file>: Path to the input file"

Nasdin

import calendar
import re
from datetime import datetime
from urllib.parse import urljoin, urlparse, parse_qs

import pandas as pd
import requests
from bs4 import BeautifulSoup

USED_BIKE_SEARCH_URL = "https://sgbikemart.com.sg/listing/usedbikes/listing/?bike_model=Honda+MSX125&bike_type=&price_from=&price_to=&license_class=2B&reg_year_from=1970&reg_year_to=2024&monthly_from=&monthly_to=&user=&status=10&category="

Nasdin

def sum_bits(larger, smaller):
    """ Sum but using bits, only positive numbers"""

    top_down_sum = larger ^ smaller
    carry = (larger & smaller) << 1
    if carry > 0:
        return sum_bits(top_down_sum, carry)
    return top_down_sum

def sub_bits(larger, smaller):

Nasdin

# Implement a hashmap in Python without using a dictionary     
# A simple toy example, look to improve when the hashes start clashing with each other either by adapting a dynamic size
# Or using a better hash function

class HashMap(object):

    def __init__(self, size, hash_function):

        self.array = [None] * size
        self.size = size

Nasdin

import sys

import cv2
import numpy as np
import xlsxwriter

if len(sys.argv) != 4:
    print("That's not how it works")
    sys.exit(404)

Nasdin

"""
Keras and talos using Mnist as toy example
"""

import talos
from keras import Sequential
from keras.activations import relu, elu, tanh, softmax
from keras.layers import Conv2D, BatchNormalization, MaxPool2D, Flatten, Dense, Dropout
from keras.losses import logcosh, binary_crossentropy
from keras.optimizers import Adam, RMSprop

Nasdin

from functools import partial

alphabet = 'abcdefghijklmnopqrstuvwxyz'
alphabet_dict = {letter: order + 1 for order, letter in enumerate(alphabet)}
alphabet_dict_reversed = {order: letter for letter, order in alphabet_dict.items()}


def encrypt_text(text: str, shift: int, decrypt: bool = False):
    shift_n = (shift * (-1 if decrypt else 1))  # Useful line to switch to decryption
    encrypted_text = [

Nasdin

import time

import pandas as pd


def string_to_csv(string: str, csv_output_name: str):
    row_gen = (x.split("=") for x in string.split(';'))

    df = pd.DataFrame(row_gen)
    df['index'] = df.groupby(0).cumcount()

Nasdin

class Player(object):
  
  # Class Attributes, tracking all players
  players = {}
  id_player_names = {}  # Just something to help you track id to players
  last_id = 0
  
  def __init__(self, name=None, height = 0, weight = 0 , bmi =0):
  
    # Player attributes, tracking a player's stats