adilkhash

import random
import datetime as dt
from airflow.decorators import task, dag

default_args = {"owner": "airflow", "start_date": dt.datetime(2024, 2, 1), "retries": 1}

@task.branch()
def choose_branch():
    return random.choice(["task_a", "task_b"])  # Randomly chooses a branch

adilkhash

const std = @import("std");
const process = std.process;

pub fn main() !void {
    var gpa = std.heap.GeneralPurposeAllocator(.{}){};
    defer _ = gpa.deinit();
    const allocator = gpa.allocator();
    const args = try std.process.argsAlloc(allocator);
    defer std.process.argsFree(allocator, args);

adilkhash

import time
from multiprocessing import Process, Value
from multiprocessing import Pool


def sum_numbers(numbers):
    result = 0
    for number in numbers:
        result += number
    return result

adilkhash

import typing as t
from concurrent.futures import ThreadPoolExecutor, as_completed
from functools import wraps

import requests


def parallelize(f: t.Callable = None, max_workers: int = 5):
    def decorator(func):
        @wraps(func)

adilkhash

from urllib.request import urlopen
from urllib.error import HTTPError
from concurrent.futures import ThreadPoolExecutor, as_completed


class HttpError(Exception):

    def __init__(self, url: str, code: int) -> None:
        self.url = url
        self.code = code

adilkhash

import datetime as dt
from urllib.parse import urljoin

import requests
from airflow.models import DAG
from airflow.operators.python import PythonOperator


default_args = {
    'owner': 'airflow',

adilkhash

import requests
from http import HTTPStatus
import pprint


class HttpError:
    def __init__(self, status_code: int):
        self.status_code = status_code

adilkhash

import logging
from logging import Handler, LogRecord

from airflow.operators.python import get_current_context


class RowsAffectedHandler(Handler):
    def emit(self, record: LogRecord) -> None:
        msg = self.format(record)
        context = get_current_context()

adilkhash

import re
from operator import add, mul
from functools import reduce
from typing import List


def multiply(iin: str, weights: List[int]) -> int:
    result = reduce(
        add,
        map(lambda i: mul(*i), zip(map(int, iin), weights))

adilkhash

import csv

import luigi
from luigi.format import UTF8
import requests
import pandas as pd
from bs4 import BeautifulSoup


class AggregateMovieRatingTask(luigi.Task):