adilkhash

import logging
import os
import shutil
from datetime import datetime, timedelta

import pendulum
import structlog
from airflow.sdk import DAG, task

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))