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#!/usr/bin/env python
# NOTE: use newer & fixed version as package: https://pypi.org/project/mkchangelog/
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import argparse
import json
import logging
import os
import re

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import asyncio
import httpx
from typing import Callable, List, Any
from rich.console import Console


console = Console()


async def producer(

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import asyncio
import argparse
import random
from typing import Any

async def worker(name: str, queue: asyncio.Queue[str], stop_event: asyncio.Event):
    while not stop_event.is_set() or not queue.empty():
        try:
            # Try to get an item from the queue without indefinitely blocking
            try:

onjin

#!/usr/bin/env python
"""
pysh

This script provides a command-line interface (CLI) for creating and running a 
nix-shell environment with specified Python packages. It supports using different 
Python versions and can optionally create a temporary virtual environment (venv) 
to install packages.

Purpose:

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.DEFAULT_GOAL := help

# use '# >>> Build commands' to create section
# use '# target: target description' to create help for target

# example output from this file:
# $ make
# Usage:
# 
# >>> Section 1

onjin

"""
Comparison of State and Strategy Patterns in Python

This script demonstrates the similarities and differences between the State and Strategy patterns.
Each pattern is implemented separately with an execution example.

### Similarities:
1. **Encapsulation of Behavior** – Both patterns encapsulate behaviors in separate classes, promoting the **Single Responsibility Principle (SRP)**.
2. **Dynamic Behavior Switching** – Both allow switching between different behaviors (strategies or states) at runtime.
3. **Use of Composition Over Inheritance** – Instead of using conditionals (`if-else` or `switch` statements), they promote using composition to delegate behavior.