import json
import logging
import os
import re
import shutil
import subprocess
from functools import lru_cache
from http.server import HTTPServer, SimpleHTTPRequestHandler
from importlib import metadata
from multiprocessing import Pool
from pathlib import Path
from typing import Any, Dict, List, Optional, Union

import mkdocs.utils
import typer
import yaml
from jinja2 import Template
from ruff.__main__ import find_ruff_bin

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.