Multi-Threading and Multi-Processing Guide

This skill provides comprehensive guidance for implementing concurrent and parallel processing in Python applications. It covers when to use multi-threading vs multi-processing, best practices, performance considerations, and practical examples using the speedy_utils library's multi-worker implementations.

When to Use Multi-Threading vs Multi-Processing

Multi-Threading (Use for I/O-bound tasks)

Best for:

• Network requests (HTTP, database queries, API calls)
• File I/O operations (reading/writing files)
• GUI applications that need to remain responsive
• Tasks waiting for external resources

When to choose threading:

# I/O-bound example: Downloading multiple files
import requests
from speedy_utils import multi_thread