Network programming in Python presents interesting challenges. Developers face race conditions, deadlocks, synchronization issues, and other obstacles when juggling simultaneous connections. Luckily, encapsulation comes to the rescue. This trusty technique brings structure, predictability, and peace of mind to networked applications. Let’s dive into some examples.
AsyncIO and Contextvars for Thread Safety
Python’s asyncio library offers excellent support for concurrent programming. Its event loop model handles thousands of tasks efficiently, but careless resource sharing might lead to trouble. Encapsulation saves the day by neatly packaging shared data, preventing conflicts and accidents.
Context vars come in handy when dealing with mutable data used by coroutines. Introduced in PEP 567, context vars help avoid thread-local storage antipatterns and simplify multi-threaded programming. Check out this modified HTTP server example taken from the official docs:
import asyncio
import sys
import http.server
import os
async def handle_request(reader, writer):
# Save…