Asynchronous Python for beginners

Explains the WSGI specification, a Python interface between applications and web servers, where a callable accepts a request and a start_response function and streams an iterable response after calling start_response.

Explore a basic WSGI Flask application demo running on localhost:9000, demonstrating single-threaded and multithreaded modes, printing the request and headers, and returning a hello world response.

Demonstrate how a WSGI blocking application shows how a single request can block health checks due to the Python interpreter lock, using sleep and a threading lock.

Explore techniques to resolve blocking in asynchronous Python, such as monkey patching, to keep microservice pipelines responsive and prevent health check timeouts and data loss.

Master monkey patching to alter runtime behavior without changing source code, swapping blocking functions with non-blocking patches, such as patching a socket in the request library to avoid blocking.

Explore monkey patching to remove blocking in the request library by patching the socket, compare synchronous and asynchronous patterns using threading and events, and observe dramatic concurrency gains.

Explore how Python's event loop coordinates asynchronous tasks and callbacks, contrast threads with coroutines, and show how async/await enables this within a Python server framework.

Explore an ASGI demo with a basic event loop in the unicorn framework. Define an async app that handles scope, receive, and send, and demonstrates chunked responses.

Explore futures theory in asynchronous python, showing how process pool and thread pool executors run non-async functions concurrently with async io, handling blocking actions like time.sleep and network requests.

This futures demo contrasts thread pool and process pool execution of blocking code, highlighting deadlocks from shared state and showing how processes avoid them, and debugging async io code.

Learn how to implement a WebSocket with async IO to push server time to multiple clients, maintaining a continuous two-way connection and comparing it to long polling.

Explore an asynchronous Python WebSocket demo that synchronizes a live counter and online user count across multiple clients, using a server-driven JSON payload and async IO.

Explore asyncio debug mode to reveal when the event loop is blocked, and learn three ways to enable debugging: environment variable, asyncio.run flag, and loop.set_debug.

Explore asyncio debugging techniques by enabling the debug logger, detect never awaited coroutines, and diagnose event loop blocking using tests, stack traces, and concurrent task demos.