🧵 Concurrency Patterns & Async Primitives in Python: Let's Learn from ZERO!

If you're building a FastAPI backend (like a social-feed app), you'll soon need to handle many requests, database calls, background jobs, and failures without making your code messy. 😵

This post starts from absolute zero . No concurrency knowledge needed! We'll slowly build up to Python's asyncio toolbox:

✅ Concurrency vs parallelism

✅ async / await and the event loop

✅ Semaphore and Lock

✅ Queue (producers, workers, backpressure)

✅ Async context managers and async generators

✅ Task queues with concurrency limits

✅ Error handling: gather , return_exceptions , fail-fast vs fail-soft

✅ JavaScript Promise.all() vs Promise.allSettled()

✅ asyncio.TaskGroup

Let's go! 🚀

1. 🤔 What is Concurrency?

Imagine you're a waiter in a restaurant 🍽️ with three customers:

☕ Customer A orders coffee

🍵 Customer B orders tea

🧃 Customer C orders juice

You take A's order to the kitchen.…