Asynchronous Python Development

Python GIL - Global Interpreter Lock

Two threads cannot be run in one process at the same time
- Each process in Python creates a key resource(GIL)
- When a thread is running, it must acquire the resource
- Since there is only one key resource per process, only one thread can run in a process at once

IO bound
- general rule of thumb is to use asyncio when you can, threading when you must.
- threading is better for IO-bound tasks.
CPU bound
- CPU-bound problems only really gain from using multiprocessing.
- threading and asyncio do not help this type of problem at all.
- Multiprocessing is well-suited for CPU-bound tasks such as, tightly bound for loops and mathematical computations.

async IO is a single-threaded, single-process design: it uses cooperative multitasking.
async IO gives a feeling of concurrency despite using a single thread in a single process.
Coroutines (a central feature of async IO) can be scheduled concurrently, but they are not inherently concurrent.
asynchronous
- Asynchronous routines are able to “pause” while waiting on their ultimate result and let other routines run in the meantime.
- Asynchronous code facilitates concurrent execution.
At the heart of async IO are coroutines.
- A coroutine is a specialized version of a Python generator function.
- a coroutine is a function that can suspend its execution before reaching return, and it can indirectly pass control to another coroutine for some time.