Creating low-level foundations and abstractions for asynchronous programming in Python (i.e., implementing concurrency without using threads).
Note on threads in Python, like C they are hardware - posix threads the GIL (Global Interpreter Lock) prevents threads in Python from running in parallel they can only run on a single CPU
What some people call "callback hell" the async_producer.py demonstrates replacing loops and threads with small callback functions that rely on the Scheduler to switch between tasks.
Use the yield stmt to create async/await and replace counting functions with producers and consumers. See yield_it.py and async-await_producer.py
Async IO in Python combines the models demonstrated in Step1 and Step 2. This is done using coroutines on top of a callback based Scheduler.
Each file is an executable.
In order of programming model progressing to final example which combines a callback based Scheduler and coroutines which in turn enables the lib to be used with either callback or coroutine I/O solutions.
Threads: threads_expl.py, add producer/consumer to threads producer.py
Scheduler: recursive callbacks in func - main.py
Yield and wrapped yield: yield_it.py
Queue and Result: async_producer.py and a_pro_clean.py
__await__: async_await_producer.py
Combine callback Scheduler and Task wrapped coroutines: async_cb_coro.py
Add I/O tcp_server: async_io.py