asyncio

letly the way to write correct code. Another thing is that in 3.7, the asyncio uses async / await and not yield from. Because of this dog fooding, the whole lib improved. 3.7 has a LOT of patches just for asyncio: https://docs.python.org/3.7/whatsnew/changelog.html#python-3... Speed (Future has been rewritten in C, and many other tweaks), fixes, _way_ better doc... Obvious shortcomming were resolved, like asyncio.wait_for() that now waits until the cancellation is complete, or asyncio.all_tasks() returning only pending tasks. A lot of little things that add up. The whole ergonomics are better, up to the command line experience with "python -X dev" which automatically add warnings and set asyncio in debug mode, and frankly you can't cleanly code async without. The final nail in the coffin are the context vars (https://docs.python.org/3/library/contextvars.html). It's the only sane way to deal with a global registery that is dependant of the current running task. It's almost always easier to upgrade to 3.7 than trying to use asyncio before it.

the examples. Simply reading all the examples on after another gives a a good insight on how asyncio should be used. * If you want to work with sockets, use the high-level "Streams"[3] if you want to stay in the standard library. `asyncio.start_server` is a powerful abstraction. If you’re willing to use a third-party library, I found that `pynng`[4] was a breeze to work with. It is compatible with asyncio and other async frameworks, and it found it more straightforward than pyzmq, which is also compatible with asyncio[5]. * If you want to run async functions in the main event loop and blocking functions in threads (with `loop.run_in_executor), Janus[7] seems to be a great way to share data. I have not used it yet though. My use case was that I wanted to read sensor data on one computer (server) and broadcast it to other computers (clients) which would in turn graph it live, or write it to disk. The server used `pyserial_asyncio`[6] to asynchronously read serial data and published it via TCP using a the pub/sub scheme from pynng (pynng.Pub0). The clients could then either synchronously or asynchronously receive the data by subscribing to the server (pynng.Sub0), and make plots in realtime. [1]: https://docs.python.org/3/library/asyncio.html [2]: https://github.com/python/asyncio/pull/465#issue-93620963 [3]: https://docs.python.org/3/library/asyncio-stream.html#asynci... [4]: https://pypi.org/project/pynng/ [5]: https://pyzmq.readthedocs.io/en/latest/api/zmq.asyncio.html [6]: https://github.com/pyserial/pyserial-asyncio [7]: https://github.com/aio-libs/janus