python-asyncio

asyncio run or run_until_complete

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Is there a simple way to make [code making use of asyncio.run] backwards compatible with Python 3.6? You can implement a simple substitute for asyncio.run and call it on older Python versions: import asyncio, sys, types def run(coro): if sys.version_info >= (3, 7): return asyncio.run(coro) # Emulate asyncio.run() on older versions # asyncio.run() requires a … Read more

Asyncio task vs coroutine

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What are the criteria to determine when a coroutine should be wrapped in a task or not? You should use a task when you want your coroutine to effectively run in the background. The code you’ve seen just awaits the coroutines directly because it needs them running in sequence. For example, consider an HTTP client … Read more

Sharing python objects across multiple workers

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It is not possible to share a python object between different processes straightforwardly. The facilities included in the multiprocessing module (like managers or shared memory) are not suitable for sharing resources between workers, since they require a master process creating the resources and do not have the durability property. Also server processes can be run … Read more

ObjectNotExecutableError when executing any SQL query using AsyncEngine

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As the exception message suggests, the str ‘SELECT id, name FROM item LIMIT 50;’ is not an executable object. To make it executable, wrap it with sqlalchemy.text. from sqlalchemy import text async with self.async_engine.connect() as con: query = “SELECT id, name FROM item LIMIT 50;” result = await con.execute(text(query)) async.connection.execute requires that its statement argument … Read more

Why do we need `async for` and `async with`?

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TLDR: for and with are non-trivial syntactic sugar that encapsulate several steps of calling related methods. This makes it impossible to manually add awaits between these steps – but properly usable async for/with need that. At the same time, this means it is vital to have async support for them. Why we can’t await nice … Read more

@asyncio.coroutine vs async def

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Yes, there are functional differences between native coroutines using async def syntax and generator-based coroutines using the asyncio.coroutine decorator. According to PEP 492, which introduces the async def syntax: Native coroutine objects do not implement __iter__ and __next__ methods. Therefore, they cannot be iterated over or passed to iter(), list(), tuple() and other built-ins. They … Read more

asyncio.gather vs asyncio.wait (vs asyncio.TaskGroup)

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Although similar in general cases (“run and get results for many tasks”), each function has some specific functionality for other cases (and see also TaskGroup for Python 3.11+ below): asyncio.gather() Returns a Future instance, allowing high level grouping of tasks: import asyncio from pprint import pprint import random async def coro(tag): print(“>”, tag) await asyncio.sleep(random.uniform(1, … Read more

Python type hinting for async function as function argument

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You are looking for: FuncType = Callable[[Any, Any], Awaitable[Any]] def consumer(function_: FuncType = None): pass # TODO: do stuff Why is the type structured like that? If you declare a function async, what you actually do is wrap it in a new function with the given parameters, which returns a Coroutine. Since this might be … Read more

Differences between Futures in Python3 and Promises in ES6

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In both Python and ES6, await/async are based on generators. Is it a correct to think Futures are the same as Promises? Not Future, but Python’s Task is roughly equivalent to Javascript’s Promise. See more details below. I have seen the terms Task, Future and Coroutine used in the asyncio documentation. What are the differences … Read more