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
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
So, as @bosnjak said, you can use async for: async for ITEM in A_ITER: BLOCK1 else: # optional BLOCK2 But if you want to iterate manually, you can simply write: it = async_iterator() await it.__anext__() But I wouldn’t recommend to do that. I think that if you are going to call something an Iterator its … Read more
You can use gather. From the Python documentation: import asyncio async def factorial(name, number): f = 1 for i in range(2, number + 1): print(f”Task {name}: Compute factorial({i})…”) await asyncio.sleep(1) f *= i print(f”Task {name}: factorial({number}) = {f}”) async def main(): # Schedule three calls *concurrently*: await asyncio.gather( factorial(“A”, 2), factorial(“B”, 3), factorial(“C”, 4), ) … Read more
Using the aiofiles: async with aiofiles.open(‘filename’, mode=”r”) as f: async for line in f: print(line) EDIT 1 As the @Jashandeep mentioned, you should care about blocking operations: Another method is select and or epoll: from select import select files_to_read, files_to_write, exceptions = select([f1, f2], [f1, f2], [f1, f2], timeout=.1) The timeout parameter is important here. … Read more
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
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
If I understand you well, you want to limit the number of simultaneous requests? There is a object inside asyncio named Semaphore, it works like an asynchronous RLock. semaphore = asyncio.Semaphore(50) #… async def limit_wrap(url): async with semaphore: # do what you want #… results = asyncio.gather([limit_wrap(url) for url in urls]) updated Suppose I make … Read more
A graceful way is using error handling api. https://docs.python.org/3/library/asyncio-eventloop.html#error-handling-api Example: import asyncio async def run_division(a, b): await asyncio.sleep(2) return a / b def custom_exception_handler(loop, context): # first, handle with default handler loop.default_exception_handler(context) exception = context.get(‘exception’) if isinstance(exception, ZeroDivisionError): print(context) loop.stop() loop = asyncio.get_event_loop() # Set custom handler loop.set_exception_handler(custom_exception_handler) loop.create_task(run_division(1, 0)) loop.run_forever()
asyncio.sleep(delay) Change it to: await asyncio.sleep(delay) asyncio.sleep is a coroutine and should be awaited.