A lightweight library for allowing async functions to be called in a synchronous manner.
Project description
AnySync
A lightweight library for allowing async functions to be called in a synchronous manner.
import asyncio
from anysync import anysync
@anysync
async def f():
return 42
assert f().run() == 42
async def main():
assert await f() == 42
asyncio.run(main())
Just pip install anysync
and you're good to go!
Usage
Coroutines
The primary use case for anysync
is to allow async functions to be called in a
synchronous manner. All you need to do is add the anysync.coroutine
decorator to your
async function:
import asyncio
import anysync
@anysync.coroutine
async def f():
return 42
assert f().run() == 42
Generators
You can also use anysync
with async generators:
import asyncio
import anysync
@anysync.generator
async def gen():
yield 1
yield 2
yield 3
assert list(gen()) == [1, 2, 3]
Note that in this case you don't need to call run()
. The generator will automatically
detect how it's being used and run the coroutine accordingly.
Context Managers
You can even use AnySync on your async context managers.
import anysync
@anysync.contextmanager
async def cm():
yield 42
with cm() as x:
assert x == 42
You can alternatively subclass the AnySyncContextManager
class:
from anysync import AnySyncContextManager
class CM(AnySyncContextManager):
async def __aenter__(self):
return 42
async def __aexit__(self, exc_type, exc, tb):
pass
with CM() as x:
assert x == 42
Comparisons
asyncio.run
Unlike asyncio.run
, an AnySync
object can be run()
even if an event loop is
already running.
For example, the following code will raise a RuntimeError
:
import asyncio
async def f():
return 42
async def test_async():
assert asyncio.run(f()) == 42
asyncio.run(test_async())
However, with AnySync, the following code will work as expected:
import asyncio
from anysync import anysync
@anysync
async def f():
return 42
async def test_async():
assert f().run() == 42
asyncio.run(test_async())
unsync
AnySync is similar to unsync
in that it allows
async functions to be called synchronously when needed. The main differences are that
AnySync works with type checkers and other async libraries like trio
via anyio
as
well as async generators and context managers.
Automatic Detection
The other approach to dealing with the challenges of mixing synchronous and asynchronous
code is to automatically infer whether a function should be run synchronously based on
whether it is being run in an async context. This approach is taken by libraries like
Prefect's
sync_compatible
decorator. The main downside is that the behavior of the function changes dynamically
depending on the context which can lead to unexpected behavior.
For example, the code below operates as expected where work()
is called in a sync
context:
from prefect.utilities.asyncutils import sync_compatible
@sync_compatible
async def request():
...
return "hello"
def work():
response = request()
...
return response.upper()
def test_sync():
assert work() == "HELLO"
test_sync()
However, if we now call work()
from an async context, the behavior changes:
import asyncio
async def test_async():
assert work() == "HELLO" # AttributeError: 'coroutine' object has no attribute 'upper'
asyncio.run(test_async())
Because work()
is now being called from an async context, request()
automatically
returns a coroutine object which causes work()
to fail.
Other Considerations
How it Works
AnySync works by detecting the presence of a running event loop. If one already exists, then AnySync uses a separate thread to run the coroutine. Where possible AnySync tries to reuse a single global background thread that's created only when it's needed. However, in the case that a program repeatedly trys to synchronously run a coroutine while in an async context, AnySync will create a new thread each time.
For example, you can count the number of threads that are used in two different scenarios. The first reuses the same global thread over and over again.
from threading import current_thread
import anysync
threads = set()
@anysync.coroutine
async def f():
threads.add(current_thread()) # runs in the main thread
return g().run()
@anysync.coroutine
async def g():
threads.add(current_thread()) # runs in anysync's global background thread
return 42
f().run()
f().run()
main_thread = current_thread()
assert len(threads - {main_thread}) == 1
In the second scenario, ends up creating two threads in addition to AnySync's global
background thread because g()
runs in the global background thread and h()
runs in a
new thread each time.
from threading import current_thread
import anysync
threads = set()
@anysync.coroutine
async def f():
threads.add(current_thread()) # runs in the main thread
return g().run()
@anysync.coroutine
async def g():
threads.add(current_thread()) # runs in anysync's global background thread
return h().run()
@anysync.coroutine
async def h():
threads.add(current_thread()) # runs in a new thread each time
return 42
f().run()
f().run()
main_thread = current_thread()
assert len(threads - {main_thread}) == 3
Interacting with contextvars
AnySync wrapped coroutines or context managers will not propagate changes to
contextvars
from async to
synchronous contexts. This is because contextvars
are not shared between threads or
event loops and AnySync must create these in order to run coroutines synchronously.
Given this, the following is not supported:
from contextvars import ContextVar
from anysync import anysync
var = ContextVar("var", default=0)
@anysync
async def f():
var.set(42)
f().run()
assert var.get() == 42 # AssertionError: 0 != 42
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