asyncio.Lock equivalent for multiple processes
Hi, I'm looking for a equivalent of asyncio.Lock ( https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern. For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout. Do I miss a new awesome library or do you have an easier approach ? Thanks for your responses. -- Ludovic Gasc (GMLudo)
Hi, I don't know if there is a third party solution for this. I think the closest you can get today using the standard library is using a multiprocessing.manager().Lock (which can be shared among processes) and call the lock.acquire() function with asyncio.run_in_executor(), using a ThreadedPoolExecutor to avoid blocking the asyncio event loop. Best regards, Roberto El mar., 17 abr. 2018 a las 0:05, Ludovic Gasc (<gmludo@gmail.com>) escribió:
Hi,
I'm looking for a equivalent of asyncio.Lock ( https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
Hi Roberto, Thanks for the pointer, it's exactly the type of feedbacks I'm looking for: Ideas that are out-of-box of my confort zone. However, in our use case, we are using gunicorn, that uses forks instead of multiprocessing to my knowledge, I can't use multiprocessing without to remove gunicorn. If somebody is using aioredlock in his project, I'm interested by feedbacks. Have a nice week. -- Ludovic Gasc (GMLudo) 2018-04-17 7:19 GMT+02:00 Roberto Martínez <robertomartinezp@gmail.com>:
Hi,
I don't know if there is a third party solution for this.
I think the closest you can get today using the standard library is using a multiprocessing.manager().Lock (which can be shared among processes) and call the lock.acquire() function with asyncio.run_in_executor(), using a ThreadedPoolExecutor to avoid blocking the asyncio event loop.
Best regards, Roberto
El mar., 17 abr. 2018 a las 0:05, Ludovic Gasc (<gmludo@gmail.com>) escribió:
Hi,
I'm looking for a equivalent of asyncio.Lock (https://docs.python.org/3/ library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
Hi, redis lock has own limitations and depending on your use case it may or may not be suitable [1]. If possible I would redefine problem and also considered: 1) create worker per specific resource type to avoid locking 2) optimistic locking 3) File system lock like in twisted, but not sure about performance and edge cases there 4) make operation on resource idempotent [1] http://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html [2] https://github.com/twisted/twisted/blob/e38cc25a67747899c6984d6ebaa8d3d13479... On Tue, 17 Apr 2018 at 13:01 Ludovic Gasc <gmludo@gmail.com> wrote:
Hi Roberto,
Thanks for the pointer, it's exactly the type of feedbacks I'm looking for: Ideas that are out-of-box of my confort zone. However, in our use case, we are using gunicorn, that uses forks instead of multiprocessing to my knowledge, I can't use multiprocessing without to remove gunicorn.
If somebody is using aioredlock in his project, I'm interested by feedbacks.
Have a nice week.
-- Ludovic Gasc (GMLudo)
2018-04-17 7:19 GMT+02:00 Roberto Martínez <robertomartinezp@gmail.com>:
Hi,
I don't know if there is a third party solution for this.
I think the closest you can get today using the standard library is using a multiprocessing.manager().Lock (which can be shared among processes) and call the lock.acquire() function with asyncio.run_in_executor(), using a ThreadedPoolExecutor to avoid blocking the asyncio event loop.
Best regards, Roberto
El mar., 17 abr. 2018 a las 0:05, Ludovic Gasc (<gmludo@gmail.com>) escribió:
Hi,
I'm looking for a equivalent of asyncio.Lock ( https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
Hi Nickolai, Thanks for your suggestions, especially for the file system lock: We don't have often locks, but we must be sure it's locked. For 1) and 4) suggestions, in fact we have several systems to sync and also a PostgreSQL transaction, the request must be treated by the same worker from beginning to end and the other systems aren't idempotent at all, it's "old-school" proprietary systems, good luck to change that ;-) Regards. -- Ludovic Gasc (GMLudo) 2018-04-17 12:46 GMT+02:00 Nickolai Novik <nickolainovik@gmail.com>:
Hi, redis lock has own limitations and depending on your use case it may or may not be suitable [1]. If possible I would redefine problem and also considered: 1) create worker per specific resource type to avoid locking 2) optimistic locking 3) File system lock like in twisted, but not sure about performance and edge cases there 4) make operation on resource idempotent
[1] http://martin.kleppmann.com/2016/02/08/how-to-do- distributed-locking.html [2] https://github.com/twisted/twisted/blob/e38cc25a67747899c6984d6ebaa8d3 d134799415/src/twisted/python/lockfile.py
On Tue, 17 Apr 2018 at 13:01 Ludovic Gasc <gmludo@gmail.com> wrote:
Hi Roberto,
Thanks for the pointer, it's exactly the type of feedbacks I'm looking for: Ideas that are out-of-box of my confort zone. However, in our use case, we are using gunicorn, that uses forks instead of multiprocessing to my knowledge, I can't use multiprocessing without to remove gunicorn.
If somebody is using aioredlock in his project, I'm interested by feedbacks.
Have a nice week.
-- Ludovic Gasc (GMLudo)
2018-04-17 7:19 GMT+02:00 Roberto Martínez <robertomartinezp@gmail.com>:
Hi,
I don't know if there is a third party solution for this.
I think the closest you can get today using the standard library is using a multiprocessing.manager().Lock (which can be shared among processes) and call the lock.acquire() function with asyncio.run_in_executor(), using a ThreadedPoolExecutor to avoid blocking the asyncio event loop.
Best regards, Roberto
El mar., 17 abr. 2018 a las 0:05, Ludovic Gasc (<gmludo@gmail.com>) escribió:
Hi,
I'm looking for a equivalent of asyncio.Lock ( https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
If you're already using PostgreSQL, you might also look at "advisory locks": https://www.postgresql.org/docs/current/static/explicit-locking.html#ADVISOR... --Chris On Tue, Apr 17, 2018 at 4:34 AM, Ludovic Gasc <gmludo@gmail.com> wrote:
Hi Nickolai,
Thanks for your suggestions, especially for the file system lock: We don't have often locks, but we must be sure it's locked.
For 1) and 4) suggestions, in fact we have several systems to sync and also a PostgreSQL transaction, the request must be treated by the same worker from beginning to end and the other systems aren't idempotent at all, it's "old-school" proprietary systems, good luck to change that ;-)
Regards. -- Ludovic Gasc (GMLudo)
2018-04-17 12:46 GMT+02:00 Nickolai Novik <nickolainovik@gmail.com>:
Hi, redis lock has own limitations and depending on your use case it may or may not be suitable [1]. If possible I would redefine problem and also considered: 1) create worker per specific resource type to avoid locking 2) optimistic locking 3) File system lock like in twisted, but not sure about performance and edge cases there 4) make operation on resource idempotent
[1] http://martin.kleppmann.com/2016/02/08/how-to-do-distributed-locking.html [2] https://github.com/twisted/twisted/blob/e38cc25a67747899c6984d6ebaa8d3d13479...
On Tue, 17 Apr 2018 at 13:01 Ludovic Gasc <gmludo@gmail.com> wrote:
Hi Roberto,
Thanks for the pointer, it's exactly the type of feedbacks I'm looking for: Ideas that are out-of-box of my confort zone. However, in our use case, we are using gunicorn, that uses forks instead of multiprocessing to my knowledge, I can't use multiprocessing without to remove gunicorn.
If somebody is using aioredlock in his project, I'm interested by feedbacks.
Have a nice week.
-- Ludovic Gasc (GMLudo)
2018-04-17 7:19 GMT+02:00 Roberto Martínez <robertomartinezp@gmail.com>:
Hi,
I don't know if there is a third party solution for this.
I think the closest you can get today using the standard library is using a multiprocessing.manager().Lock (which can be shared among processes) and call the lock.acquire() function with asyncio.run_in_executor(), using a ThreadedPoolExecutor to avoid blocking the asyncio event loop.
Best regards, Roberto
El mar., 17 abr. 2018 a las 0:05, Ludovic Gasc (<gmludo@gmail.com>) escribió:
Hi,
I'm looking for a equivalent of asyncio.Lock (https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
_______________________________________________ Async-sig mailing list Async-sig@python.org https://mail.python.org/mailman/listinfo/async-sig Code of Conduct: https://www.python.org/psf/codeofconduct/
Hi Ludovic, I believe it's relatively straightforward to implement the core functionality, if you can at first reduce it to: * allow only one coro to wait on lock at a given time (i.e. one user per process / event loop) * decide explicitly if you want other coros to continue (I assume so, as blocking entire process would be trivial) * don't care about performance too much :) Once that's done, you can allow multiple users per event loop by wrapping your inter-process lock in a regular async lock. Wrt. performance, you can start with a simple client-server implementation, for example where: * single-threaded server listens on some port, accepts 1 connection at a time, writes something on the connection and waits for connection to be closed * each client connects (not informative due to listen backlog) and waits for data, when client gets the data, it has the lock * when client wants to release the lock, it closes the connection, which unblocks the server * socket communication is relatively easy to marry to the event loop :) If you want high performance (i.e. low latency), you'd probably want to go with futex, but that may prove hard to marry to asyncio internals. I guess locking can always be proxied through a thread, at some cost to performance. If performance is important, I'd suggest starting with a thread proxy from the start. It could go like this: Each named lock gets own thread (in each process / event loop), a sync lock and condition variable. When a coro want to take the lock, it creates an empty Future, ephemerally takes the sync lock, adds this future to waiters, and signals on the condition variable and awaits this Future. Thread wakes up, validates there's someone in the queue under sync lock, tries to take classical inter-process lock (sysv or file or whatever), and when that succeeds, resolves the future using loop.call_soon_threadsafe(). I'm omitting implementation details, like what if Future is leaked (discarded before it's resolved), how release is orchestrated, etc. The key point is that offloading locking to a dedicated thread allows to reduce original problem to synchronous interprocess locking problem. Cheers! On 17 April 2018 at 06:05, Ludovic Gasc <gmludo@gmail.com> wrote:
Hi,
I'm looking for a equivalent of asyncio.Lock (https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
_______________________________________________ Async-sig mailing list Async-sig@python.org https://mail.python.org/mailman/listinfo/async-sig Code of Conduct: https://www.python.org/psf/codeofconduct/
Hi Dima, Thanks for your time and explanations :-) However, I have the intuition that it will take me more time to implement your idea compare to the builtin feature of PostgreSQL. Nevertheless, I keep your idea in mind in case of I have problems with PostgreSQL. Have a nice day. -- Ludovic Gasc (GMLudo) 2018-04-17 14:17 GMT+02:00 Dima Tisnek <dimaqq@gmail.com>:
Hi Ludovic,
I believe it's relatively straightforward to implement the core functionality, if you can at first reduce it to: * allow only one coro to wait on lock at a given time (i.e. one user per process / event loop) * decide explicitly if you want other coros to continue (I assume so, as blocking entire process would be trivial) * don't care about performance too much :)
Once that's done, you can allow multiple users per event loop by wrapping your inter-process lock in a regular async lock.
Wrt. performance, you can start with a simple client-server implementation, for example where: * single-threaded server listens on some port, accepts 1 connection at a time, writes something on the connection and waits for connection to be closed * each client connects (not informative due to listen backlog) and waits for data, when client gets the data, it has the lock * when client wants to release the lock, it closes the connection, which unblocks the server * socket communication is relatively easy to marry to the event loop :)
If you want high performance (i.e. low latency), you'd probably want to go with futex, but that may prove hard to marry to asyncio internals. I guess locking can always be proxied through a thread, at some cost to performance.
If performance is important, I'd suggest starting with a thread proxy from the start. It could go like this: Each named lock gets own thread (in each process / event loop), a sync lock and condition variable. When a coro want to take the lock, it creates an empty Future, ephemerally takes the sync lock, adds this future to waiters, and signals on the condition variable and awaits this Future. Thread wakes up, validates there's someone in the queue under sync lock, tries to take classical inter-process lock (sysv or file or whatever), and when that succeeds, resolves the future using loop.call_soon_threadsafe(). I'm omitting implementation details, like what if Future is leaked (discarded before it's resolved), how release is orchestrated, etc. The key point is that offloading locking to a dedicated thread allows to reduce original problem to synchronous interprocess locking problem.
Cheers!
On 17 April 2018 at 06:05, Ludovic Gasc <gmludo@gmail.com> wrote:
Hi,
I'm looking for a equivalent of asyncio.Lock (https://docs.python.org/3/library/asyncio-sync.html#asyncio.Lock) but shared between several processes on the same server, because I'm migrating a daemon from mono-worker to multi-worker pattern.
For now, the closest solution in term of API seems aioredlock: https://github.com/joanvila/aioredlock#aioredlock But I'm not a big fan to use polling nor with a timeout because the lock I need is very critical, I prefer to block the code than unlock with timeout.
Do I miss a new awesome library or do you have an easier approach ?
Thanks for your responses. -- Ludovic Gasc (GMLudo)
_______________________________________________ Async-sig mailing list Async-sig@python.org https://mail.python.org/mailman/listinfo/async-sig Code of Conduct: https://www.python.org/psf/codeofconduct/
participants (5)
-
Chris Jerdonek -
Dima Tisnek -
Ludovic Gasc -
Nickolai Novik -
Roberto Martínez