[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Petr, thanks for clearly stating your interests and goals for subinterpreters. This lays to rest some of my own fears. I am still skeptical that (even after the GIL is separated) they will enable multi-core in ways that multiple processes couldn't handle just as well or better, but your clear statement that *embedding* is the more important use case helps me feel supportive of the concept. On Tue, Jun 9, 2020 at 6:26 AM Petr Viktorin wrote: > On 2020-06-05 16:32, Mark Shannon wrote: > > Hi, > > > > There have been a lot of changes both to the C API and to internal > > implementations to allow multiple interpreters in a single O/S process. > > > > These changes cause backwards compatibility changes, have a negative > > performance impact, and cause a lot of churn. > > > > While I'm in favour of PEP 554, or some similar model for parallelism in > > Python, I am opposed to the changes we are currently making to support > it. > > > > > > What are sub-interpreters? > > -- > > > > A sub-interpreter is a logically independent Python process which > > supports inter-interpreter communication built on shared memory and > > channels. Passing of Python objects is supported, but only by copying, > > not by reference. Data can be shared via buffers. > > Here's my biased take on the subject: > > Interpreters are contexts in which Python runs. They contain > configuration (e.g. the import path) and runtime state (e.g. the set of > imported modules). An interpreter is created at Python startup > (Py_InitializeEx), and you can create/destroy additional ones with > Py_NewInterpreter/Py_EndInterpreter. > This is long-standing API that is used, most notably by mod_wsgi. > > Many extension modules and some stdlib modules don't play well with the > existence of multiple interpreters in a process, mainly because they use > process-global state (C static variables) rather than some more granular > scope. > This tends to result in nasty bugs (C-level crashes) when multiple > interpreters are started in parallel (Py_NewInterpreter) or in sequence > (several Py_InitializeEx/Py_FinalizeEx cycles). The bugs are similar in > both cases. > > Whether Python interpreters run sequentially or in parallel, having them > work will enable a use case I would like to see: allowing me to call > Python code from wherever I want, without thinking about global state. > Think calling Python from an utility library that doesn't care about the > rest of the application it's used in. I personally call this "the Lua > use case", because light-weight, worry-free embedding is an area where > Python loses to Lua. (And JS as well—that's a relatively recent > development, but much more worrying.) > > The part I have been involved in is moving away from process-global > state. Process-global state can be made to work, but it is much safer to > always default to module-local state (roughly what Python-language's > `global` means), and treat process-global state as exceptions one has to > think through. The API introduced in PEPs 384, 489, 573 (and future > planned ones) aims to make module-local state possible to use, then > later easy to use, and the natural default. > > Relatively recently, there is an effort to expose interpreter creation & > finalization from Python code, and also to allow communication between > them (starting with something rudimentary, sharing buffers). There is > also a push to explore making the GIL per-interpreter, which ties in to > moving away from process-global state. Both are interesting ideas, but > (like banishing global state) not the whole motivation for > changes/additions. It's probably possible to do similar things with > threads or subprocesses, sure, but if these efforts went away, the other > issues would remain. > > I am not too fond of the term "sub-interpreters", because it implies > some kind of hierarchy. Of course, if interpreter creation is exposed to > Python, you need some kind of "parent" to start the "child" and get its > result when done. Also, due to some practical issues you might (sadly, > currently) need some notion of "the main interpreter". But ideally, we > can make interpreters entirely independent to allow the "Lua use case". > In the end-game of these efforts, I see Py_NewInterpreter transparently > calling Py_InitializeEx if global state isn't set up yet, and similarly, > Py_EndInterpreter turning the lights off if it's the last one out. > ___ > Python-Dev mailing list -- python-dev@python.org > To unsubscribe send an email to python-dev-le...@python.org > https://mail.python.org/mailman3/lists/python-dev.python.org/ > Message archived at > https://mail.python.org/archives/list/python-dev@python.org/message/NLITVUIZQSUJ2F6XDTPMD7IP7FGTMNBA/ > Code of Conduct: http://python.org/psf/codeofconduct/ > -- --Guido van Rossum (python.org/~guido) *Pronouns: he/him **(why is my pronoun here?)*
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Tue, Jun 9, 2020 at 10:28 PM Petr Viktorin wrote: > > Relatively recently, there is an effort to expose interpreter creation & > finalization from Python code, and also to allow communication between > them (starting with something rudimentary, sharing buffers). There is > also a push to explore making the GIL per-interpreter, which ties in to > moving away from process-global state. Both are interesting ideas, but > (like banishing global state) not the whole motivation for > changes/additions. > Some changes for per interpreter GIL doesn't help sub interpreters so much. For example, isolating memory allocator including free list and constants between sub interpreter makes sub interpreter fatter. I assume Mark is talking about such changes. Now Victor proposing move dict free list per interpreter state and the code looks good to me. This is a change for per interpreter GIL, but not for sub interpreters. https://github.com/python/cpython/pull/20645 Should we commit this change to the master branch? Or should we create another branch for such changes? Regards, -- Inada Naoki ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/L7JRFJLDLO6E4SDXYKDPTEIEDZK2PNR4/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 2020-06-10 04:43, Inada Naoki wrote: On Tue, Jun 9, 2020 at 10:28 PM Petr Viktorin wrote: Relatively recently, there is an effort to expose interpreter creation & finalization from Python code, and also to allow communication between them (starting with something rudimentary, sharing buffers). There is also a push to explore making the GIL per-interpreter, which ties in to moving away from process-global state. Both are interesting ideas, but (like banishing global state) not the whole motivation for changes/additions. Some changes for per interpreter GIL doesn't help sub interpreters so much. For example, isolating memory allocator including free list and constants between sub interpreter makes sub interpreter fatter. I assume Mark is talking about such changes. Now Victor proposing move dict free list per interpreter state and the code looks good to me. This is a change for per interpreter GIL, but not for sub interpreters. https://github.com/python/cpython/pull/20645 Should we commit this change to the master branch? Or should we create another branch for such changes? I think that most of all, the changes aimed at breaking up the GIL need a PEP, so that everyone knows what the changes are actually about -- and especially so that everyone knows the changes are happening. Note that neither PEP 554 (which itself isn't accepted yet) nor PEP 573 is related to breaking up the GIL. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/I4DURF74SJZ3PEILBWDVR2XHOZQKRZRH/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi, I agree that embedding Python is an important use case and that we should try to leak less memory and better isolate multiple interpreters for this use case. There are multiple projects to enhance code to make it work better with multiple interpreters: * convert C extension modules to multiphase initialization (PEP 489) * move C extension module global variables (static ...) into a module state * convert static types to heap types * make free lists per interpreter * etc. From what I saw, the first side effect is that "suddenly", tests using subinterpreters start to report new reference leaks. Examples of issues and fixes: * https://github.com/python/cpython/commit/18a90248fdd92b27098cc4db773686a2d10a4d24: reference leak in the init function of the select module * https://github.com/python/cpython/commit/310e2d25170a88ef03f6fd31efcc899fe062da2c: reference cycles with encodings and _testcapi misuses PyModule_AddObject() * https://bugs.python.org/issue40050: _weakref and importlib * etc. In fact, none of these bugs is not new. I checked for a few: bugs were always there. It's just that previously, nobody paid attention to these leaks. Fixing subinterpreters helps to leak less memory even for the single interpreter (embed Python) use case. The problem is that Python never tried to clear everything at exit. One way to see the issue is the number of references at exit using a debug build, on the up-to-date master branch: $ ./python -X showrefcount -c pass [18645 refs, 6141 blocks] Python leaks 18,645 references at exit. Some of the work that I listed is tracked by https://bugs.python.org/issue1635741 which was created in 2007: "Py_Finalize() doesn't clear all Python objects at exit". Another way to see the issue is: $ PYTHONMALLOC=malloc valgrind ./python -c pass (...) ==169747== LEAK SUMMARY: ==169747==definitely lost: 48 bytes in 2 blocks ==169747==indirectly lost: 136 bytes in 6 blocks ==169747== possibly lost: 700,552 bytes in 5,677 blocks ==169747==still reachable: 5,450 bytes in 48 blocks ==169747== suppressed: 0 bytes in 0 blocks Python leaks around 700 KB at exit. Even if you ignore the "run multiple interpreters in parallel" and PEP 554 use cases, enhancing code to better work with subinterpreters also makes Python a better library to embed in applications and so is useful. Victor Le mer. 10 juin 2020 à 04:46, Inada Naoki a écrit : > > On Tue, Jun 9, 2020 at 10:28 PM Petr Viktorin wrote: > > > > Relatively recently, there is an effort to expose interpreter creation & > > finalization from Python code, and also to allow communication between > > them (starting with something rudimentary, sharing buffers). There is > > also a push to explore making the GIL per-interpreter, which ties in to > > moving away from process-global state. Both are interesting ideas, but > > (like banishing global state) not the whole motivation for > > changes/additions. > > > > Some changes for per interpreter GIL doesn't help sub interpreters so much. > For example, isolating memory allocator including free list and > constants between > sub interpreter makes sub interpreter fatter. > I assume Mark is talking about such changes. > > Now Victor proposing move dict free list per interpreter state and the code > looks good to me. This is a change for per interpreter GIL, but not > for sub interpreters. > https://github.com/python/cpython/pull/20645 > > Should we commit this change to the master branch? > Or should we create another branch for such changes? > > Regards, > -- > Inada Naoki > ___ > Python-Dev mailing list -- python-dev@python.org > To unsubscribe send an email to python-dev-le...@python.org > https://mail.python.org/mailman3/lists/python-dev.python.org/ > Message archived at > https://mail.python.org/archives/list/python-dev@python.org/message/L7JRFJLDLO6E4SDXYKDPTEIEDZK2PNR4/ > Code of Conduct: http://python.org/psf/codeofconduct/ -- Night gathers, and now my watch begins. It shall not end until my death. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/INREEYUJLL47R4ZGJ2GGJDZSPX2ORMA6/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi Petr, On 09/06/2020 2:24 pm, Petr Viktorin wrote: On 2020-06-05 16:32, Mark Shannon wrote: Hi, There have been a lot of changes both to the C API and to internal implementations to allow multiple interpreters in a single O/S process. These changes cause backwards compatibility changes, have a negative performance impact, and cause a lot of churn. While I'm in favour of PEP 554, or some similar model for parallelism in Python, I am opposed to the changes we are currently making to support it. What are sub-interpreters? -- A sub-interpreter is a logically independent Python process which supports inter-interpreter communication built on shared memory and channels. Passing of Python objects is supported, but only by copying, not by reference. Data can be shared via buffers. Here's my biased take on the subject: Interpreters are contexts in which Python runs. They contain configuration (e.g. the import path) and runtime state (e.g. the set of imported modules). An interpreter is created at Python startup (Py_InitializeEx), and you can create/destroy additional ones with Py_NewInterpreter/Py_EndInterpreter. This is long-standing API that is used, most notably by mod_wsgi. Many extension modules and some stdlib modules don't play well with the existence of multiple interpreters in a process, mainly because they use process-global state (C static variables) rather than some more granular scope. This tends to result in nasty bugs (C-level crashes) when multiple interpreters are started in parallel (Py_NewInterpreter) or in sequence (several Py_InitializeEx/Py_FinalizeEx cycles). The bugs are similar in both cases. Whether Python interpreters run sequentially or in parallel, having them work will enable a use case I would like to see: allowing me to call Python code from wherever I want, without thinking about global state. Think calling Python from an utility library that doesn't care about the rest of the application it's used in. I personally call this "the Lua use case", because light-weight, worry-free embedding is an area where Python loses to Lua. (And JS as well—that's a relatively recent development, but much more worrying.) This seems like a worthwhile goal. However I don't see why this requires having multiple Python interpreters in a single O/S process. The part I have been involved in is moving away from process-global state. Process-global state can be made to work, but it is much safer to always default to module-local state (roughly what Python-language's `global` means), and treat process-global state as exceptions one has to think through. The API introduced in PEPs 384, 489, 573 (and future planned ones) aims to make module-local state possible to use, then later easy to use, and the natural default. I don't agree. Process level state is *much* safer than module-local state. Suppose two interpreters, have both imported the same module. By using O/S processes to keep the interpreters separate, the hardware prevents the two copies of the module from interfering with each other. By sharing an address space the separation is maintained by trust and hoping that third party modules don't have too many bugs. I don't see how you can claim the later case if safer. Relatively recently, there is an effort to expose interpreter creation & finalization from Python code, and also to allow communication between them (starting with something rudimentary, sharing buffers). There is also a push to explore making the GIL per-interpreter, which ties in to moving away from process-global state. Both are interesting ideas, but (like banishing global state) not the whole motivation for changes/additions. It's probably possible to do similar things with threads or subprocesses, sure, but if these efforts went away, the other issues would remain. What other issues? Please be specific. I am not too fond of the term "sub-interpreters", because it implies some kind of hierarchy. Of course, if interpreter creation is exposed to Python, you need some kind of "parent" to start the "child" and get its result when done. Also, due to some practical issues you might (sadly, currently) need some notion of "the main interpreter". But ideally, we can make interpreters entirely independent to allow the "Lua use case". In the end-game of these efforts, I see Py_NewInterpreter transparently calling Py_InitializeEx if global state isn't set up yet, and similarly, Py_EndInterpreter turning the lights off if it's the last one out. I'll drop the "sub" from now on :) If each interpreter runs in its own process, then initializing an interpreter and initializing the "global" state are the same thing and wouldn't need a separate step. Cheers, Mark. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Wed, Jun 10, 2020 at 5:37 AM Mark Shannon wrote: > By sharing an address space the separation is maintained by trust and hoping that third party modules don't have too many bugs. By definition, the use of any third-party module (or even the standard library itself) is by trust and the hope that they don't have too many bugs. Sure, this creates a potential new class of bugs, for those who use it, while also offering the chance to find and fix old bugs like Victor found. Mostly, though, it exposes lots of bad practices that people could mostly get away with as long as the assumption was that everything would always be single-threaded, single-process, and the entire software industry is moving away from those assumptions, so it's only logical that Python takes advantage of that shift instead of becoming another legacy language. In the meantime, modules can explicitly label themselves as single-interpreter only, requiring multiprocessing instead of threading or embedding to work correctly. Modules were more than happy to label themselves as 2.x only for a decade -Em ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/JKELVIZHMZRS4VPBNJFWSP5POACQ4ODU/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/10/2020 8:33 AM, Mark Shannon wrote: Hi Petr, On 09/06/2020 2:24 pm, Petr Viktorin wrote: On 2020-06-05 16:32, Mark Shannon wrote: Whether Python interpreters run sequentially or in parallel, having them work will enable a use case I would like to see: allowing me to call Python code from wherever I want, without thinking about global state. Think calling Python from an utility library that doesn't care about the rest of the application it's used in. I personally call this "the Lua use case", because light-weight, worry-free embedding is an area where Python loses to Lua. (And JS as well—that's a relatively recent development, but much more worrying.) This seems like a worthwhile goal. However I don't see why this requires having multiple Python interpreters in a single O/S process. I assume it would be so that my code could link with library A, which embeds Python, and library B, which also embeds Python. A and B have no knowledge of each other. The part I have been involved in is moving away from process-global state. Process-global state can be made to work, but it is much safer to always default to module-local state (roughly what Python-language's `global` means), and treat process-global state as exceptions one has to think through. The API introduced in PEPs 384, 489, 573 (and future planned ones) aims to make module-local state possible to use, then later easy to use, and the natural default. I don't agree. Process level state is *much* safer than module-local state. Suppose two interpreters, have both imported the same module. By using O/S processes to keep the interpreters separate, the hardware prevents the two copies of the module from interfering with each other. By sharing an address space the separation is maintained by trust and hoping that third party modules don't have too many bugs. I don't see how you can claim the later case if safer. I've always assumed that per-module state meant per-module, per-interpreter. Maybe I've misunderstood, in which case I agree with Mark. If per-module state isn't isolated per interpreter, that sort of kills the multiple interpreter model, in my mind. Eric ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/WOOPV4QKFFZSZ5QVXMC3JBEHPTVULH4S/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
> On 10 Jun 2020, at 14:33, Mark Shannon wrote: > > Hi Petr, > > On 09/06/2020 2:24 pm, Petr Viktorin wrote: >> On 2020-06-05 16:32, Mark Shannon wrote: >>> Hi, >>> >>> There have been a lot of changes both to the C API and to internal >>> implementations to allow multiple interpreters in a single O/S process. >>> >>> These changes cause backwards compatibility changes, have a negative >>> performance impact, and cause a lot of churn. >>> >>> While I'm in favour of PEP 554, or some similar model for parallelism in >>> Python, I am opposed to the changes we are currently making to support it. >>> >>> >>> What are sub-interpreters? >>> -- >>> >>> A sub-interpreter is a logically independent Python process which supports >>> inter-interpreter communication built on shared memory and channels. >>> Passing of Python objects is supported, but only by copying, not by >>> reference. Data can be shared via buffers. >> Here's my biased take on the subject: >> Interpreters are contexts in which Python runs. They contain configuration >> (e.g. the import path) and runtime state (e.g. the set of imported modules). >> An interpreter is created at Python startup (Py_InitializeEx), and you can >> create/destroy additional ones with Py_NewInterpreter/Py_EndInterpreter. >> This is long-standing API that is used, most notably by mod_wsgi. >> Many extension modules and some stdlib modules don't play well with the >> existence of multiple interpreters in a process, mainly because they use >> process-global state (C static variables) rather than some more granular >> scope. >> This tends to result in nasty bugs (C-level crashes) when multiple >> interpreters are started in parallel (Py_NewInterpreter) or in sequence >> (several Py_InitializeEx/Py_FinalizeEx cycles). The bugs are similar in both >> cases. >> Whether Python interpreters run sequentially or in parallel, having them >> work will enable a use case I would like to see: allowing me to call Python >> code from wherever I want, without thinking about global state. Think >> calling Python from an utility library that doesn't care about the rest of >> the application it's used in. I personally call this "the Lua use case", >> because light-weight, worry-free embedding is an area where Python loses to >> Lua. (And JS as well—that's a relatively recent development, but much more >> worrying.) > > This seems like a worthwhile goal. However I don't see why this requires > having multiple Python interpreters in a single O/S process. The mod_wsgi use case seems to require this (he writes without having looked at its source code). I have another possible use case: Independent plugins written in Python in native applications written in other languages. That doesn’t mean that is worthwhile to complicate the CPython code base for these. I have no opinion on that, both because I haven’t been active for a while and because I haven’t looked at the impact the current work has had. Ronald — Twitter / micro.blog: @ronaldoussoren Blog: https://blog.ronaldoussoren.net/___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/GLKVB4JNZCZCXHNCF4F6VUBF7V6NKN5F/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi, as an user, the "lua use case" is right what I need at work. I realize that for python this is a niche case, and most users don't need any of this, but I hope it will useful to understand why having multiple independent interpreters in a single process can be an essential feature. The company I work for develop and sells a big C++ financial system with python embedded, providing critical flexibility to our customers. Python is used as a scripting language, with most cases having C++ calling a python script itself calling other C++ functions. Most of the times those scripts are in workloads I/O bound or where the time spent in python is negligible. But some workloads are really cpu bound and those tend to become GIL-bound, even with massive use of C++ helpers; some to the point that GIL-contention makes up over 80% of running time, instead of 1-5%. And every time our customers upgrade their server, they buy machines with more cores and the contention problem worsens. Obviously, our use case calls for per-thread separate interpreters: server processes run continuously and already consume gigabytes of RAM, so startup time or increased memory consumption are not issues. Shared state also is not needed, actually we try to avoid it as much as possible. In the end, removing process-global state is extremely interesting for us. Thank you, Riccardo ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/D6OSXZ7B6IAFPZN5VMZ6AEIWRPVO55I4/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Eric V. Smith wrote: > On 6/10/2020 8:33 AM, Mark Shannon wrote: > > Hi Petr, > > On 09/06/2020 2:24 pm, Petr Viktorin wrote: > > On 2020-06-05 16:32, Mark Shannon wrote: > > Whether Python interpreters run sequentially or in parallel, having > > them work will enable a use case I would like to see: allowing me to > > call Python code from wherever I want, without thinking about global > > state. Think calling Python from an utility library that doesn't care > > about the rest of the application it's used in. I personally call > > this "the Lua use case", because light-weight, worry-free embedding > > is an area where Python loses to Lua. (And JS as well—that's a > > relatively recent development, but much more worrying.) > > This seems like a worthwhile goal. However I don't see why this > > requires having multiple Python interpreters in a single O/S process. > > I assume it would be so that my code could link with library A, which > embeds Python, and library B, which also embeds Python. A and B have no > knowledge of each other. > > The part I > > have been involved in is moving away from process-global > > state. Process-global state can be made to work, but it is much safer > > to always default to module-local state (roughly what > > Python-language's global means), and treat process-global state as > > exceptions one has to think through. The API introduced in PEPs 384, > > 489, 573 (and future planned ones) aims to make module-local state > > possible to use, then later easy to use, and the natural default. > > I don't agree. Process level state is much safer than module-local > > state. > > Suppose two interpreters, have both imported the same module. > > By using O/S processes to keep the interpreters separate, the hardware > > prevents the two copies of the module from interfering with each other. > > By sharing an address space the separation is maintained by trust and > > hoping that third party modules don't have too many bugs. > > I don't see how you can claim the later case if safer. > > I've always assumed that per-module state meant per-module, > per-interpreter. It _can_, but it isn't guaranteed because we are talking about C here and people do "interesting" things when they are handed that much flexibility. 😉 Plus a bunch of work has been done in the last few years to make per-interpreter state for modules be supported. -Brett > Maybe I've misunderstood, in which case I agree with > Mark. If per-module state isn't isolated per interpreter, that sort of > kills the multiple interpreter model, in my mind. > Eric ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/WEVPITVEFX72ONIEOJ5VQZSGOCPSRLSQ/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi Riccardo, On 10/06/2020 5:51 pm, Riccardo Ghetta wrote: Hi, as an user, the "lua use case" is right what I need at work. I realize that for python this is a niche case, and most users don't need any of this, but I hope it will useful to understand why having multiple independent interpreters in a single process can be an essential feature. The company I work for develop and sells a big C++ financial system with python embedded, providing critical flexibility to our customers. Python is used as a scripting language, with most cases having C++ calling a python script itself calling other C++ functions. Most of the times those scripts are in workloads I/O bound or where the time spent in python is negligible. > But some workloads are really cpu bound and those tend to become GIL-bound, even with massive use of C++ helpers; some to the point that GIL-contention makes up over 80% of running time, instead of 1-5%. And every time our customers upgrade their server, they buy machines with more cores and the contention problem worsens. Different interpreters need to operate in their own isolated address space, or there will be horrible race conditions. Regardless of whether that separation is done in software or hardware, it has to be done. Whenever data contained in a Python object is passed to C/C++ code, there are two ways to do it. Either pass the whole object, or a reference to the underlying data. By passing the underlying data, you can release the GIL, and your problem is solved, or at least alleviated. If you can't do that, and must pass the object, then all accesses to that object must be protected by a per-interpreter lock. That's because interpreters need to operate serially, or you'll get horrible race conditions. If you need to share objects across threads, then there will be contention, regardless of how many interpreters there are, or which processes they are in. Obviously, our use case calls for per-thread separate interpreters: server processes run continuously and already consume gigabytes of RAM, so startup time or increased memory consumption are not issues. Shared state also is not needed, actually we try to avoid it as much as possible. In the end, removing process-global state is extremely interesting for us. If the additional resource consumption is irrelevant, what's the objection to spinning up a new processes? Cheers, Mark. P.S. Do try passing the underlying data, not the whole object, and dropping the GIL when calling back into C++. It can be effective. CPython already drops the GIL for some computational workloads implemented in C, like compression. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/6KYRUABTLNYNGNRBS5KRKPHKLKS2AI7U/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hello Mark, and thanks for your suggestions. However, I'm afraid I haven't explained our use of python well enough. On 11/06/2020 12:59, Mark Shannon wrote: If you need to share objects across threads, then there will be contention, regardless of how many interpreters there are, or which processes they are in. As a rule, we don't use that many python objects. Most of the time a script calls C++ functions, operating on C++ data. Perhaps with a small snippet I will explain myself better : hcpi='INFLEUR' n_months=3 base_infl=hs_base(hcpi, n_months, 0) im=hs_fs(hcpi,'sia','m',n_months,0) ip=hs_fs(hcpi,'sia','m',n_months-1,0) ir=im+(hs_range()[1].day-1)/month_days(hs_range()[1])*(ip-im) return ir/base_infl # double this is a part of a inflation estimation used in pricing an inflation-linked bond. hcpi and n_months are really parameters of the script and the hs_ functions are all implemented in C++. Some are very small and fast like hs_range, others are much more complex and slow (hs_fs), so we wrap them with Py_BEGIN_ALLOW_THREADS/Py_END_ALLOW_THREADS. As you see, here python is used more to direct C++, than manipulate objects. At GUI level things work a bit differently, but here we just tried to avoid building and destroying a lot of ephemeral python objects (unneeded anyway, because all subsequent processing is done by C++). This python script is only a part of a larger processing done in parallel by several threads, each operating in distinct instruments. Evaluating an instrument could involve zero, one, or several of those scripts. During evaluation an instrument is bound to a single thread, so from the point of view of python threads share nothing. If the additional resource consumption is irrelevant, what's the objection to spinning up a new processes? The additional resource consumption of a new python interpreter is irrelevant, but the process as a whole needs a lot of extra data making a new process rather costly. Plus there are issues of licensing, synchronization and load balancing that are much easier to resolve (for our system, at least) with threads than processes. Still, we /do/ use multiple processes, but those tend to be across administrative boundaries, or for very specific issues. Ciao, Riccardo ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/MJGGZ5HOBC5KTMQ5CPFI4NX6YYTD34F3/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
In fairness, if the process is really exiting, the OS should clear that out. Even if it is embedded, the embedding process could just release (or zero out) the entire memory allocation. I personally like plugging those leaks, but it does feel like putting purity over practicality. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/YOSDQDIXDKKG76XPBKPE4DZVTBEIDBJQ/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 11/06/2020 2:50 pm, Riccardo Ghetta wrote: Hello Mark, and thanks for your suggestions. However, I'm afraid I haven't explained our use of python well enough. On 11/06/2020 12:59, Mark Shannon wrote: If you need to share objects across threads, then there will be contention, regardless of how many interpreters there are, or which processes they are in. As a rule, we don't use that many python objects. Most of the time a script calls C++ functions, operating on C++ data. Perhaps with a small snippet I will explain myself better : hcpi='INFLEUR' n_months=3 base_infl=hs_base(hcpi, n_months, 0) im=hs_fs(hcpi,'sia','m',n_months,0) ip=hs_fs(hcpi,'sia','m',n_months-1,0) ir=im+(hs_range()[1].day-1)/month_days(hs_range()[1])*(ip-im) return ir/base_infl # double this is a part of a inflation estimation used in pricing an inflation-linked bond. hcpi and n_months are really parameters of the script and the hs_ functions are all implemented in C++. Some are very small and fast like hs_range, others are much more complex and slow (hs_fs), so we wrap them with Py_BEGIN_ALLOW_THREADS/Py_END_ALLOW_THREADS. As you see, here python is used more to direct C++, than manipulate objects. At GUI level things work a bit differently, but here we just tried to avoid building and destroying a lot of ephemeral python objects (unneeded anyway, because all subsequent processing is done by C++). This python script is only a part of a larger processing done in parallel by several threads, each operating in distinct instruments. Evaluating an instrument could involve zero, one, or several of those scripts. During evaluation an instrument is bound to a single thread, so from the point of view of python threads share nothing. If the additional resource consumption is irrelevant, what's the objection to spinning up a new processes? The additional resource consumption of a new python interpreter is irrelevant, but the process as a whole needs a lot of extra data making a new process rather costly. Starting a new process is cheap. On my machine, starting a new Python process takes under 1ms and uses a few Mbytes. The overhead largely comes from what you do with the process. The additional cost of starting a new interpreter is the same regardless of whether it is in the same process or not. There should be no need to start a new application process for a new Python interpreter. Plus there are issues of licensing, synchronization and load balancing that are much easier to resolve (for our system, at least) with threads than processes. Would this prevent CPython starting new processes, or is this just for processes managed by your application? Still, we /do/ use multiple processes, but those tend to be across administrative boundaries, or for very specific issues. Ciao, Riccardo ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/2AG665AKKLNYOXO2RNE53TOQ626PBIM7/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote: > Starting a new process is cheap. On my machine, starting a new Python > process takes under 1ms and uses a few Mbytes. Is that on Windows or Unix? Traditionally, process creation has been costly on Windows, which is why threads, and in-process solutions in general, tend to be more common on that platform. I haven't done experiments recently, but I do tend to avoid multiprocess-type solutions on Windows "just in case". I know that evaluating a new feature based on unsubstantiated assumptions informed by "it used to be like this" is ill-advised, but so is assuming that everything will be OK based on experience on a single platform :-) Personally, I'm in favour of multiple interpreter support mostly for the same reasons as Petr (easy embedding, in the style of Lua). Exposing interpreters to Python, and per-interpreter GILs, strike me as really interesting areas for experimentation, but I'm reserving final judgement on the practical benefits until we have working code and some practical experience. The incremental costs for those are low, though, as the bulk of the work is actually needed for the "easy embedding" use case. Paul ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/ZSNO3WRBWLE76W7K4CQSIEWPQIN5AJDG/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/12/2020 5:08 AM, Paul Moore wrote:
> On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote:
>> Starting a new process is cheap. On my machine, starting a new Python
>> process takes under 1ms and uses a few Mbytes.
> Is that on Windows or Unix? Traditionally, process creation has been
> costly on Windows, which is why threads, and in-process solutions in
> general, tend to be more common on that platform. I haven't done
> experiments recently, but I do tend to avoid multiprocess-type
> solutions on Windows "just in case". I know that evaluating a new
> feature based on unsubstantiated assumptions informed by "it used to
> be like this" is ill-advised, but so is assuming that everything will
> be OK based on experience on a single platform :-)
Here's a test on Windows 10, 4 logical cpus, 8 GB of ram:
>>> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
>>> globals=globals())
0.62975287
>>> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
>>> globals=globals())
40.28172119964
Or this way:
>>> timeit.timeit("""os.system('python.exe -c "exit()"')""",number=100,
>>> globals=globals())
17.46125929995
--Edwin
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/12/2020 6:18 AM, Edwin Zimmerman wrote:
> On 6/12/2020 5:08 AM, Paul Moore wrote:
>> On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote:
>>> Starting a new process is cheap. On my machine, starting a new Python
>>> process takes under 1ms and uses a few Mbytes.
>> Is that on Windows or Unix? Traditionally, process creation has been
>> costly on Windows, which is why threads, and in-process solutions in
>> general, tend to be more common on that platform. I haven't done
>> experiments recently, but I do tend to avoid multiprocess-type
>> solutions on Windows "just in case". I know that evaluating a new
>> feature based on unsubstantiated assumptions informed by "it used to
>> be like this" is ill-advised, but so is assuming that everything will
>> be OK based on experience on a single platform :-)
> Here's a test on Windows 10, 4 logical cpus, 8 GB of ram:
>
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
globals=globals())
> 0.62975287
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
globals=globals())
> 40.28172119964
>
> Or this way:
timeit.timeit("""os.system('python.exe -c "exit()"')""",number=100,
globals=globals())
> 17.46125929995
>
> --Edwin
For comparison, on a single core linux cloud server with 512 mb of ram:
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
globals=globals())
0.354354709998006
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
globals=globals())
3.847851719998289
So yeah, process creation is still rather costly on Windows.
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 12Jun2020 1008, Paul Moore wrote: On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote: Starting a new process is cheap. On my machine, starting a new Python process takes under 1ms and uses a few Mbytes. Is that on Windows or Unix? Traditionally, process creation has been costly on Windows, which is why threads, and in-process solutions in general, tend to be more common on that platform. I haven't done experiments recently, but I do tend to avoid multiprocess-type solutions on Windows "just in case". I know that evaluating a new feature based on unsubstantiated assumptions informed by "it used to be like this" is ill-advised, but so is assuming that everything will be OK based on experience on a single platform :-) It's still like that, though I'm actively involved in trying to get it improved. However, it's unlikely at this point to ever get to equivalence with Unix - Windows just sets up too many features (security, isolation, etc.) at the process boundary rather than other parts of the lifecycle. It's also *incredibly arrogant* to insist that users rewrite their applications to suit Python, rather than us doing the work to fit their needs. That's not how being a libraries/runtime developer works. Our responsibility is to humbly do the work that will benefit our users, not to find ways to put in the least possible effort and use the rest for blame-shifting. Some of us do much more talking than listening, and it does not pass unnoticed. Cheers, Steve ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/YYBRXYCIQE4B2NDOP3UT7AYR54DQVZCQ/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/11/2020 6:59 AM, Mark Shannon wrote: Hi Riccardo, On 10/06/2020 5:51 pm, Riccardo Ghetta wrote: Hi, as an user, the "lua use case" is right what I need at work. I realize that for python this is a niche case, and most users don't need any of this, but I hope it will useful to understand why having multiple independent interpreters in a single process can be an essential feature. The company I work for develop and sells a big C++ financial system with python embedded, providing critical flexibility to our customers. Python is used as a scripting language, with most cases having C++ calling a python script itself calling other C++ functions. Most of the times those scripts are in workloads I/O bound or where the time spent in python is negligible. > But some workloads are really cpu bound and those tend to become GIL-bound, even with massive use of C++ helpers; some to the point that GIL-contention makes up over 80% of running time, instead of 1-5%. And every time our customers upgrade their server, they buy machines with more cores and the contention problem worsens. Different interpreters need to operate in their own isolated address space, or there will be horrible race conditions. Regardless of whether that separation is done in software or hardware, it has to be done. I realize this is true now, but why must it always be true? Can't we fix this? At least one solution has been proposed: passing around a pointer to the current interpreter. I realize there issues here, like callbacks and signals that will need to be worked out. But I don't think it's axiomatically true that we'll always have race conditions with multiple interpreters in the same address space. Eric ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/BNBNEVUN6SLRUEQQ57SUAMP6PCCONFXF/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi Edwin,
Thanks for providing some concrete numbers.
Is it expected that creating 100 processes takes 6.3ms per process, but
that creating 1000 process takes 40ms per process? That's over 6 times
as long in the latter case.
Cheers,
Mark.
On 12/06/2020 11:29 am, Edwin Zimmerman wrote:
On 6/12/2020 6:18 AM, Edwin Zimmerman wrote:
On 6/12/2020 5:08 AM, Paul Moore wrote:
On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote:
Starting a new process is cheap. On my machine, starting a new Python
process takes under 1ms and uses a few Mbytes.
Is that on Windows or Unix? Traditionally, process creation has been
costly on Windows, which is why threads, and in-process solutions in
general, tend to be more common on that platform. I haven't done
experiments recently, but I do tend to avoid multiprocess-type
solutions on Windows "just in case". I know that evaluating a new
feature based on unsubstantiated assumptions informed by "it used to
be like this" is ill-advised, but so is assuming that everything will
be OK based on experience on a single platform :-)
Here's a test on Windows 10, 4 logical cpus, 8 GB of ram:
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
globals=globals())
0.62975287
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
globals=globals())
40.28172119964
Or this way:
timeit.timeit("""os.system('python.exe -c "exit()"')""",number=100,
globals=globals())
17.46125929995
--Edwin
For comparison, on a single core linux cloud server with 512 mb of ram:
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
globals=globals())
0.354354709998006
timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
globals=globals())
3.847851719998289
So yeah, process creation is still rather costly on Windows.
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 12/06/2020 10:45, Mark Shannon wrote: On 11/06/2020 2:50 pm, Riccardo Ghetta wrote: On 11/06/2020 12:59, Mark Shannon wrote: If the additional resource consumption is irrelevant, what's the objection to spinning up a new processes? The additional resource consumption of a new python interpreter is irrelevant, but the process as a whole needs a lot of extra data making a new process rather costly. Starting a new process is cheap. On my machine, starting a new Python process takes under 1ms and uses a few Mbytes. Sorry, I wasn't clear here. I was talking about starting one of our server processes, /with python embedded/. Since python routines are called by our C++ code and need to call other C++ routines, it cannot work alone and is surrounded by a lot of data needed for the C++ part. A python interpreter by itself would be like a cpu chip for someone needing a server. A critical component, sure, but only a small part of the whole. Plus there are issues of licensing, synchronization and load balancing that are much easier to resolve (for our system, at least) with threads than processes. Would this prevent CPython starting new processes, or is this just for processes managed by your application? Is only for application processes, but because python is always embedded there is little practical difference. I hope to not come out arrogant or dismissive, but can we take it from granted that multiprocessing is not a viable solution for our application, or at least that it would be impractical and too expensive rebuilding it from scratch to change paradigm ? At the same time, I realize that ours is a somewhat niche case and it may not be deemed interesting for python evolution. I just wanted to present a real world example of someone using python today and who would benefit immensely if python would permit multiple, separate, interpreters in a single process. Or any other solution removing the bottlenecks that currently so limit multithreaded python performance. Ciao, Riccardo ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/JSVOIN77TCOSDLRI7OALBZGGTQCPOKNE/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi Steve, On 12/06/2020 12:43 pm, Steve Dower wrote: On 12Jun2020 1008, Paul Moore wrote: On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote: Starting a new process is cheap. On my machine, starting a new Python process takes under 1ms and uses a few Mbytes. Is that on Windows or Unix? Traditionally, process creation has been costly on Windows, which is why threads, and in-process solutions in general, tend to be more common on that platform. I haven't done experiments recently, but I do tend to avoid multiprocess-type solutions on Windows "just in case". I know that evaluating a new feature based on unsubstantiated assumptions informed by "it used to be like this" is ill-advised, but so is assuming that everything will be OK based on experience on a single platform :-) It's still like that, though I'm actively involved in trying to get it improved. However, it's unlikely at this point to ever get to equivalence with Unix - Windows just sets up too many features (security, isolation, etc.) at the process boundary rather than other parts of the lifecycle. > It's also *incredibly arrogant* to insist that users rewrite their applications to suit Python, rather than us doing the work to fit their needs. That's not how being a libraries/runtime developer works. Our responsibility is to humbly do the work that will benefit our users, not to find ways to put in the least possible effort and use the rest for blame-shifting. Some of us do much more talking than listening, and it does not pass unnoticed. I don't think anyone is suggesting that users rewrite their code to work with existing features. Using any new feature is going to take some work on the users part, and we are talking about a new feature. Developer time is a finite resource and any time spent helping one set of users is not spent helping others. Likewise, optimizing for one use case may be hurting performance for other use cases. Personally, I have no idea what is important for other people, but I would like any discussion to have sound technical underpinnings. Once we have those, it becomes possible to have a meaningful discussion. Cheers, Mark. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/4U26HEVBZTETSOXKHETH23VZUXHFHAU2/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Fri, Jun 12, 2020 at 2:49 AM Mark Shannon wrote: > The overhead largely comes from what you do with the process. The > additional cost of starting a new interpreter is the same regardless of > whether it is in the same process or not. FWIW, there's more to it than that: * there is some overhead to starting the runtime and main interpreter that does not apply to additional in-process interpreters * I don't see why we shouldn't be able to come up with a strategy for interpreter startup that does not involve copying or sharing a lot of interpreter state, thus reducing startup time and memory consumption * I'm guessing that re-importing builtin/extension modules is faster than importing then new in a separate process -eric ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/M7FZL6LVEP2CRMDKGZE4BA6G7WOS542H/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
Hi Eric, On 12/06/2020 4:17 pm, Eric Snow wrote: On Fri, Jun 12, 2020 at 2:49 AM Mark Shannon wrote: The overhead largely comes from what you do with the process. The additional cost of starting a new interpreter is the same regardless of whether it is in the same process or not. FWIW, there's more to it than that: * there is some overhead to starting the runtime and main interpreter that does not apply to additional in-process interpreters You seem to be implying that there would be more overhead for a new interpreter that operates in a different O/S process. What would that be? * I don't see why we shouldn't be able to come up with a strategy for interpreter startup that does not involve copying or sharing a lot of interpreter state, thus reducing startup time and memory consumption Indeed, that would be beneficial regardless of which process the interpreter is in. * I'm guessing that re-importing builtin/extension modules is faster than importing then new in a separate process Each new interpreter need to re-import the modules. The overhead could be reduced by making more of the module immutable, allowing some sharing. For linux, at least, that benefit would apply to multiple processes as well. Cheers, Mark. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/FUN2IKFHOYSUYY6UJA7C73AWK3YMF7QD/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Fri, Jun 12, 2020 at 7:19 AM Mark Shannon wrote:
> Hi Edwin,
>
> Thanks for providing some concrete numbers.
> Is it expected that creating 100 processes takes 6.3ms per process, but
> that creating 1000 process takes 40ms per process? That's over 6 times
> as long in the latter case.
>
> Cheers,
> Mark.
>
> On 12/06/2020 11:29 am, Edwin Zimmerman wrote:
> > On 6/12/2020 6:18 AM, Edwin Zimmerman wrote:
> >> On 6/12/2020 5:08 AM, Paul Moore wrote:
> >>> On Fri, 12 Jun 2020 at 09:47, Mark Shannon wrote:
> Starting a new process is cheap. On my machine, starting a new Python
> process takes under 1ms and uses a few Mbytes.
> >>> Is that on Windows or Unix? Traditionally, process creation has been
> >>> costly on Windows, which is why threads, and in-process solutions in
> >>> general, tend to be more common on that platform. I haven't done
> >>> experiments recently, but I do tend to avoid multiprocess-type
> >>> solutions on Windows "just in case". I know that evaluating a new
> >>> feature based on unsubstantiated assumptions informed by "it used to
> >>> be like this" is ill-advised, but so is assuming that everything will
> >>> be OK based on experience on a single platform :-)
> >> Here's a test on Windows 10, 4 logical cpus, 8 GB of ram:
> >>
> >
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
> globals=globals())
> >> 0.62975287
> >
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
> globals=globals())
> >> 40.28172119964
> >>
> >> Or this way:
> > timeit.timeit("""os.system('python.exe -c "exit()"')""",number=100,
> globals=globals())
> >> 17.46125929995
> >>
> >> --Edwin
> > For comparison, on a single core linux cloud server with 512 mb of ram:
> >
> >
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
> globals=globals())
> > 0.354354709998006
> >
> >
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
> globals=globals())
> > 3.847851719998289
> >
> > So yeah, process creation is still rather costly on Windows.
>
I was wondering that too, some tests show that process creation/destruction
starts to seriously bog down after a few hundred in a row. I guess it's
hitting some resource limits it has to clean up, though creating hundreds
of processes at once sounds like an antipattern that doesn't really deserve
too much consideration. It would be rare that fork is more than a
negligible part of any workload. (With A/V on, though, it's _much_ slower
out the gate. I'm seeing over 100ms per process with Kaspersky running.)
Em
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
My previous timings were slightly inaccurate, as they compared spawning
processes on Windows to forking on Linux. Also, I changed my timing code to
run all process synchronously, to avoid hitting resource limits.
Updated Windows (Windows 7 this time, on a four core processor):
>>> timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
>>> number=1000,globals = globals())
84.7111053659259
Updated Linux with spawn (single core processor):
>>> ctx = multiprocessing.get_context('spawn')
>>> timeit.timeit('x=ctx.Process(target=exit);x.start();x.join()',
>>> number=1000,globals = globals())
60.01154333699378
Updated Linux with fork:
>>> timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
>>> number=1000,globals = globals())
4.402019854984246
Compare this to subinterpreters on my linux machine:
>>> timeit.timeit('s=_xxsubinterpreters.create();_xxsubinterpreters.destroy(s)',number=1000,
>>> globals=globals())
13.47043095799745
This shows that is speed is all that matters, multiprocessing comes out way
ahead of subinterpreters on linux, but way behind on Windows.
I need to time subinterpreters on Windows yet for the full picture, but that
will be tomorrow till I get that done.
--Edwin
From: Emily Bowman [mailto:silverback...@gmail.com]
Sent: Friday, June 12, 2020 12:44 PM
To: Mark Shannon
Cc: Python Dev
Subject: [Python-Dev] Re: My take on multiple interpreters (Was: Should we be
making so many changes in pursuit of PEP 554?)
On Fri, Jun 12, 2020 at 7:19 AM Mark Shannon mailto:m...@hotpy.org> > wrote:
Hi Edwin,
Thanks for providing some concrete numbers.
Is it expected that creating 100 processes takes 6.3ms per process, but
that creating 1000 process takes 40ms per process? That's over 6 times
as long in the latter case.
Cheers,
Mark.
On 12/06/2020 11:29 am, Edwin Zimmerman wrote:
> On 6/12/2020 6:18 AM, Edwin Zimmerman wrote:
>> On 6/12/2020 5:08 AM, Paul Moore wrote:
>>> On Fri, 12 Jun 2020 at 09:47, Mark Shannon >> <mailto:m...@hotpy.org> > wrote:
>>>> Starting a new process is cheap. On my machine, starting a new Python
>>>> process takes under 1ms and uses a few Mbytes.
>>> Is that on Windows or Unix? Traditionally, process creation has been
>>> costly on Windows, which is why threads, and in-process solutions in
>>> general, tend to be more common on that platform. I haven't done
>>> experiments recently, but I do tend to avoid multiprocess-type
>>> solutions on Windows "just in case". I know that evaluating a new
>>> feature based on unsubstantiated assumptions informed by "it used to
>>> be like this" is ill-advised, but so is assuming that everything will
>>> be OK based on experience on a single platform :-)
>> Here's a test on Windows 10, 4 logical cpus, 8 GB of ram:
>>
>>>>> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
>>>>> globals=globals())
>> 0.62975287
>>>>> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
>>>>> globals=globals())
>> 40.28172119964
>>
>> Or this way:
>>>>> timeit.timeit("""os.system('python.exe -c "exit()"')""",number=100,
>>>>> globals=globals())
>> 17.46125929995
>>
>> --Edwin
> For comparison, on a single core linux cloud server with 512 mb of ram:
>
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=100,
> globals=globals())
> 0.354354709998006
>
> timeit.timeit("""multiprocessing.Process(target=exit).start()""",number=1000,
> globals=globals())
> 3.847851719998289
>
> So yeah, process creation is still rather costly on Windows.
I was wondering that too, some tests show that process creation/destruction
starts to seriously bog down after a few hundred in a row. I guess it's hitting
some resource limits it has to clean up, though creating hundreds of processes
at once sounds like an antipattern that doesn't really deserve too much
consideration. It would be rare that fork is more than a negligible part of any
workload. (With A/V on, though, it's _much_ slower out the gate. I'm seeing
over 100ms per process with Kaspersky running.)
Em
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On Sat, Jun 13, 2020 at 3:50 AM Edwin Zimmerman wrote:
>
> My previous timings were slightly inaccurate, as they compared spawning
> processes on Windows to forking on Linux. Also, I changed my timing code to
> run all process synchronously, to avoid hitting resource limits.
>
> Updated Windows (Windows 7 this time, on a four core processor):
>
> >>> timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
> >>> number=1000,globals = globals())
> 84.7111053659259
>
Thanks, I was actually going to ask about joining the processes, since
you don't really get a good indication of timings from asynchronous
operations like that. Another interesting data point is that starting
and joining in batches makes a fairly huge difference to performance,
at least on my Linux system. Starting with your example and rescaling
the number by ten to compensate for performance differences:
>>> timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
>>> number=1,globals = globals())
14.261007152497768
Just for completeness and consistency, confirmed that adding a list
comp around it doesn't change the timings:
>>> timeit.timeit('xx=[multiprocessing.Process(target=exit) for _ in
>>> range(1)];[x.start() for x in xx];[x.join() for x in xx]',
>>> number=1,globals = globals())
14.030426062643528
But doing a hundred at a time and then joining them all cuts the time in half!
>>> timeit.timeit('xx=[multiprocessing.Process(target=exit) for _ in
>>> range(100)];[x.start() for x in xx];[x.join() for x in xx]',
>>> number=100,globals = globals())
5.470761131495237
The difference is even more drastic with spawn, although since it's
slower, I also lowered the number of iterations.
>>> ctx = multiprocessing.get_context('spawn')
>>> timeit.timeit('x=ctx.Process(target=exit);x.start();x.join()',
>>> number=1000,globals = globals())
40.82687543518841
>>> timeit.timeit('xx=[ctx.Process(target=exit) for _ in range(100)];[x.start()
>>> for x in xx];[x.join() for x in xx]', number=10,globals =
>>> globals())8.566341979429126
8.566341979429126
Would be curious to know if that's the same on Windows.
ChrisA
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/12/2020 2:17 PM, Chris Angelico wrote:
> On Sat, Jun 13, 2020 at 3:50 AM Edwin Zimmerman
> wrote:
>> My previous timings were slightly inaccurate, as they compared spawning
>> processes on Windows to forking on Linux. Also, I changed my timing code to
>> run all process synchronously, to avoid hitting resource limits.
>>
>> Updated Windows (Windows 7 this time, on a four core processor):
>>
> timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
> number=1000,globals = globals())
>> 84.7111053659259
>>
> Thanks, I was actually going to ask about joining the processes, since
> you don't really get a good indication of timings from asynchronous
> operations like that. Another interesting data point is that starting
> and joining in batches makes a fairly huge difference to performance,
> at least on my Linux system. Starting with your example and rescaling
> the number by ten to compensate for performance differences:
>
timeit.timeit('x=multiprocessing.Process(target=exit);x.start();x.join()',
number=1,globals = globals())
> 14.261007152497768
>
> Just for completeness and consistency, confirmed that adding a list
> comp around it doesn't change the timings:
>
timeit.timeit('xx=[multiprocessing.Process(target=exit) for _ in
range(1)];[x.start() for x in xx];[x.join() for x in xx]',
number=1,globals = globals())
> 14.030426062643528
>
> But doing a hundred at a time and then joining them all cuts the time in half!
>
timeit.timeit('xx=[multiprocessing.Process(target=exit) for _ in
range(100)];[x.start() for x in xx];[x.join() for x in xx]',
number=100,globals = globals())
> 5.470761131495237
>
> The difference is even more drastic with spawn, although since it's
> slower, I also lowered the number of iterations.
>
ctx = multiprocessing.get_context('spawn')
timeit.timeit('x=ctx.Process(target=exit);x.start();x.join()',
number=1000,globals = globals())
> 40.82687543518841
timeit.timeit('xx=[ctx.Process(target=exit) for _ in
range(100)];[x.start() for x in xx];[x.join() for x in xx]',
number=10,globals = globals())8.566341979429126
> 8.566341979429126
>
> Would be curious to know if that's the same on Windows.
Yea, it's the same. Watch your cpu utilization, and you will realize that your
list comprehension is parallelizing the process startups.
> ChrisA
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[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 12/06/2020 12:55, Eric V. Smith wrote: On 6/11/2020 6:59 AM, Mark Shannon wrote: Different interpreters need to operate in their own isolated address space, or there will be horrible race conditions. Regardless of whether that separation is done in software or hardware, it has to be done. I realize this is true now, but why must it always be true? Can't we fix this? At least one solution has been proposed: passing around a pointer to the current interpreter. I realize there issues here, like callbacks and signals that will need to be worked out. But I don't think it's axiomatically true that we'll always have race conditions with multiple interpreters in the same address space. Eric Axiomatically? No, but let me rise to the challenge. If (1) interpreters manage the life-cycle of objects, and (2) a race condition arises when the life-cycle or state of an object is accessed by the interpreter that did not create it, and (3) an object will sometimes be passed to an interpreter that did not create it, and (4) an interpreter with a reference to an object will sometimes access its life-cycle or state, then (5) a race condition will sometimes arise. This seems to be true (as a deduction) if all the premises hold. (1) and (2) are true in CPython as we know it. (3) is prevented (completely?) by the Python API, but not at all by the C API. (4) is implicit in an interpreter having access to an object, the way CPython and its extensions are written, so (5) follows in the case that the C API is used. You could change (1) and/or (2), maybe (4). "Passing around a pointer to the current interpreter" sounds like an attempt to break (2) or maybe (4). But I don't understand "current". What you need at any time is the interpreter (state and life-cycle manager) for the object you're about to handle, so that the receiving interpreter can delegate the action, instead of crashing ahead itself. This suggests a reference to the interpreter must be embedded in each object, but it could be implicit in the memory address. There is then still an issue that the owning interpreter has to be thread-safe (if there are threads) in the sense that it can serialise access to object state or life-cycle. If serialisation is by a GIL, the receiving interpreter must take the GIL of the owning interpreter, and we are somewhat back where we started. Note that the "current interpreter" is not a function of the current thread (or vice-versa). The current thread is running in both interpreters, and by hypothesis, so are the competing threads. Can I just point out that, while most of this argument concerns a particular implementation, we have a reason in Python (the language) for an interpreter construct: it holds the current module context, so that whenever code is executing, we can give definite meaning to the 'import' statement. Here "current interpreter" does have a meaning, and I suggest it needs to be made a property of every function object as it is defined, and picked up when the execution frame is created. This *may* help with the other, internal, use of interpreter, for life-cycle and state management, because it provides a recognisable point (function call) where one may police object ownership, but that isn't why you need it. Jeff Allen ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/GACVQJNCZLT4P3YX5IISRBOQTXXTJVMB/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/17/2020 12:07 PM, Jeff Allen wrote: On 12/06/2020 12:55, Eric V. Smith wrote: On 6/11/2020 6:59 AM, Mark Shannon wrote: Different interpreters need to operate in their own isolated address space, or there will be horrible race conditions. Regardless of whether that separation is done in software or hardware, it has to be done. I realize this is true now, but why must it always be true? Can't we fix this? At least one solution has been proposed: passing around a pointer to the current interpreter. I realize there issues here, like callbacks and signals that will need to be worked out. But I don't think it's axiomatically true that we'll always have race conditions with multiple interpreters in the same address space. Eric Axiomatically? No, but let me rise to the challenge. If (1) interpreters manage the life-cycle of objects, and (2) a race condition arises when the life-cycle or state of an object is accessed by the interpreter that did not create it, and (3) an object will sometimes be passed to an interpreter that did not create it, and (4) an interpreter with a reference to an object will sometimes access its life-cycle or state, then (5) a race condition will sometimes arise. This seems to be true (as a deduction) if all the premises hold. (1) and (2) are true in CPython as we know it. (3) is prevented (completely?) by the Python API, but not at all by the C API. (4) is implicit in an interpreter having access to an object, the way CPython and its extensions are written, so (5) follows in the case that the C API is used. You could change (1) and/or (2), maybe (4). I'm assuming that passing an object between interpreters would not be supported. It would require that the object somehow be marshalled between interpreters, so that no object would be operated on outside the interpreter that created it. So 2-5 couldn't happen in valid code. "Passing around a pointer to the current interpreter" sounds like an attempt to break (2) or maybe (4). But I don't understand "current". What you need at any time is the interpreter (state and life-cycle manager) for the object you're about to handle, so that the receiving interpreter can delegate the action, instead of crashing ahead itself. This suggests a reference to the interpreter must be embedded in each object, but it could be implicit in the memory address. Sorry for being loose with terms. If I want to create an interpreter and execute it, then I'd allocate and initialize an interpreter state object, then call it, passing the interpreter state object in to whatever Python functions I want to call. They would in turn pass that pointer to whatever they call, or access the state through it directly. That pointer is the "current interpreter". There is then still an issue that the owning interpreter has to be thread-safe (if there are threads) in the sense that it can serialise access to object state or life-cycle. If serialisation is by a GIL, the receiving interpreter must take the GIL of the owning interpreter, and we are somewhat back where we started. Note that the "current interpreter" is not a function of the current thread (or vice-versa). The current thread is running in both interpreters, and by hypothesis, so are the competing threads. Agreed that an interpreter shouldn't belong to a thread, but since an interpreter couldn't access objects of another interpreter, there'd be no need for cross-intepreter locking. There would be a GIL per interpreter, protecting access to that interpreter's state. Can I just point out that, while most of this argument concerns a particular implementation, we have a reason in Python (the language) for an interpreter construct: it holds the current module context, so that whenever code is executing, we can give definite meaning to the 'import' statement. Here "current interpreter" does have a meaning, and I suggest it needs to be made a property of every function object as it is defined, and picked up when the execution frame is created. This *may* help with the other, internal, use of interpreter, for life-cycle and state management, because it provides a recognisable point (function call) where one may police object ownership, but that isn't why you need it. There's a lot of state per interpreter, including the module state. See "struct _is" in Include/internal/pycore_interp.h. Eric Jeff Allen ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/GACVQJNCZLT4P3YX5IISRBOQTXXTJVMB/ Code of Conduct: http://python.org/psf/codeofconduct/ ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 17/06/2020 19:28, Eric V. Smith wrote: On 6/17/2020 12:07 PM, Jeff Allen wrote: If (1) interpreters manage the life-cycle of objects, and (2) a race condition arises when the life-cycle or state of an object is accessed by the interpreter that did not create it, and (3) an object will sometimes be passed to an interpreter that did not create it, and (4) an interpreter with a reference to an object will sometimes access its life-cycle or state, then (5) a race condition will sometimes arise. This seems to be true (as a deduction) if all the premises hold. I'm assuming that passing an object between interpreters would not be supported. It would require that the object somehow be marshalled between interpreters, so that no object would be operated on outside the interpreter that created it. So 2-5 couldn't happen in valid code. The Python level doesn't support it, prevents it I think, and perhaps the implementation doesn't support it, but nothing can stop C actually doing it. I would agree that with sufficient discipline in the code it should be possible to prevent the worlds from colliding. But it is difficult, so I think that is why Mark is arguing for a separate address space. Marshalling the value across is supported, but that's just the value, not a shared object. Sorry for being loose with terms. If I want to create an interpreter and execute it, then I'd allocate and initialize an interpreter state object, then call it, passing the interpreter state object in to whatever Python functions I want to call. They would in turn pass that pointer to whatever they call, or access the state through it directly. That pointer is the "current interpreter". I think that can work if you have disciplined separation, which you are assuming. I think you would pass the function to the interpreter, not the other way around. I'm assuming this is described from the perspective of some C code and your Python functions are PyFunction objects, not just text? What, however, prevents you creating that function in one interpreter and giving it to another? The function, and any closure or defaults are owned by the creating interpreter. There's a lot of state per interpreter, including the module state. See "struct _is" in Include/internal/pycore_interp.h. So much more than when I last looked! Look back in time and interpreter state mostly contains the module context (in a broad sense that includes shortcuts to sys, builtins, codec state, importlib). Ok, there's some stuff about exit handling and debugging too. The recent huge growth is to shelter previously singleton object allocation mechanisms, a consequence of the implementation choice that gives the interpreter object that responsibility too. I'm not saying this is wrong, just that it's not a concept in Python-the-language, while the module state is. Jeff ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/ESNK7A5UFBQOQXKUDWCUMS2372AL7ZPU/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
On 6/17/2020 6:03 PM, Jeff Allen wrote: On 17/06/2020 19:28, Eric V. Smith wrote: On 6/17/2020 12:07 PM, Jeff Allen wrote: If (1) interpreters manage the life-cycle of objects, and (2) a race condition arises when the life-cycle or state of an object is accessed by the interpreter that did not create it, and (3) an object will sometimes be passed to an interpreter that did not create it, and (4) an interpreter with a reference to an object will sometimes access its life-cycle or state, then (5) a race condition will sometimes arise. This seems to be true (as a deduction) if all the premises hold. I'm assuming that passing an object between interpreters would not be supported. It would require that the object somehow be marshalled between interpreters, so that no object would be operated on outside the interpreter that created it. So 2-5 couldn't happen in valid code. The Python level doesn't support it, prevents it I think, and perhaps the implementation doesn't support it, but nothing can stop C actually doing it. I would agree that with sufficient discipline in the code it should be possible to prevent the worlds from colliding. But it is difficult, so I think that is why Mark is arguing for a separate address space. Marshalling the value across is supported, but that's just the value, not a shared object. Yes, it's difficult to have the discipline in C, just as multi-threaded is difficult in C. I agree separate address spaces makes isolation much easier, but I think there are use cases that don't align with separate address spaces, and we should support those. Sorry for being loose with terms. If I want to create an interpreter and execute it, then I'd allocate and initialize an interpreter state object, then call it, passing the interpreter state object in to whatever Python functions I want to call. They would in turn pass that pointer to whatever they call, or access the state through it directly. That pointer is the "current interpreter". I think that can work if you have disciplined separation, which you are assuming. I think you would pass the function to the interpreter, not the other way around. I'm assuming this is described from the perspective of some C code and your Python functions are PyFunction objects, not just text? What, however, prevents you creating that function in one interpreter and giving it to another? The function, and any closure or defaults are owned by the creating interpreter. In the C API (which is what I think we're discussing), I think it would be passing the interpreter state to the function. And nothing would prevent you from getting it wrong. There's a lot of state per interpreter, including the module state. See "struct _is" in Include/internal/pycore_interp.h. So much more than when I last looked! Look back in time and interpreter state mostly contains the module context (in a broad sense that includes shortcuts to sys, builtins, codec state, importlib). Ok, there's some stuff about exit handling and debugging too. The recent huge growth is to shelter previously singleton object allocation mechanisms, a consequence of the implementation choice that gives the interpreter object that responsibility too. I'm not saying this is wrong, just that it's not a concept in Python-the-language, while the module state is. I think most of these changes are Victor's, and I think they're a step in the right direction. Since Python globals are really module state, it makes sense that that's the part that's visible to Python. Eric ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/TRML3XIT7IN2XZZT3MDJGP5NSZ63A6EC/ Code of Conduct: http://python.org/psf/codeofconduct/
[Python-Dev] Re: My take on multiple interpreters (Was: Should we be making so many changes in pursuit of PEP 554?)
There are the usual concurrency problems of "read a value, change it, store it back without checking whether it already changed". The only thing special about lifecycle happens at refcount 0, which should not happen when more than one interpreter has a reference. Similarly, C code can mess things up if it does something unsupported -- but that is already the case. C code *could* set the refcount to something random, but that wouldn't be considered a bug in python, because there isn't much python can do to prevent it -- and that doesn't change with a second interpreter. ___ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-le...@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at https://mail.python.org/archives/list/python-dev@python.org/message/XANKD3QYOH5KON2UVYY534EMKUB7O7SZ/ Code of Conduct: http://python.org/psf/codeofconduct/
