On 1/23/19 3:33 AM, Stephan Reiter wrote:
Thanks for the answers so far. I appreciate them!
Nathaniel, I'd like to allow Python plugins in my application. A
plugin should be allowed to bring its own modules along (i.e.
plugin-specific subdir is in sys.path when the plugin is active) and
hence some isolation of them will be needed, so that they can use
different versions of a given module. That's my main motivation for
using subinterpreters.
I thought about running plugins out-of-processes - a separate process
for every plugin - and allow them to communicate with my application
via RPC. But that makes it more complex to implement the API my
application will offer and will slow down things due to the need to
copy data.
Maybe you have another idea for me? :)
Try to make the plugins work together. Look into using pip/PyPI for your
plugins. Try to make it so each package ("plugin") would have only one
module/package, and dependencies would be other packages that can be
installed individually and shared. And keep in mind you can set up your
own package index, or distribute/install individual package files.
If that's not possible, and you want things to work now, go with subprocess.
If you want to help make subinterpreters work better, there are several
people scratching at the problem from different angles. Most/all would
welcome help, but don't expect any short-term benefits.
(FWIW, my own effort is currently blocked on PEP 580, and I hope to move
forward after a Council is elected.)
Henry, Antoine, thanks for your input; I'll check out the tests and
see what I can learn from issue 10915.
Stephan
Am Di., 22. Jan. 2019 um 22:39 Uhr schrieb Nathaniel Smith <n...@pobox.com>:
There are currently numerous incompatibilities between numpy and
subinterpreters, and no concrete plan for fixing them. The numpy team does not
consider subinterpreters to be a supported configuration, and can't help you
with any issues you run into. I know the concept of subinterpreters is really
appealing, but unfortunately the CPython implementation is not really mature or
widely supported... are you absolutely certain you need to use subinterpreters
for your application?
On Tue, Jan 22, 2019, 08:27 Stephan Reiter <stephan.rei...@gmail.com wrote:
Hi all!
I am new to the list and arriving with a concrete problem that I'd
like to fix myself.
I am embedding Python (3.6) into my C++ application and I would like
to run Python scripts isolated from each other using sub-interpreters.
I am not using threads; everything is supposed to run in the
application's main thread.
I noticed that if I create an interpreter, switch to it and execute
code that imports numpy (1.13), my application will hang.
ntdll.dll!NtWaitForSingleObject() Unknown
KernelBase.dll!WaitForSingleObjectEx() Unknown
python36.dll!_PyCOND_WAIT_MS(_PyCOND_T * cv=0x00000000748a67a0,
_RTL_CRITICAL_SECTION * cs=0x00000000748a6778, unsigned long ms=5) Line 245 C
[Inline Frame] python36.dll!PyCOND_TIMEDWAIT(_PyCOND_T *) Line 275 C
python36.dll!take_gil(_ts * tstate=0x0000023251cbc260) Line 224 C
python36.dll!PyEval_RestoreThread(_ts * tstate=0x0000023251cbc260) Line 370 C
python36.dll!PyGILState_Ensure() Line 855 C
umath.cp36-win_amd64.pyd!00007ff8c6306ab2() Unknown
umath.cp36-win_amd64.pyd!00007ff8c630723c() Unknown
umath.cp36-win_amd64.pyd!00007ff8c6303a1d() Unknown
umath.cp36-win_amd64.pyd!00007ff8c63077c0() Unknown
umath.cp36-win_amd64.pyd!00007ff8c62ff926() Unknown
[Inline Frame] python36.dll!_PyObject_FastCallDict(_object *) Line 2316 C
[Inline Frame] python36.dll!_PyObject_FastCallKeywords(_object *) Line 2480 C
python36.dll!call_function(_object * * *
pp_stack=0x00000048be5f5e40, __int64 oparg, _object * kwnames) Line
4822 C
Numpy's extension umath calls PyGILState_Ensure(), which in turn calls
PyEval_RestoreThread on the (auto) threadstate of the main
interpreter. And that's wrong.
We are already holding the GIL with the threadstate of our current
sub-interpreter, so there's no need to switch.
I know that the GIL API is not fully compatible with sub-interpreters,
as issues #10915 and #15751 illustrate.
But since I need to support calls to PyGILState_Ensure - numpy is the
best example -, I am trying to improve the situation here:
https://github.com/stephanreiter/cpython/commit/d9d3451b038af2820f500843b6a88f57270e1597
That change may be naive, but it does the trick for my use case. If
totally wrong, I don't mind pursuing another alley.
Essentially, I'd like to ask for some guidance in how to tackle this
problem while keeping the current GIL API unchanged (to avoid breaking
modules).
I am also wondering how I can test any changes I am proposing. Is
there a test suite for interpreters, for example?
Thank you very much,
Stephan
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