Doc/c-api/subinterpreters.rst
.. highlight:: c
.. _sub-interpreter-support:
While in most uses, you will only embed a single Python interpreter, there are cases where you need to create several independent interpreters in the same process and perhaps even in the same thread. Sub-interpreters allow you to do that.
The "main" interpreter is the first one created when the runtime initializes.
It is usually the only Python interpreter in a process. Unlike sub-interpreters,
the main interpreter has unique process-global responsibilities like signal
handling. It is also responsible for execution during runtime initialization and
is usually the active interpreter during runtime finalization. The
:c:func:PyInterpreterState_Main function returns a pointer to its state.
You can switch between sub-interpreters using the :c:func:PyThreadState_Swap
function. You can create and destroy them using the following functions:
.. c:type:: PyInterpreterConfig
Structure containing most parameters to configure a sub-interpreter.
Its values are used only in :c:func:Py_NewInterpreterFromConfig and
never modified by the runtime.
.. versionadded:: 3.12
Structure fields:
.. c:member:: int use_main_obmalloc
If this is ``0`` then the sub-interpreter will use its own
"object" allocator state.
Otherwise it will use (share) the main interpreter's.
If this is ``0`` then
:c:member:`~PyInterpreterConfig.check_multi_interp_extensions`
must be ``1`` (non-zero).
If this is ``1`` then :c:member:`~PyInterpreterConfig.gil`
must not be :c:macro:`PyInterpreterConfig_OWN_GIL`.
.. c:member:: int allow_fork
If this is ``0`` then the runtime will not support forking the
process in any thread where the sub-interpreter is currently active.
Otherwise fork is unrestricted.
Note that the :mod:`subprocess` module still works
when fork is disallowed.
.. c:member:: int allow_exec
If this is ``0`` then the runtime will not support replacing the
current process via exec (e.g. :func:`os.execv`) in any thread
where the sub-interpreter is currently active.
Otherwise exec is unrestricted.
Note that the :mod:`subprocess` module still works
when exec is disallowed.
.. c:member:: int allow_threads
If this is ``0`` then the sub-interpreter's :mod:`threading` module
won't create threads.
Otherwise threads are allowed.
.. c:member:: int allow_daemon_threads
If this is ``0`` then the sub-interpreter's :mod:`threading` module
won't create daemon threads.
Otherwise daemon threads are allowed (as long as
:c:member:`~PyInterpreterConfig.allow_threads` is non-zero).
.. c:member:: int check_multi_interp_extensions
If this is ``0`` then all extension modules may be imported,
including legacy (single-phase init) modules,
in any thread where the sub-interpreter is currently active.
Otherwise only multi-phase init extension modules
(see :pep:`489`) may be imported.
(Also see :c:macro:`Py_mod_multiple_interpreters`.)
This must be ``1`` (non-zero) if
:c:member:`~PyInterpreterConfig.use_main_obmalloc` is ``0``.
.. c:member:: int gil
This determines the operation of the GIL for the sub-interpreter.
It may be one of the following:
.. c:namespace:: NULL
.. c:macro:: PyInterpreterConfig_DEFAULT_GIL
Use the default selection (:c:macro:`PyInterpreterConfig_SHARED_GIL`).
.. c:macro:: PyInterpreterConfig_SHARED_GIL
Use (share) the main interpreter's GIL.
.. c:macro:: PyInterpreterConfig_OWN_GIL
Use the sub-interpreter's own GIL.
If this is :c:macro:`PyInterpreterConfig_OWN_GIL` then
:c:member:`PyInterpreterConfig.use_main_obmalloc` must be ``0``.
.. c:function:: PyStatus Py_NewInterpreterFromConfig(PyThreadState **tstate_p, const PyInterpreterConfig *config)
.. index:: pair: module; builtins pair: module; main pair: module; sys single: stdout (in module sys) single: stderr (in module sys) single: stdin (in module sys)
Create a new sub-interpreter. This is an (almost) totally separate environment
for the execution of Python code. In particular, the new interpreter has
separate, independent versions of all imported modules, including the
fundamental modules :mod:builtins, :mod:__main__ and :mod:sys. The
table of loaded modules (sys.modules) and the module search path
(sys.path) are also separate. The new environment has no sys.argv
variable. It has new standard I/O stream file objects sys.stdin,
sys.stdout and sys.stderr (however these refer to the same underlying
file descriptors).
The given config controls the options with which the interpreter is initialized.
Upon success, tstate_p will be set to the first :term:thread state
created in the new sub-interpreter. This thread state is
:term:attached <attached thread state>.
Note that no actual thread is created; see the discussion of thread states
below. If creation of the new interpreter is unsuccessful,
tstate_p is set to NULL;
no exception is set since the exception state is stored in the
:term:attached thread state, which might not exist.
Like all other Python/C API functions, an :term:attached thread state
must be present before calling this function, but it might be detached upon
returning. On success, the returned thread state will be :term:attached <attached thread state>.
If the sub-interpreter is created with its own :term:GIL then the
:term:attached thread state of the calling interpreter will be detached.
When the function returns, the new interpreter's :term:thread state
will be :term:attached <attached thread state> to the current thread and
the previous interpreter's :term:attached thread state will remain detached.
.. versionadded:: 3.12
Sub-interpreters are most effective when isolated from each other, with certain functionality restricted::
PyInterpreterConfig config = {
.use_main_obmalloc = 0,
.allow_fork = 0,
.allow_exec = 0,
.allow_threads = 1,
.allow_daemon_threads = 0,
.check_multi_interp_extensions = 1,
.gil = PyInterpreterConfig_OWN_GIL,
};
PyThreadState *tstate = NULL;
PyStatus status = Py_NewInterpreterFromConfig(&tstate, &config);
if (PyStatus_Exception(status)) {
Py_ExitStatusException(status);
}
Note that the config is used only briefly and does not get modified.
During initialization the config's values are converted into various
:c:type:PyInterpreterState values. A read-only copy of the config
may be stored internally on the :c:type:PyInterpreterState.
.. index:: single: Py_FinalizeEx (C function) single: Py_Initialize (C function)
Extension modules are shared between (sub-)interpreters as follows:
For modules using multi-phase initialization,
e.g. :c:func:PyModule_FromDefAndSpec, a separate module object is
created and initialized for each interpreter.
Only C-level static and global variables are shared between these
module objects.
For modules using legacy
:ref:single-phase initialization <single-phase-initialization>,
e.g. :c:func:PyModule_Create, the first time a particular extension
is imported, it is initialized normally, and a (shallow) copy of its
module's dictionary is squirreled away.
When the same extension is imported by another (sub-)interpreter, a new
module is initialized and filled with the contents of this copy; the
extension's init function is not called.
Objects in the module's dictionary thus end up shared across
(sub-)interpreters, which might cause unwanted behavior (see
Bugs and caveats_ below).
Note that this is different from what happens when an extension is
imported after the interpreter has been completely re-initialized by
calling :c:func:Py_FinalizeEx and :c:func:Py_Initialize; in that
case, the extension's initmodule function is called again.
As with multi-phase initialization, this means that only C-level static
and global variables are shared between these modules.
.. index:: single: close (in module os)
.. c:function:: PyThreadState* Py_NewInterpreter(void)
.. index:: pair: module; builtins pair: module; main pair: module; sys single: stdout (in module sys) single: stderr (in module sys) single: stdin (in module sys)
Create a new sub-interpreter. This is essentially just a wrapper
around :c:func:Py_NewInterpreterFromConfig with a config that
preserves the existing behavior. The result is an unisolated
sub-interpreter that shares the main interpreter's GIL, allows
fork/exec, allows daemon threads, and allows single-phase init
modules.
.. c:function:: void Py_EndInterpreter(PyThreadState *tstate)
.. index:: single: Py_FinalizeEx (C function)
Destroy the (sub-)interpreter represented by the given :term:thread state.
The given thread state must be :term:attached <attached thread state>.
When the call returns, there will be no :term:attached thread state.
All thread states associated with this interpreter are destroyed.
:c:func:Py_FinalizeEx will destroy all sub-interpreters that
haven't been explicitly destroyed at that point.
.. _per-interpreter-gil:
.. versionadded:: 3.12
Using :c:func:Py_NewInterpreterFromConfig you can create
a sub-interpreter that is completely isolated from other interpreters,
including having its own GIL. The most important benefit of this
isolation is that such an interpreter can execute Python code without
being blocked by other interpreters or blocking any others. Thus a
single Python process can truly take advantage of multiple CPU cores
when running Python code. The isolation also encourages a different
approach to concurrency than that of just using threads.
(See :pep:554 and :pep:684.)
Using an isolated interpreter requires vigilance in preserving that
isolation. That especially means not sharing any objects or mutable
state without guarantees about thread-safety. Even objects that are
otherwise immutable (e.g. None, (1, 5)) can't normally be shared
because of the refcount. One simple but less-efficient approach around
this is to use a global lock around all use of some state (or object).
Alternately, effectively immutable objects (like integers or strings)
can be made safe in spite of their refcounts by making them :term:immortal.
In fact, this has been done for the builtin singletons, small integers,
and a number of other builtin objects.
If you preserve isolation then you will have access to proper multi-core computing without the complications that come with free-threading. Failure to preserve isolation will expose you to the full consequences of free-threading, including races and hard-to-debug crashes.
Aside from that, one of the main challenges of using multiple isolated interpreters is how to communicate between them safely (not break isolation) and efficiently. The runtime and stdlib do not provide any standard approach to this yet. A future stdlib module would help mitigate the effort of preserving isolation and expose effective tools for communicating (and sharing) data between interpreters.
Because sub-interpreters (and the main interpreter) are part of the same
process, the insulation between them isn't perfect --- for example, using
low-level file operations like :func:os.close they can
(accidentally or maliciously) affect each other's open files. Because of the
way extensions are shared between (sub-)interpreters, some extensions may not
work properly; this is especially likely when using single-phase initialization
or (static) global variables.
It is possible to insert objects created in one sub-interpreter into
a namespace of another (sub-)interpreter; this should be avoided if possible.
Special care should be taken to avoid sharing user-defined functions, methods, instances or classes between sub-interpreters, since import operations executed by such objects may affect the wrong (sub-)interpreter's dictionary of loaded modules. It is equally important to avoid sharing objects from which the above are reachable.
Also note that combining this functionality with PyGILState_* APIs
is delicate, because these APIs assume a bijection between Python thread states
and OS-level threads, an assumption broken by the presence of sub-interpreters.
It is highly recommended that you don't switch sub-interpreters between a pair
of matching :c:func:PyGILState_Ensure and :c:func:PyGILState_Release calls.
Furthermore, extensions (such as :mod:ctypes) using these APIs to allow calling
of Python code from non-Python created threads will probably be broken when using
sub-interpreters.
.. c:type:: PyInterpreterState
This data structure represents the state shared by a number of cooperating threads. Threads belonging to the same interpreter share their module administration and a few other internal items. There are no public members in this structure.
Threads belonging to different interpreters initially share nothing, except process state like available memory, open file descriptors and such. The global interpreter lock is also shared by all threads, regardless of to which interpreter they belong.
.. versionchanged:: 3.12
:pep:`684` introduced the possibility
of a :ref:`per-interpreter GIL <per-interpreter-gil>`.
See :c:func:`Py_NewInterpreterFromConfig`.
.. c:function:: PyInterpreterState* PyInterpreterState_Get(void)
Get the current interpreter.
Issue a fatal error if there is no :term:attached thread state.
It cannot return NULL.
.. versionadded:: 3.9
.. c:function:: int64_t PyInterpreterState_GetID(PyInterpreterState *interp)
Return the interpreter's unique ID. If there was any error in doing
so then -1 is returned and an error is set.
The caller must have an :term:attached thread state.
.. versionadded:: 3.7
.. c:function:: PyObject* PyInterpreterState_GetDict(PyInterpreterState *interp)
Return a dictionary in which interpreter-specific data may be stored.
If this function returns NULL then no exception has been raised and
the caller should assume no interpreter-specific dict is available.
This is not a replacement for :c:func:PyModule_GetState(), which
extensions should use to store interpreter-specific state information.
The returned dictionary is borrowed from the interpreter and is valid until interpreter shutdown.
.. versionadded:: 3.8
.. c:type:: PyObject* (*_PyFrameEvalFunction)(PyThreadState *tstate, _PyInterpreterFrame *frame, int throwflag)
Type of a frame evaluation function.
The throwflag parameter is used by the throw() method of generators:
if non-zero, handle the current exception.
.. versionchanged:: 3.9 The function now takes a tstate parameter.
.. versionchanged:: 3.11
The frame parameter changed from PyFrameObject* to _PyInterpreterFrame*.
.. c:function:: _PyFrameEvalFunction _PyInterpreterState_GetEvalFrameFunc(PyInterpreterState *interp)
Get the frame evaluation function.
See the :pep:523 "Adding a frame evaluation API to CPython".
.. versionadded:: 3.9
.. c:function:: void _PyInterpreterState_SetEvalFrameFunc(PyInterpreterState *interp, _PyFrameEvalFunction eval_frame)
Set the frame evaluation function.
See the :pep:523 "Adding a frame evaluation API to CPython".
.. versionadded:: 3.9
All of the following functions must be called after :c:func:Py_Initialize.
.. versionchanged:: 3.7
:c:func:Py_Initialize() now initializes the :term:GIL
and sets an :term:attached thread state.
.. c:function:: PyInterpreterState* PyInterpreterState_New()
Create a new interpreter state object. An :term:attached thread state is not needed,
but may optionally exist if it is necessary to serialize calls to this
function.
.. audit-event:: cpython.PyInterpreterState_New "" c.PyInterpreterState_New
.. c:function:: void PyInterpreterState_Clear(PyInterpreterState *interp)
Reset all information in an interpreter state object. There must be
an :term:attached thread state for the interpreter.
.. audit-event:: cpython.PyInterpreterState_Clear "" c.PyInterpreterState_Clear
.. c:function:: void PyInterpreterState_Delete(PyInterpreterState *interp)
Destroy an interpreter state object. There should not be an
:term:attached thread state for the target interpreter. The interpreter
state must have been reset with a previous call to :c:func:PyInterpreterState_Clear.
.. _advanced-debugging:
These functions are only intended to be used by advanced debugging tools.
.. c:function:: PyInterpreterState* PyInterpreterState_Head()
Return the interpreter state object at the head of the list of all such objects.
.. c:function:: PyInterpreterState* PyInterpreterState_Main()
Return the main interpreter state object.
.. c:function:: PyInterpreterState* PyInterpreterState_Next(PyInterpreterState *interp)
Return the next interpreter state object after interp from the list of all such objects.
.. c:function:: PyThreadState * PyInterpreterState_ThreadHead(PyInterpreterState *interp)
Return the pointer to the first :c:type:PyThreadState object in the list of
threads associated with the interpreter interp.
.. c:function:: PyThreadState* PyThreadState_Next(PyThreadState *tstate)
Return the next thread state object after tstate from the list of all such
objects belonging to the same :c:type:PyInterpreterState object.