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msgid "Isolating Extension Modules"
msgid "Abstract"
msgstr "Streszczenie"
"Traditionally, state belonging to Python extension modules was kept in C "
"``static`` variables, which have process-wide scope. This document describes "
"problems of such per-process state and shows a safer way: per-module state."
"The document also describes how to switch to per-module state where "
"possible. This transition involves allocating space for that state, "
"potentially switching from static types to heap types, and—perhaps most "
"importantly—accessing per-module state from code."
msgid "Who should read this"
"This guide is written for maintainers of :ref:`C-API <c-api-index>` "
"extensions who would like to make that extension safer to use in "
"applications where Python itself is used as a library."
msgid "Background"
"An *interpreter* is the context in which Python code runs. It contains "
"configuration (e.g. the import path) and runtime state (e.g. the set of "
"imported modules)."
"Python supports running multiple interpreters in one process. There are two "
"cases to think about—users may run interpreters:"
"in sequence, with several :c:func:`Py_InitializeEx`/:c:func:`Py_FinalizeEx` "
"cycles, and"
"in parallel, managing \"sub-interpreters\" using :c:func:"
"`Py_NewInterpreter`/:c:func:`Py_EndInterpreter`."
"Both cases (and combinations of them) would be most useful when embedding "
"Python within a library. Libraries generally shouldn't make assumptions "
"about the application that uses them, which include assuming a process-wide "
"\"main Python interpreter\"."
"Historically, Python extension modules don't handle this use case well. Many "
"extension modules (and even some stdlib modules) use *per-process* global "
"state, because C ``static`` variables are extremely easy to use. Thus, data "
"that should be specific to an interpreter ends up being shared between "
"interpreters. Unless the extension developer is careful, it is very easy to "
"introduce edge cases that lead to crashes when a module is loaded in more "
"than one interpreter in the same process."
"Unfortunately, *per-interpreter* state is not easy to achieve. Extension "
"authors tend to not keep multiple interpreters in mind when developing, and "
"it is currently cumbersome to test the behavior."
msgid "Enter Per-Module State"
"Instead of focusing on per-interpreter state, Python's C API is evolving to "
"better support the more granular *per-module* state. This means that C-level "
"data should be attached to a *module object*. Each interpreter creates its "
"own module object, keeping the data separate. For testing the isolation, "
"multiple module objects corresponding to a single extension can even be "
"loaded in a single interpreter."
"Per-module state provides an easy way to think about lifetime and resource "
"ownership: the extension module will initialize when a module object is "
"created, and clean up when it's freed. In this regard, a module is just like "
"any other :c:expr:`PyObject *`; there are no \"on interpreter shutdown\" "
"hooks to think—or forget—about."
"Note that there are use cases for different kinds of \"globals\": per-"
"process, per-interpreter, per-thread or per-task state. With per-module "
"state as the default, these are still possible, but you should treat them as "
"exceptional cases: if you need them, you should give them additional care "
"and testing. (Note that this guide does not cover them.)"
msgid "Isolated Module Objects"
"The key point to keep in mind when developing an extension module is that "
"several module objects can be created from a single shared library. For "
">>> import sys\n"
">>> import binascii\n"
">>> old_binascii = binascii\n"
">>> del sys.modules['binascii']\n"
">>> import binascii  # create a new module object\n"
">>> old_binascii == binascii\n"
"As a rule of thumb, the two modules should be completely independent. All "
"objects and state specific to the module should be encapsulated within the "
"module object, not shared with other module objects, and cleaned up when the "
"module object is deallocated. Since this just is a rule of thumb, exceptions "
"are possible (see `Managing Global State`_), but they will need more thought "
"and attention to edge cases."
"While some modules could do with less stringent restrictions, isolated "
"modules make it easier to set clear expectations and guidelines that work "
"across a variety of use cases."
msgid "Surprising Edge Cases"
"Note that isolated modules do create some surprising edge cases. Most "
"notably, each module object will typically not share its classes and "
"exceptions with other similar modules. Continuing from the `example above "
"<Isolated Module Objects_>`__, note that ``old_binascii.Error`` and "
"``binascii.Error`` are separate objects. In the following code, the "
"exception is *not* caught:"
">>> old_binascii.Error == binascii.Error\n"
">>> try:\n"
"...     old_binascii.unhexlify(b'qwertyuiop')\n"
"... except binascii.Error:\n"
"...     print('boo')\n"
"Traceback (most recent call last):\n"
"  File \"<stdin>\", line 2, in <module>\n"
"binascii.Error: Non-hexadecimal digit found"
"This is expected. Notice that pure-Python modules behave the same way: it is "
"a part of how Python works."
"The goal is to make extension modules safe at the C level, not to make hacks "
"behave intuitively. Mutating ``sys.modules`` \"manually\" counts as a hack."
msgid "Making Modules Safe with Multiple Interpreters"
msgid "Managing Global State"
"Sometimes, the state associated with a Python module is not specific to that "
"module, but to the entire process (or something else \"more global\" than a "
"module). For example:"
msgid "The ``readline`` module manages *the* terminal."
"A module running on a circuit board wants to control *the* on-board LED."
"In these cases, the Python module should provide *access* to the global "
"state, rather than *own* it. If possible, write the module so that multiple "
"copies of it can access the state independently (along with other libraries, "
"whether for Python or other languages). If that is not possible, consider "
"explicit locking."
"If it is necessary to use process-global state, the simplest way to avoid "
"issues with multiple interpreters is to explicitly prevent a module from "
"being loaded more than once per process—see :ref:`isolating-extensions-"
msgid "Managing Per-Module State"
"To use per-module state, use :ref:`multi-phase extension module "
"initialization <multi-phase-initialization>`. This signals that your module "
"supports multiple interpreters correctly."
"Set ``PyModuleDef.m_size`` to a positive number to request that many bytes "
"of storage local to the module. Usually, this will be set to the size of "
"some module-specific ``struct``, which can store all of the module's C-level "
"state. In particular, it is where you should put pointers to classes "
"(including exceptions, but excluding static types) and settings (e.g. "
"``csv``'s :py:data:`~csv.field_size_limit`) which the C code needs to "
"function."
"Another option is to store state in the module's ``__dict__``, but you must "
"avoid crashing when users modify ``__dict__`` from Python code. This usually "
"means error- and type-checking at the C level, which is easy to get wrong "
"and hard to test sufficiently."
"However, if module state is not needed in C code, storing it in ``__dict__`` "
"only is a good idea."
"If the module state includes ``PyObject`` pointers, the module object must "
"hold references to those objects and implement the module-level hooks "
"``m_traverse``, ``m_clear`` and ``m_free``. These work like ``tp_traverse``, "
"``tp_clear`` and ``tp_free`` of a class. Adding them will require some work "
"and make the code longer; this is the price for modules which can be "
"unloaded cleanly."
"An example of a module with per-module state is currently available as "
"`xxlimited <https://github.com/python/cpython/blob/master/Modules/xxlimited."
"c>`__; example module initialization shown at the bottom of the file."
msgid "Opt-Out: Limiting to One Module Object per Process"
"A non-negative ``PyModuleDef.m_size`` signals that a module supports "
"multiple interpreters correctly. If this is not yet the case for your "
"module, you can explicitly make your module loadable only once per process. "
"For example::"
"// A process-wide flag\n"
"static int loaded = 0;\n"
"// Mutex to provide thread safety (only needed for free-threaded Python)\n"
"static PyMutex modinit_mutex = {0};\n"
"static int\n"
"exec_module(PyObject* module)\n"
"    PyMutex_Lock(&modinit_mutex);\n"
"    if (loaded) {\n"
"        PyMutex_Unlock(&modinit_mutex);\n"
"        PyErr_SetString(PyExc_ImportError,\n"
"                        \"cannot load module more than once per process\");\n"
"        return -1;\n"
"    loaded = 1;\n"
"    PyMutex_Unlock(&modinit_mutex);\n"
"    // ... rest of initialization\n"
"If your module's :c:member:`PyModuleDef.m_clear` function is able to prepare "
"for future re-initialization, it should clear the ``loaded`` flag. In this "
"case, your module won't support multiple instances existing *concurrently*, "
"but it will, for example, support being loaded after Python runtime shutdown "
"(:c:func:`Py_FinalizeEx`) and re-initialization (:c:func:`Py_Initialize`)."
msgid "Module State Access from Functions"
"Accessing the state from module-level functions is straightforward. "
"Functions get the module object as their first argument; for extracting the "
"state, you can use ``PyModule_GetState``::"
"static PyObject *\n"
"func(PyObject *module, PyObject *args)\n"
"    my_struct *state = (my_struct*)PyModule_GetState(module);\n"
"    if (state == NULL) {\n"
"        return NULL;\n"
"    // ... rest of logic\n"
"``PyModule_GetState`` may return ``NULL`` without setting an exception if "
"there is no module state, i.e. ``PyModuleDef.m_size`` was zero. In your own "
"module, you're in control of ``m_size``, so this is easy to prevent."
msgid "Heap Types"
"Traditionally, types defined in C code are *static*; that is, ``static "
"PyTypeObject`` structures defined directly in code and initialized using "
"``PyType_Ready()``."
"Such types are necessarily shared across the process. Sharing them between "
"module objects requires paying attention to any state they own or access. To "
"limit the possible issues, static types are immutable at the Python level: "
"for example, you can't set ``str.myattribute = 123``."
"Sharing truly immutable objects between interpreters is fine, as long as "
"they don't provide access to mutable objects. However, in CPython, every "
"Python object has a mutable implementation detail: the reference count. "
"Changes to the refcount are guarded by the GIL. Thus, code that shares any "
"Python objects across interpreters implicitly depends on CPython's current, "
"process-wide GIL."
"Because they are immutable and process-global, static types cannot access "
"\"their\" module state. If any method of such a type requires access to "
"module state, the type must be converted to a *heap-allocated type*, or "
"*heap type* for short. These correspond more closely to classes created by "
"Python's ``class`` statement."
msgid "For new modules, using heap types by default is a good rule of thumb."
msgid "Changing Static Types to Heap Types"
"Static types can be converted to heap types, but note that the heap type API "
"was not designed for \"lossless\" conversion from static types—that is, "
"creating a type that works exactly like a given static type. So, when "
"rewriting the class definition in a new API, you are likely to "
"unintentionally change a few details (e.g. pickleability or inherited "
"slots). Always test the details that are important to you."
"Watch out for the following two points in particular (but note that this is "
"not a comprehensive list):"
"Unlike static types, heap type objects are mutable by default. Use the :c:"
"macro:`Py_TPFLAGS_IMMUTABLETYPE` flag to prevent mutability."
"Heap types inherit :c:member:`~PyTypeObject.tp_new` by default, so it may "
"become possible to instantiate them from Python code. You can prevent this "
"with the :c:macro:`Py_TPFLAGS_DISALLOW_INSTANTIATION` flag."
msgid "Defining Heap Types"
"Heap types can be created by filling a :c:struct:`PyType_Spec` structure, a "
"description or \"blueprint\" of a class, and calling :c:func:"
"`PyType_FromModuleAndSpec` to construct a new class object."
"Other functions, like :c:func:`PyType_FromSpec`, can also create heap types, "
"but :c:func:`PyType_FromModuleAndSpec` associates the module with the class, "
"allowing access to the module state from methods."
"The class should generally be stored in *both* the module state (for safe "
"access from C) and the module's ``__dict__`` (for access from Python code)."
msgid "Garbage-Collection Protocol"
"Instances of heap types hold a reference to their type. This ensures that "
"the type isn't destroyed before all its instances are, but may result in "
"reference cycles that need to be broken by the garbage collector."
"To avoid memory leaks, instances of heap types must implement the garbage "
"collection protocol. That is, heap types should:"
msgid "Have the :c:macro:`Py_TPFLAGS_HAVE_GC` flag."
"Define a traverse function using :c:data:`Py_tp_traverse`, which visits the "
"type (e.g. using ``Py_VISIT(Py_TYPE(self))``)."
"Please refer to the documentation of :c:macro:`Py_TPFLAGS_HAVE_GC` and :c:"
"member:`~PyTypeObject.tp_traverse` for additional considerations."
"The API for defining heap types grew organically, leaving it somewhat "
"awkward to use in its current state. The following sections will guide you "
"through common issues."
msgid "``tp_traverse`` in Python 3.8 and lower"
"The requirement to visit the type from ``tp_traverse`` was added in Python "
"3.9. If you support Python 3.8 and lower, the traverse function must *not* "
"visit the type, so it must be more complicated::"
"static int my_traverse(PyObject *self, visitproc visit, void *arg)\n"
"    if (Py_Version >= 0x03090000) {\n"
"        Py_VISIT(Py_TYPE(self));\n"
"    return 0;\n"
"Unfortunately, :c:data:`Py_Version` was only added in Python 3.11. As a "
"replacement, use:"
msgid ":c:macro:`PY_VERSION_HEX`, if not using the stable ABI, or"
":py:data:`sys.version_info` (via :c:func:`PySys_GetObject` and :c:func:"
"`PyArg_ParseTuple`)."
msgid "Delegating ``tp_traverse``"
"If your traverse function delegates to the :c:member:`~PyTypeObject."
"tp_traverse` of its base class (or another type), ensure that "
"``Py_TYPE(self)`` is visited only once. Note that only heap type are "
"expected to visit the type in ``tp_traverse``."
msgid "For example, if your traverse function includes::"
msgid "base->tp_traverse(self, visit, arg)"
msgid "...and ``base`` may be a static type, then it should also include::"
"if (base->tp_flags & Py_TPFLAGS_HEAPTYPE) {\n"
"    // a heap type's tp_traverse already visited Py_TYPE(self)\n"
"} else {\n"
"    if (Py_Version >= 0x03090000) {\n"
"        Py_VISIT(Py_TYPE(self));\n"
"It is not necessary to handle the type's reference count in :c:member:"
"`~PyTypeObject.tp_new` and :c:member:`~PyTypeObject.tp_clear`."
msgid "Defining ``tp_dealloc``"
"If your type has a custom :c:member:`~PyTypeObject.tp_dealloc` function, it "
"needs to:"
"call :c:func:`PyObject_GC_UnTrack` before any fields are invalidated, and"
msgid "decrement the reference count of the type."
"To keep the type valid while ``tp_free`` is called, the type's refcount "
"needs to be decremented *after* the instance is deallocated. For example::"
"static void my_dealloc(PyObject *self)\n"
"    PyObject_GC_UnTrack(self);\n"
"    ...\n"
"    PyTypeObject *type = Py_TYPE(self);\n"
"    type->tp_free(self);\n"
"    Py_DECREF(type);\n"
"The default ``tp_dealloc`` function does this, so if your type does *not* "
"override ``tp_dealloc`` you don't need to add it."
msgid "Not overriding ``tp_free``"
"The :c:member:`~PyTypeObject.tp_free` slot of a heap type must be set to :c:"
"func:`PyObject_GC_Del`. This is the default; do not override it."
msgid "Avoiding ``PyObject_New``"
msgid "GC-tracked objects need to be allocated using GC-aware functions."
msgid "If you use :c:func:`PyObject_New` or :c:func:`PyObject_NewVar`:"
"Get and call type's :c:member:`~PyTypeObject.tp_alloc` slot, if possible. "
"That is, replace ``TYPE *o = PyObject_New(TYPE, typeobj)`` with::"
msgid "TYPE *o = typeobj->tp_alloc(typeobj, 0);"
"Replace ``o = PyObject_NewVar(TYPE, typeobj, size)`` with the same, but use "
"size instead of the 0."
"If the above is not possible (e.g. inside a custom ``tp_alloc``), call :c:"
"func:`PyObject_GC_New` or :c:func:`PyObject_GC_NewVar`::"
"TYPE *o = PyObject_GC_New(TYPE, typeobj);\n"
"TYPE *o = PyObject_GC_NewVar(TYPE, typeobj, size);"
msgid "Module State Access from Classes"
"If you have a type object defined with :c:func:`PyType_FromModuleAndSpec`, "
"you can call :c:func:`PyType_GetModule` to get the associated module, and "
"then :c:func:`PyModule_GetState` to get the module's state."
"To save a some tedious error-handling boilerplate code, you can combine "
"these two steps with :c:func:`PyType_GetModuleState`, resulting in::"
"my_struct *state = (my_struct*)PyType_GetModuleState(type);\n"
"if (state == NULL) {\n"
"    return NULL;\n"
msgid "Module State Access from Regular Methods"
"Accessing the module-level state from methods of a class is somewhat more "
"complicated, but is possible thanks to API introduced in Python 3.9. To get "
"the state, you need to first get the *defining class*, and then get the "
"module state from it."
"The largest roadblock is getting *the class a method was defined in*, or "
"that method's \"defining class\" for short. The defining class can have a "
"reference to the module it is part of."
"Do not confuse the defining class with ``Py_TYPE(self)``. If the method is "
"called on a *subclass* of your type, ``Py_TYPE(self)`` will refer to that "
"subclass, which may be defined in different module than yours."
"The following Python code can illustrate the concept. ``Base."
"get_defining_class`` returns ``Base`` even if ``type(self) == Sub``:"
"class Base:\n"
"    def get_type_of_self(self):\n"
"        return type(self)\n"
"    def get_defining_class(self):\n"
"        return __class__\n"
"class Sub(Base):\n"
"For a method to get its \"defining class\", it must use the :ref:"
"`METH_METHOD | METH_FASTCALL | METH_KEYWORDS <METH_METHOD-METH_FASTCALL-"
"METH_KEYWORDS>` :c:type:`calling convention <PyMethodDef>` and the "
"corresponding :c:type:`PyCMethod` signature::"
"PyObject *PyCMethod(\n"
"    PyObject *self,               // object the method was called on\n"
"    PyTypeObject *defining_class, // defining class\n"
"    PyObject *const *args,        // C array of arguments\n"
"    Py_ssize_t nargs,             // length of \"args\"\n"
"    PyObject *kwnames)            // NULL, or dict of keyword arguments"
"Once you have the defining class, call :c:func:`PyType_GetModuleState` to "
"get the state of its associated module."
msgid "For example::"
msgstr "Dla przykładu::"
"static PyObject *\n"
"example_method(PyObject *self,\n"
"        PyTypeObject *defining_class,\n"
"        PyObject *const *args,\n"
"        Py_ssize_t nargs,\n"
"        PyObject *kwnames)\n"
"    my_struct *state = (my_struct*)PyType_GetModuleState(defining_class);\n"
"    if (state == NULL) {\n"
"        return NULL;\n"
"    ... // rest of logic\n"
"PyDoc_STRVAR(example_method_doc, \"...\");\n"
"static PyMethodDef my_methods[] = {\n"
"    {\"example_method\",\n"
"      (PyCFunction)(void(*)(void))example_method,\n"
"      METH_METHOD|METH_FASTCALL|METH_KEYWORDS,\n"
"      example_method_doc}\n"
"    {NULL},\n"
msgid "Module State Access from Slot Methods, Getters and Setters"
msgid "This is new in Python 3.11."
"Slot methods—the fast C equivalents for special methods, such as :c:member:"
"`~PyNumberMethods.nb_add` for :py:attr:`~object.__add__` or :c:member:"
"`~PyTypeObject.tp_new` for initialization—have a very simple API that "
"doesn't allow passing in the defining class, unlike with :c:type:"
"`PyCMethod`. The same goes for getters and setters defined with :c:type:"
"`PyGetSetDef`."
"To access the module state in these cases, use the :c:func:"
"`PyType_GetModuleByDef` function, and pass in the module definition. Once "
"you have the module, call :c:func:`PyModule_GetState` to get the state::"
"PyObject *module = PyType_GetModuleByDef(Py_TYPE(self), &module_def);\n"
"my_struct *state = (my_struct*)PyModule_GetState(module);\n"
"if (state == NULL) {\n"
"    return NULL;\n"
":c:func:`!PyType_GetModuleByDef` works by searching the :term:`method "
"resolution order` (i.e. all superclasses) for the first superclass that has "
"a corresponding module."
"In very exotic cases (inheritance chains spanning multiple modules created "
"from the same definition), :c:func:`!PyType_GetModuleByDef` might not return "
"the module of the true defining class. However, it will always return a "
"module with the same definition, ensuring a compatible C memory layout."
msgid "Lifetime of the Module State"
"When a module object is garbage-collected, its module state is freed. For "
"each pointer to (a part of) the module state, you must hold a reference to "
"the module object."
"Usually this is not an issue, because types created with :c:func:"
"`PyType_FromModuleAndSpec`, and their instances, hold a reference to the "
"module. However, you must be careful in reference counting when you "
"reference module state from other places, such as callbacks for external "
"libraries."
msgid "Open Issues"
msgid "Several issues around per-module state and heap types are still open."
"Discussions about improving the situation are best held on the `discuss "
"forum under c-api tag <https://discuss.python.org/c/core-dev/c-api/30>`__."
msgid "Per-Class Scope"
"It is currently (as of Python 3.11) not possible to attach state to "
"individual *types* without relying on CPython implementation details (which "
"may change in the future—perhaps, ironically, to allow a proper solution for "
"per-class scope)."
msgid "Lossless Conversion to Heap Types"
"The heap type API was not designed for \"lossless\" conversion from static "
"types; that is, creating a type that works exactly like a given static type."
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