Inicialização, finalização e threads¶

Veja Configuração de inicialização do Python para detalhes sobre como configurar o interpretador antes da inicialização.

Antes da inicialização do Python¶

Em uma aplicação que incorpora Python, a função Py_Initialize() deve ser chamada antes de usar qualquer outra função da API Python/C; com exceção de algumas funções e as variáveis globais de configuração.

As seguintes funções podem ser seguramente chamadas antes da inicialização do Python.

Funções que inicializam o interpretador:
- Py_Initialize()
- Py_InitializeEx()
- Py_InitializeFromConfig()
- Py_BytesMain()
- Py_Main()
- as funções de pré-inicialização de tempo de execução cobertas em Configuração de Inicialização do Python
Funções de configuração
- PyImport_AppendInittab()
- PyImport_ExtendInittab()
- PyInitFrozenExtensions()
- PyMem_SetAllocator()
- PyMem_SetupDebugHooks()
- PyObject_SetArenaAllocator()
- Py_SetProgramName()
- Py_SetPythonHome()
- PySys_ResetWarnOptions()
- as funções de configuração cobertas em Configuração de Inicialização do Python
Funções informativas:
Utilitários:
- Py_DecodeLocale()
- o relatório de status é funções utilitárias cobertas em Configuração de Inicialização do Python
Alocadores de memória:
Sincronização:
- PyMutex_Lock()
- PyMutex_Unlock()

Nota

Apesar de sua aparente semelhança com algumas das funções listadas acima, as seguintes funções não devem ser chamadas antes que o interpretador tenha sido inicializado: Py_EncodeLocale(), Py_GetPath(), Py_GetPrefix(), Py_GetExecPrefix(), Py_GetProgramFullPath(), Py_GetPythonHome(), Py_GetProgramName(), PyEval_InitThreads(), e Py_RunMain().

Variáveis de configuração global¶

Python tem variáveis para a configuração global a fim de controlar diferentes características e opções. Por padrão, estes sinalizadores são controlados por opções de linha de comando.

Quando um sinalizador é definido por uma opção, o valor do sinalizador é o número de vezes que a opção foi definida. Por exemplo,``-b`` define Py_BytesWarningFlag para 1 e -bb define Py_BytesWarningFlag para 2.

int Py_BytesWarningFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.bytes_warning deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Emite um aviso ao comparar bytes ou bytearray com str ou bytes com int. Emite um erro se for maior ou igual a 2.

Definida pela opção -b.

Deprecated since version 3.12, removed in version 3.14.

int Py_DebugFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.parser_debug deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Ativa a saída de depuração do analisador sintático (somente para especialistas, dependendo das opções de compilação).

Definida pela a opção -d e a variável de ambiente PYTHONDEBUG.

Deprecated since version 3.12, removed in version 3.14.

int Py_DontWriteBytecodeFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.write_bytecode deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Se definida como diferente de zero, o Python não tentará escrever arquivos .pyc na importação de módulos fonte.

Definida pela opção -B e pela variável de ambiente PYTHONDONTWRITEBYTECODE.

Deprecated since version 3.12, removed in version 3.14.

int Py_FrozenFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.pathconfig_warnings deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Suprime mensagens de erro ao calcular o caminho de pesquisa do módulo em Py_GetPath().

Sinalizador privado usado pelos programas _freeze_module e frozenmain.

Deprecated since version 3.12, removed in version 3.14.

int Py_HashRandomizationFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração de PyConfig.hash_seed e PyConfig.use_hash_seed deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Definida como 1 se a variável de ambiente PYTHONHASHSEED estiver definida como uma string não vazia.

Se o sinalizador for diferente de zero, lê a variável de ambiente PYTHONHASHSEED para inicializar a semente de hash secreta.

Deprecated since version 3.12, removed in version 3.14.

int Py_IgnoreEnvironmentFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.use_environment deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Ignora todas as variáveis de ambiente PYTHON*, por exemplo PYTHONPATH e PYTHONHOME, que podem estar definidas.

Definida pelas opções -E e -I.

Deprecated since version 3.12, removed in version 3.14.

int Py_InspectFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.inspect deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Quando um script é passado como primeiro argumento ou a opção -c é usada, entre no modo interativo após executar o script ou o comando, mesmo quando sys.stdin não parece ser um terminal.

Definida pela opção -i e pela variável de ambiente PYTHONINSPECT.

Deprecated since version 3.12, removed in version 3.14.

int Py_InteractiveFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.interactive deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Definida pela opção -i.

Obsoleto desde a versão 3.12.

int Py_IsolatedFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.isolated deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Executa o Python no modo isolado. No modo isolado, sys.path não contém nem o diretório do script nem o diretório de pacotes de sites do usuário.

Definida pela opção -I.

Adicionado na versão 3.4.

Deprecated since version 3.12, removed in version 3.14.

int Py_LegacyWindowsFSEncodingFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyPreConfig.legacy_windows_fs_encoding deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Se o sinalizador for diferente de zero, use a codificação mbcs com o tratador de erros replace, em vez da codificação UTF-8 com o tratador de erros surrogatepass, para a codificação do sistema de arquivos e tratador de erros e codificação do sistema de arquivos.

Definida como 1 se a variável de ambiente PYTHONLEGACYWINDOWSFSENCODING estiver definida como uma string não vazia.

Veja PEP 529 para mais detalhes.

Disponibilidade

Deprecated since version 3.12, removed in version 3.14.

int Py_LegacyWindowsStdioFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.legacy_windows_stdio deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Se o sinalizador for diferente de zero, usa io.FileIO em vez de io._WindowsConsoleIO para fluxos padrão sys.

Definida como 1 se a variável de ambiente PYTHONLEGACYWINDOWSSTDIO estiver definida como uma string não vazia.

Veja a PEP 528 para mais detalhes.

Disponibilidade

Deprecated since version 3.12, removed in version 3.14.

int Py_NoSiteFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.site_import deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Desabilita a importação do módulo site e as manipulações dependentes do site de sys.path que isso acarreta. Também desabilita essas manipulações se site for explicitamente importado mais tarde (chame site.main() se você quiser que eles sejam acionados).

Definida pela opção -S.

Deprecated since version 3.12, removed in version 3.14.

int Py_NoUserSiteDirectory¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.user_site_directory deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Não adiciona o diretório site-packages de usuário a sys.path.

Definida pelas opções -s e -I, e pela variável de ambiente PYTHONNOUSERSITE.

Deprecated since version 3.12, removed in version 3.14.

int Py_OptimizeFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.optimization_level deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Definida pela opção -O e pela variável de ambiente PYTHONOPTIMIZE.

Deprecated since version 3.12, removed in version 3.14.

int Py_QuietFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.quiet deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Não exibe as mensagens de direito autoral e de versão nem mesmo no modo interativo.

Definida pela opção -q.

Adicionado na versão 3.2.

Deprecated since version 3.12, removed in version 3.14.

int Py_UnbufferedStdioFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.buffered_stdio deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Força os fluxos stdout e stderr a não serem armazenados em buffer.

Definida pela opção -u e pela variável de ambiente PYTHONUNBUFFERED.

Deprecated since version 3.12, removed in version 3.14.

int Py_VerboseFlag¶

Esta API é mantida para compatibilidade com versões anteriores: a configuração PyConfig.verbose deve ser usada em seu lugar, consulte Configuração de inicialização do Python.

Exibe uma mensagem cada vez que um módulo é inicializado, mostrando o local (nome do arquivo ou módulo embutido) de onde ele é carregado. Se maior ou igual a 2, exibe uma mensagem para cada arquivo que é verificado durante a busca por um módulo. Também fornece informações sobre a limpeza do módulo na saída.

Definida pela a opção -v e a variável de ambiente PYTHONVERBOSE.

Deprecated since version 3.12, removed in version 3.14.

Inicializando e encerrando o interpretador¶

void Py_Initialize()¶

Parte da ABI Estável.

Inicializa o interpretador Python. Em uma aplicação que incorpora o Python, isto deve ser chamado antes do uso de qualquer outra função do Python/C API; veja Antes da Inicialização do Python para algumas exceções.

Isso inicializa a tabela de módulos carregados (sys.modules) e cria os módulos fundamentais builtins, __main__ e sys. Também inicializa o caminho de pesquisa de módulos (sys.path). Isso não define sys.argv; use a API da Configuração de inicialização do Python para isso. Isso é um no-op quando chamado pela segunda vez (sem chamar Py_FinalizeEx() primeiro). Não há valor de retorno; é um erro fatal se a inicialização falhar.

Usa Py_InitializeFromConfig() para personalizar a Configuração de inicialização do Python.

Nota

No Windows, altera o modo do console de O_TEXT para O_BINARY, o que também afetará usos não Python do console usando o Runtime C.

void Py_InitializeEx(int initsigs)¶

Parte da ABI Estável.

Esta função funciona como Py_Initialize() se initsigs for 1. Se initsigs for 0, ela pula o registro de inicialização de manipuladores de sinal, o que pode ser útil quando o CPython é incorporado como parte de uma aplicação maior.

Usa Py_InitializeFromConfig() para personalizar a Configuração de inicialização do Python.

PyStatus Py_InitializeFromConfig(const PyConfig *config)¶

Initialize Python from config configuration, as described in Initialization with PyConfig.

See the Configuração de Inicialização do Python section for details on pre-initializing the interpreter, populating the runtime configuration structure, and querying the returned status structure.

int Py_IsInitialized()¶: Parte da ABI Estável.
Return true (nonzero) when the Python interpreter has been initialized, false (zero) if not. After Py_FinalizeEx() is called, this returns false until Py_Initialize() is called again.

int Py_IsFinalizing()¶: Parte da ABI Estável desde a versão 3.13.
Return true (non-zero) if the main Python interpreter is shutting down. Return false (zero) otherwise.

Adicionado na versão 3.13.

int Py_FinalizeEx()¶

Parte da ABI Estável desde a versão 3.6.

Undo all initializations made by Py_Initialize() and subsequent use of Python/C API functions, and destroy all sub-interpreters (see Py_NewInterpreter() below) that were created and not yet destroyed since the last call to Py_Initialize(). This is a no-op when called for a second time (without calling Py_Initialize() again first).

Since this is the reverse of Py_Initialize(), it should be called in the same thread with the same interpreter active. That means the main thread and the main interpreter. This should never be called while Py_RunMain() is running.

Normally the return value is 0. If there were errors during finalization (flushing buffered data), -1 is returned.

Note that Python will do a best effort at freeing all memory allocated by the Python interpreter. Therefore, any C-Extension should make sure to correctly clean up all of the preveiously allocated PyObjects before using them in subsequent calls to Py_Initialize(). Otherwise it could introduce vulnerabilities and incorrect behavior.

This function is provided for a number of reasons. An embedding application might want to restart Python without having to restart the application itself. An application that has loaded the Python interpreter from a dynamically loadable library (or DLL) might want to free all memory allocated by Python before unloading the DLL. During a hunt for memory leaks in an application a developer might want to free all memory allocated by Python before exiting from the application.

Bugs and caveats: The destruction of modules and objects in modules is done in random order; this may cause destructors (__del__() methods) to fail when they depend on other objects (even functions) or modules. Dynamically loaded extension modules loaded by Python are not unloaded. Small amounts of memory allocated by the Python interpreter may not be freed (if you find a leak, please report it). Memory tied up in circular references between objects is not freed. Interned strings will all be deallocated regardless of their reference count. Some memory allocated by extension modules may not be freed. Some extensions may not work properly if their initialization routine is called more than once; this can happen if an application calls Py_Initialize() and Py_FinalizeEx() more than once. Py_FinalizeEx() must not be called recursively from within itself. Therefore, it must not be called by any code that may be run as part of the interpreter shutdown process, such as atexit handlers, object finalizers, or any code that may be run while flushing the stdout and stderr files.

Levanta um evento de auditoria cpython._PySys_ClearAuditHooks sem argumentos.

Adicionado na versão 3.6.

void Py_Finalize()¶: Parte da ABI Estável.
This is a backwards-compatible version of Py_FinalizeEx() that disregards the return value.

int Py_BytesMain(int argc, char **argv)¶: Parte da ABI Estável desde a versão 3.8.
Similar to Py_Main() but argv is an array of bytes strings, allowing the calling application to delegate the text decoding step to the CPython runtime.

Adicionado na versão 3.8.

int Py_Main(int argc, wchar_t **argv)¶

Parte da ABI Estável.

The main program for the standard interpreter, encapsulating a full initialization/finalization cycle, as well as additional behaviour to implement reading configurations settings from the environment and command line, and then executing __main__ in accordance with Linha de comando.

This is made available for programs which wish to support the full CPython command line interface, rather than just embedding a Python runtime in a larger application.

The argc and argv parameters are similar to those which are passed to a C program’s main() function, except that the argv entries are first converted to wchar_t using Py_DecodeLocale(). It is also important to note that the argument list entries may be modified to point to strings other than those passed in (however, the contents of the strings pointed to by the argument list are not modified).

The return value will be 0 if the interpreter exits normally (i.e., without an exception), 1 if the interpreter exits due to an exception, or 2 if the argument list does not represent a valid Python command line.

Note that if an otherwise unhandled SystemExit is raised, this function will not return 1, but exit the process, as long as Py_InspectFlag is not set. If Py_InspectFlag is set, execution will drop into the interactive Python prompt, at which point a second otherwise unhandled SystemExit will still exit the process, while any other means of exiting will set the return value as described above.

In terms of the CPython runtime configuration APIs documented in the runtime configuration section (and without accounting for error handling), Py_Main is approximately equivalent to:

PyConfig config;
PyConfig_InitPythonConfig(&config);
PyConfig_SetArgv(&config, argc, argv);
Py_InitializeFromConfig(&config);
PyConfig_Clear(&config);

Py_RunMain();

In normal usage, an embedding application will call this function instead of calling Py_Initialize(), Py_InitializeEx() or Py_InitializeFromConfig() directly, and all settings will be applied as described elsewhere in this documentation. If this function is instead called after a preceding runtime initialization API call, then exactly which environmental and command line configuration settings will be updated is version dependent (as it depends on which settings correctly support being modified after they have already been set once when the runtime was first initialized).

int Py_RunMain(void)¶

Executes the main module in a fully configured CPython runtime.

Executes the command (PyConfig.run_command), the script (PyConfig.run_filename) or the module (PyConfig.run_module) specified on the command line or in the configuration. If none of these values are set, runs the interactive Python prompt (REPL) using the __main__ module’s global namespace.

If PyConfig.inspect is not set (the default), the return value will be 0 if the interpreter exits normally (that is, without raising an exception), or 1 if the interpreter exits due to an exception. If an otherwise unhandled SystemExit is raised, the function will immediately exit the process instead of returning 1.

If PyConfig.inspect is set (such as when the -i option is used), rather than returning when the interpreter exits, execution will instead resume in an interactive Python prompt (REPL) using the __main__ module’s global namespace. If the interpreter exited with an exception, it is immediately raised in the REPL session. The function return value is then determined by the way the REPL session terminates: returning 0 if the session terminates without raising an unhandled exception, exiting immediately for an unhandled SystemExit, and returning 1 for any other unhandled exception.

This function always finalizes the Python interpreter regardless of whether it returns a value or immediately exits the process due to an unhandled SystemExit exception.

See Python Configuration for an example of a customized Python that always runs in isolated mode using Py_RunMain().

Process-wide parameters¶

void Py_SetProgramName(const wchar_t *name)¶

Parte da ABI Estável.

This API is kept for backward compatibility: setting PyConfig.program_name should be used instead, see Python Initialization Configuration.

Esta função deve ser chamada antes de Py_Initialize() ser chamada pela primeira vez, caso seja solicitada. Ela diz ao interpretador o valor do argumento argv[0] para a função main() do programa (convertido em caracteres amplos). Isto é utilizado por Py_GetPath() e algumas outras funções abaixo para encontrar as bibliotecas de tempo de execução relativas ao executável do interpretador. O valor padrão é 'python'. O argumento deve apontar para um caractere string amplo terminado em zero no armazenamento estático, cujo conteúdo não mudará durante a execução do programa. Nenhum código no interpretador Python mudará o conteúdo deste armazenamento.

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

Obsoleto desde a versão 3.11.

wchar_t *Py_GetProgramName()¶

Parte da ABI Estável.

Return the program name set with PyConfig.program_name, or the default. The returned string points into static storage; the caller should not modify its value.

This function should not be called before Py_Initialize(), otherwise it returns NULL.

Alterado na versão 3.10: It now returns NULL if called before Py_Initialize().

Deprecated since version 3.13, will be removed in version 3.15: Get sys.executable instead.

wchar_t *Py_GetPrefix()¶

Parte da ABI Estável.

Return the prefix for installed platform-independent files. This is derived through a number of complicated rules from the program name set with PyConfig.program_name and some environment variables; for example, if the program name is '/usr/local/bin/python', the prefix is '/usr/local'. The returned string points into static storage; the caller should not modify its value. This corresponds to the prefix variable in the top-level Makefile and the --prefix argument to the configure script at build time. The value is available to Python code as sys.base_prefix. It is only useful on Unix. See also the next function.

This function should not be called before Py_Initialize(), otherwise it returns NULL.

Alterado na versão 3.10: It now returns NULL if called before Py_Initialize().

Deprecated since version 3.13, will be removed in version 3.15: Get sys.base_prefix instead, or sys.prefix if virtual environments need to be handled.

wchar_t *Py_GetExecPrefix()¶

Parte da ABI Estável.

Return the exec-prefix for installed platform-dependent files. This is derived through a number of complicated rules from the program name set with PyConfig.program_name and some environment variables; for example, if the program name is '/usr/local/bin/python', the exec-prefix is '/usr/local'. The returned string points into static storage; the caller should not modify its value. This corresponds to the exec_prefix variable in the top-level Makefile and the --exec-prefix argument to the configure script at build time. The value is available to Python code as sys.base_exec_prefix. It is only useful on Unix.

Background: The exec-prefix differs from the prefix when platform dependent files (such as executables and shared libraries) are installed in a different directory tree. In a typical installation, platform dependent files may be installed in the /usr/local/plat subtree while platform independent may be installed in /usr/local.

Generally speaking, a platform is a combination of hardware and software families, e.g. Sparc machines running the Solaris 2.x operating system are considered the same platform, but Intel machines running Solaris 2.x are another platform, and Intel machines running Linux are yet another platform. Different major revisions of the same operating system generally also form different platforms. Non-Unix operating systems are a different story; the installation strategies on those systems are so different that the prefix and exec-prefix are meaningless, and set to the empty string. Note that compiled Python bytecode files are platform independent (but not independent from the Python version by which they were compiled!).

System administrators will know how to configure the mount or automount programs to share /usr/local between platforms while having /usr/local/plat be a different filesystem for each platform.

This function should not be called before Py_Initialize(), otherwise it returns NULL.

Alterado na versão 3.10: It now returns NULL if called before Py_Initialize().

Deprecated since version 3.13, will be removed in version 3.15: Get sys.base_exec_prefix instead, or sys.exec_prefix if virtual environments need to be handled.

wchar_t *Py_GetProgramFullPath()¶

Parte da ABI Estável.

Return the full program name of the Python executable; this is computed as a side-effect of deriving the default module search path from the program name (set by PyConfig.program_name). The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.executable.

This function should not be called before Py_Initialize(), otherwise it returns NULL.

Alterado na versão 3.10: It now returns NULL if called before Py_Initialize().

Deprecated since version 3.13, will be removed in version 3.15: Get sys.executable instead.

wchar_t *Py_GetPath()¶

Parte da ABI Estável.

Return the default module search path; this is computed from the program name (set by PyConfig.program_name) and some environment variables. The returned string consists of a series of directory names separated by a platform dependent delimiter character. The delimiter character is ':' on Unix and macOS, ';' on Windows. The returned string points into static storage; the caller should not modify its value. The list sys.path is initialized with this value on interpreter startup; it can be (and usually is) modified later to change the search path for loading modules.

This function should not be called before Py_Initialize(), otherwise it returns NULL.

Alterado na versão 3.10: It now returns NULL if called before Py_Initialize().

Deprecated since version 3.13, will be removed in version 3.15: Get sys.path instead.

const char *Py_GetVersion()¶

Parte da ABI Estável.

Retorna a verão deste interpretador Python. Esta é uma string que se parece com

"3.0a5+ (py3k:63103M, May 12 2008, 00:53:55) \n[GCC 4.2.3]"

The first word (up to the first space character) is the current Python version; the first characters are the major and minor version separated by a period. The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.version.

Thread State and the Global Interpreter Lock¶

The Python interpreter is not fully thread-safe. In order to support multi-threaded Python programs, there’s a global lock, called the global interpreter lock or GIL, that must be held by the current thread before it can safely access Python objects. Without the lock, even the simplest operations could cause problems in a multi-threaded program: for example, when two threads simultaneously increment the reference count of the same object, the reference count could end up being incremented only once instead of twice.

Therefore, the rule exists that only the thread that has acquired the GIL may operate on Python objects or call Python/C API functions. In order to emulate concurrency of execution, the interpreter regularly tries to switch threads (see sys.setswitchinterval()). The lock is also released around potentially blocking I/O operations like reading or writing a file, so that other Python threads can run in the meantime.

The Python interpreter keeps some thread-specific bookkeeping information inside a data structure called PyThreadState. There’s also one global variable pointing to the current PyThreadState: it can be retrieved using PyThreadState_Get().

Releasing the GIL from extension code¶

A maioria dos códigos de extensão que manipulam a GIL tem a seguinte estrutura:

Save the thread state in a local variable.
Release the global interpreter lock.
... Do some blocking I/O operation ...
Reacquire the global interpreter lock.
Restore the thread state from the local variable.

This is so common that a pair of macros exists to simplify it:

Py_BEGIN_ALLOW_THREADS
... Do some blocking I/O operation ...
Py_END_ALLOW_THREADS

A macro Py_BEGIN_ALLOW_THREADS abre um novo bloco e declara uma variável local oculta; a macro Py_END_ALLOW_THREADS fecha o bloco.

The block above expands to the following code:

PyThreadState *_save;

_save = PyEval_SaveThread();
... Do some blocking I/O operation ...
PyEval_RestoreThread(_save);

Here is how these functions work: the global interpreter lock is used to protect the pointer to the current thread state. When releasing the lock and saving the thread state, the current thread state pointer must be retrieved before the lock is released (since another thread could immediately acquire the lock and store its own thread state in the global variable). Conversely, when acquiring the lock and restoring the thread state, the lock must be acquired before storing the thread state pointer.

Nota

Calling system I/O functions is the most common use case for releasing the GIL, but it can also be useful before calling long-running computations which don’t need access to Python objects, such as compression or cryptographic functions operating over memory buffers. For example, the standard zlib and hashlib modules release the GIL when compressing or hashing data.

Non-Python created threads¶

When threads are created using the dedicated Python APIs (such as the threading module), a thread state is automatically associated to them and the code showed above is therefore correct. However, when threads are created from C (for example by a third-party library with its own thread management), they don’t hold the GIL, nor is there a thread state structure for them.

If you need to call Python code from these threads (often this will be part of a callback API provided by the aforementioned third-party library), you must first register these threads with the interpreter by creating a thread state data structure, then acquiring the GIL, and finally storing their thread state pointer, before you can start using the Python/C API. When you are done, you should reset the thread state pointer, release the GIL, and finally free the thread state data structure.

The PyGILState_Ensure() and PyGILState_Release() functions do all of the above automatically. The typical idiom for calling into Python from a C thread is:

PyGILState_STATE gstate;
gstate = PyGILState_Ensure();

/* Perform Python actions here. */
result = CallSomeFunction();
/* evaluate result or handle exception */

/* Release the thread. No Python API allowed beyond this point. */
PyGILState_Release(gstate);

Note that the PyGILState_* functions assume there is only one global interpreter (created automatically by Py_Initialize()). Python supports the creation of additional interpreters (using Py_NewInterpreter()), but mixing multiple interpreters and the PyGILState_* API is unsupported.

Cuidados com o uso de fork()¶

Another important thing to note about threads is their behaviour in the face of the C fork() call. On most systems with fork(), after a process forks only the thread that issued the fork will exist. This has a concrete impact both on how locks must be handled and on all stored state in CPython’s runtime.

The fact that only the “current” thread remains means any locks held by other threads will never be released. Python solves this for os.fork() by acquiring the locks it uses internally before the fork, and releasing them afterwards. In addition, it resets any Lock Objects in the child. When extending or embedding Python, there is no way to inform Python of additional (non-Python) locks that need to be acquired before or reset after a fork. OS facilities such as pthread_atfork() would need to be used to accomplish the same thing. Additionally, when extending or embedding Python, calling fork() directly rather than through os.fork() (and returning to or calling into Python) may result in a deadlock by one of Python’s internal locks being held by a thread that is defunct after the fork. PyOS_AfterFork_Child() tries to reset the necessary locks, but is not always able to.

The fact that all other threads go away also means that CPython’s runtime state there must be cleaned up properly, which os.fork() does. This means finalizing all other PyThreadState objects belonging to the current interpreter and all other PyInterpreterState objects. Due to this and the special nature of the “main” interpreter, fork() should only be called in that interpreter’s “main” thread, where the CPython global runtime was originally initialized. The only exception is if exec() will be called immediately after.

Cautions regarding runtime finalization¶

In the late stage of interpreter shutdown, after attempting to wait for non-daemon threads to exit (though this can be interrupted by KeyboardInterrupt) and running the atexit functions, the runtime is marked as finalizing: _Py_IsFinalizing() and sys.is_finalizing() return true. At this point, only the finalization thread that initiated finalization (typically the main thread) is allowed to acquire the GIL.

If any thread, other than the finalization thread, attempts to acquire the GIL during finalization, either explicitly via PyGILState_Ensure(), Py_END_ALLOW_THREADS, PyEval_AcquireThread(), or PyEval_AcquireLock(), or implicitly when the interpreter attempts to reacquire it after having yielded it, the thread enters a permanently blocked state where it remains until the program exits. In most cases this is harmless, but this can result in deadlock if a later stage of finalization attempts to acquire a lock owned by the blocked thread, or otherwise waits on the blocked thread.

Gross? Yes. This prevents random crashes and/or unexpectedly skipped C++ finalizations further up the call stack when such threads were forcibly exited here in CPython 3.13 and earlier. The CPython runtime GIL acquiring C APIs have never had any error reporting or handling expectations at GIL acquisition time that would’ve allowed for graceful exit from this situation. Changing that would require new stable C APIs and rewriting the majority of C code in the CPython ecosystem to use those with error handling.

High-level API¶

Estes são os tipos e as funções mais comumente usados na escrita de um código de extensão em C, ou ao incorporar o interpretador Python:

type PyInterpreterState¶

Parte da API Limitada (como uma estrutura opaca).

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.

type PyThreadState¶

Parte da API Limitada (como uma estrutura opaca).

This data structure represents the state of a single thread. The only public data member is:

PyInterpreterState *interp¶: This thread’s interpreter state.

void PyEval_InitThreads()¶

Parte da ABI Estável.

Função descontinuada que não faz nada.

In Python 3.6 and older, this function created the GIL if it didn’t exist.

Alterado na versão 3.9: The function now does nothing.

Alterado na versão 3.7: Esta função agora é chamada por Py_Initialize(), então não há mais necessidade de você chamá-la.

Alterado na versão 3.2: Esta função não pode mais ser chamada antes de Py_Initialize().

Obsoleto desde a versão 3.9.

PyThreadState *PyEval_SaveThread()¶: Parte da ABI Estável.
Release the global interpreter lock (if it has been created) and reset the thread state to NULL, returning the previous thread state (which is not NULL). If the lock has been created, the current thread must have acquired it.

void PyEval_RestoreThread(PyThreadState *tstate)¶: Parte da ABI Estável.
Acquire the global interpreter lock (if it has been created) and set the thread state to tstate, which must not be NULL. If the lock has been created, the current thread must not have acquired it, otherwise deadlock ensues.

Nota

Calling this function from a thread when the runtime is finalizing will hang the thread until the program exits, even if the thread was not created by Python. Refer to Cautions regarding runtime finalization for more details.

Alterado na versão 3.14: Hangs the current thread, rather than terminating it, if called while the interpreter is finalizing.

PyThreadState *PyThreadState_Get()¶

Parte da ABI Estável.

Return the current thread state. The global interpreter lock must be held. When the current thread state is NULL, this issues a fatal error (so that the caller needn’t check for NULL).

PyThreadState *PyThreadState_GetUnchecked()¶: Similar to PyThreadState_Get(), but don’t kill the process with a fatal error if it is NULL. The caller is responsible to check if the result is NULL.

Adicionado na versão 3.13: In Python 3.5 to 3.12, the function was private and known as _PyThreadState_UncheckedGet().

PyThreadState *PyThreadState_Swap(PyThreadState *tstate)¶: Parte da ABI Estável.
Swap the current thread state with the thread state given by the argument tstate, which may be NULL. The global interpreter lock must be held and is not released.

The following functions use thread-local storage, and are not compatible with sub-interpreters:

PyGILState_STATE PyGILState_Ensure()¶

Parte da ABI Estável.

Certifique-se de que a thread atual esteja pronta para chamar a API Python C, independentemente do estado atual do Python ou da trava global do interpretador (GIL). Isso pode ser chamado quantas vezes desejar por uma thread, desde que cada chamada corresponda a uma chamada para PyGILState_Release(). Em geral, outras APIs relacionadas a threads podem ser usadas entre chamadas PyGILState_Ensure() e PyGILState_Release() desde que o estado da thread seja restaurado ao seu estado anterior antes de Release(). Por exemplo, o uso normal das macros Py_BEGIN_ALLOW_THREADS e Py_END_ALLOW_THREADS é aceitável.

The return value is an opaque “handle” to the thread state when PyGILState_Ensure() was called, and must be passed to PyGILState_Release() to ensure Python is left in the same state. Even though recursive calls are allowed, these handles cannot be shared - each unique call to PyGILState_Ensure() must save the handle for its call to PyGILState_Release().

When the function returns, the current thread will hold the GIL and be able to call arbitrary Python code. Failure is a fatal error.

Nota

Calling this function from a thread when the runtime is finalizing will hang the thread until the program exits, even if the thread was not created by Python. Refer to Cautions regarding runtime finalization for more details.

Alterado na versão 3.14: Hangs the current thread, rather than terminating it, if called while the interpreter is finalizing.

void PyGILState_Release(PyGILState_STATE)¶

Parte da ABI Estável.

Release any resources previously acquired. After this call, Python’s state will be the same as it was prior to the corresponding PyGILState_Ensure() call (but generally this state will be unknown to the caller, hence the use of the GILState API).

Every call to PyGILState_Ensure() must be matched by a call to PyGILState_Release() on the same thread.

PyThreadState *PyGILState_GetThisThreadState()¶: Parte da ABI Estável.
Get the current thread state for this thread. May return NULL if no GILState API has been used on the current thread. Note that the main thread always has such a thread-state, even if no auto-thread-state call has been made on the main thread. This is mainly a helper/diagnostic function.

int PyGILState_Check()¶: Return 1 if the current thread is holding the GIL and 0 otherwise. This function can be called from any thread at any time. Only if it has had its Python thread state initialized and currently is holding the GIL will it return 1. This is mainly a helper/diagnostic function. It can be useful for example in callback contexts or memory allocation functions when knowing that the GIL is locked can allow the caller to perform sensitive actions or otherwise behave differently.

Adicionado na versão 3.4.

The following macros are normally used without a trailing semicolon; look for example usage in the Python source distribution.

Py_BEGIN_ALLOW_THREADS¶: Parte da ABI Estável.
Esta macro se expande para { PyThreadState *_save; _save = PyEval_SaveThread();. Observe que ele contém uma chave de abertura; ele deve ser combinado com a seguinte macro Py_END_ALLOW_THREADS. Veja acima para uma discussão mais aprofundada desta macro.

Py_END_ALLOW_THREADS¶: Parte da ABI Estável.
Esta macro se expande para PyEval_RestoreThread(_save); }. Observe que ele contém uma chave de fechamento; ele deve ser combinado com uma macro Py_BEGIN_ALLOW_THREADS anterior. Veja acima para uma discussão mais aprofundada desta macro.

Py_BLOCK_THREADS¶: Parte da ABI Estável.
Esta macro se expande para PyEval_RestoreThread(_save);: é equivalente a Py_END_ALLOW_THREADS sem a chave de fechamento.

Py_UNBLOCK_THREADS¶: Parte da ABI Estável.
Esta macro se expande para _save = PyEval_SaveThread();: é equivalente a Py_BEGIN_ALLOW_THREADS sem a chave de abertura e declaração de variável.

Low-level API¶

All of the following functions must be called after Py_Initialize().

Alterado na versão 3.7: Py_Initialize() now initializes the GIL.

PyInterpreterState *PyInterpreterState_New()¶

Parte da ABI Estável.

Create a new interpreter state object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

Levanta um evento de auditoria cpython.PyInterpreterState_New sem argumentos.

void PyInterpreterState_Clear(PyInterpreterState *interp)¶

Parte da ABI Estável.

Reset all information in an interpreter state object. The global interpreter lock must be held.

Levanta um evento de auditoria cpython.PyInterpreterState_Clear sem argumentos.

void PyInterpreterState_Delete(PyInterpreterState *interp)¶: Parte da ABI Estável.
Destroy an interpreter state object. The global interpreter lock need not be held. The interpreter state must have been reset with a previous call to PyInterpreterState_Clear().

PyThreadState *PyThreadState_New(PyInterpreterState *interp)¶: Parte da ABI Estável.
Create a new thread state object belonging to the given interpreter object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

void PyThreadState_Clear(PyThreadState *tstate)¶: Parte da ABI Estável.
Reset all information in a thread state object. The global interpreter lock must be held.

Alterado na versão 3.9: This function now calls the PyThreadState.on_delete callback. Previously, that happened in PyThreadState_Delete().

void PyThreadState_Delete(PyThreadState *tstate)¶: Parte da ABI Estável.
Destroy a thread state object. The global interpreter lock need not be held. The thread state must have been reset with a previous call to PyThreadState_Clear().

void PyThreadState_DeleteCurrent(void)¶: Destroy the current thread state and release the global interpreter lock. Like PyThreadState_Delete(), the global interpreter lock must be held. The thread state must have been reset with a previous call to PyThreadState_Clear().

PyFrameObject *PyThreadState_GetFrame(PyThreadState *tstate)¶

Parte da ABI Estável desde a versão 3.10.

Get the current frame of the Python thread state tstate.

Return a strong reference. Return NULL if no frame is currently executing.

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 PyInterpreterState_Main() function returns a pointer to its state.

You can switch between sub-interpreters using the PyThreadState_Swap() function. You can create and destroy them using the following functions:

type PyInterpreterConfig¶

Structure containing most parameters to configure a sub-interpreter. Its values are used only in Py_NewInterpreterFromConfig() and never modified by the runtime.

Adicionado na versão 3.12.

Campos de estrutura:

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 check_multi_interp_extensions must be 1 (non-zero). If this is 1 then gil must not be PyInterpreterConfig_OWN_GIL.

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 subprocess module still works when fork is disallowed.

int allow_exec¶

If this is 0 then the runtime will not support replacing the current process via exec (e.g. os.execv()) in any thread where the sub-interpreter is currently active. Otherwise exec is unrestricted.

Note that the subprocess module still works when exec is disallowed.

int allow_threads¶: If this is 0 then the sub-interpreter’s threading module won’t create threads. Otherwise threads are allowed.

int allow_daemon_threads¶: If this is 0 then the sub-interpreter’s threading module won’t create daemon threads. Otherwise daemon threads are allowed (as long as allow_threads is non-zero).

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 Py_mod_multiple_interpreters.)

This must be 1 (non-zero) if use_main_obmalloc is 0.

int gil¶

This determines the operation of the GIL for the sub-interpreter. It may be one of the following:

PyInterpreterConfig_DEFAULT_GIL¶: Use the default selection (PyInterpreterConfig_SHARED_GIL).

PyInterpreterConfig_SHARED_GIL¶: Use (share) the main interpreter’s GIL.

PyInterpreterConfig_OWN_GIL¶: Use the sub-interpreter’s own GIL.

If this is PyInterpreterConfig_OWN_GIL then PyInterpreterConfig.use_main_obmalloc must be 0.

PyStatus Py_NewInterpreterFromConfig(PyThreadState **tstate_p, const PyInterpreterConfig *config)¶

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 builtins, __main__ and 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 thread state created in the new sub-interpreter. This thread state is made in the current 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 current thread state and there may not be a current thread state.

Like all other Python/C API functions, the global interpreter lock must be held before calling this function and is still held when it returns. Likewise a current thread state must be set on entry. On success, the returned thread state will be set as current. If the sub-interpreter is created with its own GIL then the GIL of the calling interpreter will be released. When the function returns, the new interpreter’s GIL will be held by the current thread and the previously interpreter’s GIL will remain released here.

Adicionado na versão 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 = Py_NewInterpreterFromConfig(&config);

Note that the config is used only briefly and does not get modified. During initialization the config’s values are converted into various PyInterpreterState values. A read-only copy of the config may be stored internally on the PyInterpreterState.

Extension modules are shared between (sub-)interpreters as follows:

For modules using multi-phase initialization, e.g. 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 single-phase initialization, e.g. 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 Py_FinalizeEx() and 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.

PyThreadState *Py_NewInterpreter(void)¶: Parte da ABI Estável.
Create a new sub-interpreter. This is essentially just a wrapper around 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.

void Py_EndInterpreter(PyThreadState *tstate)¶

Parte da ABI Estável.

Destroy the (sub-)interpreter represented by the given thread state. The given thread state must be the current thread state. See the discussion of thread states below. When the call returns, the current thread state is NULL. All thread states associated with this interpreter are destroyed. The global interpreter lock used by the target interpreter must be held before calling this function. No GIL is held when it returns.

Py_FinalizeEx() will destroy all sub-interpreters that haven’t been explicitly destroyed at that point.

A Per-Interpreter GIL¶

Using 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.)

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 immortal. In fact, this has been done for the builtin singletons, small integers, and a number of other builtin objects.

Se você preservar o isolamento, terá acesso à computação multi-core adequada, sem as complicações que acompanham o uso de threads livres. A falha em preservar o isolamento traz a exposição a todas as consequências de threads livres, incluindo corridas e travamentos difíceis de depurar.

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.

Adicionado na versão 3.12.

Bugs and caveats¶

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 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 PyGILState_Ensure() and PyGILState_Release() calls. Furthermore, extensions (such as ctypes) using these APIs to allow calling of Python code from non-Python created threads will probably be broken when using sub-interpreters.

Notificações assíncronas¶

A mechanism is provided to make asynchronous notifications to the main interpreter thread. These notifications take the form of a function pointer and a void pointer argument.

int Py_AddPendingCall(int (*func)(void*), void *arg)¶

Parte da ABI Estável.

Schedule a function to be called from the main interpreter thread. On success, 0 is returned and func is queued for being called in the main thread. On failure, -1 is returned without setting any exception.

When successfully queued, func will be eventually called from the main interpreter thread with the argument arg. It will be called asynchronously with respect to normally running Python code, but with both these conditions met:

on a bytecode boundary;
with the main thread holding the global interpreter lock (func can therefore use the full C API).

func must return 0 on success, or -1 on failure with an exception set. func won’t be interrupted to perform another asynchronous notification recursively, but it can still be interrupted to switch threads if the global interpreter lock is released.

This function doesn’t need a current thread state to run, and it doesn’t need the global interpreter lock.

To call this function in a subinterpreter, the caller must hold the GIL. Otherwise, the function func can be scheduled to be called from the wrong interpreter.

Aviso

This is a low-level function, only useful for very special cases. There is no guarantee that func will be called as quick as possible. If the main thread is busy executing a system call, func won’t be called before the system call returns. This function is generally not suitable for calling Python code from arbitrary C threads. Instead, use the PyGILState API.

Adicionado na versão 3.1.

Alterado na versão 3.9: If this function is called in a subinterpreter, the function func is now scheduled to be called from the subinterpreter, rather than being called from the main interpreter. Each subinterpreter now has its own list of scheduled calls.

Profiling and Tracing¶

The Python interpreter provides some low-level support for attaching profiling and execution tracing facilities. These are used for profiling, debugging, and coverage analysis tools.

This C interface allows the profiling or tracing code to avoid the overhead of calling through Python-level callable objects, making a direct C function call instead. The essential attributes of the facility have not changed; the interface allows trace functions to be installed per-thread, and the basic events reported to the trace function are the same as had been reported to the Python-level trace functions in previous versions.

typedef int (*Py_tracefunc)(PyObject *obj, PyFrameObject *frame, int what, PyObject *arg)¶

The type of the trace function registered using PyEval_SetProfile() and PyEval_SetTrace(). The first parameter is the object passed to the registration function as obj, frame is the frame object to which the event pertains, what is one of the constants PyTrace_CALL, PyTrace_EXCEPTION, PyTrace_LINE, PyTrace_RETURN, PyTrace_C_CALL, PyTrace_C_EXCEPTION, PyTrace_C_RETURN, or PyTrace_OPCODE, and arg depends on the value of what:

Value of what	Meaning of arg
`PyTrace_CALL`	Always `Py_None`.
`PyTrace_EXCEPTION`	Exception information as returned by `sys.exc_info()`.
`PyTrace_LINE`	Always `Py_None`.
`PyTrace_RETURN`	Value being returned to the caller, or `NULL` if caused by an exception.
`PyTrace_C_CALL`	Function object being called.
`PyTrace_C_EXCEPTION`	Function object being called.
`PyTrace_C_RETURN`	Function object being called.
`PyTrace_OPCODE`	Always `Py_None`.

int PyTrace_CALL¶: The value of the what parameter to a Py_tracefunc function when a new call to a function or method is being reported, or a new entry into a generator. Note that the creation of the iterator for a generator function is not reported as there is no control transfer to the Python bytecode in the corresponding frame.

int PyTrace_EXCEPTION¶: The value of the what parameter to a Py_tracefunc function when an exception has been raised. The callback function is called with this value for what when after any bytecode is processed after which the exception becomes set within the frame being executed. The effect of this is that as exception propagation causes the Python stack to unwind, the callback is called upon return to each frame as the exception propagates. Only trace functions receives these events; they are not needed by the profiler.

int PyTrace_LINE¶: The value passed as the what parameter to a Py_tracefunc function (but not a profiling function) when a line-number event is being reported. It may be disabled for a frame by setting f_trace_lines to 0 on that frame.

int PyTrace_RETURN¶: The value for the what parameter to Py_tracefunc functions when a call is about to return.

int PyTrace_C_CALL¶: The value for the what parameter to Py_tracefunc functions when a C function is about to be called.

int PyTrace_C_EXCEPTION¶: The value for the what parameter to Py_tracefunc functions when a C function has raised an exception.

int PyTrace_C_RETURN¶: The value for the what parameter to Py_tracefunc functions when a C function has returned.

int PyTrace_OPCODE¶: The value for the what parameter to Py_tracefunc functions (but not profiling functions) when a new opcode is about to be executed. This event is not emitted by default: it must be explicitly requested by setting f_trace_opcodes to 1 on the frame.

void PyEval_SetProfile(Py_tracefunc func, PyObject *obj)¶

Set the profiler function to func. The obj parameter is passed to the function as its first parameter, and may be any Python object, or NULL. If the profile function needs to maintain state, using a different value for obj for each thread provides a convenient and thread-safe place to store it. The profile function is called for all monitored events except PyTrace_LINE PyTrace_OPCODE and PyTrace_EXCEPTION.

See also the sys.setprofile() function.

The caller must hold the GIL.

void PyEval_SetProfileAllThreads(Py_tracefunc func, PyObject *obj)¶

Like PyEval_SetProfile() but sets the profile function in all running threads belonging to the current interpreter instead of the setting it only on the current thread.

The caller must hold the GIL.

As PyEval_SetProfile(), this function ignores any exceptions raised while setting the profile functions in all threads.

Adicionado na versão 3.12.

void PyEval_SetTrace(Py_tracefunc func, PyObject *obj)¶

Set the tracing function to func. This is similar to PyEval_SetProfile(), except the tracing function does receive line-number events and per-opcode events, but does not receive any event related to C function objects being called. Any trace function registered using PyEval_SetTrace() will not receive PyTrace_C_CALL, PyTrace_C_EXCEPTION or PyTrace_C_RETURN as a value for the what parameter.

Reference tracing¶

Adicionado na versão 3.13.

typedef int (*PyRefTracer)(PyObject*, int event, void *data)¶: The type of the trace function registered using PyRefTracer_SetTracer(). The first parameter is a Python object that has been just created (when event is set to PyRefTracer_CREATE) or about to be destroyed (when event is set to PyRefTracer_DESTROY). The data argument is the opaque pointer that was provided when PyRefTracer_SetTracer() was called.

Adicionado na versão 3.13.

int PyRefTracer_CREATE¶: The value for the event parameter to PyRefTracer functions when a Python object has been created.

int PyRefTracer_DESTROY¶: The value for the event parameter to PyRefTracer functions when a Python object has been destroyed.

int PyRefTracer_SetTracer(PyRefTracer tracer, void *data)¶

Register a reference tracer function. The function will be called when a new Python has been created or when an object is going to be destroyed. If data is provided it must be an opaque pointer that will be provided when the tracer function is called. Return 0 on success. Set an exception and return -1 on error.

Not that tracer functions must not create Python objects inside or otherwise the call will be re-entrant. The tracer also must not clear any existing exception or set an exception. The GIL will be held every time the tracer function is called.

The GIL must be held when calling this function.

Adicionado na versão 3.13.

PyRefTracer PyRefTracer_GetTracer(void **data)¶

Get the registered reference tracer function and the value of the opaque data pointer that was registered when PyRefTracer_SetTracer() was called. If no tracer was registered this function will return NULL and will set the data pointer to NULL.

The GIL must be held when calling this function.

Adicionado na versão 3.13.

Advanced Debugger Support¶

These functions are only intended to be used by advanced debugging tools.

PyInterpreterState *PyInterpreterState_Head()¶: Return the interpreter state object at the head of the list of all such objects.

PyInterpreterState *PyInterpreterState_Main()¶: Return the main interpreter state object.

PyInterpreterState *PyInterpreterState_Next(PyInterpreterState *interp)¶: Return the next interpreter state object after interp from the list of all such objects.

PyThreadState *PyInterpreterState_ThreadHead(PyInterpreterState *interp)¶: Return the pointer to the first PyThreadState object in the list of threads associated with the interpreter interp.

PyThreadState *PyThreadState_Next(PyThreadState *tstate)¶: Return the next thread state object after tstate from the list of all such objects belonging to the same PyInterpreterState object.

Thread Local Storage Support¶

The Python interpreter provides low-level support for thread-local storage (TLS) which wraps the underlying native TLS implementation to support the Python-level thread local storage API (threading.local). The CPython C level APIs are similar to those offered by pthreads and Windows: use a thread key and functions to associate a void* value per thread.

The GIL does not need to be held when calling these functions; they supply their own locking.

Note that Python.h does not include the declaration of the TLS APIs, you need to include pythread.h to use thread-local storage.

Nota

None of these API functions handle memory management on behalf of the void* values. You need to allocate and deallocate them yourself. If the void* values happen to be PyObject*, these functions don’t do refcount operations on them either.

Thread Specific Storage (TSS) API¶

TSS API is introduced to supersede the use of the existing TLS API within the CPython interpreter. This API uses a new type Py_tss_t instead of int to represent thread keys.

Adicionado na versão 3.7.

Ver também

“A New C-API for Thread-Local Storage in CPython” (PEP 539)

type Py_tss_t¶

This data structure represents the state of a thread key, the definition of which may depend on the underlying TLS implementation, and it has an internal field representing the key’s initialization state. There are no public members in this structure.

Quando Py_LIMITED_API não é definido, a alocação estática deste tipo por Py_tss_NEEDS_INIT é permitida.

Py_tss_NEEDS_INIT¶: This macro expands to the initializer for Py_tss_t variables. Note that this macro won’t be defined with Py_LIMITED_API.

Alocação dinâmica¶

Dynamic allocation of the Py_tss_t, required in extension modules built with Py_LIMITED_API, where static allocation of this type is not possible due to its implementation being opaque at build time.

Py_tss_t *PyThread_tss_alloc()¶: Parte da ABI Estável desde a versão 3.7.
Retorna um valor que é o mesmo estado de um valor inicializado com Py_tss_NEEDS_INIT, ou NULL no caso de falha de alocação dinâmica.

void PyThread_tss_free(Py_tss_t *key)¶: Parte da ABI Estável desde a versão 3.7.
Free the given key allocated by PyThread_tss_alloc(), after first calling PyThread_tss_delete() to ensure any associated thread locals have been unassigned. This is a no-op if the key argument is NULL.

Nota

A freed key becomes a dangling pointer. You should reset the key to NULL.

Métodos¶

The parameter key of these functions must not be NULL. Moreover, the behaviors of PyThread_tss_set() and PyThread_tss_get() are undefined if the given Py_tss_t has not been initialized by PyThread_tss_create().

int PyThread_tss_is_created(Py_tss_t *key)¶: Parte da ABI Estável desde a versão 3.7.
Return a non-zero value if the given Py_tss_t has been initialized by PyThread_tss_create().

int PyThread_tss_create(Py_tss_t *key)¶: Parte da ABI Estável desde a versão 3.7.
Retorna um valor zero na inicialização bem-sucedida de uma chave TSS. O comportamento é indefinido se o valor apontado pelo argumento key não for inicializado por Py_tss_NEEDS_INIT. Essa função pode ser chamada repetidamente na mesma tecla – chamá-la em uma tecla já inicializada não funciona e retorna imediatamente com sucesso.

void PyThread_tss_delete(Py_tss_t *key)¶: Parte da ABI Estável desde a versão 3.7.
Destroy a TSS key to forget the values associated with the key across all threads, and change the key’s initialization state to uninitialized. A destroyed key is able to be initialized again by PyThread_tss_create(). This function can be called repeatedly on the same key – calling it on an already destroyed key is a no-op.

int PyThread_tss_set(Py_tss_t *key, void *value)¶: Parte da ABI Estável desde a versão 3.7.
Return a zero value to indicate successfully associating a void* value with a TSS key in the current thread. Each thread has a distinct mapping of the key to a void* value.

void *PyThread_tss_get(Py_tss_t *key)¶: Parte da ABI Estável desde a versão 3.7.
Return the void* value associated with a TSS key in the current thread. This returns NULL if no value is associated with the key in the current thread.

Thread Local Storage (TLS) API¶

Obsoleto desde a versão 3.7: This API is superseded by Thread Specific Storage (TSS) API.

Nota

This version of the API does not support platforms where the native TLS key is defined in a way that cannot be safely cast to int. On such platforms, PyThread_create_key() will return immediately with a failure status, and the other TLS functions will all be no-ops on such platforms.

Due to the compatibility problem noted above, this version of the API should not be used in new code.

int PyThread_create_key()¶: Parte da ABI Estável.

void PyThread_delete_key(int key)¶: Parte da ABI Estável.

int PyThread_set_key_value(int key, void *value)¶: Parte da ABI Estável.

void *PyThread_get_key_value(int key)¶: Parte da ABI Estável.

void PyThread_delete_key_value(int key)¶: Parte da ABI Estável.

void PyThread_ReInitTLS()¶: Parte da ABI Estável.

Synchronization Primitives¶

The C-API provides a basic mutual exclusion lock.

type PyMutex¶

A mutual exclusion lock. The PyMutex should be initialized to zero to represent the unlocked state. For example:

PyMutex mutex = {0};

Instances of PyMutex should not be copied or moved. Both the contents and address of a PyMutex are meaningful, and it must remain at a fixed, writable location in memory.

Nota

A PyMutex currently occupies one byte, but the size should be considered unstable. The size may change in future Python releases without a deprecation period.

Adicionado na versão 3.13.

void PyMutex_Lock(PyMutex *m)¶: Lock mutex m. If another thread has already locked it, the calling thread will block until the mutex is unlocked. While blocked, the thread will temporarily release the GIL if it is held.

Adicionado na versão 3.13.

void PyMutex_Unlock(PyMutex *m)¶: Unlock mutex m. The mutex must be locked — otherwise, the function will issue a fatal error.

Adicionado na versão 3.13.

Python Critical Section API¶

The critical section API provides a deadlock avoidance layer on top of per-object locks for free-threaded CPython. They are intended to replace reliance on the global interpreter lock, and are no-ops in versions of Python with the global interpreter lock.

Critical sections avoid deadlocks by implicitly suspending active critical sections and releasing the locks during calls to PyEval_SaveThread(). When PyEval_RestoreThread() is called, the most recent critical section is resumed, and its locks reacquired. This means the critical section API provides weaker guarantees than traditional locks – they are useful because their behavior is similar to the GIL.

The functions and structs used by the macros are exposed for cases where C macros are not available. They should only be used as in the given macro expansions. Note that the sizes and contents of the structures may change in future Python versions.

Nota

Operations that need to lock two objects at once must use Py_BEGIN_CRITICAL_SECTION2. You cannot use nested critical sections to lock more than one object at once, because the inner critical section may suspend the outer critical sections. This API does not provide a way to lock more than two objects at once.

Exemplo de uso:

static PyObject *
set_field(MyObject *self, PyObject *value)
{
   Py_BEGIN_CRITICAL_SECTION(self);
   Py_SETREF(self->field, Py_XNewRef(value));
   Py_END_CRITICAL_SECTION();
   Py_RETURN_NONE;
}

In the above example, Py_SETREF calls Py_DECREF, which can call arbitrary code through an object’s deallocation function. The critical section API avoids potential deadlocks due to reentrancy and lock ordering by allowing the runtime to temporarily suspend the critical section if the code triggered by the finalizer blocks and calls PyEval_SaveThread().

Py_BEGIN_CRITICAL_SECTION(op)¶

Acquires the per-object lock for the object op and begins a critical section.

In the free-threaded build, this macro expands to:

{
    PyCriticalSection _py_cs;
    PyCriticalSection_Begin(&_py_cs, (PyObject*)(op))

In the default build, this macro expands to {.

Adicionado na versão 3.13.

Py_END_CRITICAL_SECTION()¶

Ends the critical section and releases the per-object lock.

In the free-threaded build, this macro expands to:

    PyCriticalSection_End(&_py_cs);
}

In the default build, this macro expands to }.

Adicionado na versão 3.13.

Py_BEGIN_CRITICAL_SECTION2(a, b)¶

Acquires the per-objects locks for the objects a and b and begins a critical section. The locks are acquired in a consistent order (lowest address first) to avoid lock ordering deadlocks.

In the free-threaded build, this macro expands to:

{
    PyCriticalSection2 _py_cs2;
    PyCriticalSection_Begin2(&_py_cs2, (PyObject*)(a), (PyObject*)(b))

In the default build, this macro expands to {.

Adicionado na versão 3.13.

Py_END_CRITICAL_SECTION2()¶

Ends the critical section and releases the per-object locks.

In the free-threaded build, this macro expands to:

    PyCriticalSection_End2(&_py_cs2);
}

In the default build, this macro expands to }.

Adicionado na versão 3.13.

Inicialização, finalização e threads¶

Antes da inicialização do Python¶

Variáveis de configuração global¶

Inicializando e encerrando o interpretador¶

Process-wide parameters¶

Thread State and the Global Interpreter Lock¶

Releasing the GIL from extension code¶

Non-Python created threads¶

Cuidados com o uso de fork()¶

Cautions regarding runtime finalization¶

High-level API¶

Low-level API¶

Sub-interpreter support¶

A Per-Interpreter GIL¶

Bugs and caveats¶

Notificações assíncronas¶

Profiling and Tracing¶

Reference tracing¶

Advanced Debugger Support¶

Thread Local Storage Support¶

Thread Specific Storage (TSS) API¶

Alocação dinâmica¶

Métodos¶

Thread Local Storage (TLS) API¶

Synchronization Primitives¶

Python Critical Section API¶

Tabela de Conteúdo

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