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# Exceptions

## Built-in C++ to Python exception translation

When Python calls C++ code through pybind11, pybind11 provides a C++ exception handler that will trap C++ exceptions, translate them to the corresponding Python exception, and raise them so that Python code can handle them.

pybind11 defines translations for `std::exception` and its standard subclasses, and several special exception classes that translate to specific Python exceptions. Note that these are not actually Python exceptions, so they cannot be examined using the Python C API. Instead, they are pure C++ objects that pybind11 will translate the corresponding Python exception when they arrive at its exception handler.

Exception thrown by C++ | Translated to Python exception type
--- | ---
`std::exception` | `RuntimeError`
`std::bad_alloc` | `MemoryError`
`std::domain_error` | `ValueError`
`std::invalid_argument` | `ValueError`
`std::length_error` | `ValueError`
`std::out_of_range` | `IndexError`
`std::range_error` | `ValueError`
`std::overflow_error` | `OverflowError`
`pybind11::stop_iteration` | `StopIteration` (used to implement custom iterators)
`pybind11::index_error` | `IndexError` (used to indicate out of bounds access in `__getitem__`, `__setitem__`, etc.)
`pybind11::key_error` | `KeyError` (used to indicate out of bounds access in `__getitem__`, `__setitem__` in dict-like objects, etc.)
`pybind11::value_error` | `ValueError` (used to indicate wrong value passed in `container.remove(...)`)
`pybind11::type_error` | `TypeError`
`pybind11::buffer_error` | `BufferError`
`pybind11::import_error` | `ImportError`
`pybind11::attribute_error` | `AttributeError`
Any other exception | `RuntimeError`

Exception translation is not bidirectional. That is, catching the C++ exceptions defined above will not trap exceptions that originate from Python. For that, catch `pybind11::error_already_set`. See below for further details.

There is also a special exception `cast_error` that is thrown by `handle::call()` when the input arguments cannot be converted to Python objects.

## Registering custom translators

If the default exception conversion policy described above is insufficient, pybind11 also provides support for registering custom exception translators. Similar to pybind11 classes, exception translators can be local to the module they are defined in or global to the entire python session. To register a simple exception conversion that translates a C++ exception into a new Python exception using the C++ exception’s `what()` method, a helper function is available:

    py::register_exception<CppExp>(module, "PyExp");

This call creates a Python exception class with the name `PyExp` in the given module and automatically converts any encountered exceptions of type `CppExp` into Python exceptions of type `PyExp`.

A matching function is available for registering a local exception translator:

    py::register_local_exception<CppExp>(module, "PyExp");

It is possible to specify base class for the exception using the third parameter, a `handle`:

    py::register_exception<CppExp>(module, "PyExp", PyExc_RuntimeError);
    py::register_local_exception<CppExp>(module, "PyExp", PyExc_RuntimeError);

Then `PyExp` can be caught both as `PyExp` and `RuntimeError`.

The class objects of the built-in Python exceptions are listed in the Python documentation on Standard Exceptions. The default base class is `PyExc_Exception`.

When more advanced exception translation is needed, the functions `py::register_exception_translator(translator)` and `py::register_local_exception_translator(translator)` can be used to register functions that can translate arbitrary exception types (and which may include additional logic to do so). The functions takes a stateless callable (e.g. a function pointer or a lambda function without captured variables) with the call signature `void(std::exception_ptr)`.

When a C++ exception is thrown, the registered exception translators are tried in reverse order of registration (i.e. the last registered translator gets the first shot at handling the exception). All local translators will be tried before a global translator is tried.

Inside the translator, `std::rethrow_exception` should be used within a try block to re-throw the exception. One or more catch clauses to catch the appropriate exceptions should then be used with each clause using `py::set_error()` (see below).

To declare a custom Python exception type, declare a `py::exception` variable and use this in the associated exception translator (note: it is often useful to make this a static declaration when using it inside a lambda expression without requiring capturing).

The following example demonstrates this for a hypothetical exception classes `MyCustomException` and `OtherException`: the first is translated to a custom python exception `MyCustomError`, while the second is translated to a standard python RuntimeError:

    PYBIND11_CONSTINIT static py::gil_safe_call_once_and_store<py::object> exc_storage;
    exc_storage.call_once_and_store_result(
        [&]() { return py::exception<MyCustomException>(m, "MyCustomError"); });
    py::register_exception_translator([](std::exception_ptr p) {
        try {
            if (p) std::rethrow_exception(p);
        } catch (const MyCustomException &e) {
            py::set_error(exc_storage.get_stored(), e.what());
        } catch (const OtherException &e) {
            py::set_error(PyExc_RuntimeError, e.what());
        }
    });

Multiple exceptions can be handled by a single translator, as shown in the example above. If the exception is not caught by the current translator, the previously registered one gets a chance.

If none of the registered exception translators is able to handle the exception, it is handled by the default converter as described in the previous section.

See also

The file `tests/test_exceptions.cpp` contains examples of various custom exception translators and custom exception types.

Note

Call `py::set_error()` for every exception caught in a custom exception translator. Failure to do so will cause Python to crash with `SystemError: error return without exception set`.

Exceptions that you do not plan to handle should simply not be caught, or may be explicitly (re-)thrown to delegate it to the other, previously-declared existing exception translators.

Note that `libc++` and `libstdc++` behave differently under macOS with `-fvisibility=hidden`. Therefore exceptions that are used across ABI boundaries need to be explicitly exported, as exercised in `tests/test_exceptions.h`. See also: “Problems with C++ exceptions” under GCC Wiki.

## Local vs Global Exception Translators

When a global exception translator is registered, it will be applied across all modules in the reverse order of registration. This can create behavior where the order of module import influences how exceptions are translated.

If module1 has the following translator:

    py::register_exception_translator([](std::exception_ptr p) {
      try {
          if (p) std::rethrow_exception(p);
      } catch (const std::invalid_argument &e) {
          py::set_error(PyExc_ArgumentError, "module1 handled this");
      }
    }

and module2 has the following similar translator:

    py::register_exception_translator([](std::exception_ptr p) {
      try {
          if (p) std::rethrow_exception(p);
      } catch (const std::invalid_argument &e) {
          py::set_error(PyExc_ArgumentError, "module2 handled this");
      }
    }

then which translator handles the invalid_argument will be determined by the order that module1 and module2 are imported. Since exception translators are applied in the reverse order of registration, which ever module was imported last will “win” and that translator will be applied.

If there are multiple pybind11 modules that share exception types (either standard built-in or custom) loaded into a single python instance and consistent error handling behavior is needed, then local translators should be used.

Changing the previous example to use `register_local_exception_translator` would mean that when invalid_argument is thrown in the module2 code, the module2 translator will always handle it, while in module1, the module1 translator will do the same.

## Handling exceptions from Python in C++

When C++ calls Python functions, such as in a callback function or when manipulating Python objects, and Python raises an `Exception`, pybind11 converts the Python exception into a C++ exception of type `pybind11::error_already_set` whose payload contains a C++ string textual summary and the actual Python exception. `error_already_set` is used to propagate Python exception back to Python (or possibly, handle them in C++).

Exception raised in Python | Thrown as C++ exception type
--- | ---
Any Python `Exception` | `pybind11::error_already_set`

For example:

    try {
        // open("missing.txt", "r")
        auto file = py::module_::import("io").attr("open")("missing.txt", "r");
        auto text = file.attr("read")();
        file.attr("close")();
    } catch (py::error_already_set &e) {
        if (e.matches(PyExc_FileNotFoundError)) {
            py::print("missing.txt not found");
        } else if (e.matches(PyExc_PermissionError)) {
            py::print("missing.txt found but not accessible");
        } else {
            throw;
        }
    }

Note that C++ to Python exception translation does not apply here, since that is a method for translating C++ exceptions to Python, not vice versa. The error raised from Python is always `error_already_set`.

This example illustrates this behavior:

    try {
        py::eval("raise ValueError('The Ring')");
    } catch (py::value_error &boromir) {
        // Boromir never gets the ring
        assert(false);
    } catch (py::error_already_set &frodo) {
        // Frodo gets the ring
        py::print("I will take the ring");
    }

    try {
        // py::value_error is a request for pybind11 to raise a Python exception
        throw py::value_error("The ball");
    } catch (py::error_already_set &cat) {
        // cat won't catch the ball since
        // py::value_error is not a Python exception
        assert(false);
    } catch (py::value_error &dog) {
        // dog will catch the ball
        py::print("Run Spot run");
        throw;  // Throw it again (pybind11 will raise ValueError)
    }

## Handling errors from the Python C API

Where possible, use pybind11 wrappers instead of calling the Python C API directly. When calling the Python C API directly, in addition to manually managing reference counts, one must follow the pybind11 error protocol, which is outlined here.

After calling the Python C API, if Python returns an error, `throw py::error_already_set();`, which allows pybind11 to deal with the exception and pass it back to the Python interpreter. This includes calls to the error setting functions such as `py::set_error()`.

    py::set_error(PyExc_TypeError, "C API type error demo");
    throw py::error_already_set();

    // But it would be easier to simply...
    throw py::type_error("pybind11 wrapper type error");

Alternately, to ignore the error, call PyErr_Clear.

Any Python error must be thrown or cleared, or Python/pybind11 will be left in an invalid state.

## Handling warnings from the Python C API

Wrappers for handling Python warnings are provided in `pybind11/warnings.h`. This header must be included explicitly; it is not transitively included via `pybind11/pybind11.h`.

Warnings can be raised with the `warn` function:

    py::warnings::warn("This is a warning!", PyExc_Warning);

    // Optionally, a `stack_level` can be specified.
    py::warnings::warn("Another one!", PyExc_DeprecationWarning, 3);

New warning types can be registered at the module level using `new_warning_type`:

    py::warnings::new_warning_type(m, "CustomWarning", PyExc_RuntimeWarning);

## Chaining exceptions (‘raise from’)

Python has a mechanism for indicating that exceptions were caused by other exceptions:

    try:
        print(1 / 0)
    except Exception as exc:
        raise RuntimeError("could not divide by zero") from exc

To do a similar thing in pybind11, you can use the `py::raise_from` function. It sets the current python error indicator, so to continue propagating the exception you should `throw py::error_already_set()`.

    try {
        py::eval("print(1 / 0"));
    } catch (py::error_already_set &e) {
        py::raise_from(e, PyExc_RuntimeError, "could not divide by zero");
        throw py::error_already_set();
    }

Added in version 2.8.

## Handling unraisable exceptions

If a Python function invoked from a C++ destructor or any function marked `noexcept(true)` (collectively, “noexcept functions”) throws an exception, there is no way to propagate the exception, as such functions may not throw. Should they throw or fail to catch any exceptions in their call graph, the C++ runtime calls `std::terminate()` to abort immediately.

Similarly, Python exceptions raised in a class’s `__del__` method do not propagate, but `sys.unraisablehook()` is triggered and an auditing event is logged.

Any noexcept function should have a try-catch block that traps class:`error_already_set` (or any other exception that can occur). Note that pybind11 wrappers around Python exceptions such as `pybind11::value_error` are not Python exceptions; they are C++ exceptions that pybind11 catches and converts to Python exceptions. Noexcept functions cannot propagate these exceptions either. A useful approach is to convert them to Python exceptions and then `discard_as_unraisable` as shown below.

    void nonthrowing_func() noexcept(true) {
        try {
            // ...
        } catch (py::error_already_set &eas) {
            // Discard the Python error using Python APIs, using the C++ magic
            // variable __func__. Python already knows the type and value and of the
            // exception object.
            eas.discard_as_unraisable(__func__);
        } catch (const std::exception &e) {
            // Log and discard C++ exceptions.
            third_party::log(e);
        }
    }

Added in version 2.6.