Upgrade guide

This is a companion guide to the Changelog. While the changelog briefly lists all of the new features, improvements and bug fixes, this upgrade guide focuses only the subset which directly impacts your experience when upgrading to a new version. But it goes into more detail. This includes things like deprecated APIs and their replacements, build system changes, general code modernization and other useful information.

v2.2

Deprecation of the PYBIND11_PLUGIN macro

PYBIND11_MODULE is now the preferred way to create module entry points. The old macro emits a compile-time deprecation warning.

// old
PYBIND11_PLUGIN(example) {
    py::module m("example", "documentation string");

    m.def("add", [](int a, int b) { return a + b; });

    return m.ptr();
}

// new
PYBIND11_MODULE(example, m) {
    m.doc() = "documentation string"; // optional

    m.def("add", [](int a, int b) { return a + b; });
}

New API for defining custom constructors and pickling functions

The old placement-new custom constructors have been deprecated. The new approach uses py::init() and factory functions to greatly improve type safety.

Placement-new can be called accidentally with an incompatible type (without any compiler errors or warnings), or it can initialize the same object multiple times if not careful with the Python-side __init__ calls. The new-style custom constructors prevent such mistakes. See Custom constructors for details.

// old -- deprecated (runtime warning shown only in debug mode)
py::class<Foo>(m, "Foo")
    .def("__init__", [](Foo &self, ...) {
        new (&self) Foo(...); // uses placement-new
    });

// new
py::class<Foo>(m, "Foo")
    .def(py::init([](...) { // Note: no `self` argument
        return new Foo(...); // return by raw pointer
        // or: return std::make_unique<Foo>(...); // return by holder
        // or: return Foo(...); // return by value (move constructor)
    }));

Mirroring the custom constructor changes, py::pickle() is now the preferred way to get and set object state. See Pickling support for details.

// old -- deprecated (runtime warning shown only in debug mode)
py::class<Foo>(m, "Foo")
    ...
    .def("__getstate__", [](const Foo &self) {
        return py::make_tuple(self.value1(), self.value2(), ...);
    })
    .def("__setstate__", [](Foo &self, py::tuple t) {
        new (&self) Foo(t[0].cast<std::string>(), ...);
    });

// new
py::class<Foo>(m, "Foo")
    ...
    .def(py::pickle(
        [](const Foo &self) { // __getstate__
            return py::make_tuple(f.value1(), f.value2(), ...); // unchanged
        },
        [](py::tuple t) { // __setstate__, note: no `self` argument
            return new Foo(t[0].cast<std::string>(), ...);
            // or: return std::make_unique<Foo>(...); // return by holder
            // or: return Foo(...); // return by value (move constructor)
        }
    ));

For both the constructors and pickling, warnings are shown at module initialization time (on import, not when the functions are called). They’re only visible when compiled in debug mode. Sample warning:

pybind11-bound class 'mymodule.Foo' is using an old-style placement-new '__init__'
which has been deprecated. See the upgrade guide in pybind11's docs.

Stricter enforcement of hidden symbol visibility for pybind11 modules

pybind11 now tries to actively enforce hidden symbol visibility for modules. If you’re using either one of pybind11’s CMake or Python build systems (the two example repositories) and you haven’t been exporting any symbols, there’s nothing to be concerned about. All the changes have been done transparently in the background. If you were building manually or relied on specific default visibility, read on.

Setting default symbol visibility to hidden has always been recommended for pybind11 (see How can I create smaller binaries?). On Linux and macOS, hidden symbol visibility (in conjunction with the strip utility) yields much smaller module binaries. CPython’s extension docs also recommend hiding symbols by default, with the goal of avoiding symbol name clashes between modules. Starting with v2.2, pybind11 enforces this more strictly: (1) by declaring all symbols inside the pybind11 namespace as hidden and (2) by including the -fvisibility=hidden flag on Linux and macOS (only for extension modules, not for embedding the interpreter).

The namespace-scope hidden visibility is done automatically in pybind11’s headers and it’s generally transparent to users. It ensures that:

• Modules compiled with different pybind11 versions don’t clash with each other.
• Some new features, like py::module_local bindings, can work as intended.

The -fvisibility=hidden flag applies the same visibility to user bindings outside of the pybind11 namespace. It’s now set automatic by pybind11’s CMake and Python build systems, but this needs to be done manually by users of other build systems. Adding this flag:

• Minimizes the chances of symbol conflicts between modules. E.g. if two unrelated modules were statically linked to different (ABI-incompatible) versions of the same third-party library, a symbol clash would be likely (and would end with unpredictable results).
• Produces smaller binaries on Linux and macOS, as pointed out previously.

Within pybind11’s CMake build system, pybind11_add_module has always been setting the -fvisibility=hidden flag in release mode. From now on, it’s being applied unconditionally, even in debug mode and it can no longer be opted out of with the NO_EXTRAS option. The pybind11::module target now also adds this flag to it’s interface. The pybind11::embed target is unchanged.

The most significant change here is for the pybind11::module target. If you were previously relying on default visibility, i.e. if your Python module was doubling as a shared library with dependents, you’ll need to either export symbols manually (recommended for cross-platform libraries) or factor out the shared library (and have the Python module link to it like the other dependents). As a temporary workaround, you can also restore default visibility using the CMake code below, but this is not recommended in the long run:

target_link_libraries(mymodule PRIVATE pybind11::module)

add_library(restore_default_visibility INTERFACE)
target_compile_options(restore_default_visibility INTERFACE -fvisibility=default)
target_link_libraries(mymodule PRIVATE restore_default_visibility)

Local STL container bindings

Previous pybind11 versions could only bind types globally – all pybind11 modules, even unrelated ones, would have access to the same exported types. However, this would also result in a conflict if two modules exported the same C++ type, which is especially problematic for very common types, e.g. std::vector<int>. Module-local class bindings were added to resolve this (see that section for a complete usage guide).

py::class_ still defaults to global bindings (because these types are usually unique across modules), however in order to avoid clashes of opaque types, py::bind_vector and py::bind_map will now bind STL containers as py::module_local if their elements are: builtins (int, float, etc.), not bound using py::class_, or bound as py::module_local. For example, this change allows multiple modules to bind std::vector<int> without causing conflicts. See Binding STL containers for more details.

When upgrading to this version, if you have multiple modules which depend on a single global binding of an STL container, note that all modules can still accept foreign py::module_local types in the direction of Python-to-C++. The locality only affects the C++-to-Python direction. If this is needed in multiple modules, you’ll need to either:

• Add a copy of the same STL binding to all of the modules which need it.
• Restore the global status of that single binding by marking it py::module_local(false).

The latter is an easy workaround, but in the long run it would be best to localize all common type bindings in order to avoid conflicts with third-party modules.

Negative strides for Python buffer objects and numpy arrays

Support for negative strides required changing the integer type from unsigned to signed in the interfaces of py::buffer_info and py::array. If you have compiler warnings enabled, you may notice some new conversion warnings after upgrading. These can be resolved using static_cast.

Deprecation of some py::object APIs

To compare py::object instances by pointer, you should now use obj1.is(obj2) which is equivalent to obj1 is obj2 in Python. Previously, pybind11 used operator== for this (obj1 == obj2), but that could be confusing and is now deprecated (so that it can eventually be replaced with proper rich object comparison in a future release).

For classes which inherit from py::object, borrowed and stolen were previously available as protected constructor tags. Now the types should be used directly instead: borrowed_t{} and stolen_t{} (#771).

Stricter compile-time error checking

Some error checks have been moved from run time to compile time. Notably, automatic conversion of std::shared_ptr<T> is not possible when T is not directly registered with py::class_<T> (e.g. std::shared_ptr<int> or std::shared_ptr<std::vector<T>> are not automatically convertible). Attempting to bind a function with such arguments now results in a compile-time error instead of waiting to fail at run time.

py::init<...>() constructor definitions are also stricter and now prevent bindings which could cause unexpected behavior:

struct Example {
    Example(int &);
};

py::class_<Example>(m, "Example")
    .def(py::init<int &>()); // OK, exact match
    // .def(py::init<int>()); // compile-time error, mismatch

A non-const lvalue reference is not allowed to bind to an rvalue. However, note that a constructor taking const T & can still be registered using py::init<T>() because a const lvalue reference can bind to an rvalue.

v2.1

Minimum compiler versions are enforced at compile time

The minimums also apply to v2.0 but the check is now explicit and a compile-time error is raised if the compiler does not meet the requirements:

• GCC >= 4.8
• clang >= 3.3 (appleclang >= 5.0)
• MSVC >= 2015u3
• Intel C++ >= 15.0

The py::metaclass attribute is not required for static properties

Binding classes with static properties is now possible by default. The zero-parameter version of py::metaclass() is deprecated. However, a new one-parameter py::metaclass(python_type) version was added for rare cases when a custom metaclass is needed to override pybind11’s default.

// old -- emits a deprecation warning
py::class_<Foo>(m, "Foo", py::metaclass())
    .def_property_readonly_static("foo", ...);

// new -- static properties work without the attribute
py::class_<Foo>(m, "Foo")
    .def_property_readonly_static("foo", ...);

// new -- advanced feature, override pybind11's default metaclass
py::class_<Bar>(m, "Bar", py::metaclass(custom_python_type))
    ...

v2.0

Breaking changes in py::class_

These changes were necessary to make type definitions in pybind11 future-proof, to support PyPy via its cpyext mechanism (#527), and to improve efficiency (rev. 86d825).

1. Declarations of types that provide access via the buffer protocol must now include the py::buffer_protocol() annotation as an argument to the py::class_ constructor.

   py::class_<Matrix>("Matrix", py::buffer_protocol())
       .def(py::init<...>())
       .def_buffer(...);
   

2. Classes which include static properties (e.g. def_readwrite_static()) must now include the py::metaclass() attribute. Note: this requirement has since been removed in v2.1. If you’re upgrading from 1.x, it’s recommended to skip directly to v2.1 or newer.

3. This version of pybind11 uses a redesigned mechanism for instantiating trampoline classes that are used to override virtual methods from within Python. This led to the following user-visible syntax change:

   // old v1.x syntax
   py::class_<TrampolineClass>("MyClass")
       .alias<MyClass>()
       ...
   
   // new v2.x syntax
   py::class_<MyClass, TrampolineClass>("MyClass")
       ...
   

   Importantly, both the original and the trampoline class are now specified as arguments to the py::class_ template, and the alias<..>() call is gone. The new scheme has zero overhead in cases when Python doesn’t override any functions of the underlying C++ class. rev. 86d825.

   The class type must be the first template argument given to py::class_ while the trampoline can be mixed in arbitrary order with other arguments (see the following section).

Deprecation of the py::base<T>() attribute

py::base<T>() was deprecated in favor of specifying T as a template argument to py::class_. This new syntax also supports multiple inheritance. Note that, while the type being exported must be the first argument in the py::class_<Class, ...> template, the order of the following types (bases, holder and/or trampoline) is not important.

// old v1.x
py::class_<Derived>("Derived", py::base<Base>());

// new v2.x
py::class_<Derived, Base>("Derived");

// new -- multiple inheritance
py::class_<Derived, Base1, Base2>("Derived");

// new -- apart from `Derived` the argument order can be arbitrary
py::class_<Derived, Base1, Holder, Base2, Trampoline>("Derived");

Out-of-the-box support for std::shared_ptr

The relevant type caster is now built in, so it’s no longer necessary to include a declaration of the form:

PYBIND11_DECLARE_HOLDER_TYPE(T, std::shared_ptr<T>)

Continuing to do so won’t cause an error or even a deprecation warning, but it’s completely redundant.

Deprecation of a few py::object APIs

All of the old-style calls emit deprecation warnings.

Old syntax	New syntax
obj.call(args...)	obj(args...)
obj.str()	py::str(obj)
auto l = py::list(obj); l.check()	py::isinstance<py::list>(obj)
py::object(ptr, true)	py::reinterpret_borrow<py::object>(ptr)
py::object(ptr, false)	py::reinterpret_steal<py::object>(ptr)
if (obj.attr("foo"))	if (py::hasattr(obj, "foo"))
if (obj["bar"])	if (obj.contains("bar"))