genpybind

Autogeneration of Python bindings from manually annotated C++ headers

Genpybind is a tool based on clang that automatically generates code to expose a C++ API as a Python extension via pybind11. Say goodbye to the tedious task of writing and updating binding code by hand! Genpybind ensures that your Python bindings always stay in sync with your C++ API, complete with docstrings, parameter names, and default arguments. This is especially valuable for still-evolving APIs where manual bindings can quickly become outdated.

While genpybind does require some manual hints in the form of unobtrusive annotation macros¹, it results in a self-contained header file that concisely describes both the C++ and Python interfaces of your library. This approach keeps you in control and requires less heuristics in genpybind's implementation, thereby reducing complexity. Though it does require the ability to modify the original interface declarations, so code which is not under your control needs to fall back on manually written bindings.

Besides the main use case of exposing a C++ API to Python, genpybind has proven useful during C++ library development:

It enables interactive exploration of a library's API via the Python REPL.
This exploration can form the basis for unit tests using Python's low-boilerplate testing frameworks like pytest.
And maybe most importantly, it enables hassle-free property-based testing via hypothesis, which still has no C++-native equivalent.

Example

To expose a C++ interface via a Python module, GENPYBIND annotations are added to the C++ declarations:

#pragma once

#include <genpybind/genpybind.h>

namespace readme GENPYBIND(visible) {

/// Describes how the output will taste.
enum class Flavor {
  /// Like you would expect.
  bland,
  /// It tastes different.
  fruity,
};

/// A contrived example.
class Example {
public:
  static constexpr int GENPYBIND(hidden) not_exposed = 10;

  /// Do a complicated calculation.
  int calculate(Flavor flavor = Flavor::fruity) const;

  GENPYBIND(getter_for(something))
  int getSomething() const;

  GENPYBIND(setter_for(something))
  void setSomething(int value);

private:
  int m_value = 0;
};

} // namespace readme

The resulting module can then be used like this:

>>> import readme as m
>>> obj = m.Example()
>>> obj.something
0
>>> obj.something = 42
>>> obj.something
42
>>> obj.calculate()  # default argument
-42
>>> obj.calculate(m.Flavor.bland)
42
>>> print(m.Example.__doc__)
A contrived example.
>>> print(m.Flavor.__doc__)
Describes how the output will taste.

Members:

  bland : Like you would expect.

  fruity : It tastes different.
>>> help(obj.calculate)
Help on method calculate in module readme:

calculate(...) method of readme.Example instance
    calculate(self: readme.Example, flavor: readme.Flavor = <Flavor.fruity: 1>) -> int

    Do a complicated calculation.

For the example presented above, genpybind will generate code equivalent to the following: (Note that docstrings, argument names and default arguments work out of the box, without extra annotations.)

void expose_context_readme_Flavor(py::enum_<readme::Flavor>& context);
void expose_context_readme_Example(py::class_<readme::Example>& context);

PYBIND11_MODULE(readme, root) {
  auto context_readme_Flavor = py::enum_<readme::Flavor>(
      root, "Flavor", "Describes how the output will taste.");
  auto context_readme_Example = py::class_<readme::Example>(
      root, "Example", "A contrived example.");

  expose_context_readme_Flavor(context_readme_Flavor);
  expose_context_readme_Example(context_readme_Example);
}

void expose_context_readme_Flavor(py::enum_<readme::Flavor>& context) {
  context.value("bland", readme::Flavor::bland, "Like you would expect.");
  context.value("fruity", readme::Flavor::fruity, "It tastes different.");
}

void expose_context_readme_Example(py::class_<readme::Example>& context) {
  context.def(py::init<>(), "");
  context.def(py::init<const readme::Example&>(), "", py::arg(""));
  context.def("calculate",
              py::overload_cast<readme::Flavor>(&readme::Example::calculate, py::const_),
              "Do a complicated calculation.",
              py::arg("flavor") = readme::Flavor::fruity);
  context.def_property(
      "something",
      py::overload_cast<>(&readme::Example::getSomething, py::const_),
      py::overload_cast<int>(&readme::Example::setSomething));
}

Implementation

The current implementation is a prototype based on clang's libtooling API. A previous proof-of-concept Python implementation I developed at the Electronic Vision(s) Group ran into limits of the libclang bindings and required a patched LLVM/clang build. Still, it's used successfully in the experiment software stack of their neuromorphic computing platform, i.e., the described approach is viable for an existing code base.

The current iteration still lacks some polishing. Some known shortcomings remain, the documentation is still lacking, and build support (and automated testing) on different platforms is pending.

Known defects and shortcomings

Documentation is minimal at the moment. If you want to look at example use-cases the integration tests might provide a starting point.
Expressions and types in default arguments, return values, or GENPYBIND_MANUAL instructions are not consistently expanded to their fully qualified form. As a workaround it is suggested to use the fully-qualified name where necessary.

Changes compared to the Python prototype

Apart from the less involved build process, the current implementation comes with many new features and improvements. For example, considerably better error messages. As a small price to pay there are several breaking changes:

opaque is now known as expose_here.
expose_as(__repr__) (or __str__) should be used in place of stringstream.
tag should be replaced by only_expose_in.
inline_base no longer supports globs/wildcards.
accessor_for is no longer supported, use getter_for/setter_for instead.
writeable is no longer supported, use readonly instead.

Installation

So far, the only tested platform is Fedora Workstation 40, though at least Debian has been tested in the past. You should be able to adapt the instructions to other distributions.

Check out the repo, the following commands should be run from the repo root.

Install dependencies:

dnf install \
  llvm-devel clang-devel gtest-devel gmock-devel cmake ninja-build \
  python3-devel python3-pip pybind11-devel

Set up the build:
```
cmake -B ./build -G Ninja .
```

Build and install (adapt the prefix accordingly):

cmake --build ./build
cmake --install ./build --prefix ~/.local

See genpybind_add_module in tools/genpybind.cmake and how it's used in an example project for how to integrate genpybind into your build. Depending on the prefix you used during installation, you might need to specify the location of genpybindConfig.cmake explicitly in downstream builds, e.g.: cmake … -Dgenpybind_DIR="$HOME/.local/share/cmake/genpybind" ….

Extra steps (for development)

Inside a virtual environment (e.g., via direnv with layout python), install the Python dependencies (used in tests):
```
pip install -r requirements.txt
```

Set up pre-commit:

pip install pre-commit
pre-commit install

Build and run the tests:
```
PYTHONPATH=$PWD/build/tests ninja -C build test
```
If you use direnv, it's convenient to add path_add PYTHONPATH build/tests to your .envrc.

Annotations

Top-level declarations are only exposed via the Python bindings (“visible”) if they have a GENPYBIND(…) annotation. Nested declarations, such as member variables and member functions inherit the visibility of their parent by default.

There are several possible modifiers that can be passed as arguments to GENPYBIND(…) to affect how and where a declaration is exposed or to make use of advanced pybind11 features.

Where to place the `GENPYBIND(…)` annotation

Behind the scenes, the GENPYBIND macro expands to an attribute, in particular the older GNU extension syntax __attribute__ at this time. Consequently, you can consult the GCC documentation on details w.r.t. attribute placement. Here are some common examples for your convenience:

struct GENPYBIND(visible) Example {
  void hidden_method() GENPYBIND(hidden);

  GENPYBIND(readonly)
  int readonly_field = 3;
};
enum class GENPYBIND(visible) Enum {};
void example() GENPYBIND(visible);

namespace readme GENPYBIND(visible) {}

TODO: Describe annotation argument types and when quotes can be omitted for string arguments.

General modifiers

`visible` and `hidden`

visible and hidden can be used to override the default visibility of a declaration. By default, top-level declarations are hidden, and nested declarations inherit the visibility of their parent. So one has to explicitly “opt-in” to exposing a declaration. Any use of GENPYBIND(…) annotations (even without arguments) implies visible, unless hidden is used explicitly.

Namespaces are a special case: By default, they have no effect on the visibility of contained declarations and other attributes on namespaces do not imply visible. However, an explicit visible annotation on a namespace can be used to make all nested declarations visible by default. The hidden keyword can then be used to exclude individual declarations again.

struct GENPYBIND() A {
  GENPYBIND(hidden)
  int some_field;
};

struct GENPYBIND(visible) B {};

// This would not have been exposed anyways, but we can
// include `hidden` to document our intent explicitly.
struct GENPYBIND(hidden) C {};

namespace example GENPYBIND(visible) {
struct Example {}; // Visible, even though there is no annotation.
}

`expose_as`

By default a declaration will be exposed using the name of its C++ identifier. expose_as can be used to choose a different name in the Python bindings:

struct GENPYBIND(expose_as(Example)) example {};

This can also be used to define special methods like __repr__ or __hash__:

GENPYBIND(expose_as(__hash__))
int hash() const;

`GENPYBIND_MANUAL` (manual bindings)

You can always fall back on hand-written bindings that is embedded in the generated binding code. This can be a convenient escape hatch for pybind11 features that are not (yet) supported by genpybind.

Inside structs and classes

Inside structs and classes, parent can be used to refer to the corresponding pybind11::class_ instance. If you need to access members of the parent class, you can use GENPYBIND_PARENT_TYPE instead of directly referring to its name. This is necessary, as the definitions is not yet complete at the point of the macro.

struct GENPYBIND(visible) Example {
  bool values[2] GENPYBIND(hidden) = {false, false};

  GENPYBIND_MANUAL({
    using Example = GENPYBIND_PARENT_TYPE;
    parent.def("__getitem__",
               [](Example& self, bool key) { return self.values[key]; });
    parent.def("__setitem__", [](Example& self, bool key, bool value) {
      self.values[key] = value;
    });
  })

At the top level, as a preamble or `postamble` to the binding code

If GENPYBIND_MANUAL is usde at the top-level, the contained code is emitted before all auto-generated binding code. This can be useful to, e.g., import another module (see the only_expose_in annotation on namespaces) that is used in function signatures:

GENPYBIND_MANUAL({
  ::pybind11::module::import("common");
})

The postamble modifier can be used to embed code after all auto-generated binding code, e.g., to dynamically patch the generated bindings:

GENPYBIND(postamble)
GENPYBIND_MANUAL({
  auto example = parent.attr("Example");
  // …patch example…
})

Note that parent can be used to refer to the corresponding pybind11::module.

In general, different GENPYBIND_MANUAL blocks are emitted in the order in which they were defined.

Namespaces

For all accessible headers, the annotations of a particular header have to match, as long as the namespace contains at least one annotated declaration exposed via the bindings:

namespace example GENPYBIND(module) {
struct GENPYBIND(visible) Example {};
}

// OK: No annotated declarations
namespace example {
struct Hidden {};
}

// OK: Same annotations
namespace example GENPYBIND(module) {
struct GENPYBIND(visible) Other {};
}

`module`

Namespaces can be annotated using module to turn them into sub-modules of the generated Python module. Namespaces that do not have this annotation have no effect on the module hierarchy of the generated Python bindings.

E.g., if readme is the name of the top-level module, X in the following example would be exposed as readme.nested.X:

namespace nested GENPYBIND(module) {
class GENPYBIND(visible) X {};
} // namespace nested

`only_expose_in`

When generating multiple Python libraries, only_expose_in should be used to only expose declarations in the corresponding module. When used on a namespace, all nested declarations are only exposed if one of the arguments to only_expose_in matches the name of the top-level module, which is derived from the basename of the header file passed to genpybind. For example:

// In common.h:
namespace common GENPYBIND(only_expose_in(common)) {
struct GENPYBIND(visible) Example {};
}

// In downstream.h:
# include <…/common.h>
namespace downstream GENPYBIND(only_expose_in(downstream)) {
void sink(common::Example input) GENPYBIND(visible);
}

Example is only available via the common module, instead of being duplicated / exposed twice:

from common import Example
from downstream import sink
sink(Example())

Enums

`arithmetic`

The arithmetic modifier can be used to expose arithmetic operations on the generated enum by passing the pybind11::arithmetic() tag to the pybind11::enum_ constructor:

enum GENPYBIND(arithmetic) Access { READ = 4, WRITE = 2, EXECUTE = 1 };

`export_values`

The export_values modifier controls whether enumerators are available in the parent scope. By default, this is only the case for unscoped enums.

In the following example defaults are overridden s.t. RED is only available as example.Color.RED and HIGH is available as example.HIGH:

enum GENPYBIND(export_values(false)) Color { RED, GREEN, BLUE };

enum class GENPYBIND(export_values) Level { HIGH, MEDIUM, LOW };

Structs and classes

`dynamic_attr` (dynamic attributes)

The dynamic_attr modifier can be used to allow additional attributes to be set at runtime, by passing the pybind11::dynamic_attr() tag to the pybind11::class_ constructor. I.e., in the following example, thing.unknown_attribute = 5 would work on an instance thing = Thing().

struct GENPYBIND(dynamic_attr) Thing {};

`hide_base`

By default, base classes included as template parameters of pybind11::class_, which has the effect that the inheritance relationship is represented on the Python side. If that's not what you want, you can opt out using hide_base:

struct GENPYBIND(hide_base) HideAll : common::Base, Base2, Base3 {};
struct GENPYBIND(hide_base("common::Base")) HideOne : common::Base, Base2, Base3 {};
struct GENPYBIND(hide_base("Base2", "Base3")) HideTwo : common::Base, Base2, Base3 {};

`holder_type`

The holder_type modifier can be used to set the [holder type][pybind11-smart] used to manage references to objects (defaults to std::unique_ptr<…>).

struct GENPYBIND(holder_type("std::shared_ptr<Example>")) Example
    : public std::enable_shared_from_this<Example> {
  std::shared_ptr<Example> clone();
};

`implicit_conversion` (on constructor)

The implicit_conversion modifier can be added to converting constructors to denote that the corresponding conversion should be registered as an implicit conversion via pybind11::implicitly_convertible<…>:

struct GENPYBIND(visible) Implicit {
  explicit Implicit(int value) GENPYBIND(implicit_conversion);
  Implicit(Example example) GENPYBIND(implicit_conversion);
};

`inline_base`

Similar to hide_base described above, inline_base has the effect that the inheritance relationship is not represented on the Python side. In addition, declarations nested in the base class are pulled in, as if they were defined in the current class. This is useful for mixins / CRTP code.

struct GENPYBIND(inline_base) InlineAll : common::Base, Base2, Base3 {};
struct GENPYBIND(inline_base("common::Base")) InlineOne : common::Base, Base2, Base3 {};
struct GENPYBIND(inline_base("Base2", "Base3")) InlineTwo : common::Base, Base2, Base3 {};

Templates

Explicit template instantiations have the same visibility as the corresponding template by default. They can be selectively exposed by adding any GENPYBIND annotation. expose_as can be used to rename individual instantiations. Else, a fallback name is generated by replacing special characters with underscores. E.g., Some<int> is exposed as Some_int_.

template <typename T> struct ExposeSome {};
extern template struct GENPYBIND(expose_as(IntSomething))
    ExposeSome<int>; // selectively exposed
extern template struct ExposeSome<double>; // not exposed

template <typename T> struct GENPYBIND(visible) ExposeAll {};
extern template struct ExposeAll<int>;
extern template struct GENPYBIND(expose_as(BoolEx)) ExposeAll<bool>;

Type aliases (`using` and `typedef`)

Type aliases are hidden (i.e., not exposed) by default and they do not inherit the default visibility. If they are marked as visible, a simple alias is created in the Python bindings by assigning a reference to the alias target to an attribute. I.e., using in the following example is equivalent to the assignment X.Alias = Y in Python.

struct GENPYBIND(visible) X {
  using Alias GENPYBIND(visible) = Y;
};

Note: [Using declarations][using-decl] are not type aliases. [using-decl]: https://en.cppreference.com/w/cpp/language/using_declaration

`expose_here`

The expose_here modifier can be used to influence where the alias target is exposed. This can be useful to, e.g., pull in / “transplant” declarations from another module or a nested scope. Or to selectively expose single-purpose template instances in a particular scope. The corresponding declarations are then no longer exposed in their original declaration context.

struct GENPYBIND(visible) Example {
  using tag_type GENPYBIND(expose_here) = common::Tag<Example>;
};

`encourage`

The encourage modifier can be used to make the target of a type alias visible in its original scope. This can be useful to selectively instantiate templates. (This implies an “assignment”-style alias on the Python side, as described above.)

struct GENPYBIND(visible) Example {
  using value_type GENPYBIND(encourage) =
      common::Ranged<int, common::Gt<0>, common::Lt<5>>;
};

Functions and member functions / methods

`keep_alive`

The keep_alive modifier corresponds to pybind11's call policy of the same name. It can be used to indicate the intended lifetime of objects passed to or returned from (member) functions: keep_alive(<bound>, <who>) means that <who> should be kept alive at least as long as <bound>. <who> and <bound> can either be the name of a function parameter, return (the function's return value), or this (the instance a member function is called on). Behind the scenes this is translated into the index-based notation used by pybind11.

struct GENPYBIND(visible) Container {
  GENPYBIND(keep_alive(this, resource))
  Container(Resource *resource);
};

`noconvert`

noconvert can be used to disable implicit conversion for arguments passed via certain function parameters (multiple parameter names can be specified):

GENPYBIND(noconvert(value))
double no_ints_please(double value);

`required`

The required modifier can be used to prohibit None arguments for certain function parameters (multiple parameter names can be specified). It is equivalent to calling .none(false) on the corresponding pybind11::arg object.

GENPYBIND(required(Example))
void required(Example *example)

`return_value_policy`

The return_value_policy modifier can be used to set any return value policy supported by pybind11:

struct GENPYBIND(visible) Example {
  GENPYBIND(return_value_policy(reference_internal))
  Thing& thing();
};

`getter_for` / `setter_for` (member functions only)

getter_for and setter_for can be used to expose member function as Python properties:

struct GENPYBIND(visible) Example {
  GENPYBIND(getter_for(value))
  int getValue() const;

  GENPYBIND(setter_for(value))
  void setValue(int value);

  GENPYBIND(getter_for(readonly))
  bool getReadonly() const;
};

Operators

Special methods like __eq__ are emitted for unary (+, -, !) and binary (+, -, *, /, %, ^, &, |, <, >, <<, >>, ==, !=, <=, >=) operators defined on classes. Operators can be either member functions or free functions in a the associated namespace of the class (found via ADL). Where necessary, operators and parameters are switched: E.g., operator<(int, T) cannot be exposed as int.__lt__ so it is exposed as T.__gt__ instead.

struct GENPYBIND(visible) Number {
  bool operator==(Number other) const { return value == other.value; }
  friend bool operator<(const Number &lhs, const Number &rhs) {
    return lhs.value < rhs.value;
  }
  friend bool operator>(int lhs, Number rhs) { return lhs > rhs.value; }
};

TODO: Support for the spaceship operator is pending.

`std::ostream` operators

std::ostream operators are only exposed when opted in via, e.g., expose_as(__repr__):

struct GENPYBIND(visible) Example {
  GENPYBIND(expose_as(__str__))
  friend std::ostream& operator<<(std::ostream& os, const Example& value);
};

Variables and member variables / fields

Variables are exposed using def_readonly and def_readwrite (and their _static variants) according to their constness.

`readonly`

The readonly modifier can be used if a non-const variable should be exposed as read-only:

struct GENPYBIND(visible) Example {
  GENPYBIND(readonly)
  int readonly_field = 0;
};

During normal compilation these macros have no effect on the generated code, as they are defined to be empty. The annotation system is implemented using the annotate attribute specifier, which is available as a GNU language extension via __attribute__((...)). As the annotation macros only have to be parsed by clang and are empty during normal compilation the annotated code can still be compiled by any C++ compiler. See genpybind.h for the definition of the macros. ↩

Name		Name	Last commit message	Last commit date
Latest commit History 220 Commits
.github/workflows		.github/workflows
LICENSES		LICENSES
example-project		example-project
include/genpybind		include/genpybind
public/genpybind		public/genpybind
src		src
tests		tests
tools		tools
.clang-format		.clang-format
.clang-tidy		.clang-tidy
.gitignore		.gitignore
.iwyu-mapping-file.yaml		.iwyu-mapping-file.yaml
.pre-commit-config.yaml		.pre-commit-config.yaml
CMakeLists.txt		CMakeLists.txt
README.md		README.md
requirements.in		requirements.in
requirements.txt		requirements.txt
ruff.toml		ruff.toml

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genpybind

Example

Implementation

Known defects and shortcomings

Changes compared to the Python prototype

Installation

Extra steps (for development)

Annotations

Where to place the GENPYBIND(…) annotation

General modifiers

visible and hidden

expose_as

GENPYBIND_MANUAL (manual bindings)

Inside structs and classes

At the top level, as a preamble or postamble to the binding code

Namespaces

module

only_expose_in

Enums

arithmetic

export_values

Structs and classes

dynamic_attr (dynamic attributes)

hide_base

holder_type

implicit_conversion (on constructor)

inline_base

Templates

Type aliases (using and typedef)

expose_here

encourage

Functions and member functions / methods

keep_alive

noconvert

required

return_value_policy

getter_for / setter_for (member functions only)