hpp-python

hpp-python provides native Python bindings for the HPP (Humanoid Path Planner) C++ libraries (hpp-core, hpp-constraints, hpp-pinocchio, hpp-manipulation, ...), generated with boost::python. These bindings differ from the ones provided by hpp-corbaserver: they are native, in-process bindings that do not use a CORBA middleware, so there is no client/server split and no serialization overhead.

The resulting pyhpp package mirrors the C++ namespace layout:

• pyhpp.pinocchio — robot model (Device), grippers, Lie-group utilities. Wraps hpp-pinocchio.
• pyhpp.constraints — differentiable functions, transformations, implicit/explicit constraints, the hierarchical iterative solver. Wraps hpp-constraints.
• pyhpp.core — planning problem, path planners, path optimizers, path validation, roadmap, steering methods. Wraps hpp-core.
• pyhpp.manipulation — manipulation-specific Device, constraint graph, path planners/optimizers for manipulation problems, URDF/SRDF loading. Wraps hpp-manipulation and hpp-manipulation-urdf.
• pyhpp.tools — pure-Python helpers (xacro processing, constraint-error reporting) that are not generated bindings.

Table of contents

• Module dependency graph
• Dependencies
• Installation
  • From source with CMake
  • With Nix
• Documentation generation
  • Injecting Doxygen docstrings into bindings
  • API reference from stubs
• License

Module dependency graph

The BOOST_PYTHON_MODULE initializers import each other in a fixed order, which also reflects the underlying C++ library dependencies:

flowchart LR
    pin["pyhpp.pinocchio\n(hpp-pinocchio)"]
    cons["pyhpp.constraints\n(hpp-constraints)"]
    core["pyhpp.core\n(hpp-core)"]
    manip["pyhpp.manipulation\n(hpp-manipulation)"]
    ext["pinocchio\n(external package)"]

    ext --> pin
    pin --> cons
    cons --> core
    core --> manip

    style pin fill:#dbe9f4,stroke:#4a90d9
    style cons fill:#dbe9f4,stroke:#4a90d9
    style core fill:#dbe9f4,stroke:#4a90d9
    style manip fill:#dbe9f4,stroke:#4a90d9
    style ext fill:#e8f4e8,stroke:#4a9d4a

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Dependencies

• Python ≥ 3.10, with numpy
• Boost.Python (found via search_for_boost_python())
• eigenpy
• Pinocchio (C++ and Python)
• HPP C++ libraries: hpp-util, hpp-pinocchio, hpp-constraints, hpp-core, hpp-manipulation, hpp-manipulation-urdf
• Optional: pybind11-stubgen to generate .pyi type stubs (GENERATE_PYTHON_STUBS, default ON)
• For running the test suite (BUILD_TESTING): example-robot-data, hpp-environments

Installation

From source with CMake

git clone https://github.com/humanoid-path-planner/hpp-python.git
mkdir hpp-python/build
cd hpp-python/build
cmake -DCMAKE_INSTALL_PREFIX=<your_install_prefix> -DCMAKE_BUILD_TYPE=Release ..
make
make test
make install

Relevant CMake options:

• GENERATE_PYTHON_STUBS (default ON): generate .pyi stub files with pybind11-stubgen for IDE autocompletion; automatically disabled if the tool is not found.
• HPP_DEBUG (default OFF): enable hpp-util debug logging (-DHPP_DEBUG).
• HPP_BENCHMARK (default OFF): enable hpp-util benchmark output (-DHPP_ENABLE_BENCHMARK).
• BUILD_TESTING: build and run the unit/integration test suite (requires example-robot-data and hpp-environments).

With Nix

A flake is provided, pulling hpp-constraints, hpp-core and hpp-manipulation from their own flakes and building against github:gepetto/nix:

nix build github:humanoid-path-planner/hpp-python

Documentation generation

Injecting Doxygen docstrings into bindings

Script doc/configure.py is used to generate documentation of Python objects from C++ objects. It reads the XML documentation generated by doxygen so the dependencies must provide such files. To make it work, do:

• Add GENERATE_XML=YES into doc/Doxyfile.extra.in of all the dependency of this project.
• Install the generated documentation by adding the following lines to CMakeLists.txt:

IF(_INSTALL_DOC)
  INSTALL(DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/doc/doxygen-xml
    DESTINATION ${CMAKE_INSTALL_DOCDIR})
ENDIF()

File doc/configure.py contains a short documentation of how to document the bindings.

API reference from stubs

After building and installing pyhpp, pybind11-stubgen produces .pyi stub files under the Python site-packages directory.

doc/fix_stubs.py improves those raw Boost.Python stubs in-place by recovering proper parameter names, types, and return-type annotations from the embedded docstrings. The fixed stubs are useful on their own — IDEs (autocompletion, type checking) and static analysis tools consume them directly, independently of any documentation generation step:

python doc/fix_stubs.py path/to/site-packages/pyhpp/
# or individual files:
python doc/fix_stubs.py path/to/site-packages/pyhpp/core/bindings.pyi

Optional JSON override files can supply or correct signatures that cannot be inferred from docstrings alone (--setter-overrides, --method-overrides).

doc/gen_api_md.py reads the (optionally fixed) stubs and generates one Markdown file per module — suitable for mdbook — plus an index.md, with syntax-coloured signatures and clickable cross-module type links:

python doc/gen_api_md.py \
    --stubs path/to/site-packages \
    --output path/to/docs/api/

Modules covered: pyhpp.core, pyhpp.core.path, pyhpp.core.path_optimization, pyhpp.core.problem_target, pyhpp.constraints, pyhpp.manipulation, pyhpp.manipulation.urdf, pyhpp.manipulation.steering_method, pyhpp.pinocchio, pyhpp.pinocchio.urdf.

License

hpp-python is released under the BSD 2-Clause License, Copyright (c) 2018-2025, CNRS.