Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/openai/mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
https://github.com/openai/mujoco-py
Last synced: 5 days ago
JSON representation
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
- Host: GitHub
- URL: https://github.com/openai/mujoco-py
- Owner: openai
- License: other
- Created: 2016-04-24T17:55:58.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-12-10T12:47:21.000Z (about 1 year ago)
- Last Synced: 2025-01-07T11:06:35.070Z (12 days ago)
- Language: Cython
- Homepage:
- Size: 5.55 MB
- Stars: 2,900
- Watchers: 195
- Forks: 811
- Open Issues: 426
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
- awesome-physics - mujoco-py - A physics engine for detailed, efficient rigid body simulations with contacts (Mechanics / Rigid Bodies and Physics Engines)
- awesome-simulation - mujoco-py - mujoco-py allows using MuJoCo from Python 3 ([MuJoCo](https://mujoco.org))
- awesome-decision-transformer - MuJoco - berkeley/d4rl) (Papers / ICML 2021)
- awesome-model-based-RL - mujoco
- awesome-exploration-rl - MuJoCo
README
**Status**: Deprecated
### `mujoco-py` does not support versions of MuJoCo after 2.1.0.
### New users should depend on the [official MuJoCo Python bindings](https://github.com/deepmind/mujoco/blob/main/python/README.md).
# mujoco-py [](https://openai.github.io/mujoco-py/build/html/index.html) [](https://travis-ci.org/openai/mujoco-py)
[MuJoCo](http://mujoco.org/) is a physics engine for detailed, efficient rigid body simulations with contacts.
`mujoco-py` allows using MuJoCo from Python 3.
This library has been updated to be compatible with MuJoCo version 2.1 released on 2021-10-18.
## Synopsis
### Requirements
The following platforms are currently supported:
- Linux with Python 3.6+. See [the `Dockerfile`](Dockerfile) for the canonical list of system dependencies.
- OS X with Python 3.6+.
The following platforms are DEPRECATED and unsupported:
- Windows support has been DEPRECATED and removed in [2.0.2.0](https://github.com/openai/mujoco-py/releases/tag/v2.0.2.0a1). One known good past version is [1.50.1.68](https://github.com/openai/mujoco-py/blob/9ea9bb000d6b8551b99f9aa440862e0c7f7b4191/README.md#requirements).
- Python 2 has been DEPRECATED and removed in [1.50.1.0](https://github.com/openai/mujoco-py/releases/tag/1.50.1.0). Python 2 users can stay on the [`0.5` branch](https://github.com/openai/mujoco-py/tree/0.5). The latest release there is [`0.5.7`](https://github.com/openai/mujoco-py/releases/tag/0.5.7) which can be installed with `pip install mujoco-py==0.5.7`.
### Install MuJoCo
1. Download the MuJoCo version 2.1 binaries for
[Linux](https://mujoco.org/download/mujoco210-linux-x86_64.tar.gz) or
[OSX](https://mujoco.org/download/mujoco210-macos-x86_64.tar.gz).
1. Extract the downloaded `mujoco210` directory into `~/.mujoco/mujoco210`.
If you want to specify a nonstandard location for the package,
use the env variable `MUJOCO_PY_MUJOCO_PATH`.
### Install and use `mujoco-py`
To include `mujoco-py` in your own package, add it to your requirements like so:
```
mujoco-py<2.2,>=2.1
```
To play with `mujoco-py` interactively, follow these steps:
```
$ pip3 install -U 'mujoco-py<2.2,>=2.1'
$ python3
import mujoco_py
import os
mj_path = mujoco_py.utils.discover_mujoco()
xml_path = os.path.join(mj_path, 'model', 'humanoid.xml')
model = mujoco_py.load_model_from_path(xml_path)
sim = mujoco_py.MjSim(model)
print(sim.data.qpos)
# [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
sim.step()
print(sim.data.qpos)
# [-2.09531783e-19 2.72130735e-05 6.14480786e-22 -3.45474715e-06
# 7.42993721e-06 -1.40711141e-04 -3.04253586e-04 -2.07559344e-04
# 8.50646247e-05 -3.45474715e-06 7.42993721e-06 -1.40711141e-04
# -3.04253586e-04 -2.07559344e-04 -8.50646247e-05 1.11317030e-04
# -7.03465386e-05 -2.22862221e-05 -1.11317030e-04 7.03465386e-05
# -2.22862221e-05]
```
See the [full documentation](https://openai.github.io/mujoco-py/build/html/index.html) for advanced usage.
## Troubleshooting
### You're on MacOS and you see `clang: error: unsupported option '-fopenmp'`
If this happend during installation or just running `python -c "import mujoco_py"` then the issue seems to be related to [this](https://github.com/velocyto-team/velocyto.R/issues/2#issuecomment-341165967) and the TL;DR is that for macOS the default compiler Apple clang LLVM does not support openmp. So you can try to install another clang/llvm installation. For example (requires [brew](https://brew.sh/)):
```bash
brew install llvm
brew install boost
brew install hdf5
# Add this to your .bashrc/.zshrc:
export PATH="/usr/local/opt/llvm/bin:$PATH"
export CC="/usr/local/opt/llvm/bin/clang"
export CXX="/usr/local/opt/llvm/bin/clang++"
export CXX11="/usr/local/opt/llvm/bin/clang++"
export CXX14="/usr/local/opt/llvm/bin/clang++"
export CXX17="/usr/local/opt/llvm/bin/clang++"
export CXX1X="/usr/local/opt/llvm/bin/clang++"
export LDFLAGS="-L/usr/local/opt/llvm/lib"
export CPPFLAGS="-I/usr/local/opt/llvm/include"
```
**Note:** Don't forget to source your `.bashrc/.zshrc` after editing it and try to install `mujoco-py` again:
```bash
# Make sure your python environment is activated
pip install -U 'mujoco-py<2.2,>=2.1'
```
### Missing GLFW
A common error when installing is:
raise ImportError("Failed to load GLFW3 shared library.")
Which happens when the `glfw` python package fails to find a GLFW dynamic library.
MuJoCo ships with its own copy of this library, which can be used during installation.
Add the path to the mujoco bin directory to your dynamic loader:
LD_LIBRARY_PATH=$HOME/.mujoco/mujoco210/bin pip install mujoco-py
This is particularly useful on Ubuntu 14.04, which does not have a GLFW package.
### Ubuntu installtion troubleshooting
Because `mujoco_py` has compiled native code that needs to be linked to a supplied MuJoCo binary, it's installation
on linux can be more challenging than pure Python source packages.
To install mujoco-py on Ubuntu, make sure you have the following libraries installed:
sudo apt install libosmesa6-dev libgl1-mesa-glx libglfw3
If you installed above libraries and you still see an error that `-lGL` cannot be found, most likely you need
to create the symbolic link directly:
sudo ln -s /usr/lib/x86_64-linux-gnu/libGL.so.1 /usr/lib/x86_64-linux-gnu/libGL.so
## Usage Examples
A number of examples demonstrating some advanced features of `mujoco-py` can be found in [`examples/`](/./examples/). These include:
- [`body_interaction.py`](./examples/body_interaction.py): shows interactions between colliding bodies
- [`disco_fetch.py`](./examples/disco_fetch.py): shows how `TextureModder` can be used to randomize object textures
- [`internal_functions.py`](./examples/internal_functions.py): shows how to call raw mujoco functions like `mjv_room2model`
- [`markers_demo.py`](./examples/markers_demo.py): shows how to add visualization-only geoms to the viewer
- [`serialize_model.py`](./examples/serialize_model.py): shows how to save and restore a model
- [`setting_state.py`](./examples/setting_state.py): shows how to reset the simulation to a given state
- [`tosser.py`](./examples/tosser.py): shows a simple actuated object sorting robot application
See the [full documentation](https://openai.github.io/mujoco-py/build/html/index.html) for advanced usage.
## Development
To run the provided unit and integrations tests:
```
make test
```
To test GPU-backed rendering, run:
```
make test_gpu
```
This is somewhat dependent on internal OpenAI infrastructure at the moment, but it should run if you change the `Makefile` parameters for your own setup.
## Changelog
- 03/08/2018: We removed MjSimPool, because most of benefit one can get with multiple processes having single simulation.
## Credits
`mujoco-py` is maintained by the OpenAI Robotics team. Contributors include:
- Alex Ray
- Bob McGrew
- Jonas Schneider
- Jonathan Ho
- Peter Welinder
- Wojciech Zaremba
- Jerry Tworek