# Unity ML-Agents Python Interface
The `mlagents_envs` Python package is part of the
[ML-Agents Toolkit](https://github.com/Unity-Technologies/ml-agents).
`mlagents_envs` provides three Python APIs that allows direct interaction with the
Unity game engine:
- A single agent API (Gym API)
- A gym-like multi-agent API (PettingZoo API)
- A low-level API (LLAPI)
The LLAPI is used by the trainer implementation in `mlagents`.
`mlagents_envs` can be used independently of `mlagents` for Python
communication.
## Installation
Install the `mlagents_envs` package with:
```sh
python -m pip install mlagents_envs==1.1.0
```
## Usage & More Information
See
- [Gym API Guide](../docs/Python-Gym-API.md)
- [PettingZoo API Guide](../docs/Python-PettingZoo-API.md)
- [Python API Guide](../docs/Python-LLAPI.md)
for more information on how to use the API to interact with a Unity environment.
For more information on the ML-Agents Toolkit and how to instrument a Unity
scene with the ML-Agents SDK, check out the main
[ML-Agents Toolkit documentation](../docs/Readme.md).
## Limitations
- `mlagents_envs` uses localhost ports to exchange data between Unity and
Python. As such, multiple instances can have their ports collide, leading to
errors. Make sure to use a different port if you are using multiple instances
of `UnityEnvironment`.
- Communication between Unity and the Python `UnityEnvironment` is not secure.
- On Linux, ports are not released immediately after the communication closes.
As such, you cannot reuse ports right after closing a `UnityEnvironment`.
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