Metadata-Version: 2.5
Name: bluebird-gymnasium
Version: 0.3.0
Summary: An gymnasium environment for air traffic control.
Project-URL: Documentation, http://docs.projectbluebird.ai
Project-URL: Repository, https://github.com/project-bluebird/BluebirdATC
Author: Project Bluebird
License-Expression: AGPL-3.0-or-later
Requires-Python: <3.15,>=3.10
Requires-Dist: bluebird-dt==0.2.0
Requires-Dist: gymnasium>=0.29.1
Requires-Dist: imageio<3,>=2.37.4
Requires-Dist: jupyter<2,>=1.1.1
Description-Content-Type: text/markdown

# Bluebird Gymnasium [![PyPI version](https://img.shields.io/pypi/v/bluebird-gymnasium?logo=pypi&logoColor=white)](https://pypi.org/project/bluebird-gymnasium/) <img src="../images/BBATC_logo.png" alt="BluebirdATC logo" align="right" height="160" />

`bluebird-gymnasium` is suite of gymnasium environments for air traffic control (ATC).
The environments are based on [bluebird-dt](https://github.com/project-bluebird/BluebirdATC/tree/main/bluebird-dt) (an ATC simulator).
The environments support research in agent-based learning (e.g. reinforcement learning) for ATC.
It supports either single agent or multi-agents scenarios.
## Installation

Install from PyPI:

```bash
pip install bluebird-gymnasium
```

Or, if you're using [uv](https://docs.astral.sh/uv/), you can add it to your environment:

```bash
uv add bluebird-gymnasium
```

## Getting started

### Basic usage

`bluebird-gymnasium` currently supports the following environments/airspace:
X sector, Y sector, I sector, Xplus sector and Springfield sector.

To instantiate a X sector environment with the default config, run:

```python
import gymnasium as gym
import bluebird_gymnasium

env = gym.make("SectorXEnv-v0")
```

### Sample agents

Below, an example agent that takes random actions.

```python
import gymnasium as gym
import bluebird_gymnasium

env = gym.make("SectorXEnv-v0")
obs, info = env.reset()
done = False

while not done:
    action = env.action_space.sample()
    obs, reward, done, truncated, info = env.step(action)
```

Various examples of using the `bluebird-gymnasium` package can be found in the form of Jupyter notebooks in the [examples](https://github.com/project-bluebird/BluebirdATC/tree/main/bluebird-gymnasium/examples) directory or in the [documentation](https://docs.projectbluebird.ai/examples/competition/Competition-Intro/) for the AI(r) Traffic Controller Challenge.

## Documentation

The documentation of the latest release is available at [https://docs.projectbluebird.ai](https://docs.projectbluebird.ai).

<div align="center"><img src="../images/BB_logo.png" alt="ProjectBluebird"></div>