<!-- PyPI long description lives here. Keep links absolute. -->
# Rusty Runways — Python Bindings
[](https://dennislent.github.io/RustyRunways)
[](https://pypi.org/project/rusty-runways/)
<p align="center">
<img src="https://github.com/DennisLent/RustyRunways/raw/main/docs/assets/rusty_runways.png" alt="Rusty Runways" width="640" />
</p>
Deterministic airline logistics simulation written in Rust with a rich Python API for scripting, analysis, and RL/ML. Includes fast vectorized environments and optional Gymnasium wrappers.
— Full docs: https://dennislent.github.io/RustyRunways
## Install
Python (PyPI):
```bash
pip install rusty-runways
# Optional Gym wrappers
pip install 'rusty-runways[gym]'
```
Local dev (build from source):
```bash
cd crates/py
maturin develop --release
```
## Quick Start (Python)
Engine bindings (single and vector):
```python
from rusty_runways_py import GameEnv, VectorGameEnv
g = GameEnv(seed=1, num_airports=5, cash=1_000_000)
g.step(1)
print(g.time(), g.cash())
venv = VectorGameEnv(4, seed=1)
venv.step_all(1, parallel=True)
print(venv.times())
```
Notes:
- Seeds control determinism.
- `VectorGameEnv.step_all(..., parallel=True)` releases the GIL and uses Rayon under the hood.
## Gymnasium Wrappers (optional)
Wrappers live in the pure‑Python package `rusty_runways` and require `gymnasium`:
```python
from stable_baselines3 import PPO
from stable_baselines3.common.vec_env import DummyVecEnv
from rusty_runways import RustyRunwaysGymEnv, make_sb3_envs
# Single‑env Gym
env = RustyRunwaysGymEnv(seed=1, num_airports=5)
# SB3 convenience (DummyVecEnv)
vec_env = DummyVecEnv(make_sb3_envs(4, seed=1, num_airports=5))
model = PPO("MlpPolicy", vec_env, verbose=1)
model.learn(total_timesteps=10_000)
```
## Links
- Documentation: https://dennislent.github.io/RustyRunways
- Source: https://github.com/DennisLent/RustyRunways
- Issues: https://github.com/DennisLent/RustyRunways/issues
License: MIT
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"description": "<!-- PyPI long description lives here. Keep links absolute. -->\n\n# Rusty Runways \u2014 Python Bindings\n\n[](https://dennislent.github.io/RustyRunways)\n[](https://pypi.org/project/rusty-runways/)\n\n<p align=\"center\">\n <img src=\"https://github.com/DennisLent/RustyRunways/raw/main/docs/assets/rusty_runways.png\" alt=\"Rusty Runways\" width=\"640\" />\n</p>\n\nDeterministic airline logistics simulation written in Rust with a rich Python API for scripting, analysis, and RL/ML. Includes fast vectorized environments and optional Gymnasium wrappers.\n\n\u2014 Full docs: https://dennislent.github.io/RustyRunways\n\n## Install\n\nPython (PyPI):\n\n```bash\npip install rusty-runways\n\n# Optional Gym wrappers\npip install 'rusty-runways[gym]'\n```\n\nLocal dev (build from source):\n\n```bash\ncd crates/py\nmaturin develop --release\n```\n\n## Quick Start (Python)\n\nEngine bindings (single and vector):\n\n```python\nfrom rusty_runways_py import GameEnv, VectorGameEnv\n\ng = GameEnv(seed=1, num_airports=5, cash=1_000_000)\ng.step(1)\nprint(g.time(), g.cash())\n\nvenv = VectorGameEnv(4, seed=1)\nvenv.step_all(1, parallel=True)\nprint(venv.times())\n```\n\nNotes:\n- Seeds control determinism.\n- `VectorGameEnv.step_all(..., parallel=True)` releases the GIL and uses Rayon under the hood.\n\n## Gymnasium Wrappers (optional)\n\nWrappers live in the pure\u2011Python package `rusty_runways` and require `gymnasium`:\n\n```python\nfrom stable_baselines3 import PPO\nfrom stable_baselines3.common.vec_env import DummyVecEnv\nfrom rusty_runways import RustyRunwaysGymEnv, make_sb3_envs\n\n# Single\u2011env Gym\nenv = RustyRunwaysGymEnv(seed=1, num_airports=5)\n\n# SB3 convenience (DummyVecEnv)\nvec_env = DummyVecEnv(make_sb3_envs(4, seed=1, num_airports=5))\nmodel = PPO(\"MlpPolicy\", vec_env, verbose=1)\nmodel.learn(total_timesteps=10_000)\n```\n\n## Links\n\n- Documentation: https://dennislent.github.io/RustyRunways\n- Source: https://github.com/DennisLent/RustyRunways\n- Issues: https://github.com/DennisLent/RustyRunways/issues\n\nLicense: MIT\n\n",
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