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environment-framework-0.3.0a1
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مشاهده بیشترتوضیحات
Loose building blocks to create agent-environment loops.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | environment-framework-0.3.0a1 |
| نام | environment-framework |
| نسخه کتابخانه | 0.3.0a1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Reto Barmettler |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/environment-framework/ |
| مجوز | - |
# 🌐 Environment Framework
This repository contains the Python package `environment-framework`. The project aims to provide loose building blocks to manage the logic, observation, estimation and visualization of an agent-environment loop. It can be used to implement problems which might be solved with reinforcement learning or dynamic programming algorithms.
A wrapper around [`gymnasium`](https://github.com/Farama-Foundation/Gymnasium) is provided to connect to well-known frameworks in the field.
> The wrapper for gymnasium uses the gymnasium>=0.26 API structure!
### 🤔 Why create this project?
The project emerges from a previous project of mine. It was used to separate the different elements of the projects agent-environment-loop.
## 🚀 Get Started
#### Installation
```bash
pip3 install environment-framework
```
### 👩🏫 GridWorld Example
The implemented example of `GridWorld` can also be found in a Jupyter notebook [grid_world.ipynb](example/grid_world.ipynb).
```bash
pip3 install "environment-framework[extra]"
jupyter lab
```
```python
class Action(Enum):
UP = 0
DOWN = 1
RIGHT = 2
LEFT = 3
class GridWorldGame:
def __init__(self, size: int) -> None:
self.size = size
self.player_position = (0, 0)
self.target_position = (0, 0)
self.reset()
@property
def done(self) -> bool:
return self.player_position == self.target_position
@property
def space(self) -> Space:
return Discrete(4)
def act(self, action: Action, **_: Any) -> None:
if action == Action.UP:
self.player_position = (self.player_position[0], self.player_position[1] - 1)
if action == Action.DOWN:
self.player_position = (self.player_position[0], self.player_position[1] + 1)
if action == Action.RIGHT:
self.player_position = (self.player_position[0] + 1, self.player_position[1])
if action == Action.LEFT:
self.player_position = (self.player_position[0] - 1, self.player_position[1])
corrected_x = max(0, min(self.size - 1, self.player_position[0]))
corrected_y = max(0, min(self.size - 1, self.player_position[1]))
self.player_position = (corrected_x, corrected_y)
def reset(self) -> None:
def get_random_position() -> int:
return randint(0, self.size - 1)
self.player_position = (get_random_position(), get_random_position())
self.target_position = (get_random_position(), get_random_position())
if self.done:
self.reset()
class GridWorldObserver:
def __init__(self, game: GridWorldGame) -> None:
self.game = game
@property
def space(self) -> Space:
return Box(shape=(4,), low=-math.inf, high=math.inf)
def observe(self, _: Any) -> NDArray:
return np.array([*self.game.player_position, *self.game.target_position])
class GridWorldEstimator:
def __init__(self, game: GridWorldGame) -> None:
self.game = game
def estimate(self, _: Any) -> float:
return -1 + float(self.game.done)
class GridWorldVisualizer:
# We use BGR
BLUE = [255, 0, 0]
GREEN = [0, 255, 0]
def __init__(self, game: GridWorldGame) -> None:
self.game = game
def render(self, _: Any) -> Any:
frame = [[[0 for k in range(3)] for j in range(self.game.size)] for i in range(self.game.size)]
frame[self.game.player_position[1]][self.game.player_position[0]] = self.BLUE
frame[self.game.target_position[1]][self.game.target_position[0]] = self.GREEN
return frame
class GridWorldLevel(Level):
_game: GridWorldGame
_observer: GridWorldObserver
_estimator: GridWorldEstimator
_visualizer: GridWorldVisualizer
def __init__(
self,
game: GridWorldGame,
observer: GridWorldObserver,
estimator: GridWorldEstimator,
visualizer: GridWorldVisualizer,
) -> None:
super().__init__(game, observer, estimator, visualizer)
def reset(self) -> None:
self._game.reset()
def step(self, action: Action) -> Any:
if isinstance(action, np.int64): # handle integer inputs
action = Action(action)
self._game.act(action)
game = GridWorldGame(7)
level = GridWorldLevel(game, GridWorldObserver(game), GridWorldEstimator(game), GridWorldVisualizer(game))
simulator = Simulator(level)
while not simulator.done:
action = Action(randint(0, 3))
simulator.step(action)
```
### 📃 Documentation
Some doc-strings are already added. Documentation is a work-in-progress and will be updated on a time by time basis.
### 💃🕺 Contribution
I welcome everybody contributing to this project. Please read the [CONTRIBUTING.md](./CONTRIBUTING.md) for more information.
Feel free to open an issue on the project if you have any further questions.
## 💻 Development
The repository provides tools for development using [hatch](https://hatch.pypa.io/latest/).
All dependencies for the project also can be found in a `requirements`-file.
Install the development dependencies.
```bash
pip3 install -r requirements/dev.txt
```
or
```bash
pip3 install "environment-framework[dev]"
```
#### Tools
To run all development tools, type checking, linting and tests `hatch` is required.
```bash
make all
```
#### Type checking
Type checking with `mypy`.
```bash
make mypy
```
#### Linting
Linting with `pylint`.
```bash
make lint
```
#### Tests
Run tests with `pytest`.
```bash
make test
```
#### Update dependencies
Update python requirements with `pip-compile`.
```bash
make update
```
## 🧾 License
This repository is licensed under the MIT License.
نیازمندی
| مقدار | نام |
|---|---|
| - | gymnasium>=0.26 |
| - | numpy |
| xtr | genbadge[all]; |
| xtr | hatch; |
| xtr | hatch-regex-commit; |
| xtr | hatch; |
| xtr | ipywidgets; |
| xtr | jupyterlab; |
| xtr | jupytext; |
| xtr | opencv-python; |
| xtr | sb3-contrib>=2.0.0a1; |
| xtr | tqdm; |
| xtr | pylint; |
| xtr | black; |
| xtr | isort; |
| xtr | pytest; |
| xtr | pytest-cov; |
| xtr | pytest-mock; |
| xtr | mypy; |
| xtr | types-pyyaml; |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl environment-framework-0.3.0a1:
pip install environment-framework-0.3.0a1.whl
نصب پکیج tar.gz environment-framework-0.3.0a1:
pip install environment-framework-0.3.0a1.tar.gz