Metadata-Version: 1.1
Name: gym-tetris
Version: 1.2.9
Summary: Tetris for OpenAI Gym
Home-page: https://github.com/Kautenja/gym-tetris
Author: Christian Kauten
Author-email: kautencreations@gmail.com
License: MIT
Description-Content-Type: text/markdown
Description: # gym-![T][]etris
        
        [T]: https://user-images.githubusercontent.com/2184469/41186381-ebd61f8c-6b5a-11e8-98ce-874e29801308.png
        
        [![PackageVersion][pypi-version]][pypi-home]
        [![PythonVersion][python-version]][python-home]
        [![Stable][pypi-status]][pypi-home]
        [![Format][pypi-format]][pypi-home]
        [![License][pypi-license]](LICENSE)
        
        [pypi-version]: https://badge.fury.io/py/gym-tetris.svg
        [pypi-license]: https://img.shields.io/pypi/l/gym-tetris.svg
        [pypi-status]: https://img.shields.io/pypi/status/gym-tetris.svg
        [pypi-format]: https://img.shields.io/pypi/format/gym-tetris.svg
        [pypi-home]: https://badge.fury.io/py/gym-tetris
        [python-version]: https://img.shields.io/pypi/pyversions/gym-tetris.svg
        [python-home]: https://python.org
        
        An [OpenAI Gym](https://github.com/openai/gym) environment for Tetris. This
        environemnt derives from the [Tetromino clone][Tetromino] developed by Al
        Sweigart.
        
        ![Tetris](https://user-images.githubusercontent.com/2184469/41186404-826ebba2-6b5b-11e8-8215-eb21d765b0b9.png)
        
        [Tetromino]: http://inventwithpython.com/blog/2010/11/18/code-comments-tutorial-tetromino/
        
        
        # Installation
        
        The preferred installation of `gym-tetris` is from `pip`:
        
        ```shell
        pip install gym-tetris
        ```
        
        # Usage
        
        ## Python
        
        You must import `gym_tetris` before trying to make an environment. This is
        because gym environments are registered at runtime.
        
        ```python
        import gym_tetris
        env = gym_tetris.make('Tetris-v0')
        
        done = True
        for step in range(5000):
            if done:
                state = env.reset()
            state, reward, done, info = env.step(env.action_space.sample())
        
        env.close()
        ```
        
        **NOTE:** `gym_tetris.make` is just an alias to `gym.make` for
        convenience.
        
        ## Command Line
        
        `gym_tetris` feature a command line interface for playing environments using
        either the keyboard, or uniform random movement.
        
        ```shell
        gym_tetris -e <the environment ID to play> -m <`human` or `random`>
        ```
        
        **NOTE:** by default, `-e` is set to `Tetris-v0` and `-m` is set to
        `human`.
        
        # Citation
        
        Please cite `gym-tetris` if you use it in your research.
        
        ```tex
        @misc{gym-tetris,
          author = {Albert Sweigart and Christian Kauten},
          title = {{Tetris} for {OpenAI Gym}},
          year = {2018},
          publisher = {GitHub},
          howpublished = {\url{https://github.com/Kautenja/gym-tetris}},
        }
        ```
        
Keywords: OpenAI-Gym Tetris Reinforcement-Learning-Environment
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.5
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