semvec/pypi-packages huggingface dataset:
gogame 1.0.0
An easy way to simulate and automize go-like programs.
License: MIT
Requires Python: >=3.8
Keywords: go gogame

gogame
======

An easy way to simulate and automize go-like programs.

Installing
----------

To install the library from PyPi, you can just run the following command:

.. code:: sh

    # Linux/macOS
    python3 -m pip install -U gogame

    # Windows
    py -3 -m pip install -U gogame

To install from the development sources, do the following:

.. code:: sh

    $ git clone https://github.com/BlackRaven0405/gogame
    $ cd gogame
    $ python3 -m pip install -U .

Quick Example
-------------

.. code:: py

    import gogame


    class RandomPlayer(gogame.Player):
        def play(self):
            return self.playable_moves()[0]


    b = gogame.Board()
    p1 = RandomPlayer(name="John")
    p2 = RandomPlayer(name="Smith")
    b.join(p1)
    b.join(p2)
    winner = b.run_game()
    print(winner)

You can find more examples in the example directory.

Links
-----

- `Documentation <https://gogame.readthedocs.io/en/latest/>`_
- `Rules of go <https://en.wikipedia.org/wiki/Rules_of_Go>`_
neurogenome 0.1.4
A universal API for create artificial neural networks with a genetic code.
License: MIT
Requires Python: >=3.7,<4.0

<img src="https://raw.githubusercontent.com/Aiyyskhan/NeuroGenome/main/docs/NeuroGenome_1_1_white.jpeg" align="middle" width="1000"/>

<p align="center">
<img src="https://img.shields.io/badge/version-v0.1.4-blue.svg?style=flat&colorA=007D8A&colorB=E1523D">
<img src="https://img.shields.io/badge/license-MIT-brightgreen">
</p>

**NeuroGenome** is a bioinspired open-source project that allows you to create artificial neural networks with a genetic code.

- [Installation](#installation)
- [Settings example](#settings-example)
- [Examples](#examples)
- [License](#license)

## Installation
```python
pip install neurogenome
```
## Settings example

```python
# gene localization scheme
schema_0 = [
	[
		["i0","i1","i0","i1"],
		["h1","h0","h1","h0"]
	],
	[
		["i2","i3","i2","i3"],
		["h3","h2","h3","h2"]
	],
	[
		["o0","o1"],
		["o1","o0"]
	]
]

# hyperparameters
SETTINGS = {
	"population size": 50,
	"number of leaders": 5,
	"select by": "max",
	"number of input nodes per gene": 5,
	"number of hidden nodes per gene": 4,
	"number of output nodes per gene": 3,
	"schema": schema_0,
}
```

## Examples

_in the pipeline_

## License

[MIT](https://opensource.org/licenses/MIT)