semvec/pypi-packages huggingface dataset:
hypermemory 0.2.2
Meta-data core functionalities for Hyperactive
License: MIT
Keywords: visualization,data-science

<h1> Hypermemory </h1>

<h2 align="center">Meta-data core functionalities for Hyperactive.</h2>

<br>

This package is a collection of core functionalities for the memory module in Hyperactive. It enables Hyperactive to "remember" previous evaluations, which can save significant computation time. The effect is, that every position in the search-space that has been evaluated once never needs to be evaluated again. The previous calculated score has been stored and can just be looked up instead of recalculating it.
Hypermemory also enables persistent storage of python-objects in the meta-data. This means, that information about the objective-function and python-objects in the search-space can be saved and read via the dill-package.

<br>

<table>
  <tbody>
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      <td>
        <strong>Master status:</strong>
      </td>
      <td>
        <a href="https://travis-ci.com/SimonBlanke/Hypermemory">
          <img src="https://img.shields.io/travis/com/SimonBlanke/Hypermemory/master?style=flat-square&logo=travis" alt="img not loaded: try F5 :)">
        </a>
        <a href="https://coveralls.io/github/SimonBlanke/Hypermemory">
          <img src="https://img.shields.io/coveralls/github/SimonBlanke/Hypermemory?style=flat-square&logo=codecov" alt="img not loaded: try F5 :)">
        </a>
      </td>
    </tr>
    <tr/>
    <tr align="left" valign="center">
      <td>
         <strong>Code quality:</strong>
      </td>
      <td>
        <a href="https://codeclimate.com/github/SimonBlanke/Hypermemory">
        <img src="https://img.shields.io/codeclimate/maintainability/SimonBlanke/Hypermemory?style=flat-square&logo=code-climate" alt="img not loaded: try F5 :)">
        </a>
        <a href="https://scrutinizer-ci.com/g/SimonBlanke/Hypermemory/">
        <img src="https://img.shields.io/scrutinizer/quality/g/SimonBlanke/Hypermemory?style=flat-square&logo=scrutinizer-ci" alt="img not loaded: try F5 :)">
        </a>
      </td>
    </tr>
    <tr/>    <tr align="left" valign="center">
      <td>
        <strong>Latest versions:</strong>
      </td>
      <td>
        <a href="https://pypi.org/project/hypermemory/">
          <img src="https://img.shields.io/pypi/v/Hypermemory?style=flat-square&logo=PyPi&logoColor=white" alt="img not loaded: try F5 :)">
        </a>
      </td>
    </tr>
  </tbody>
</table>
chess-cheat 1.0.3
Chess-Cheat is a tool to cheat at online chess
License: MIT
Requires Python: >=3.8

# Chess-Cheat
##### A tool to cheat at online chess

Launch Chess-Cheat, open your favourite chess website and the tool will dinamically overlay the best move for you.

![Example](https://raw.githubusercontent.com/GabrieleMaurina/chess-cheat/master/images/example.png)

### Install

Prerequisites to install:
* [Python 3](https://www.python.org/ "Python website")
* [Stockfish](https://stockfishchess.org/ "Stockfish website")

Then simply run:

`python -m pip install chess-cheat`

### Usage

Launch it as follow:

`python -m chess-cheat`

How the UI works:
* The switch "White/Black" allows you to tell Chess-Cheat if you are playing white or black.
* The "Board" button allows you to tell Chess-Cheat where the board is on the screen to facilitate recognition.
* The best move foy you is displayed both as an arrow and as a string.
* A green background indicates that it is working correctly.
* A red background indicates that it is not finding the board on the screen.

### Cloning this repo

To successfully clone Chess-Cheat from this repo and execute it you need to run:

`git clone https://github.com/GabrieleMaurina/chess-cheat.git`

Then install the following dependencies:
* [Python 3](https://www.python.org/ "Python website")
* [Tensorflow](https://pypi.org/project/tensorflow/ "Tensorflow for python")
* [Numpy](https://pypi.org/project/numpy/ "Numpy for python")
* [Stockfish](https://stockfishchess.org/ "Stockfish website") installed in your system
* [Stockfish](https://pypi.org/project/stockfish/ "Stockfish for python") for python
* [Pillow](https://pypi.org/project/Pillow/ "Pillow for python")
* [Pyscreenshot](https://pypi.org/project/pyscreenshot/ "Pyscreenshot for python")
* [Timeout decorator](https://pypi.org/project/timeout-decorator/ "Timeout decorator for python")

### How it works

Chess-Cheat is based on [Tensorflow_Chessbot](https://github.com/Elucidation/tensorflow_chessbot "Tensorflow_Chessbot github") for recognizing the chessboard on your screen.

It uses [Stockfish](https://stockfishchess.org/ "Stockfish website") to compute the best move.

It displays the arrows and the buttons on the screen with [Tkinter](https://docs.python.org/3/library/tkinter.html "Tkinter documentation").

### Why is the arrow blinking?

Because the image recognition model needs to see the board unobstructed. By making the arrow blink, it has a chance to capture the screen.