PyPi Release Docker CI

ChessLib Python Extension

About

This project provides an efficient chess draw generation extension for Python3. The main purpose of this project is enabling further TensorFlow AI projects and learning how to write an efficient Python3 extension (using good old C).

Usage

Install the official Python package using pip:

pip install chesslib

Use the chesslib package like in the following example:

import chesslib
import numpy as np
import random


def test():

    # create a new chess board in start formation
    board = chesslib.ChessBoard_StartFormation()

    # generate all possible draws
    draws = chesslib.GenerateDraws(board, chesslib.ChessColor_White, chesslib.ChessDraw_Null, True)

    # apply one of the possible draws
    draw_to_apply = draws[random.randint(0, len(draws) - 1)]
    new_board = chesslib.ApplyDraw(board, draw_to_apply)

    # write the draw's name
    print(chesslib.VisualizeDraw(draw_to_apply))

    # visualize the board before / after applying the draw
    print(chesslib.VisualizeBoard(board))
    print(chesslib.VisualizeBoard(new_board))

    # revert the draw (just call ApplyDraw again with the new board)
    rev_board = chesslib.ApplyDraw(new_board, draw_to_apply)

    # get the board's 40-byte-hash and create a new board instance from the hash
    board_hash = chesslib.Board_ToHash(board)
    board_reloaded = chesslib.Board_FromHash(board_hash)

    # see tests/ folder for more examples

How to Develop

The commands for dev-testing the chesslib are wrapped within a Docker environment. Therefore build the 'Dockerfile-dev' file which takes your source code and performs all required CI steps (build + install + unit tests). Afterwards you may attach to the Docker image with the bash console interactively and run commands, etc.

# make a dev build using the 'Dockerfile-dev' build environment
# this runs all CI steps (build + install + unit tests)
docker build . --file Dockerfile-dev -t "chesslib-dev"

# attach to the build environment's interactive bash console (leave the session with 'exit')
docker run "chesslib-dev" -it bash

# mount a Python test script into the build environment and run it
docker run -v $PWD:/scripts "chesslib-dev" python3 /scripts/test.py

Advantages of this approach are that it simplifies the dev machine setup a lot as you only need Docker, git and a good text editor on your local machine. Moreover you don't mess up your dev machine when trying to build and install the chesslib package for debugging again and again. And most importantly you keep your local copy of the git repo clean as all temporary files are created within the Docker container, so you basically don't need to worry about accidentially including build files into git commits, etc.

For a quickstart, set up your dev machine as a VM (e.g. Ubuntu 20.04 hosted by VirtualBox). After successfully creating the VM, use following commands to install all essential dev tools (git, docker, good text editor).

# install docker (e.g. Ubuntu 20.04)
sudo apt-get update && sudo apt-get install -y git docker.io
sudo usermod -aG docker $USER && reboot

# download the project's source code (if you haven't done before)
git clone https://github.com/Bonifatius94/ChessLib.Py
cd ChessLib.Py

# install the 'Visual Studio Code' text editor (optional)
sudo snap install code --classic

Copyright

You may use this project under the MIT licence's conditions.

Metadata

Release files for chesslib 1.0.333892592

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for chesslib 1.0.333892592
File	Interpreter	ABI	Platform	Reset
chesslib-1.0.333892592-cp39-cp39-manylinux2010_x86_64.whl 63.5 kB Feb 27, 2021	CPython 3.9	CPython 3.9	Linux glibc 2.12+ x86-64	Details
chesslib-1.0.333892592-cp37-cp37m-manylinux2010_x86_64.whl 64.6 kB Feb 27, 2021	CPython 3.7	CPython 3.7 pymalloc	Linux glibc 2.12+ x86-64	Details

Total release size: 128.1 kB

Release files / chesslib-1.0.333892592-cp39-cp39-manylinux2010_x86_64.whl

Download URL	chesslib-1.0.333892592-cp39-cp39-manylinux2010_x86_64.whl
Size	63.5 kB
Tags	CPython 3.9 Linux glibc 2.12+ x86-64
SHA-256 checksum How to use checksums	`30d97d3bfea8bc2979a6f277d2aa2102a812d614a79381a10fce3546853bed86`
BLAKE2b-256 checksum How to use checksums	`4f175e621e0123e2618559ffb0462fa266cbf6ef281abc76edc692f8af0a474b`
Upload date	Feb 27, 2021
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.8.7`

Release files / chesslib-1.0.333892592-cp37-cp37m-manylinux2010_x86_64.whl

Download URL	chesslib-1.0.333892592-cp37-cp37m-manylinux2010_x86_64.whl
Size	64.6 kB
Tags	CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum How to use checksums	`6b54b5498abfeda88837040840178b281e8bc159a1fb9d9cacb108fa2188c6f1`
BLAKE2b-256 checksum How to use checksums	`2d4b56aa8b4a93d71c61a6ecf4bdf69304c757fb30a00bd935183bb52600f0c2`
Upload date	Feb 27, 2021
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.8.7`