A ~2000 Elo Python chess engine

1 month ago 1

Moonfish is a didactic Python chess engine designed to showcase parallel search algorithms and modern chess programming techniques. Built with code readability as a priority, Moonfish makes advanced concepts easily accessible providing a more approachable alternative to cpp engines.

The engine achieves approximately ~2000 Elo when playing against Lichess Stockfish bots (beats level 5 and loses to level 6) and includes comprehensive test suites including the Bratko-Kopec tactical test positions.

Python 3.10

Install the python library:

From python:

$ python >>> import chess >>> import moonfish >>> board = chess.Board() >>> moonfish.search_move(board) Move.from_uci('g1f3')

You can also call the CLI, the CLI works as an UCI Compatible Engine:

$ moonfish --mode=uci uci # <- user input id name Moonfish id author luccabb uciok

You can also run it as an API:

Then send a request:

$ curl "http://localhost:5000/?fen=rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR%20w%20KQkq%20-%200%201&depth=4&quiescence_search_depth=3&null_move=True&null_move_r=2&algorithm=alpha_beta" { "body": { "move": "e2e4" }, "headers": { "Access-Control-Allow-Headers": "Content-Type", "Access-Control-Allow-Methods": "OPTIONS,GET", "Access-Control-Allow-Origin": "*" }, "statusCode": 200 }

Alpha-Beta Pruning - Negamax with α-β cutoffs
Lazy SMP - Shared memory parallel search utilizing all CPU cores
Layer-based Parallelization - Distributing work at specific search depths
Null Move Pruning - Skip moves to detect zugzwang positions
Quiescence Search - Extended search for tactical positions

Evaluation & Optimization

PeSTO Evaluation - Piece-square tables (PST) with tapered evaluation. Using Rofchade's PST.
Transposition Tables - Caching to avoid redundant calculations
Move Ordering - MVV-LVA (Most Valuable Victim - Least Valuable Attacker)
Syzygy Tablebase support for perfect endgame play
Opening Book integration (Cerebellum format)

UCI Protocol - Compatible with popular chess GUIs
Web API - RESTful interface for online integration
Lichess Bot - Ready for deployment on Lichess.org

Parameter Description Default Options

--mode	Engine Mode	uci	uci, api
--algorithm	Search algorithm	alpha_beta	alpha_beta, lazy_smp, parallel_alpha_beta_layer_1
--depth	Search depth	3	1-N
--null-move	Whether to use null move pruning	False	True, False
--null-mov-r	Null move reduction factor	2	1-N
--quiescence-search-depth	Max depth of quiescence search	3	1-N
--syzygy-path	Tablebase directory	None	Valid path