Train your chess board vision on your own games: drill the checks, captures, threats, mistakes and missed mates you keep overlooking.
Project description
boardviz
Analyze your chess.com history for recurring mistakes — especially the "big think → blunder" pattern that bites when you're winning — and drill those positions in an interactive, timed trainer that scores each move on a +2..−2 scale.
What it does
- Import your games from chess.com (last N games, walking monthly archives).
- Filter by color, time control, and outcome.
- Review engine-confirmed mistakes and cluster the recurring ones (by pawn structure, move type, phase, opening).
- Big-think analytic — tests whether long thinks lead to more mistakes, split by game state (winning / equal / losing).
- Trainer — replays your mistake positions; you make a move and get a +2..−2 grade, with a time penalty (e.g. blitz −1 after 10s, −2 after 20s).
- Scout any opponent's history, and grade both sides of your own games.
Setup
uv sync
Stockfish engine (required)
The analysis needs a Stockfish binary. It is not committed (GPL-3.0; the app itself is MIT and drives the engine arm's-length over UCI). Provide one of:
- Place
stockfish.exeinengines/(this repo already vendors it locally), or - Set
STOCKFISH_PATHto your own binary.
Download official builds from https://stockfishchess.org/download/ (Windows
AVX2). The vendored engine's license is in engines/Stockfish-LICENSE.txt.
Usage
uv run boardviz fetch --user hucker233 --n 100 # download last 100 games
uv run boardviz analyze --user hucker233 # engine analysis (cached)
uv run streamlit run src/boardviz/app.py # launch the app
Data (raw archives + the SQLite DB) lives in data/ and is gitignored.
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