testsAndMisc-archive/python_pkg/stockfish_analysis/analyze_chess_game.py
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459 lines
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Python
Executable File

#!/usr/bin/env python3
"""Analyze a chess game's moves using a local Stockfish engine and rate each move.
Usage:
python3 python_pkg/analyze_chess_game.py <path-to-file>
[--engine stockfish]
[--time 0.5 | --depth 20]
[--threads auto|N]
[--hash-mb auto|MB]
[--multipv N]
[--last-move-only]
Notes:
- Requires python-chess. Install from python_pkg/stockfish_analysis/requirements.txt
- The input file can be a pure PGN or a log file containing a PGN section.
- The script tries to locate the PGN by looking for a 'PGN:' marker,
PGN tags '[...]', or a move list starting with '1.'.
- Stockfish is CPU-based; it doesn't use GPU VRAM. "Full power" here means
using many CPU threads and a large transposition table (Hash).
"""
from __future__ import annotations
import argparse
import contextlib
import io
import logging
import multiprocessing
from pathlib import Path
import re
import sys
from python_pkg.stockfish_analysis._move_analysis import (
AnalysisContext,
MoveAnalysis,
_analyze_single_move,
fmt_eval,
)
_logger = logging.getLogger(__name__)
try:
import psutil
except ImportError: # pragma: no cover
psutil = None
try:
import chess
import chess.engine
import chess.pgn
except ImportError: # pragma: no cover
_logger.exception("Missing dependency. Please install python-chess:")
_logger.exception(" pip install -r python_pkg/stockfish_analysis/requirements.txt")
raise
# Memory configuration constants
MEMINFO_PARTS_MIN = 2
HIGH_THREAD_COUNT = 16
def extract_pgn_text(raw: str) -> str | None:
"""Try to extract a PGN block from a possibly noisy file.
Strategies tried in order:
1) Everything after a line that equals or starts with 'PGN:'
2) From the first PGN tag line '[' to the end
3) From the first line starting with an integer and a dot (e.g., '1.') to the end
"""
lines = raw.splitlines()
# 1) After 'PGN:' marker
for i, line in enumerate(lines):
if line.strip().startswith("PGN:"):
# everything after this line
pgn = "\n".join(lines[i + 1 :]).strip()
if pgn: # pragma: no branch
return pgn
# 2) From first tag line
for i, line in enumerate(lines):
if line.strip().startswith("[") and "]" in line:
pgn = "\n".join(lines[i:]).strip()
if pgn: # pragma: no branch
return pgn
# 3) From first move number
move_start_re = re.compile(r"^\s*\d+\.")
for i, line in enumerate(lines):
if move_start_re.match(line):
pgn = "\n".join(lines[i:]).strip()
if pgn: # pragma: no branch
return pgn
return None
def _parse_threads(value: str) -> int | None:
v = value.strip().lower()
if v in ("auto", "max", ""): # auto-detect
return None
try:
n = int(v)
return max(1, n)
except ValueError:
msg = "--threads must be an integer or 'auto'"
raise argparse.ArgumentTypeError(msg) from None
def _parse_hash_mb(value: str) -> int | None:
v = value.strip().lower()
if v in ("auto", "max", ""): # auto-detect
return None
try:
mb = int(v)
return max(16, mb)
except ValueError:
msg = "--hash-mb must be an integer (MB) or 'auto'"
raise argparse.ArgumentTypeError(msg) from None
def _detect_total_mem_mb() -> int | None:
# Prefer psutil if available
if psutil is not None:
with contextlib.suppress(Exception):
return int(psutil.virtual_memory().total // (1024 * 1024))
# Fallback approach for Linux systems using proc meminfo.
with (
contextlib.suppress(Exception),
Path("/proc/meminfo").open(encoding="utf-8", errors="ignore") as f,
):
for line in f:
if line.startswith("MemTotal:"):
parts = line.split()
if len(parts) >= MEMINFO_PARTS_MIN and parts[1].isdigit():
# Value is in kB
kb = int(parts[1])
return kb // 1024
return None
def _auto_hash_mb(threads_wanted: int, engine_options: dict[str, object]) -> int:
total_mb = _detect_total_mem_mb() or 2048
# Heuristic: cap at 4 GiB by default; keep at most half of RAM; ensure >= 64MB
half_ram = max(64, total_mb // 2)
target = half_ram
# Respect engine "Hash" max if exposed
opt = engine_options.get("Hash")
max_allowed = None
try:
max_allowed = opt.max if opt is not None else None
except AttributeError:
max_allowed = None
if isinstance(max_allowed, int):
target = min(target, max_allowed)
# Some rough scaling: if very many threads, give a bit more (but not huge)
if threads_wanted >= HIGH_THREAD_COUNT:
target = min(target + 1024, (total_mb * 3) // 4)
return max(64, int(target))
# Type aliases for clarity
EngineOptions = dict[str, object]
def _build_argument_parser() -> argparse.ArgumentParser:
"""Build and return the argument parser for the analysis script."""
ap = argparse.ArgumentParser(
description="Analyze a chess game's moves with Stockfish and rate each move."
)
ap.add_argument("file", help="Path to a PGN file or a log containing a PGN section")
ap.add_argument(
"--engine",
default="stockfish",
help="Path to stockfish executable (default: stockfish)",
)
ap.add_argument(
"--time",
type=float,
default=0.5,
help="Analysis time per evaluation in seconds (default: 0.5)",
)
ap.add_argument(
"--depth",
type=int,
default=None,
help="Fixed depth per evaluation (overrides --time)",
)
ap.add_argument(
"--threads",
type=_parse_threads,
default=None,
metavar="auto|N",
help="Engine threads to use (default: auto = all logical cores)",
)
ap.add_argument(
"--hash-mb",
type=_parse_hash_mb,
default=None,
metavar="auto|MB",
help="Hash table size in MB (default: auto = up to half RAM, capped)",
)
ap.add_argument(
"--multipv",
type=int,
default=2,
help="Number of principal variations to compute (default: 1)",
)
ap.add_argument(
"--last-move-only",
action="store_true",
help=(
"Analyze only the last move of the main line "
"(reports its eval and the best move)"
),
)
return ap
def _load_game(file_path: str) -> chess.pgn.Game:
"""Load and parse a chess game from a file."""
if not Path(file_path).is_file():
_logger.error("Input not found: %s", file_path)
sys.exit(1)
with Path(file_path).open(encoding="utf-8", errors="replace") as f:
raw = f.read()
pgn_text = extract_pgn_text(raw)
if not pgn_text:
_logger.error("Could not locate PGN text in the file.")
sys.exit(2)
game = chess.pgn.read_game(io.StringIO(pgn_text))
if game is None:
_logger.error("Failed to parse PGN.")
sys.exit(3)
return game
def _configure_threads(
engine: chess.engine.SimpleEngine,
options: EngineOptions,
requested: int | None,
) -> int:
"""Configure engine thread count and return actual threads used."""
wanted = requested if requested is not None else (multiprocessing.cpu_count() or 1)
if "Threads" not in options:
return wanted
try:
max_thr = getattr(options["Threads"], "max", None)
min_thr = getattr(options["Threads"], "min", 1)
if isinstance(max_thr, int):
wanted = min(wanted, max_thr)
if isinstance(min_thr, int):
wanted = max(wanted, min_thr)
engine.configure({"Threads": int(wanted)})
except (AttributeError, TypeError, ValueError):
_logger.debug("Failed to configure Threads option")
return wanted
def _configure_hash(
engine: chess.engine.SimpleEngine,
options: EngineOptions,
requested: int | None,
threads: int,
) -> None:
"""Configure engine hash table size."""
if "Hash" not in options:
return
try:
target = (
int(requested) if requested is not None else _auto_hash_mb(threads, options)
)
max_hash = getattr(options["Hash"], "max", None)
min_hash = getattr(options["Hash"], "min", 16)
if isinstance(max_hash, int):
target = min(target, max_hash)
if isinstance(min_hash, int):
target = max(target, min_hash)
engine.configure({"Hash": int(target)})
except (AttributeError, TypeError, ValueError):
_logger.debug("Failed to configure Hash option")
def _configure_multipv(
_engine: chess.engine.SimpleEngine, options: EngineOptions, requested: int
) -> int:
"""Configure MultiPV and return effective value."""
effective = max(1, int(requested))
# MultiPV is automatically managed by python-chess and passed directly to
# engine.analyse(..., multipv=N) — do not configure() it here.
if "MultiPV" in options:
try:
max_mpv = getattr(options["MultiPV"], "max", None)
if isinstance(max_mpv, int):
effective = min(effective, max_mpv)
except (AttributeError, TypeError, ValueError):
_logger.debug("Failed to read MultiPV max option")
return effective
def _configure_nnue(engine: chess.engine.SimpleEngine, options: EngineOptions) -> None:
"""Enable NNUE if supported."""
for nnue_key in ("Use NNUE", "UseNNUE"):
if nnue_key in options:
with contextlib.suppress(Exception):
engine.configure({nnue_key: True})
def _setup_engine(
args: argparse.Namespace,
) -> tuple[chess.engine.SimpleEngine, int, chess.engine.Limit]:
"""Initialize and configure the chess engine."""
try:
engine = chess.engine.SimpleEngine.popen_uci([args.engine])
except FileNotFoundError:
_logger.exception("Could not launch engine at: %s", args.engine)
_logger.exception(
"Ensure Stockfish is installed and in PATH, or specify with --engine."
)
sys.exit(4)
try:
options = engine.options
except AttributeError:
options = {}
threads = _configure_threads(engine, options, args.threads)
_configure_hash(engine, options, args.hash_mb, threads)
effective_mpv = _configure_multipv(engine, options, args.multipv)
_configure_nnue(engine, options)
limit: chess.engine.Limit
if args.depth is not None:
limit = chess.engine.Limit(depth=args.depth)
else:
limit = chess.engine.Limit(time=max(0.05, args.time))
_log_engine_config(engine, threads, effective_mpv)
return engine, effective_mpv, limit
def _log_engine_config(
engine: chess.engine.SimpleEngine, threads: int, multipv: int
) -> None:
"""Log engine configuration summary."""
try:
hash_val = engine.options.get("Hash")
hash_show = int(hash_val.value) if hash_val else None
except (AttributeError, TypeError, ValueError):
hash_show = None
if hash_show is not None:
_logger.info(
"Using engine options: Threads=%s, Hash=%s MB, MultiPV=%s",
threads,
hash_show,
multipv,
)
else:
_logger.info("Using engine options: Threads=%s, MultiPV=%s", threads, multipv)
def _log_move_analysis(ply: int, result: MoveAnalysis, *, mover_white: bool) -> None:
"""Log a single move's analysis result."""
side = "W" if mover_white else "B"
loss_str = str(result.cp_loss) if result.cp_loss is not None else ""
_logger.info(
"%3d %s %-8s %10s %9s %5s %-12s %s",
ply,
side,
result.san,
fmt_eval(result.played_cp, result.played_mate),
fmt_eval(result.best_cp, result.best_mate),
loss_str,
result.classification,
result.best_san,
)
def _run_analysis(
game: chess.pgn.Game, ctx: AnalysisContext, *, last_move_only: bool
) -> None:
"""Run the move-by-move analysis."""
board = game.board()
_logger.info("Game:")
white = game.headers.get("White", "White")
black = game.headers.get("Black", "Black")
result = game.headers.get("Result", "*")
_logger.info(" %s vs %s Result: %s", white, black, result)
_logger.info("")
_logger.info(
"Columns: ply side move played_eval best_eval loss class best_suggestion"
)
if last_move_only:
_analyze_last_move(game, board, ctx)
else:
_analyze_all_moves(game, board, ctx)
def _analyze_last_move(
node: chess.pgn.Game, board: chess.Board, ctx: AnalysisContext
) -> None:
"""Walk to last move and analyze only that ply."""
if not node.variations:
_logger.warning("No moves found in the game.")
return
ply = 1
while node.variations: # pragma: no branch
move_node = node.variations[0]
move = move_node.move
if not move_node.variations:
result = _analyze_single_move(ctx, board, move)
_log_move_analysis(ply, result, mover_white=board.turn)
break
board.push(move)
node = move_node
ply += 1
def _analyze_all_moves(
node: chess.pgn.Game, board: chess.Board, ctx: AnalysisContext
) -> None:
"""Analyze all moves in the game."""
ply = 1
while node.variations:
move_node = node.variations[0]
move = move_node.move
mover_white = board.turn
result = _analyze_single_move(ctx, board, move)
_log_move_analysis(ply, result, mover_white=mover_white)
node = move_node
ply += 1
board.push(move)
def main() -> None:
"""Parse arguments and run chess game analysis."""
args = _build_argument_parser().parse_args()
game = _load_game(args.file)
engine, effective_mpv, limit = _setup_engine(args)
ctx = AnalysisContext(engine=engine, limit=limit, multipv=effective_mpv)
try:
_run_analysis(game, ctx, last_move_only=args.last_move_only)
finally:
engine.quit()
if __name__ == "__main__":
main()