streak-hunting-spreadsheet/endgames.py

64 lines
2 KiB
Python
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2023-11-11 01:38:37 +01:00
import json
import re
import subprocess
from typing import Dict
from pathlib import Path
DATA_FILE = Path('endgame-data.json')
if not DATA_FILE.exists():
DATA_FILE.write_text('{}')
with open(DATA_FILE, 'r') as f:
DATA: Dict = json.loads(f.read())
def analyze_game(game_id: int):
probabilities = {}
for deck_size in range(1, 16):
try:
result = subprocess.run(['./endgame-analyzer', '-g', str(game_id), '-d', str(deck_size), '-i', '0'], stdout=subprocess.PIPE, timeout=30)
except subprocess.TimeoutExpired:
return probabilities
output = result.stdout.decode('utf-8')
m = re.search('Probability with optimal play: .*/.* ~ ([0-9.]+)', output)
if not m:
raise ValueError("Invalid program output: {}".format(output))
probabilities[str(deck_size)] = m.group(1)
return probabilities
def full_analyze_game(game_id: int):
probabilities = {}
try:
result = subprocess.run(['./endgame-analyzer', '-g', str(game_id), '-d', str(deck_size), '-i', '0', '--all-clues', '-r'], stdout=subprocess.PIPE, timeout=180)
except subproces.TimeoutExpired:
return probabilities
output = result.stdout.decode('utf-8')
for m in re.finditer('Probability with (\d+) cards left in deck and (\d) clues (+|-\d): .*/.* ~ ([0-9.]+)', output):
probabilities[m.group(1)][m.group(3)] = m.group(4)
return probabilities
def full_analyze_game_cached(game_id: int):
cached = DATA.get('all', {}).get(str(game_id), None)
if cached is not None:
return cached
result = full_analyze_game(game_id)
DATA['all'][game_id] = result
save_cache()
return result
def analyze_game_cached(game_id: int):
cached = DATA['normal'].get(str(game_id), None)
if cached is not None:
return cached
result = analyze_game(game_id)
DATA['normal'][game_id] = result
save_cache()
return result
def save_cache():
with open(DATA_FILE, 'w') as f:
f.writelines(json.dumps(DATA, indent=2))