从游戏到数据：用 Python 解析炉石传说盒子本地数据，构建个人对局分析看板

import os

def parse_hsa_config():
    config_path = os.path.join(os.getenv('APPDATA'), 'HSAng', 'hsa.config')
    config = {}
    try:
        with open(config_path, 'r', encoding='utf-8') as f:
            for line in f:
                line = line.strip()
                if line and not line.startswith('#') and '=' in line:
                    key, _, value = line.partition('=')
                    config[key.strip()] = value.strip()
    except FileNotFoundError:
        print(f"配置文件未找到: {config_path}")
    return config

cfg = parse_hsa_config()
print(cfg)

import json
import glob

def load_all_json(data_dir):
    records = []
    for filepath in glob.glob(os.path.join(data_dir, '*.json')):
        try:
            with open(filepath, 'r', encoding='utf-8') as f:
                data = json.load(f)
                if isinstance(data, list):
                    records.extend(data)
                elif isinstance(data, dict):
                    records.append(data)
        except (json.JSONDecodeError, UnicodeDecodeError):
            print(f"跳过无法解析的文件: {filepath}")
    return records

base_dir = os.path.join(os.getenv('APPDATA'), 'HSAng')
all_records = load_all_json(base_dir)
print(f"共加载 {len(all_records)} 条记录")

import pandas as pd

df = pd.DataFrame(all_records)
# 根据实际字段做筛选与重命名，以下为常见字段示例
if not df.empty:
    df = df.rename(columns={
        'hero': '使用职业',
        'opponent': '对手职业',
        'result': '胜负',
        'timestamp': '对局时间'
    })
    print(df[['对局时间', '使用职业', '对手职业', '胜负']].head(10))

import re
from datetime import datetime

def parse_power_log(log_path):
    events = []
    zone_change_pattern = re.compile(
        r'(?P<timestamp>\d{2}:\d{2}:\d{2}\.\d+)\s+'
        r'ZoneChangeList\.ProcessChanges\(\)\s*-\s*'
        r'id=(?P<card_id>\d+).*'
        r'from\s*(?P<from_zone>\w+)\s*->\s*(?P<to_zone>\w+)'
    )
    try:
        with open(log_path, 'r', encoding='utf-8', errors='ignore') as f:
            for line in f:
                m = zone_change_pattern.search(line)
                if m:
                    events.append(m.groupdict())
    except FileNotFoundError:
        pass
    return events

log_dir = os.path.join(os.getenv('LOCALAPPDATA'), 'Blizzard', 'Hearthstone', 'Logs')
power_log = os.path.join(log_dir, 'Power.log')
zone_events = parse_power_log(power_log)
print(f"解析到 {len(zone_events)} 条卡牌转移事件")

df['对局时间'] = pd.to_datetime(df['对局时间'], unit='ms', errors='coerce')
df = df.dropna(subset=['胜负'])
df = df[df['胜负'].isin(['win', 'lose'])]

profession_map = {
    1: '德鲁伊', 2: '猎人', 3: '法师', 4: '圣骑士',
    5: '牧师',  6: '潜行者', 7: '萨满', 8: '术士',
    9: '战士', 10: '恶魔猎手', 11: '死亡骑士'
}
df['使用职业名'] = df['使用职业'].map(profession_map)
df['对手职业名'] = df['对手职业'].map(profession_map)

import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif'] = ['SimHei']  # 中文显示
stats = df.groupby('使用职业名')['胜负'].apply(
    lambda x: (x == 'win').sum() / len(x)
).sort_values(ascending=False)

plt.figure(figsize=(10, 5))
stats.plot(kind='bar', color='#4CAF50')
plt.title('各职业胜率对比')
plt.ylabel('胜率')
plt.xticks(rotation=45)
plt.tight_layout()
plt.savefig('winrate_by_class.png', dpi=150)

df['日期'] = df['对局时间'].dt.date
pivot = df.pivot_table(
    values='胜负', index='使用职业名', columns='日期',
    aggfunc=lambda x: (x == 'win').sum() / len(x)
)
plt.figure(figsize=(12, 6))
plt.imshow(pivot, cmap='RdYlGn', aspect='auto')
plt.colorbar(label='胜率')
plt.xticks(range(len(pivot.columns)), pivot.columns, rotation=45)
plt.yticks(range(len(pivot.index)), pivot.index)
plt.title('每日各职业胜率热力图')
plt.tight_layout()
plt.savefig('heatmap.png', dpi=150)