# -*- coding: utf-8 -*-
"""
评估"预生成每型号 zip"方案的收益与代价。
扫描 web 发布目录的 step/，统计原始总体积 vs zip 后体积。
"""
import os, zipfile, io, random

WEB = r'D:/开发/OnebotCatalog/release/web_2026.08/step'
if not os.path.isdir(WEB):
    raise SystemExit('找不到 ' + WEB)

files = [f for f in os.listdir(WEB) if f.lower().endswith(('.step', '.stp'))]
print(f'step 文件数: {len(files)}')

tot = sum(os.path.getsize(os.path.join(WEB, f)) for f in files)
print(f'原始总体积: {tot/1073741824:.2f} GB')

# 抽样测压缩率（避免全量压缩耗时）
random.seed(42)
sample = random.sample(files, min(40, len(files)))
raw = zipped = 0
for f in sample:
    p = os.path.join(WEB, f)
    n = os.path.getsize(p)
    buf = io.BytesIO()
    with zipfile.ZipFile(buf, 'w', zipfile.ZIP_DEFLATED, compresslevel=6) as z:
        z.write(p, f[:-4] + '.step' if f.lower().endswith('.stp') else f)
    raw += n
    zipped += buf.tell()
print(f'\n抽样 {len(sample)} 个:')
print(f'  原始 {raw/1048576:.1f} MB -> zip {zipped/1048576:.1f} MB  (省 {(1-zipped/raw)*100:.1f}%)')
print(f'\n推算全量:')
print(f'  stepz 目录约 {(tot*(zipped/raw))/1073741824:.2f} GB')
print(f'  部署总目录 = step {tot/1073741824:.2f}GB + stepz {(tot*(zipped/raw))/1073741824:.2f}GB'
      f' = {(tot*(1+zipped/raw))/1073741824:.2f} GB')
print(f'\n购物车场景收益 (选 20 个型号, 平均 {tot/len(files)/1048576:.1f}MB/个):')
per = tot / len(files)
print(f'  现状: 传 {20*per/1048576:.0f} MB 原始文件')
print(f'  改后: 传 {20*per*(zipped/raw)/1048576:.0f} MB 压缩文件')