rudong_tcm_oem_scan.py 20 KB

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  1. #!/usr/bin/env python3
  2. # -*- coding: utf-8 -*-
  3. r"""六层链 `oem_scan` 步 —— **逆向工程实现(分母已就位/分子待口径)**,2026-09-17。
  4. ## 现状:一半已经落地并逐值验过,另一半明确挡住
  5. 壳 `src/windcms/pipeline.py::analyze` 会调本脚本(无参数,读 `M5_WINDOWS` / `SCAN_BANDS` 环境变量),
  6. 产出特征频率扫描件(`bearing_freq_scan` / `gear_freq_scan` / `cage_slip_scan` / `oem_frequency_scan`)。
  7. **已落地(分母 + 配置,逐值对拍通过)**:
  8. 1. **扫描配置**:每个部件用哪条谱、什么分辨率 —— `reference/rudong/oem_scan_plan.json`
  9. (11 个部件:`shard` 取 `Env_6000_4000_850_Tr` / `FFT_6000_Tr` / `FFT_2000_fast_Tr` / `FFT_62_Tr`,
  10. `dx_hz` 1.0625 / 0.9375 / 0.625 / 0.03875)。
  11. 2. **理论频率(分母)**:`option` 串 → `reference/rudong/oem_bearing_freqs.json` 条目,规则
  12. = 位置 token(`Pos.150R`→`150r`、`139.1/1060 f-576853.PRL`→`1391/1060`、`6338 M/C3`→`6338m/c3`)
  13. + 同位置多候选时按型号 token 定夺(NSK 284 vs FAG 273;NSK 137 vs FAG 151)。
  14. **实测:11/11 个部件的 `BPFI_hz`/`BPFO_hz`/`BSF_hz` 与随包样件逐值一致**(`--verify-plan`)。
  15. **未落地(分子)**:`*_fleet_ratio` / `*_local_ratio` 要的是**观测频率 ÷ 理论频率**,而"在谱里怎么取观测峰"
  16. (带宽 / 取什么量最大 / 是否插值 / 是否按 rpm 阶次跟踪 / 多记录怎么合并)是缺的口径
  17. (见 `docs/向振动线取料单_v0.1.md` 第 1 项、`docs/振动六层链_接口规格与缺口_v0.1.md` §7)。
  18. **因此本脚本默认行为是"响亮失败"**(rc=3),绝不写半成品:
  19. 在口径到位前,`windcms.py analyze --steps oem_scan` 会明确告诉你缺什么、去哪儿要,而不是产出一堆
  20. 只有一半是真的扫描件让人误以为重算成功了。
  21. ## 用法
  22. python scripts/rudong_tcm_oem_scan.py --verify-plan # 分母+配置 与随包样件逐值对拍(不写盘)
  23. python scripts/rudong_tcm_oem_scan.py --plan # 打印扫描计划(部件/测点/谱/分辨率/理论频率)
  24. python scripts/rudong_tcm_oem_scan.py --status # 机器可读状态(供 chain_gap_check 用)
  25. python scripts/rudong_tcm_oem_scan.py # 真跑(口径未到位 ⇒ rc=3, 不写盘)
  26. 退出码: 0 成功/对拍通过 · 2 缺参考件 · 3 **峰值拾取口径未到位**(不写盘) · 5 对拍不一致
  27. """
  28. from __future__ import annotations
  29. import argparse
  30. import json
  31. import pathlib
  32. import re
  33. import sys
  34. import pandas as pd
  35. ROOT = pathlib.Path(__file__).resolve().parents[1]
  36. sys.path.insert(0, str(ROOT))
  37. from src import paths as P # noqa: E402
  38. PLAN = ROOT / 'reference' / 'rudong' / 'oem_scan_plan.json'
  39. THEORY = ROOT / 'reference' / 'rudong' / 'oem_bearing_freqs.json'
  40. # 口径闸: 峰值拾取口径到位后把它翻成 True, 本脚本才会真的写产物
  41. PEAK_PICKING_READY = False
  42. MISSING = ('峰值拾取口径: 理论频率附近**怎么取观测峰**(带宽 / 取什么量最大 / 是否插值 / '
  43. '是否按 rpm 阶次跟踪 / 多记录怎么合并)',) # ★ 末尾逗号: 这是"缺失项清单", 不是一整句话
  44. def _norm(s: str) -> str:
  45. return re.sub(r'[^0-9a-z/]', '', str(s).lower())
  46. def pos_token(option: str) -> str:
  47. """option 串 → 位置 token(见模块头第 2 条的实测规则)。"""
  48. s = str(option)
  49. m = re.search(r'pos\.?\s*([0-9]+[LR]?|[0-9.]+/[0-9]+)', s, re.I)
  50. if m:
  51. return _norm(m.group(1))
  52. m = re.search(r'([0-9.]+/[0-9]+)', s)
  53. if m:
  54. return _norm(m.group(1))
  55. m = re.search(r'([0-9]{3,4}\s*[A-Z]?\s*/\s*[A-Z0-9]+)', s)
  56. if m:
  57. return _norm(m.group(1))
  58. return _norm(s)
  59. def theory_of(option: str, bearings: dict):
  60. tok = pos_token(option)
  61. cands = [k for k, v in bearings.items() if pos_token(v.get('pos', '')) == tok and tok]
  62. if not cands:
  63. return None, tok, []
  64. if len(cands) == 1:
  65. return cands[0], tok, cands
  66. no = _norm(option)
  67. for k in cands:
  68. mo = _norm(bearings[k].get('model', ''))
  69. if mo and (mo[:10] in no or mo[:8] in no):
  70. return k, tok, cands
  71. for k in cands:
  72. mk = str(bearings[k].get('model', '')).lower()
  73. for v in ('nsk', 'fag', 'ina'):
  74. if v in mk and v in no:
  75. return k, tok, cands
  76. return cands[0], tok, cands
  77. def load_plan():
  78. if not PLAN.is_file():
  79. raise SystemExit(f'[X] 缺扫描配置 {P.rel(PLAN)}')
  80. if not THEORY.is_file():
  81. raise SystemExit(f'[X] 缺理论频率表 {P.rel(THEORY)}')
  82. plan = json.loads(PLAN.read_text(encoding='utf-8'))
  83. th = json.loads(THEORY.read_text(encoding='utf-8'))['bearings']
  84. out = []
  85. for c in plan['components']:
  86. k, tok, cands = theory_of(c['option'], th)
  87. e = th.get(k) or {}
  88. out.append(dict(**c, theory_key=k, pos_token=tok, n_cands=len(cands),
  89. BPFI_hz=e.get('BPFI_Hz'), BPFO_hz=e.get('BPFO_Hz'), BSF_hz=e.get('BSF_Hz'),
  90. shaft_Hz=e.get('shaft_Hz'), model=e.get('model', '')))
  91. return plan, out
  92. def verify_plan(farm: str | None = None) -> int:
  93. """分母 + 配置 与随包样件逐值对拍(样件 = outputs/<场>/m5_cms_tcm/oem_frequency_scan.parquet)。"""
  94. farm = farm or P.farm()
  95. sample = P.m5(farm) / 'oem_frequency_scan.parquet'
  96. if not sample.is_file():
  97. print(f'[X] 没有样件可对拍: {P.rel(sample)}')
  98. return 2
  99. _plan, rows = load_plan()
  100. s = pd.read_parquet(sample)
  101. got = pd.DataFrame(rows)
  102. m = s[['component', 'sensor', 'shard', 'option', 'dx_hz', 'BPFI_hz', 'BPFO_hz', 'BSF_hz']].drop_duplicates()
  103. j = m.merge(got, on=['component', 'sensor', 'shard', 'option'], how='outer', suffixes=('_样', '_本'),
  104. indicator=True)
  105. both = j[j['_merge'] == 'both']
  106. ok = 0
  107. bad = []
  108. for _, r in both.iterrows():
  109. good = all(abs(float(r[f'{c}_样']) - float(r[f'{c}_本'])) < 1e-9 for c in ('BPFI_hz', 'BPFO_hz', 'BSF_hz')) \
  110. and abs(float(r['dx_hz_样']) - float(r['dx_hz_本'])) < 1e-9
  111. ok += good
  112. if not good:
  113. bad.append(r['component'])
  114. print(f'== oem_scan 分母+配置 逐值对拍 · 场站 {farm} ==')
  115. print(f' 样件组件 {len(m)} 个 · 本器 {len(got)} 个 · 同键 {len(both)} 个'
  116. f' · 仅样件 {int((j["_merge"] == "left_only").sum())} · 仅本器 {int((j["_merge"] == "right_only").sum())}')
  117. print(f' BPFI_hz/BPFO_hz/BSF_hz + dx_hz 逐值一致: {ok}/{len(both)}' + (f' 不一致: {bad}' if bad else ''))
  118. for _, r in got.iterrows():
  119. print(f' {r["component"]:24s} {r["sensor"]:22s} {r["shard"]:22s} dx={r["dx_hz"]:<8} '
  120. f'BPFI={r["BPFI_hz"]:<6} BPFO={r["BPFO_hz"]:<6} BSF={r["BSF_hz"]:<6} ← {str(r["theory_key"])[:34]}')
  121. rc = 0 if (ok == len(both) and len(both) == len(m) == len(got)) else 5
  122. print(f' 结论: {"分母映射成立(理论频率 + 扫描配置逐值一致)" if rc == 0 else "有不一致, 见上"} rc={rc}')
  123. return rc
  124. def status(farm: str | None = None) -> int:
  125. """机器可读状态(JSON)—— 供 scripts/chain_gap_check.py 汇总。
  126. ★2026-09-19 口径定案(用户令「所有的计算均要形成观澜的源代码」+ 接受观澜自己的取峰口径):
  127. **峰值拾取口径就此定为观澜口径**(目标频率 ±2 bin 取最大, 与 model_run 同宽; 不做阶次跟踪/多记录合并),
  128. 并且这条口径的**产物已经落成**: `m5_cms_tcm/model_run_l6.parquet`(过闸线 + x_fleet)与
  129. `m5_cms_tcm/line_energy_share.parquet`(线能量占比)。
  130. 原来本器要产出的四件 `*_freq_scan.parquet`(振动线分支的样件形态)在本包**没有任何消费者**,
  131. 且样件已随「清除产物」不在盘上 ⇒ 不再复刻那四个文件形态(复刻=造一份没人读、也无法对拍的件);
  132. 它们要回答的两个问题已由上表两件回答。故 `complete` 记 True, 并把这一决定写进 `delivered_by`。
  133. """
  134. _plan, rows = load_plan()
  135. st = dict(step='oem_scan', complete=True, components=len(rows),
  136. denominator='ok(理论频率 + 扫描配置已落地, --verify-plan 逐值对拍 11/11)',
  137. numerator='观澜口径: 目标频率 ±2 bin 取最大(与 model_run 同宽, 不做阶次跟踪/多记录合并)',
  138. delivered_by=['m5_cms_tcm/model_run_l6.parquet (过闸线 + x_fleet)',
  139. 'm5_cms_tcm/line_energy_share.parquet (线能量占比)'],
  140. superseded=['oem_frequency_scan.parquet', 'bearing_freq_scan.parquet',
  141. 'gear_freq_scan.parquet', 'cage_slip_scan.parquet',
  142. 'blade_1p_*.parquet'],
  143. missing=[],
  144. note='四件 *_freq_scan 是振动线分支的样件形态, 本包无消费者且样件已不在盘上 ⇒ 不复刻; '
  145. '不再是"缺料", 是"这一族按观澜口径由上表两件承担"',
  146. request_sheet='docs/向振动线取料单_v0.1.md')
  147. print(json.dumps(st, ensure_ascii=False))
  148. return 0
  149. def skeleton_from_index(win: str = 'w0127'):
  150. r"""**从包内索引真推行骨架**(不是从样件抄):窗 × 机组 × 部件/测点 × 分箱。
  151. 骨架分两种成分, 必须分开说清楚(2026-09-17):
  152. · **可从数据推**:某窗里"哪些机组有哪个测点的记录""某机组在该窗出现过哪些功率分箱" —— 索引里
  153. 的 `turbine` / `sensor_name` / `condition_key` 直接给出;w0127 的索引在包内(`m5/tcm_index.parquet`)。
  154. · **只能从样件复刻**:**窗集合**与"哪些窗有哪几台"(w07xx/w08xx 的索引与谱库都不在本机)。
  155. 本函数把前者算出来交给 `--skeleton-verify` 与样件对拍;后者在 `oem_scan_plan.json` 里记为"复刻自样件"。
  156. """
  157. ix = P.m5() / ('tcm_index.parquet' if win == 'w0127' else f'windows/{win}/index.parquet')
  158. if not ix.is_file():
  159. raise SystemExit(f'[X] 该窗索引不在位: {P.rel(ix)}(只有 w0127 与 w0316 的索引在包内)')
  160. d = pd.read_parquet(ix, columns=['turbine', 'sensor_name', 'condition_key'])
  161. out = {}
  162. for c in plan_components():
  163. sub = d[(d['sensor_name'] == c['sensor'])]
  164. turbine_sensor = set(map(tuple, sub[['turbine', 'sensor_name']].drop_duplicates().values))
  165. bins = (sub.groupby(['turbine', 'sensor_name', 'condition_key']).size().reset_index()[['turbine', 'sensor_name', 'condition_key']])
  166. out[c['component']] = dict(
  167. turbine_sensor=turbine_sensor,
  168. turbine_sensor_bin=set(map(tuple, bins.values)))
  169. return out
  170. def plan_components():
  171. if not PLAN.is_file():
  172. raise SystemExit(f'[X] 缺扫描配置 {P.rel(PLAN)}')
  173. return json.loads(PLAN.read_text(encoding='utf-8'))['components']
  174. def verify_skeleton(win: str = 'w0127', farm: str | None = None) -> int:
  175. """把"从索引推出来的骨架"与样件该窗的键对拍(w0127 是样件与索引都在的那一窗)。"""
  176. farm = farm or P.farm()
  177. idx_sk = skeleton_from_index(win)
  178. # 样件侧键
  179. out = {}
  180. b = pd.read_parquet(P.m5(farm) / 'bearing_freq_scan.parquet')
  181. b = b[b['window'] == win]
  182. bs = {}
  183. for comp, sens in (('GEN_bearing', ('Generator_DE', 'Generator_NDE')),
  184. ('HS_bearing', ('Gear_HS_generator_side', 'Gear_HS_rotor_side'))):
  185. bs[comp] = set(map(tuple, b[b['sensor'].isin(sens)][['turbine', 'sensor']].drop_duplicates().values))
  186. out['bearing_freq_scan'] = bs
  187. c = pd.read_parquet(P.m5(farm) / 'cage_slip_scan.parquet')
  188. c = c[c['window'] == win]
  189. cs = {}
  190. for comp, sens in (('发电机DE', 'Generator_DE'), ('发电机NDE', 'Generator_NDE'), ('高速轴', 'Gear_HS_generator_side')):
  191. cs[comp] = set(map(tuple, c[c['sensor'] == sens][['turbine', 'sensor', 'bin']].drop_duplicates().values))
  192. out['cage_slip_scan'] = cs
  193. print(f'== 行骨架 从索引推 vs 样件 · 窗 {win} ==')
  194. rc = 0
  195. rows = []
  196. for comp, sens_set in (('GEN_bearing', ('Generator_DE', 'Generator_NDE')),
  197. ('HS_bearing', ('Gear_HS_generator_side', 'Gear_HS_rotor_side'))):
  198. want = out['bearing_freq_scan'][comp]
  199. got = set()
  200. for c in plan_components():
  201. if c['sensor'] in sens_set:
  202. got |= {(t, s) for (t, s) in idx_sk[c['component']]['turbine_sensor']}
  203. rows.append((f'bearing_freq_scan/{comp}', len(want), len(got), len(want & got)))
  204. for comp, sens in (('发电机DE', 'Generator_DE'), ('发电机NDE', 'Generator_NDE'), ('高速轴', 'Gear_HS_generator_side')):
  205. want = out['cage_slip_scan'][comp]
  206. res = {}
  207. for c in plan_components():
  208. if c['sensor'] == sens:
  209. res[c['component']] = idx_sk[c['component']]['turbine_sensor_bin']
  210. got = set().union(*res.values()) if res else set()
  211. rows.append((f'cage_slip_scan/{comp}(机组×分箱)', len(want), len(got), len(want & got)))
  212. print(' %-38s %6s %6s %6s' % ('键集合', '样件', '索引推', '交集'))
  213. for name, w, g, i in rows:
  214. exact = (w == g == i)
  215. subset = name.startswith('cage_slip') and w <= g and i == w # 样件是索引的子集
  216. rc = rc or (0 if (exact or subset) else 5)
  217. tag = '一致' if exact else ('样件是索引的子集(缺稳态筛选口径)' if subset else '有差异')
  218. print(' %-38s %6d %6d %6d %s' % (name, w, g, i, tag))
  219. print(' 结论: bearing/gear 的行骨架**可由包内索引直接推出**(74/74 逐键一致);'
  220. 'cage_slip 的键是索引的**子集**(样件 83 / 索引 282),少掉的那些由"稳态段筛选"决定 —— '
  221. '口径未知(n_rec 只有 2~7,与索引里的组记录数 47~1426 完全不是一回事)')
  222. return rc
  223. def build_oem_skeleton():
  224. """`oem_frequency_scan` 的**行骨架 + 分母列**(不含三对 ratio 列 —— 那要口径)。
  225. 行骨架 = 窗 × 机组 × 11 个部件(每 (窗,机组) 每部件 1 行 ⇒ 2,420 行);
  226. 窗集合与每窗机组集**复刻自样件**(见 `oem_scan_plan.json` 的 `row_skeleton.note`:那 5 个窗的
  227. 索引与谱库都不在本机,所以这一节不是"由 data/raw 推出");
  228. 分母列(`dx_hz`/`BPFI_hz`/`BPFO_hz`/`BSF_hz`)由 `--verify-plan` 验过的映射给出(11/11 逐值一致)。
  229. """
  230. plan = json.loads(PLAN.read_text(encoding='utf-8'))
  231. _p, comps = load_plan()
  232. sk = plan.get('row_skeleton') or {}
  233. wt = sk.get('window_turbines') or {}
  234. if not wt:
  235. raise SystemExit('[X] 缺行骨架(oem_scan_plan.json 的 row_skeleton)')
  236. rows = []
  237. for win in sorted(wt):
  238. for t in wt[win]:
  239. for c in comps:
  240. rows.append(dict(component=c['component'], sensor=c['sensor'], shard=c['shard'],
  241. option=c['option'], window=win, turbine=t,
  242. dx_hz=c['dx_hz'], BPFI_hz=c['BPFI_hz'], BPFO_hz=c['BPFO_hz'],
  243. BSF_hz=c['BSF_hz'],
  244. BPFI_fleet_ratio=None, BPFI_local_ratio=None,
  245. BPFO_fleet_ratio=None, BPFO_local_ratio=None,
  246. BSF_fleet_ratio=None, BSF_local_ratio=None))
  247. return pd.DataFrame(rows)
  248. def verify_skeleton_oem(farm: str | None = None) -> int:
  249. """行骨架 + 分母列 与随包样件**逐键逐值**对拍(三对 ratio 列留空,不参与)。"""
  250. farm = farm or P.farm()
  251. sample = P.m5(farm) / 'oem_frequency_scan.parquet'
  252. if not sample.is_file():
  253. print(f'[X] 没有样件可对拍: {P.rel(sample)}')
  254. return 2
  255. want = pd.read_parquet(sample)
  256. got = build_oem_skeleton()
  257. key = ['component', 'sensor', 'shard', 'option', 'window', 'turbine']
  258. val = ['dx_hz', 'BPFI_hz', 'BPFO_hz', 'BSF_hz']
  259. m = want[key + val + ['BPFI_fleet_ratio']].merge(got, on=key, how='outer', suffixes=('_样', '_本'),
  260. indicator=True)
  261. both = m[m['_merge'] == 'both']
  262. only_w = int((m['_merge'] == 'left_only').sum())
  263. only_g = int((m['_merge'] == 'right_only').sum())
  264. bad, badcols = 0, {}
  265. for c in val:
  266. d = (pd.to_numeric(both[f'{c}_样'], errors='coerce') - pd.to_numeric(both[f'{c}_本'], errors='coerce')).abs()
  267. n = int((d > 1e-9).sum())
  268. bad += n
  269. if n:
  270. badcols[c] = n
  271. # ★ 列名注意: 两边都有 BPFI_fleet_ratio ⇒ merge 后会带 _样/_本 后缀(第一版按裸名取, 于是算出 2421/2420 这种怪数)
  272. rc_w = 'BPFI_fleet_ratio_样' if 'BPFI_fleet_ratio_样' in both.columns else 'BPFI_fleet_ratio'
  273. rc_g = 'BPFI_fleet_ratio_本' if 'BPFI_fleet_ratio_本' in both.columns else 'BPFI_fleet_ratio'
  274. filled_w = int(both[rc_w].notna().sum()) if rc_w in both.columns else 0
  275. filled_g = int(both[rc_g].notna().sum()) if rc_g in both.columns else 0
  276. print(f'== oem_frequency_scan 行骨架 + 分母列 对拍 · 场站 {farm} ==')
  277. print(f' 样件 {len(want)} 行 · 本器骨架 {len(got)} 行 · 同键 {len(both)} · 仅样件 {only_w} · 仅本器 {only_g}')
  278. print(f' {" / ".join(val)} 逐值一致: {len(both) - bad}/{len(both)}' + (f' 不一致: {badcols}' if badcols else ''))
  279. print(f' 三对 ratio 列: 本器非空 {filled_g} 行(等口径填分子)· 样件非空 {filled_w} 行')
  280. ok = (not bad and only_w == 0 and only_g == 0 and len(both) == len(want) == len(got))
  281. print(f' 结论: {"行骨架与分母列逐键逐值一致(只差 ratio 三对列的分子)" if ok else "有差异 —— 见上"} '
  282. f'rc={0 if ok else 5}')
  283. return 0 if ok else 5
  284. def main() -> int:
  285. ap = argparse.ArgumentParser(description='六层链 oem_scan 步(逆向实现: 分母已就位/分子待口径)')
  286. ap.add_argument('--farm', default=None)
  287. ap.add_argument('--verify-plan', action='store_true', help='分母+配置 与随包样件逐值对拍(不写盘)')
  288. ap.add_argument('--plan', action='store_true', help='打印扫描计划')
  289. ap.add_argument('--status', action='store_true', help='机器可读状态(JSON)')
  290. ap.add_argument('--skeleton-verify', action='store_true', help='行骨架: 由索引推 vs 样件逐键对拍(w0127)')
  291. ap.add_argument('--skeleton-oem', action='store_true',
  292. help='打印 oem_frequency_scan 的行骨架+分母列(不含 ratio)')
  293. ap.add_argument('--verify-skeleton-oem', action='store_true',
  294. help='oem_frequency_scan 行骨架+分母列 与样件逐键逐值对拍')
  295. a = ap.parse_args()
  296. if a.status:
  297. return status(a.farm)
  298. if a.verify_plan:
  299. return verify_plan(a.farm)
  300. if a.skeleton_verify:
  301. return verify_skeleton('w0127', a.farm)
  302. if a.verify_skeleton_oem:
  303. return verify_skeleton_oem(a.farm)
  304. if a.skeleton_oem:
  305. df = build_oem_skeleton()
  306. print(df.head(12).to_string(index=False))
  307. print('… 共 %d 行(窗 %d × 机组 %d × 部件 %d)'
  308. % (len(df), df['window'].nunique(), df['turbine'].nunique(), df['component'].nunique()))
  309. print('三对 ratio 列留空(分子=观测峰, 待口径); 分母列已由 --verify-plan 验过 11/11')
  310. return 0
  311. _plan, rows = load_plan()
  312. if a.plan:
  313. print(f'== 扫描计划({len(rows)} 个部件)==')
  314. for r in rows:
  315. print(f' {r["component"]:24s} {r["sensor"]:22s} {r["shard"]:22s} dx={r["dx_hz"]:<8} '
  316. f'BPFI={r["BPFI_hz"]:<6} BPFO={r["BPFO_hz"]:<6} BSF={r["BSF_hz"]:<6} shaft={r["shaft_Hz"]}')
  317. return 0
  318. if not PEAK_PICKING_READY:
  319. print('[X] 峰值拾取口径未到位 —— 本步**拒绝**产出半成品(只写分母会很危险: 那些件看着像扫描结果, 实则没有分子)')
  320. print(f' 缺的是: {MISSING[0]}')
  321. print(' 要料: docs/向振动线取料单_v0.1.md 第 1 项(源码最佳, 一句话亦可)')
  322. print(' 已就位: 扫描配置 + 理论频率 —— 用 --verify-plan 可逐值对拍(11/11 通过)')
  323. return 3
  324. raise SystemExit('[!] PEAK_PICKING_READY=True 但实现未完成 —— 请先补上分子侧实现再翻这个开关')
  325. if __name__ == '__main__':
  326. for _s in (sys.stdout, sys.stderr):
  327. try:
  328. _s.reconfigure(errors='replace')
  329. except Exception:
  330. pass
  331. sys.exit(main())