feat: blocks 命令 — 本地板块文件同步（行业/概念/指数/地区） - #40
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- 新模块 blocks.py：四条数据链解析（infoharbor_block.dat 概念/指数/风格、 tdxhy×tdxzs3 类别12 行业多级、spblock.dat 跨市场指数补充、base.dbf DY×tdxzs 地区） - infoharbor 截断板块名经 880 码还原 tdxzs 官方全名；空板块由 spblock 同名成分补齐（中证500/1000 等）；spblock 独有板块归为"特殊" - block_stock_relation 表：新增 block_type，唯一约束改 (block_type, block_name, code)（880 码可空 + 同名跨体系）；全量替换式快照写入 - cli：blocks 子命令 + sync 末尾自动执行；status 纳入板块表统计 - 迁移脚本 scripts/migrate_block_relation.sql（原表无写入路径，直接重建） - 测试 +7：四链解析逐字段断言（合成 GBK/DBF fixture）+ 快照替换语义 + 缺文件降级 - 真实数据验证：136,143 条入库；与导出 CSV 比对行业 127/127、地区 32/32、 概念 269/270（1 个为 tdxzs 官方全名变体）、指数 73+9 小众缺失（无本地源） Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- DELETE + INSERT 同一 engine.begin() 事务，任一批次失败不再留下 空表/半新半旧快照 - 新增回滚测试：坏数据写入失败后旧快照行数不变 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Summary
tdx2db sync自动同步板块-个股关系入库，替代"通达信手工导出 CSV → 导入"流程；板块新鲜度与行情同节奏。Related Issue
Closes #39
What Changed
infoharbor_block.dat（文本 GBK；截断名经 880 码还原 tdxzs 官方全名）tdxhy.cfgX 码 ×tdxzs3.cfg类别 12（881 研究行业，一/二/三级各一行）spblock.dat（中证500/1000/2000/A500、国证2000、深证成指等，infoharbor 空板块自动补齐；独有板块归"特殊"）base.dbfDY 字段（struct 手工解析 DBF，仅取 GPDM/DY）×tdxzs.cfg类别 3block_stock_relation：+block_type 列，唯一约束 (block_type, block_name, code)，全量替换式快照（板块关系无历史语义）；迁移脚本附blocks子命令（--csv-only/--db-only）+sync第 3 步自动执行；status纳入统计Why This Approach
Done Criteria Mapping（vs issue #39）
How to Test
pytest（62 passed）tdx2db --tdx-path <TDX> --db-type sqlite --db-name t blocks --db-only→ 实测入库 136,143 条（行业 467 / 概念 270 / 指数 115 / 地区 32 / 风格 157 / 特殊 23 个板块）tdx2db status应显示 block_stock_relation 行数Risks / Tradeoffs
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