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feat: 离线 fixture 测试、unknown 字段探测脚本、高可用传输层
- tests/fixtures/：录制 12 条命令真实响应 body（hex），配套 json 预期值 - tests/unit/test_commands_offline.py：13 个离线 pytest，无需网络，验证 各命令解析正确性及所有已知 bug 修复（#1~#5） - scripts/probe_unknowns.py：对比 unknown_1/2/3/5~8 与均价、涨停价等假设， 输出相关性分析报告，供后续字段逆向使用 - transport/sync.py：新增 ping_host()、ping_all()（并发测速）、KNOWN_HOSTS - client.py：TdxClient.from_best_host() 工厂方法（自动优选最低延迟服务器）、 TdxClient.ping_all() 静态代理、_execute() 断线自动重连（重试一次） - 修复 GetTransactionDataCmd.parse_response 多余 skip 参数调用 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
minionszyw
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
283682f6b4
commit
0fa685dbdd
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"""未知字段探测脚本：通过批量拉取多只股票数据，尝试推断各 unknown_N 字段的含义。
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用法：
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cd /home/m/xmtdx
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python3 scripts/probe_unknowns.py
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输出：
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1. MinuteBar.unknown_1 vs 分钟均价（累计成交额 / 累计成交量）
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2. SecurityQuote.unknown_2/3/5/6/7/8 与已知行情指标的相关关系
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"""
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from __future__ import annotations
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import sys
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import pathlib
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sys.path.insert(0, str(pathlib.Path(__file__).parent.parent / "src"))
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from xmtdx import TdxClient, Market, KlineCategory
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HOST = "180.153.18.170"
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# 沪深各取若干活跃股票
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SH_CODES = ["600000", "600036", "601318", "600519", "601628"]
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SZ_CODES = ["000001", "000002", "000858", "002415", "300750"]
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SEP = "-" * 72
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# ---------------------------------------------------------------------------
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# Part 1: MinuteBar.unknown_1 — 是否为分钟均价？
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# ---------------------------------------------------------------------------
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def probe_minute_unknown_1(c: TdxClient) -> None:
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print(SEP)
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print("Part 1: MinuteBar.unknown_1 vs 分钟均价 (历史某日)")
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print(SEP)
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# 使用历史分时，数据确定（不随时间变化）
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DATE = 20250108
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code, market = "600000", Market.SH
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bars = c.get_history_minute_time_data(market, code, DATE)
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print(f" {market.name} {code} 日期={DATE} 共 {len(bars)} 条分时\n")
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# 同时拉取当日日线 K 作为参考（含 amount/vol 可算均价）
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# 分时数据无直接成交额，需要用 price × vol 近似
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# 若 unknown_1 == round(price × 100) 则为原始价格单位均价
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print(f" {'分钟':>6} {'price':>8} {'vol':>8} {'unknown_1':>12} {'price*100':>10} {'diff':>8}")
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print(f" {'':-<6} {'':-<8} {'':-<8} {'':-<12} {'':-<10} {'':-<8}")
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exact_match = 0
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close_match = 0
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for i, b in enumerate(bars[:30]): # 只打印前30条
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price_x100 = round(b.price * 100)
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diff = b.unknown_1 - price_x100
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exact = b.unknown_1 == price_x100
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close = abs(diff) <= 2
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if exact:
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exact_match += 1
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if close:
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close_match += 1
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flag = " <<< exact" if exact else (" ≈" if close else "")
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print(f" {i+1:>6} {b.price:>8.2f} {b.vol:>8} {b.unknown_1:>12} {price_x100:>10} {diff:>+8}{flag}")
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# Count across all bars
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all_exact = sum(1 for b in bars if b.unknown_1 == round(b.price * 100))
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all_close = sum(1 for b in bars if abs(b.unknown_1 - round(b.price * 100)) <= 2)
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print(f"\n 全部 {len(bars)} 条：")
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print(f" unknown_1 == price*100 (精确): {all_exact}/{len(bars)} ({100*all_exact/len(bars):.1f}%)")
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print(f" unknown_1 ≈ price*100 (±2): {all_close}/{len(bars)} ({100*all_close/len(bars):.1f}%)")
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# Try another hypothesis: unknown_1 is a cumulative average price (均价)
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# Compute running avg: sum(price*vol)/sum(vol)
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print(f"\n 另一假设：unknown_1 = 当日累计均价×100")
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cum_pv = 0.0
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cum_v = 0
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correct_avg = 0
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for b in bars:
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cum_pv += b.price * b.vol
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cum_v += b.vol
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if cum_v > 0:
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avg = cum_pv / cum_v
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expected = round(avg * 100)
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if abs(b.unknown_1 - expected) <= 2:
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correct_avg += 1
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print(f" unknown_1 ≈ 累计均价×100 (±2): {correct_avg}/{len(bars)} ({100*correct_avg/len(bars):.1f}%)")
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# ---------------------------------------------------------------------------
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# Part 2: SecurityQuote.unknown_N fields
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# ---------------------------------------------------------------------------
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def probe_quote_unknowns(c: TdxClient) -> None:
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print(f"\n{SEP}")
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print("Part 2: SecurityQuote.unknown_2/3/5/6/7/8 — 与已知字段的关系")
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print(SEP)
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pairs = [(Market.SH, code) for code in SH_CODES] + [(Market.SZ, code) for code in SZ_CODES]
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quotes = c.get_security_quotes(pairs)
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print(f" {'market':>6} {'code':>8} {'pre_close':>10} {'price':>8} "
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f"{'u2':>6} {'u3':>8} {'u5':>6} {'u6':>6} {'u7':>6} {'u8':>6} {'rise_spd':>10}")
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print(f" {'':-<6} {'':-<8} {'':-<10} {'':-<8} "
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f"{'':-<6} {'':-<8} {'':-<6} {'':-<6} {'':-<6} {'':-<6} {'':-<10}")
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for q in quotes:
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pct = (q.price - q.pre_close) / q.pre_close * 100 if q.pre_close else 0
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print(
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f" {q.market.name:>6} {q.code:>8} {q.pre_close:>10.2f} {q.price:>8.2f} "
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f"{q.unknown_2:>6} {q.unknown_3:>8} {q.unknown_5:>6} "
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f"{q.unknown_6:>6} {q.unknown_7:>6} {q.unknown_8:>6} {q.rise_speed:>10.4f}"
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)
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print(f"\n 注：rise_speed = reversed_bytes9/100（已确认 = 涨速）")
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# Hypothesis: unknown_3 might relate to 涨停/跌停 price
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# 涨停 = pre_close * 1.10 (rounded to 2 decimal)
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print(f"\n 假设 unknown_3 = 涨停价×100：")
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print(f" {'code':>8} {'涨停价×100 预期':>16} {'unknown_3':>10} {'diff':>6}")
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for q in quotes:
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if q.pre_close > 0:
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limit_up = round(q.pre_close * 1.10 * 100)
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diff = q.unknown_3 - limit_up
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print(f" {q.code:>8} {limit_up:>16} {q.unknown_3:>10} {diff:>+6}")
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print(f"\n 假设 unknown_3 = 跌停价×100：")
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print(f" {'code':>8} {'跌停价×100 预期':>16} {'unknown_3':>10} {'diff':>6}")
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for q in quotes:
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if q.pre_close > 0:
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limit_dn = round(q.pre_close * 0.90 * 100)
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diff = q.unknown_3 - limit_dn
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print(f" {q.code:>8} {limit_dn:>16} {q.unknown_3:>10} {diff:>+6}")
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# unknown_2: often -1 or small value — check if it's 换手率×10000 or similar
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print(f"\n unknown_2 raw values: {[q.unknown_2 for q in quotes]}")
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print(f" unknown_5 raw values: {[q.unknown_5 for q in quotes]}")
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print(f" unknown_6 raw values: {[q.unknown_6 for q in quotes]}")
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print(f" unknown_7 raw values: {[q.unknown_7 for q in quotes]}")
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print(f" unknown_8 raw values: {[q.unknown_8 for q in quotes]}")
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# Print raw bytes for manual inspection
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print(f"\n 原始字节（前20字节 hex）：")
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for q in quotes:
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print(f" {q.code}: {q._raw[:20].hex()}")
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# ---------------------------------------------------------------------------
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# Part 3: TransactionRecord.unknown_last — 是否为秒数？
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# ---------------------------------------------------------------------------
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def probe_transaction_unknown_last(c: TdxClient) -> None:
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print(f"\n{SEP}")
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print("Part 3: TransactionRecord.unknown_last — 是否为秒或序号？")
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print(SEP)
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recs = c.get_history_transaction_data(Market.SH, "600000", 20250108, 0, 30)
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print(f" {'序号':>4} {'时间':>6} {'price':>8} {'vol':>6} {'buy':>4} {'unknown_last':>14}")
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print(f" {'':-<4} {'':-<6} {'':-<8} {'':-<6} {'':-<4} {'':-<14}")
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for i, r in enumerate(recs):
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print(f" {i+1:>4} {r.hour:02d}:{r.minute:02d} {r.price:>8.2f} {r.vol:>6} {r.buyorsell:>4} {r.unknown_last:>14}")
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unique = len({r.unknown_last for r in recs})
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print(f"\n unknown_last 唯一值数量: {unique}/{len(recs)}")
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print(f" 值分布: {sorted({r.unknown_last for r in recs})}")
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# ---------------------------------------------------------------------------
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# main
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# ---------------------------------------------------------------------------
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def main() -> None:
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print(f"连接 {HOST}:7709 ...")
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with TdxClient(HOST) as c:
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probe_minute_unknown_1(c)
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probe_quote_unknowns(c)
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probe_transaction_unknown_last(c)
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print(f"\n{SEP}")
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print("探测完成。根据以上输出可判断各字段含义，更新 models/ 文档注释。")
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if __name__ == "__main__":
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main()
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