From bfb8789ae8bf9ec6bdfc112ad48b8ce90b07b86f Mon Sep 17 00:00:00 2001 From: awayings Date: Tue, 8 Sep 2026 23:21:26 +0800 Subject: [PATCH 1/6] =?UTF-8?q?docs:=20README=20CLI=20=E7=AB=A0=E6=8C=89?= =?UTF-8?q?=E5=9F=9F=E6=8B=86=E8=87=B3=20docs/cli*.md=20+=20chanlun/data-l?= =?UTF-8?q?ocal=EF=BC=88=E5=90=AB=E5=8F=82=E6=95=B0=E8=A1=A8=E5=8E=BB?= =?UTF-8?q?=E9=87=8D=E5=90=88=E5=B9=B6=EF=BC=89?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - cli.md 命令总览（补 chanlun/zhuoyao/bias-signal 漏项）+ 按域导航 - cli-market / cli-finance / cli-indicators / cli-screen / cli-backtest 按域拆分 - cli-backtest 吸收 backtest_usage CLI 章的 backtest/optimize 参数表与 --indicators 说明 - chanlun.md（CLI+Python）、data-local.md（warehouse+offline）按主题合一 - 策略 demo 图复制至 docs/images/demo/，图片与内联链接路径改写为 docs 内相对路径 Co-Authored-By: Claude --- docs/chanlun.md | 148 ++++++++++++++++ docs/cli-backtest.md | 371 +++++++++++++++++++++++++++++++++++++++++ docs/cli-finance.md | 41 +++++ docs/cli-indicators.md | 127 ++++++++++++++ docs/cli-market.md | 95 +++++++++++ docs/cli-screen.md | 160 ++++++++++++++++++ docs/cli.md | 83 +++++++++ docs/data-local.md | 88 ++++++++++ docs/images/demo/1.png | Bin 0 -> 168546 bytes docs/images/demo/2.png | Bin 0 -> 147885 bytes docs/images/demo/3.png | Bin 0 -> 177862 bytes docs/images/demo/4.png | Bin 0 -> 189528 bytes 12 files changed, 1113 insertions(+) create mode 100644 docs/chanlun.md create mode 100644 docs/cli-backtest.md create mode 100644 docs/cli-finance.md create mode 100644 docs/cli-indicators.md create mode 100644 docs/cli-market.md create mode 100644 docs/cli-screen.md create mode 100644 docs/cli.md create mode 100644 docs/data-local.md create mode 100644 docs/images/demo/1.png create mode 100644 docs/images/demo/2.png create mode 100644 docs/images/demo/3.png create mode 100644 docs/images/demo/4.png diff --git a/docs/chanlun.md b/docs/chanlun.md new file mode 100644 index 0000000..6ee3af2 --- /dev/null +++ b/docs/chanlun.md @@ -0,0 +1,148 @@ +# 缠论分析 + +## CLI 用法 + +基于缠论理论的技术分析，计算管道：`K 线合并 → 分型识别 → 笔 → 中枢 → 线段 → 买卖点 → 背驰`。默认输出 JSON，加 `--table` 输出可读表格。：`K 线合并 → 分型识别 → 笔 → 中枢 → 线段 → 买卖点 → 背驰`。默认输出 JSON，加 `--table` 输出可读表格。 + +```bash +easy-tdx chanlun SZ 000001 --table +easy-tdx chanlun SH 600519 --adjust QFQ --table +easy-tdx chanlun SZ 000001 --period 30MIN + +# 多级别联立：分析日线最后一笔在 30 分钟级别中的走势结构 +easy-tdx chanlun SZ 000001 --multi-level 30MIN --table +easy-tdx chanlun SH 600519 --multi-level 5MIN +``` + +### 输出示例 + +以 `easy-tdx chanlun SH 601088 --table` 为例，输出分五个部分： + +**概要统计** + +``` +标的: 601088 周期: DAILY +原始K线: 800 缠论K线: 589 +分型: 275 笔: 131 中枢: 21 线段: 40 +买卖点: 125 背驰: 73 +``` + +| 字段 | 含义 | +|------|------| +| 原始 K 线 | 从服务端获取的原始 K 线条数 | +| 缠论 K 线 | 经过包含处理（合并）后的 K 线条数，数量一定 ≤ 原始 K 线 | +| 分型 | 识别出的顶分型 + 底分型总数 | +| 笔 | 相邻两个异向分型之间的连线（涨跌方向交替） | +| 中枢 | 至少 3 笔重叠区域形成的密集成交区间 | +| 线段 | 由笔构成的更大级别走势单位 | +| 买卖点 | 一二三类买卖点信号总数 | +| 背驰 | 力度衰减信号总数（笔背驰 / 盘整背驰 / 趋势背驰） | + +**笔** + +``` +[0] ↑ 2023-02-17 → 2023-02-23 h=28.46 l=26.76 ✓ +[1] ↓ 2023-02-23 → 2023-02-28 h=28.46 l=27.8 ✓ +[2] ↑ 2023-02-28 → 2023-03-09 h=29.77 l=27.8 ✓ +``` + +笔是缠论的基本走势单位。每条笔连接一个顶分型和一个底分型，方向严格交替（↑↓↑↓…）。`✓` 表示已确认（后续出现了反向笔），`…` 表示仍在进行中。 + +- `↑`：向上笔，起点是底分型（低点），终点是顶分型（高点） +- `↓`：向下笔，起点是顶分型（高点），终点是底分型（低点） +- `h`/`l`：该笔范围内的最高价 / 最低价 + +**中枢** + +``` +[0] zg=28.46 zd=28.11 gg=32.56 dd=26.76 lines=11 ✓ +[1] zg=31.2 zd=30.45 gg=32.56 dd=27.9 lines=3 ✓ +``` + +中枢是至少 3 笔重叠形成的密集成交区间，代表多空博弈的平衡区域。`✓` 表示已脱离，`…` 表示价格仍在中枢区间内震荡。 + +| 字段 | 含义 | +|------|------| +| `zg` | 中枢上沿（区间内最高的低点）— 支撑/压力的关键分界 | +| `zd` | 中枢下沿（区间内最低的高点） | +| `gg` | 中枢区间内的最高价 | +| `dd` | 中枢区间内的最低价 | +| `lines` | 构成该中枢的笔数，笔数越多代表震荡越充分 | + +中枢的意义：价格在中枢内震荡 → 突破中枢上沿看涨，跌破下沿看跌。`zg`/`zd` 是实战中最常用的参考价位。 + +**线段** + +``` +[0] ↑ 2023-02-17 → 2023-03-09 h=29.77 l=26.76 +[1] ↓ 2023-02-28 → 2023-03-29 h=29.77 l=27.18 +``` + +线段是比笔更大的走势单位，由多笔重叠组合而成。线段的方向不严格交替，可能出现连续同向（如连续多段向上），代表更高一级的趋势方向。实战中通常在线段级别判断大方向，在笔级别找买卖点。 + +**买卖点** + +``` +1buy: 中枢下方力度衰减，一类买点 (l=27.30 < zd=46.72) +2buy: 回调不创新低，二类买点 (l=27.33) +3buy: 回调不破中枢上沿，三类买点 (l=27.80 > zg=27.58) +1sell: 中枢上方力度衰减，一类卖点 (h=50.38 > zg=46.97) +2sell: 反弹不创新高，二类卖点 (h=29.32) +3sell: 反弹不破中枢下沿，三类卖点 (h=28.46 < zd=46.72) +``` + +缠论定义三类买点和三类卖点： + +| 类型 | 买点含义 | 卖点含义 | +|------|----------|----------| +| 一类 | 下跌趋势末端，力度衰减后的第一个低点（抄底） | 上涨趋势末端，力度衰减后的第一个高点（逃顶） | +| 二类 | 一类买点后的回调不创新低（确认反转） | 一类卖点后的反弹不创新高（确认反转） | +| 三类 | 回调不进入中枢上沿（趋势确认，中枢上方买） | 反弹不进入中枢下沿（趋势确认，中枢下方卖） | + +括号内的条件是该信号的触发依据，如 `l=27.80 > zg=27.58` 表示回调低点 27.80 高于中枢上沿 27.58，所以是三类买点。 + +**背驰** + +``` +[✓] bi: 笔背驰: 笔[4] 力度=1.32 < 笔[2] 力度=1.97 +[✓] pz: 盘整背驰: 中枢[11] 内末笔力度=2.49 < 首笔力度=6.64 +[✓] qs: 趋势背驰(上): 中枢[1] 离开力度=3.32 < 中枢[0] 离开力度=4.45 +``` + +背驰是力度衰减信号，表明当前走势动力正在减弱，可能即将反转。力度通过 MACD 面积计算，数值越小力度越弱。 + +| 类型 | 含义 | +|------|------| +| `bi`（笔背驰） | 同向相邻两笔比较，后一笔力度 < 前一笔 → 该方向动力减弱 | +| `pz`（盘整背驰） | 同一中枢内，末笔力度 < 首笔 → 中枢内动力衰减，即将突破 | +| `qs`（趋势背驰） | 两个同向中枢之间比较，后一中枢离开力度 < 前一中枢 → 趋势可能终结 | + +`[✓]` 表示确认背驰。趋势背驰(上)代表上涨趋势可能结束，趋势背驰(下)代表下跌趋势可能结束。 + + +## Python 用法 + +基于缠论理论的技术分析模块，接收 easy_tdx 的 K 线 DataFrame，输出笔、中枢、线段、买卖点、背驰等分析结果： + +```python +from easy_tdx.chanlun import ChanlunAnalyser, ChanlunConfig + +# 使用 easy_tdx 获取 K 线数据 +with TdxClient() as client: + df = client.get_security_bars(Market.SH, "600519", KlineCategory.DAY, 0, 800) + +# 缠论分析 +analyser = ChanlunAnalyser("SH600519", "DAILY") +result = analyser.process_klines(df) + +# 获取结果 +print(f"笔数: {len(result.bis)}") +print(f"中枢数: {len(result.zss)}") +print(f"线段数: {len(result.xds)}") +print(f"买卖点: {[m.msg for m in result.mmds]}") +print(f"背驰: {[b.msg for b in result.bcs]}") + +# JSON 兼容字典输出 +print(result.to_dict()) +``` + diff --git a/docs/cli-backtest.md b/docs/cli-backtest.md new file mode 100644 index 0000000..dac2e33 --- /dev/null +++ b/docs/cli-backtest.md @@ -0,0 +1,371 @@ +# CLI 参考 — 回测与寻优 + +## 回测引擎 + +> 📖 **完整使用手册**：[backtest_usage.md](./backtest_usage.md) —— +> 涵盖策略编写（`init()`/`next()`）、行情数据访问、指标注册、订单模拟、 +> 绩效指标、组合回测、调仓引擎与完整示例。回测相关用法以该手册为准。 + +内置向量回测引擎，加载 Python 策略文件即可跑回测。策略继承 `Strategy` 基类，在 `init()` 注册指标，在 `next()` 逐 bar 生成买卖信号，引擎完成订单模拟、持仓跟踪和绩效分析。 + +**单策略回测：** + +```bash +easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --count 2000 --cash 1000000 --adjust QFQ --table +# 推荐加上 --slippage 0.01 模拟真实滑点（元/股），使回测更贴近实盘 + +# 缠论自动桥接：引擎自动计算缠论分析并注入策略 self.chanlun +easy-tdx backtest SZ 000001 --strategy-file strategies/chanlun_strategy.py --chanlun-level DAILY --table + +# 预计算指标（MACD, KDJ 会作为额外列注入 DataFrame） +easy-tdx backtest SZ 000001 \ + --strategy-file strategies/macd_strategy.py \ + --indicators MACD,KDJ +``` + +`backtest` 命令 CLI 参数： + +| 参数 | 默认值 | 说明 | +|------|--------|------| +| `MARKET` | — | 市场代码：SZ / SH | +| `CODE` | — | 股票代码：如 000001 | +| `--strategy-file` | — | Python 策略文件路径 | +| `--cash` | 100000 | 初始资金 | +| `--commission` | 0.0003 | 佣金率 | +| `--execution` | next_open | 成交价规则 | +| `--period` | DAILY | K 线周期 | +| `--adjust` | NONE | 复权方式：NONE / QFQ / HFQ | +| `--count` | 500 | K 线数量 | +| `--indicators` | — | 预计算指标（逗号分隔） | +| `--table` | False | 表格输出 | +| `--output` | json | 输出格式：json / table / csv | +| `--wf` | False | 附加 Walk-Forward 样本外验证 | +| `--wf-windows` | 7 | Walk-Forward 窗口数 | +| `--evaluate` | False | 一条龙评估（回测+WF+适配性+评分+评级+基准对比） | +| `--auto-fees` | False | 按标的品种自动解析费率 | + +**样本外验证（v1.25）：** + +```bash +# 附加 Walk-Forward 七窗样本外验证（每窗独立开仓，窗口数可调） +easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --wf --wf-windows 7 + +# 一条龙评估：回测 + WF + 适配性体检 + 综合评分 + S-D 评级 + 买入持有基准对比 +easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --evaluate +``` + +输出示例： + +``` +=== 回测绩效概要 === +总收益率: 1413.51% +年化收益: 40.85% +最大回撤: 76.75% +夏普比率: 0.88 +胜率: 20.8% +交易次数: 24 +``` + +> ⚠️ **回测 ≠ 实盘**。以上收益率为历史数据回测结果，包含幸存者偏差和过拟合风险， +> 不构成投资建议。实际交易需考虑滑点、流动性、涨跌停无法成交等因素。 +> 请在充分理解策略逻辑后谨慎使用。 + +**参数网格寻优（optimize）与内置策略列表（strategies）：** + +```bash +# 列出全部内置策略（名称/参数默认值/预设寻优网格） +easy-tdx strategies + +# 单策略网格寻优（预设网格或 --param 自定义，--workers 4 进程并行） +easy-tdx optimize SZ 000001 --strategy ma_cross +easy-tdx optimize SZ 000001 --strategy ma_cross --param fast=5,10,15 --param slow=20,60 + +# 一键寻优所有内置策略：逐策略按预设网格寻优后全局排名（对应 Web UI /optimize 页） +easy-tdx optimize SZ 000001 --all --workers 4 --table + +# strategies 也支持 JSON 输出（含完整参数 schema，与 Web API GET /backtest/strategies 同构） +easy-tdx strategies --output json +``` + +`optimize` 参数： + +| 参数 | 默认值 | 说明 | +|------|--------|------| +| `--strategy` | — | 注册表策略名（与 `--all` 二选一） | +| `--all` | False | 一键寻优所有内置策略（STRATEGY_PRESETS 预设网格） | +| `--param` | 预设网格 | 自定义参数网格，如 `fast=5,10,15`（最多 2 个参数，笛卡尔积 ≤ 200） | +| `--cash` | 1000000 | 初始资金 | +| `--commission` | 0.0003 | 佣金率 | +| `--slippage` | 0.0 | 滑点 | +| `--workers` | 1 | 并行进程数（2+ 进程级并行；1 = 串行 + 指标缓存复用） | +| `--top` | 15 | 表格输出显示前 N 行 | + +Python API 同名能力：`easy_tdx.backtest.optimizer.ParamGridOptimizer`（单策略）与 +`easy_tdx.backtest.optimizer.optimize_all_strategies`（一键全策略）。 + +**全策略批量对比（CLI）：** + +`easy-tdx run-all` 一行命令跑完 `strategies/` 下所有策略并排名： + +```bash +easy-tdx run-all SZ 300308 --count 2000 --cash 1000000 --adjust QFQ + +# 多因子组合回测 +easy-tdx run-all SZ 300308 --combo 2 --combo-mode MAJORITY + +# 加 --show 自动弹出最佳策略的资金曲线 vs 股价对比图 +easy-tdx run-all SZ 300308 --count 2000 --cash 1000000 --adjust QFQ --show + +# 自定义策略目录 +easy-tdx run-all SZ 300308 --strategies-dir my_strategies/ +``` + +也可使用项目自带的 `run_all_strategies.py` 脚本（功能相同）： + +```bash +python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ + +# 加 --show 自动弹出最佳策略的资金曲线 vs 股价对比图 +python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ --show +``` + +**多因子组合回测：** + +自动遍历所有 2 因子 / 3 因子组合，找到最优搭配： + +```bash +# 自动寻找最佳 2 因子和 3 因子组合（MAJORITY 模式） +python -X utf8 run_all_strategies.py SZ 300308 --combo 2 --combo 3 --combo-mode majority + +# CLI 方式 +easy-tdx run-all SZ 300308 --combo 2 --combo 3 --combo-mode majority +``` + +CLI 指定策略文件组合： + +```bash +easy-tdx backtest SZ 000001 \ + --combo-strategies strategies/macd_cross.py,strategies/rsi_reversal.py,strategies/bollinger_breakout.py \ + --combo-mode majority --table +``` + +Python API： + +```python +from easy_tdx.backtest import CombinationRunner + +runner = CombinationRunner( + strategy_classes=[MACDStrategy, RSIStrategy, BollingerStrategy], + df=df, cash=100000, +) +results = runner.screen(combo_sizes=(2, 3), mode="MAJORITY") +for r in results[:5]: + print(f"{r.name}: 收益={r.result.performance['total_return']:.2%}") +``` + +信号合并模式： + +| 模式 | 买入条件 | 卖出条件 | 特点 | +|------|---------|---------|------| +| `AND` | 所有因子都看多 | 所有因子都看空 | 极保守，交易少但精确 | +| `MAJORITY` | 过半因子看多 | 过半因子看空 | 平衡，推荐默认 | +| `OR` | 任一因子看多 | 任一因子看空 | 激进，信号多噪声大 | + +`--show` 会用 matplotlib 弹出一个双轴对比窗口：左轴蓝色线是归一化股价，右轴红色线是最佳策略的资金曲线，绿三角=买入、黄三角=卖出，标题显示股票名称和关键绩效指标。需要 `pip install matplotlib`。 + +**多标的组合回测（portfolio）：** + +`easy-tdx portfolio` 对多只股票同时回测，共享资金池，按均等比例分配，汇总组合整体绩效： + +```bash +# 两只股票组合回测 +easy-tdx portfolio --stocks SZ:000001,SH:600519 --strategy-file strategies/ma_cross.py --table + +# 自定义资金和周期 +easy-tdx portfolio --stocks SZ:000001,SH:600519,SH:600036 \ + --strategy-file strategies/expma_cross.py --cash 500000 --period DAILY --count 1000 --table + +# 搭配缠论桥接 +easy-tdx portfolio --stocks SZ:000001,SH:600519 \ + --strategy-file strategies/chanlun_strategy.py --chanlun-level DAILY --table + +# 组合级 Walk-Forward / 一条龙评估（与 Web UI /portfolio 页同构） +easy-tdx portfolio --stocks SZ:000001,SH:600519 \ + --strategy-file strategies/ma_cross.py --wf --wf-windows 7 +easy-tdx portfolio --stocks SZ:000001,SH:600519 \ + --strategy-file strategies/ma_cross.py --evaluate +``` + +输出示例： + +``` +=== 组合回测绩效概要 === +标的数量: 3 +总资金: 200,000 +组合收益率: 28.50% +组合年化: 28.50% + +── 各标的详情 ── + SZ000001: 收益=35.20% 夏普=0.92 回撤=15.30% 分配=33% 交易=12 + SH600519: 收益=18.40% 夏普=0.68 回撤=8.50% 分配=33% 交易=8 + SH600036: 收益=31.90% 夏普=0.85 回撤=12.10% 分配=33% 交易=15 +``` + +| 参数 | 说明 | +|------|------| +| `--stocks` | 股票列表：逗号分隔的 `市场:代码`（如 `SZ:000001,SH:600519`） | +| `--cash` | 总资金（默认 20 万） | +| `--allocation` | 资金分配方式（目前支持 `equal` 均等分配） | +| `--chanlun-level` | 自动计算缠论分析并注入策略（如 DAILY/30MIN） | + + +## 批量运行全部策略（run-all） + + +``` +发现 9 个策略文件 +标的: SZ 300308 | K线: 2000 | 资金: 1,000,000 | 复权: QFQ +================================================================================ + +>> 运行策略: bias_reversal ... 完成 (2.4s) +>> 运行策略: bollinger_breakout ... 完成 (0.6s) +>> 运行策略: expma_cross ... 完成 (0.6s) +>> 运行策略: kdj_golden ... 完成 (0.1s) +>> 运行策略: ma_cross ... 完成 (1.4s) +>> 运行策略: macd_cross ... 完成 (2.1s) +>> 运行策略: rsi_reversal ... 完成 (0.2s) +>> 运行策略: turtle_breakout ... 完成 (0.1s) +>> 运行策略: volume_price ... 完成 (6.3s) + +================================================================================ +[*] 策略绩效排名 (按总收益率降序) +================================================================================ + 排名 策略 总收益率 年化收益 最大回撤 夏普 胜率 交易次数 盈亏比 +---------------------------------------------------------------------------------------------------- + *1* 1 expma_cross 1413.51% 40.85% 76.75% 0.88 20.8% 24 6.45 + *2* 2 ma_cross 1258.07% 38.94% 58.01% 0.87 38.2% 55 2.21 + *3* 3 turtle_breakout 905.07% 33.76% 48.30% 0.83 75.0% 4 10.14 + 4 bias_reversal 504.94% 25.47% 42.25% 0.70 66.3% 95 2.08 + 5 macd_cross 387.67% 22.11% 61.08% 0.60 40.0% 85 2.20 + 6 volume_price 247.72% 17.01% 65.73% 0.50 43.3% 254 1.40 + 7 bollinger_breakout 169.65% 13.32% 49.71% 0.44 66.7% 24 1.93 + 8 rsi_reversal 95.89% 8.85% 56.51% 0.33 57.1% 7 2.48 + 9 kdj_golden 89.10% 8.36% 61.86% 0.32 66.7% 3 10.49 +``` + +综合评分（夏普 × 0.4 + 收益/回撤 × 0.3 + 胜率 × 0.3）： + +``` + *1* 1 turtle_breakout 23.04 0.83 0.70 75.0% + *2* 2 bias_reversal 20.35 0.70 0.60 66.3% + *3* 3 bollinger_breakout 20.26 0.44 0.27 66.7% +``` + +换一个标的再跑： + +```bash +# 贵州茅台 +python -X utf8 run_all_strategies.py SH 600519 --count 2000 --cash 1000000 --adjust QFQ +``` + +### `--show` 可视化效果 + +

+
+ SH601088 中国神华 — bollinger_breakout 策略 | 收益 1281.8% +

+ +

+
+ SH600522 中天科技 — kdj_golden 策略 | 收益 568.6% +

+ +

+
+ SH601179 中国西电 — expma_cross 策略 | 收益 168.0% +

+ +

+
+ SH600519 贵州茅台 — bollinger_breakout 策略 | 收益 187.0% +

+ +> **⚠️ Demo 展示，不作为操作依据。** 历史回测收益不代表未来表现，策略参数未经过样本外验证。 + +### 自带策略示例 + +`strategies/` 目录下有 16 个开箱即用的策略文件，可直接用于 `--strategy-file`： + +| 文件 | 策略 | 类型 | 适合行情 | +|------|------|------|----------| +| `ma_cross.py` | 双均线交叉（MA5/MA20） | 趋势跟踪 | 单边趋势 | +| `expma_cross.py` | EMA12/EMA50 交叉 | 趋势跟踪 | 单边趋势（比 MA 更灵敏） | +| `macd_cross.py` | MACD 金叉死叉 | 趋势跟踪 | 中长线趋势 | +| `bollinger_breakout.py` | 布林带突破 | 震荡反转 | 横盘震荡 | +| `rsi_reversal.py` | RSI 超买超卖 | 反转 | 震荡市 | +| `kdj_golden.py` | KDJ 低位金叉/高位死叉 | 反转 | 短线震荡 | +| `turtle_breakout.py` | 海龟交易法（唐安奇通道） | 趋势突破 | 牛市启动 | +| `bias_reversal.py` | 乖离率反转 | 反转 | 震荡回归 | +| `volume_price.py` | 量价配合 | 综合判断 | 放量突破 | +| `zhuoyao_momentum.py` | 捉妖大师多周期共振 | 趋势跟踪 | 多周期共振强势股 | +| `dmi_trend.py` | DMI/ADX 趋势强度跟踪 | 趋势跟踪 | 单边趋势（过滤震荡） | +| `cci_breakout.py` | CCI ±100 区间突破 | 区间突破 | 震荡转趋势 | +| `mfi_volume.py` | MFI 量价反转 | 量价反转 | 震荡市（带量能确认） | +| `trix_cross.py` | TRIX 三重平滑趋势交叉 | 趋势跟踪 | 中长线（抗噪音） | +| `mtm_momentum.py` | MTM 动量零线穿越 | 动量 | 趋势拐点 | +| `obv_trend.py` | OBV 能量潮趋势 | 量价趋势 | 资金持续流入的上升趋势 | + +编写自定义策略只需继承 `Strategy` 基类： + +```python +from easy_tdx.backtest import Strategy +from easy_tdx import MyTT + + +class MyStrategy(Strategy): + def init(self): + self.ma = self.I(MyTT.MA, self.data.close, 10) + + def next(self): + if self.data.close[0] > self.ma[self._bar_index]: + self.buy(size=0) # size=0 表示全仓 + elif self.position["size"] > 0: + self.sell(size=0) # size=0 表示清仓 +``` + +完整 API 参考：[backtest_usage.md](./backtest_usage.md) +## 量化因子与组合管理 + +新增三大模块：**因子引擎**（19 个内置因子 + 自定义扩展）、**因子分析**（IC/分层/衰减）、**组合管理**（4 种优化器 + 再平衡引擎）。加上**高级回测增强**：可插拔滑点模型（方根冲击/成交量比例）、执行仿真（TWAP/VWAP/限价单）、归因分析（Brinson + 因子归因）。 + +```python +from easy_tdx.factor import FactorEngine, FactorAnalyzer, preprocess +from easy_tdx.portfolio import RebalanceEngine, FactorWeightedOptimizer +from easy_tdx.backtest import BacktestEngine +from easy_tdx.backtest.slippage import SquareRootSlippage +from easy_tdx.backtest.execution import TWAPExecution + +# 因子研究 +engine = FactorEngine() +factor_data = engine.compute_cross_section(data, ["momentum_20d", "rsi_14"]) +clean = preprocess(factor_data, ["momentum_20d", "rsi_14"]) +forward_returns = engine.compute_forward_returns(data, period=5) +report = FactorAnalyzer(clean, forward_returns).full_report("momentum_20d") +print(f"IC均值={report.mean_ic:.4f} ICIR={report.icir:.4f}") + +# 组合回测 +result = RebalanceEngine( + FactorWeightedOptimizer(), factor_name="momentum_20d", n_stocks=50, cash=1_000_000, +).run(data, start_date=20230101, end_date=20240101) +print(f"年化={result.performance['annual_return']:.2%}") + +# 高级回测（滑点 + 执行仿真） +engine = BacktestEngine( + MyStrategy, cash=1_000_000, + slippage_model=SquareRootSlippage(impact_coeff=0.1), + execution_model=TWAPExecution(n_bars=3), +) +``` + +详细用法和完整工作流示例：**[quantitative-guide.md](./quantitative-guide.md)** + diff --git a/docs/cli-finance.md b/docs/cli-finance.md new file mode 100644 index 0000000..4758664 --- /dev/null +++ b/docs/cli-finance.md @@ -0,0 +1,41 @@ +# CLI 参考 — 财务与公告 + +## 公告检索（巨潮资讯网） + +```bash +easy-tdx announcement 688017 # 默认 30 条，JSON 输出 +easy-tdx announcement 601088 --count 10 --page 2 # 翻页 +easy-tdx announcement 000001 --table # 表格输出（不截断 url） + +# 下载最新 5 条公告的 PDF 到 ./pdfs 目录 +easy-tdx announcement 601088 --count 5 --download 5 --download-dir ./pdfs +``` + +> 独立数据源（巨潮资讯网），无需连接 TDX 行情服务器即可使用。 +> 返回的 ``url`` 含 4 参数可直接打开，``pdf_url`` 为 PDF 直链。 + +## 财务 + +```bash +easy-tdx f10 600519 # 茅台利润表，最近 8 期（默认 lrb） +easy-tdx f10 600519 --type fzb --num 4 # 资产负债表，最近 4 期 +easy-tdx f10 000001 --type llb --table # 平安现金流量表，表格输出 +``` + +> 新浪财经数据源，``--type`` 支持 ``lrb``（利润表）/``fzb``（资产负债表）/``llb``（现金流量表）。 +> 独立于 TDX 行情服务器，``item_value`` 已转 float 可直接数值计算，同比附 ``{科目}_同比`` 列。 + +## 通达信原生 F10 与最新财务快照 + +走通达信协议（与 Web 层 ``/finance`` ``/company/*`` 端点同源），覆盖 ``f10``（新浪三表）之外的 F10 全文板块。完整示例见 [examples/06_finance/](../examples/06_finance/README.md)。 + +```bash +easy-tdx finance-info SH 600519 --table # 最新财务快照（30+ 项单期指标） +easy-tdx company-info SH 600519 # F10 板块目录（最新提示/公司概况/...） +easy-tdx company-info SH 600519 "公司概况" # 读板块完整正文（自动解析+读全，无需 offset/length） +easy-tdx company-info SH 600519 600519.txt # 也可直接传文件名（此时用 --offset/--length） +``` + +- ``finance-info``：最新一期财务快照，含股本结构、资产负债、利润、现金流、每股指标（37 字段）。与 ``f10`` 互补——前者是单期快照，后者是多期三表。 +- ``company-info``：**一个命令两种用法**——无板块名参数列 F10 板块目录，有板块名参数读正文。目录含 16 个板块（最新提示、公司概况、财务分析、股东研究、股本结构、资本运作、业内点评、行业分析、公司大事、研究报告、经营分析、主力追踪、分红扩股、高层治理、龙虎榜单、关联个股）。 +- 读正文时传板块名即可自动读取完整内容（按目录 length 分块循环，大板块如「公司大事」也能一次读全）；``--offset``/``--length`` 仅在传文件名时生效。通达信多服务器目录版本不一致时自动重试命中。 diff --git a/docs/cli-indicators.md b/docs/cli-indicators.md new file mode 100644 index 0000000..b9e4390 --- /dev/null +++ b/docs/cli-indicators.md @@ -0,0 +1,127 @@ +# CLI 参考 — 技术指标与公式 + +## 技术指标 + +```bash +easy-tdx indicator-list --table # 列出所有可用指标 +easy-tdx indicator MACD -m SH -c 600519 --table # MACD +easy-tdx indicator KDJ -m SZ -c 000001 --table # KDJ +easy-tdx indicator RSI -m SH -c 600519 --table # RSI +easy-tdx indicator BOLL -m SH -c 600519 --table # BOLL 布林带 +easy-tdx indicator DMI -m SH -c 600519 --table # DMI 动向指标 +easy-tdx indicator ATR -m SH -c 600519 --table # ATR 真实波幅 +easy-tdx indicator WR -m SH -c 600519 --table # WR 威廉指标 +easy-tdx indicator CCI -m SH -c 600519 --table # CCI 顺势指标 +easy-tdx indicator BIAS -m SZ -c 000001 --table # BIAS 乖离率 +easy-tdx indicator BIAS_SIGNAL -m SH -c 600519 --table # 30日乖离率信号 +easy-tdx indicator OBV -m SZ -c 000001 --table # OBV 能量潮 + +# 多指标同时计算 +easy-tdx indicator MACD,KDJ,RSI,BOLL -m SH -c 600519 --count 10 --table + +# 自定义参数 +easy-tdx indicator MACD -m SH -c 600519 --params SHORT=10,LONG=22 + +# 分钟线指标 +easy-tdx indicator MACD -m SH -c 600519 --period 5MIN --count 50 + +# 仅输出指标值（不含 OHLCV） +easy-tdx indicator RSI -m SZ -c 000001 --no-ohlcv +``` + +## 通达信公式（v1.27） + +粘贴通达信公式即可计算 / 选股 / 回测——命名布尔输出自动成为买卖信号（名字含「买/卖」或 BUY/SELL 优先），30+ 白名单函数（MA/EMA/SMA/HHV/LLV/REF/CROSS/LONGCROSS/MACD/KDJ/RSI/BOLL/ATR…）向量化求值，无未来数据： + +```bash +# 公式计算（最后一根各列值 + 最近信号明细） +easy-tdx formula compute SH 600519 --formula "金叉: CROSS(MA(C,5), MA(C,20));" + +# 批量选股：信号在最后一根 = 1 的标的（--symbols 支持逗号分隔或 @文件） +easy-tdx formula screen --symbols SH:600519,SZ:000001 --formula "金叉: CROSS(MA(C,5), MA(C,20));" + +# 公式回测：买/卖列自动挑选，信号下一根开盘成交，输出绩效 + 评级 + 评分 +easy-tdx formula backtest SH 600519 --file my_formula.txt +``` + +## 捉妖大师（重点） + +捉妖大师是多周期涨幅共振指标，通过 20/60/120 日涨幅及指数平滑判断短中长线趋势是否同向，用于筛选趋势刚启动的强势股。 + +```bash +easy-tdx indicator ZHUOYAO -m SH -c 600519 --count 30 --table + +# 自定义周期参数 +easy-tdx indicator ZHUOYAO -m SZ -c 000001 --params N1=90,N2=45,N3=15 + +# 结合其他指标一起看 +easy-tdx indicator ZHUOYAO,MACD,KDJ -m SH -c 600519 --count 20 --table +``` + +输出列说明： + +| 列名 | 含义 | +|------|------| +| `ZY_LONG` | 长线 — 120 日涨幅的 10 日指数平滑 | +| `ZY_MID` | 中线 — 60 日涨幅(%) | +| `ZY_SHORT` | 短线 — 20 日涨幅(%) | +| `ZY_TREND` | 趋势 — 中线的 10 日指数平滑 | + +**核心信号：** 四线全部 > 0 且短线 > 中线 > 长线 = 短中长趋势完全一致向上，是强势股特征。详见 [捉妖大师指标详解](./indicator-zhuoyao.md)。 + +## 30日乖离率信号（重点） + +30日乖离率信号指标，在标准乖离率（BIAS）基础上叠加短/长信号线，通过三者位置关系判断趋势方向和转折点。源自通达信经典指标。 + +```bash +easy-tdx indicator BIAS_SIGNAL -m SH -c 600519 --count 60 --table + +# 自定义周期参数 +easy-tdx indicator BIAS_SIGNAL -m SZ -c 000001 --params P=5,M=20 + +# 结合其他指标一起看 +easy-tdx indicator BIAS_SIGNAL,MACD,KDJ -m SH -c 600519 --count 30 --table +``` + +输出列说明： + +| 列名 | 含义 | +|------|------| +| `BS_X` | M日乖离率 — 当前价格偏离30日均线的百分比 | +| `BS_SMA` | 短周期信号线 — 乖离率的 P 日均线，过滤短期噪音 | +| `BS_LMA` | 长周期信号线 — 乖离率的 M 日均线，捕捉中期趋势方向 | + +**核心信号：** X > S_SMA 且 X_LMA 上升 = 多头确认（通达信红色）；S_SMA > X 或 X_LMA 下降 = 空头预警（通达信绿色）。多空判断非对称设计——多头需两个条件同时满足，空头只需其一，偏向保守预警。详见 [30日乖离率信号指标详解](./indicator-bias-signal.md)。 + +```python +# Python API 用法 +from easy_tdx import MacClient, Market + +with MacClient.from_best_host() as c: + df = c.get_stock_kline_with_indicators( + Market.SH, "600519", + indicators=["BIAS_SIGNAL"], + count=60, + ) + # df 包含: datetime, open, close, high, low, vol, amount + # + BS_X, BS_SMA, BS_LMA +``` + +支持 34 个指标：MACD, KDJ, RSI, BOLL, DMI, ATR, WR, CCI, BIAS, BIAS_SIGNAL, OBV, VR, EMV, MFI, BRAR, ASI, TRIX, DPO, MTM, ROC, EXPMA, BBI, PSY, DFMA, CR, KTN, XSII, MASS, TAQ, ZHUOYAO, SAR, VWAP, AROON, FK。 + +```python +# Python API 用法 +from easy_tdx import MacClient, Market + +with MacClient.from_best_host() as c: + df = c.get_stock_kline_with_indicators( + Market.SH, "600519", + indicators=["ZHUOYAO"], + count=30, + ) + # df 包含: datetime, open, close, high, low, vol, amount + # + ZY_LONG, ZY_MID, ZY_SHORT, ZY_TREND +``` + +支持 34 个指标：MACD, KDJ, RSI, BOLL, DMI, ATR, WR, CCI, BIAS, BIAS_SIGNAL, OBV, VR, EMV, MFI, BRAR, ASI, TRIX, DPO, MTM, ROC, EXPMA, BBI, PSY, DFMA, CR, KTN, XSII, MASS, TAQ, ZHUOYAO, SAR, VWAP, AROON, FK。 + diff --git a/docs/cli-market.md b/docs/cli-market.md new file mode 100644 index 0000000..6d8372a --- /dev/null +++ b/docs/cli-market.md @@ -0,0 +1,95 @@ +# CLI 参考 — 行情数据 + +## 输出格式 + +`easy-tdx` 默认输出 JSON（一行一条记录），`--table` 切换表格，`--output csv` 输出 CSV。 + +## 基础 + +```bash +easy-tdx ping # 服务器测速 +easy-tdx version # 版本号 +``` + +## 行情 + +```bash +# K 线 +easy-tdx kline SZ 000001 --count 30 --table +easy-tdx kline SH 600519 --period 5MIN --adjust QFQ + +# 实时报价 +easy-tdx quote "SZ 000001,SH 600519" --table + +# 市场分类报价（按涨幅排序） +easy-tdx quote-list A --count 20 --table +easy-tdx quote-list KCB --sort TOTAL_AMOUNT --order ASC +easy-tdx quote-list CYB --count 50 +``` + +## 分时 / 成交 + +```bash +easy-tdx tick SZ 000001 --table +easy-tdx tick SH 600519 --days 5 +easy-tdx tick SZ 000001 --date 20250115 + +easy-tdx transaction SZ 000001 --count 100 --table +easy-tdx transaction SH 600519 --date 20250115 +``` + +## 板块 + +```bash +easy-tdx board-list --type GN --table +easy-tdx board-list --type HY --count 200 +easy-tdx board-members 881001 --table +easy-tdx belong-board SZ 000001 --table +easy-tdx board-summary 881001 --table # 板块汇总（成交额/主力净流入/涨跌家数） +easy-tdx board-summary 881001 --members --table # 含成分股明细 +easy-tdx board-ranking --type HY --top 10 --table # 行业板块排行 +easy-tdx board-ranking --type GN --sort-by amount # 概念板块按成交额排行 + +# 板块 N 日涨跌幅排行（默认全部，支持指定日期） +easy-tdx board-change-ranking --table # 行业 20 日涨跌幅排行 +easy-tdx board-change-ranking --type GN --days 10 --table # 概念 10 日涨跌幅排行 +easy-tdx board-change-ranking --type HY --date 20250530 --days 20 --table +easy-tdx board-change-ranking --type HY --top 10 --asc # 行业跌幅前10 +``` + +## 资金 / 监控 + +```bash +easy-tdx capital-flow SH 600519 --table +easy-tdx auction SZ 000001 --table +easy-tdx unusual SH --count 100 --table +easy-tdx market-stat --table +easy-tdx server-info --table +easy-tdx symbol-info SZ 000001 --table +``` + +## 中金所成交持仓排名（v1.29.1） + +```bash +easy-tdx ccpm IF --table # 最近有数据的交易日（缺省自动回溯） +easy-tdx ccpm IF --date 2026-09-02 # 指定交易日 +easy-tdx ccpm all --date 2026-08-28 --table # 全部 8 个品种一次抓取 +easy-tdx ccpm TL --refresh # 忽略本地缓存，强制重新抓取 +``` + +> 独立数据源（中金所官网），无需连接 TDX 行情服务器。品种：IF 沪深300 / IH 上证50 / IC 中证500 / IM 中证1000 股指期货，TS/TF/T/TL 为 2/5/10/30 年期国债期货。 +> 每个交易日收盘后约 16:15 发布，含该品种**全部合约 × 三类排名（成交量 / 持买单量·多单 / 持卖单量·空单）× 各前 20 名会员**； +> 数据发布后不可变，按日缓存到 `~/.easy_tdx/cache/ccpm/`，历史二次查询零网络。 +> JSON 输出为英文列名（vol/long_pos/short_pos 等，机器友好），`--table` 自动切换中文表头。 +> WebUI 对应「期货持仓排名」页（含新手科普），API 为 `GET /api/v1/ccpm/rank`。 + +## 扩展市场（港股/美股/期货） + +```bash +easy-tdx ex markets # 列出可用市场 +easy-tdx ex kline HK_MAIN_BOARD 00700 --count 30 --table # 港股 K 线 +easy-tdx ex kline US_STOCK AAPL --table # 美股 K 线 +easy-tdx ex quote US_STOCK TSLA --table # 美股报价 +easy-tdx ex quote-list HK_MAIN_BOARD --table # 港股商品列表 +easy-tdx ex tick HK_MAIN_BOARD 00700 --table # 港股分时 +``` diff --git a/docs/cli-screen.md b/docs/cli-screen.md new file mode 100644 index 0000000..0c54d0d --- /dev/null +++ b/docs/cli-screen.md @@ -0,0 +1,160 @@ +# CLI 参考 — 策略选股扫描 + +## 策略选股扫描（screen） + +把策略翻转成选股器：给定一个策略，扫描全市场找出今天触发买入信号的股票，再对这些信号做历史回测排名。**纯离线数据**，读取本地通达信 `.day` 文件，全市场约 30-60 秒。 + +两步走工作流： + +**第一步：信号扫描（scan）** + +```bash +# 扫描沪深全 A，找出 RSI 超卖触发的股票 +easy-tdx screen scan --strategy strategies/rsi_reversal.py --output signals.json + +# 缩小范围 +easy-tdx screen scan --strategy strategies/macd_cross.py --universe sz --output signals.json + +# 从自定义股票列表扫描 +easy-tdx screen scan --strategy strategies/bollinger_breakout.py --universe my_stocks.txt --output signals.json + +# 并发扫描（推荐 4-8 进程，速度提升 4-8 倍） +easy-tdx screen scan --strategy strategies/rsi_reversal.py --workers 4 --output signals.json + +# 增量扫描（缓存未修改的 .day 文件，跳过重复计算） +easy-tdx screen scan --strategy strategies/rsi_reversal.py --cache scan_cache.json --output signals.json +``` + +输出示例（JSON）： + +```json +{ + "scan_time": "2026-06-10T18:30:00", + "strategy": "RSIStrategy", + "total_scanned": 4832, + "total_signals": 37, + "signals": [ + {"code": "000001", "market": "SZ", "signal_date": 20260610, "last_close": 12.35}, + {"code": "600519", "market": "SH", "signal_date": 20260610, "last_close": 1800.0} + ] +} +``` + +**第二步：回测排名（rank）** + +```bash +# 按夏普比率排名（默认） +easy-tdx screen rank --from signals.json --sort sharpe --top 20 --table + +# 按最大回撤排名（越小越好，用 --sort-reverse） +easy-tdx screen rank --from signals.json --sort max_drawdown --sort-reverse --table + +# 管道模式：一步到位 +easy-tdx screen scan --strategy strategies/rsi_reversal.py | easy-tdx screen rank --from - --table + +# 补齐股票名称（需要网络） +easy-tdx screen rank --from signals.json --sort sharpe --top 10 --table --names +``` + +输出示例（`--table`）： + +``` +[*] 信号排名 (按 sharpe 降序, 共 37 只) +══════════════════════════════════════════════════════════════════════════ +排名 代码 名称 总收益率 年化收益 最大回撤 夏普 胜率 交易 + *1 SZ300308 中际旭创 45.23% 18.72% 12.35% 1.85 62.5% 16 + *2 SH600519 贵州茅台 38.10% 15.90% 8.21% 1.62 58.3% 12 +``` + +| 参数 | 说明 | +|------|------| +| `--universe` | `all`（默认，沪深全 A）/ `sh` / `sz` / 文件路径（每行 "市场 代码"） | +| `--vipdoc` | 离线数据目录（默认自动检测通达信安装路径） | +| `--workers` | 并发进程数：`0` 串行（默认）/ `2+` ProcessPoolExecutor 并发（推荐 4-8） | +| `--cache` | 增量扫描缓存文件路径（JSON，mtime 未变的文件自动跳过） | +| `--sort` | 排序指标：`sharpe`（默认）/ `total_return` / `max_drawdown` / `win_rate` 等 | +| `--sort-reverse` | 升序（用于回撤等越小越好的指标） | +| `--names` | 在线补齐股票名称（默认关闭，只查排名中的几十只） | +| `--count` | rank 使用最近 N 条 K 线（0=全部，默认 0） | + +### 强势股排名（strength） + +按 **5 / 20 / 60 日涨幅加权**合成强势分，从全市场选出"最近最强"的股票。**纯离线数据**，读取本地通达信 `.day` 文件，全市场约 30-60 秒（并发可压到 10 秒内）。 + +**三种预设模式：** + +| 模式 | 性格 | 权重 (w5/w20/w60) | 波动率惩罚 | 适合 | +|------|------|-------------------|-----------|------| +| `steady`（默认） | 中长期稳健 | 0.2 / 0.3 / 0.5 | ✅ 除以 vol_20 | 选"稳着涨"的票，妖股被高波动压低 | +| `breakout` | 近期妖股爆发 | 0.6 / 0.3 / 0.1 | ❌ 纯加权涨幅 | 选"短期最猛"的票，妖股本身就是高波动 | +| `balanced` | 三周期均衡 | 等权 + vol 调整 | ✅ 除以 vol_20 | 不确定时的安全默认 | + +> 💡 **为什么 breakout 不除波动率？** 妖股本质高波动，除以 vol 会把它压下去，与"找妖股"目标矛盾。steady 除以 vol 是为了奖励"稳着涨"的票（vol 小，score 放大）。 + +```bash +# 中长期稳健强势 Top 50（默认 steady 模式） +easy-tdx screen strength --preset steady --top 50 --table + +# 近期妖股爆发 Top 20（补齐股票名称） +easy-tdx screen strength --preset breakout --top 20 --names --table + +# 三周期均衡 +easy-tdx screen strength --preset balanced --top 30 --table + +# 自定义权重（自动归一化，5:3:2 = 0.5:0.3:0.2） +easy-tdx screen strength --w5 0.5 --w20 0.3 --w60 0.2 --top 30 --table + +# 并发扫描（推荐 4-8 进程） +easy-tdx screen strength --preset steady --top 100 --workers 4 --table + +# 过滤低流动性（最近 5 日日均成交额 ≥ 5000 万） +easy-tdx screen strength --preset breakout --top 30 --min-amount 50000000 --table + +# 缩小范围 + 输出到文件 +easy-tdx screen strength --universe sz --top 30 --output sz_strength.json +``` + +输出示例（`--table`）： + +``` +[*] 强势股排名 [steady] 共 50 只 + 数据截止: 2026-06-24 | 中长期稳健强势：权重偏 60 日，波动率惩罚，选出稳着涨的票 +════════════════════════════════════════════════════════════════════════════════ +排名 代码 名称 现价 5日 20日 60日 波动率 强势分 + *1 SZ300308 中际旭创 85.20 8.12% 15.34% 30.21% 0.0180 9.52 + *2 SH600519 贵州茅台 1800.00 3.25% 5.10% 10.05% 0.0120 6.21 +``` + +输出示例（JSON）： + +```json +{ + "scan_time": "2026-06-25T10:30:00", + "preset": "steady", + "preset_desc": "中长期稳健强势：权重偏 60 日，波动率惩罚...", + "data_date": 20260624, + "total_ranked": 50, + "ranking": [ + {"rank": 1, "code": "300308", "market": "SZ", "name": "中际旭创", + "last_close": 85.20, "last_date": 20260624, + "ret_5": 0.0812, "ret_20": 0.1534, "ret_60": 0.3021, + "vol_20": 0.0180, "strength": 9.52} + ] +} +``` + +| 参数 | 说明 | +|------|------| +| `--preset` | 预设模式：`steady`（默认）/ `breakout` / `balanced` | +| `--w5` `--w20` `--w60` | 自定义三周期权重（覆盖预设，自动归一化） | +| `--vol-adjusted` / `--no-vol-adjusted` | 波动率惩罚开关（覆盖预设） | +| `--top` | 返回前 N 名（默认 50） | +| `--universe` | `all`（默认）/ `sh` / `sz` / 文件路径 | +| `--min-listed-days` | 最小上市天数（默认 65，保证能算 60 日涨幅） | +| `--min-amount` | 最近 5 日日均成交额下限（元，默认 0 不过滤） | +| `--workers` | 并发进程数：`0` 串行 / `4+` 并发（推荐 4-8） | +| `--names` | 在线补齐股票名称（默认关闭） | +| `--output` | 输出 JSON 文件（默认 stdout） | + +> ⚠️ **数据时效**：strength 依赖本地 `.day` 文件。输出中的 `data_date` / `last_date` 字段标注数据截止日，请先用 `easy-tdx offline sync` 同步最新数据。 + diff --git a/docs/cli.md b/docs/cli.md new file mode 100644 index 0000000..0d55d23 --- /dev/null +++ b/docs/cli.md @@ -0,0 +1,83 @@ +# CLI 命令总览 + +`easy-tdx` 全部命令速查表。按域的详细用法与示例见分域文档： + +| 域 | 文档 | +|------|------| +| 行情 / 分时 / 板块 / 资金 / 中金所 / 扩展市场 | [cli-market.md](./cli-market.md) | +| 公告 / 财务 / F10 | [cli-finance.md](./cli-finance.md) | +| 技术指标 / 通达信公式 | [cli-indicators.md](./cli-indicators.md) | +| 缠论分析 | [chanlun.md](./chanlun.md) | +| 回测 / 寻优 / 组合 / run-all | [cli-backtest.md](./cli-backtest.md) | +| 选股扫描 / 强势股排名 | [cli-screen.md](./cli-screen.md) | +| K 线仓库 / 离线数据 | [data-local.md](./data-local.md) | +| Web 服务（serve） | [web-api.md](./web-api.md) | + +## 命令汇总 + +| 命令 | 说明 | +|------|------| +| `ping` | 服务器延迟测速 | +| `version` | 版本号 | +| `kline` | K 线（日/周/月/分钟，支持复权） | +| `quote` | 实时报价（单只/批量） | +| `quote-list` | 市场分类排序报价（A/SH/SZ/KCB/CYB） | +| `tick` | 分时图（单日/多日/历史） | +| `transaction` | 逐笔成交 | +| `board-list` | 板块列表（行业/概念/风格） | +| `board-members` | 板块成分股报价 | +| `board-summary` | 板块汇总（成交额、主力净流入、涨跌家数） | +| `board-ranking` | 板块涨跌幅排行榜（行业/概念排行） | +| `board-change-ranking` | 板块 N 日涨跌幅排行（支持指定截止日期） | +| `belong-board` | 个股所属板块 | +| `capital-flow` | 资金流向 | +| `auction` | 集合竞价 | +| `unusual` | 市场异动 | +| `market-stat` | 全市场涨跌统计 | +| `server-info` | 服务器交易时段 | +| `symbol-info` | 个股特征快照 | +| `indicator` | 技术指标计算（34 个：MACD/KDJ/RSI/BOLL/DMI/ATR...） | +| `indicator-list` | 列出可用技术指标 | +| `chanlun` | 缠论分析（笔/中枢/线段/买卖点/背驰，支持多级别联立） | +| `indicator ZHUOYAO` | 捉妖大师信号（多周期 ROC 共振），详解见 [indicator-zhuoyao.md](./indicator-zhuoyao.md) | +| `indicator BIAS_SIGNAL` | 30 日乖离率信号，详解见 [indicator-bias-signal.md](./indicator-bias-signal.md) | +| `backtest` | 回测引擎（加载策略文件，输出绩效报告） | +| `portfolio` | 多标的组合回测（共享资金池，均等分配，汇总绩效） | +| `factor list` | 列出所有内置因子 | +| `factor analyze` | 因子分析（IC/分层/衰减） | +| `pfactor backtest` | 组合因子选股回测 | +| `run-all` | 批量运行所有策略并排名（绩效排名 + 综合评分 + 可选图表） | +| `optimize` | 参数网格寻优（单策略网格搜索，或 `--all` 一键寻优所有内置策略并排名） | +| `strategies` | 列出内置策略注册表（名称/中文标签/参数默认值/预设寻优网格） | +| `formula compute` | 通达信公式计算（命名布尔输出即买卖信号） | +| `formula screen` | 公式批量选股（信号在最后一根 = 1 的标的） | +| `formula backtest` | 公式回测（买/卖列自动挑选，输出绩效 + 评级 + 评分） | +| `warehouse sync` | 本地 K 线仓库增量同步（DuckDB，需 `easy-tdx[warehouse]`） | +| `warehouse query` | 仓库查询（默认忽略未收盘的临时 bar） | +| `warehouse stats` | 仓库统计（各标的行数/数据范围） | +| `warehouse check` | 仓库健康自检（缺口/除权跳变/新鲜度） | +| `ccpm` | 中金所成交持仓排名（官网每日发布，按日落盘缓存） | +| `announcement` | 公告检索（巨潮资讯网，独立数据源，支持下载 PDF） | +| `screen scan` | 策略选股扫描（纯离线，全市场信号扫描） | +| `screen rank` | 扫描结果回测排名（按夏普/回撤等指标排序） | +| `screen strength` | 强势股排名（5/20/60 日涨幅加权，steady/breakout/balanced 三预设） | +| `serve` | 启动 Web API 服务器（REST + WebSocket，需 `easy-tdx[web]`） | +| `f10` | 财报三表（新浪：利润表/资产负债表/现金流量表） | +| `finance-info` | 最新财务快照（通达信协议，30+ 项单期指标） | +| `company-info` | F10 公司信息（无板块名列目录 / 有板块名读正文） | +| `fund-flow` | 历史资金流向（CLI 暂未实现，Web API `/fund-flow/history` 可用） | +| `ex kline` | 扩展市场 K 线 | +| `ex quote` | 扩展市场报价 | +| `ex quote-list` | 扩展市场商品列表 | +| `ex tick` | 扩展市场分时 | +| `ex markets` | 列出可用扩展市场 | +| `offline home` | 检测通达信安装目录 | +| `offline daily` | A 股日线（本地 .day 文件） | +| `offline sync-daily` | 从服务端同步单只股票日线到本地 .day 文件 | +| `offline sync-all` | 一键同步沪深全市场日线（扫描本地 .day 文件） | +| `offline min` | 分钟线（本地 .5/.lc1/.lc5 文件） | +| `offline ex-files` | 列出扩展市场可用文件 | +| `offline ex-daily` | 扩展市场日线（期货/港股/外盘） | +| `offline gbbq` | 股本变迁数据 | +| `offline financial` | 历史财务数据 | +| `offline blocks` | 自定义板块数据 | diff --git a/docs/data-local.md b/docs/data-local.md new file mode 100644 index 0000000..b83b118 --- /dev/null +++ b/docs/data-local.md @@ -0,0 +1,88 @@ +# 本地数据：K 线仓库与离线文件 + +## 本地 K 线仓库（v1.26） + +行情沉淀为 DuckDB 单文件列存（可选依赖：`pip install easy-tdx[warehouse]`），增量同步 + 临时收盘价状态机 + 健康自检： + +```bash +easy-tdx warehouse sync --symbols SH:600519,SZ:000001 # 首次全量，此后只补尾部 +easy-tdx warehouse query SH 600519 --count 30 # 默认忽略未收盘的临时 bar +easy-tdx warehouse stats # 各标的行数 / 数据范围 +easy-tdx warehouse check # 缺口 / 除权跳变 / 新鲜度体检 +``` + +## 离线数据 CLI + +从本地通达信安装目录直接读取数据文件，无需网络连接： + +```bash +easy-tdx offline home # 检测通达信安装目录 +easy-tdx offline daily SH 600000 --count 10 --table # A 股日线 +easy-tdx offline min SZ 000001 --type lc5 --table # 分钟线（5min/lc1/lc5） +easy-tdx offline ex-files --table # 列出扩展市场可用文件 +easy-tdx offline ex-daily 38#2_CPI --count 5 --table # 扩展市场日线（期货/港股/外盘） +easy-tdx offline gbbq C:\new_jyplug\T0002\hq_cache\gbbq --table # 股本变迁 +easy-tdx offline financial C:\new_jyplug\vipdoc\fin\gpcw20260331.dat # 历史财务 +easy-tdx offline blocks C:\new_jyplug\T0002\blocknew --table # 自定义板块 +``` + +从服务端获取最新日线并写入本地 .day 文件，替代通达信内置下载功能： + +```bash +# 同步单只股票日线（自动增量/全量） +easy-tdx offline sync-daily SZ 000001 +easy-tdx offline sync-daily SH 600519 --vipdoc C:\new_jyplug\vipdoc + +# 一键同步沪深全市场（每天一条命令） +easy-tdx offline sync-all +``` + +> 建议在通达信关闭时执行 sync 命令，避免文件被锁定。空文件自动全量下载，已有数据只做增量追加。 + + +## 离线数据读取（Python） + +无需网络，从本地通达信安装目录直接读取： + +```python +from easy_tdx.offline import detect_tdx_home, read_daily_bars, find_daily_bar_file +from easy_tdx import Market + +home = detect_tdx_home() +filepath = find_daily_bar_file(Market.SH, "600000") +bars = read_daily_bars(filepath) +``` + +支持：日线、分钟线、扩展市场日线、板块、股本变迁、历史财务数据。 + +## 离线数据写入同步（Python） + +从服务端获取最新数据并追加写入本地通达信数据文件： + +```python +from easy_tdx.offline import ( + encode_daily_bar, append_daily_bars, get_last_bar_date, + encode_5min_bar, append_5min_bars, + encode_lc_min_bar, append_lc_min_bars, +) +from easy_tdx import Market +from easy_tdx.client import TdxClient + +# 追加日线到 .day 文件（自动跳过重复日期） +from easy_tdx.offline import sync_daily_bars_from_security_bars + +# 手动编码单条记录 +bar_bytes = encode_daily_bar(bar, price_coeff=0.01, vol_coeff=0.01) + +# 获取文件末尾日期 +last_date = get_last_bar_date("C:/new_jyplug/vipdoc/sh/lday/sh600000.day") +``` + +v1.5.0 起可通过 CLI 直接使用： + +```bash +easy-tdx offline daily SH 600000 --count 10 --table +easy-tdx offline ex-files --table +easy-tdx offline ex-daily 29#A1801 --table +``` + diff --git a/docs/images/demo/1.png b/docs/images/demo/1.png new file mode 100644 index 0000000000000000000000000000000000000000..807a97f36992bc417cd41ff821e1480760bc9ed4 GIT binary patch literal 168546 zcmc$`cRbdA8$R4#NXZD52H7JSAt@nyOPLX(jO-O!$Vzr(?-8+^n}@AEv4<2=rfm!kX)l0!6ycI?!srSbFf14 zhT;*Wqs||_E0zbvZD!2Gt4mo9jcdG%-*uC%r|eGkQ*Zri>g0PV_9n5!KDIf);OG{) z{OhX)ndmO2to6-}y+Lon-|z+XTmKf=m2;~R*Zt3{RxT}9=s(}#i*4=~9RKtEWBnuA z|MTsR>eHqF`>ppio1OpjJ^8b7!p;5r#k8+=@4vsspNhosME~<`>~S%w|M~Xnh5zp^ 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=?UTF-8?q?=E8=A7=84=E8=8C=83=E5=B9=B6=E5=85=A5=20web-api?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - web-api.md：REST/WebSocket/SSE 端点与示例；吸收 api_reference.md 的 WebSocket 帧表/控制消息/行为约定/前端接入，消除两处互补重复 - web-ui.md：行情终端与回测工作台零代码操作手册（原错位嵌套在 「本地 K 线仓库」章节下的 Web UI 块，补全章节结构） Co-Authored-By: Claude --- docs/web-api.md | 269 ++++++++++++++++++++++++++++++++++++++++++++++++ docs/web-ui.md | 101 ++++++++++++++++++ 2 files changed, 370 insertions(+) create mode 100644 docs/web-api.md create mode 100644 docs/web-ui.md diff --git a/docs/web-api.md b/docs/web-api.md new file mode 100644 index 0000000..c19733b --- /dev/null +++ b/docs/web-api.md @@ -0,0 +1,269 @@ +# Web API（REST + WebSocket） + +## 概述 + +将 easy-tdx 暴露为 REST + WebSocket 服务，供前端、其他语言或远程调用。无需额外注册，零配置启动。 + +## 安装 + +```bash +# 标准安装 +pip install easy-tdx[web] + +# 开发模式（从源码安装，支持热重载） +pip install -e ".[web]" +``` + +## 快速启动 + +```bash +# 启动 Web API 服务器（自动连接最优 TDX 服务器） +easy-tdx serve + +# 启动后浏览器打开 http://127.0.0.1:8000/docs 查看完整 API 文档（Swagger UI） +# 也可以访问 http://127.0.0.1:8000/redoc 查看 ReDoc 格式文档 + +# 指定端口和 TDX 服务器 +easy-tdx serve --port 8080 --tdx-host 119.147.212.81 + +# 开发模式（代码修改后自动重载） +easy-tdx serve --reload +``` + +> 💡 启动后访问 **http://127.0.0.1:8000/docs** 可以看到完整的交互式 API 文档，支持在线调试每个接口。 + +## REST API 示例 + +```bash +# ── 基础行情 ── +# 获取深圳市场证券数量 +curl "http://localhost:8000/api/v1/security/count?market=SZ" + +# 获取股票K线 +curl "http://localhost:8000/api/v1/bars?market=SZ&code=000001&category=DAY&count=100" + +# 批量获取实时行情 +curl -X POST "http://localhost:8000/api/v1/quotes" \ + -H "Content-Type: application/json" \ + -d '{"stocks": [{"market": "SZ", "code": "000001"}, {"market": "SH", "code": "600000"}]}' + +# 市场统计 +curl "http://localhost:8000/api/v1/market/stat" + +# 全市场强势股排名（基于本地 vipdoc 数据，扫描约 30-60 秒） +# steady = 中长期稳健 / breakout = 近期妖股 / balanced = 均衡 +curl "http://localhost:8000/api/v1/market/strength?preset=breakout&top_n=20" + +# 自定义权重 + 过滤低流动性（日均成交额 ≥ 5000 万） +curl "http://localhost:8000/api/v1/market/strength?w5=0.5&w20=0.3&w60=0.2&min_amount=50000000&top_n=30" + +# 板块信息（标准协议） +curl "http://localhost:8000/api/v1/block?filename=block_gn.dat" + +# ── 板块分析（MAC 协议）── +# 行业板块列表 +curl "http://localhost:8000/api/v1/board-mac/list?board_type=HY&count=50" + +# 板块成分股（按涨幅排序） +curl "http://localhost:8000/api/v1/board-mac/members?board_symbol=881001&count=20" + +# 个股所属板块 +curl "http://localhost:8000/api/v1/board-mac/belong?market=SZ&code=000001" + +# 板块摘要（含主力净流入、涨跌家数） +curl "http://localhost:8000/api/v1/board-mac/summary?board_symbol=881001" + +# 行业板块涨幅排名 Top 10 +curl "http://localhost:8000/api/v1/board-mac/ranking?board_type=HY&top_n=10" + +# 板块 20 日涨幅排行 +curl "http://localhost:8000/api/v1/board-mac/change-ranking?board_type=HY&days=20&top_n=10" + +# ── 资金 / 信息 ── +# 个股资金流向（主力/散户净流入） +curl "http://localhost:8000/api/v1/mac/capital-flow?market=SH&code=600519" + +# 个股基本信息快照 +curl "http://localhost:8000/api/v1/mac/symbol-info?market=SZ&code=000001" + +# 服务器交易时段信息 +curl "http://localhost:8000/api/v1/mac/server-info" + +# ── 公告检索（巨潮资讯网，独立数据源）── +# 检索公司公告（无需 TDX 行情服务器） +curl "http://localhost:8000/api/v1/announcements?code=688017&count=30&page=1" +# 返回每条含 url（4 参数可直点打开）和 pdf_url（PDF 直链）： +# {"data": [{"title":"...","type":"...","date":"...","url":".../detail?stockCode=...","pdf_url":"http://static.cninfo.com.cn/.../xxx.PDF",...}], "count": 30} + +# ── 财报三表（新浪财经，独立数据源）── +# 利润表（type: lrb/fzb/llb） +curl "http://localhost:8000/api/v1/sina/financial-report?code=600519&type=lrb&num=8" +# 返回每行一期（最新在前），列为科目名（float）+ {科目}_同比（如有）： + +# ── 排行 / 竞价 / 异动 ── +# 全 A 涨幅排行前 20 +curl "http://localhost:8000/api/v1/mac/quote-list?category=A&count=20&sort_type=CHANGE_PCT" + +# 集合竞价数据 +curl "http://localhost:8000/api/v1/mac/auction?market=SZ&code=000001" + +# 市场异动行情 +curl "http://localhost:8000/api/v1/mac/unusual?market=SH&count=50" + +# ── 扩展市场（期货/港股/美股）── +# 港股 K 线 +curl "http://localhost:8000/api/v1/ex/bars?market=HK_MAIN_BOARD&code=00700&category=DAY&count=30" + +# 美股实时报价 +curl "http://localhost:8000/api/v1/ex/quote?market=US_STOCK&code=AAPL" + +# ── 技术指标 ── +# 列出所有可用指标 +curl "http://localhost:8000/api/v1/indicator/list" + +# 计算 MACD + KDJ 指标 +curl -X POST "http://localhost:8000/api/v1/indicator/compute" \ + -H "Content-Type: application/json" \ + -d '{"data": [{"open":10,"close":10.5,"high":11,"low":9.5,"vol":1000}], "indicators": ["MACD", "KDJ"]}' + +# ── 缠论分析 ── +curl -X POST "http://localhost:8000/api/v1/chanlun/analyze" \ + -H "Content-Type: application/json" \ + -d '{"market": "SZ", "code": "000001", "category": "DAY", "count": 200}' + +# ── 板块总览（一次取全部板块：当日涨跌幅 + 涨速 + 3/5/20日/YTD 涨幅 + 领涨股，服务端 15s 缓存）── +# board_type: HY 行业一级 / HY2 行业二级 / GN 概念 / FG 风格 / DQ 地区 +curl "http://localhost:8000/api/v1/board-mac/overview?board_type=HY" +curl "http://localhost:8000/api/v1/board-mac/overview?board_type=GN" + +# ── 回测任务（WebUI 回测工作台同款后端）── +# 列出内置策略及参数 schema +curl "http://localhost:8000/api/v1/backtest/strategies" +# 提交异步回测（strategy 见 /backtest/strategies；完整字段与 portfolio/multi/optimize/wf/evaluate +# 各端点的请求体以 /docs 的 Swagger 为准），返回 task_id +curl -X POST "http://localhost:8000/api/v1/backtest/run/async" \ + -H "Content-Type: application/json" \ + -d '{"strategy": "ma_cross", "symbol": "SZ:000001", "category": "DAY", "count": 2000}' +# 轮询任务结果（对比页/导出亦走 /backtest/tasks） +curl "http://localhost:8000/api/v1/backtest/tasks/" + +# ── 策略库（保存的策略持久化 SQLite）── +curl "http://localhost:8000/api/v1/strategies" + +# ── 自选股 ── +curl "http://localhost:8000/api/v1/watchlist" +curl -X POST "http://localhost:8000/api/v1/watchlist" \ + -H "Content-Type: application/json" -d '{"market": "SH", "code": "600519", "name": "贵州茅台"}' + +# ── AI 解读（模型 Key 只存本地 ~/.easy_tdx/llm.json）── +curl "http://localhost:8000/api/v1/llm/config" # 当前配置 + Provider 预设 +curl -X POST "http://localhost:8000/api/v1/llm/chat/async" \ + -H "Content-Type: application/json" \ + -d '{"prompt": "解读这份回测报告：..."}' # 后台任务，GET /llm/chat/tasks/{id} 轮询 + +# ── 交易时段（自动刷新门控用）── +curl "http://localhost:8000/api/v1/market/session" +``` + +## WebSocket 实时行情 + +`/api/v1/ws/realtime/{symbol}`（v1.28 起接通数据源）：连接即订阅指定标的，服务端 +经 `RealtimeDataFeed`（按 `interval` 秒轮询五档快照 → `EventBus`）推送 tick 帧； +连接断开自动退订，无人订阅时完全停止轮询。盘外时段默认只睡不拉（交易时段过滤）， +本地冒烟/演示可配合 `EASY_TDX_E2E_MOCK=1` 的合成行情随时验证（见 +`scripts/ws_smoke.py`）。 + +```javascript +const ws = new WebSocket("ws://localhost:8000/api/v1/ws/realtime/SZ000001"); + +ws.onmessage = (event) => { + const frame = JSON.parse(event.data); + if (frame.type === "tick") { + // {type:"tick", symbol:"SZ000001", market:"SZ", code:"000001", + // price:10.5, volume:12345, ts:1760000000.0, + // open, high, low, pre_close, amount, name} + console.log(frame.symbol, frame.price, frame.ts); + } else if (frame.type === "ping") { + // 服务端 30s 空闲心跳，忽略即可（客户端无须回包） + } +}; + +// 动态订阅更多标的（服务端回 {"type":"status","msg":"subscribed SH600000"}） +ws.send(JSON.stringify({action: "subscribe", symbol: "SH600000"})); +// 退订 +ws.send(JSON.stringify({action: "unsubscribe", symbol: "SH600000"})); +``` + +### 服务端推送帧（JSON） + +| type | 触发 | 字段 | +|------|------|------| +| `tick` | 轮询到标的的最新快照（价格/量变化才推，约 `interval` 秒一拍） | `symbol`、`market`、`code`、`price`、`volume`、`ts`（epoch 秒）、`open`、`high`、`low`、`pre_close`、`amount`、`name` | +| `ping` | 连续 30s 未收到客户端消息的心跳 | —（客户端忽略即可，无须回包） | +| `status` | 客户端 subscribe/unsubscribe 的确认 | `msg`（如 `subscribed SH600000`） | +| `error` | 非法 JSON / 未知 action / 超出订阅上限 | `msg` | + +### 客户端控制消息（JSON 文本帧） + +```json +{"action": "subscribe", "symbol": "SH600000"} +{"action": "unsubscribe", "symbol": "SH600000"} +``` + +### 行为约定 + +- **连接即订阅** path 上的 symbol；断开自动退订全部标的。 +- **按需轮询**：订阅集合为空时服务端不产生任何行情请求；去重后标的总数上限 + 80（`get_stock_quotes` 协议约束）。 +- **交易时段**：默认 A 股时段外只睡不拉（无 tick 帧，心跳照发）；mock 模式 + （`EASY_TDX_E2E_MOCK=1`）不受限制。 +- **背压**：消费过慢时丢最旧快照保最新，不积压。 +- 环境变量：`EASY_TDX_WS_INTERVAL`（轮询间隔秒数，默认 3.0）。 + +浏览器接入建议（自动重连 + 心跳容忍）：`onclose` 后指数退避重连（参考 +`web-ui/src/stores/quotes.ts` 对 SSE 的同类处理）；`{"type":"ping"}` 心跳帧直接 +忽略、不回包；连续 N 秒无任何帧（含 ping）再视为僵死连接主动重连。 + +### 前端接入方式（自动重连 + 心跳容忍） + +```typescript +function connectRealtime(symbol: string, onTick: (f: TickFrame) => void) { + let retry = 0 + let ws: WebSocket | null = null + const open = () => { + ws = new WebSocket(`ws://${location.host}/api/v1/ws/realtime/${symbol}`) + ws.onmessage = (e) => { + const frame = JSON.parse(e.data) + if (frame.type === 'tick') { retry = 0; onTick(frame) } // ping/status 忽略 + } + ws.onclose = () => { + retry += 1 + setTimeout(open, Math.min(1000 * 2 ** (retry - 1), 30_000)) // 指数退避 + } + } + open() + return () => ws?.close() +} +``` + +> 说明：看板/自选页的实时刷新已由 SSE `/stream/quotes`（全量快照、单连接共享） +> 承担；WS 通道定位是**按需订阅单标的 tick 事件**（后续实时策略信号的接入点）， +> 两条链路按场景选用，不要求同时连接。手动冒烟见 `scripts/ws_smoke.py`。 + + +## API 文档 + +启动服务后访问： +- Swagger UI: http://localhost:8000/docs +- ReDoc: http://localhost:8000/redoc + +## 编程 API + +```python +from easy_tdx.web import create_app +import uvicorn + +app = create_app(host="119.147.212.81", port=7709) +uvicorn.run(app, host="0.0.0.0", port=8000) +``` + diff --git a/docs/web-ui.md b/docs/web-ui.md new file mode 100644 index 0000000..b36da9a --- /dev/null +++ b/docs/web-ui.md @@ -0,0 +1,101 @@ +# Web UI 使用手册 + +## 概述 + +行情终端 + 回测可视化 Web UI（v1.17 新增，v1.23 升级为行情终端）。不想写命令行？用浏览器。`easy-tdx serve` 一条命令启动，浏览器自动打开 `http://localhost:8000`。 + +Web UI 截图 1 + +Web UI 截图 2 + +Web UI 截图 3 + +Web UI 包含两大模块： + +- **行情终端**——侧边栏专业终端布局（行情：市场看板 / 行业总览 / 概念总览 / 自选行情 / 龙头池 / 期货持仓排名）： + - **市场看板**：五大指数实时行情（SSE 推送）、全市场涨跌统计（涨/跌/平/涨停/跌停 + 堆叠条）、行业/概念板块热度榜、涨幅榜/跌幅榜、两市异动雷达（加速拉升/封涨停板/大单托盘等），点击个股打开五档盘口 + 分时/日K 对话框； + - **行业总览 / 概念总览**（v1.32.1）：全部行业（一级/二级可切）/概念板块一屏尽览——板块广度统计条、涨跌幅分布直方图、热力图与表格双视图、搜索过滤、涨幅/跌幅/涨速异动三榜、翻红/翻绿轮动时间线，30s 自动刷新（休市暂停）；点击板块复用详情弹窗（分时/日K + 成分股涨跌榜直达个股）； + - **自选行情**：输入 6 位代码一键加自选（SQLite 持久化），全表实时刷新（SSE），行内迷你分时图，点击行看个股详情； + - **龙头池**：159 只核心龙头名单一键只扫龙头（名单仅为扫描范围，不构成任何推荐）； + - **期货持仓排名**（v1.29.1）：中金所每日成交/持仓前 20 名会员一键采集（品种下拉 + 日期选择 + 自动回溯最近交易日开关），合约页签自动标注主力，前 20 名合计多单/空单/净持仓概览，三组排名并排表格；附「品种一览」「多单空单加减仓怎么看」新手科普（重点：排名看不出套保还是投机，空单多 ≠ 看空市场）； + - **实时推送架构**：后端单条轮询循环 fan-out 到所有 SSE 连接（交易时段 ~8s 一拍，盘外降频 60s，无人订阅自动休眠），前端指数退避重连。 +- **回测工作台**——浏览器里选标的、挑策略、调参数，K 线买卖点、净值回撤、25 项绩效指标一目了然。支持组合回测、参数网格寻优、多策略结果对比、策略库（SQLite 持久化）与多策略资金分仓、信号雷达、Walk-Forward / 一条龙附加分析、**AI 解读与解读历史**（分析：单标的回测 / 组合回测 / 参数寻优 / 结果对比 / 策略库 / 信号雷达 / AI 解读历史），全程零代码。 + +## 启动 + +**前置条件：** + +```bash +# 需安装 web 可选依赖（FastAPI + Uvicorn） +pip install -e ".[web]" +``` + +**启动（一条命令）：** + +```bash +# 启动后端 + 自动打开浏览器（默认 http://localhost:8000） +easy-tdx serve + +# 自定义端口/不自动开浏览器 +easy-tdx serve --port 8080 --no-open-browser +``` + +> 后端启动后约 1-2 秒会自动弹出浏览器。前端界面已编译进 `web-ui/dist/`，由后端同源托管，无需单独跑前端开发服务器。后端行情连接失败时回测路由仍可用（用内联数据），但取行情功能需要后端连通通达信服务器。 + +## 桌面版（EXE） + +不想装 Python？下载 EXE 直接用（面向零基础用户）： + +Windows 用户可以下载打包好的单一 EXE（约 80-150MB），双击即可使用，无需安装 Python/Node 或任何依赖： + +1. 到 [Releases 页面](../../releases) 下载最新的 `easy-tdx-<版本>-windows.exe` +2. 双击运行（首次会被 SmartScreen 拦截，点"更多信息 → 仍要运行"） +3. 等待 2-5 秒，浏览器自动打开回测界面 +4. 右下角任务栏出现小图标，右键 → "退出" 可关闭 + +EXE 打包方法见 [`packaging.md`](./packaging.md)。 + +## 回测工作台页面 + +打开浏览器后，「分析」分组下是回测工作台的核心页面： + +### 1. 单标的回测（首页 `/`） + +左侧配置面板从上到下填写，右侧自动出图： + +- **取行情**：选市场（深/沪/北），填 6 位代码，选周期（日线/周线/分钟线），设日期范围（默认最近 3 年），点「取行情」。超过 800 根会自动翻页拼接 +- **选策略**：下拉选 18 个内置策略之一（双均线交叉、MACD、布林带、RSI、KDJ、唐安奇通道、CCI 等），选中后参数表单自动出现，按推荐范围调参 +- **资金与成本**：初始资金、佣金率、滑点、成交模式（默认 next_open 下一根开盘成交） +- 点「开始回测」，右侧依次出：K 线主图（红三角=买入、绿钉=卖出）、净值曲线与回撤双轴图、25 项绩效指标表（总收益/夏普/最大回撤/胜率/盈亏比/Ulcer/VaR/SQN 等）、成交记录明细 +- 结果区右上角有「💾 保存策略」按钮，把当前策略 + 标的 + 成绩快照存进策略库，下次直接载入或参与组合回测 + +### 2. 组合回测（`/portfolio`） + +- 添加多只标的（如 SZ:000001、SH:600519），选策略和日期范围 +- 点「开始组合回测」，右侧出：组合整体绩效（加权收益率）、组合净值曲线（各标的按日期对齐求和）、各标的净值归一化叠加对比图、各标的绩效横向对比表 +- 同样有「保存策略」按钮，可把整个组合配置存进策略库 + +### 3. 参数寻优（`/optimize`） + +- 先取行情（同单标的），选策略 +- 勾选 1-2 个想寻优的参数，填入取值列表（逗号分隔，如 fast 填 `5,10,20,30`），页面实时显示网格点数（上限 200） +- 点「开始寻优」，右侧出：最优结果摘要、参数热力图（2 参数时，颜色映射收益率）、所有网格点排名表 +- 排名表每行有「查看」按钮，点击跳转单标的回测页，自动填充该参数组合跑完整回测 + +### 4. 结果对比（`/compare`） + +- 左侧列出最近 20 个已完成的回测任务（含单标的和组合） +- 勾选 2-4 个，右侧出：归一化净值叠加图（初始=1，看相对走势）、8 项核心指标横向对比表（总收益/夏普/最大回撤/胜率/盈亏比/交易数/年化/波动率） + +### 5. 策略库（`/strategies`，v1.17.11 新增） + +- 保存你觉得不错的策略，下次直接载入或重跑。数据存在本地 SQLite 单文件（`~/.easy_tdx/strategies.db`，重启不丢） +- 每张卡片展示策略名、标的、保存时的成绩快照（总收益/夏普/回撤）、标签、备注、创建时间 +- **载入**：点「载入」跳转对应回测页（单标的/组合），自动回填标的、日期、策略参数，可直接重跑 +- **多策略组合回测**：勾选多个单标的策略（卡片左上角复选框），点顶部「组合回测(N)」——每个策略各拿 1/N 资金、各跑在它保存时的原标的上（取最新行情），净值曲线按日期对齐求和，看综合表现。结果区展示：组合净值曲线、25 项完整绩效指标（与单标的同口径）、各策略绩效对比表、净值叠加图、各策略当前持仓表（回测结束时谁还套着票） + +## 注意事项 + +> ⚠️ **任务不持久化**：回测结果存在后端进程内存，重启 `easy-tdx serve` 后清空。对比页只能选当前运行期间产生的任务。**策略库除外**——保存到策略库的策略持久存在 SQLite，重启不丢。 + +技术栈：Vue 3 + Vite + TypeScript + Pinia + ECharts（按需引入，构建产物约 800KB）。前端代码在 `web-ui/` 目录，独立 `package.json`，不依赖 Python 环境。 From 36b586b0159919eab2cb1eb663b74033a5eebb1e Mon Sep 17 00:00:00 2001 From: awayings Date: Tue, 8 Sep 2026 23:21:35 +0800 Subject: [PATCH 3/6] =?UTF-8?q?docs:=20README=20Python=20API=20=E7=AB=A0?= =?UTF-8?q?=E6=8B=86=E8=87=B3=20python-api.md=EF=BC=88=E6=95=99=E7=A8=8B?= =?UTF-8?q?=EF=BC=89=EF=BC=8C=E6=9E=9A=E4=B8=BE/API=20=E5=88=97=E8=A1=A8?= =?UTF-8?q?=E5=BD=92=E5=85=A5=E5=8F=82=E8=80=83=E6=96=87=E6=A1=A3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - python-api.md：连接/MAC/统一客户端/标准协议/离线/缠论/公告/财报/实时轮询教程 - MAC 协议枚举（Period/Adjust/Category/BoardType/SortType/ExMarket）并入 field_mapping.md - MacClient/MacExClient 完整方法表并入 api_reference.md（TdxClient 表与正文重复，删除） Co-Authored-By: Claude --- docs/python-api.md | 421 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 421 insertions(+) create mode 100644 docs/python-api.md diff --git a/docs/python-api.md b/docs/python-api.md new file mode 100644 index 0000000..205ce45 --- /dev/null +++ b/docs/python-api.md @@ -0,0 +1,421 @@ +# Python API 使用指南 + +## 连接管理 + +所有客户端支持 `from_best_host()` 自动选最低延迟服务器： + +```python +from easy_tdx import MacClient + +with MacClient.from_best_host() as c: + df = c.get_stock_kline(...) +``` + +| 客户端 | 端口 | 覆盖范围 | +|--------|------|----------| +| `MacClient` / `AsyncMacClient` | 7709 | A 股行情（MAC 协议，推荐） | +| `MacExClient` / `AsyncMacExClient` | 7727 | 港股/美股/期货（MAC 协议） | +| `UnifiedTdxClient` / `AsyncUnifiedTdxClient` | 自动 | A 股 + 扩展市场统一入口 | +| `TdxClient` / `AsyncTdxClient` | 7709 | A 股行情（标准协议） | + +## MAC 协议（推荐） + +### 报价 + +```python +from easy_tdx import MacClient, Market, Category, SortType, SortOrder + +with MacClient.from_best_host() as c: + # 批量报价（最多 80 只/次） + df = c.get_stock_quotes([(Market.SH, "600519"), (Market.SZ, "000858")]) + + # 市场分类排序报价 + df = c.get_stock_quotes_list( + Category.A, count=20, + sort_type=SortType.CHANGE_PCT, + sort_order=SortOrder.DESC, + ) +``` + +返回列：`market, code, name` + 动态字段（`pre_close, open, high, low, close, vol, amount, turnover, vol_ratio` 等）。 + +### K 线（支持复权） + +```python +from easy_tdx import MacClient, Market, Period, Adjust + +with MacClient.from_best_host() as c: + # 日K前复权 + df = c.get_stock_kline(Market.SH, "600519", Period.DAILY, count=10, adjust=Adjust.QFQ) + # 5分钟线 + df = c.get_stock_kline(Market.SZ, "000001", Period.MIN_5, count=100) +``` + +返回列：`datetime, open, close, high, low, vol, amount`。 + +### 技术指标 + +自动获取 200+ 条历史数据预热 EMA，返回最后 `count` 条带指标的结果： + +```python +from easy_tdx import MacClient, Market, Period, Adjust +from easy_tdx.indicator import compute_indicators, list_indicators + +with MacClient.from_best_host() as c: + # 便捷方法：获取 K 线 + 计算指标一步完成（默认前复权） + df = c.get_stock_kline_with_indicators( + Market.SH, "600519", + indicators=["MACD", "KDJ", "RSI", "BOLL"], + count=30, + ) + # df 包含: datetime, open, close, high, low, vol, amount + # + MACD_DIF, MACD_DEA, MACD_HIST, KDJ_K, KDJ_D, KDJ_J, RSI, + # BOLL_UPPER, BOLL_MID, BOLL_LOWER + + # 自定义指标参数 + df = c.get_stock_kline_with_indicators( + Market.SH, "600519", + indicators=["MACD"], + params={"MACD": {"SHORT": 10, "LONG": 22}}, + ) + + # 独立使用：对已有 DataFrame 计算指标 + raw = c.get_stock_kline(Market.SH, "600519", Period.DAILY, count=200, adjust=Adjust.QFQ) + result = compute_indicators(raw, ["ATR", "CCI", "WR"], tail=30) + + # 查看所有可用指标 + for info in list_indicators(): + print(info["name"], info["description"], info["outputs"]) +``` + +支持 34 个技术指标： + +| 指标 | 输入 | 输出列 | +|------|------|--------| +| MACD | close | MACD_DIF, MACD_DEA, MACD_HIST | +| KDJ | close, high, low | KDJ_K, KDJ_D, KDJ_J | +| RSI | close | RSI | +| BOLL | close | BOLL_UPPER, BOLL_MID, BOLL_LOWER | +| DMI | close, high, low | DMI_PDI, DMI_MDI, DMI_ADX, DMI_ADXR | +| ATR | close, high, low | ATR | +| WR | close, high, low | WR1, WR2 | +| CCI | close, high, low | CCI | +| BIAS | close | BIAS1, BIAS2, BIAS3 | +| OBV | close, vol | OBV | +| VR | close, vol | VR | +| EMV | high, low, vol | EMV, EMV_MA | +| MFI | close, high, low, vol | MFI | +| BRAR | open, close, high, low | AR, BR | +| ASI | open, close, high, low | ASI, ASI_MA | +| TRIX | close | TRIX, TRIX_MA | +| DPO | close | DPO, DPO_MA | +| MTM | close | MTM, MTM_MA | +| ROC | close | ROC, ROC_MA | +| EXPMA | close | EXPMA_12, EXPMA_50 | +| BBI | close | BBI | +| PSY | close | PSY, PSY_MA | +| DFMA | close | DFMA_DIF, DFMA_DMA | +| CR | close, high, low | CR | +| KTN | close, high, low | KTN_UPPER, KTN_MID, KTN_LOWER | +| XSII | close, high, low | XSII_TD1, XSII_TD2, XSII_TD3, XSII_TD4 | +| MASS | high, low | MASS, MASS_MA | +| TAQ | high, low | TAQ_UP, TAQ_MID, TAQ_DOWN | +| ZHUOYAO | close | ZY_LONG, ZY_MID, ZY_SHORT, ZY_TREND | +| BIAS_SIGNAL | close | BS_X, BS_SMA, BS_LMA | +| SAR | high, low | SAR（抛物线转向/动态止损位） | +| VWAP | close, high, low, vol | VWAP（N日滚动成交量加权均价） | +| AROON | high, low | AROON_UP, AROON_DOWN, AROON_OSC | +| FK | close | FK（EMA(2) 突破斜率外推 EMA(42)） | + +### 分时 + +```python +with MacClient.from_best_host() as c: + df = c.get_tick_chart(Market.SH, "600519") # 单日分时 + df = c.get_tick_charts(Market.SH, "600519", days=3) # 多日分时（最多5天） + df = c.get_chart_sampling(Market.SH, "600519") # 240点缩略采样 +``` + +### 逐笔成交 + +```python +with MacClient.from_best_host() as c: + df = c.get_transactions(Market.SH, "600519", count=100) + df = c.get_transactions(Market.SH, "600519", count=100, date=20250115) +``` + +### 板块 + +```python +from easy_tdx import BoardSortColumn, BoardType + +with MacClient.from_best_host() as c: + df = c.get_board_list(BoardType.GN) # 概念板块 + df = c.get_board_list(sort_column=BoardSortColumn.SPEED) # 按涨速排序取涨速% + df = c.get_board_members("881001", sort_type=SortType.CHANGE_PCT) + df = c.get_belong_board(Market.SZ, "000001") # 个股所属板块 + + # 板块汇总：成交额、主力净流入、涨跌家数 + summary = c.get_board_summary("881001") + # summary = { + # "member_count": 82, + # "amount": 5823456000.0, # 板块总成交额（元） + # "vol": 412356789, # 板块总成交量（股） + # "main_net_amount": -123456.0, # 当日主力净流入 + # "main_net_3d": -567890.0, # 近3日主力净流入 + # "main_net_5d": -234567.0, # 近5日主力净流入 + # "up_count": 45, + # "down_count": 37, + # "members": DataFrame(...), # 成分股明细 + # } + + # 板块涨跌幅排行榜 + df = c.get_board_ranking(BoardType.HY, top_n=10, sort_by="change_pct") + df = c.get_board_ranking(BoardType.GN, top_n=20, sort_by="main_net_amount") + # 返回列：code, name, change_pct, amount, vol, main_net_amount, up_count, down_count, member_count + + # 板块 N 日涨跌幅排行（支持指定截止日期，默认全部） + df = c.get_board_change_ranking(BoardType.HY, days=20) + df = c.get_board_change_ranking(BoardType.GN, target_date=20250530, days=10, top_n=15) + # 返回列：code, name, close_end, close_start, change_pct +``` + +### 资金流向 + +```python +with MacClient.from_best_host() as c: + df = c.get_capital_flow(Market.SH, "600519") +``` + +返回列：`date, main_in, main_out, main_net, small_in/out/net, mid_in/out/net, large_in/out/net`。 + +### 监控 + +```python +with MacClient.from_best_host() as c: + df = c.get_auction(Market.SH, "600519") # 集合竞价 + df = c.get_unusual(Market.SH) # 市场异动 + df = c.get_symbol_info(Market.SZ, "000001") # 个股特征快照 + df = c.get_server_info() # 服务器交易时段 +``` + +`get_unusual` 返回列含 `unusual_type`（类型码）与 `desc`（中文描述），共 19 种类型 +（主力买卖/加速拉升/急速拉升/盘中强弱/竞价异动/涨跌停/大单盘口等）。类型码→名称 +可用顶层常量映射： + +```python +from easy_tdx import UNUSUAL_TYPE_NAMES + +df["type_name"] = df["unusual_type"].map(UNUSUAL_TYPE_NAMES) +``` + +## 扩展市场 + +```python +from datetime import date + +from easy_tdx import MacExClient, ExMarket, Period + +with MacExClient.from_best_host() as c: + count = c.goods_count(ExMarket.HK_MAIN_BOARD) + df = c.goods_list(ExMarket.HK_MAIN_BOARD, start=0, count=50) + df = c.goods_kline(ExMarket.US_STOCK, "AAPL", Period.DAILY, count=10) + df = c.goods_quotes([(ExMarket.HK_MAIN_BOARD, "00700")]) + df = c.goods_tick_chart(ExMarket.HK_MAIN_BOARD, "00700") + df = c.goods_transaction(ExMarket.HK_MAIN_BOARD, "00700", count=100) + df = c.goods_transaction_all(ExMarket.HK_MAIN_BOARD, "00700", date(2026, 7, 3)) # 港股当日全部逐笔 +``` + +> **逐笔成交排序**：通达信协议为**倒序**——`start=0` 指向最新一笔（收盘方向），`count=2000` 默认只取最近 2000 笔。港股单日成交常达数万笔（如 02715 约 1.3 万笔/日），若需当日全部成交，用 `goods_transaction_all`（仅港股股票类市场，自动按 1800/页翻页取全天，安全上限 9 万条；返回协议原生倒序，需正序展示自行 `df.iloc[::-1]`）。 + +## 统一客户端 + +```python +from easy_tdx import UnifiedTdxClient, ExMarket, Market, Period + +with UnifiedTdxClient() as client: + # A 股 -- 自动路由到 MacClient + df = client.get_stock_kline(Market.SH, "600519", Period.DAILY, count=5) + df = client.get_stock_quotes([(Market.SH, "600519")]) + df = client.get_board_list() + + # 扩展市场 -- 自动路由到 MacExClient + df = client.goods_kline(ExMarket.HK_MAIN_BOARD, "00700", Period.DAILY, count=5) +``` + +## 标准协议 + +```python +from easy_tdx import TdxClient, Market, KlineCategory + +with TdxClient.from_best_host() as c: + count = c.get_security_count(Market.SH) + stocks = c.get_security_list(Market.SH, start=0) + quotes = c.get_security_quotes([(Market.SH, "600000"), (Market.SZ, "000001")]) + bars = c.get_security_bars(Market.SZ, "002176", KlineCategory.DAY, 0, 100) + minute = c.get_minute_time_data(Market.SH, "600000") + trades = c.get_transaction_data(Market.SH, "600000", 0, 20) + flow = c.get_fund_flow(Market.SH, "600519") + blocks = c.get_block_info("block_gn.dat") + xdxr = c.get_xdxr_info(Market.SH, "600519") + stat = c.get_market_stat() +``` + +> **资金流口径注意**（Issue #55）：`get_fund_flow` / `get_history_fund_flow` 按 0x0fb5 逐笔接口的"单笔成交额"分档，而该接口返回的记录是交易所真实逐笔**聚合**后的（实测 000001.SZ 单日约 17:1），分档看的也不是挂单额。结果：高价股小单档可不足成交额 1%、主力档常占 95%+，`main_net_inflow` 实质更接近"当日主动买卖总失衡"。东财/同花顺的"主力净流入"基于 L2 逐笔委托、按挂单额分档——两套口径**不可比**（实证同规则选股信号重合度仅约 14%），勿混用于同一张表或同一个因子。 + +`AsyncTdxClient` 提供对应的 `async def` 方法，接口一一对应。 + +## SecurityQuote 字段说明 + +`get_security_quotes()` 返回的 DataFrame 包含以下特殊字段： + +| 字段 | 类型 | 说明 | +|------|------|------| +| `trading_status` | int | 交易状态标志。`0x8020`(32800) = 停牌，其余值表示正常交易或集合竞价 | +| `open_amount` | float | 集合竞价成交金额（元）。仅个股有效，指数该字段无意义 | +| `server_time` | str | 服务器时间，格式 `HH:MM:SS.mmm` | +| `unknown_2` | int | 指数: 集合竞价成交金额/100；个股: 舍入残差≈0 | +| `unknown_3` | int | 个股: 集合竞价成交金额/100；指数: 负值/无意义 | +| `unknown_5-8` | int | 保留字段，恒为 0 | + +检测停牌： + +```python +df = c.get_security_quotes([(Market.SH, "600000")]) +is_suspended = df.iloc[0]["trading_status"] == 0x8020 +``` + + +## 公告检索（巨潮资讯网） + +独立数据源（巨潮资讯网 cninfo），无需连接 TDX 行情服务器即可检索公司公告。 +标准库 urllib 实现，零额外依赖。 + +```python +from easy_tdx.cninfo import CninfoClient + +client = CninfoClient() + +# 检索公告（默认 30 条，最新在前） +df = client.get_announcements("688017") +# → DataFrame[title, type, date, url, code, org_id, announcement_id, announcement_time, pdf_url] + +# 翻页 + 自定义数量 +df = client.get_announcements("601088", count=10, page=2) + +# 返回示例（url 含 4 参数可直点打开，pdf_url 为 PDF 直链）： +# title type date url pdf_url +# 0 关于召开2025年年度股东大会... 股东大会 2025-06-14 .../detail?stockCode=688017&announcementId=... http://static.cninfo.com.cn/.../xxx.PDF +# 1 2024年年度报告 PDF 2025-03-28 .../detail?stockCode=688017&announcementId=... http://static.cninfo.com.cn/.../yyy.PDF +``` + +> - ``type`` 优先取 cninfo 的 ``announcementTypeName``；该字段对很多公告为 null +> （数据源限制），此时回退到 ``adjunctType``（如 "PDF"），再为空给空字符串。 +> - ``url`` 必须含 4 参数（``stockCode``/``announcementId``/``orgId``/``announcementTime``） +> 才能打开，少参数会 404。 +> - orgId 解析沿用 #19 修复：动态拉取官方映射表，查不到回退硬编码规则， +> 保证 601xxx 等非标 orgId 段也能正常查询。 + +### 下载公告 PDF + +```python +# 下载最新一条公告的 PDF 到当前目录 +df = client.get_announcements("601088", count=5) +path = client.download_pdf(df.iloc[0]) # 接受 Announcement 或 DataFrame 的一行 +print(path) # /abs/path/20260605_1225351400.PDF + +# 批量下载 +for _, row in df.iterrows(): + try: + path = client.download_pdf(row, dest_dir="./pdfs") + except Exception as e: + print(f"跳过（无附件或失败）: {e}") +``` + +## 财报三表（新浪财经） + +独立数据源（新浪财经），无需连接 TDX 行情服务器即可获取利润表/资产负债表/现金流量表。 +标准库 urllib 实现，零额外依赖。 + +```python +from easy_tdx.sina import SinaClient + +client = SinaClient() + +# 利润表（默认 8 期，最新在前） +df = client.get_financial_report("600519", report_type="lrb") +# → DataFrame，每行一期，列 = [报告期, 营业总收入, 营业总收入_同比, ...] + +# 资产负债表 / 现金流量表（report_type 也接受中文别名：利润表/资产负债表/现金流量表） +df = client.get_financial_report("600519", report_type="fzb", num=4) +df = client.get_financial_report("600519", report_type="llb", num=4) + +# 返回示例（item_value 已转 float，可直接数值计算）： +# 报告期 营业总收入 营业总收入_同比 营业收入 营业收入_同比 +# 0 2026-03-31 54702912385.23 0.06336 53909252220.51 0.06538 +# 1 2025-12-31 174000000000.00 0.10000 NaN NaN +``` + +> - ``item_value`` 是字符串（新浪原始格式），本实现转 float；空/非数值转 None +> - 有同比的科目附加 ``{科目}_同比`` 列（float 比例，如 0.06336 = +6.3%） +> - 大类标题行（如 ``流动资产``，原 ``item_value=""``）保留为 None，反映报表结构 + +## 实时行情轮询（RealtimeDataFeed） + +> ⚠️ 通达信协议**没有服务端推送**，只有请求/响应。本模块的「实时」是 **轮询五档快照近似** +> （默认约 3 秒延迟），适合盘中信号提醒、轻量监控；**不适合高频 / 逐笔撮合**。 + +`EventBus` 自身是纯发布/订阅管道，不会产生数据。要让 `RealtimeStrategy` 跑起来， +需要配合 `RealtimeDataFeed`：它自动完成 `get_stock_quotes → MarketEvent → bus.publish`。 + +```python +import asyncio +from easy_tdx.mac.client import AsyncMacClient +from easy_tdx.realtime import ( + EventBus, + RealtimeStrategy, + MarketEvent, + RealtimeDataFeed, +) + + +class MyStrategy(RealtimeStrategy): + def on_tick(self, event: MarketEvent) -> None: + print(f"{event.market}{event.code} price={event.price} vol={event.volume}") + + +async def main(): + bus = EventBus() + strategy = MyStrategy() + bus.subscribe("SZ000001", strategy.on_tick) # 注意：key 必须带市场前缀 + + feed = RealtimeDataFeed( + bus=bus, + symbols=[(0, "000001"), (1, "600519")], # [(Market.SZ, code), ...]，单批 ≤80 只 + interval=3.0, # 轮询间隔（秒），下限 0.1 + dedup=True, # (price, volume) 未变的标的跳过发布 + # sessions=(), # 传空 tuple 表示全天轮询；默认仅 9:15-11:30 / 13:00-15:00 + ) + async with AsyncMacClient.from_best_host() as client: + await feed.run_async(client) # Ctrl+C 或 feed.stop() 退出 + + +asyncio.run(main()) +``` + +同步客户端（`MacClient`）用 `run_sync`，feed 会把阻塞调用丢到线程池，不卡事件循环： + +```python +from easy_tdx.mac.client import MacClient + +with MacClient.from_best_host() as client: + feed.run_sync(client) +``` + +> **关键坑（issue #34）**： +> - 订阅 key 必须与 `publish` 内部拼的 `f"{market}{code}"` 一致，即 `"SZ000001"` +> 而不是 `"000001"`；否则事件分发匹配不到。 +> - 传给 `subscribe` 的必须是**实例的绑定方法** `strategy.on_tick`， +> 不是未绑定的类方法 `MyStrategy.on_tick`。 +> - 整个流程跑在 `asyncio.run()` 里，否则协程不会被调度。 + From 990b4a7802a838a3ac854e0598e950842c26a99b Mon Sep 17 00:00:00 2001 From: awayings Date: Tue, 8 Sep 2026 23:21:44 +0800 Subject: [PATCH 4/6] =?UTF-8?q?docs:=20=E6=8B=86=E5=88=86=E8=B6=85?= =?UTF-8?q?=E5=A4=A7=E6=96=87=E6=A1=A3=E2=80=94=E2=80=94=E6=95=99=E7=A8=8B?= =?UTF-8?q?/=E5=8F=82=E8=80=83=E5=88=86=E7=A6=BB=EF=BC=8C=E5=8E=BB?= =?UTF-8?q?=E8=BF=87=E6=9C=9F=E7=89=88=E6=9C=AC=E6=A8=AA=E5=B9=85=EF=BC=8C?= =?UTF-8?q?=E6=A8=A1=E5=9E=8B=E6=9E=9A=E4=B8=BE=E5=BD=92=E5=B9=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - backtest_usage（742→485）：CLI 章移交 cli-backtest.md，示例/注意事项 抽至 backtest-examples.md，重建目录 - quantitative-guide（628→325）：第 5-7 章（滑点/执行仿真/归因/工作流） 抽至 quantitative-advanced.md 并重编号 - api_reference（704→478）：删除过期版本横幅（1.16.2）与快速开始教程段； 数据模型/枚举与 field_mapping.md 逐表核对后去重（field_mapping 为唯一权威）； WebSocket 节随 web-api.md 合并移除 - field_mapping：吸收 MAC 协议枚举（Period/Adjust/Category/BoardType/ SortType/ExMarket），全部文档回到 ≤500 行 Co-Authored-By: Claude --- docs/api_reference.md | 308 +++++---------------------------- docs/backtest-examples.md | 153 +++++++++++++++++ docs/backtest_usage.md | 265 +---------------------------- docs/field_mapping.md | 75 +++++++- docs/quantitative-advanced.md | 308 +++++++++++++++++++++++++++++++++ docs/quantitative-guide.md | 310 +--------------------------------- 6 files changed, 581 insertions(+), 838 deletions(-) create mode 100644 docs/backtest-examples.md create mode 100644 docs/quantitative-advanced.md diff --git a/docs/api_reference.md b/docs/api_reference.md index 2171671..6096f26 100644 --- a/docs/api_reference.md +++ b/docs/api_reference.md @@ -1,10 +1,11 @@ # easy_tdx API 参考文档 -> 版本: 1.16.2 | 运行时依赖: pandas / tzdata / click | 需要网络连接通达信行情服务器 +> 本文档为**方法速查参考**；上手教程见 [python-api.md](./python-api.md)，数据模型与枚举字段见 [field_mapping.md](./field_mapping.md)，Web 服务端点见 [web-api.md](./web-api.md)。 +> +> 文档不写死版本号，对应版本以 [CHANGELOG.md](../CHANGELOG.md) 与 pyproject.toml 为准。 ## 目录 -- [快速开始](#快速开始) - [客户端](#客户端) - [TdxClient（同步）](#tdxclient同步) - [AsyncTdxClient（异步）](#asynctdxclient异步) @@ -18,29 +19,10 @@ - [资金流向](#资金流向) - [文件下载](#文件下载) - [市场统计](#市场统计) -- [数据模型](#数据模型) -- [枚举](#枚举) - [异常](#异常) - [涨跌停价计算](#涨跌停价计算) - ---- - -## 快速开始 - -```python -from easy_tdx import TdxClient, Market, KlineCategory - -# 自动选择最优服务器 -with TdxClient.from_best_host() as c: - # 沪市证券总数 - count = c.get_security_count(Market.SH) - - # 浦发银行日K线 - bars = c.get_security_bars(Market.SH, "600000", KlineCategory.DAY, 0, 10) - - # 实时行情 - quotes = c.get_security_quotes([(Market.SH, "600000"), (Market.SZ, "000001")]) -``` +- [全局常量](#全局常量) +- [完整 API 列表（MAC 协议客户端）](#完整-api-列表mac-协议客户端) --- @@ -396,193 +378,6 @@ c.get_market_stat() -> MarketStat --- -## 数据模型 - -### SecurityInfo - -证券列表条目。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| market | `Market` | 市场代码 | -| code | `str` | 证券代码 | -| name | `str` | 证券名称 | -| volunit | `int` | 成交量单位（手 = volunit 股） | -| decimal_point | `int` | 价格小数位数 | -| pre_close | `float` | 昨收价 | -| industry_tdx | `str` | 通达信行业代码（扩展字段） | -| industry_sw | `str` | 申万行业代码（扩展字段） | - -### SecurityQuote - -实时五档行情。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| market | `Market` | 市场代码 | -| code | `str` | 证券代码 | -| price | `float` | 现价 | -| pre_close | `float` | 昨收 | -| open | `float` | 今开 | -| high | `float` | 最高 | -| low | `float` | 最低 | -| vol | `float` | 总成交量（手） | -| amount | `float` | 成交额（元） | -| bid1~bid5 | `float` | 买一到买五价 | -| bid_vol1~bid_vol5 | `float` | 买一到买五量 | -| ask1~ask5 | `float` | 卖一到卖五价 | -| ask_vol1~ask_vol5 | `float` | 卖一到卖五量 | -| s_vol | `float` | 内盘（主动卖） | -| b_vol | `float` | 外盘（主动买） | -| rise_speed | `float` | 涨速 | -| server_time | `str` | 服务器时间 | - -### SecurityBar - -K 线数据。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| open | `float` | 开盘价 | -| close | `float` | 收盘价 | -| high | `float` | 最高价 | -| low | `float` | 最低价 | -| vol | `float` | 成交量（股） | -| amount | `float` | 成交额（元） | -| year | `int` | 年 | -| month | `int` | 月 | -| day | `int` | 日 | -| hour | `int` | 时 | -| minute | `int` | 分 | -| datetime_str | `str` | 属性，格式化时间字符串 | - -### MinuteBar - -分时数据。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| price | `float` | 价格 | -| vol | `int` | 成交量 | - -### TransactionRecord - -逐笔成交。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| hour | `int` | 时 | -| minute | `int` | 分 | -| price | `float` | 成交价 | -| vol | `int` | 成交量 | -| buyorsell | `int` | 方向（0=买, 1=卖, 2=中性, 8=集合竞价） | - -### XdxrRecord - -除权除息记录。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| market | `Market` | 市场 | -| code | `str` | 代码 | -| year/month/day | `int` | 日期 | -| category | `int` | 事件类型（见 XDXR_CATEGORY_NAMES） | -| fenhong | `float \| None` | 每股分红（元） | -| peigujia | `float \| None` | 配股价 | -| songzhuangu | `float \| None` | 每股送转股比例 | -| peigu | `float \| None` | 每股配股比例 | - -### FinanceInfo - -最新财务数据。包含股本结构（流通股本、总股本、国家股等）、资产负债（总资产、净资产等）、利润指标（主营收入、净利润等）和每股指标。字段名使用拼音，完整列表见源码 `models/finance.py`。 - -### CompanyInfoCategory - -公司信息文件目录。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| name | `str` | 目录名 | -| filename | `str` | 文件名 | -| start | `int` | 起始偏移 | -| length | `int` | 内容长度 | - -### TdxBlock - -板块信息。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| name | `str` | 板块名称 | -| category | `int` | 分类（0=行业, 1=地域, 2=概念, 3=风格） | -| count | `int` | 成分股数量 | -| codes | `list[str]` | 成分股代码列表 | - -### MarketStat - -市场统计。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| up_count | `int` | 上涨家数 | -| down_count | `int` | 下跌家数 | -| neutral_count | `int` | 平盘家数 | -| suspended_count | `int` | 停牌估算 | -| total_count | `int` | 总计 | -| total_amount | `float` | 总成交额 | -| total_volume | `float` | 总成交量 | -| total_market_cap | `float` | 总市值（元），来自 880001 收盘价 | -| limit_up_count | `int` | 涨停家数，来自 880006 close | -| limit_down_count | `int` | 跌停家数，来自 880006 open | - -### FundFlow - -资金流向。 - -| 字段 | 类型 | 说明 | -|------|------|------| -| super_in / super_out | `float` | 超大单流入/流出 | -| large_in / large_out | `float` | 大单流入/流出 | -| medium_in / medium_out | `float` | 中单流入/流出 | -| small_in / small_out | `float` | 小单流入/流出 | -| main_net_inflow | `float` | 属性：主力净流入（超大+大） | -| total_net_inflow | `float` | 属性：全单净流入 | - -### HistoricalFundFlow - -历史日线资金流向。字段同 FundFlow，额外包含 `year`/`month`/`day` 日期字段。 - ---- - -## 枚举 - -### Market - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | SZ | 深圳 | -| 1 | SH | 上海 | -| 2 | BJ | 北京 | - -### KlineCategory - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | MIN_5 | 5 分钟 | -| 1 | MIN_15 | 15 分钟 | -| 2 | MIN_30 | 30 分钟 | -| 3 | MIN_60 | 60 分钟 | -| 4 | DAY | 日线 | -| 5 | WEEK | 周线 | -| 6 | MONTH | 月线 | -| 7 | MIN_1 | 1 分钟 | -| 8 | MIN_3 | 3 分钟（内部用） | -| 9 | YEAR | 年线 | -| 10 | SEASON | 季线 | -| 11 | YEAR_ALT | 年线（备用） | - ---- - ## 异常 所有异常继承自 `TdxError`。 @@ -640,65 +435,44 @@ compute_price_limits(market, code, name, pre_close, listed_days=None) | `KNOWN_EX_HOSTS` | `list[str]` | 扩展行情服务器列表 | | `XDXR_CATEGORY_NAMES` | `dict[int, str]` | 除权除息事件类型映射 | ---- +## 完整 API 列表（MAC 协议客户端） -## WebSocket 实时行情（serve /ws/realtime/*） +### MacClient / AsyncMacClient -`easy-tdx serve` 后可建立 WebSocket 连接（v1.28 起联动 `RealtimeDataFeed`，此前 -该端点不推送数据）： +| 方法 | 说明 | +|------|------| +| `get_stock_quotes(stocks, fields)` | 批量实时报价 | +| `get_stock_quotes_list(category, ...)` | 市场分类排序报价 | +| `get_stock_kline(market, code, period, ...)` | K 线（支持复权） | +| `get_stock_kline_with_indicators(market, code, indicators, ...)` | K 线 + 技术指标 | +| `get_tick_chart(market, code, date)` | 单日分时图 | +| `get_tick_charts(market, code, days)` | 多日分时图 | +| `get_chart_sampling(market, code)` | 分时缩略采样 | +| `get_transactions(market, code, ...)` | 逐笔成交 | +| `get_symbol_info(market, code)` | 个股特征快照 | +| `get_board_list(board_type, ..., sort_column)` | 板块列表（sort_value 列=排序键指标值） | +| `get_board_members(board_symbol, ...)` | 板块成分股报价 | +| `get_board_summary(board_symbol, ...)` | 板块汇总（成交额、主力净流入、涨跌家数） | +| `get_board_ranking(board_type, top_n, sort_by, ...)` | 板块涨跌幅排行榜（行业/概念排行） | +| `get_board_change_ranking(board_type, target_date, days, ...)` | 板块 N 日涨跌幅排行 | +| `get_belong_board(market, code)` | 个股所属板块 | +| `get_capital_flow(market, code)` | 资金流向 | +| `get_auction(market, code)` | 集合竞价 | +| `get_unusual(market, ...)` | 市场异动 | +| `get_server_info()` | 服务器交易时段 | +| `get_kline_offset(offset, count)` | K 线偏移信息 | +| `get_goods_list(market, ...)` | 扩展市场商品列表 | -``` -ws://127.0.0.1:8000/api/v1/ws/realtime/{symbol} # symbol 如 SZ000001 / SH600519 -``` +### MacExClient / AsyncMacExClient -### 服务端推送帧（JSON） +| 方法 | 说明 | +|------|------| +| `goods_count(market)` | 商品总数 | +| `goods_list(market, start, count)` | 商品列表 | +| `goods_quotes(stocks, fields)` | 批量报价 | +| `goods_quotes_list(market, ...)` | 市场分类报价列表 | +| `goods_kline(market, code, period, ...)` | K 线（支持复权） | +| `goods_tick_chart(market, code, ...)` | 分时图 | +| `goods_chart_sampling(market, code)` | 分时缩略采样 | +| `goods_transaction(market, code, ...)` | 逐笔成交 | -| type | 触发 | 字段 | -|------|------|------| -| `tick` | 轮询到标的的最新快照（价格/量变化才推，约 `interval` 秒一拍） | `symbol`、`market`、`code`、`price`、`volume`、`ts`（epoch 秒）、`open`、`high`、`low`、`pre_close`、`amount`、`name` | -| `ping` | 连续 30s 未收到客户端消息的心跳 | —（客户端忽略即可，无须回包） | -| `status` | 客户端 subscribe/unsubscribe 的确认 | `msg`（如 `subscribed SH600000`） | -| `error` | 非法 JSON / 未知 action / 超出订阅上限 | `msg` | - -### 客户端控制消息（JSON 文本帧） - -```json -{"action": "subscribe", "symbol": "SH600000"} -{"action": "unsubscribe", "symbol": "SH600000"} -``` - -### 行为约定 - -- **连接即订阅** path 上的 symbol；断开自动退订全部标的。 -- **按需轮询**：订阅集合为空时服务端不产生任何行情请求；去重后标的总数上限 - 80（`get_stock_quotes` 协议约束）。 -- **交易时段**：默认 A 股时段外只睡不拉（无 tick 帧，心跳照发）；mock 模式 - （`EASY_TDX_E2E_MOCK=1`）不受限制。 -- **背压**：消费过慢时丢最旧快照保最新，不积压。 -- 环境变量：`EASY_TDX_WS_INTERVAL`（轮询间隔秒数，默认 3.0）。 - -### 前端接入方式（自动重连 + 心跳容忍） - -```typescript -function connectRealtime(symbol: string, onTick: (f: TickFrame) => void) { - let retry = 0 - let ws: WebSocket | null = null - const open = () => { - ws = new WebSocket(`ws://${location.host}/api/v1/ws/realtime/${symbol}`) - ws.onmessage = (e) => { - const frame = JSON.parse(e.data) - if (frame.type === 'tick') { retry = 0; onTick(frame) } // ping/status 忽略 - } - ws.onclose = () => { - retry += 1 - setTimeout(open, Math.min(1000 * 2 ** (retry - 1), 30_000)) // 指数退避 - } - } - open() - return () => ws?.close() -} -``` - -> 说明：看板/自选页的实时刷新已由 SSE `/stream/quotes`（全量快照、单连接共享） -> 承担；WS 通道定位是**按需订阅单标的 tick 事件**（后续实时策略信号的接入点）， -> 两条链路按场景选用，不要求同时连接。手动冒烟见 `scripts/ws_smoke.py`。 diff --git a/docs/backtest-examples.md b/docs/backtest-examples.md new file mode 100644 index 0000000..9c7ab3d --- /dev/null +++ b/docs/backtest-examples.md @@ -0,0 +1,153 @@ +# 回测完整示例集 + +本文件汇集回测引擎的完整可运行示例与注意事项，配合 [backtest_usage.md](./backtest_usage.md)（手册）与 [cli-backtest.md](./cli-backtest.md)（CLI 参考）使用。 + +## 完整示例 + +### 示例 1：双均线交叉策略 + +```python +"""双均线交叉策略：MA5 上穿 MA20 买入，下穿卖出。""" +import pandas as pd +from easy_tdx.backtest import BacktestEngine, Strategy, crossover +from easy_tdx import MyTT + + +class DualMACross(Strategy): + def init(self): + self.ma5 = self.I(MyTT.MA, self.data.close, 5) + self.ma20 = self.I(MyTT.MA, self.data.close, 20) + self.golden = crossover(self.ma5, self.ma20) + self.death = crossover(self.ma20, self.ma5) + + def next(self): + if self.golden[self._bar_index] and self.position["size"] == 0: + self.buy(size=0) + elif self.death[self._bar_index] and self.position["size"] > 0: + self.sell(size=0) + + +# 构造模拟数据（实际使用 TdxClient 获取） +dates = pd.date_range("2024-01-01", periods=200, freq="D") +import numpy as np +rng = np.random.default_rng(42) +close = 10.0 + np.cumsum(rng.normal(0, 0.2, 200)) + +df = pd.DataFrame({ + "datetime": dates, + "open": close + rng.uniform(-0.1, 0.1, 200), + "close": close, + "high": close + rng.uniform(0, 0.3, 200), + "low": close - rng.uniform(0, 0.3, 200), + "vol": rng.integers(10000, 100000, 200), +}) + +engine = BacktestEngine(DualMACross, cash=100000, commission=0.0003) +result = engine.run(df) + +result.summary() +print(f"\n年化收益: {result.performance['annual_return']:.2%}") +print(f"夏普比率: {result.performance['sharpe']:.2f}") +``` + +### 示例 2：MACD 策略 + 预计算指标 + +```python +"""MACD 策略：DIF 上穿 DEA 买入，下穿卖出。""" +from easy_tdx.backtest import BacktestEngine, Strategy, crossover +from easy_tdx import MyTT + + +class MACDStrategy(Strategy): + def init(self): + dif, dea, macd_hist = self.I(MyTT.MACD, self.data.close) + self.dif = dif + self.dea = dea + self.golden = crossover(dif, dea) + self.death = crossover(dea, dif) + + def next(self): + if self.golden[self._bar_index] and self.position["size"] == 0: + self.buy(size=0) + elif self.death[self._bar_index] and self.position["size"] > 0: + self.sell(size=0) + + +engine = BacktestEngine(MACDStrategy, cash=100000) +result = engine.run(df) # df 包含 OHLCV 数据 +``` + +### 示例 3：布林带突破 + 滑点模拟 + +```python +"""布林带策略：跌破下轨买入，突破上轨卖出，模拟滑点。""" +from easy_tdx.backtest import BacktestEngine, Strategy +from easy_tdx import MyTT + + +class BollingerBreakout(Strategy): + def init(self): + upper, mid, lower = self.I(MyTT.BOLL, self.data.close, 20) + self.upper = upper + self.lower = lower + + def next(self): + cur = self.data.close[0] + if cur <= self.lower[self._bar_index] and self.position["size"] == 0: + self.buy(size=0) + elif cur >= self.upper[self._bar_index] and self.position["size"] > 0: + self.sell(size=0) + + +# 模拟滑点和保守成交价 +engine = BacktestEngine( + BollingerBreakout, + cash=100000, + slippage=0.02, # 每股 2 分钱滑点 + execution="worst", # 保守成交价 + reject_policy="skip", # 资金不足直接跳过 +) +result = engine.run(df) +``` + +### 示例 4：从文件运行 CLI + +```python +# save as rsi_strategy.py +from easy_tdx.backtest import Strategy +from easy_tdx import MyTT + + +class RSIStrategy(Strategy): + """RSI 超卖超买策略。""" + def init(self): + self.rsi = self.I(MyTT.RSI, self.data.close, 14) + + def next(self): + cur_rsi = self.rsi[self._bar_index] + if cur_rsi < 30 and self.position["size"] == 0: + self.buy(size=0) + elif cur_rsi > 70 and self.position["size"] > 0: + self.sell(size=0) +``` + +```bash +easy-tdx backtest SZ 000001 \ + --strategy-file rsi_strategy.py \ + --cash 200000 \ + --execution next_open \ + --count 1000 \ + --adjust QFQ \ + --table +``` + +--- + +## 注意事项 + +1. **DataFrame 格式要求**：必须包含 `datetime`, `open`, `close`, `high`, `low` 列。`vol`/`amount` 为可选但推荐。 +2. **成交时机**：默认 `next_open` 模式下，信号产生后需等待下一根 K 线才能成交。如果信号在最后一根 K 线产生，则无法成交。 +3. **整手交易**：A 股按 100 股整手交易。全仓模式会自动向下取整到 100 的倍数。 +4. **做空限制**：v1 不支持做空，卖出数量不能超过当前持仓。 +5. **未来函数警告**：使用 `this_close` 模式时，结果中的 `config.future_leak_warning` 会标记为 `True`。 +6. **多笔同 bar 交易**：引擎支持同一根 K 线上产生多笔交易（如分批建仓），按顺序依次撮合。 diff --git a/docs/backtest_usage.md b/docs/backtest_usage.md index dca7046..5a05ed6 100644 --- a/docs/backtest_usage.md +++ b/docs/backtest_usage.md @@ -21,15 +21,12 @@ - [资金曲线](#资金曲线) - [交易记录](#交易记录) - [序列化输出](#序列化输出) -- [CLI 命令行](#cli-命令行) - - [内置策略列表（strategies）](#内置策略列表strategies) - - [参数网格寻优（optimize）](#参数网格寻优optimize) - - [组合级分析（portfolio）](#组合级分析portfolio) +- [CLI 命令行](#cli-命令行) → 见 [cli-backtest.md](./cli-backtest.md) - [进阶用法](#进阶用法) - [预计算指标列](#预计算指标列) - [缠论结果注入](#缠论结果注入) - [自定义策略文件](#自定义策略文件) -- [完整示例](#完整示例) +- [完整示例](#完整示例) → 见 [backtest-examples.md](./backtest-examples.md) --- @@ -392,115 +389,10 @@ config = result.config --- + ## CLI 命令行 -```bash -# 基本用法 -easy-tdx backtest SZ 000001 --strategy-file my_strategy.py - -# 查看帮助 -easy-tdx backtest --help - -# 指定参数 -easy-tdx backtest SH 600519 \ - --strategy-file ma_cross.py \ - --cash 50000 \ - --commission 0.0003 \ - --execution next_open \ - --period DAILY \ - --count 500 \ - --table - -# 预计算指标（MACD, KDJ 会作为额外列注入 DataFrame） -easy-tdx backtest SZ 000001 \ - --strategy-file macd_strategy.py \ - --indicators MACD,KDJ - -# 输出 JSON（默认） -easy-tdx backtest SZ 000001 --strategy-file my_strategy.py - -# 输出表格 -easy-tdx backtest SZ 000001 --strategy-file my_strategy.py --table -``` - -**CLI 参数**： - -| 参数 | 默认值 | 说明 | -|------|--------|------| -| `MARKET` | — | 市场代码：SZ / SH | -| `CODE` | — | 股票代码：如 000001 | -| `--strategy-file` | — | Python 策略文件路径 | -| `--strategy` | — | DSL 表达式（P1，尚未实现） | -| `--cash` | 100000 | 初始资金 | -| `--commission` | 0.0003 | 佣金率 | -| `--execution` | next_open | 成交价规则 | -| `--period` | DAILY | K 线周期 | -| `--adjust` | NONE | 复权方式：NONE / QFQ / HFQ | -| `--count` | 500 | K 线数量 | -| `--indicators` | — | 预计算指标（逗号分隔） | -| `--table` | False | 表格输出 | -| `--output` | json | 输出格式：json / table / csv | -| `--wf` | False | 附加 Walk-Forward 样本外验证 | -| `--wf-windows` | 7 | Walk-Forward 窗口数 | -| `--evaluate` | False | 一条龙评估（回测+WF+适配性+评分+评级+基准对比） | -| `--auto-fees` | False | 按标的品种自动解析费率 | - -### 内置策略列表（strategies） - -```bash -# 表格列出全部内置策略（名称/参数/预设寻优网格） -easy-tdx strategies - -# JSON 输出（含完整参数 schema，与 Web API GET /backtest/strategies 同构） -easy-tdx strategies --output json -``` - -### 参数网格寻优（optimize） - -对注册表内置策略的 1-2 个参数做网格搜索，按总收益率排名： - -```bash -# 单策略：用该策略的预设寻优网格（见 strategies 命令） -easy-tdx optimize SZ 000001 --strategy ma_cross - -# 单策略：自定义网格（--param 参数名=值1,值2，可多次指定） -easy-tdx optimize SZ 000001 --strategy ma_cross --param fast=5,10,15 --param slow=20,60 - -# 一键寻优所有内置策略：逐策略按预设网格寻优后全局排名 -easy-tdx optimize SZ 000001 --all - -# 并行加速（2+ 进程级并行；1 = 串行 + 指标缓存复用） -easy-tdx optimize SZ 000001 --all --workers 4 -``` - -**optimize 参数**： - -| 参数 | 默认值 | 说明 | -|------|--------|------| -| `--strategy` | — | 注册表策略名（与 `--all` 二选一） | -| `--all` | False | 一键寻优所有内置策略（STRATEGY_PRESETS 预设网格） | -| `--param` | 预设网格 | 自定义参数网格，如 `fast=5,10,15`（最多 2 个参数，笛卡尔积 ≤ 200） | -| `--cash` | 1000000 | 初始资金 | -| `--commission` | 0.0003 | 佣金率 | -| `--slippage` | 0.0 | 滑点 | -| `--workers` | 1 | 并行进程数 | -| `--top` | 15 | 表格输出显示前 N 行 | - -Python API 同名能力：`easy_tdx.backtest.optimizer.ParamGridOptimizer`（单策略）与 -`easy_tdx.backtest.optimizer.optimize_all_strategies`（一键全策略）。 - -### 组合级分析（portfolio） - -```bash -# 组合级 Walk-Forward 样本外验证（全部标的日期并集切窗，每窗独立开仓） -easy-tdx portfolio --stocks SZ:000001,SH:600519 --strategy-file strategies/ma_cross.py --wf --wf-windows 7 - -# 组合级一条龙评估：组合回测 + 组合WF + 跨标的适配性 + 综合评分 -# + 组合评级 + 等权买入持有基准对比（与 Web UI /portfolio 页同构） -easy-tdx portfolio --stocks SZ:000001,SH:600519 --strategy-file strategies/ma_cross.py --evaluate -``` - ---- +CLI 用法见 [cli-backtest.md](./cli-backtest.md)（回测/寻优/组合/run-all 命令与参数）。 ## 进阶用法 @@ -591,152 +483,3 @@ easy-tdx backtest SZ 000001 --strategy-file my_strategy.py --table --- -## 完整示例 - -### 示例 1：双均线交叉策略 - -```python -"""双均线交叉策略：MA5 上穿 MA20 买入，下穿卖出。""" -import pandas as pd -from easy_tdx.backtest import BacktestEngine, Strategy, crossover -from easy_tdx import MyTT - - -class DualMACross(Strategy): - def init(self): - self.ma5 = self.I(MyTT.MA, self.data.close, 5) - self.ma20 = self.I(MyTT.MA, self.data.close, 20) - self.golden = crossover(self.ma5, self.ma20) - self.death = crossover(self.ma20, self.ma5) - - def next(self): - if self.golden[self._bar_index] and self.position["size"] == 0: - self.buy(size=0) - elif self.death[self._bar_index] and self.position["size"] > 0: - self.sell(size=0) - - -# 构造模拟数据（实际使用 TdxClient 获取） -dates = pd.date_range("2024-01-01", periods=200, freq="D") -import numpy as np -rng = np.random.default_rng(42) -close = 10.0 + np.cumsum(rng.normal(0, 0.2, 200)) - -df = pd.DataFrame({ - "datetime": dates, - "open": close + rng.uniform(-0.1, 0.1, 200), - "close": close, - "high": close + rng.uniform(0, 0.3, 200), - "low": close - rng.uniform(0, 0.3, 200), - "vol": rng.integers(10000, 100000, 200), -}) - -engine = BacktestEngine(DualMACross, cash=100000, commission=0.0003) -result = engine.run(df) - -result.summary() -print(f"\n年化收益: {result.performance['annual_return']:.2%}") -print(f"夏普比率: {result.performance['sharpe']:.2f}") -``` - -### 示例 2：MACD 策略 + 预计算指标 - -```python -"""MACD 策略：DIF 上穿 DEA 买入，下穿卖出。""" -from easy_tdx.backtest import BacktestEngine, Strategy, crossover -from easy_tdx import MyTT - - -class MACDStrategy(Strategy): - def init(self): - dif, dea, macd_hist = self.I(MyTT.MACD, self.data.close) - self.dif = dif - self.dea = dea - self.golden = crossover(dif, dea) - self.death = crossover(dea, dif) - - def next(self): - if self.golden[self._bar_index] and self.position["size"] == 0: - self.buy(size=0) - elif self.death[self._bar_index] and self.position["size"] > 0: - self.sell(size=0) - - -engine = BacktestEngine(MACDStrategy, cash=100000) -result = engine.run(df) # df 包含 OHLCV 数据 -``` - -### 示例 3：布林带突破 + 滑点模拟 - -```python -"""布林带策略：跌破下轨买入，突破上轨卖出，模拟滑点。""" -from easy_tdx.backtest import BacktestEngine, Strategy -from easy_tdx import MyTT - - -class BollingerBreakout(Strategy): - def init(self): - upper, mid, lower = self.I(MyTT.BOLL, self.data.close, 20) - self.upper = upper - self.lower = lower - - def next(self): - cur = self.data.close[0] - if cur <= self.lower[self._bar_index] and self.position["size"] == 0: - self.buy(size=0) - elif cur >= self.upper[self._bar_index] and self.position["size"] > 0: - self.sell(size=0) - - -# 模拟滑点和保守成交价 -engine = BacktestEngine( - BollingerBreakout, - cash=100000, - slippage=0.02, # 每股 2 分钱滑点 - execution="worst", # 保守成交价 - reject_policy="skip", # 资金不足直接跳过 -) -result = engine.run(df) -``` - -### 示例 4：从文件运行 CLI - -```python -# save as rsi_strategy.py -from easy_tdx.backtest import Strategy -from easy_tdx import MyTT - - -class RSIStrategy(Strategy): - """RSI 超卖超买策略。""" - def init(self): - self.rsi = self.I(MyTT.RSI, self.data.close, 14) - - def next(self): - cur_rsi = self.rsi[self._bar_index] - if cur_rsi < 30 and self.position["size"] == 0: - self.buy(size=0) - elif cur_rsi > 70 and self.position["size"] > 0: - self.sell(size=0) -``` - -```bash -easy-tdx backtest SZ 000001 \ - --strategy-file rsi_strategy.py \ - --cash 200000 \ - --execution next_open \ - --count 1000 \ - --adjust QFQ \ - --table -``` - ---- - -## 注意事项 - -1. **DataFrame 格式要求**：必须包含 `datetime`, `open`, `close`, `high`, `low` 列。`vol`/`amount` 为可选但推荐。 -2. **成交时机**：默认 `next_open` 模式下，信号产生后需等待下一根 K 线才能成交。如果信号在最后一根 K 线产生，则无法成交。 -3. **整手交易**：A 股按 100 股整手交易。全仓模式会自动向下取整到 100 的倍数。 -4. **做空限制**：v1 不支持做空，卖出数量不能超过当前持仓。 -5. **未来函数警告**：使用 `this_close` 模式时，结果中的 `config.future_leak_warning` 会标记为 `True`。 -6. **多笔同 bar 交易**：引擎支持同一根 K 线上产生多笔交易（如分批建仓），按顺序依次撮合。 diff --git a/docs/field_mapping.md b/docs/field_mapping.md index 42aa4c3..a180efa 100644 --- a/docs/field_mapping.md +++ b/docs/field_mapping.md @@ -1,6 +1,6 @@ # easy_tdx 字段映射表 -> 模型字段名 ↔ 中文含义 ↔ 数据类型对照 +> 模型字段名 ↔ 中文含义 ↔ 数据类型对照。方法速查见 [api_reference.md](./api_reference.md)，上手教程见 [python-api.md](./python-api.md)。 --- @@ -313,3 +313,76 @@ | 9 | YEAR | 年线 | | 10 | SEASON | 季线 | | 11 | YEAR_ALT | 年线（备用） | + +## 枚举参考 + +### Period（K 线周期） + +| 值 | 名称 | 说明 | +|----|------|------| +| 7 | `MIN_1` | 1 分钟 | +| 0 | `MIN_5` | 5 分钟 | +| 1 | `MIN_15` | 15 分钟 | +| 2 | `MIN_30` | 30 分钟 | +| 3 | `MIN_60` | 60 分钟 | +| 4 | `DAILY` | 日线 | +| 5 | `WEEKLY` | 周线 | +| 6 | `MONTHLY` | 月线 | +| 10 | `QUARTERLY` | 季线 | +| 11 | `YEARLY` | 年线 | + +### Adjust（复权类型） + +| 值 | 名称 | 说明 | +|----|------|------| +| 0 | `NONE` | 不复权 | +| 1 | `QFQ` | 前复权 | +| 2 | `HFQ` | 后复权 | + +### Category（市场分类） + +| 值 | 名称 | 说明 | +|----|------|------| +| 0 | `SH` | 上证 A 股 | +| 2 | `SZ` | 深证 A 股 | +| 6 | `A` | 全部 A 股 | +| 7 | `B` | B 股 | +| 8 | `KCB` | 科创板 | +| 12 | `BJ` | 北证 A 股 | +| 14 | `CYB` | 创业板 | + +### BoardType（板块类型） + +| 值 | 名称 | 说明 | +|----|------|------| +| 0 | `HY` | 行业一级 | +| 1 | `HY2` | 行业二级 | +| 3 | `GN` | 概念 | +| 4 | `FG` | 风格 | +| 5 | `DQ` | 地区 | +| 255 | `ALL` | 全部 | + +### SortType（排序字段） + +| 名称 | 说明 | +|------|------| +| `CODE` | 代码 | +| `PRICE` | 现价 | +| `CHANGE_PCT` | 涨幅% | +| `VOLUME` | 成交量 | +| `TOTAL_AMOUNT` | 成交额 | +| `TURNOVER_RATE` | 换手% | +| `MAIN_NET_AMOUNT` | 主力净额 | + +### ExMarket（扩展市场） + +| 值 | 名称 | 说明 | +|----|------|------| +| 28 | `ZZ_FUTURES` | 郑州商品 | +| 29 | `DL_FUTURES` | 大连商品 | +| 30 | `SH_FUTURES` | 上海期货 | +| 31 | `HK_MAIN_BOARD` | 香港主板 | +| 47 | `CFFEX_FUTURES` | 中金所期货 | +| 48 | `HK_GEM` | 香港创业板 | +| 74 | `US_STOCK` | 美国股票 | + diff --git a/docs/quantitative-advanced.md b/docs/quantitative-advanced.md new file mode 100644 index 0000000..95fcbe6 --- /dev/null +++ b/docs/quantitative-advanced.md @@ -0,0 +1,308 @@ +# 量化进阶：执行仿真与归因 + +滑点建模、执行仿真（TWAP/VWAP/限价单）、归因分析与完整工作流。因子/组合基础见 [quantitative-guide.md](./quantitative-guide.md)。 + +## 1. 高级回测 + +### 1.1 滑点模型 + +4 种可插拔滑点模型，替代原有固定滑点： + +```python +from easy_tdx.backtest import BacktestEngine +from easy_tdx.backtest.slippage import ( + FixedSlippage, + PercentSlippage, + SquareRootSlippage, + VolumeSlippage, +) + +# 1. 固定每股滑点（与旧行为一致） +model1 = FixedSlippage(per_share=0.01) + +# 2. 按金额百分比 +model2 = PercentSlippage(rate=0.001) + +# 3. 方根市场冲击模型（Almgren-Chriss 简化版） +# impact = sigma * sqrt(participation_rate) * price * size * coeff +# A 股量化主流：参与率 >5% 时冲击显著 +model3 = SquareRootSlippage(impact_coeff=0.1) + +# 4. 成交量比例滑点 +model4 = VolumeSlippage(base_bps=10.0) + +# 在 BacktestEngine 中使用 +engine = BacktestEngine( + MyStrategy, + cash=1_000_000, + slippage_model=SquareRootSlippage(impact_coeff=0.1), +) +result = engine.run(df) +``` + +**模型选择建议**： + +| 场景 | 推荐模型 | 参数 | +|------|---------|------| +| 快速原型 | `FixedSlippage` | `per_share=0.01` | +| 中频策略 | `PercentSlippage` | `rate=0.001` | +| 大额订单 | `SquareRootSlippage` | `impact_coeff=0.1` | +| 低流动性股票 | `VolumeSlippage` | `base_bps=10.0` | + +### 1.2 执行仿真 + +4 种执行模型，将单笔信号拆分为多笔子交易： + +```python +from easy_tdx.backtest.execution import ( + ImmediateExecution, + TWAPExecution, + VWAPExecution, + LimitExecution, +) + +# 1. 即时成交（默认，与旧行为一致） +exec1 = ImmediateExecution() + +# 2. TWAP：时间加权平均价格，N 根 K 线均匀拆单 +exec2 = TWAPExecution(n_bars=5) + +# 3. VWAP：成交量加权平均价格，按历史量分布拆单 +exec3 = VWAPExecution(n_bars=5, volume_lookback=20) + +# 4. 限价单：目标价挂单，TTL 内未触发则放弃 +exec4 = LimitExecution(ttl_bars=5) + +# 在 BacktestEngine 中使用 +engine = BacktestEngine( + MyStrategy, + cash=1_000_000, + execution_model=TWAPExecution(n_bars=3), + slippage_model=SquareRootSlippage(), +) +result = engine.run(df) +``` + +**执行模型选择**： + +| 场景 | 推荐模型 | 参数 | +|------|---------|------| +| 小额/快速验证 | `ImmediateExecution` | 默认 | +| 大额建仓/平仓 | `TWAPExecution` | `n_bars=3~5` | +| 追踪 VWAP 基准 | `VWAPExecution` | `n_bars=5` | +| 精确入场价位 | `LimitExecution` | `ttl_bars=5` | + +**TWAP vs VWAP 示例**： + +```python +# TWAP: 300 股拆成 3 笔 100 股，在 bar 1/2/3 以 close 执行 +engine = BacktestEngine( + MyStrategy, cash=100_000, + execution_model=TWAPExecution(n_bars=3), +) + +# VWAP: 按成交量分布拆 300 股 — 成交量大的 bar 分配更多 +engine = BacktestEngine( + MyStrategy, cash=100_000, + execution_model=VWAPExecution(n_bars=3, volume_lookback=20), +) + +# 限价单：在 50 元挂买入，5 根 K 线内 low <= 50 才成交 +class LimitBuyStrategy(Strategy): + def init(self): pass + def next(self): + if self._bar_index == 0: + self.buy(size=100, price=50.0) # 指定限价 + +engine = BacktestEngine( + LimitBuyStrategy, cash=100_000, + execution_model=LimitExecution(ttl_bars=5), +) +``` + +### 1.3 归因分析 + +从回测结果生成归因报告： + +```python +from easy_tdx.backtest import BacktestEngine +from easy_tdx.backtest.attribution import AttributionAnalyzer + +# 运行回测 +engine = BacktestEngine(MyStrategy, cash=1_000_000) +result = engine.run(df) + +# --- 成本归因 --- +analyzer = AttributionAnalyzer(result.trades, result.equity_curve) +cost_report = analyzer.cost_attribution() +print(f"总收益: {cost_report.total_return:.2%}") +print(f"总交易成本: {cost_report.total_trade_cost:.0f} 元") +print(f" 佣金: {cost_report.commission_cost:.0f}") +print(f" 滑点: {cost_report.slippage_cost:.0f}") +print(f" 印花税: {cost_report.stamp_tax_cost:.0f}") + +# --- Brinson 归因（需要基准）--- +import numpy as np +import pandas as pd +# 构造基准曲线（如沪深300） +benchmark = pd.DataFrame({ + "datetime": result.equity_curve["datetime"], + "total": np.linspace(100000, 108000, len(result.equity_curve)), +}) +analyzer = AttributionAnalyzer(result.trades, result.equity_curve, benchmark=benchmark) +brinson_report = analyzer.brinson_attribution() +print(f"配置贡献: {brinson_report.allocation_return:.2%}") +print(f"选股贡献: {brinson_report.selection_return:.2%}") +print(f"交叉效应: {brinson_report.interaction_return:.2%}") + +# --- 因子归因（需要因子数据）--- +exposures = pd.DataFrame({"momentum": [0.5, 0.3, 0.2], "quality": [0.1, -0.1, 0.0]}) +returns = pd.DataFrame({"momentum": [0.05, 0.03, 0.02], "quality": [0.01, -0.02, 0.0]}) +analyzer = AttributionAnalyzer( + result.trades, result.equity_curve, + factor_exposures=exposures, factor_returns=returns, +) +factor_report = analyzer.factor_attribution() +for name, ret in factor_report.factor_returns.items(): + print(f" {name}: {ret:.4f}") +print(f"特质收益: {factor_report.specific_return:.4f}") + +# --- 完整报告（自动选择最佳归因模式）--- +full_report = analyzer.full_report() +``` + +**归因模式优先级**：因子归因 > Brinson 归因 > 成本归因。`full_report()` 自动选择数据最完整的模式。 + +--- + +## 2. CLI 命令 + +```bash +# 列出所有内置因子 +easy-tdx factor list --table + +# 因子分析（需要数据，输出示例代码） +easy-tdx factor analyze momentum_20d + +# 组合因子回测（需要数据，输出示例代码） +easy-tdx pfactor backtest momentum_20d --n-stocks 10 --optimizer factor_weighted +``` + +CLI 命令输出 Python API 示例代码，方便复制使用。完整的因子计算和组合回测建议通过 Python API 完成。 + +--- + +## 3. 完整工作流示例 + +从数据获取到组合回测再到归因分析的完整管道： + +```python +""" +easy-tdx 量化研究完整工作流示例。 + +依赖: pip install easy-tdx +""" + +from easy_tdx import TdxClient, Market, KlineCategory +from easy_tdx.factor import FactorEngine, FactorAnalyzer, preprocess +from easy_tdx.portfolio import RebalanceEngine, FactorWeightedOptimizer +from easy_tdx.backtest import BacktestEngine +from easy_tdx.backtest.slippage import SquareRootSlippage +from easy_tdx.backtest.execution import TWAPExecution +from easy_tdx.backtest.attribution import AttributionAnalyzer + +# ── 1. 数据获取 ────────────────────────────────────── +client = TdxClient() +stock_pool = ["000001", "000858", "600519", "600036", "601318", + "000333", "002415", "601012", "600276", "000568"] + +data = {} +for code in stock_pool: + market = Market.SH if code.startswith("6") else Market.SZ + data[code] = client.get_security_bars( + market, code, KlineCategory.DAY, 0, 500 + ) +print(f"获取 {len(data)} 只股票数据") + +# ── 2. 因子计算 ────────────────────────────────────── +engine = FactorEngine() +factor_data = engine.compute_cross_section( + data, ["momentum_20d", "volatility_20d", "rsi_14"] +) +print(f"截面因子数据: {len(factor_data)} 行") + +# ── 3. 因子预处理 ───────────────────────────────────── +clean = preprocess( + factor_data, + factor_names=["momentum_20d", "volatility_20d", "rsi_14"], + steps=["winsorize", "zscore", "fill_missing"], +) + +# ── 4. 因子分析 ────────────────────────────────────── +forward_returns = engine.compute_forward_returns(data, period=5) + +for factor_name in ["momentum_20d", "volatility_20d", "rsi_14"]: + analyzer = FactorAnalyzer(clean, forward_returns) + report = analyzer.full_report(factor_name) + print(f"\n── {factor_name} ──") + print(f" IC均值: {report.mean_ic:.4f} ICIR: {report.icir:.4f}") + print(f" 多头年化: {report.long_only_annual:.2%}") + print(f" 多空夏普: {report.long_short_sharpe:.4f}") + +# ── 5. 组合回测 ────────────────────────────────────── +rebalancer = RebalanceEngine( + optimizer=FactorWeightedOptimizer(), + factor_name="momentum_20d", + n_stocks=5, + rebalance_freq="M", + cash=1_000_000, +) +result = rebalancer.run(data, start_date=20230101, end_date=20240101) +print(f"\n── 组合回测 ──") +print(f" 总收益: {result.performance['total_return']:.2%}") +print(f" 年化: {result.performance['annual_return']:.2%}") +print(f" 最大回撤: {result.performance['max_drawdown']:.2%}") +print(f" 夏普: {result.performance['sharpe']:.4f}") + +# ── 6. 高级单策略回测（滑点 + 执行仿真）────── +from easy_tdx.backtest import Strategy + +class MomentumStrategy(Strategy): + def init(self): + pass + def next(self): + if self._bar_index < 20: + return + ret = (self.data.close[0] - self.data.close[-20]) / self.data.close[-20] + if ret > 0.05 and self.position["size"] == 0: + self.buy(size=0) + elif ret < -0.03 and self.position["size"] > 0: + self.sell(size=0) + +bt_engine = BacktestEngine( + MomentumStrategy, + cash=500_000, + slippage_model=SquareRootSlippage(impact_coeff=0.1), + execution_model=TWAPExecution(n_bars=3), +) +# 选一只股票做回测 +bt_result = bt_engine.run(data["600519"]) +print(f"\n── 高级回测（600519）──") +print(f" 总收益: {bt_result.performance['total_return']:.2%}") +print(f" 夏普: {bt_result.performance['sharpe']:.4f}") + +# ── 7. 归因分析 ────────────────────────────────────── +att_analyzer = AttributionAnalyzer(bt_result.trades, bt_result.equity_curve) +cost_report = att_analyzer.cost_attribution() +print(f"\n── 成本归因 ──") +print(f" 总交易成本: {cost_report.total_trade_cost:.0f} 元") +print(f" 佣金: {cost_report.commission_cost:.0f}") +print(f" 滑点: {cost_report.slippage_cost:.0f}") +print(f" 印花税: {cost_report.stamp_tax_cost:.0f}") + +print("\n完成。") +client.close() +``` + +--- + diff --git a/docs/quantitative-guide.md b/docs/quantitative-guide.md index ad54f3e..3f00db2 100644 --- a/docs/quantitative-guide.md +++ b/docs/quantitative-guide.md @@ -18,12 +18,7 @@ - [4.1 权重优化器](#41-权重优化器) - [4.2 风险模型](#42-风险模型) - [4.3 再平衡引擎](#43-再平衡引擎) -- [5. 高级回测](#5-高级回测) - - [5.1 滑点模型](#51-滑点模型) - - [5.2 执行仿真](#52-执行仿真) - - [5.3 归因分析](#53-归因分析) -- [6. CLI 命令](#6-cli-命令) -- [7. 完整工作流示例](#7-完整工作流示例) +- [高级回测（滑点/执行仿真/归因）、CLI 与完整工作流](#高级回测滑点执行仿真归因cli-与完整工作流) → 见 [quantitative-advanced.md](./quantitative-advanced.md) --- @@ -309,309 +304,6 @@ for state in result.states[-5:]: --- -## 5. 高级回测 - -### 5.1 滑点模型 - -4 种可插拔滑点模型，替代原有固定滑点： - -```python -from easy_tdx.backtest import BacktestEngine -from easy_tdx.backtest.slippage import ( - FixedSlippage, - PercentSlippage, - SquareRootSlippage, - VolumeSlippage, -) - -# 1. 固定每股滑点（与旧行为一致） -model1 = FixedSlippage(per_share=0.01) - -# 2. 按金额百分比 -model2 = PercentSlippage(rate=0.001) - -# 3. 方根市场冲击模型（Almgren-Chriss 简化版） -# impact = sigma * sqrt(participation_rate) * price * size * coeff -# A 股量化主流：参与率 >5% 时冲击显著 -model3 = SquareRootSlippage(impact_coeff=0.1) - -# 4. 成交量比例滑点 -model4 = VolumeSlippage(base_bps=10.0) - -# 在 BacktestEngine 中使用 -engine = BacktestEngine( - MyStrategy, - cash=1_000_000, - slippage_model=SquareRootSlippage(impact_coeff=0.1), -) -result = engine.run(df) -``` - -**模型选择建议**： - -| 场景 | 推荐模型 | 参数 | -|------|---------|------| -| 快速原型 | `FixedSlippage` | `per_share=0.01` | -| 中频策略 | `PercentSlippage` | `rate=0.001` | -| 大额订单 | `SquareRootSlippage` | `impact_coeff=0.1` | -| 低流动性股票 | `VolumeSlippage` | `base_bps=10.0` | - -### 5.2 执行仿真 - -4 种执行模型，将单笔信号拆分为多笔子交易： - -```python -from easy_tdx.backtest.execution import ( - ImmediateExecution, - TWAPExecution, - VWAPExecution, - LimitExecution, -) - -# 1. 即时成交（默认，与旧行为一致） -exec1 = ImmediateExecution() - -# 2. TWAP：时间加权平均价格，N 根 K 线均匀拆单 -exec2 = TWAPExecution(n_bars=5) - -# 3. VWAP：成交量加权平均价格，按历史量分布拆单 -exec3 = VWAPExecution(n_bars=5, volume_lookback=20) - -# 4. 限价单：目标价挂单，TTL 内未触发则放弃 -exec4 = LimitExecution(ttl_bars=5) - -# 在 BacktestEngine 中使用 -engine = BacktestEngine( - MyStrategy, - cash=1_000_000, - execution_model=TWAPExecution(n_bars=3), - slippage_model=SquareRootSlippage(), -) -result = engine.run(df) -``` - -**执行模型选择**： - -| 场景 | 推荐模型 | 参数 | -|------|---------|------| -| 小额/快速验证 | `ImmediateExecution` | 默认 | -| 大额建仓/平仓 | `TWAPExecution` | `n_bars=3~5` | -| 追踪 VWAP 基准 | `VWAPExecution` | `n_bars=5` | -| 精确入场价位 | `LimitExecution` | `ttl_bars=5` | - -**TWAP vs VWAP 示例**： - -```python -# TWAP: 300 股拆成 3 笔 100 股，在 bar 1/2/3 以 close 执行 -engine = BacktestEngine( - MyStrategy, cash=100_000, - execution_model=TWAPExecution(n_bars=3), -) - -# VWAP: 按成交量分布拆 300 股 — 成交量大的 bar 分配更多 -engine = BacktestEngine( - MyStrategy, cash=100_000, - execution_model=VWAPExecution(n_bars=3, volume_lookback=20), -) - -# 限价单：在 50 元挂买入，5 根 K 线内 low <= 50 才成交 -class LimitBuyStrategy(Strategy): - def init(self): pass - def next(self): - if self._bar_index == 0: - self.buy(size=100, price=50.0) # 指定限价 - -engine = BacktestEngine( - LimitBuyStrategy, cash=100_000, - execution_model=LimitExecution(ttl_bars=5), -) -``` - -### 5.3 归因分析 - -从回测结果生成归因报告： - -```python -from easy_tdx.backtest import BacktestEngine -from easy_tdx.backtest.attribution import AttributionAnalyzer - -# 运行回测 -engine = BacktestEngine(MyStrategy, cash=1_000_000) -result = engine.run(df) - -# --- 成本归因 --- -analyzer = AttributionAnalyzer(result.trades, result.equity_curve) -cost_report = analyzer.cost_attribution() -print(f"总收益: {cost_report.total_return:.2%}") -print(f"总交易成本: {cost_report.total_trade_cost:.0f} 元") -print(f" 佣金: {cost_report.commission_cost:.0f}") -print(f" 滑点: {cost_report.slippage_cost:.0f}") -print(f" 印花税: {cost_report.stamp_tax_cost:.0f}") - -# --- Brinson 归因（需要基准）--- -import numpy as np -import pandas as pd -# 构造基准曲线（如沪深300） -benchmark = pd.DataFrame({ - "datetime": result.equity_curve["datetime"], - "total": np.linspace(100000, 108000, len(result.equity_curve)), -}) -analyzer = AttributionAnalyzer(result.trades, result.equity_curve, benchmark=benchmark) -brinson_report = analyzer.brinson_attribution() -print(f"配置贡献: {brinson_report.allocation_return:.2%}") -print(f"选股贡献: {brinson_report.selection_return:.2%}") -print(f"交叉效应: {brinson_report.interaction_return:.2%}") - -# --- 因子归因（需要因子数据）--- -exposures = pd.DataFrame({"momentum": [0.5, 0.3, 0.2], "quality": [0.1, -0.1, 0.0]}) -returns = pd.DataFrame({"momentum": [0.05, 0.03, 0.02], "quality": [0.01, -0.02, 0.0]}) -analyzer = AttributionAnalyzer( - result.trades, result.equity_curve, - factor_exposures=exposures, factor_returns=returns, -) -factor_report = analyzer.factor_attribution() -for name, ret in factor_report.factor_returns.items(): - print(f" {name}: {ret:.4f}") -print(f"特质收益: {factor_report.specific_return:.4f}") - -# --- 完整报告（自动选择最佳归因模式）--- -full_report = analyzer.full_report() -``` - -**归因模式优先级**：因子归因 > Brinson 归因 > 成本归因。`full_report()` 自动选择数据最完整的模式。 - ---- - -## 6. CLI 命令 - -```bash -# 列出所有内置因子 -easy-tdx factor list --table - -# 因子分析（需要数据，输出示例代码） -easy-tdx factor analyze momentum_20d - -# 组合因子回测（需要数据，输出示例代码） -easy-tdx pfactor backtest momentum_20d --n-stocks 10 --optimizer factor_weighted -``` - -CLI 命令输出 Python API 示例代码，方便复制使用。完整的因子计算和组合回测建议通过 Python API 完成。 - ---- - -## 7. 完整工作流示例 - -从数据获取到组合回测再到归因分析的完整管道： - -```python -""" -easy-tdx 量化研究完整工作流示例。 - -依赖: pip install easy-tdx -""" - -from easy_tdx import TdxClient, Market, KlineCategory -from easy_tdx.factor import FactorEngine, FactorAnalyzer, preprocess -from easy_tdx.portfolio import RebalanceEngine, FactorWeightedOptimizer -from easy_tdx.backtest import BacktestEngine -from easy_tdx.backtest.slippage import SquareRootSlippage -from easy_tdx.backtest.execution import TWAPExecution -from easy_tdx.backtest.attribution import AttributionAnalyzer - -# ── 1. 数据获取 ────────────────────────────────────── -client = TdxClient() -stock_pool = ["000001", "000858", "600519", "600036", "601318", - "000333", "002415", "601012", "600276", "000568"] - -data = {} -for code in stock_pool: - market = Market.SH if code.startswith("6") else Market.SZ - data[code] = client.get_security_bars( - market, code, KlineCategory.DAY, 0, 500 - ) -print(f"获取 {len(data)} 只股票数据") - -# ── 2. 因子计算 ────────────────────────────────────── -engine = FactorEngine() -factor_data = engine.compute_cross_section( - data, ["momentum_20d", "volatility_20d", "rsi_14"] -) -print(f"截面因子数据: {len(factor_data)} 行") - -# ── 3. 因子预处理 ───────────────────────────────────── -clean = preprocess( - factor_data, - factor_names=["momentum_20d", "volatility_20d", "rsi_14"], - steps=["winsorize", "zscore", "fill_missing"], -) - -# ── 4. 因子分析 ────────────────────────────────────── -forward_returns = engine.compute_forward_returns(data, period=5) - -for factor_name in ["momentum_20d", "volatility_20d", "rsi_14"]: - analyzer = FactorAnalyzer(clean, forward_returns) - report = analyzer.full_report(factor_name) - print(f"\n── {factor_name} ──") - print(f" IC均值: {report.mean_ic:.4f} ICIR: {report.icir:.4f}") - print(f" 多头年化: {report.long_only_annual:.2%}") - print(f" 多空夏普: {report.long_short_sharpe:.4f}") - -# ── 5. 组合回测 ────────────────────────────────────── -rebalancer = RebalanceEngine( - optimizer=FactorWeightedOptimizer(), - factor_name="momentum_20d", - n_stocks=5, - rebalance_freq="M", - cash=1_000_000, -) -result = rebalancer.run(data, start_date=20230101, end_date=20240101) -print(f"\n── 组合回测 ──") -print(f" 总收益: {result.performance['total_return']:.2%}") -print(f" 年化: {result.performance['annual_return']:.2%}") -print(f" 最大回撤: {result.performance['max_drawdown']:.2%}") -print(f" 夏普: {result.performance['sharpe']:.4f}") - -# ── 6. 高级单策略回测（滑点 + 执行仿真）────── -from easy_tdx.backtest import Strategy - -class MomentumStrategy(Strategy): - def init(self): - pass - def next(self): - if self._bar_index < 20: - return - ret = (self.data.close[0] - self.data.close[-20]) / self.data.close[-20] - if ret > 0.05 and self.position["size"] == 0: - self.buy(size=0) - elif ret < -0.03 and self.position["size"] > 0: - self.sell(size=0) - -bt_engine = BacktestEngine( - MomentumStrategy, - cash=500_000, - slippage_model=SquareRootSlippage(impact_coeff=0.1), - execution_model=TWAPExecution(n_bars=3), -) -# 选一只股票做回测 -bt_result = bt_engine.run(data["600519"]) -print(f"\n── 高级回测（600519）──") -print(f" 总收益: {bt_result.performance['total_return']:.2%}") -print(f" 夏普: {bt_result.performance['sharpe']:.4f}") - -# ── 7. 归因分析 ────────────────────────────────────── -att_analyzer = AttributionAnalyzer(bt_result.trades, bt_result.equity_curve) -cost_report = att_analyzer.cost_attribution() -print(f"\n── 成本归因 ──") -print(f" 总交易成本: {cost_report.total_trade_cost:.0f} 元") -print(f" 佣金: {cost_report.commission_cost:.0f}") -print(f" 滑点: {cost_report.slippage_cost:.0f}") -print(f" 印花税: {cost_report.stamp_tax_cost:.0f}") - -print("\n完成。") -client.close() -``` - ---- ## 向后兼容 From ae24c3a5f154b78baa916867c93675166adcea9b Mon Sep 17 00:00:00 2001 From: awayings Date: Tue, 8 Sep 2026 23:21:50 +0800 Subject: [PATCH 5/6] =?UTF-8?q?docs:=20=E6=96=B0=E5=A2=9E=20architecture/d?= =?UTF-8?q?evelopment=EF=BC=8C=E9=87=8D=E5=86=99=20docs/index.md=20?= =?UTF-8?q?=E5=85=A8=E9=87=8F=E7=B4=A2=E5=BC=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - architecture.md：七层架构图 + 源码树 + 分层要点（越层直调/协议层无 IO/ e2e_mock 替身/__main__ 三形态/平台差异） - development.md：环境初始化/测试三层分布/静态检查/开发流程四阶段 （需求 Issue→开发测试→提交 CI→发布 release+CHANGELOG）/文档规范 - index.md：人类目录（分类+每文件一句描述+历史归档标注）+ 完整 toctree （38 个 md 全部入树，消除 ReadTheDocs orphan 页面） Co-Authored-By: Claude --- docs/architecture.md | 54 ++++++++++++++++++++++ docs/development.md | 87 ++++++++++++++++++++++++++++++++++ docs/index.md | 108 +++++++++++++++++++++++++++++++++++++++++-- 3 files changed, 244 insertions(+), 5 deletions(-) create mode 100644 docs/architecture.md create mode 100644 docs/development.md diff --git a/docs/architecture.md b/docs/architecture.md new file mode 100644 index 0000000..f181603 --- /dev/null +++ b/docs/architecture.md @@ -0,0 +1,54 @@ +# 架构 + +easy-tdx 七层架构总览：接口 → 服务 → 领域 → 持久 → 网关 → 协议 → 外部源 + +七层分层，请求自上而下、数据（pandas DataFrame）自下而上：**① 用户接口层**（Web UI / CLI / Python API / 桌面 EXE）→ **② Web 服务层**（FastAPI + SSE 实时推送 + 异步任务）→ **③ 领域层**（回测 / 指标 / 缠论 / 因子 / 选股 / 组合，纯计算零网络）→ **④ 数据持久层**（DuckDB K 线仓库 + 通达信本地 vipdoc 文件）→ **⑤ 客户端网关层**（8 个客户端 + 健康分 / 故障转移）→ **⑥ 协议层**（通达信二进制协议编解码）→ **⑦ 外部数据源**（通达信服务器 / 中金所 / 新浪 / 巨潮 / LLM）。虚线为旁路直连（HTTP 数据源 / 本地文件 / CLI 与 Python API 越层直调）。 + +🖼️ 交互版架构图（可缩放平移、悬停查看 38 个模块的职责详情、一键导出 PNG）：[architecture.html](./architecture.html) + +## 源码树 + +``` +src/easy_tdx/ +├── client.py # TdxClient / AsyncTdxClient（标准协议） +├── unified.py # UnifiedTdxClient（统一入口） +├── config.py # 服务器地址、端口、超时配置 +├── indicator.py # 技术指标计算（34 个，基于 MyTT） +├── MyTT.py # 麦语言技术指标算法库 +├── mac/ +│ ├── client.py # MacClient / AsyncMacClient（MAC 协议） +│ ├── enums.py # Period, Adjust, Category, ExMarket, SortType, ... +│ ├── models.py # MacBar, MacQuoteField, MacTick, BoardInfo, ... +│ └── commands/ # MAC 命令（build_request + parse_response，无 IO） +├── ex/ +│ ├── client.py # ExTdxClient / AsyncExTdxClient（标准协议扩展市场） +│ ├── mac_client.py # MacExClient / AsyncMacExClient（MAC 协议扩展市场） +│ └── transport/ # ExTdxConnection（端口 7727） +├── transport/ +│ ├── sync.py # TdxConnection + ping_host / ping_all +│ └── async_.py # AsyncTdxConnection（asyncio） +├── commands/ # 标准协议命令（无 IO） +├── codec/ # price / volume / datetime / frame / bitmap 编解码 +├── chanlun/ # 缠论技术分析（K线合并/分型/笔/线段/中枢/买卖点/背驰） +├── factor/ # 因子引擎（Factor ABC/19内置因子/截面计算/因子分析/预处理管道） +├── portfolio/ # 组合管理（4优化器/风险模型/再平衡引擎） +├── backtest/ # 回测引擎（Strategy基类/向量化引擎/多因子组合/滑点模型/执行仿真/归因分析） +├── screen/ # 策略选股扫描（scan信号扫描/rank回测排名/并发扫描/增量缓存） +├── realtime/ # 实时数据推送框架（EventBus/事件驱动/asyncio） +├── web/ # Web API（FastAPI REST + WebSocket） +├── models/ # 纯 dataclass，无业务逻辑 +├── offline/ # 离线数据读写模块（读取 + 写入同步） +└── cli/ # easy-tdx CLI（click） +``` + +commands 层不依赖 transport，可独立单测。 + +## 分层要点 + +- **协议层无 IO**：`commands/`、`codec/`、`mac/commands/` 只做编解码，可完全离线单测（`tests/fixtures/` 的 hex dump 即其测试镜像）。 +- **领域层零网络**：`backtest/`、`chanlun/`、`factor/`、`portfolio/`、`screen/` 只吃 DataFrame，不碰网络——这是回测/扫描可在无行情连接时运行的基础。 +- **网关层统一入口**：`unified.py` 封装 8 个客户端（标准/MAC × 同步/异步 × 常规/扩展），带健康分与故障转移；上层（Web、CLI）优先走它。 +- **越层直调**：CLI 与 Python API 不经过 Web 服务层，直接调网关/领域层；HTTP 数据源（新浪/巨潮/中金所）与本地文件直读是旁路。因此同一功能常有三处入口（CLI 命令 / Python API / REST 端点），改领域逻辑三处受益；改协议/网关时注意 Web 层的替身切入点（`web/e2e_mock.py` 在 `EASY_TDX_E2E_MOCK=1` 下替换全部客户端）。 +- **CLI 薄封装**：`cli/cmd_*.py` 每个文件一个 click 命令组，业务全部在领域/网关层；领域模块内也有 CLI（`backtest/cli.py`、`screen/cli.py`），由 `cli/__init__.py` 汇总注册。入口链：`easy-tdx` 命令 → `_editable_guard:main`（可编辑安装失效时打印修复指引）→ CLI。 +- **`python -m easy_tdx` 三种形态**（`__main__.py`）：开发态无参默认等价 `easy-tdx serve`；打包态双击走托盘（uvicorn 后台线程 + 主线程 pystray 托盘）；multiprocessing 子进程拦截保护（Windows spawn 下防止子进程重复启动 uvicorn，一键寻优/screen 扫描等多进程功能依赖它）。 +- **离线数据平台差异**：`.day` 文件路径分隔符 / GBK 文件名 / 时区行为在 Windows 与 Linux 不同，CI 有 Windows matrix 覆盖，改 `offline/` 时留意。 diff --git a/docs/development.md b/docs/development.md new file mode 100644 index 0000000..f7e97a9 --- /dev/null +++ b/docs/development.md @@ -0,0 +1,87 @@ +# 开发环境与流程 + +本文档是开发者的完整工作流参考。命令速查亦见 [CLAUDE.md](../CLAUDE.md)。 + +## 环境初始化 + +```bash +git clone git@github.com:awayings/easy_tdx.git && cd easy_tdx +uv sync --all-extras # 建 .venv 并装全部 extras（普通 uv sync 只装基础依赖） +``` + +CI 不用 uv，走 `pip install -e ".[dev]"` + `pip install -r requirements-dev.txt`。改依赖时两套流程都要考虑：pyproject.toml 只写下界+上界，`uv.lock` 与 `requirements-dev.txt` 才是可复现锁（dev 工具链锁定版本必须兼容 Python 3.10，CI 矩阵跑 3.10/3.12/3.13）。 + +前端：`cd web-ui && npm ci && npm run build`（`build` = vue-tsc 类型检查 + vite build）。**`pip install -e .` 要求 `web-ui/dist` 存在**（hatchling `force-include` 把它打进 wheel 的 `easy_tdx/web/dist/`），所以改前端后、跑 Python 测试/安装前必须先构建。 + +## 测试 + +```bash +python -m pytest tests/unit/ -v # 单元测试（无需网络，全部 mock） +XMTDX_LIVE=1 python -m pytest tests/integration/ -v # 集成测试（连真实通达信服务器，默认 skip） +python -m pytest tests/unit/ --cov src/easy_tdx --cov-fail-under=60 # 覆盖率门槛 60 +``` + +三层测试分布： + +| 层 | 位置 | 跑在哪 | 说明 | +|---|---|---|---| +| 单元 | `tests/unit/` | CI（6 格矩阵）+ 本地 | 全 mock：`tests/fixtures/` 真实协议 hex dump + JSON 对照，`tests/golden/` 期望输出 | +| 集成 | `tests/integration/` | **仅本地** | `XMTDX_LIVE=1` 才执行，连真实 TDX 服务器 smoke test | +| 前端 E2E | `web-ui/e2e/*.spec.ts` | CI frontend job + 本地 | Playwright，`EASY_TDX_E2E_MOCK=1` 后端合成行情，不连真实服务器 | + +- `tests/conftest.py` 默认设 `EASY_TDX_NO_TASK_DB=1`，防单测污染 `~/.easy_tdx/tasks.db`；需要测试存储的用例用 `EASY_TDX_CONFIG_DIR` 指向 `tmp_path` 显式重开。 +- `tests/unit/test_ai_llm.py` 依赖 LLM API key 轮询，CI 用 `--ignore` 跳过，本地有 mock 可跑。 +- `asyncio_mode = "auto"`：async 测试无需 `@pytest.mark.asyncio`。 + +## 静态检查 + +```bash +mypy src/ # strict 模式（pyproject 配置） +ruff check src/ tests/ # E/F/I/UP 规则 +ruff format --check src/ tests/ +``` + +mypy/ruff 均排除 `src/easy_tdx/exchange_margin.py`；`MyTT.py` 有手写 `MyTT.pyi` stub 保持 strict 检查。 + +本地一键门禁（等价 CI 三 job 的本地版）： + +```bash +bash scripts/verify_ci.sh # ruff → format → mypy → pytest（排除 integration）→ 前端 build + E2E +bash scripts/verify_ci.sh --fast # 只跑静态检查 +# 可选：ln -s ../../scripts/verify_ci.sh .git/hooks/pre-push +``` + +## 开发流程 + +### a. 需求（Issue） + +- 功能/缺陷先在 GitHub Issues 提出；代码注释与提交说明中引用编号（如 `#58`、`审计 #9`）。 +- 复杂功能先写设计文档再动手（历史范本：`docs/board-overview-design.md`、`docs/hotspot-rolling-design.md`，以及 `docs/superpowers/` 下的 specs）。 +- 功能变更时同步评估文档更新（见「文档规范」）。 + +### b. 开发与测试 + +- 新功能/修复按 TDD 习惯先写红测试再实现；单元测试必须零网络、零真实服务器依赖。 +- 命令形态变更时 `easy-tdx --help` 自检；Web 路由变更时 `/docs` Swagger 自检。 + +### c. 提交与 CI + +- 提交信息带前缀（`feat:` / `fix:` / `test:` / `docs:` / `refactor:`，可带作用域如 `feat(web):`），中文描述。push/PR 到 `main` 触发 `ci.yml`： + - test job：ubuntu/windows × py3.10/3.12/3.13 六格矩阵跑单测（覆盖率 ≥60）+ ruff + format + - mypy job：strict 模式（py3.13） + - frontend job：vue-tsc + Playwright mock E2E +- **集成测试不进 CI**（依赖真实 TDX 服务器），发布前本地 `XMTDX_LIVE=1` 手动跑一遍。 + +### d. 发布版本 + +1. 收敛时打一个聚合提交 `release: vX.Y.Z — 中文一句话摘要`，同一提交内包含：代码与测试改动 + `pyproject.toml` 版本号 bump + `CHANGELOG.md` 新增版本小节。 +2. CHANGELOG 遵循 Keep a Changelog（zh-CN）：`## [X.Y.Z] — 日期` 倒序最新在前，先一段加粗导语再按主题分 `###` 小节，条目带文件链接，测试小节报数字验收（如「全量 1820 通过，ruff / mypy / vue-tsc 全绿」）。**无 Unreleased 区，CHANGELOG 在 release 提交时写入**。 +3. 打 tag 推送即自动发布：`git tag vX.Y.Z && git push origin vX.Y.Z`，触发两个独立 workflow——`publish.yml`（PyPI trusted publishing，OIDC 无 token）与 `release.yml`（Windows EXE via PyInstaller + GitHub Release，正文含 SHA256/SmartScreen 说明；GitHub release notes 自动生成，**不读取 CHANGELOG.md**）。 +4. 版本单一来源是 `pyproject.toml`（前端品牌区版本来自后端 `GET /api/v1/meta`）；文档一律不写死版本号。 + +## 文档规范 + +- **大小限制**：每份文档约 500 行为上限，超限必须拆分，通过 [index.md](./index.md) 与 README 文档导航串联。过大文件不可新增。 +- **类型两分**：教程（how-to，代码示例）与参考（速查/字段/命令表）原则上分开成文。 +- **可达性标准**：任何文档变更必须以「[README.md](../README.md) + [docs/index.md](./index.md) 可达的文件」为标准——新文件必须同时进 README 文档导航与 index.md；删除/改名必须同步修复全部链接。 +- **禁止硬编码版本横幅**：版本信息以 `pyproject.toml` 与 `CHANGELOG.md` 为准；功能引入说明里的版本标注（如「v1.29.1」）除外。 diff --git a/docs/index.md b/docs/index.md index c85d9ac..2d622e1 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,16 +1,114 @@ -# easy-tdx 文档 +# easy-tdx 文档索引 + +本索引是文档的目录目录：**新增或删除文档必须同步更新本文件与 README 文档导航**（见 [development.md](./development.md) 的文档规范）。每份文档 ≤500 行，超限拆分；教程（how-to）与参考（速查）分开成文。 + +## 开始 + +- [README](../README.md) — 项目门面：功能总览、30 秒上手、安装、文档导航（ReadTheDocs 落地页即其包含） + +## CLI 参考 + +- [cli.md](./cli.md) — 全部命令速查表 + 按域导航 +- [cli-market.md](./cli-market.md) — 行情数据：报价 / K线 / 分时 / 板块 / 资金 / 中金所 / 扩展市场 +- [cli-finance.md](./cli-finance.md) — 财务与公告：巨潮公告检索 / 财报三表 / 通达信 F10 +- [cli-indicators.md](./cli-indicators.md) — 技术指标与公式：34 指标 / 通达信公式 / 捉妖 / 乖离率 +- [cli-backtest.md](./cli-backtest.md) — 回测与寻优：backtest / optimize / portfolio / run-all（含参数表） +- [cli-screen.md](./cli-screen.md) — 选股扫描：全市场信号扫描 / 强势股排名 +- [chanlun.md](./chanlun.md) — 缠论分析（CLI + Python，含完整输出示例） + +## 本地数据 + +- [data-local.md](./data-local.md) — K 线仓库（DuckDB）与 vipdoc 离线读写（CLI + Python 合一操作手册） + +## Web + +- [web-api.md](./web-api.md) — REST + WebSocket + SSE 端点与示例、帧规范 +- [web-ui.md](./web-ui.md) — 行情终端与回测工作台零代码操作手册 +- [packaging.md](./packaging.md) — Windows EXE 打包（PyInstaller）与分发 + +## Python API + +- [python-api.md](./python-api.md) — 教程：连接管理 / MAC 协议 / 统一客户端 / 离线 / 缠论 / 公告 / 财报 / 实时轮询 +- [api_reference.md](./api_reference.md) — 参考：TdxClient 标准协议方法速查 + MAC 客户端方法表 +- [field_mapping.md](./field_mapping.md) — 参考：数据模型字段 ↔ 中文含义 ↔ 类型 + 枚举（标准 + MAC） + +## 回测与量化 + +- [backtest_usage.md](./backtest_usage.md) — 回测引擎使用手册（策略 / 配置 / 结果） +- [backtest-examples.md](./backtest-examples.md) — 完整示例集 + 注意事项 +- [quantitative-guide.md](./quantitative-guide.md) — 因子引擎与组合管理（基础） +- [quantitative-advanced.md](./quantitative-advanced.md) — 滑点模型 / 执行仿真 / 归因分析 / 完整工作流 + +## 指标深度 + +- [indicator-zhuoyao.md](./indicator-zhuoyao.md) — 捉妖大师（ZHUOYAO）多周期 ROC 共振详解 +- [indicator-bias-signal.md](./indicator-bias-signal.md) — 30 日乖离率信号（BIAS_SIGNAL）详解 + +## 开发者 + +- [architecture.md](./architecture.md) — 七层架构图 / 源码树 / 分层要点 +- [development.md](./development.md) — 环境初始化 / 测试 / CI / 发布流程 / 文档规范 + +## 协议与逆向 + +- [protocol-reverse-engineering.md](./protocol-reverse-engineering.md) — 通达信二进制协议逆向过程 +- [protocol-unknown-fields.md](./protocol-unknown-fields.md) — 未知字段研究日志（活文档） + +## 历史归档（已实施 / 规划完成，供追溯） + +- [board-overview-design.md](./board-overview-design.md) — 行业/概念总览页设计稿（已上线） +- [hotspot-rolling-design.md](./hotspot-rolling-design.md) — 市场热点滚动页设计稿（已上线） +- [market-insights-roadmap.md](./market-insights-roadmap.md) — 盘面洞察功能路线图（已收尾） +- [upgrade-plan-2026H2.md](./upgrade-plan-2026H2.md) — 2026 H2 升级计划（全部阶段完成） +- [superpowers/](superpowers/) — 回测/因子/组合引擎的计划与设计存档（v1.11–v1.15 时代，非现行文档） + +## HTML 资产（仅 GitHub 可交互，ReadTheDocs 不发布） + +- [architecture.html](./architecture.html) — 38 模块交互式架构图（可缩放平移、导出 PNG） +- [回测系统完全上手手册.html](./回测系统完全上手手册.html) — 零基础图文回测手册（13 章） + +--- ```{toctree} -:maxdepth: 2 -:caption: 目录 +:maxdepth: 1 +:caption: 文档目录 readme +cli +cli-market +cli-finance +cli-indicators +cli-backtest +cli-screen +chanlun +data-local +web-api +web-ui +python-api api_reference field_mapping backtest_usage +backtest-examples quantitative-guide -protocol-reverse-engineering -protocol-unknown-fields +quantitative-advanced indicator-zhuoyao indicator-bias-signal +architecture +development +packaging +protocol-reverse-engineering +protocol-unknown-fields +board-overview-design +hotspot-rolling-design +market-insights-roadmap +upgrade-plan-2026H2 +superpowers/plans/2026-06-09-backtest-engine +superpowers/plans/2026-06-12-v1.11.0-factor-engine +superpowers/plans/2026-06-12-v1.12.0-factor-analysis +superpowers/plans/2026-06-12-v1.13.0-portfolio +superpowers/plans/2026-06-12-v1.14.0-slippage-execution +superpowers/plans/2026-06-12-v1.15.0-attribution +superpowers/specs/2026-06-09-backtest-engine-design +superpowers/specs/2026-06-12-advanced-backtest-design +superpowers/specs/2026-06-12-quantitative-factor-engine-design ``` From f58010ead8482408166d70cdac53f5c54b98bbde Mon Sep 17 00:00:00 2001 From: awayings Date: Tue, 8 Sep 2026 23:21:55 +0800 Subject: [PATCH 6/6] =?UTF-8?q?docs:=20README=20=E7=98=A6=E8=BA=AB?= =?UTF-8?q?=E8=87=B3=20204=20=E8=A1=8C=20+=20=E6=96=87=E6=A1=A3=E5=AF=BC?= =?UTF-8?q?=E8=88=AA=EF=BC=9B=E4=BF=AE=E5=A4=8D=20examples=20=E8=B4=A2?= =?UTF-8?q?=E5=8A=A1=E9=94=9A=E7=82=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - README 保留功能介绍/30 秒上手/架构摘要/安装/Web UI 入口，CLI 参考、 Web API、Python API、枚举、完整 API 列表、架构树、开发章节全部移交 docs/ - 新增「文档导航」段：24 份 docs 全部从 README 可达，完整索引见 docs/index.md - examples/06_finance/README.md 的 #财务 锚点改指 docs/cli-finance.md#财务 Co-Authored-By: Claude --- README.md | 2017 +-------------------------------- examples/06_finance/README.md | 2 +- 2 files changed, 40 insertions(+), 1979 deletions(-) diff --git a/README.md b/README.md index 8695711..4d02335 100644 --- a/README.md +++ b/README.md @@ -127,2002 +127,63 @@ easy-tdx serve # 行情终端 + 回测工作台 随便用，随便改，随便分发。 **数据面前，人人平等。** + ## 项目架构 easy-tdx 七层架构总览：接口 → 服务 → 领域 → 持久 → 网关 → 协议 → 外部源 -七层分层，请求自上而下、数据（pandas DataFrame）自下而上：**① 用户接口层**（Web UI / CLI / Python API / 桌面 EXE）→ **② Web 服务层**（FastAPI + SSE 实时推送 + 异步任务）→ **③ 领域层**（回测 / 指标 / 缠论 / 因子 / 选股 / 组合，纯计算零网络）→ **④ 数据持久层**（DuckDB K 线仓库 + 通达信本地 vipdoc 文件）→ **⑤ 客户端网关层**（8 个客户端 + 健康分 / 故障转移）→ **⑥ 协议层**（通达信二进制协议编解码）→ **⑦ 外部数据源**（通达信服务器 / 中金所 / 新浪 / 巨潮 / LLM）。虚线为旁路直连（HTTP 数据源 / 本地文件 / CLI 与 Python API 越层直调）。 +七层分层，请求自上而下、数据（pandas DataFrame）自下而上：**用户接口层**（Web UI / CLI / Python API / 桌面 EXE）→ **Web 服务层**（FastAPI + SSE 实时推送 + 异步任务）→ **领域层**（回测 / 指标 / 缠论 / 因子 / 选股 / 组合，纯计算零网络）→ **数据持久层**（DuckDB K 线仓库 + 通达信本地 vipdoc 文件）→ **客户端网关层**（8 个客户端 + 健康分 / 故障转移）→ **协议层**（通达信二进制协议编解码）→ **外部数据源**（通达信服务器 / 中金所 / 新浪 / 巨潮 / LLM）。 -🖼️ 交互版架构图（可缩放平移、悬停查看 38 个模块的职责详情、一键导出 PNG）：[docs/architecture.html](./docs/architecture.html) +🖼️ 交互版架构图（38 模块职责详情）+ 源码树 + 分层要点：[docs/architecture.md](./docs/architecture.md) · [architecture.html](./docs/architecture.html) ## 安装 ```bash -pip install easy-tdx +pip install easy-tdx # 自动注册 easy-tdx CLI 命令 +pip install -e ".[dev]" # 开发模式（测试 / 静态检查工具链） +pip install -e ".[web]" # Web API 模式（FastAPI + Uvicorn） ``` -安装后自动注册 `easy-tdx` CLI 命令： +可选依赖分组：`warehouse`（DuckDB 本地 K 线仓库）、`baostock`（通达信全部路径失败时的最后一级兜底数据源，仅日/周/月线，`EASY_TDX_BAOSTOCK=0` 可关闭）、`packaging`（PyInstaller 打包 EXE）。开发环境初始化（uv）与完整开发流程见 [docs/development.md](./docs/development.md)。 -```bash -easy-tdx --help -``` - -开发模式： - -```bash -pip install -e ".[dev]" - -# 开发 Web API 模式（含 FastAPI + Uvicorn） -pip install -e ".[web]" -``` - -### 可选：baostock 自动兜底数据源 - -通达信协议依赖第三方行情服务器，为了"部分兜底、总好过全挂"，可选安装 baostock 作为最后一级自动回退： - -```bash -pip install "easy-tdx[baostock]" -``` - -装完即自动生效，平时**一次都不会调用**——只有当 MAC 协议与标准协议两条 TDX 路径全部失败或返回空时才启用，响应中会带 `source: "baostock"` 字段标注数据来源。设置环境变量 `EASY_TDX_BAOSTOCK=0` 可随时关闭。边界：baostock 是收盘后更新的数据源（当日数据约 17:30 后才有），因此只兜 **日/周/月 K 线** 的历史数据（覆盖沪深，不含北交所），实时行情、分时、板块等能力仍由通达信协议提供。本地 K 线仓库同步同样支持：`easy-tdx warehouse sync --symbols SH:600519 --source auto|tdx|baostock`（默认 auto）。 - -## CLI 参考 - -`easy-tdx` 默认输出 JSON（一行一条记录），`--table` 切换表格，`--output csv` 输出 CSV。 - -### 基础 - -```bash -easy-tdx ping # 服务器测速 -easy-tdx version # 版本号 -``` - -### 行情 - -```bash -# K 线 -easy-tdx kline SZ 000001 --count 30 --table -easy-tdx kline SH 600519 --period 5MIN --adjust QFQ - -# 实时报价 -easy-tdx quote "SZ 000001,SH 600519" --table - -# 市场分类报价（按涨幅排序） -easy-tdx quote-list A --count 20 --table -easy-tdx quote-list KCB --sort TOTAL_AMOUNT --order ASC -easy-tdx quote-list CYB --count 50 -``` - -### 分时 / 成交 - -```bash -easy-tdx tick SZ 000001 --table -easy-tdx tick SH 600519 --days 5 -easy-tdx tick SZ 000001 --date 20250115 - -easy-tdx transaction SZ 000001 --count 100 --table -easy-tdx transaction SH 600519 --date 20250115 -``` - -### 板块 - -```bash -easy-tdx board-list --type GN --table -easy-tdx board-list --type HY --count 200 -easy-tdx board-members 881001 --table -easy-tdx belong-board SZ 000001 --table -easy-tdx board-summary 881001 --table # 板块汇总（成交额/主力净流入/涨跌家数） -easy-tdx board-summary 881001 --members --table # 含成分股明细 -easy-tdx board-ranking --type HY --top 10 --table # 行业板块排行 -easy-tdx board-ranking --type GN --sort-by amount # 概念板块按成交额排行 - -# 板块 N 日涨跌幅排行（默认全部，支持指定日期） -easy-tdx board-change-ranking --table # 行业 20 日涨跌幅排行 -easy-tdx board-change-ranking --type GN --days 10 --table # 概念 10 日涨跌幅排行 -easy-tdx board-change-ranking --type HY --date 20250530 --days 20 --table -easy-tdx board-change-ranking --type HY --top 10 --asc # 行业跌幅前10 -``` - -### 资金 / 监控 - -```bash -easy-tdx capital-flow SH 600519 --table -easy-tdx auction SZ 000001 --table -easy-tdx unusual SH --count 100 --table -easy-tdx market-stat --table -easy-tdx server-info --table -easy-tdx symbol-info SZ 000001 --table -``` - -### 公告检索（巨潮资讯网） - -```bash -easy-tdx announcement 688017 # 默认 30 条，JSON 输出 -easy-tdx announcement 601088 --count 10 --page 2 # 翻页 -easy-tdx announcement 000001 --table # 表格输出（不截断 url） - -# 下载最新 5 条公告的 PDF 到 ./pdfs 目录 -easy-tdx announcement 601088 --count 5 --download 5 --download-dir ./pdfs -``` - -> 独立数据源（巨潮资讯网），无需连接 TDX 行情服务器即可使用。 -> 返回的 ``url`` 含 4 参数可直接打开，``pdf_url`` 为 PDF 直链。 - -### 中金所成交持仓排名（v1.29.1） - -```bash -easy-tdx ccpm IF --table # 最近有数据的交易日（缺省自动回溯） -easy-tdx ccpm IF --date 2026-09-02 # 指定交易日 -easy-tdx ccpm all --date 2026-08-28 --table # 全部 8 个品种一次抓取 -easy-tdx ccpm TL --refresh # 忽略本地缓存，强制重新抓取 -``` - -> 独立数据源（中金所官网），无需连接 TDX 行情服务器。品种：IF 沪深300 / IH 上证50 / IC 中证500 / IM 中证1000 股指期货，TS/TF/T/TL 为 2/5/10/30 年期国债期货。 -> 每个交易日收盘后约 16:15 发布，含该品种**全部合约 × 三类排名（成交量 / 持买单量·多单 / 持卖单量·空单）× 各前 20 名会员**； -> 数据发布后不可变，按日缓存到 `~/.easy_tdx/cache/ccpm/`，历史二次查询零网络。 -> JSON 输出为英文列名（vol/long_pos/short_pos 等，机器友好），`--table` 自动切换中文表头。 -> WebUI 对应「期货持仓排名」页（含新手科普），API 为 `GET /api/v1/ccpm/rank`。 - -### 技术指标 - -```bash -easy-tdx indicator-list --table # 列出所有可用指标 -easy-tdx indicator MACD -m SH -c 600519 --table # MACD -easy-tdx indicator KDJ -m SZ -c 000001 --table # KDJ -easy-tdx indicator RSI -m SH -c 600519 --table # RSI -easy-tdx indicator BOLL -m SH -c 600519 --table # BOLL 布林带 -easy-tdx indicator DMI -m SH -c 600519 --table # DMI 动向指标 -easy-tdx indicator ATR -m SH -c 600519 --table # ATR 真实波幅 -easy-tdx indicator WR -m SH -c 600519 --table # WR 威廉指标 -easy-tdx indicator CCI -m SH -c 600519 --table # CCI 顺势指标 -easy-tdx indicator BIAS -m SZ -c 000001 --table # BIAS 乖离率 -easy-tdx indicator BIAS_SIGNAL -m SH -c 600519 --table # 30日乖离率信号 -easy-tdx indicator OBV -m SZ -c 000001 --table # OBV 能量潮 - -# 多指标同时计算 -easy-tdx indicator MACD,KDJ,RSI,BOLL -m SH -c 600519 --count 10 --table - -# 自定义参数 -easy-tdx indicator MACD -m SH -c 600519 --params SHORT=10,LONG=22 - -# 分钟线指标 -easy-tdx indicator MACD -m SH -c 600519 --period 5MIN --count 50 - -# 仅输出指标值（不含 OHLCV） -easy-tdx indicator RSI -m SZ -c 000001 --no-ohlcv -``` - -### 缠论分析 - -基于缠论理论的技术分析，计算管道：`K 线合并 → 分型识别 → 笔 → 中枢 → 线段 → 买卖点 → 背驰`。默认输出 JSON，加 `--table` 输出可读表格。 - -```bash -easy-tdx chanlun SZ 000001 --table -easy-tdx chanlun SH 600519 --adjust QFQ --table -easy-tdx chanlun SZ 000001 --period 30MIN - -# 多级别联立：分析日线最后一笔在 30 分钟级别中的走势结构 -easy-tdx chanlun SZ 000001 --multi-level 30MIN --table -easy-tdx chanlun SH 600519 --multi-level 5MIN -``` - -#### 输出示例 - -以 `easy-tdx chanlun SH 601088 --table` 为例，输出分五个部分： - -**概要统计** - -``` -标的: 601088 周期: DAILY -原始K线: 800 缠论K线: 589 -分型: 275 笔: 131 中枢: 21 线段: 40 -买卖点: 125 背驰: 73 -``` - -| 字段 | 含义 | -|------|------| -| 原始 K 线 | 从服务端获取的原始 K 线条数 | -| 缠论 K 线 | 经过包含处理（合并）后的 K 线条数，数量一定 ≤ 原始 K 线 | -| 分型 | 识别出的顶分型 + 底分型总数 | -| 笔 | 相邻两个异向分型之间的连线（涨跌方向交替） | -| 中枢 | 至少 3 笔重叠区域形成的密集成交区间 | -| 线段 | 由笔构成的更大级别走势单位 | -| 买卖点 | 一二三类买卖点信号总数 | -| 背驰 | 力度衰减信号总数（笔背驰 / 盘整背驰 / 趋势背驰） | - -**笔** - -``` -[0] ↑ 2023-02-17 → 2023-02-23 h=28.46 l=26.76 ✓ -[1] ↓ 2023-02-23 → 2023-02-28 h=28.46 l=27.8 ✓ -[2] ↑ 2023-02-28 → 2023-03-09 h=29.77 l=27.8 ✓ -``` - -笔是缠论的基本走势单位。每条笔连接一个顶分型和一个底分型，方向严格交替（↑↓↑↓…）。`✓` 表示已确认（后续出现了反向笔），`…` 表示仍在进行中。 - -- `↑`：向上笔，起点是底分型（低点），终点是顶分型（高点） -- `↓`：向下笔，起点是顶分型（高点），终点是底分型（低点） -- `h`/`l`：该笔范围内的最高价 / 最低价 - -**中枢** - -``` -[0] zg=28.46 zd=28.11 gg=32.56 dd=26.76 lines=11 ✓ -[1] zg=31.2 zd=30.45 gg=32.56 dd=27.9 lines=3 ✓ -``` - -中枢是至少 3 笔重叠形成的密集成交区间，代表多空博弈的平衡区域。`✓` 表示已脱离，`…` 表示价格仍在中枢区间内震荡。 - -| 字段 | 含义 | -|------|------| -| `zg` | 中枢上沿（区间内最高的低点）— 支撑/压力的关键分界 | -| `zd` | 中枢下沿（区间内最低的高点） | -| `gg` | 中枢区间内的最高价 | -| `dd` | 中枢区间内的最低价 | -| `lines` | 构成该中枢的笔数，笔数越多代表震荡越充分 | - -中枢的意义：价格在中枢内震荡 → 突破中枢上沿看涨，跌破下沿看跌。`zg`/`zd` 是实战中最常用的参考价位。 - -**线段** - -``` -[0] ↑ 2023-02-17 → 2023-03-09 h=29.77 l=26.76 -[1] ↓ 2023-02-28 → 2023-03-29 h=29.77 l=27.18 -``` - -线段是比笔更大的走势单位，由多笔重叠组合而成。线段的方向不严格交替，可能出现连续同向（如连续多段向上），代表更高一级的趋势方向。实战中通常在线段级别判断大方向，在笔级别找买卖点。 - -**买卖点** - -``` -1buy: 中枢下方力度衰减，一类买点 (l=27.30 < zd=46.72) -2buy: 回调不创新低，二类买点 (l=27.33) -3buy: 回调不破中枢上沿，三类买点 (l=27.80 > zg=27.58) -1sell: 中枢上方力度衰减，一类卖点 (h=50.38 > zg=46.97) -2sell: 反弹不创新高，二类卖点 (h=29.32) -3sell: 反弹不破中枢下沿，三类卖点 (h=28.46 < zd=46.72) -``` - -缠论定义三类买点和三类卖点： - -| 类型 | 买点含义 | 卖点含义 | -|------|----------|----------| -| 一类 | 下跌趋势末端，力度衰减后的第一个低点（抄底） | 上涨趋势末端，力度衰减后的第一个高点（逃顶） | -| 二类 | 一类买点后的回调不创新低（确认反转） | 一类卖点后的反弹不创新高（确认反转） | -| 三类 | 回调不进入中枢上沿（趋势确认，中枢上方买） | 反弹不进入中枢下沿（趋势确认，中枢下方卖） | - -括号内的条件是该信号的触发依据，如 `l=27.80 > zg=27.58` 表示回调低点 27.80 高于中枢上沿 27.58，所以是三类买点。 - -**背驰** - -``` -[✓] bi: 笔背驰: 笔[4] 力度=1.32 < 笔[2] 力度=1.97 -[✓] pz: 盘整背驰: 中枢[11] 内末笔力度=2.49 < 首笔力度=6.64 -[✓] qs: 趋势背驰(上): 中枢[1] 离开力度=3.32 < 中枢[0] 离开力度=4.45 -``` - -背驰是力度衰减信号，表明当前走势动力正在减弱，可能即将反转。力度通过 MACD 面积计算，数值越小力度越弱。 - -| 类型 | 含义 | -|------|------| -| `bi`（笔背驰） | 同向相邻两笔比较，后一笔力度 < 前一笔 → 该方向动力减弱 | -| `pz`（盘整背驰） | 同一中枢内，末笔力度 < 首笔 → 中枢内动力衰减，即将突破 | -| `qs`（趋势背驰） | 两个同向中枢之间比较，后一中枢离开力度 < 前一中枢 → 趋势可能终结 | - -`[✓]` 表示确认背驰。趋势背驰(上)代表上涨趋势可能结束，趋势背驰(下)代表下跌趋势可能结束。 - -### 回测引擎 - -> 📖 **完整使用手册**：[docs/backtest_usage.md](docs/backtest_usage.md) —— -> 涵盖策略编写（`init()`/`next()`）、行情数据访问、指标注册、订单模拟、 -> 绩效指标、组合回测、调仓引擎与完整示例。回测相关用法以该手册为准。 - -内置向量回测引擎，加载 Python 策略文件即可跑回测。策略继承 `Strategy` 基类，在 `init()` 注册指标，在 `next()` 逐 bar 生成买卖信号，引擎完成订单模拟、持仓跟踪和绩效分析。 - -**单策略回测：** - -```bash -easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --count 2000 --cash 1000000 --adjust QFQ --table -# 推荐加上 --slippage 0.01 模拟真实滑点（元/股），使回测更贴近实盘 - -# 缠论自动桥接：引擎自动计算缠论分析并注入策略 self.chanlun -easy-tdx backtest SZ 000001 --strategy-file strategies/chanlun_strategy.py --chanlun-level DAILY --table -``` - -**样本外验证（v1.25）：** - -```bash -# 附加 Walk-Forward 七窗样本外验证（每窗独立开仓，窗口数可调） -easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --wf --wf-windows 7 - -# 一条龙评估：回测 + WF + 适配性体检 + 综合评分 + S-D 评级 + 买入持有基准对比 -easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --evaluate -``` - -输出示例： - -``` -=== 回测绩效概要 === -总收益率: 1413.51% -年化收益: 40.85% -最大回撤: 76.75% -夏普比率: 0.88 -胜率: 20.8% -交易次数: 24 -``` - -> ⚠️ **回测 ≠ 实盘**。以上收益率为历史数据回测结果，包含幸存者偏差和过拟合风险， -> 不构成投资建议。实际交易需考虑滑点、流动性、涨跌停无法成交等因素。 -> 请在充分理解策略逻辑后谨慎使用。 - -**参数网格寻优（optimize）与内置策略列表（strategies）：** - -```bash -# 列出全部内置策略（名称/参数默认值/预设寻优网格） -easy-tdx strategies - -# 单策略网格寻优（预设网格或 --param 自定义，--workers 4 进程并行） -easy-tdx optimize SZ 000001 --strategy ma_cross -easy-tdx optimize SZ 000001 --strategy ma_cross --param fast=5,10,15 --param slow=20,60 - -# 一键寻优所有内置策略：逐策略按预设网格寻优后全局排名（对应 Web UI /optimize 页） -easy-tdx optimize SZ 000001 --all --workers 4 --table -``` - -**全策略批量对比（CLI）：** - -`easy-tdx run-all` 一行命令跑完 `strategies/` 下所有策略并排名： - -```bash -easy-tdx run-all SZ 300308 --count 2000 --cash 1000000 --adjust QFQ - -# 多因子组合回测 -easy-tdx run-all SZ 300308 --combo 2 --combo-mode MAJORITY - -# 加 --show 自动弹出最佳策略的资金曲线 vs 股价对比图 -easy-tdx run-all SZ 300308 --count 2000 --cash 1000000 --adjust QFQ --show - -# 自定义策略目录 -easy-tdx run-all SZ 300308 --strategies-dir my_strategies/ -``` - -也可使用项目自带的 `run_all_strategies.py` 脚本（功能相同）： - -```bash -python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ - -# 加 --show 自动弹出最佳策略的资金曲线 vs 股价对比图 -python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ --show -``` - -**多因子组合回测：** - -自动遍历所有 2 因子 / 3 因子组合，找到最优搭配： - -```bash -# 自动寻找最佳 2 因子和 3 因子组合（MAJORITY 模式） -python -X utf8 run_all_strategies.py SZ 300308 --combo 2 --combo 3 --combo-mode majority - -# CLI 方式 -easy-tdx run-all SZ 300308 --combo 2 --combo 3 --combo-mode majority -``` - -CLI 指定策略文件组合： - -```bash -easy-tdx backtest SZ 000001 \ - --combo-strategies strategies/macd_cross.py,strategies/rsi_reversal.py,strategies/bollinger_breakout.py \ - --combo-mode majority --table -``` - -Python API： - -```python -from easy_tdx.backtest import CombinationRunner - -runner = CombinationRunner( - strategy_classes=[MACDStrategy, RSIStrategy, BollingerStrategy], - df=df, cash=100000, -) -results = runner.screen(combo_sizes=(2, 3), mode="MAJORITY") -for r in results[:5]: - print(f"{r.name}: 收益={r.result.performance['total_return']:.2%}") -``` - -信号合并模式： - -| 模式 | 买入条件 | 卖出条件 | 特点 | -|------|---------|---------|------| -| `AND` | 所有因子都看多 | 所有因子都看空 | 极保守，交易少但精确 | -| `MAJORITY` | 过半因子看多 | 过半因子看空 | 平衡，推荐默认 | -| `OR` | 任一因子看多 | 任一因子看空 | 激进，信号多噪声大 | - -`--show` 会用 matplotlib 弹出一个双轴对比窗口：左轴蓝色线是归一化股价，右轴红色线是最佳策略的资金曲线，绿三角=买入、黄三角=卖出，标题显示股票名称和关键绩效指标。需要 `pip install matplotlib`。 - -**多标的组合回测（portfolio）：** - -`easy-tdx portfolio` 对多只股票同时回测，共享资金池，按均等比例分配，汇总组合整体绩效： - -```bash -# 两只股票组合回测 -easy-tdx portfolio --stocks SZ:000001,SH:600519 --strategy-file strategies/ma_cross.py --table - -# 自定义资金和周期 -easy-tdx portfolio --stocks SZ:000001,SH:600519,SH:600036 \ - --strategy-file strategies/expma_cross.py --cash 500000 --period DAILY --count 1000 --table - -# 搭配缠论桥接 -easy-tdx portfolio --stocks SZ:000001,SH:600519 \ - --strategy-file strategies/chanlun_strategy.py --chanlun-level DAILY --table - -# 组合级 Walk-Forward / 一条龙评估（与 Web UI /portfolio 页同构） -easy-tdx portfolio --stocks SZ:000001,SH:600519 \ - --strategy-file strategies/ma_cross.py --wf --wf-windows 7 -easy-tdx portfolio --stocks SZ:000001,SH:600519 \ - --strategy-file strategies/ma_cross.py --evaluate -``` - -输出示例： - -``` -=== 组合回测绩效概要 === -标的数量: 3 -总资金: 200,000 -组合收益率: 28.50% -组合年化: 28.50% - -── 各标的详情 ── - SZ000001: 收益=35.20% 夏普=0.92 回撤=15.30% 分配=33% 交易=12 - SH600519: 收益=18.40% 夏普=0.68 回撤=8.50% 分配=33% 交易=8 - SH600036: 收益=31.90% 夏普=0.85 回撤=12.10% 分配=33% 交易=15 -``` - -| 参数 | 说明 | -|------|------| -| `--stocks` | 股票列表：逗号分隔的 `市场:代码`（如 `SZ:000001,SH:600519`） | -| `--cash` | 总资金（默认 20 万） | -| `--allocation` | 资金分配方式（目前支持 `equal` 均等分配） | -| `--chanlun-level` | 自动计算缠论分析并注入策略（如 DAILY/30MIN） | - -### 通达信公式（v1.27） - -粘贴通达信公式即可计算 / 选股 / 回测——命名布尔输出自动成为买卖信号（名字含「买/卖」或 BUY/SELL 优先），30+ 白名单函数（MA/EMA/SMA/HHV/LLV/REF/CROSS/LONGCROSS/MACD/KDJ/RSI/BOLL/ATR…）向量化求值，无未来数据： - -```bash -# 公式计算（最后一根各列值 + 最近信号明细） -easy-tdx formula compute SH 600519 --formula "金叉: CROSS(MA(C,5), MA(C,20));" - -# 批量选股：信号在最后一根 = 1 的标的（--symbols 支持逗号分隔或 @文件） -easy-tdx formula screen --symbols SH:600519,SZ:000001 --formula "金叉: CROSS(MA(C,5), MA(C,20));" - -# 公式回测：买/卖列自动挑选，信号下一根开盘成交，输出绩效 + 评级 + 评分 -easy-tdx formula backtest SH 600519 --file my_formula.txt -``` - -### 本地 K 线仓库（v1.26） - -行情沉淀为 DuckDB 单文件列存（可选依赖：`pip install easy-tdx[warehouse]`），增量同步 + 临时收盘价状态机 + 健康自检： - -```bash -easy-tdx warehouse sync --symbols SH:600519,SZ:000001 # 首次全量，此后只补尾部 -easy-tdx warehouse query SH 600519 --count 30 # 默认忽略未收盘的临时 bar -easy-tdx warehouse stats # 各标的行数 / 数据范围 -easy-tdx warehouse check # 缺口 / 除权跳变 / 新鲜度体检 -``` - -**行情终端 + 回测可视化 Web UI（v1.17 新增，v1.23 升级为行情终端）：** - -Web UI 截图 1 - -Web UI 截图 2 - -Web UI 截图 3 - -不想写命令行？用浏览器。`easy-tdx serve` 一条命令启动，浏览器自动打开 `http://localhost:8000`。 - -Web UI 包含两大模块： - -- **行情终端**——侧边栏专业终端布局（行情：市场看板 / 行业总览 / 概念总览 / 自选行情 / 龙头池 / 期货持仓排名）： - - **市场看板**：五大指数实时行情（SSE 推送）、全市场涨跌统计（涨/跌/平/涨停/跌停 + 堆叠条）、行业/概念板块热度榜、涨幅榜/跌幅榜、两市异动雷达（加速拉升/封涨停板/大单托盘等），点击个股打开五档盘口 + 分时/日K 对话框； - - **行业总览 / 概念总览**（v1.32.1）：全部行业（一级/二级可切）/概念板块一屏尽览——板块广度统计条、涨跌幅分布直方图、热力图与表格双视图、搜索过滤、涨幅/跌幅/涨速异动三榜、翻红/翻绿轮动时间线，30s 自动刷新（休市暂停）；点击板块复用详情弹窗（分时/日K + 成分股涨跌榜直达个股）； - - **自选行情**：输入 6 位代码一键加自选（SQLite 持久化），全表实时刷新（SSE），行内迷你分时图，点击行看个股详情； - - **龙头池**：159 只核心龙头名单一键只扫龙头（名单仅为扫描范围，不构成任何推荐）； - - **期货持仓排名**（v1.29.1）：中金所每日成交/持仓前 20 名会员一键采集（品种下拉 + 日期选择 + 自动回溯最近交易日开关），合约页签自动标注主力，前 20 名合计多单/空单/净持仓概览，三组排名并排表格；附「品种一览」「多单空单加减仓怎么看」新手科普（重点：排名看不出套保还是投机，空单多 ≠ 看空市场）； - - **实时推送架构**：后端单条轮询循环 fan-out 到所有 SSE 连接（交易时段 ~8s 一拍，盘外降频 60s，无人订阅自动休眠），前端指数退避重连。 -- **回测工作台**——浏览器里选标的、挑策略、调参数，K 线买卖点、净值回撤、25 项绩效指标一目了然。支持组合回测、参数网格寻优、多策略结果对比、策略库（SQLite 持久化）与多策略资金分仓、信号雷达、Walk-Forward / 一条龙附加分析、**AI 解读与解读历史**（分析：单标的回测 / 组合回测 / 参数寻优 / 结果对比 / 策略库 / 信号雷达 / AI 解读历史），全程零代码。 - -**前置条件：** - -```bash -# 需安装 web 可选依赖（FastAPI + Uvicorn） -pip install -e ".[web]" -``` - -**启动（一条命令）：** - -```bash -# 启动后端 + 自动打开浏览器（默认 http://localhost:8000） -easy-tdx serve - -# 自定义端口/不自动开浏览器 -easy-tdx serve --port 8080 --no-open-browser -``` - -> 后端启动后约 1-2 秒会自动弹出浏览器。前端界面已编译进 `web-ui/dist/`，由后端同源托管，无需单独跑前端开发服务器。后端行情连接失败时回测路由仍可用（用内联数据），但取行情功能需要后端连通通达信服务器。 - -**不想装 Python？下载 EXE 直接用（面向零基础用户）：** - -Windows 用户可以下载打包好的单一 EXE（约 80-150MB），双击即可使用，无需安装 Python/Node 或任何依赖： - -1. 到 [Releases 页面](../../releases) 下载最新的 `easy-tdx-<版本>-windows.exe` -2. 双击运行（首次会被 SmartScreen 拦截，点"更多信息 → 仍要运行"） -3. 等待 2-5 秒，浏览器自动打开回测界面 -4. 右下角任务栏出现小图标，右键 → "退出" 可关闭 - -EXE 打包方法见 [`docs/packaging.md`](./docs/packaging.md)。 - -打开浏览器后，「分析」分组下是回测工作台的核心页面： - -**1. 单标的回测**（首页 `/`） - -左侧配置面板从上到下填写，右侧自动出图： - -- **取行情**：选市场（深/沪/北），填 6 位代码，选周期（日线/周线/分钟线），设日期范围（默认最近 3 年），点「取行情」。超过 800 根会自动翻页拼接 -- **选策略**：下拉选 18 个内置策略之一（双均线交叉、MACD、布林带、RSI、KDJ、唐安奇通道、CCI 等），选中后参数表单自动出现，按推荐范围调参 -- **资金与成本**：初始资金、佣金率、滑点、成交模式（默认 next_open 下一根开盘成交） -- 点「开始回测」，右侧依次出：K 线主图（红三角=买入、绿钉=卖出）、净值曲线与回撤双轴图、25 项绩效指标表（总收益/夏普/最大回撤/胜率/盈亏比/Ulcer/VaR/SQN 等）、成交记录明细 -- 结果区右上角有「💾 保存策略」按钮，把当前策略 + 标的 + 成绩快照存进策略库，下次直接载入或参与组合回测 - -**2. 组合回测**（`/portfolio`） - -- 添加多只标的（如 SZ:000001、SH:600519），选策略和日期范围 -- 点「开始组合回测」，右侧出：组合整体绩效（加权收益率）、组合净值曲线（各标的按日期对齐求和）、各标的净值归一化叠加对比图、各标的绩效横向对比表 -- 同样有「保存策略」按钮，可把整个组合配置存进策略库 - -**3. 参数寻优**（`/optimize`） - -- 先取行情（同单标的），选策略 -- 勾选 1-2 个想寻优的参数，填入取值列表（逗号分隔，如 fast 填 `5,10,20,30`），页面实时显示网格点数（上限 200） -- 点「开始寻优」，右侧出：最优结果摘要、参数热力图（2 参数时，颜色映射收益率）、所有网格点排名表 -- 排名表每行有「查看」按钮，点击跳转单标的回测页，自动填充该参数组合跑完整回测 - -**4. 结果对比**（`/compare`） - -- 左侧列出最近 20 个已完成的回测任务（含单标的和组合） -- 勾选 2-4 个，右侧出：归一化净值叠加图（初始=1，看相对走势）、8 项核心指标横向对比表（总收益/夏普/最大回撤/胜率/盈亏比/交易数/年化/波动率） - -**5. 策略库**（`/strategies`，v1.17.11 新增） - -- 保存你觉得不错的策略，下次直接载入或重跑。数据存在本地 SQLite 单文件（`~/.easy_tdx/strategies.db`，重启不丢） -- 每张卡片展示策略名、标的、保存时的成绩快照（总收益/夏普/回撤）、标签、备注、创建时间 -- **载入**：点「载入」跳转对应回测页（单标的/组合），自动回填标的、日期、策略参数，可直接重跑 -- **多策略组合回测**：勾选多个单标的策略（卡片左上角复选框），点顶部「组合回测(N)」——每个策略各拿 1/N 资金、各跑在它保存时的原标的上（取最新行情），净值曲线按日期对齐求和，看综合表现。结果区展示：组合净值曲线、25 项完整绩效指标（与单标的同口径）、各策略绩效对比表、净值叠加图、各策略当前持仓表（回测结束时谁还套着票） - -> ⚠️ **任务不持久化**：回测结果存在后端进程内存，重启 `easy-tdx serve` 后清空。对比页只能选当前运行期间产生的任务。**策略库除外**——保存到策略库的策略持久存在 SQLite，重启不丢。 - -技术栈：Vue 3 + Vite + TypeScript + Pinia + ECharts（按需引入，构建产物约 800KB）。前端代码在 `web-ui/` 目录，独立 `package.json`，不依赖 Python 环境。 - - - -``` -发现 9 个策略文件 -标的: SZ 300308 | K线: 2000 | 资金: 1,000,000 | 复权: QFQ -================================================================================ - ->> 运行策略: bias_reversal ... 完成 (2.4s) ->> 运行策略: bollinger_breakout ... 完成 (0.6s) ->> 运行策略: expma_cross ... 完成 (0.6s) ->> 运行策略: kdj_golden ... 完成 (0.1s) ->> 运行策略: ma_cross ... 完成 (1.4s) ->> 运行策略: macd_cross ... 完成 (2.1s) ->> 运行策略: rsi_reversal ... 完成 (0.2s) ->> 运行策略: turtle_breakout ... 完成 (0.1s) ->> 运行策略: volume_price ... 完成 (6.3s) - -================================================================================ -[*] 策略绩效排名 (按总收益率降序) -================================================================================ - 排名 策略 总收益率 年化收益 最大回撤 夏普 胜率 交易次数 盈亏比 ----------------------------------------------------------------------------------------------------- - *1* 1 expma_cross 1413.51% 40.85% 76.75% 0.88 20.8% 24 6.45 - *2* 2 ma_cross 1258.07% 38.94% 58.01% 0.87 38.2% 55 2.21 - *3* 3 turtle_breakout 905.07% 33.76% 48.30% 0.83 75.0% 4 10.14 - 4 bias_reversal 504.94% 25.47% 42.25% 0.70 66.3% 95 2.08 - 5 macd_cross 387.67% 22.11% 61.08% 0.60 40.0% 85 2.20 - 6 volume_price 247.72% 17.01% 65.73% 0.50 43.3% 254 1.40 - 7 bollinger_breakout 169.65% 13.32% 49.71% 0.44 66.7% 24 1.93 - 8 rsi_reversal 95.89% 8.85% 56.51% 0.33 57.1% 7 2.48 - 9 kdj_golden 89.10% 8.36% 61.86% 0.32 66.7% 3 10.49 -``` - -综合评分（夏普 × 0.4 + 收益/回撤 × 0.3 + 胜率 × 0.3）： - -``` - *1* 1 turtle_breakout 23.04 0.83 0.70 75.0% - *2* 2 bias_reversal 20.35 0.70 0.60 66.3% - *3* 3 bollinger_breakout 20.26 0.44 0.27 66.7% -``` - -换一个标的再跑： - -```bash -# 贵州茅台 -python -X utf8 run_all_strategies.py SH 600519 --count 2000 --cash 1000000 --adjust QFQ -``` - -#### `--show` 可视化效果 - -

-
- SH601088 中国神华 — bollinger_breakout 策略 | 收益 1281.8% -

- -

-
- SH600522 中天科技 — kdj_golden 策略 | 收益 568.6% -

- -

-
- SH601179 中国西电 — expma_cross 策略 | 收益 168.0% -

- -

-
- SH600519 贵州茅台 — bollinger_breakout 策略 | 收益 187.0% -

- -> **⚠️ Demo 展示，不作为操作依据。** 历史回测收益不代表未来表现，策略参数未经过样本外验证。 - -#### 自带策略示例 - -`strategies/` 目录下有 16 个开箱即用的策略文件，可直接用于 `--strategy-file`： - -| 文件 | 策略 | 类型 | 适合行情 | -|------|------|------|----------| -| `ma_cross.py` | 双均线交叉（MA5/MA20） | 趋势跟踪 | 单边趋势 | -| `expma_cross.py` | EMA12/EMA50 交叉 | 趋势跟踪 | 单边趋势（比 MA 更灵敏） | -| `macd_cross.py` | MACD 金叉死叉 | 趋势跟踪 | 中长线趋势 | -| `bollinger_breakout.py` | 布林带突破 | 震荡反转 | 横盘震荡 | -| `rsi_reversal.py` | RSI 超买超卖 | 反转 | 震荡市 | -| `kdj_golden.py` | KDJ 低位金叉/高位死叉 | 反转 | 短线震荡 | -| `turtle_breakout.py` | 海龟交易法（唐安奇通道） | 趋势突破 | 牛市启动 | -| `bias_reversal.py` | 乖离率反转 | 反转 | 震荡回归 | -| `volume_price.py` | 量价配合 | 综合判断 | 放量突破 | -| `zhuoyao_momentum.py` | 捉妖大师多周期共振 | 趋势跟踪 | 多周期共振强势股 | -| `dmi_trend.py` | DMI/ADX 趋势强度跟踪 | 趋势跟踪 | 单边趋势（过滤震荡） | -| `cci_breakout.py` | CCI ±100 区间突破 | 区间突破 | 震荡转趋势 | -| `mfi_volume.py` | MFI 量价反转 | 量价反转 | 震荡市（带量能确认） | -| `trix_cross.py` | TRIX 三重平滑趋势交叉 | 趋势跟踪 | 中长线（抗噪音） | -| `mtm_momentum.py` | MTM 动量零线穿越 | 动量 | 趋势拐点 | -| `obv_trend.py` | OBV 能量潮趋势 | 量价趋势 | 资金持续流入的上升趋势 | - -编写自定义策略只需继承 `Strategy` 基类： - -```python -from easy_tdx.backtest import Strategy -from easy_tdx import MyTT - - -class MyStrategy(Strategy): - def init(self): - self.ma = self.I(MyTT.MA, self.data.close, 10) - - def next(self): - if self.data.close[0] > self.ma[self._bar_index]: - self.buy(size=0) # size=0 表示全仓 - elif self.position["size"] > 0: - self.sell(size=0) # size=0 表示清仓 -``` - -完整 API 参考：[docs/backtest_usage.md](docs/backtest_usage.md) - -### 量化因子与组合管理 - -新增三大模块：**因子引擎**（19 个内置因子 + 自定义扩展）、**因子分析**（IC/分层/衰减）、**组合管理**（4 种优化器 + 再平衡引擎）。加上**高级回测增强**：可插拔滑点模型（方根冲击/成交量比例）、执行仿真（TWAP/VWAP/限价单）、归因分析（Brinson + 因子归因）。 - -```python -from easy_tdx.factor import FactorEngine, FactorAnalyzer, preprocess -from easy_tdx.portfolio import RebalanceEngine, FactorWeightedOptimizer -from easy_tdx.backtest import BacktestEngine -from easy_tdx.backtest.slippage import SquareRootSlippage -from easy_tdx.backtest.execution import TWAPExecution - -# 因子研究 -engine = FactorEngine() -factor_data = engine.compute_cross_section(data, ["momentum_20d", "rsi_14"]) -clean = preprocess(factor_data, ["momentum_20d", "rsi_14"]) -forward_returns = engine.compute_forward_returns(data, period=5) -report = FactorAnalyzer(clean, forward_returns).full_report("momentum_20d") -print(f"IC均值={report.mean_ic:.4f} ICIR={report.icir:.4f}") - -# 组合回测 -result = RebalanceEngine( - FactorWeightedOptimizer(), factor_name="momentum_20d", n_stocks=50, cash=1_000_000, -).run(data, start_date=20230101, end_date=20240101) -print(f"年化={result.performance['annual_return']:.2%}") - -# 高级回测（滑点 + 执行仿真） -engine = BacktestEngine( - MyStrategy, cash=1_000_000, - slippage_model=SquareRootSlippage(impact_coeff=0.1), - execution_model=TWAPExecution(n_bars=3), -) -``` - -详细用法和完整工作流示例：**[docs/quantitative-guide.md](docs/quantitative-guide.md)** - -### 策略选股扫描（screen） - -把策略翻转成选股器：给定一个策略，扫描全市场找出今天触发买入信号的股票，再对这些信号做历史回测排名。**纯离线数据**，读取本地通达信 `.day` 文件，全市场约 30-60 秒。 - -两步走工作流： - -**第一步：信号扫描（scan）** - -```bash -# 扫描沪深全 A，找出 RSI 超卖触发的股票 -easy-tdx screen scan --strategy strategies/rsi_reversal.py --output signals.json - -# 缩小范围 -easy-tdx screen scan --strategy strategies/macd_cross.py --universe sz --output signals.json - -# 从自定义股票列表扫描 -easy-tdx screen scan --strategy strategies/bollinger_breakout.py --universe my_stocks.txt --output signals.json - -# 并发扫描（推荐 4-8 进程，速度提升 4-8 倍） -easy-tdx screen scan --strategy strategies/rsi_reversal.py --workers 4 --output signals.json - -# 增量扫描（缓存未修改的 .day 文件，跳过重复计算） -easy-tdx screen scan --strategy strategies/rsi_reversal.py --cache scan_cache.json --output signals.json -``` - -输出示例（JSON）： - -```json -{ - "scan_time": "2026-06-10T18:30:00", - "strategy": "RSIStrategy", - "total_scanned": 4832, - "total_signals": 37, - "signals": [ - {"code": "000001", "market": "SZ", "signal_date": 20260610, "last_close": 12.35}, - {"code": "600519", "market": "SH", "signal_date": 20260610, "last_close": 1800.0} - ] -} -``` - -**第二步：回测排名（rank）** - -```bash -# 按夏普比率排名（默认） -easy-tdx screen rank --from signals.json --sort sharpe --top 20 --table - -# 按最大回撤排名（越小越好，用 --sort-reverse） -easy-tdx screen rank --from signals.json --sort max_drawdown --sort-reverse --table - -# 管道模式：一步到位 -easy-tdx screen scan --strategy strategies/rsi_reversal.py | easy-tdx screen rank --from - --table - -# 补齐股票名称（需要网络） -easy-tdx screen rank --from signals.json --sort sharpe --top 10 --table --names -``` - -输出示例（`--table`）： - -``` -[*] 信号排名 (按 sharpe 降序, 共 37 只) -══════════════════════════════════════════════════════════════════════════ -排名 代码 名称 总收益率 年化收益 最大回撤 夏普 胜率 交易 - *1 SZ300308 中际旭创 45.23% 18.72% 12.35% 1.85 62.5% 16 - *2 SH600519 贵州茅台 38.10% 15.90% 8.21% 1.62 58.3% 12 -``` - -| 参数 | 说明 | -|------|------| -| `--universe` | `all`（默认，沪深全 A）/ `sh` / `sz` / 文件路径（每行 "市场 代码"） | -| `--vipdoc` | 离线数据目录（默认自动检测通达信安装路径） | -| `--workers` | 并发进程数：`0` 串行（默认）/ `2+` ProcessPoolExecutor 并发（推荐 4-8） | -| `--cache` | 增量扫描缓存文件路径（JSON，mtime 未变的文件自动跳过） | -| `--sort` | 排序指标：`sharpe`（默认）/ `total_return` / `max_drawdown` / `win_rate` 等 | -| `--sort-reverse` | 升序（用于回撤等越小越好的指标） | -| `--names` | 在线补齐股票名称（默认关闭，只查排名中的几十只） | -| `--count` | rank 使用最近 N 条 K 线（0=全部，默认 0） | - -#### 强势股排名（strength） - -按 **5 / 20 / 60 日涨幅加权**合成强势分，从全市场选出"最近最强"的股票。**纯离线数据**，读取本地通达信 `.day` 文件，全市场约 30-60 秒（并发可压到 10 秒内）。 - -**三种预设模式：** - -| 模式 | 性格 | 权重 (w5/w20/w60) | 波动率惩罚 | 适合 | -|------|------|-------------------|-----------|------| -| `steady`（默认） | 中长期稳健 | 0.2 / 0.3 / 0.5 | ✅ 除以 vol_20 | 选"稳着涨"的票，妖股被高波动压低 | -| `breakout` | 近期妖股爆发 | 0.6 / 0.3 / 0.1 | ❌ 纯加权涨幅 | 选"短期最猛"的票，妖股本身就是高波动 | -| `balanced` | 三周期均衡 | 等权 + vol 调整 | ✅ 除以 vol_20 | 不确定时的安全默认 | - -> 💡 **为什么 breakout 不除波动率？** 妖股本质高波动，除以 vol 会把它压下去，与"找妖股"目标矛盾。steady 除以 vol 是为了奖励"稳着涨"的票（vol 小，score 放大）。 - -```bash -# 中长期稳健强势 Top 50（默认 steady 模式） -easy-tdx screen strength --preset steady --top 50 --table - -# 近期妖股爆发 Top 20（补齐股票名称） -easy-tdx screen strength --preset breakout --top 20 --names --table - -# 三周期均衡 -easy-tdx screen strength --preset balanced --top 30 --table - -# 自定义权重（自动归一化，5:3:2 = 0.5:0.3:0.2） -easy-tdx screen strength --w5 0.5 --w20 0.3 --w60 0.2 --top 30 --table - -# 并发扫描（推荐 4-8 进程） -easy-tdx screen strength --preset steady --top 100 --workers 4 --table - -# 过滤低流动性（最近 5 日日均成交额 ≥ 5000 万） -easy-tdx screen strength --preset breakout --top 30 --min-amount 50000000 --table - -# 缩小范围 + 输出到文件 -easy-tdx screen strength --universe sz --top 30 --output sz_strength.json -``` - -输出示例（`--table`）： - -``` -[*] 强势股排名 [steady] 共 50 只 - 数据截止: 2026-06-24 | 中长期稳健强势：权重偏 60 日，波动率惩罚，选出稳着涨的票 -════════════════════════════════════════════════════════════════════════════════ -排名 代码 名称 现价 5日 20日 60日 波动率 强势分 - *1 SZ300308 中际旭创 85.20 8.12% 15.34% 30.21% 0.0180 9.52 - *2 SH600519 贵州茅台 1800.00 3.25% 5.10% 10.05% 0.0120 6.21 -``` - -输出示例（JSON）： - -```json -{ - "scan_time": "2026-06-25T10:30:00", - "preset": "steady", - "preset_desc": "中长期稳健强势：权重偏 60 日，波动率惩罚...", - "data_date": 20260624, - "total_ranked": 50, - "ranking": [ - {"rank": 1, "code": "300308", "market": "SZ", "name": "中际旭创", - "last_close": 85.20, "last_date": 20260624, - "ret_5": 0.0812, "ret_20": 0.1534, "ret_60": 0.3021, - "vol_20": 0.0180, "strength": 9.52} - ] -} -``` - -| 参数 | 说明 | -|------|------| -| `--preset` | 预设模式：`steady`（默认）/ `breakout` / `balanced` | -| `--w5` `--w20` `--w60` | 自定义三周期权重（覆盖预设，自动归一化） | -| `--vol-adjusted` / `--no-vol-adjusted` | 波动率惩罚开关（覆盖预设） | -| `--top` | 返回前 N 名（默认 50） | -| `--universe` | `all`（默认）/ `sh` / `sz` / 文件路径 | -| `--min-listed-days` | 最小上市天数（默认 65，保证能算 60 日涨幅） | -| `--min-amount` | 最近 5 日日均成交额下限（元，默认 0 不过滤） | -| `--workers` | 并发进程数：`0` 串行 / `4+` 并发（推荐 4-8） | -| `--names` | 在线补齐股票名称（默认关闭） | -| `--output` | 输出 JSON 文件（默认 stdout） | - -> ⚠️ **数据时效**：strength 依赖本地 `.day` 文件。输出中的 `data_date` / `last_date` 字段标注数据截止日，请先用 `easy-tdx offline sync` 同步最新数据。 - -### 捉妖大师（重点） - -捉妖大师是多周期涨幅共振指标，通过 20/60/120 日涨幅及指数平滑判断短中长线趋势是否同向，用于筛选趋势刚启动的强势股。 - -```bash -easy-tdx indicator ZHUOYAO -m SH -c 600519 --count 30 --table - -# 自定义周期参数 -easy-tdx indicator ZHUOYAO -m SZ -c 000001 --params N1=90,N2=45,N3=15 - -# 结合其他指标一起看 -easy-tdx indicator ZHUOYAO,MACD,KDJ -m SH -c 600519 --count 20 --table -``` - -输出列说明： - -| 列名 | 含义 | -|------|------| -| `ZY_LONG` | 长线 — 120 日涨幅的 10 日指数平滑 | -| `ZY_MID` | 中线 — 60 日涨幅(%) | -| `ZY_SHORT` | 短线 — 20 日涨幅(%) | -| `ZY_TREND` | 趋势 — 中线的 10 日指数平滑 | - -**核心信号：** 四线全部 > 0 且短线 > 中线 > 长线 = 短中长趋势完全一致向上，是强势股特征。详见 [捉妖大师指标详解](docs/indicator-zhuoyao.md)。 - -### 30日乖离率信号（重点） - -30日乖离率信号指标，在标准乖离率（BIAS）基础上叠加短/长信号线，通过三者位置关系判断趋势方向和转折点。源自通达信经典指标。 - -```bash -easy-tdx indicator BIAS_SIGNAL -m SH -c 600519 --count 60 --table - -# 自定义周期参数 -easy-tdx indicator BIAS_SIGNAL -m SZ -c 000001 --params P=5,M=20 - -# 结合其他指标一起看 -easy-tdx indicator BIAS_SIGNAL,MACD,KDJ -m SH -c 600519 --count 30 --table -``` - -输出列说明： - -| 列名 | 含义 | -|------|------| -| `BS_X` | M日乖离率 — 当前价格偏离30日均线的百分比 | -| `BS_SMA` | 短周期信号线 — 乖离率的 P 日均线，过滤短期噪音 | -| `BS_LMA` | 长周期信号线 — 乖离率的 M 日均线，捕捉中期趋势方向 | - -**核心信号：** X > S_SMA 且 X_LMA 上升 = 多头确认（通达信红色）；S_SMA > X 或 X_LMA 下降 = 空头预警（通达信绿色）。多空判断非对称设计——多头需两个条件同时满足，空头只需其一，偏向保守预警。详见 [30日乖离率信号指标详解](docs/indicator-bias-signal.md)。 - -```python -# Python API 用法 -from easy_tdx import MacClient, Market - -with MacClient.from_best_host() as c: - df = c.get_stock_kline_with_indicators( - Market.SH, "600519", - indicators=["BIAS_SIGNAL"], - count=60, - ) - # df 包含: datetime, open, close, high, low, vol, amount - # + BS_X, BS_SMA, BS_LMA -``` - -支持 34 个指标：MACD, KDJ, RSI, BOLL, DMI, ATR, WR, CCI, BIAS, BIAS_SIGNAL, OBV, VR, EMV, MFI, BRAR, ASI, TRIX, DPO, MTM, ROC, EXPMA, BBI, PSY, DFMA, CR, KTN, XSII, MASS, TAQ, ZHUOYAO, SAR, VWAP, AROON, FK。 - -```python -# Python API 用法 -from easy_tdx import MacClient, Market - -with MacClient.from_best_host() as c: - df = c.get_stock_kline_with_indicators( - Market.SH, "600519", - indicators=["ZHUOYAO"], - count=30, - ) - # df 包含: datetime, open, close, high, low, vol, amount - # + ZY_LONG, ZY_MID, ZY_SHORT, ZY_TREND -``` - -支持 34 个指标：MACD, KDJ, RSI, BOLL, DMI, ATR, WR, CCI, BIAS, BIAS_SIGNAL, OBV, VR, EMV, MFI, BRAR, ASI, TRIX, DPO, MTM, ROC, EXPMA, BBI, PSY, DFMA, CR, KTN, XSII, MASS, TAQ, ZHUOYAO, SAR, VWAP, AROON, FK。 - -### 财务 - -```bash -easy-tdx f10 600519 # 茅台利润表，最近 8 期（默认 lrb） -easy-tdx f10 600519 --type fzb --num 4 # 资产负债表，最近 4 期 -easy-tdx f10 000001 --type llb --table # 平安现金流量表，表格输出 -``` - -> 新浪财经数据源，``--type`` 支持 ``lrb``（利润表）/``fzb``（资产负债表）/``llb``（现金流量表）。 -> 独立于 TDX 行情服务器，``item_value`` 已转 float 可直接数值计算，同比附 ``{科目}_同比`` 列。 - -### 通达信原生 F10 与最新财务快照 - -走通达信协议（与 Web 层 ``/finance`` ``/company/*`` 端点同源），覆盖 ``f10``（新浪三表）之外的 F10 全文板块。完整示例见 [examples/06_finance/](./examples/06_finance/README.md)。 - -```bash -easy-tdx finance-info SH 600519 --table # 最新财务快照（30+ 项单期指标） -easy-tdx company-info SH 600519 # F10 板块目录（最新提示/公司概况/...） -easy-tdx company-info SH 600519 "公司概况" # 读板块完整正文（自动解析+读全，无需 offset/length） -easy-tdx company-info SH 600519 600519.txt # 也可直接传文件名（此时用 --offset/--length） -``` - -- ``finance-info``：最新一期财务快照，含股本结构、资产负债、利润、现金流、每股指标（37 字段）。与 ``f10`` 互补——前者是单期快照，后者是多期三表。 -- ``company-info``：**一个命令两种用法**——无板块名参数列 F10 板块目录，有板块名参数读正文。目录含 16 个板块（最新提示、公司概况、财务分析、股东研究、股本结构、资本运作、业内点评、行业分析、公司大事、研究报告、经营分析、主力追踪、分红扩股、高层治理、龙虎榜单、关联个股）。 -- 读正文时传板块名即可自动读取完整内容（按目录 length 分块循环，大板块如「公司大事」也能一次读全）；``--offset``/``--length`` 仅在传文件名时生效。通达信多服务器目录版本不一致时自动重试命中。 - - -### 扩展市场（港股/美股/期货） - -```bash -easy-tdx ex markets # 列出可用市场 -easy-tdx ex kline HK_MAIN_BOARD 00700 --count 30 --table # 港股 K 线 -easy-tdx ex kline US_STOCK AAPL --table # 美股 K 线 -easy-tdx ex quote US_STOCK TSLA --table # 美股报价 -easy-tdx ex quote-list HK_MAIN_BOARD --table # 港股商品列表 -easy-tdx ex tick HK_MAIN_BOARD 00700 --table # 港股分时 -``` - -### 离线数据（读取 + 写入同步） - -从本地通达信安装目录直接读取数据文件，无需网络连接： - -```bash -easy-tdx offline home # 检测通达信安装目录 -easy-tdx offline daily SH 600000 --count 10 --table # A 股日线 -easy-tdx offline min SZ 000001 --type lc5 --table # 分钟线（5min/lc1/lc5） -easy-tdx offline ex-files --table # 列出扩展市场可用文件 -easy-tdx offline ex-daily 38#2_CPI --count 5 --table # 扩展市场日线（期货/港股/外盘） -easy-tdx offline gbbq C:\new_jyplug\T0002\hq_cache\gbbq --table # 股本变迁 -easy-tdx offline financial C:\new_jyplug\vipdoc\fin\gpcw20260331.dat # 历史财务 -easy-tdx offline blocks C:\new_jyplug\T0002\blocknew --table # 自定义板块 -``` - -从服务端获取最新日线并写入本地 .day 文件，替代通达信内置下载功能： - -```bash -# 同步单只股票日线（自动增量/全量） -easy-tdx offline sync-daily SZ 000001 -easy-tdx offline sync-daily SH 600519 --vipdoc C:\new_jyplug\vipdoc - -# 一键同步沪深全市场（每天一条命令） -easy-tdx offline sync-all -``` - -> 建议在通达信关闭时执行 sync 命令，避免文件被锁定。空文件自动全量下载，已有数据只做增量追加。 - -## Web API - -将 easy-tdx 暴露为 REST + WebSocket 服务，供前端、其他语言或远程调用。无需额外注册，零配置启动。 - -### 安装 - -```bash -# 标准安装 -pip install easy-tdx[web] - -# 开发模式（从源码安装，支持热重载） -pip install -e ".[web]" -``` - -### 快速启动 - -```bash -# 启动 Web API 服务器（自动连接最优 TDX 服务器） -easy-tdx serve - -# 启动后浏览器打开 http://127.0.0.1:8000/docs 查看完整 API 文档（Swagger UI） -# 也可以访问 http://127.0.0.1:8000/redoc 查看 ReDoc 格式文档 - -# 指定端口和 TDX 服务器 -easy-tdx serve --port 8080 --tdx-host 119.147.212.81 - -# 开发模式（代码修改后自动重载） -easy-tdx serve --reload -``` - -> 💡 启动后访问 **http://127.0.0.1:8000/docs** 可以看到完整的交互式 API 文档，支持在线调试每个接口。 - -### REST API 示例 - -```bash -# ── 基础行情 ── -# 获取深圳市场证券数量 -curl "http://localhost:8000/api/v1/security/count?market=SZ" - -# 获取股票K线 -curl "http://localhost:8000/api/v1/bars?market=SZ&code=000001&category=DAY&count=100" - -# 批量获取实时行情 -curl -X POST "http://localhost:8000/api/v1/quotes" \ - -H "Content-Type: application/json" \ - -d '{"stocks": [{"market": "SZ", "code": "000001"}, {"market": "SH", "code": "600000"}]}' - -# 市场统计 -curl "http://localhost:8000/api/v1/market/stat" - -# 全市场强势股排名（基于本地 vipdoc 数据，扫描约 30-60 秒） -# steady = 中长期稳健 / breakout = 近期妖股 / balanced = 均衡 -curl "http://localhost:8000/api/v1/market/strength?preset=breakout&top_n=20" - -# 自定义权重 + 过滤低流动性（日均成交额 ≥ 5000 万） -curl "http://localhost:8000/api/v1/market/strength?w5=0.5&w20=0.3&w60=0.2&min_amount=50000000&top_n=30" - -# 板块信息（标准协议） -curl "http://localhost:8000/api/v1/block?filename=block_gn.dat" - -# ── 板块分析（MAC 协议）── -# 行业板块列表 -curl "http://localhost:8000/api/v1/board-mac/list?board_type=HY&count=50" - -# 板块成分股（按涨幅排序） -curl "http://localhost:8000/api/v1/board-mac/members?board_symbol=881001&count=20" - -# 个股所属板块 -curl "http://localhost:8000/api/v1/board-mac/belong?market=SZ&code=000001" - -# 板块摘要（含主力净流入、涨跌家数） -curl "http://localhost:8000/api/v1/board-mac/summary?board_symbol=881001" - -# 行业板块涨幅排名 Top 10 -curl "http://localhost:8000/api/v1/board-mac/ranking?board_type=HY&top_n=10" - -# 板块 20 日涨幅排行 -curl "http://localhost:8000/api/v1/board-mac/change-ranking?board_type=HY&days=20&top_n=10" - -# ── 资金 / 信息 ── -# 个股资金流向（主力/散户净流入） -curl "http://localhost:8000/api/v1/mac/capital-flow?market=SH&code=600519" - -# 个股基本信息快照 -curl "http://localhost:8000/api/v1/mac/symbol-info?market=SZ&code=000001" - -# 服务器交易时段信息 -curl "http://localhost:8000/api/v1/mac/server-info" - -# ── 公告检索（巨潮资讯网，独立数据源）── -# 检索公司公告（无需 TDX 行情服务器） -curl "http://localhost:8000/api/v1/announcements?code=688017&count=30&page=1" -# 返回每条含 url（4 参数可直点打开）和 pdf_url（PDF 直链）： -# {"data": [{"title":"...","type":"...","date":"...","url":".../detail?stockCode=...","pdf_url":"http://static.cninfo.com.cn/.../xxx.PDF",...}], "count": 30} - -# ── 财报三表（新浪财经，独立数据源）── -# 利润表（type: lrb/fzb/llb） -curl "http://localhost:8000/api/v1/sina/financial-report?code=600519&type=lrb&num=8" -# 返回每行一期（最新在前），列为科目名（float）+ {科目}_同比（如有）： - -# ── 排行 / 竞价 / 异动 ── -# 全 A 涨幅排行前 20 -curl "http://localhost:8000/api/v1/mac/quote-list?category=A&count=20&sort_type=CHANGE_PCT" - -# 集合竞价数据 -curl "http://localhost:8000/api/v1/mac/auction?market=SZ&code=000001" - -# 市场异动行情 -curl "http://localhost:8000/api/v1/mac/unusual?market=SH&count=50" - -# ── 扩展市场（期货/港股/美股）── -# 港股 K 线 -curl "http://localhost:8000/api/v1/ex/bars?market=HK_MAIN_BOARD&code=00700&category=DAY&count=30" - -# 美股实时报价 -curl "http://localhost:8000/api/v1/ex/quote?market=US_STOCK&code=AAPL" - -# ── 技术指标 ── -# 列出所有可用指标 -curl "http://localhost:8000/api/v1/indicator/list" - -# 计算 MACD + KDJ 指标 -curl -X POST "http://localhost:8000/api/v1/indicator/compute" \ - -H "Content-Type: application/json" \ - -d '{"data": [{"open":10,"close":10.5,"high":11,"low":9.5,"vol":1000}], "indicators": ["MACD", "KDJ"]}' - -# ── 缠论分析 ── -curl -X POST "http://localhost:8000/api/v1/chanlun/analyze" \ - -H "Content-Type: application/json" \ - -d '{"market": "SZ", "code": "000001", "category": "DAY", "count": 200}' - -# ── 板块总览（一次取全部板块：当日涨跌幅 + 涨速 + 3/5/20日/YTD 涨幅 + 领涨股，服务端 15s 缓存）── -# board_type: HY 行业一级 / HY2 行业二级 / GN 概念 / FG 风格 / DQ 地区 -curl "http://localhost:8000/api/v1/board-mac/overview?board_type=HY" -curl "http://localhost:8000/api/v1/board-mac/overview?board_type=GN" - -# ── 回测任务（WebUI 回测工作台同款后端）── -# 列出内置策略及参数 schema -curl "http://localhost:8000/api/v1/backtest/strategies" -# 提交异步回测（strategy 见 /backtest/strategies；完整字段与 portfolio/multi/optimize/wf/evaluate -# 各端点的请求体以 /docs 的 Swagger 为准），返回 task_id -curl -X POST "http://localhost:8000/api/v1/backtest/run/async" \ - -H "Content-Type: application/json" \ - -d '{"strategy": "ma_cross", "symbol": "SZ:000001", "category": "DAY", "count": 2000}' -# 轮询任务结果（对比页/导出亦走 /backtest/tasks） -curl "http://localhost:8000/api/v1/backtest/tasks/" - -# ── 策略库（保存的策略持久化 SQLite）── -curl "http://localhost:8000/api/v1/strategies" - -# ── 自选股 ── -curl "http://localhost:8000/api/v1/watchlist" -curl -X POST "http://localhost:8000/api/v1/watchlist" \ - -H "Content-Type: application/json" -d '{"market": "SH", "code": "600519", "name": "贵州茅台"}' - -# ── AI 解读（模型 Key 只存本地 ~/.easy_tdx/llm.json）── -curl "http://localhost:8000/api/v1/llm/config" # 当前配置 + Provider 预设 -curl -X POST "http://localhost:8000/api/v1/llm/chat/async" \ - -H "Content-Type: application/json" \ - -d '{"prompt": "解读这份回测报告：..."}' # 后台任务，GET /llm/chat/tasks/{id} 轮询 - -# ── 交易时段（自动刷新门控用）── -curl "http://localhost:8000/api/v1/market/session" -``` - -### WebSocket 实时行情 - -`/api/v1/ws/realtime/{symbol}`（v1.28 起接通数据源）：连接即订阅指定标的，服务端 -经 `RealtimeDataFeed`（按 `interval` 秒轮询五档快照 → `EventBus`）推送 tick 帧； -连接断开自动退订，无人订阅时完全停止轮询。盘外时段默认只睡不拉（交易时段过滤）， -本地冒烟/演示可配合 `EASY_TDX_E2E_MOCK=1` 的合成行情随时验证（见 -`scripts/ws_smoke.py`）。 - -```javascript -const ws = new WebSocket("ws://localhost:8000/api/v1/ws/realtime/SZ000001"); - -ws.onmessage = (event) => { - const frame = JSON.parse(event.data); - if (frame.type === "tick") { - // {type:"tick", symbol:"SZ000001", market:"SZ", code:"000001", - // price:10.5, volume:12345, ts:1760000000.0, - // open, high, low, pre_close, amount, name} - console.log(frame.symbol, frame.price, frame.ts); - } else if (frame.type === "ping") { - // 服务端 30s 空闲心跳，忽略即可（客户端无须回包） - } -}; - -// 动态订阅更多标的（服务端回 {"type":"status","msg":"subscribed SH600000"}） -ws.send(JSON.stringify({action: "subscribe", symbol: "SH600000"})); -// 退订 -ws.send(JSON.stringify({action: "unsubscribe", symbol: "SH600000"})); -``` - -浏览器接入建议（自动重连 + 心跳容忍）：`onclose` 后指数退避重连（参考 -`web-ui/src/stores/quotes.ts` 对 SSE 的同类处理）；`{"type":"ping"}` 心跳帧直接 -忽略、不回包；连续 N 秒无任何帧（含 ping）再视为僵死连接主动重连。协议字段完整 -说明见 `docs/api_reference.md` 的 WebSocket 一节；单标的 WS 订阅与看板 SSE -（全量快照）并存不冲突，按需选用。 - -### API 文档 - -启动服务后访问： -- Swagger UI: http://localhost:8000/docs -- ReDoc: http://localhost:8000/redoc - -### 编程 API - -```python -from easy_tdx.web import create_app -import uvicorn - -app = create_app(host="119.147.212.81", port=7709) -uvicorn.run(app, host="0.0.0.0", port=8000) -``` - -## CLI 命令汇总 - -| 命令 | 说明 | -|------|------| -| `ping` | 服务器延迟测速 | -| `version` | 版本号 | -| `kline` | K 线（日/周/月/分钟，支持复权） | -| `quote` | 实时报价（单只/批量） | -| `quote-list` | 市场分类排序报价（A/SH/SZ/KCB/CYB） | -| `tick` | 分时图（单日/多日/历史） | -| `transaction` | 逐笔成交 | -| `board-list` | 板块列表（行业/概念/风格） | -| `board-members` | 板块成分股报价 | -| `board-summary` | 板块汇总（成交额、主力净流入、涨跌家数） | -| `board-ranking` | 板块涨跌幅排行榜（行业/概念排行） | -| `board-change-ranking` | 板块 N 日涨跌幅排行（支持指定截止日期） | -| `belong-board` | 个股所属板块 | -| `capital-flow` | 资金流向 | -| `auction` | 集合竞价 | -| `unusual` | 市场异动 | -| `market-stat` | 全市场涨跌统计 | -| `server-info` | 服务器交易时段 | -| `symbol-info` | 个股特征快照 | -| `indicator` | 技术指标计算（34 个：MACD/KDJ/RSI/BOLL/DMI/ATR...） | -| `indicator-list` | 列出可用技术指标 | -| `backtest` | 回测引擎（加载策略文件，输出绩效报告） | -| `portfolio` | 多标的组合回测（共享资金池，均等分配，汇总绩效） | -| `factor list` | 列出所有内置因子 | -| `factor analyze` | 因子分析（IC/分层/衰减） | -| `pfactor backtest` | 组合因子选股回测 | -| `run-all` | 批量运行所有策略并排名（绩效排名 + 综合评分 + 可选图表） | -| `optimize` | 参数网格寻优（单策略网格搜索，或 `--all` 一键寻优所有内置策略并排名） | -| `strategies` | 列出内置策略注册表（名称/中文标签/参数默认值/预设寻优网格） | -| `formula compute` | 通达信公式计算（命名布尔输出即买卖信号） | -| `formula screen` | 公式批量选股（信号在最后一根 = 1 的标的） | -| `formula backtest` | 公式回测（买/卖列自动挑选，输出绩效 + 评级 + 评分） | -| `warehouse sync` | 本地 K 线仓库增量同步（DuckDB，需 `easy-tdx[warehouse]`） | -| `warehouse query` | 仓库查询（默认忽略未收盘的临时 bar） | -| `warehouse stats` | 仓库统计（各标的行数/数据范围） | -| `warehouse check` | 仓库健康自检（缺口/除权跳变/新鲜度） | -| `ccpm` | 中金所成交持仓排名（官网每日发布，按日落盘缓存） | -| `announcement` | 公告检索（巨潮资讯网，独立数据源，支持下载 PDF） | -| `screen scan` | 策略选股扫描（纯离线，全市场信号扫描） | -| `screen rank` | 扫描结果回测排名（按夏普/回撤等指标排序） | -| `screen strength` | 强势股排名（5/20/60 日涨幅加权，steady/breakout/balanced 三预设） | -| `serve` | 启动 Web API 服务器（REST + WebSocket，需 `easy-tdx[web]`） | -| `f10` | 财报三表（新浪：利润表/资产负债表/现金流量表） | -| `finance-info` | 最新财务快照（通达信协议，30+ 项单期指标） | -| `company-info` | F10 公司信息（无板块名列目录 / 有板块名读正文） | -| `fund-flow` | 历史资金流向（CLI 暂未实现，Web API `/fund-flow/history` 可用） | -| `ex kline` | 扩展市场 K 线 | -| `ex quote` | 扩展市场报价 | -| `ex quote-list` | 扩展市场商品列表 | -| `ex tick` | 扩展市场分时 | -| `ex markets` | 列出可用扩展市场 | -| `offline home` | 检测通达信安装目录 | -| `offline daily` | A 股日线（本地 .day 文件） | -| `offline sync-daily` | 从服务端同步单只股票日线到本地 .day 文件 | -| `offline sync-all` | 一键同步沪深全市场日线（扫描本地 .day 文件） | -| `offline min` | 分钟线（本地 .5/.lc1/.lc5 文件） | -| `offline ex-files` | 列出扩展市场可用文件 | -| `offline ex-daily` | 扩展市场日线（期货/港股/外盘） | -| `offline gbbq` | 股本变迁数据 | -| `offline financial` | 历史财务数据 | -| `offline blocks` | 自定义板块数据 | - -## Python API - -### 连接管理 - -所有客户端支持 `from_best_host()` 自动选最低延迟服务器： - -```python -from easy_tdx import MacClient - -with MacClient.from_best_host() as c: - df = c.get_stock_kline(...) -``` - -| 客户端 | 端口 | 覆盖范围 | -|--------|------|----------| -| `MacClient` / `AsyncMacClient` | 7709 | A 股行情（MAC 协议，推荐） | -| `MacExClient` / `AsyncMacExClient` | 7727 | 港股/美股/期货（MAC 协议） | -| `UnifiedTdxClient` / `AsyncUnifiedTdxClient` | 自动 | A 股 + 扩展市场统一入口 | -| `TdxClient` / `AsyncTdxClient` | 7709 | A 股行情（标准协议） | - -### MAC 协议（推荐） - -#### 报价 - -```python -from easy_tdx import MacClient, Market, Category, SortType, SortOrder - -with MacClient.from_best_host() as c: - # 批量报价（最多 80 只/次） - df = c.get_stock_quotes([(Market.SH, "600519"), (Market.SZ, "000858")]) - - # 市场分类排序报价 - df = c.get_stock_quotes_list( - Category.A, count=20, - sort_type=SortType.CHANGE_PCT, - sort_order=SortOrder.DESC, - ) -``` - -返回列：`market, code, name` + 动态字段（`pre_close, open, high, low, close, vol, amount, turnover, vol_ratio` 等）。 - -#### K 线（支持复权） - -```python -from easy_tdx import MacClient, Market, Period, Adjust - -with MacClient.from_best_host() as c: - # 日K前复权 - df = c.get_stock_kline(Market.SH, "600519", Period.DAILY, count=10, adjust=Adjust.QFQ) - # 5分钟线 - df = c.get_stock_kline(Market.SZ, "000001", Period.MIN_5, count=100) -``` - -返回列：`datetime, open, close, high, low, vol, amount`。 - -#### 技术指标 - -自动获取 200+ 条历史数据预热 EMA，返回最后 `count` 条带指标的结果： - -```python -from easy_tdx import MacClient, Market, Period, Adjust -from easy_tdx.indicator import compute_indicators, list_indicators - -with MacClient.from_best_host() as c: - # 便捷方法：获取 K 线 + 计算指标一步完成（默认前复权） - df = c.get_stock_kline_with_indicators( - Market.SH, "600519", - indicators=["MACD", "KDJ", "RSI", "BOLL"], - count=30, - ) - # df 包含: datetime, open, close, high, low, vol, amount - # + MACD_DIF, MACD_DEA, MACD_HIST, KDJ_K, KDJ_D, KDJ_J, RSI, - # BOLL_UPPER, BOLL_MID, BOLL_LOWER - - # 自定义指标参数 - df = c.get_stock_kline_with_indicators( - Market.SH, "600519", - indicators=["MACD"], - params={"MACD": {"SHORT": 10, "LONG": 22}}, - ) - - # 独立使用：对已有 DataFrame 计算指标 - raw = c.get_stock_kline(Market.SH, "600519", Period.DAILY, count=200, adjust=Adjust.QFQ) - result = compute_indicators(raw, ["ATR", "CCI", "WR"], tail=30) - - # 查看所有可用指标 - for info in list_indicators(): - print(info["name"], info["description"], info["outputs"]) -``` - -支持 34 个技术指标： - -| 指标 | 输入 | 输出列 | -|------|------|--------| -| MACD | close | MACD_DIF, MACD_DEA, MACD_HIST | -| KDJ | close, high, low | KDJ_K, KDJ_D, KDJ_J | -| RSI | close | RSI | -| BOLL | close | BOLL_UPPER, BOLL_MID, BOLL_LOWER | -| DMI | close, high, low | DMI_PDI, DMI_MDI, DMI_ADX, DMI_ADXR | -| ATR | close, high, low | ATR | -| WR | close, high, low | WR1, WR2 | -| CCI | close, high, low | CCI | -| BIAS | close | BIAS1, BIAS2, BIAS3 | -| OBV | close, vol | OBV | -| VR | close, vol | VR | -| EMV | high, low, vol | EMV, EMV_MA | -| MFI | close, high, low, vol | MFI | -| BRAR | open, close, high, low | AR, BR | -| ASI | open, close, high, low | ASI, ASI_MA | -| TRIX | close | TRIX, TRIX_MA | -| DPO | close | DPO, DPO_MA | -| MTM | close | MTM, MTM_MA | -| ROC | close | ROC, ROC_MA | -| EXPMA | close | EXPMA_12, EXPMA_50 | -| BBI | close | BBI | -| PSY | close | PSY, PSY_MA | -| DFMA | close | DFMA_DIF, DFMA_DMA | -| CR | close, high, low | CR | -| KTN | close, high, low | KTN_UPPER, KTN_MID, KTN_LOWER | -| XSII | close, high, low | XSII_TD1, XSII_TD2, XSII_TD3, XSII_TD4 | -| MASS | high, low | MASS, MASS_MA | -| TAQ | high, low | TAQ_UP, TAQ_MID, TAQ_DOWN | -| ZHUOYAO | close | ZY_LONG, ZY_MID, ZY_SHORT, ZY_TREND | -| BIAS_SIGNAL | close | BS_X, BS_SMA, BS_LMA | -| SAR | high, low | SAR（抛物线转向/动态止损位） | -| VWAP | close, high, low, vol | VWAP（N日滚动成交量加权均价） | -| AROON | high, low | AROON_UP, AROON_DOWN, AROON_OSC | -| FK | close | FK（EMA(2) 突破斜率外推 EMA(42)） | - -#### 分时 - -```python -with MacClient.from_best_host() as c: - df = c.get_tick_chart(Market.SH, "600519") # 单日分时 - df = c.get_tick_charts(Market.SH, "600519", days=3) # 多日分时（最多5天） - df = c.get_chart_sampling(Market.SH, "600519") # 240点缩略采样 -``` - -#### 逐笔成交 - -```python -with MacClient.from_best_host() as c: - df = c.get_transactions(Market.SH, "600519", count=100) - df = c.get_transactions(Market.SH, "600519", count=100, date=20250115) -``` - -#### 板块 - -```python -from easy_tdx import BoardSortColumn, BoardType - -with MacClient.from_best_host() as c: - df = c.get_board_list(BoardType.GN) # 概念板块 - df = c.get_board_list(sort_column=BoardSortColumn.SPEED) # 按涨速排序取涨速% - df = c.get_board_members("881001", sort_type=SortType.CHANGE_PCT) - df = c.get_belong_board(Market.SZ, "000001") # 个股所属板块 - - # 板块汇总：成交额、主力净流入、涨跌家数 - summary = c.get_board_summary("881001") - # summary = { - # "member_count": 82, - # "amount": 5823456000.0, # 板块总成交额（元） - # "vol": 412356789, # 板块总成交量（股） - # "main_net_amount": -123456.0, # 当日主力净流入 - # "main_net_3d": -567890.0, # 近3日主力净流入 - # "main_net_5d": -234567.0, # 近5日主力净流入 - # "up_count": 45, - # "down_count": 37, - # "members": DataFrame(...), # 成分股明细 - # } - - # 板块涨跌幅排行榜 - df = c.get_board_ranking(BoardType.HY, top_n=10, sort_by="change_pct") - df = c.get_board_ranking(BoardType.GN, top_n=20, sort_by="main_net_amount") - # 返回列：code, name, change_pct, amount, vol, main_net_amount, up_count, down_count, member_count - - # 板块 N 日涨跌幅排行（支持指定截止日期，默认全部） - df = c.get_board_change_ranking(BoardType.HY, days=20) - df = c.get_board_change_ranking(BoardType.GN, target_date=20250530, days=10, top_n=15) - # 返回列：code, name, close_end, close_start, change_pct -``` - -#### 资金流向 - -```python -with MacClient.from_best_host() as c: - df = c.get_capital_flow(Market.SH, "600519") -``` - -返回列：`date, main_in, main_out, main_net, small_in/out/net, mid_in/out/net, large_in/out/net`。 - -#### 监控 - -```python -with MacClient.from_best_host() as c: - df = c.get_auction(Market.SH, "600519") # 集合竞价 - df = c.get_unusual(Market.SH) # 市场异动 - df = c.get_symbol_info(Market.SZ, "000001") # 个股特征快照 - df = c.get_server_info() # 服务器交易时段 -``` - -`get_unusual` 返回列含 `unusual_type`（类型码）与 `desc`（中文描述），共 19 种类型 -（主力买卖/加速拉升/急速拉升/盘中强弱/竞价异动/涨跌停/大单盘口等）。类型码→名称 -可用顶层常量映射： - -```python -from easy_tdx import UNUSUAL_TYPE_NAMES - -df["type_name"] = df["unusual_type"].map(UNUSUAL_TYPE_NAMES) -``` - -### 扩展市场 - -```python -from datetime import date - -from easy_tdx import MacExClient, ExMarket, Period - -with MacExClient.from_best_host() as c: - count = c.goods_count(ExMarket.HK_MAIN_BOARD) - df = c.goods_list(ExMarket.HK_MAIN_BOARD, start=0, count=50) - df = c.goods_kline(ExMarket.US_STOCK, "AAPL", Period.DAILY, count=10) - df = c.goods_quotes([(ExMarket.HK_MAIN_BOARD, "00700")]) - df = c.goods_tick_chart(ExMarket.HK_MAIN_BOARD, "00700") - df = c.goods_transaction(ExMarket.HK_MAIN_BOARD, "00700", count=100) - df = c.goods_transaction_all(ExMarket.HK_MAIN_BOARD, "00700", date(2026, 7, 3)) # 港股当日全部逐笔 -``` - -> **逐笔成交排序**：通达信协议为**倒序**——`start=0` 指向最新一笔（收盘方向），`count=2000` 默认只取最近 2000 笔。港股单日成交常达数万笔（如 02715 约 1.3 万笔/日），若需当日全部成交，用 `goods_transaction_all`（仅港股股票类市场，自动按 1800/页翻页取全天，安全上限 9 万条；返回协议原生倒序，需正序展示自行 `df.iloc[::-1]`）。 - -### 统一客户端 - -```python -from easy_tdx import UnifiedTdxClient, ExMarket, Market, Period - -with UnifiedTdxClient() as client: - # A 股 -- 自动路由到 MacClient - df = client.get_stock_kline(Market.SH, "600519", Period.DAILY, count=5) - df = client.get_stock_quotes([(Market.SH, "600519")]) - df = client.get_board_list() - - # 扩展市场 -- 自动路由到 MacExClient - df = client.goods_kline(ExMarket.HK_MAIN_BOARD, "00700", Period.DAILY, count=5) -``` - -### 标准协议 - -```python -from easy_tdx import TdxClient, Market, KlineCategory - -with TdxClient.from_best_host() as c: - count = c.get_security_count(Market.SH) - stocks = c.get_security_list(Market.SH, start=0) - quotes = c.get_security_quotes([(Market.SH, "600000"), (Market.SZ, "000001")]) - bars = c.get_security_bars(Market.SZ, "002176", KlineCategory.DAY, 0, 100) - minute = c.get_minute_time_data(Market.SH, "600000") - trades = c.get_transaction_data(Market.SH, "600000", 0, 20) - flow = c.get_fund_flow(Market.SH, "600519") - blocks = c.get_block_info("block_gn.dat") - xdxr = c.get_xdxr_info(Market.SH, "600519") - stat = c.get_market_stat() -``` - -> **资金流口径注意**（Issue #55）：`get_fund_flow` / `get_history_fund_flow` 按 0x0fb5 逐笔接口的"单笔成交额"分档，而该接口返回的记录是交易所真实逐笔**聚合**后的（实测 000001.SZ 单日约 17:1），分档看的也不是挂单额。结果：高价股小单档可不足成交额 1%、主力档常占 95%+，`main_net_inflow` 实质更接近"当日主动买卖总失衡"。东财/同花顺的"主力净流入"基于 L2 逐笔委托、按挂单额分档——两套口径**不可比**（实证同规则选股信号重合度仅约 14%），勿混用于同一张表或同一个因子。 - -`AsyncTdxClient` 提供对应的 `async def` 方法，接口一一对应。 - -### SecurityQuote 字段说明 - -`get_security_quotes()` 返回的 DataFrame 包含以下特殊字段： - -| 字段 | 类型 | 说明 | -|------|------|------| -| `trading_status` | int | 交易状态标志。`0x8020`(32800) = 停牌，其余值表示正常交易或集合竞价 | -| `open_amount` | float | 集合竞价成交金额（元）。仅个股有效，指数该字段无意义 | -| `server_time` | str | 服务器时间，格式 `HH:MM:SS.mmm` | -| `unknown_2` | int | 指数: 集合竞价成交金额/100；个股: 舍入残差≈0 | -| `unknown_3` | int | 个股: 集合竞价成交金额/100；指数: 负值/无意义 | -| `unknown_5-8` | int | 保留字段，恒为 0 | - -检测停牌： - -```python -df = c.get_security_quotes([(Market.SH, "600000")]) -is_suspended = df.iloc[0]["trading_status"] == 0x8020 -``` - -### 离线数据读取 - -无需网络，从本地通达信安装目录直接读取： - -```python -from easy_tdx.offline import detect_tdx_home, read_daily_bars, find_daily_bar_file -from easy_tdx import Market - -home = detect_tdx_home() -filepath = find_daily_bar_file(Market.SH, "600000") -bars = read_daily_bars(filepath) -``` - -支持：日线、分钟线、扩展市场日线、板块、股本变迁、历史财务数据。 - -### 离线数据写入同步 - -从服务端获取最新数据并追加写入本地通达信数据文件： - -```python -from easy_tdx.offline import ( - encode_daily_bar, append_daily_bars, get_last_bar_date, - encode_5min_bar, append_5min_bars, - encode_lc_min_bar, append_lc_min_bars, -) -from easy_tdx import Market -from easy_tdx.client import TdxClient - -# 追加日线到 .day 文件（自动跳过重复日期） -from easy_tdx.offline import sync_daily_bars_from_security_bars - -# 手动编码单条记录 -bar_bytes = encode_daily_bar(bar, price_coeff=0.01, vol_coeff=0.01) - -# 获取文件末尾日期 -last_date = get_last_bar_date("C:/new_jyplug/vipdoc/sh/lday/sh600000.day") -``` - -v1.5.0 起可通过 CLI 直接使用： - -```bash -easy-tdx offline daily SH 600000 --count 10 --table -easy-tdx offline ex-files --table -easy-tdx offline ex-daily 29#A1801 --table -``` - -### 缠论分析 - -基于缠论理论的技术分析模块，接收 easy_tdx 的 K 线 DataFrame，输出笔、中枢、线段、买卖点、背驰等分析结果： - -```python -from easy_tdx.chanlun import ChanlunAnalyser, ChanlunConfig - -# 使用 easy_tdx 获取 K 线数据 -with TdxClient() as client: - df = client.get_security_bars(Market.SH, "600519", KlineCategory.DAY, 0, 800) - -# 缠论分析 -analyser = ChanlunAnalyser("SH600519", "DAILY") -result = analyser.process_klines(df) - -# 获取结果 -print(f"笔数: {len(result.bis)}") -print(f"中枢数: {len(result.zss)}") -print(f"线段数: {len(result.xds)}") -print(f"买卖点: {[m.msg for m in result.mmds]}") -print(f"背驰: {[b.msg for b in result.bcs]}") - -# JSON 兼容字典输出 -print(result.to_dict()) -``` - -### 公告检索（巨潮资讯网） - -独立数据源（巨潮资讯网 cninfo），无需连接 TDX 行情服务器即可检索公司公告。 -标准库 urllib 实现，零额外依赖。 - -```python -from easy_tdx.cninfo import CninfoClient - -client = CninfoClient() - -# 检索公告（默认 30 条，最新在前） -df = client.get_announcements("688017") -# → DataFrame[title, type, date, url, code, org_id, announcement_id, announcement_time, pdf_url] - -# 翻页 + 自定义数量 -df = client.get_announcements("601088", count=10, page=2) - -# 返回示例（url 含 4 参数可直点打开，pdf_url 为 PDF 直链）： -# title type date url pdf_url -# 0 关于召开2025年年度股东大会... 股东大会 2025-06-14 .../detail?stockCode=688017&announcementId=... http://static.cninfo.com.cn/.../xxx.PDF -# 1 2024年年度报告 PDF 2025-03-28 .../detail?stockCode=688017&announcementId=... http://static.cninfo.com.cn/.../yyy.PDF -``` - -> - ``type`` 优先取 cninfo 的 ``announcementTypeName``；该字段对很多公告为 null -> （数据源限制），此时回退到 ``adjunctType``（如 "PDF"），再为空给空字符串。 -> - ``url`` 必须含 4 参数（``stockCode``/``announcementId``/``orgId``/``announcementTime``） -> 才能打开，少参数会 404。 -> - orgId 解析沿用 #19 修复：动态拉取官方映射表，查不到回退硬编码规则， -> 保证 601xxx 等非标 orgId 段也能正常查询。 - -#### 下载公告 PDF - -```python -# 下载最新一条公告的 PDF 到当前目录 -df = client.get_announcements("601088", count=5) -path = client.download_pdf(df.iloc[0]) # 接受 Announcement 或 DataFrame 的一行 -print(path) # /abs/path/20260605_1225351400.PDF - -# 批量下载 -for _, row in df.iterrows(): - try: - path = client.download_pdf(row, dest_dir="./pdfs") - except Exception as e: - print(f"跳过（无附件或失败）: {e}") -``` - -### 财报三表（新浪财经） - -独立数据源（新浪财经），无需连接 TDX 行情服务器即可获取利润表/资产负债表/现金流量表。 -标准库 urllib 实现，零额外依赖。 - -```python -from easy_tdx.sina import SinaClient - -client = SinaClient() - -# 利润表（默认 8 期，最新在前） -df = client.get_financial_report("600519", report_type="lrb") -# → DataFrame，每行一期，列 = [报告期, 营业总收入, 营业总收入_同比, ...] - -# 资产负债表 / 现金流量表（report_type 也接受中文别名：利润表/资产负债表/现金流量表） -df = client.get_financial_report("600519", report_type="fzb", num=4) -df = client.get_financial_report("600519", report_type="llb", num=4) - -# 返回示例（item_value 已转 float，可直接数值计算）： -# 报告期 营业总收入 营业总收入_同比 营业收入 营业收入_同比 -# 0 2026-03-31 54702912385.23 0.06336 53909252220.51 0.06538 -# 1 2025-12-31 174000000000.00 0.10000 NaN NaN -``` - -> - ``item_value`` 是字符串（新浪原始格式），本实现转 float；空/非数值转 None -> - 有同比的科目附加 ``{科目}_同比`` 列（float 比例，如 0.06336 = +6.3%） -> - 大类标题行（如 ``流动资产``，原 ``item_value=""``）保留为 None，反映报表结构 - -### 实时行情轮询（RealtimeDataFeed） - -> ⚠️ 通达信协议**没有服务端推送**，只有请求/响应。本模块的「实时」是 **轮询五档快照近似** -> （默认约 3 秒延迟），适合盘中信号提醒、轻量监控；**不适合高频 / 逐笔撮合**。 - -`EventBus` 自身是纯发布/订阅管道，不会产生数据。要让 `RealtimeStrategy` 跑起来， -需要配合 `RealtimeDataFeed`：它自动完成 `get_stock_quotes → MarketEvent → bus.publish`。 - -```python -import asyncio -from easy_tdx.mac.client import AsyncMacClient -from easy_tdx.realtime import ( - EventBus, - RealtimeStrategy, - MarketEvent, - RealtimeDataFeed, -) - - -class MyStrategy(RealtimeStrategy): - def on_tick(self, event: MarketEvent) -> None: - print(f"{event.market}{event.code} price={event.price} vol={event.volume}") - - -async def main(): - bus = EventBus() - strategy = MyStrategy() - bus.subscribe("SZ000001", strategy.on_tick) # 注意：key 必须带市场前缀 - - feed = RealtimeDataFeed( - bus=bus, - symbols=[(0, "000001"), (1, "600519")], # [(Market.SZ, code), ...]，单批 ≤80 只 - interval=3.0, # 轮询间隔（秒），下限 0.1 - dedup=True, # (price, volume) 未变的标的跳过发布 - # sessions=(), # 传空 tuple 表示全天轮询；默认仅 9:15-11:30 / 13:00-15:00 - ) - async with AsyncMacClient.from_best_host() as client: - await feed.run_async(client) # Ctrl+C 或 feed.stop() 退出 - - -asyncio.run(main()) -``` - -同步客户端（`MacClient`）用 `run_sync`，feed 会把阻塞调用丢到线程池，不卡事件循环： - -```python -from easy_tdx.mac.client import MacClient - -with MacClient.from_best_host() as client: - feed.run_sync(client) -``` +## Web UI 零代码使用 -> **关键坑（issue #34）**： -> - 订阅 key 必须与 `publish` 内部拼的 `f"{market}{code}"` 一致，即 `"SZ000001"` -> 而不是 `"000001"`；否则事件分发匹配不到。 -> - 传给 `subscribe` 的必须是**实例的绑定方法** `strategy.on_tick`， -> 不是未绑定的类方法 `MyStrategy.on_tick`。 -> - 整个流程跑在 `asyncio.run()` 里，否则协程不会被调度。 +`easy-tdx serve` 一条命令启动行情终端 + 回测工作台，浏览器自动打开 `http://localhost:8000`；不想装 Python 可下载 Windows 单文件 EXE 双击使用。页面操作手册见 [docs/web-ui.md](./docs/web-ui.md)。 -## 枚举参考 +## 文档导航 -### Period（K 线周期） +**快速入口**：[GitHub Wiki](https://github.com/handsomejustin/easy_tdx/wiki) · [回测系统完全上手手册](./docs/回测系统完全上手手册.html)（零基础图文，13 章）· [交互式架构图](./docs/architecture.html) -| 值 | 名称 | 说明 | +| 域 | 文档 | 说明 | |----|------|------| -| 7 | `MIN_1` | 1 分钟 | -| 0 | `MIN_5` | 5 分钟 | -| 1 | `MIN_15` | 15 分钟 | -| 2 | `MIN_30` | 30 分钟 | -| 3 | `MIN_60` | 60 分钟 | -| 4 | `DAILY` | 日线 | -| 5 | `WEEKLY` | 周线 | -| 6 | `MONTHLY` | 月线 | -| 10 | `QUARTERLY` | 季线 | -| 11 | `YEARLY` | 年线 | +| CLI | [cli.md](./docs/cli.md) | 全部命令速查表 + 按域导航 | +| CLI | [cli-market.md](./docs/cli-market.md) | 报价 / K线 / 分时 / 板块 / 资金 / 中金所 / 扩展市场 | +| CLI | [cli-finance.md](./docs/cli-finance.md) | 巨潮公告检索 / 财报三表 / 通达信 F10 | +| CLI | [cli-indicators.md](./docs/cli-indicators.md) | 34 个技术指标 / 通达信公式 / 捉妖 / 乖离率 | +| CLI | [cli-backtest.md](./docs/cli-backtest.md) | backtest / optimize / portfolio / run-all | +| CLI | [cli-screen.md](./docs/cli-screen.md) | 全市场选股扫描 / 强势股排名 | +| 教程 | [chanlun.md](./docs/chanlun.md) | 缠论分析（CLI + Python） | +| 教程 | [data-local.md](./docs/data-local.md) | 本地数据：DuckDB 仓库 / vipdoc 离线读写 | +| Web | [web-api.md](./docs/web-api.md) | REST + WebSocket + SSE 端点与示例 | +| Web | [web-ui.md](./docs/web-ui.md) | 行情终端与回测工作台操作手册 | +| Web | [packaging.md](./docs/packaging.md) | Windows EXE 打包与分发 | +| Python | [python-api.md](./docs/python-api.md) | 教程：连接 / 行情 / 指标 / 缠论 / 公告 / 财报 / 实时轮询 | +| Python | [api_reference.md](./docs/api_reference.md) | 参考：客户端方法速查 | +| Python | [field_mapping.md](./docs/field_mapping.md) | 参考：数据模型与枚举字段对照 | +| 回测 | [backtest_usage.md](./docs/backtest_usage.md) | 引擎使用手册（策略 / 配置 / 结果） | +| 回测 | [backtest-examples.md](./docs/backtest-examples.md) | 完整示例集 + 注意事项 | +| 量化 | [quantitative-guide.md](./docs/quantitative-guide.md) | 因子引擎与组合管理 | +| 量化 | [quantitative-advanced.md](./docs/quantitative-advanced.md) | 滑点 / 执行仿真 / 归因 / 完整工作流 | +| 指标 | [indicator-zhuoyao.md](./docs/indicator-zhuoyao.md) | 捉妖大师信号详解 | +| 指标 | [indicator-bias-signal.md](./docs/indicator-bias-signal.md) | 30 日乖离率信号详解 | +| 开发者 | [architecture.md](./docs/architecture.md) | 七层架构 / 源码树 / 分层要点 | +| 开发者 | [development.md](./docs/development.md) | 环境 / 测试 / CI / 发布流程 / 文档规范 | +| 协议 | [protocol-reverse-engineering.md](./docs/protocol-reverse-engineering.md) | 通达信协议逆向过程 | +| 协议 | [protocol-unknown-fields.md](./docs/protocol-unknown-fields.md) | 未知字段研究日志（活文档） | -### Adjust（复权类型） - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | `NONE` | 不复权 | -| 1 | `QFQ` | 前复权 | -| 2 | `HFQ` | 后复权 | - -### Category（市场分类） - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | `SH` | 上证 A 股 | -| 2 | `SZ` | 深证 A 股 | -| 6 | `A` | 全部 A 股 | -| 7 | `B` | B 股 | -| 8 | `KCB` | 科创板 | -| 12 | `BJ` | 北证 A 股 | -| 14 | `CYB` | 创业板 | - -### BoardType（板块类型） - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | `HY` | 行业一级 | -| 1 | `HY2` | 行业二级 | -| 3 | `GN` | 概念 | -| 4 | `FG` | 风格 | -| 5 | `DQ` | 地区 | -| 255 | `ALL` | 全部 | - -### SortType（排序字段） - -| 名称 | 说明 | -|------|------| -| `CODE` | 代码 | -| `PRICE` | 现价 | -| `CHANGE_PCT` | 涨幅% | -| `VOLUME` | 成交量 | -| `TOTAL_AMOUNT` | 成交额 | -| `TURNOVER_RATE` | 换手% | -| `MAIN_NET_AMOUNT` | 主力净额 | - -### ExMarket（扩展市场） - -| 值 | 名称 | 说明 | -|----|------|------| -| 28 | `ZZ_FUTURES` | 郑州商品 | -| 29 | `DL_FUTURES` | 大连商品 | -| 30 | `SH_FUTURES` | 上海期货 | -| 31 | `HK_MAIN_BOARD` | 香港主板 | -| 47 | `CFFEX_FUTURES` | 中金所期货 | -| 48 | `HK_GEM` | 香港创业板 | -| 74 | `US_STOCK` | 美国股票 | - -### Market（市场） - -| 值 | 名称 | 说明 | -|----|------|------| -| 0 | `SZ` | 深圳 | -| 1 | `SH` | 上海 | -| 2 | `BJ` | 北京 | - -## 完整 API 列表 - -### MacClient / AsyncMacClient - -| 方法 | 说明 | -|------|------| -| `get_stock_quotes(stocks, fields)` | 批量实时报价 | -| `get_stock_quotes_list(category, ...)` | 市场分类排序报价 | -| `get_stock_kline(market, code, period, ...)` | K 线（支持复权） | -| `get_stock_kline_with_indicators(market, code, indicators, ...)` | K 线 + 技术指标 | -| `get_tick_chart(market, code, date)` | 单日分时图 | -| `get_tick_charts(market, code, days)` | 多日分时图 | -| `get_chart_sampling(market, code)` | 分时缩略采样 | -| `get_transactions(market, code, ...)` | 逐笔成交 | -| `get_symbol_info(market, code)` | 个股特征快照 | -| `get_board_list(board_type, ..., sort_column)` | 板块列表（sort_value 列=排序键指标值） | -| `get_board_members(board_symbol, ...)` | 板块成分股报价 | -| `get_board_summary(board_symbol, ...)` | 板块汇总（成交额、主力净流入、涨跌家数） | -| `get_board_ranking(board_type, top_n, sort_by, ...)` | 板块涨跌幅排行榜（行业/概念排行） | -| `get_board_change_ranking(board_type, target_date, days, ...)` | 板块 N 日涨跌幅排行 | -| `get_belong_board(market, code)` | 个股所属板块 | -| `get_capital_flow(market, code)` | 资金流向 | -| `get_auction(market, code)` | 集合竞价 | -| `get_unusual(market, ...)` | 市场异动 | -| `get_server_info()` | 服务器交易时段 | -| `get_kline_offset(offset, count)` | K 线偏移信息 | -| `get_goods_list(market, ...)` | 扩展市场商品列表 | - -### MacExClient / AsyncMacExClient - -| 方法 | 说明 | -|------|------| -| `goods_count(market)` | 商品总数 | -| `goods_list(market, start, count)` | 商品列表 | -| `goods_quotes(stocks, fields)` | 批量报价 | -| `goods_quotes_list(market, ...)` | 市场分类报价列表 | -| `goods_kline(market, code, period, ...)` | K 线（支持复权） | -| `goods_tick_chart(market, code, ...)` | 分时图 | -| `goods_chart_sampling(market, code)` | 分时缩略采样 | -| `goods_transaction(market, code, ...)` | 逐笔成交 | - -### TdxClient / AsyncTdxClient - -| 方法 | 说明 | -|------|------| -| `get_security_count(market)` | 市场证券总数 | -| `get_security_list(market, start)` | 证券列表（分页） | -| `get_security_list_all()` | 沪深 A 股完整列表（含行业） | -| `get_security_quotes(stocks)` | 批量五档行情 | -| `get_security_bars(market, code, ...)` | 个股 K 线 | -| `get_index_bars(market, code, ...)` | 指数 K 线 | -| `get_minute_time_data(market, code)` | 今日分时 | -| `get_history_minute_time_data(market, code, date)` | 历史分时 | -| `get_transaction_data(market, code, ...)` | 当日逐笔成交 | -| `get_history_transaction_data(...)` | 历史逐笔成交 | -| `get_fund_flow(market, code)` | 当日资金流向（口径注意见上文） | -| `get_history_fund_flow(market, code, ...)` | 历史资金流向（口径注意见上文） | -| `get_xdxr_info(market, code)` | 除权除息历史 | -| `get_finance_info(market, code)` | 最新财务数据 | -| `get_company_info_category(market, code)` | 公司信息目录 | -| `get_company_info_content(...)` | 公司信息文本 | -| `get_block_info(filename)` | 板块信息 | -| `get_report_file(filename)` | 下载服务器文件 | -| `get_market_stat()` | 全市场涨跌统计 | -| `get_price_limits(market, code, name, pre_close)` | 涨跌停价 | - -## 架构 - -``` -src/easy_tdx/ -├── client.py # TdxClient / AsyncTdxClient（标准协议） -├── unified.py # UnifiedTdxClient（统一入口） -├── config.py # 服务器地址、端口、超时配置 -├── indicator.py # 技术指标计算（34 个，基于 MyTT） -├── MyTT.py # 麦语言技术指标算法库 -├── mac/ -│ ├── client.py # MacClient / AsyncMacClient（MAC 协议） -│ ├── enums.py # Period, Adjust, Category, ExMarket, SortType, ... -│ ├── models.py # MacBar, MacQuoteField, MacTick, BoardInfo, ... -│ └── commands/ # MAC 命令（build_request + parse_response，无 IO） -├── ex/ -│ ├── client.py # ExTdxClient / AsyncExTdxClient（标准协议扩展市场） -│ ├── mac_client.py # MacExClient / AsyncMacExClient（MAC 协议扩展市场） -│ └── transport/ # ExTdxConnection（端口 7727） -├── transport/ -│ ├── sync.py # TdxConnection + ping_host / ping_all -│ └── async_.py # AsyncTdxConnection（asyncio） -├── commands/ # 标准协议命令（无 IO） -├── codec/ # price / volume / datetime / frame / bitmap 编解码 -├── chanlun/ # 缠论技术分析（K线合并/分型/笔/线段/中枢/买卖点/背驰） -├── factor/ # 因子引擎（Factor ABC/19内置因子/截面计算/因子分析/预处理管道） -├── portfolio/ # 组合管理（4优化器/风险模型/再平衡引擎） -├── backtest/ # 回测引擎（Strategy基类/向量化引擎/多因子组合/滑点模型/执行仿真/归因分析） -├── screen/ # 策略选股扫描（scan信号扫描/rank回测排名/并发扫描/增量缓存） -├── realtime/ # 实时数据推送框架（EventBus/事件驱动/asyncio） -├── web/ # Web API（FastAPI REST + WebSocket） -├── models/ # 纯 dataclass，无业务逻辑 -├── offline/ # 离线数据读写模块（读取 + 写入同步） -└── cli/ # easy-tdx CLI（click） -``` - -commands 层不依赖 transport，可独立单测。 - -## 开发 - -```bash -python -m pytest tests/unit/ -v # 单元测试（无需网络） -XMTDX_LIVE=1 python -m pytest tests/integration/ -v # 集成测试 -mypy src/ # 类型检查 -ruff check src/ tests/ # lint -ruff format --check src/ tests/ # format check -``` +> 📦 历史归档（均已实施/规划完成，供追溯）：board-overview-design、hotspot-rolling-design、market-insights-roadmap、upgrade-plan-2026H2（见 docs/ 目录）与 docs/superpowers/（计划存档）。 +> +> 完整文档索引（分类目录 + 归档标注）见 [docs/index.md](./docs/index.md)。 ## 致谢 diff --git a/examples/06_finance/README.md b/examples/06_finance/README.md index 00baf9f..81aa112 100644 --- a/examples/06_finance/README.md +++ b/examples/06_finance/README.md @@ -1,6 +1,6 @@ # 06. 财务数据与 F10 公司信息 -通达信原生协议（TdxClient）提供两类财务/公司数据，独立于 [新浪三表 `f10`](../../README.md#财务)： +通达信原生协议（TdxClient）提供两类财务/公司数据，独立于 [新浪三表 `f10`](../../docs/cli-finance.md#财务)： | 命令 / 接口 | 数据 | 说明 | |-------------|------|------|