a65adcc2e5
Sources: extracted from two upstream archives (skill-repo, skills-main),
merged with the following policy:
- 15 broken symlinks (pointing to /Users/jameslee/.cc-switch/skills or
../../.agents/skills on a foreign machine) discarded
- 3 real name collisions with identical content (ai-pair, ifind-http-api,
zhipu-websearch) kept as one copy
- Functional overlaps deduped keeping the strongest variant:
- docx family: kept docx (official, full toolchain) + docx-cn
(GB/T 9704 Chinese official-document constants),
dropped docx_writer (no scripts, name collided with docx)
- humanizer family: kept humanizer-zh (6 zh reference docs),
dropped humanizer (en, redundant for CN workflow)
- Skills that only ran in a foreign environment removed:
ablemind-ops, app-publish, hlb-design-system, openclaw-adj-skill,
claude-driver
- alphapai excluded from this public repo because its SKILL.md hard-coded
live credentials
Result: 25 skills, 572 files, ~7.5 MB.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
158 lines
3.3 KiB
Markdown
158 lines
3.3 KiB
Markdown
# 连接器与变换操作参考
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## ConnectorFactory — 3 种数据连接器
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ConnectorFactory 通过 `type` 字段自动路由到对应的连接器。
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### csv — CSV 文件连接器
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从本地 CSV 文件加载 DataFrame。
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```json
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{"type": "csv", "path": "data/stock.csv", "encoding": "utf-8"}
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```
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- `path`: 相对于 `data_dir`（默认 `ppt-st/data/`）或绝对路径
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- `encoding`: 默认 `utf-8`
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### xlsx — Excel 文件连接器
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从 Excel 文件加载 DataFrame。
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```json
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{"type": "xlsx", "path": "data/report.xlsx", "sheet_name": "Sheet1"}
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```
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- `path`: 同 csv
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- `sheet_name`: 工作表名，默认第一个
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### tushare — Tushare 金融数据连接器
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从 Tushare Pro API 获取 A 股市场数据。
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```json
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{
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"type": "tushare",
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"api_name": "pro_bar",
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"ts_code": "600519.SH",
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"start_date": "20240101",
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"end_date": "20241231"
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}
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```
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支持的 `api_name`:
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- `index_daily`: 指数日线数据（需 `ts_code` 或 `index_code`）
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- `pro_bar`: 通用日线数据，前复权（需 `ts_code`）
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返回的 DataFrame 自动按 `trade_date` 升序排列，`trade_date` 列已转为 datetime。
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前置条件: `TUSHARE_TOKEN` 环境变量或 `.env` 文件。
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## DataFrameTransformer — 7 种变换操作
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变换在 `transforms` 中定义，每个变换指定 `from`（数据源）和 `ops`（有序操作列表）。
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### 多源合并
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`from` 支持字符串（单源）或数组（多源 concat）:
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```json
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{"from": ["stock_data", "index_data"], "ops": [...]}
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```
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多源使用 `pd.concat(axis=1)` 按列合并。
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### groupby — 分组聚合
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```json
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{"type": "groupby", "by": ["year"], "agg": {"close": "mean", "vol": "sum"}}
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```
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### pivot — 透视表
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```json
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{"type": "pivot", "index": "trade_date", "columns": "indicator", "values": "value"}
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```
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### compute — 计算新列
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```json
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{"type": "compute", "expr": "close / close.iloc[0] - 1", "output_col": "cumulative_return"}
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```
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使用 `pandas.DataFrame.eval()`，支持列名引用。
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### filter — 条件过滤
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```json
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{"type": "filter", "condition": "close > 100 and vol > 10000"}
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```
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使用 `pandas.DataFrame.query()`。
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### sort — 排序
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```json
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{"type": "sort", "sort_by": ["trade_date"], "ascending": true}
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```
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### rename — 重命名列
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```json
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{"type": "rename", "map": {"trade_date": "日期", "close": "收盘价"}}
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```
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### merge — 未实现
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会抛 `NotImplementedError`。替代方案:
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```json
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{"from": ["src1", "src2"], "ops": [...]}
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```
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用 `from` 数组实现 concat，然后用其他 ops 整理。
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## 常用组合模式
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### 合并两个 Tushare 序列
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```json
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{
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"datasources": {
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"stock": {"type": "tushare", "api_name": "pro_bar", "ts_code": "600519.SH"},
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"index": {"type": "tushare", "api_name": "pro_bar", "ts_code": "000300.SH"}
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},
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"transforms": {
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"combined": {
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"from": ["stock", "index"],
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"ops": [
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{"type": "rename", "map": {"close": "stock_close"}}
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]
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}
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}
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}
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```
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### 计算累计收益率
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```json
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{
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"ops": [
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{"type": "sort", "sort_by": ["trade_date"]},
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{"type": "compute", "expr": "close / close.iloc[0] - 1", "output_col": "累计收益率"}
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]
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}
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```
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### 过滤后重命名
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```json
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{
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"ops": [
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{"type": "filter", "condition": "trade_date >= '2024-01-01'"},
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{"type": "rename", "map": {"trade_date": "日期", "close": "收盘价"}},
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{"type": "sort", "sort_by": ["日期"]}
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]
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}
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```
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