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>
566 lines
17 KiB
Markdown
566 lines
17 KiB
Markdown
---
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name: windpy-sdk
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description: WindPy SDK 本地调用参考手册。当用户需要编写使用 Wind 金融终端 Python API (from WindPy import w) 的代码时使用此技能。覆盖全部数据函数的签名、参数、返回值和示例。
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---
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# WindPy SDK 本地调用参考手册
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本技能提供 Wind 金融终端 Python API (`from WindPy import w`) 的完整函数参考，用于编写直接调用 WindPy SDK 的 Python 代码。
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## 触发条件
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当用户需要：
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- 编写使用 `from WindPy import w` 的 Python 代码
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- 查询 Wind API 某个函数的用法、参数或字段
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- 获取 A 股/债券/基金/期货/宏观数据的 Wind 代码
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- 调试 WindPy SDK 调用错误
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## 连接管理
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```python
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from WindPy import w
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w.start() # 启动连接，默认超时120秒
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w.start(waitTime=60) # 自定义超时60秒
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w.isconnected() # 返回 True/False
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w.stop() # 停止连接（程序退出自动调用，一般不需要）
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```
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**注意事项：**
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- `w.start()` 不会重复启动，需改参数时先 `w.stop()` 再 `w.start()`
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- Mac 版 SDK 部分财务报表字段不可用（错误码 -40520017、-40522006）
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---
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## 核心数据函数
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### 1. w.wsd() — 日级时间序列
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获取单品种多指标 或 多品种单指标 的日级时间序列数据。
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```python
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w.wsd(codes, fields, beginTime, endTime, options, usedf=True)
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```
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| 参数 | 类型 | 必选 | 说明 |
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|------|------|------|------|
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| codes | str/list | 是 | 证券代码。多品种时 fields 只能单个 |
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| fields | str/list | 是 | 指标。如 `"close,high,low,open"` |
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| beginTime | str/datetime | 否 | 起始日期。支持 `"2024-01-01"`, `"20240101"`, `"-30D"`, `"IPO"` |
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| endTime | str/datetime | 否 | 截止日期。默认当前日期 |
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| options | str | 否 | 参数字符串，见下方 |
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**常用 options：**
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- `PriceAdj=F` 前复权 / `B` 后复权 / 不填=不复权
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- `Period=D` 日 / `W` 周 / `M` 月 / `Q` 季 / `Y` 年
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- `Days=Trading` 交易日(默认) / `Weekdays` 工作日 / `Alldays` 日历日
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- `Fill=Previous` 沿用前值 / `Blank` 返回空值
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- `TradingCalendar=SSE` 上交所(默认) / `SZSE` / `HKEX` / `NYSE` 等
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**返回值：** `(ErrorCode, DataFrame)` 当 `usedf=True`
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```python
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# 单品种多指标
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err, df = w.wsd("600519.SH", "open,high,low,close,volume,amt,pct_chg",
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"2024-01-01", "2024-06-30", "PriceAdj=F", usedf=True)
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# 多品种单指标
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err, df = w.wsd("600519.SH,000858.SZ,000001.SZ", "close",
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"-30D", "", "PriceAdj=F", usedf=True)
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# 月线数据
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err, df = w.wsd("600519.SH", "close,volume", "-2Y", "", "Period=M", usedf=True)
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# 资金流向
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err, df = w.wsd("600519.SH",
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"mfd_inflow_xl,mfd_inflow_l,mfd_inflow_m,mfd_inflow_s,mfd_inflow",
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"-30D", "", "", usedf=True)
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# 债券数据
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err, df = w.wsd("010107.SH", "ytm_b,duration,convexity,close",
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"2024-01-01", "2024-06-30", "PriceAdj=CP", usedf=True)
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```
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**常用 fields（行情）：** `open, high, low, close, pre_close, volume, amt, pct_chg, turn, vwap, mkt_cap_ard, pe_ttm, pb_lf`
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**常用 fields（资金流向）：** `mfd_inflow_xl`(超大单), `mfd_inflow_l`(大单), `mfd_inflow_m`(中单), `mfd_inflow_s`(小单), `mfd_inflow`(主力净流入)
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---
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### 2. w.wss() — 截面快照
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获取多品种多指标的**某一时点**截面数据。
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```python
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w.wss(codes, fields, options, usedf=True)
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```
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| 参数 | 类型 | 必选 | 说明 |
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|------|------|------|------|
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| codes | str/list | 是 | 证券代码，支持多品种 |
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| fields | str/list | 是 | 指标，支持多指标 |
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| options | str | 否 | 如 `tradeDate`, `rptDate`, `rptType` 等 |
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**常用 options：**
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- `tradeDate=20240101` 指定交易日
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- `rptDate=20231231` 指定报告期
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- `rptType=408001000` 合并报表(默认) / `408004000` 合并报表(调整) / `408005000` 合并报表(更正前)
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- `year=2024` 指定年份（业绩预告用）
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- `currencyType=CNY` 币种
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```python
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# 行情快照（多品种多指标）
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err, df = w.wss("600519.SH,000858.SZ",
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"sec_name,close,pct_chg,pe_ttm,pb_lf,mkt_cap_ard",
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f"tradeDate=20240628", usedf=True)
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# 基本信息
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err, df = w.wss("600519.SH",
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"sec_name,sec_englishname,industry_sw,industry_sw_level2,"
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"listdate,province,chairman,mkt_cap_ard,total_shares,float_a_shares",
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"", usedf=True)
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# 核心财务指标
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err, df = w.wss("600519.SH",
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"roe_ttm,roa_ttm,grossprofit_margin,netprofit_margin,"
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"eps_ttm,pe_ttm,pb_lf,ps_ttm,current_ratio,debttoassets,"
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"yoynetprofit,yoyrevenue",
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f"tradeDate=20240628", usedf=True)
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# 利润表
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err, df = w.wss("600519.SH",
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"tot_oper_rev,oper_rev,tot_oper_cost,oper_cost,"
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"oper_profit,tot_profit,net_profit_is,eps_basic,eps_diluted",
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"rptDate=20231231;rptType=408001000", usedf=True)
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# 资产负债表
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err, df = w.wss("600519.SH",
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"tot_assets,tot_cur_assets,cash_equivalents,inventories,"
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"tot_non_cur_assets,fix_assets,tot_liab,tot_cur_liab,"
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"st_borrow,lt_borrow,tot_equity,undist_profit",
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"rptDate=20231231;rptType=408001000", usedf=True)
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# 现金流量表
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err, df = w.wss("600519.SH",
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"net_cash_flows_oper_act,net_cash_flows_inv_act,"
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"net_cash_flows_fnc_act,free_cash_flow",
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"rptDate=20231231;rptType=408001000", usedf=True)
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# 业绩预告
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err, df = w.wss("600519.SH",
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"profitnotice_date,profitnotice_style,"
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"profitnotice_netprofitmin,profitnotice_netprofitmax,"
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"profitnotice_changemin,profitnotice_changemax,profitnotice_reason",
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f"year=2024", usedf=True)
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# 业绩快报
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err, df = w.wss("600519.SH",
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"expr_discdate,expr_oper_rev,expr_oper_profit,expr_tot_profit,"
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"expr_net_profit_parent_comp,expr_eps_basic,expr_roe_diluted,"
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"expr_yoy_oper_rev,expr_yoy_net_profit",
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"rptDate=20231231", usedf=True)
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# 区间涨跌幅
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err, df = w.wss("600519.SH,000858.SZ", "sec_name,pct_chg_per",
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"startDate=20240101;endDate=20240628", usedf=True)
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```
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**常用 fields 速查见** `references/field-catalog.md`
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---
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### 3. w.wsq() — 实时行情
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获取当天实时行情快照，或订阅实时数据推送。
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```python
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# 快照模式
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w.wsq(codes, fields, usedf=True)
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# 订阅模式
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w.wsq(codes, fields, func=callback_function)
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w.cancelRequest(requestID) # 取消订阅, 0=取消全部
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```
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```python
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# 快照
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err, df = w.wsq("600519.SH,000858.SZ",
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"rt_last,rt_open,rt_high,rt_low,rt_pct_chg,rt_vol,rt_amt,rt_chg",
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usedf=True)
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# 订阅模式
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def on_quote(indata):
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print(f"Code: {indata.Codes}, Fields: {indata.Fields}, Data: {indata.Data}")
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data = w.wsq("600519.SH", "rt_last,rt_vol", func=on_quote)
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# ... 等待回调 ...
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w.cancelRequest(data.RequestID) # 取消订阅
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```
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**实时行情 fields（rt_ 前缀）：** `rt_last`(最新价), `rt_open`, `rt_high`, `rt_low`, `rt_pre_close`, `rt_pct_chg`, `rt_chg`, `rt_vol`(成交量), `rt_amt`(成交额), `rt_last_vol`(最新成交量)
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---
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### 4. w.wsi() — 分钟级 K 线
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获取 1-60 分钟级别的 OHLCV 数据。支持国内六大交易所近三年数据。
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```python
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w.wsi(codes, fields, beginTime, endTime, options, usedf=True)
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```
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| 参数 | 类型 | 必选 | 说明 |
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|------|------|------|------|
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| codes | str/list | 是 | 证券代码（带后缀） |
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| fields | str/list | 是 | 如 `"open,high,low,close,volume"` |
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| beginTime | str/datetime | 否 | 如 `"2024-06-28 09:30:00"` |
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| endTime | str/datetime | 否 | 默认当前时间 |
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**options：**
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- `BarSize=5` 分钟数（1-60，默认1）
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- `PriceAdj=F` 前复权 / `B` 后复权 / `U` 不复权(默认)
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- `Fill=Previous` 沿用前值
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**限制：** 单品种近三年；多品种时 品种数×天数 ≤ 100
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```python
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# 5分钟K线
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err, df = w.wsi("600519.SH", "open,high,low,close,volume,amt",
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"2024-06-28 09:30:00", "2024-06-28 15:00:00", "BarSize=5", usedf=True)
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# 15分钟K线（最近3天）
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err, df = w.wsi("600519.SH", "open,high,low,close,volume",
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"-3D 09:30:00", "", "BarSize=15", usedf=True)
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# 期货分钟数据
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err, df = w.wsi("IF00.CFE", "open,high,low,close",
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"2024-06-28 09:30:00", "2024-06-28 15:00:00", "BarSize=1", usedf=True)
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```
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---
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### 5. w.wst() — Tick 逐笔数据
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获取日内盘口买卖五档快照和分时成交数据。仅支持单品种，近七个交易日。
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```python
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w.wst(codes, fields, beginTime, endTime, options, usedf=True)
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```
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```python
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# 逐笔成交
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err, df = w.wst("600519.SH", "last,volume,amt,bid1,bsize1,ask1,asize1",
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"2024-06-28 09:30:00", "2024-06-28 11:30:00", "", usedf=True)
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```
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**Tick fields：** `last`(最新价), `volume`, `amt`, `bid1~bid5`(买1~5价), `bsize1~bsize5`(买1~5量), `ask1~ask5`(卖1~5价), `asize1~asize5`(卖1~5量)
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---
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### 6. w.wses() — 板块日级时间序列
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获取板块级别的历史日序列数据（如板块平均收盘价、PE等）。
|
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```python
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w.wses(codes, fields, beginTime, endTime, options, usedf=True)
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```
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**注意：** 一次仅支持单指标，可多板块。
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```python
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# 上证A股和深证A股的平均收盘价
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err, df = w.wses("a001010200000000,a001010300000000", "sec_close_avg",
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"2024-01-01", "2024-06-30", "", usedf=True)
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```
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**options：**
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- `DynamicTime=0` 使用板块历史成分 / `1` 使用最新成分(默认)
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- `Period=D` 日(默认) / `W` 周 / `M` 月
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---
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### 7. w.wsee() — 板块截面快照
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获取多板块多指标的某一天截面数据。
|
||
|
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```python
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w.wsee(codes, fields, options, usedf=True)
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```
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```python
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# 多板块截面对比
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err, df = w.wsee("a001010200000000,a001010300000000",
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"sec_close_avg,sec_pct_chg_avg,sec_pe_ttm_median",
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"tradeDate=20240628", usedf=True)
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```
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|
||
---
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### 8. w.wset() — 报表数据集
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获取板块成分、指数成分、龙虎榜、分红送转、停复牌等报表数据。
|
||
|
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```python
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w.wset(tableName, options, usedf=True)
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```
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| tableName | 用途 | options 示例 |
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|-----------|------|-------------|
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| `sectorconstituent` | 板块成分股 | `date=2024-06-28;sectorid=a001010100000000` |
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| `indexconstituent` | 指数成分股 | `date=2024-06-28;windcode=000300.SH` |
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| `abnormalactivitiesranking` | 龙虎榜 | `startdate=2024-06-28;enddate=2024-06-28;field=...` |
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||
| `dividendproposal` | 分红方案 | `year=2024` |
|
||
| `tradingsuspend` | 停牌股票 | `startdate=2024-06-28;enddate=2024-06-28` |
|
||
| `marginassetsandliabilities` | 融资融券标的 | `date=2024-06-28;sectorid=...` |
|
||
| `etfconstituent` | ETF 申赎清单 | `date=2024-06-28;windcode=510300.SH` |
|
||
|
||
```python
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# 全部A股成分股
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err, df = w.wset("sectorconstituent",
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"date=2024-06-28;sectorid=a001010100000000", usedf=True)
|
||
# 返回列: date, wind_code, sec_name
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||
|
||
# 沪深300成分股
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||
err, df = w.wset("indexconstituent",
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||
"date=2024-06-28;windcode=000300.SH", usedf=True)
|
||
|
||
# 申万一级行业成分股
|
||
err, df = w.wset("sectorconstituent",
|
||
"date=2024-06-28;sectorid=a39901011g000000", usedf=True)
|
||
|
||
# 龙虎榜
|
||
err, df = w.wset("abnormalactivitiesranking",
|
||
"startdate=2024-06-28;enddate=2024-06-28;"
|
||
"field=trade_dt,wind_code,sec_name,close,pct_chg,netbuyamt",
|
||
usedf=True)
|
||
```
|
||
|
||
**常用板块 sectorid：**
|
||
| 板块 | sectorid |
|
||
|------|----------|
|
||
| 全部A股 | `a001010100000000` |
|
||
| 上证A股 | `a001010200000000` |
|
||
| 深证A股 | `a001010300000000` |
|
||
| 创业板 | `1000006528000000` |
|
||
| 科创板 | `a001010l00000000` |
|
||
| 全部年金养老金 | `1000019226000000` |
|
||
| 混合养老金 | `1000023520000000` |
|
||
| 股票养老金 | `1000023515000000` |
|
||
| Wind股票型养老金 | `1000027483000000` |
|
||
|
||
---
|
||
|
||
### 9. w.edb() — 宏观经济数据库
|
||
|
||
获取 Wind EDB 宏观经济数据库中的指标数据。
|
||
|
||
```python
|
||
w.edb(codes, beginTime, endTime, options, usedf=True)
|
||
```
|
||
|
||
```python
|
||
# GDP
|
||
err, df = w.edb("M5567876,M5567889", "2022-01-01", "2024-06-30",
|
||
"Fill=Previous", usedf=True)
|
||
|
||
# CPI
|
||
err, df = w.edb("M0000612,M0000705,M0085932,M0085934", "2023-01-01", "",
|
||
"Fill=Previous", usedf=True)
|
||
|
||
# PMI
|
||
err, df = w.edb("M0017126,M0017127,M5206730", "2023-01-01", "",
|
||
"Fill=Previous", usedf=True)
|
||
|
||
# M2
|
||
err, df = w.edb("M0001384,M0001385,M0001391", "2023-01-01", "",
|
||
"Fill=Previous", usedf=True)
|
||
|
||
# 利率
|
||
err, df = w.edb("M0329537,M0329538,M0017139", "2023-01-01", "",
|
||
"Fill=Previous", usedf=True)
|
||
```
|
||
|
||
**完整 EDB 指标代码见** `references/edb-indicators.md`
|
||
|
||
---
|
||
|
||
### 10. 交易日历函数
|
||
|
||
```python
|
||
# w.tdays() — 获取日期区间内的交易日序列
|
||
data = w.tdays("2024-01-01", "2024-06-30", "")
|
||
dates = data.Data[0] # [datetime, datetime, ...]
|
||
|
||
# w.tdaysoffset() — 获取偏移后的交易日
|
||
data = w.tdaysoffset(0) # 最近交易日
|
||
data = w.tdaysoffset(-10) # 前推10个交易日
|
||
data = w.tdaysoffset(-3, "2024-06-28", "Period=M") # 前推3个月
|
||
date = data.Data[0][0] # datetime 对象
|
||
|
||
# w.tdayscount() — 统计区间内交易日数量
|
||
data = w.tdayscount("2024-01-01", "2024-12-31", "")
|
||
count = data.Data[0][0] # int
|
||
```
|
||
|
||
**options：**
|
||
- `Days=Trading` 交易日(默认) / `Weekdays` 工作日 / `Alldays` 日历日
|
||
- `Period=D` 天(默认) / `W` 周 / `M` 月 / `Q` 季 / `Y` 年
|
||
- `TradingCalendar=SSE` 上交所(默认) / 其他交易所代码
|
||
|
||
---
|
||
|
||
## 日期宏
|
||
|
||
WindPy 支持相对日期表达式：
|
||
|
||
| 格式 | 含义 | 示例 |
|
||
|------|------|------|
|
||
| `-5D` | 前推5个日历日 | beginTime="-5D" |
|
||
| `-10TD` | 前推10个交易日 | beginTime="-10TD" |
|
||
| `-1M` | 前推1个月 | beginTime="-1M" |
|
||
| `-2Y` | 前推2年 | beginTime="-2Y" |
|
||
| `IPO` | 上市首日 | beginTime="IPO" |
|
||
| `LYR` | 去年年报 | rptDate 参数 |
|
||
| `MRQ` | 最新一期 | rptDate 参数 |
|
||
| `RYF` | 本年初 | beginTime="RYF" |
|
||
| `LME` | 上月末 | endTime="LME" |
|
||
| `ED` | 截止日期 | 用于计算 `ED-10D` |
|
||
|
||
---
|
||
|
||
## 返回值处理
|
||
|
||
### 使用 usedf=True（推荐）
|
||
|
||
```python
|
||
err, df = w.wsd("600519.SH", "close", "-10D", "", "", usedf=True)
|
||
if err == 0:
|
||
print(df) # pandas DataFrame
|
||
print(df.columns) # ['CLOSE']
|
||
else:
|
||
print(f"错误: {err}")
|
||
```
|
||
|
||
### 不使用 usedf（返回 WindData 对象）
|
||
|
||
```python
|
||
data = w.wsd("600519.SH", "close", "-10D", "")
|
||
if data.ErrorCode == 0:
|
||
print(data.Codes) # ['600519.SH']
|
||
print(data.Fields) # ['CLOSE']
|
||
print(data.Times) # [datetime, ...]
|
||
print(data.Data) # [[1800.0, 1810.5, ...]]
|
||
```
|
||
|
||
### 错误码说明
|
||
|
||
| 错误码 | 含义 |
|
||
|--------|------|
|
||
| 0 | 成功 |
|
||
| -40520007 | 无数据权限 |
|
||
| -40520017 | 字段不支持（Mac常见） |
|
||
| -40522006 | 参数错误 |
|
||
| -40521001 | 网络连接失败 |
|
||
|
||
---
|
||
|
||
## 常用代码模板
|
||
|
||
### 获取最近交易日
|
||
|
||
```python
|
||
from datetime import datetime
|
||
|
||
def get_latest_trade_date():
|
||
data = w.tdaysoffset(0, datetime.now().strftime('%Y-%m-%d'), "")
|
||
if data.ErrorCode == 0:
|
||
return data.Data[0][0].strftime('%Y-%m-%d')
|
||
return datetime.now().strftime('%Y-%m-%d')
|
||
|
||
def get_trade_date_offset(n):
|
||
"""前推 n 个交易日"""
|
||
data = w.tdaysoffset(-n, datetime.now().strftime('%Y-%m-%d'), "")
|
||
if data.ErrorCode == 0:
|
||
return data.Data[0][0].strftime('%Y-%m-%d')
|
||
return datetime.now().strftime('%Y-%m-%d')
|
||
```
|
||
|
||
### 批量获取板块所有股票数据
|
||
|
||
```python
|
||
trade_date = get_latest_trade_date()
|
||
|
||
# 获取成分股
|
||
data = w.wset("sectorconstituent", f"date={trade_date};sectorid=a001010100000000")
|
||
stocks = data.Data[1] # wind_code 列表
|
||
|
||
# 获取数据
|
||
err, df = w.wss(stocks,
|
||
"sec_name,industry_sw,close,pct_chg,pe_ttm,pb_lf,mkt_cap_ard",
|
||
f"tradeDate={trade_date.replace('-','')}", usedf=True)
|
||
```
|
||
|
||
### 多期财务数据对比
|
||
|
||
```python
|
||
results = {}
|
||
for year in range(2019, 2024):
|
||
err, df = w.wss("600519.SH",
|
||
"tot_oper_rev,net_profit_is,roe_diluted,eps_basic",
|
||
f"rptDate={year}1231;rptType=408001000", usedf=True)
|
||
if err == 0:
|
||
results[year] = df.iloc[0].to_dict()
|
||
|
||
import pandas as pd
|
||
summary = pd.DataFrame(results).T
|
||
```
|
||
|
||
### 养老金基金数据批量获取
|
||
|
||
```python
|
||
# 获取混合养老金板块成分基金（代码格式 xxBxxx.OF）
|
||
err, df_sector = w.wset("sectorconstituent",
|
||
"date=20260307;sectorId=1000023520000000;", usedf=True)
|
||
fund_codes = df_sector['wind_code'].tolist()
|
||
code_to_name = dict(zip(df_sector['wind_code'], df_sector['sec_name']))
|
||
|
||
# 获取净值（多品种单指标）
|
||
err, df_nav = w.wsd(fund_codes, "nav",
|
||
"2020-01-01", "2026-03-07", "unit=1;", usedf=True)
|
||
|
||
# 获取基金资产净值（注意：用 netasset_total，不要用 vnetasset_total）
|
||
err, df_na = w.wsd(fund_codes, "netasset_total",
|
||
"2020-01-01", "2026-03-07", "unit=1;", usedf=True)
|
||
|
||
# 列名加上基金名称，便于识别
|
||
df_nav.columns = [f"{c}|{code_to_name.get(c, '')}" for c in df_nav.columns]
|
||
```
|
||
|
||
### 相关性分析
|
||
|
||
```python
|
||
import numpy as np
|
||
|
||
err, df = w.wsd("600519.SH,000858.SZ,000001.SZ", "close",
|
||
"-250TD", "", "PriceAdj=F", usedf=True)
|
||
|
||
if err == 0:
|
||
returns = df.pct_change().dropna()
|
||
corr = returns.corr()
|
||
print(corr)
|
||
```
|
||
|
||
---
|
||
|
||
## 注意事项
|
||
|
||
1. **usedf=True** 返回 `(ErrorCode, DataFrame)`；不加返回 `WindData` 对象
|
||
2. **日期格式** 均可用 `"2024-01-01"`, `"20240101"`, `"-5D"`, datetime 对象
|
||
3. **wsd 多品种** 时 fields 只能选一个
|
||
4. **wss 一次** 只能取一个交易日/报告期，但可多品种多指标
|
||
5. **wsi** 多品种时：品种数 × 天数 ≤ 100
|
||
6. **wst** 仅支持单品种，近 7 个交易日
|
||
7. **DataFrame 列名** 自动大写：`close` → `CLOSE`, `pe_ttm` → `PE_TTM`
|
||
8. **股票代码格式**：`600519.SH`(沪), `000001.SZ`(深), `300750.SZ`(创), `688xxx.SH`(科创), `8xxxxx.BJ`(北交所), `xxBxxx.OF`(养老金基金)
|
||
9. **基金字段**：`vnetasset_total` 不可用（错误码 -40522007），应使用 `netasset_total` 获取基金资产净值
|