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>
287 lines
10 KiB
Python
287 lines
10 KiB
Python
"""
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Wind 客户端 — 直连 WindPy，自动检测登录状态，返回 pandas DataFrame。
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用法:
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from wind_client import wsd, wss, wset, wsq, edb, health
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from wind_client import wsi, wst, wsee, wses, wsed
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from wind_client import tdays, tdaysoffset, tdayscount
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from wind_client import weqs, htocode, wai, wgel
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df = wsd("000300.SH", "close,pct_chg", "-30D")
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df = wss("600519.SH,000858.SZ", "sec_name,close,pe_ttm", "tradeDate=20241231")
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df = wset("sectorconstituent", "date=20241231;windcode=000300.SH")
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df = wsq("600519.SH", "rt_last,rt_pct_chg")
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df = edb("M0001383", "2024-01-01", "2024-12-31")
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dates = tdays("20260101", "20260226")
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"""
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import os
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import re
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import sys
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import atexit
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import pandas as pd
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# ---------------------------------------------------------------------------
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# WindPy 连接管理
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# ---------------------------------------------------------------------------
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_w = None
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def _check_auto_login() -> bool:
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"""检查 Wind 是否配置了自动登录。"""
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config_path = os.path.expanduser("~/.Wind/WFT/users/Auth/user.config")
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if not os.path.exists(config_path):
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return False
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try:
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with open(config_path, "r", encoding="utf-8") as f:
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content = f.read()
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match = re.search(r'isAutoLogin="(\d+)"', content)
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return match is not None and match.group(1) == "1"
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except Exception:
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return False
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def _ensure_connected():
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"""确保 WindPy 已连接，首次调用时自动 w.start()。"""
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global _w
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if _w is not None and _w.isconnected():
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return _w
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from WindPy import w as _wind
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_w = _wind
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if _w.isconnected():
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return _w
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if not _check_auto_login():
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print("[wind_client] 警告: Wind 未开启自动登录，可能弹出登录窗口", file=sys.stderr)
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print("[wind_client] 请在 Wind 终端设置中勾选「自动登录」", file=sys.stderr)
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ret = _w.start(waitTime=30)
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if not _w.isconnected():
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raise RuntimeError(f"Wind 连接失败: {ret}")
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atexit.register(_cleanup)
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return _w
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def _cleanup():
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global _w
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if _w is not None and _w.isconnected():
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_w.stop()
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_w = None
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# ---------------------------------------------------------------------------
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# WindData → DataFrame 转换
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# ---------------------------------------------------------------------------
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def _is_synthetic_codes(codes: list) -> bool:
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"""判断 Codes 是否为 wset 返回的行号 ("1","2","3",...)。"""
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if not codes:
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return False
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return all(isinstance(c, str) and c.isdigit() for c in codes[:10])
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def _serialize_times(times) -> list:
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"""将 WindData.Times 转为字符串列表。"""
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if not times:
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return []
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return [str(t) for t in times]
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def _to_dataframe(result, endpoint: str = "") -> pd.DataFrame:
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"""将 WindData 对象转为 DataFrame。"""
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if hasattr(result, 'ErrorCode') and result.ErrorCode != 0:
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raise RuntimeError(f"Wind error {result.ErrorCode}: {result.Data}")
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data = result.Data if hasattr(result, 'Data') and result.Data else []
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fields = result.Fields if hasattr(result, 'Fields') and result.Fields else []
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codes = [str(c) for c in result.Codes] if hasattr(result, 'Codes') and result.Codes else []
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times = result.Times if hasattr(result, 'Times') and result.Times else []
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if not data:
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return pd.DataFrame()
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# wset: Codes 为行号 ("1","2",...), 不是真实代码
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if _is_synthetic_codes(codes) and fields:
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return pd.DataFrame(dict(zip(fields, data)))
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# 截面接口: 按代码索引
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_cross_section = {"wss", "wsq", "wsee", "wsed"}
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if endpoint in _cross_section and codes:
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df = pd.DataFrame(dict(zip(fields, data)), index=codes)
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df.index.name = "code"
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return df
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# 判断是否为时间序列: data[0] 长度匹配 times 长度
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row_len = len(data[0]) if data else 0
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is_time_series = times and row_len == len(times)
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if is_time_series:
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n_codes = len(codes) if codes else 0
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if n_codes > 1 and len(data) == n_codes:
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# 多代码单字段
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df = pd.DataFrame(dict(zip(codes, data)), index=pd.to_datetime(times))
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df.index.name = "date"
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return df
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# 单代码: 按字段分列
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df = pd.DataFrame(dict(zip(fields, data)), index=pd.to_datetime(times))
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df.index.name = "date"
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return df
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# 截面 fallback
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if codes and row_len == len(codes):
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df = pd.DataFrame(dict(zip(fields, data)), index=codes)
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df.index.name = "code"
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return df
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# fallback
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if fields:
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return pd.DataFrame(dict(zip(fields, data)))
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return pd.DataFrame(data)
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# ---------------------------------------------------------------------------
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# 公开 API — 对齐 WindPy 原生接口
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# ---------------------------------------------------------------------------
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def wsd(codes: str, fields: str, begin: str = "", end: str = "", options: str = "") -> pd.DataFrame:
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"""日级时间序列，等价于 w.wsd()。"""
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w = _ensure_connected()
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result = w.wsd(codes, fields, begin, end, options)
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return _to_dataframe(result, "wsd")
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def wss(codes: str, fields: str, options: str = "") -> pd.DataFrame:
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"""截面快照，等价于 w.wss()。"""
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w = _ensure_connected()
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result = w.wss(codes, fields, options)
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return _to_dataframe(result, "wss")
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def wset(table_name: str, options: str = "") -> pd.DataFrame:
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"""报表数据集，等价于 w.wset()。"""
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w = _ensure_connected()
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result = w.wset(table_name, options)
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return _to_dataframe(result, "wset")
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def wsq(codes: str, fields: str, options: str = "") -> pd.DataFrame:
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"""实时行情快照，等价于 w.wsq()。"""
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w = _ensure_connected()
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result = w.wsq(codes, fields, options)
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return _to_dataframe(result, "wsq")
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def edb(codes: str, begin: str = "", end: str = "", options: str = "") -> pd.DataFrame:
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"""宏观经济指标，等价于 w.edb()。"""
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w = _ensure_connected()
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result = w.edb(codes, begin, end, options)
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return _to_dataframe(result, "edb")
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def wsi(codes: str, fields: str, begin: str = "", end: str = "", options: str = "") -> pd.DataFrame:
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"""分钟K线序列，等价于 w.wsi()。options 常用: BarSize=1/5/15/30/60"""
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w = _ensure_connected()
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result = w.wsi(codes, fields, begin, end, options)
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return _to_dataframe(result, "wsi")
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def wst(codes: str, fields: str, begin: str = "", end: str = "", options: str = "") -> pd.DataFrame:
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"""日内Tick跳价，等价于 w.wst()。"""
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w = _ensure_connected()
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result = w.wst(codes, fields, begin, end, options)
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return _to_dataframe(result, "wst")
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def wsee(codes: str, fields: str, options: str = "") -> pd.DataFrame:
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"""板块多维数据，等价于 w.wsee()。codes 为板块/指数代码。"""
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w = _ensure_connected()
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result = w.wsee(codes, fields, options)
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return _to_dataframe(result, "wsee")
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def wses(codes: str, fields: str, begin: str = "", end: str = "", options: str = "") -> pd.DataFrame:
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"""板块时间序列，等价于 w.wses()。"""
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w = _ensure_connected()
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result = w.wses(codes, fields, begin, end, options)
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return _to_dataframe(result, "wses")
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def wsed(codes: str, fields: str, options: str = "") -> pd.DataFrame:
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"""板块查询，等价于 w.wsed()。codes 为 SectorID。"""
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w = _ensure_connected()
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result = w.wsed(codes, fields, options)
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return _to_dataframe(result, "wsed")
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def tdays(begin: str = "", end: str = "", options: str = "") -> list:
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"""交易日列表，等价于 w.tdays()。返回日期字符串列表。"""
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w = _ensure_connected()
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result = w.tdays(begin, end, options)
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if hasattr(result, 'ErrorCode') and result.ErrorCode != 0:
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raise RuntimeError(f"Wind error {result.ErrorCode}: {result.Data}")
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data = result.Data if hasattr(result, 'Data') and result.Data else []
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return _serialize_times(data[0]) if data else []
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def tdaysoffset(offset: int, begin: str = "", options: str = "") -> str:
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"""交易日偏移，等价于 w.tdaysoffset()。返回偏移后的日期字符串。"""
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if not begin:
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from datetime import date
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begin = date.today().strftime("%Y%m%d")
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w = _ensure_connected()
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result = w.tdaysoffset(offset, begin, options)
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if hasattr(result, 'ErrorCode') and result.ErrorCode != 0:
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raise RuntimeError(f"Wind error {result.ErrorCode}: {result.Data}")
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data = result.Data if hasattr(result, 'Data') and result.Data else []
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return str(data[0][0]) if data and data[0] else ""
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def tdayscount(begin: str = "", end: str = "", options: str = "") -> int:
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"""交易日计数，等价于 w.tdayscount()。返回交易日数量。"""
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w = _ensure_connected()
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result = w.tdayscount(begin, end, options)
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if hasattr(result, 'ErrorCode') and result.ErrorCode != 0:
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raise RuntimeError(f"Wind error {result.ErrorCode}: {result.Data}")
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data = result.Data if hasattr(result, 'Data') and result.Data else []
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return int(data[0][0]) if data and data[0] else 0
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def weqs(filtername: str, options: str = "") -> pd.DataFrame:
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"""条件选股，等价于 w.weqs()。"""
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w = _ensure_connected()
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result = w.weqs(filtername, options)
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return _to_dataframe(result, "weqs")
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def htocode(codes: str, sec_type: str, options: str = "") -> pd.DataFrame:
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"""代码转换（名称/简称→Wind代码），等价于 w.htocode()。"""
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w = _ensure_connected()
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result = w.htocode(codes, sec_type, options)
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return _to_dataframe(result, "htocode")
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def wai(func: str, input: str, options: str = "") -> pd.DataFrame:
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"""智能API，等价于 w.wai()。"""
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w = _ensure_connected()
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result = w.wai(func, input, options)
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return _to_dataframe(result, "wai")
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def wgel(funname: str, windid: str, options: str = "") -> pd.DataFrame:
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"""企业库，等价于 w.wgel()。"""
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w = _ensure_connected()
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result = w.wgel(funname, windid, options)
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return _to_dataframe(result, "wgel")
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def health() -> dict:
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"""检查 Wind 连接状态。"""
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try:
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w = _ensure_connected()
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return {"status": "ok", "connected": w.isconnected()}
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except Exception as e:
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return {"status": "error", "message": str(e)}
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