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>
103 lines
3.3 KiB
Markdown
103 lines
3.3 KiB
Markdown
## 周线行情
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----
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接口：weekly
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描述：获取A股周线行情，本接口每周最后一个交易日更新，如需要使用每天更新的周线数据，请使用[日度更新的周线行情接口](https://tushare.pro/document/2?doc_id=336)。
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限量：单次最大6000行，可使用交易日期循环提取，总量不限制
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积分：用户需要至少2000积分才可以调取，具体请参阅[积分获取办法](https://tushare.pro/document/1?doc_id=13)
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<br>
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<br>
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**输入参数**
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名称 | 类型 | 必选 | 描述
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---- | ----- | ---- | ----
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ts_code | str | N | TS代码 （ts_code,trade_date两个参数任选一）
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trade_date | str | N | 交易日期 （每周最后一个交易日期，YYYYMMDD格式）
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start_date | str | N | 开始日期
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end_date | str | N | 结束日期
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<br>
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<br>
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**输出参数**
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名称 | 类型 | 默认显示 | 描述
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--- | ---- | ---- | ----
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ts_code | str | Y | 股票代码
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trade_date | str | Y | 交易日期
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close | float | Y | 周收盘价
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open | float | Y | 周开盘价
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high | float | Y | 周最高价
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low | float | Y | 周最低价
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pre_close | float | Y | 上一周收盘价
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change | float | Y | 周涨跌额
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pct_chg | float | Y | 周涨跌 （未复权，未*100，如果是复权请用 [通用行情接口](https://tushare.pro/document/2?doc_id=109)，如需%单位请*100 ）
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vol | float | Y | 周成交量
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amount | float | Y | 周成交额
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<br>
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<br>
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**接口用法**
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```python
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pro = ts.pro_api()
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df = pro.weekly(ts_code='000001.SZ', start_date='20180101', end_date='20181101', fields='ts_code,trade_date,open,high,low,close,vol,amount')
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```
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或者
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```python
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df = pro.weekly(trade_date='20181123', fields='ts_code,trade_date,open,high,low,close,vol,amount')
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```
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<br>
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<br>
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**数据样例**
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ts_code trade_date close open high low vol \
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0 000001.SZ 20181026 11.18 10.81 11.46 10.71 9062500.14
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1 000001.SZ 20181019 10.76 10.39 10.78 9.92 7235319.55
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2 000001.SZ 20181012 10.30 10.70 10.79 9.70 7257596.97
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3 000001.SZ 20180928 11.05 10.52 11.27 10.48 5458134.13
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4 000001.SZ 20180921 10.67 9.80 10.70 9.68 5120305.29
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5 000001.SZ 20180914 9.84 10.01 10.10 9.81 3534261.76
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6 000001.SZ 20180907 10.01 10.09 10.55 9.93 4708303.81
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7 000001.SZ 20180831 10.13 10.02 10.43 9.97 6715867.92
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8 000001.SZ 20180824 10.03 8.90 10.28 8.87 6697713.52
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9 000001.SZ 20180817 8.81 9.12 9.16 8.64 3206923.44
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10 000001.SZ 20180810 9.23 8.94 9.35 8.88 3054338.56
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11 000001.SZ 20180803 8.91 9.32 9.50 8.88 3648566.35
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12 000001.SZ 20180727 9.25 9.04 9.59 9.00 5170189.41
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13 000001.SZ 20180720 9.11 8.85 9.20 8.61 3806004.47
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14 000001.SZ 20180713 8.88 8.69 9.03 8.58 4901983.84
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15 000001.SZ 20180706 8.66 9.05 9.05 8.45 5125563.53
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16 000001.SZ 20180629 9.09 9.91 9.92 8.87 5150575.93
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amount
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0 1.002282e+07
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1 7.482596e+06
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2 7.483906e+06
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3 5.904901e+06
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4 5.225262e+06
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5 3.501724e+06
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6 4.796533e+06
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7 6.858804e+06
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8 6.358840e+06
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9 2.854248e+06
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10 2.787629e+06
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11 3.363448e+06
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12 4.826484e+06
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13 3.371040e+06
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14 4.346872e+06
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15 4.446723e+06
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16 4.764107e+06
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