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>
102 lines
3.5 KiB
Markdown
102 lines
3.5 KiB
Markdown
## 月线行情
|
||
----
|
||
|
||
接口:monthly
|
||
描述:获取A股月线数据
|
||
限量:单次最大4500行,总量不限制
|
||
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)
|
||
|
||
**输入参数**
|
||
|
||
名称 | 类型 | 必选 | 描述
|
||
---- | ----- | ---- | ----
|
||
ts_code | str | N | TS代码 (ts_code,trade_date两个参数任选一)
|
||
trade_date | str | N | 交易日期 (每月最后一个交易日日期,YYYYMMDD格式)
|
||
start_date | str | N | 开始日期
|
||
end_date | str | N | 结束日期
|
||
|
||
|
||
**输出参数**
|
||
|
||
名称 | 类型 | 默认显示 | 描述
|
||
--- | ---- | ---- | ----
|
||
ts_code | str | Y | 股票代码
|
||
trade_date | str | Y | 交易日期
|
||
close | float | Y | 月收盘价
|
||
open | float | Y | 月开盘价
|
||
high | float | Y | 月最高价
|
||
low | float | Y | 月最低价
|
||
pre_close | float | Y | 上月收盘价
|
||
change | float | Y | 月涨跌额
|
||
pct_chg | float | Y | 月涨跌幅 (未复权,如果是复权请用 [通用行情接口](https://tushare.pro/document/2?doc_id=109) )
|
||
vol | float | Y | 月成交量
|
||
amount | float | Y | 月成交额
|
||
|
||
|
||
**接口用法**
|
||
|
||
```python
|
||
|
||
pro = ts.pro_api()
|
||
|
||
df = pro.monthly(ts_code='000001.SZ', start_date='20180101', end_date='20181101', fields='ts_code,trade_date,open,high,low,close,vol,amount')
|
||
|
||
```
|
||
|
||
或者
|
||
|
||
```python
|
||
|
||
df = pro.monthly(trade_date='20181031', fields='ts_code,trade_date,open,high,low,close,vol,amount')
|
||
|
||
```
|
||
|
||
**数据样例**
|
||
|
||
ts_code trade_date close open high low vol \
|
||
0 000001.SZ 20181031 10.91 10.70 11.46 9.70 27801557.09
|
||
1 000001.SZ 20180930 11.05 10.09 11.27 9.68 18821004.99
|
||
2 000001.SZ 20180831 10.13 9.42 10.43 8.64 21896873.02
|
||
3 000001.SZ 20180731 9.42 9.05 9.59 8.45 20430278.02
|
||
4 000001.SZ 20180630 9.09 10.15 10.46 8.87 18179888.58
|
||
5 000001.SZ 20180531 10.18 10.97 11.23 10.02 18267177.83
|
||
6 000001.SZ 20180430 10.85 10.87 11.94 10.51 23495990.53
|
||
7 000001.SZ 20180331 10.90 11.92 12.34 10.55 23129969.15
|
||
8 000001.SZ 20180228 12.05 13.95 14.57 11.38 25624473.21
|
||
9 000001.SZ 20180131 14.05 13.35 15.13 12.86 46145376.46
|
||
10 000001.SZ 20171231 13.30 13.40 13.86 12.64 29661838.16
|
||
11 000001.SZ 20171130 13.38 11.56 15.24 11.09 42481293.87
|
||
12 000001.SZ 20171031 11.54 11.57 11.73 11.12 13951964.07
|
||
13 000001.SZ 20170930 11.11 11.28 11.94 10.82 16101838.41
|
||
14 000001.SZ 20170831 11.28 10.64 11.74 9.99 26281362.76
|
||
15 000001.SZ 20170731 10.67 9.40 11.33 9.27 35360949.04
|
||
16 000001.SZ 20170630 9.39 9.20 9.49 8.99 12718091.74
|
||
17 000001.SZ 20170531 9.20 8.96 9.23 8.54 12252646.46
|
||
18 000001.SZ 20170430 8.99 9.16 9.22 8.89 8024338.26
|
||
19 000001.SZ 20170331 9.17 9.49 9.55 9.06 12889345.37
|
||
20 000001.SZ 20170228 9.48 9.34 9.62 9.23 8460527.09
|
||
21 000001.SZ 20170131 9.33 9.11 9.34 9.07 7629258.66
|
||
|
||
amount
|
||
0 2.960878e+07
|
||
1 1.942842e+07
|
||
2 2.088672e+07
|
||
3 1.832737e+07
|
||
4 1.791251e+07
|
||
5 1.965278e+07
|
||
6 2.655691e+07
|
||
7 2.692560e+07
|
||
8 3.322504e+07
|
||
9 6.454870e+07
|
||
10 3.914290e+07
|
||
11 5.604279e+07
|
||
12 1.597217e+07
|
||
13 1.827867e+07
|
||
14 2.859479e+07
|
||
15 3.736988e+07
|
||
16 1.171552e+07
|
||
17 1.083921e+07
|
||
18 7.268941e+06
|
||
19 1.197751e+07
|
||
20 7.977982e+06
|
||
21 7.001209e+06 |