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A股量化数据分析工具，基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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使用东方财富 API 获取 A 股（沪市/深市）及指数的日内分时数据。当用户询问某只 A 股或指数的日内走势、分时数据、当日行情、实时价格、分时图数据时，必须使用此 skill。触发关键词包括：分时数据、日内数据、今日行情、分时走势、intraday、当日走势、东方财富获取数据。支持沪市（market=1）和深市（market=0）。
| name | akshare-stock |
| license | MIT |
| description | A股量化数据分析工具，基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。 |
| source | https://github.com/1yihui/YiHui |
| compatibility | any-agent |
安装依赖：
pip install akshare
import akshare as ak
# 个股实时行情
stock_zh_a_spot_em()
stock_zh_a_spot_em(symbol="北证A股")
import akshare as ak
# 日K线
stock_zh_a_hist(symbol="000001", period="daily", start_date="20240101", end_date="20241231", adjust="qfq")
# 周K线
stock_zh_a_hist(symbol="000001", period="weekly", start_date="20240101", end_date="20241231", adjust="qfq")
# 月K线
stock_zh_a_hist(symbol="000001", period="monthly", start_date="20240101", end_date="20241231", adjust="qfq")
import akshare as ak
# 财务报表
stock_financial_abstract_ths(symbol="000001", indicator="按报告期")
# 主要财务指标
stock_financial_analysis_indicator(symbol="000001")
import akshare as ak
# 行业板块行情
stock_board_industry_name_em()
# 概念板块行情
stock_board_concept_name_em()
# 板块内个股
stock_board_industry_cons_em(symbol="半导体")
import akshare as ak
# 个股资金流向
stock_individual_fund_flow(stock="000001", market="sh")
# 大单净流入
stock_individual_fund_flow(stock="000001", market="sh", symbol="大单净流入")
import akshare as ak
# 每日龙虎榜
stock_lhb_detail_em(date="20240930")
# 机构调研
stock_zlzj_em()
import akshare as ak
# 新股申购
stock_new_ipo_em()
# 待上市新股
stock_new_ipo_start_em()
import akshare as ak
# 融资融券
stock_margin_sse(symbol="600000")
# 融资融券明细
stock_rzrq_detail_em(symbol="600000", date="20240930")
如果 AkShare 安装失败，可使用 baostock（更轻量）:
import baostock as bs
# 登录
lg = bs.login()
print(lg.error_msg)
# 获取历史K线
rs = bs.query_history_k_data_plus('sh.600519',
'date,code,open,high,low,close,volume',
start_date='20250101',
end_date='20251231')
data_list = []
while rs.next:
data_list.append(rs.get_row_data())
bs.logout()