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jqdatasdk

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Chinese

jqdatasdk 聚宽数据获取

jqdatasdk JoinQuant Data Acquisition

任务目标

Task Objectives

  • 本 Skill 用于:通过聚宽数据接口获取A股市场数据、财务指标和因子数据
  • 能力包含:实时行情、历史K线、财务数据、指标数据、股票信息、因子数据
  • 触发条件:用户提及聚宽、jqdata、jqdatasdk或需要获取A股数据、财务信息、因子数据时
  • This Skill is used to: Obtain A-share market data, financial indicators and factor data through the JoinQuant data interface
  • Capabilities include: Real-time market quotes, historical K-lines, financial data, indicator data, stock information, factor data
  • Trigger conditions: When users mention JoinQuant, jqdata, jqdatasdk or need to obtain A-share data, financial information, factor data

前置准备

Preparations

  • 依赖说明:安装 jqdatasdk 库（已包含在 dependency 中）
  • 凭证配置:需配置聚宽账号 Token（环境变量: JQDATA_TOKEN）或登录用户名及密码（环境变量: JQDATA_USERNAME、JQDATA_PASSWORD）
  • 账号申请:访问 https://www.joinquant.com/ 注册账号并获取 API Token（详见 references/jqdatasdk_quickstart.md）
  • Dependency description: Install the jqdatasdk library (included in dependency)
  • Credential configuration: Configure JoinQuant account Token (environment variable: JQDATA_TOKEN) or login username and password (environment variables: JQDATA_USERNAME, JQDATA_PASSWORD)
  • Account application: Visit https://www.joinquant.com/ to register an account and obtain API Token (see references/jqdatasdk_quickstart.md for details)

操作步骤

Operation Steps

  • 标准流程:
    1. 确定数据需求 — 智能体理解用户意图（行情/K线/财务/因子等）
    2. 调用对应脚本 — 根据数据类型选择脚本
    3. 解析结果 — 智能体分析返回的 JSON 格式数据
  • 脚本调用映射:
    • 行情/K线/实时数据 → 
      python scripts/market_data.py --type price --code 000001.XSHE --start 2024-01-01 --end 2024-01-31
    • 财务数据/指标/估值 → 
      python scripts/financial_data.py --type fundamentals --code 000001.XSHE --statDate 2024
    • 股票列表/信息 → 
      python scripts/stock_info.py --type all_securities --security_type stock
    • 因子数据 → 
      python scripts/factor_data.py --code 000001.XSHE --factor valuation --start 2024-01-01 --end 2024-01-31
  • 可选分支:
    • 当需要多只股票数据:使用 --code 参数逗号分隔
    • 当需要指定频率:使用 --frequency 参数（1min/5min/15min/30min/60min/120min/daily/weekly/monthly）
    • 当需要调整价格类型:使用 --fq_ref_date 参数或直接指定复权类型
  • Standard process:
    1. Confirm data requirements — The agent understands the user's intent (market quotes/K-lines/financials/factors, etc.)
    2. Call the corresponding script — Select the script based on data type
    3. Parse results — The agent analyzes the returned JSON format data
  • Script call mapping:
    • Market quotes/K-lines/real-time data → 
      python scripts/market_data.py --type price --code 000001.XSHE --start 2024-01-01 --end 2024-01-31
    • Financial data/indicators/valuation → 
      python scripts/financial_data.py --type fundamentals --code 000001.XSHE --statDate 2024
    • Stock list/information → 
      python scripts/stock_info.py --type all_securities --security_type stock
    • Factor data → 
      python scripts/factor_data.py --code 000001.XSHE --factor valuation --start 2024-01-01 --end 2024-01-31
  • Optional branches:
    • When data for multiple stocks is needed: Use the --code parameter separated by commas
    • When specifying frequency is needed: Use the --frequency parameter (1min/5min/15min/30min/60min/120min/daily/weekly/monthly)
    • When adjusting price type is needed: Use the --fq_ref_date parameter or directly specify the right-adjustment type

使用示例

Usage Examples

  • 示例1:获取股票日K线数据
    • 场景/输入:用户说"查看平安银行最近一个月的K线数据"
    • 预期产出:返回日期、开盘价、最高价、最低价、收盘价、成交量等OHLCV数据
    • 关键要点:调用 
      python scripts/market_data.py --type price --code 000001.XSHE --start 2024-03-01 --end 2024-03-31 --frequency daily
  • 示例2:查询财务指标
    • 场景/输入:用户说"获取招商银行2023年的财务指标"
    • 预期产出:返回PE、PB、ROE、营业收入、净利润等财务指标
    • 关键要点:调用 
      python scripts/financial_data.py --type indicators --code 600036.XSHG --statDate 2023
  • 示例3:获取因子数据
    • 场景/输入:用户说"查询贵州茅台的估值因子"
    • 预期产出:返回市盈率、市净率、市值等估值因子数据
    • 关键要点:调用 
      python scripts/factor_data.py --code 600519.XSHG --factor valuation --start 2024-01-01 --end 2024-03-31
  • Example 1: Obtain daily K-line data of stocks
    • Scenario/Input: User says "Check the K-line data of Ping An Bank in the recent month"
    • Expected output: Return OHLCV data such as date, opening price, highest price, lowest price, closing price, trading volume, etc.
    • Key points: Call 
      python scripts/market_data.py --type price --code 000001.XSHE --start 2024-03-01 --end 2024-03-31 --frequency daily
  • Example 2: Query financial indicators
    • Scenario/Input: User says "Obtain the financial indicators of China Merchants Bank in 2023"
    • Expected output: Return financial indicators such as PE, PB, ROE, operating income, net profit, etc.
    • Key points: Call 
      python scripts/financial_data.py --type indicators --code 600036.XSHG --statDate 2023
  • Example 3: Obtain factor data
    • Scenario/Input: User says "Query the valuation factors of Kweichow Moutai"
    • Expected output: Return valuation factor data such as price-earnings ratio, price-to-book ratio, market value, etc.
    • Key points: Call 
      python scripts/factor_data.py --code 600519.XSHG --factor valuation --start 2024-01-01 --end 2024-03-31

资源索引

Resource Index

  • 脚本:
    • scripts/market_data.py (用途与参数:获取行情/K线/实时数据，支持 --type/--code/--start/--end/--frequency/--count)
    • scripts/financial_data.py (用途与参数:获取财务/指标/估值数据，支持 --type/--code/--statDate/--columns)
    • scripts/stock_info.py (用途与参数:获取股票列表/信息，支持 --type/--security_type/--code)
    • scripts/factor_data.py (用途与参数:获取因子数据，支持 --code/--factor/--start/--end)
  • 参考:
    • references/jqdatasdk_quickstart.md (何时读取:首次配置或认证失败时)
    • references/api.md (何时读取：需要使用聚宽 Python API、查看详细API参数说明时)
  • Scripts:
    • scripts/market_data.py (Purpose and parameters: Obtain market quotes/K-lines/real-time data, supports --type/--code/--start/--end/--frequency/--count)
    • scripts/financial_data.py (Purpose and parameters: Obtain financial/indicator/valuation data, supports --type/--code/--statDate/--columns)
    • scripts/stock_info.py (Purpose and parameters: Obtain stock list/information, supports --type/--security_type/--code)
    • scripts/factor_data.py (Purpose and parameters: Obtain factor data, supports --code/--factor/--start/--end)
  • References:
    • references/jqdatasdk_quickstart.md (When to read: First configuration or authentication failure)
    • references/api.md (When to read: Need to use JoinQuant Python API, view detailed API parameter descriptions)

注意事项

Notes

  • 脚本执行需配置聚宽账号 Token 或登录用户名及密码，首次使用需先完成凭证配置
  • 聚宽股票代码格式:上海市场为 XXXXXX.XSHG，深圳市场为 XXXXXX.XSHE
  • 部分数据（如财务数据）可能有延迟，建议在交易日9:30-15:00之外获取
  • 脚本返回 JSON 格式数据，智能体负责解析并转换为用户友好的展示
  • 调用频率有限制，避免短时间内大量请求（详见聚宽官方文档）
  • 首次使用建议先读取 jqdatasdk_quickstart.md 完成认证配置
  • Script execution requires configuring JoinQuant account Token or login username and password, complete credential configuration first for initial use
  • JoinQuant stock code format: Shanghai market is XXXXXX.XSHG, Shenzhen market is XXXXXX.XSHE
  • Some data (such as financial data) may have delays, it is recommended to obtain it outside of 9:30-15:00 on trading days
  • Scripts return data in JSON format, the agent is responsible for parsing and converting it into user-friendly display
  • There are limits on call frequency, avoid a large number of requests in a short time (see JoinQuant official documentation for details)
  • It is recommended to read jqdatasdk_quickstart.md first to complete authentication configuration for initial use