# 导入函数库 from jqdata import * def initialize(context): g.security = ['300530.XSHE','688590.XSHG'] run_daily(period, time='every_bar') g.filed=['open','close','low','high'] g.stocks = get_index_stocks('000001.XSHG') def period(context): # 计算某一只股票5日最高价的均价 w = attribute_history(security=g.security[1],count=5,fields=g.filed[3]) avg_high = w['high'].mean() print(avg_high) #查询上证指数市值前10股票 q = query(valuation.code, valuation.market_cap).filter(valuation.code.in_(g.stocks)).order_by(valuation.market_cap.desc()).limit(20) df = get_fundamentals(q) for index,row in df.iterrows(): stock_code = row['code'] security_info = get_security_info(stock_code) stock_name = security_info.display_name market_cap = row['market_cap'] print("股票名称:%s,市值:%s" % (stock_name,market_cap))

交作业： #query_object = query(valuation.code,balance.retained_profit).filter((valuation.capitalization>=1000)&(valuation.pe_ratio< 10)).order_by(valuation.market_cap.desc()).limit(10) #dataframe = get_fundamentals(query_object, date='2016-01-01') #print(dataframe) from jqdata import * import tushare as ts import csv import pandas as pd import numpy as np import time security_target = '600066.XSHG' def initialize(context): # 在初始化函数中，context 作为参数传入 time = context.current_dt print(f"当前时间: {time}") aver_high = 0 s = attribute_history(security_target, 5, '1d', 'high', skip_paused=True, df=True, fq='pre').iloc[:,0] for i in s: print(i) aver_high+=i print(f'{security_target}的前 5 个交易日的最高价格平均是{aver_high/5:02f}')

Python API 编程测试 from jqdatasdk import * auth('1xxxxxxxxx91','xxxxxxxxx') #固定时间的最近5日平均最高价 data_1=get_price(security='000001.XSHE',count=5,end_date='2024-08-11', fields=['high']) print(data_1) print(f"000001.XSHE'2024-08-11'最近5日的平均最高价是:{data_1['high'].values.mean()}") q=query(valuation.code,valuation.circulating_market_cap)\ .filter(valuation.code.in_(get_index_stocks('000001.XSHG',date='2024-08-12')))\ .order_by(valuation.circulating_market_cap.desc()).limit(5) w=get_fundamentals(q,date='2024-08-12') print(w)

from jqdata import * def initialize(context): run_daily(period, time='every_bar') g.security = '000001.XSHG' # 上证指数代码 def period(context): # 获取当前指数的所有成分股代码 index_stocks = get_index_stocks(g.security) # 查询成分股市值前5大的股票 q = query(valuation.code, valuation.market_cap) # 构建查询对象 q = q.filter(valuation.code.in_(index_stocks)) # 使用 .in_() 过滤成分股 q = q.order_by(valuation.market_cap.desc()) # 按流通市值降序排列 q = q.limit(5) # 取前5名 result = get_fundamentals(q) # ✅ 正确调用方式 # 输出结果（调试用途） print(result)

def getStock(context): # 获取上证指数市值最大的股票之一。 index_stocks=get_index_stocks('000016.XSHG') # 构建查询条件 q=query(valuation.code)\ .filter(valuation.code.in_(index_stocks))\ .order_by(valuation.market_cap.desc())\ .limit(5) result = get_fundamentals(q) # ✅ 正确调用方式 stock_codes = result['code'].tolist() # 提取股票代码列、转换为列表 print("市值最大的5只股票%s"%stock_codes) return stock_codes # 市值最大的5只股票['601398.XSHG', '601939.XSHG', '601857.XSHG', '601288.XSHG', '601988.XSHG']

q=query(valuation.code).filter(valuation.market_cap).order_by(valuation.market_cap.desc()).limit(5) a=get_fundamentals(q) a.loc[:,'code'].tolist()

#获取任一股票最近5个交易日最高价的平均价 p=history(count=5, unit='1d', field='high', \ security_list='000001.XSHE', df=True, skip_paused=False, fq=None) print(p.mean()) #生成一个list，list中为上证指数成分股中流通市值最大的5个股票的股票代码 stocks=get_index_stocks('000001.XSHG') df=get_fundamentals(query(valuation.code,valuation.market_cap)\ .filter(valuation.code.in_(stocks))\ .order_by(valuation.circulating_market_cap.desc())\ .limit(10),date='2018-03-12') print(df)

""" 获取上证指数（000001.XSHG）市值最高的5只股票 """ import jqdatasdk from jqdatasdk import * from dotenv import load_dotenv import os load_dotenv() # 从环境变量读取聚宽账号和密码 USERNAME = os.getenv('JQ_USERNAME') PASSWORD = os.getenv('JQ_PASSWORD') if not USERNAME or not PASSWORD: raise ValueError("请先设置环境变量 JQ_USERNAME 和 JQ_PASSWORD") # 登录聚宽 jqdatasdk.auth(USERNAME, PASSWORD) # 1. 获取上证指数成分股列表 stock_list = jqdatasdk.get_index_stocks('000001.XSHG',date='2025-02-01') # 2. 查询这些股票的总市值，并按市值降序排列，取前5名 q = query(valuation.code,valuation.market_cap).filter(valuation.code.in_(stock_list)).order_by(valuation.market_cap.desc()).limit(5) r = jqdatasdk.get_fundamentals(q,date='2025-02-03') # 3. 打印市值最高的5只股票 print("上证指数市值最高的5只股票：") for i, row in r.iterrows(): print(f"{i+1}. 股票代码: {row['code']} 市值: {row['market_cap']} ")

感谢分享！！

为什么我的选择试用时，总是显示账号已被注册啊，导致我没法在本地pycharm上运行代码(没有权限)

学习

https://www.joinquant.com/help/api/help#name:api_old 学习打卡

2025.06.09 打卡

量挺大的

@董卓 高手啊

``` # 获取上证指数市值最大的5只股票。 index_stocks=get_index_stocks('000016.XSHG') # 构建查询条件 q=query(valuation.code,valuation.market_cap ).filter(valuation.code.in_(index_stocks) ).order_by(valuation.market_cap.desc() ).limit(5) re = get_fundamentals(q) print("市值最大的5只股票:\n%s" % re) ``` 2018-03-01 00:00:00 - INFO - 市值最大的5只股票: code market_cap 0 601398.XSHG 23772.2973 1 601857.XSHG 14641.6782 2 601288.XSHG 13413.9970 3 601988.XSHG 12452.6036 4 601318.XSHG 12386.6916

``` from jqdatasdk import * import jqdatasdk as jq jq.auth('手机号', '密码') # df = jq.get_price("000001.XSHE",'2024-03-09','2024-04-09') # print(df) # 获取上证50指数的成分股 index_stocks = jq.get_index_stocks('000016.XSHG', date='2024-04-09') print("上证50指数成分股:", index_stocks) # 检查成分股列表是否为空 if not index_stocks: print("成分股列表为空，请检查日期和指数代码。") else: # 构建查询条件 q = query( valuation.code, valuation.market_cap ).filter( valuation.code.in_(index_stocks) ).order_by( valuation.market_cap.desc() ).limit(5) # 获取基金基本面数据 re = jq.get_fundamentals(q,'2024-04-09') print("查询结果:\n", re) # 检查查询结果是否为空 if re.empty: print("查询结果为空，请检查查询条件和日期。") else: print("市值最大的5只股票:\n", re) ```

``` # 导入函数库 from jqdata import * # 获取一只股票最近5个交易日最高价的平均价 stock_price = attribute_history(security='000001.XSHE', count=5, unit='1d', fields=["high"]) print(stock_price.mean()) # 上证指数成分股中流通市值最大的5个股票的股票代码 index_stocks = get_index_stocks("000016.XSHG","2025-07-01") q = query(valuation.code, valuation.circulating_market_cap ).filter(valuation.code.in_(index_stocks) ).order_by(valuation.circulating_market_cap.desc() ).limit(5) w=get_fundamentals(q) print(w) ```

seventh