How to Scrape Real-Time Stock Data from Eastmoney with Python

1. Introduction

In a Python community, members discussed how to fetch intraday stock data from Eastmoney, showing a sample screenshot of the time‑frequency data.

A previous guide on retrieving other fund information with Python was referenced (link omitted).

A group member shared an initial code snippet.

# -*- coding: utf-8 -*-
# @Time    : 2022/6/1 23:10
# @Author  : Thresh
# @File    : 1.py
import json
import requests

for page in range(5):
    params = (
        ('pagesize', '144'),
        ('ut', '7eea3edcaed734bea9cbfc24409ed989'),
        ('dpt', 'wzfscj'),
        ('cb', 'jQuery1124029337350072397084_1631343037828'),
        ('pageindex', str(page)),
        ('id', '6009051'),
        ('sort', '1'),
        ('ft', '1'),
        ('code', '688103'),
        ('market', '1'),
        ('_', '1631343037827'),
    )
    response = requests.get('http://push2ex.eastmoney.com/getStockFenShi', params=params, verify=False)
    response = response.text
    response = response.split('(')[1]
    response = response.split(')')[0]
    response = json.loads(response)
    data_lis = response["data"]["data"]
    for data in data_lis:
        print(data)

2. Implementation

The goal is to obtain minute‑level stock data, and two methods are presented.

Method 1 discovers the request URL (shown below).

Opening this URL returns dense JSON data.

Method 1 uses urllib and pandas to request the URL and parse the JSON.

import urllib.request
import pandas as pd
url = 'http://16.push2.eastmoney.com/api/qt/stock/details/sse?fields1=f1,f2,f3,f4&fields2=f51,f52,f53,f54,f55&mpi=2000&ut=bd1d9ddb04089700cf9c27f6f7426281&fltt=2&pos=-0&secid=1.688103'
with urllib.request.urlopen(url=url) as r:
    data = r.readline().decode().lstrip('data:')
print(data)
df = pd.DataFrame(eval(data)['data'])
print(df)

Method 2 employs a low‑level HTTPConnection to request the same endpoint, revealing the underlying IP address.

# -*- coding: utf-8 -*-
from http.client import HTTPConnection

url = 'http://97.push2.eastmoney.com/'
# 119.3.12.115:80
http_conn = HTTPConnection('119.3.12.115', 80)

params = "/api/qt/stock/details/sse?fields1=f1,f2,f3,f4&fields2=f51,f52,f53,f54,f55&mpi=2000&ut=bd1d9ddb04089700cf9c27f6f7426281&fltt=2&pos=-0&secid=0.300059"
headers = {
    "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9",
    "Accept-Encoding": "gzip, deflate",
    "Accept-Language": "zh-CN,zh;q=0.9",
    "Cache-Control": "no-cache",
    "Connection": "keep-alive",
    "Host": "97.push2.eastmoney.com",
    "Pragma": "no-cache",
    "Upgrade-Insecure-Requests": "1",
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
}
http_conn.request("GET", params, headers=headers)

with http_conn.getresponse() as response:
    while not response.closed:
        for line in response:
            print(line.decode("utf-8"))

Method 1 is simpler, while Method 2 offers deeper control; both can be adapted for similar data‑fetching tasks.

3. Conclusion

The article provides two complete Python web‑scraping solutions for retrieving Eastmoney intraday stock data, including URL discovery, code implementation, and execution results, enabling readers to apply these techniques to their own data‑mining projects.