使用Python获取新浪财经行情数据有多种方法，以下为几种不同场景下的获取方式： ### 爬取历史交易数据 可通过构造特定URL来获取某只股票在特定日期的历史交易数据。示例代码如下： ```python import requests import csv import re def get_stock_data(date, symbol): page = 1 all_records = [] while True: url = f'http://market.finance.sina.com.cn/transHis.php?symbol={symbol}&date={date}&page={page}' headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.41' } res = requests.get(url, headers=headers) # 假设网页返回的表格数据在特定的HTML标签内，这里使用正则表达式提取 records = re.findall(r'<tr>(.*?)</tr>', res.text) if not records or len(records) == 1: # 若没有数据或只有表头则停止 break for record in records[1:]: # 跳过表头 data = re.findall(r'<td>(.*?)</td>', record) all_records.append(data) page += 1 # 保存到CSV文件 with open(f'{symbol}_{date}.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile) writer.writerow(['时间', '成交价', '价格变动', '成交量(手)', '成交额(元)', '性质']) writer.writerows(all_records) # 计算最大值、最小值和平均值 prices = [float(record[1]) for record in all_records] max_price = max(prices) min_price = min(prices) avg_price = sum(prices) / len(prices) print(f"当日股票的最大值: {max_price}") print(f"当日股票的最小值: {min_price}") print(f"当日股票的平均值: {avg_price}") # 示例调用 date = '2021-04-27' symbol = 'sz000001' get_stock_data(date, symbol) ``` ### 获取实时行情数据 可以通过请求特定URL并使用正则表达式提取所需数据。示例代码如下： ```python import requests import re def get_realtime_data(symbol): url = f'https://hq.sinajs.cn/etag.php?_=1676394972987&list={symbol}' headers = { 'Accept': '*/*', 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6', 'Connection': 'keep-alive', 'Host': 'hq.sinajs.cn', 'Referer': f'https://finance.sina.com.cn/realstock/company/{symbol}/nc.shtml?qq-pf-to=pcqq.c2c', 'sec-ch-ua': '"Chromium";v="110", "Not A(Brand";v="24", "Microsoft Edge";v="110"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': '"Windows"', 'Sec-Fetch-Dest': 'script', 'Sec-Fetch-Mode': 'no-cors', 'Sec-Fetch-Site': 'cross-site', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.41' } res = requests.get(url, headers=headers) data = re.findall('.*?电,(.*?),"', res.text, re.S)[0] return data # 示例调用 symbol = 'sh600835' realtime_data = get_realtime_data(symbol) print(realtime_data) ``` ### 获取行情数据并写入MongoDB 使用`akshare`库获取股票行情数据，并将其写入MongoDB。示例代码如下： ```python import pymongo import akshare as ak import json # 打开数据库 mongo_client = pymongo.MongoClient('mongodb://localhost:27017/') # 若没有Database和Collection，则会自动创建 mongo_db = mongo_client['SinaData'] mongo_collection = mongo_db['sz000001'] # 在量化投资研究中普遍采用后复权数据 新浪财经 stock_zh_a_daily_qfq_df = ak.stock_zh_a_daily(symbol="sz000001", adjust="qfq") # 历史行情数据(前复权) print(stock_zh_a_daily_qfq_df) print(type(stock_zh_a_daily_qfq_df)) # DataFrame # DataFrame日期列转换为字符串 stock_zh_a_daily_qfq_df['date'] = stock_zh_a_daily_qfq_df['date'].astype(str) # 将DataFrame写入MongoDB data = json.loads(stock_zh_a_daily_qfq_df.T.to_json()).values() mongo_collection.insert_many(data) ```