引言

在信息爆炸的时代，获取实时的财经资讯对于投资者和金融从业者来说至关重要。然而，手动浏览网页收集财经文章耗时费力，为了解决这一问题，本文将介绍如何使用Python编写一个爬虫程序来自动爬取网易财经下关于财经的文章

1. 爬虫代码概述

本文将使用Python编写一个爬虫程序，该程序能够爬取网易财经下关于财经的文章，并将爬取的结果保存为JSON文件。爬虫程序的主要流程如下：

• 设置请求头信息，模拟浏览器访问
• 定义爬取函数，根据不同的文章类型爬取相应的URL
• 解析爬取的网页内容，提取文章标题、链接等信息
• 将爬取结果保存为JSON文件
• 多线程并发爬取文章内容并保存

2. 网页分析与URL获取

在爬取网易财经的文章之前，我们需要先分析网页结构并获取相应的URL。通过分析，我们发现网易财经的财经文章分为股票、商业、基金、房产和理财五个类别。每个类别的文章都有对应的URL，我们可以根据这些URL来爬取相应的文章

base_url = ['https://money.163.com/special/00259BVP/news_flow_index.js?callback=data_callback',
            'https://money.163.com/special/00259BVP/news_flow_biz.js?callback=data_callback',
            'https://money.163.com/special/00259BVP/news_flow_fund.js?callback=data_callback',
            'https://money.163.com/special/00259BVP/news_flow_house.js?callback=data_callback',
            'https://money.163.com/special/00259BVP/news_flow_licai.js?callback=data_callback']

3. 爬虫实现

我们使用Python的requests库发送HTTP请求并使用BeautifulSoup库解析网页内容。以下是爬取网易财经文章的主要代码：

import requests
import re
from bs4 import BeautifulSoup
from tqdm import tqdm
import os
import bag
from concurrent.futures import ThreadPoolExecutor

# 设置请求头信息
session = requests.session()
session.headers['User-Agent'] = r'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36'
session.headers['Referer'] = r'https://money.163.com/'
session.headers['Accept-Language'] = 'zh-CN,zh;q=0.9'

# 定义爬取函数
def get_url(url, kind):
    num = 1
    result = []
    while True:
        if num == 1:
            resp = session.get(url)
        else:
            if num < 10:
                resp = session.get(url.replace('.js?callback=data_callback', '') + f'_0{num}' + '.js?callback=data_callback')
            else:
                resp = session.get(url.replace('.js?callback=data_callback', '') + f'_{num}' + '.js?callback=data_callback')
        if resp.status_code == 404:
            break
        num += 1
        title = re.findall(r'"title":"(.*?)"', resp.text, re.S)
        docurl = re.findall(r'"docurl":"(.*?)"', resp.text, re.S)
        label = re.findall('"label":"(.*?)"', resp.text, re.S)
        keyword = re.findall(r'"keywords":\[(.*?)]', resp.text, re.S)
        mid = []
        for k in keyword:
            mid1 = []
            for j in re.findall(r'"keyname":"(.*?)"', str(k), re.S):
                mid1.append(j.strip())
            mid.append(','.join(mid1))
        for i in range(len(title)):
            result.append([
                title[i],
                docurl[i],
                label[i],
                kind,
                mid[i]
            ])
    return result

# 爬取文章内容
def get_data(ls):
    resp = session.get(ls[1])
    resp.encoding = 'utf8'
    resp.close()

    html = BeautifulSoup(resp.text, 'lxml')

    content = []
    p = re.compile(r'<p.*?>(.*?)</p>', re.S)
    contents = html.find_all('div', class_='post_body')
    for info in re.findall(p, str(contents)):
        content.append(re.sub('<.*?>', '', info))
    return [ls[-1], ls[0], '\n'.join(content), ls[-2], ls[1]]

# 主函数
def main():
    base_url = ['https://money.163.com/special/00259BVP/news_flow_index.js?callback=data_callback',
                'https://money.163.com/special/00259BVP/news_flow_biz.js?callback=data_callback',
                'https://money.163.com/special/00259BVP/news_flow_fund.js?callback=data_callback',
                'https://money.163.com/special/00259BVP/news_flow_house.js?callback=data_callback',
                'https://money.163.com/special/00259BVP/news_flow_licai.js?callback=data_callback']
    kind = ['股票', '商业', '基金', '房产', '理财']

    path = r'./财经(根数据).json'
    save_path = r'./财经.json'

    if os.path.isfile(path):
        source_ls = bag.Bag.read_json(path)
    else:
        source_ls = []

    index = 0
    urls = []
    for url in base_url:
        result = get_url(url, kind[index])
        index += 1
        urls = urls + result

    newly_added = []
    if len(source_ls) == 0:
        bag.Bag.save_json(urls, path)
        newly_added = urls
    else:
        flag = [i[1] for i in source_ls]
        for link in urls:
            if link[1] in flag:
                pass
            else:
                newly_added.append(link)
    if len(newly_added) == 0:
        print('无新数据')
    else:
        bag.Bag.save_json(newly_added + source_ls, path)
        if os.path.isfile(save_path):
            data_result = bag.Bag.read_json(save_path)
        else:
            data_result = []
        with ThreadPoolExecutor(max_workers=20) as t:
            tasks = []
            for url in tqdm(newly_added, desc='网易财经'):
                url: list
                tasks.append(t.submit(get_data, url))

            end = []
            for task in tqdm(tasks, desc='网易财经'):
                end.append(task.result())
            bag.Bag.save_json(end + data_result, save_path)

if __name__ == '__main__':
    main()

4. 结果保存与展示

爬取的结果将保存为JSON文件，方便后续处理和分析。可以使用bag库来保存和读取JSON文件。以下是保存结果的代码：

import os
import bag

# 保存结果
path = r'./财经(根数据).json'
save_path = r'./财经.json'

if os.path.isfile(path):
    source_ls = bag.Bag.read_json(path)
else:
    source_ls = []
...
...

if len(newly_added) == 0:
    print('无新数据')
else:
    bag.Bag.save_json(newly_added + source_ls, path)
    if os.path.isfile(save_path):
        data_result = bag.Bag.read_json(save_path)
    else:
        data_result = []
    with ThreadPoolExecutor(max_workers=20) as t:
        tasks = []
        for url in tqdm(newly_added, desc='网易财经'):
            url: list
            tasks.append(t.submit(get_data, url))

        end = []
        for task in tqdm(tasks, desc='网易财经'):
            end.append(task.result())
        bag.Bag.save_json(end + data_result, save_path)

5.运行结果

6. 总结

本文介绍了如何使用Python编写一个爬虫程序来爬取网易财经下关于财经的文章。通过分析网页结构，获取相应的URL，并使用requests和BeautifulSoup库来发送HTTP请求和解析网页内容。最后，将爬取的结果保存为JSON文件。该爬虫程序可以帮助投资者和金融从业者快速获取财经资讯，提高工作效率。

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