信息时代程序员轻松带你爬取汽车之家数据

使用BeautifulSoup模块
使用正则表达式
使用到多线程爬取
使用说明
使用前请安装BeauifulSoup
运行程序后会在当前目录下生成txt文件,内容为json格式.如下所示:

{“branch_first_letter”: “S”, “branch_name”: “萨博”, “branch_id”: “64”, “producer”: “萨博”, “producer_id”: “”, “car_series”: “Saab 900”, “car_series_id”: “s2630”, “car_price”: }
源代码
#!/usr/bin/env python 
# -*- coding: utf-8 -*-
# @Time    : 2020/1/16 15:34
# @Author  : wsx
# @Site    : 
# @File    : cars.py
# @Software: PyCharm

import json
from multiprocessing import Pool
import requests
from requests.exceptions import RequestException
import re
from bs4 import BeautifulSoup


def get_one_page(url):
    """
    请求网页函数.
    :param url:
    :return:
    """
    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64; rv:68.0) Gecko/20100101 Firefox/68.0'}
    try:
        response = requests.get(url, headers=headers)
        print(response.status_code)
        if response.status_code == 200:
            return response.text
        return None
    except RequestException:
        return None


def parse_one_page(html, first_letter):
    """
    网页处理函数, 生成器
    :param html:
    :param first_letter:
    :return:iterable
    """
    # 加载网页
    soup = BeautifulSoup(html, 'lxml')
    # 创建字典,存储数据
    info = {'branch_first_letter': '', 'branch_name': '', 'branch_id': '', 'producer': '', 'producer_id': '',
            'car_series': '', 'car_series_id': '', 'car_price': ''}
    # 找出所需信息在的标签
    branches = soup.find_all('dl')
    # 先获取品牌
    for branch in branches:
        info['branch_name'] = branch.dt.div.a.string.strip()
        info['branch_id'] = branch['id']
        info['branch_first_letter'] = first_letter
        print('正在抓取...品牌:', info['branch_name'])

        # 生成新的处理块
        block = branch.find_all('dd')
        soup = BeautifulSoup(str(block), 'lxml')
        # 获取某一品牌下的所有制造商
        producers = soup.find_all('div', attrs={'class': 'h3-tit'})

        for producer in producers:
            info['producer'] = producer.a.get_text().strip()
            # 找不到这个参数呀.
            info['producer_id'] = ''
            print('正在抓取...生产商:', info['producer'])
            cars = producer.find_next('ul')

            for car in cars.find_all('li', attrs={'id': True}):
                info['car_series_id'] = car['id']
                info['car_series'] = car.h4.a.get_text().strip()
                # 价格这个参数难提取, 初步过滤一下
                price = car.find_all('a', attrs={'class': True, 'data-value': False})
                # 判断一下抓取的是不是价格, 用正则表达式再过滤一下
                if price:
                    print(price[0].get_text())
                    if re.match('.*?万.*?', price[0].get_text(), re.S):
                        info['car_price'] = price[0].get_text().strip()
                    else:
                        info['car_price'] = '暂无报价'
                # 做成迭代器
                yield info


def write_file(content):
    """
    将抓取数据保存成Json文件
    :param content:
    :return: None
    """
    with open('cars.txt', 'a', encoding='utf-8') as f:
        f.write(json.dumps(content, ensure_ascii=False) + '
')
        f.close()


def main(first_letter):
    """
    主函数
    :param first_letter:
    :return: None
    """
    html = get_one_page('https://www.autohome.com.cn/grade/carhtml/' + first_letter + '.html')
    soup = BeautifulSoup(html, 'lxml')
    html = soup.prettify()

    # 测试时先存在本地以免频繁访问站点
    # with open('car_home.html', 'w', encoding='utf-8') as f:
    #     f.write(html)
    #     f.close()
    # with open('car_home.html', 'r', encoding='utf-8') as f:
    #     html = f.read()
    #     f.close()

    for item in parse_one_page(html, first_letter):
        write_file(item)


if __name__ == '__main__':
    # 如不需要按照字母顺序, 则uncomment
    # pool = Pool()
    # pool.map(main, [chr(i + ord('A')) for i in range(26)])
    # 如需要多线程, 则comment
    for letter in [chr(i + ord('A')) for i in range(26)]:
        main(letter)

大家可能会问:为什么爬取个简单的数据还要三层循环?我主要考虑到数据之间的关联性、层级性才使用了三层循环,这样才能保证数据之间的层级关系保持不乱。
编写代码过程中遇到BeautifulSoup中,find_all()方法如果只需要确定是否存在某个属性,而不指定具体属性值,可以写成下面这样:

car.find_all('a', attrs={'class': True, 'data-value': False})
原文地址:https://www.cnblogs.com/jiguangdongtaiip/p/13565845.html