python爬虫：搜狗微信公众号文章信息的采集（https://weixin.sogou.com/），保存csv文件

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互联网集市收集整理的这篇技术教程文章主要介绍了python爬虫：搜狗微信公众号文章信息的采集（https://weixin.sogou.com/），保存csv文件，小编现在分享给大家，供广大互联网技能从业者学习和参考。文章包含3085字，纯文字阅读大概需要5分钟。

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import requests
from requests.exceptions import RequestException
from lxml import etree
import csv
import re
import time
from urllib import parse
import time


def get_page(url):
    """
        获取网页的源代码
    :param url:
    :return:
    """
    try:
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50',

        }
        response = requests.get(url, headers=headers)
        if response.status_code == 200:
            return response.text
        return None
    except RequestException:
        return None

def timeswitch(chuo):

    tupTime = time.localtime(chuo)  # 秒时间戳
    stadardTime = time.strftime("%Y-%m-%d %H:%M:%S", tupTime)
    return stadardTime

def parse_page(text):
    """
        解析网页源代码
    :param text:
    :return:
    """
    html = etree.HTML(text)

    '''
    movie_name = html.xpath("//*[@id='sogou_vr_11002601_title_0']/text()[1]")
    actor = html.xpath("//p[@class='star']/text()")
    actor = list(map(lambda item: re.sub('\s+', '', item), actor))
    time = html.xpath("//p[@class='releasetime']/text()")
    grade1 = html.xpath("//p[@class='score']/i[@class='integer']/text()")
    grade2 = html.xpath("//p[@class='score']/i[@class='fraction']/text()")
    new = [grade1[i] + grade2[i] for i in range(min(len(grade1), len(grade2)))]
    ranking = html.xpath("///dd/i/text()")
    return zip(ranking, movie_name, actor, time, new)
    '''

    biaotinew = list()
    biaoti = html.xpath("//div[@class='txt-box']/h3/a")
    for bt in biaoti:
        b = bt.xpath("string(.)")
        biaotinew.append(b)
    print(biaotinew)

    wangzhinew = list()
    base_url = 'https://weixin.sogou.com'
    wangzhi = html.xpath("//div[@class='txt-box']/h3//@href")
    for wz in wangzhi:
        w = "".join(list(base_url)+wangzhi)
        wangzhinew.append(w)
    print(wangzhinew)

    zhaiyaonew = list()
    zhaiyao = html.xpath("//p[@class='txt-info']")
    for bt in zhaiyao:
        b = bt.xpath("string(.)")
        zhaiyaonew.append(b)
    print(zhaiyaonew)

    gzh  = html.xpath("//a[@class='account']/text()")
    print(gzh)

    lastnew = list()
    shijiannew = list()
    shijian = html.xpath("//div[2]/div/span")
    for bt in shijian:
        b = bt.xpath("string(.)")
        shijiannew.append(b)
    for bp in shijiannew :
        newstr  = re.findall(r"\d+\.?\d*",bp)
        # ['1.45', '5', '6.45', '8.82']
        lastor = ''.join(newstr)
        lastnew.append(timeswitch(int(lastor)))
    print(lastnew)




    return zip(biaotinew,wangzhinew,zhaiyaonew,gzh,lastnew)




def change_page1(number):
    """
        翻页
    :param number:
    :return:
    """
    base_url ='https://weixin.sogou.com/weixin?oq=&query=python&_sug_type_=1&sut=0&lkt=0%2C0%2C0&s_from=input&ri=1&_sug_=n&type=2&sst0=1604564741184&page='
    url = base_url +str(number)+'&ie=utf8&p=40040108&dp=1&w=01015002&dr=1'
    return url


def save_to_csv(result, filename):
    """
        保存
    :param result:
    :param filename:
    :return:
    """
    with open(filename, 'a',encoding='utf-8-sig',newline="") as csvfile:
        writer = csv.writer(csvfile, dialect='excel')
        writer.writerow(result)


def main():
    """
    主函数
    :return:
    """
    f = open('message.csv', 'a+', encoding='utf-8-sig', newline="")  # newline取消空行
    csv_writer = csv.writer(f)
    csv_writer.writerow(["文章名称","文章链接地址","摘要","公众号名称","发布时间"])
    f.close()




    for number in range(1,6):
        url = change_page1(number)
        text = get_page(url)
        result = parse_page(text)
        for a in result:
            save_to_csv(a, filename='message.csv')


if __name__ == '__main__':
    main()

内容总结

以上是互联网集市为您收集整理的python爬虫：搜狗微信公众号文章信息的采集（https://weixin.sogou.com/），保存csv文件全部内容，希望文章能够帮你解决python爬虫：搜狗微信公众号文章信息的采集（https://weixin.sogou.com/），保存csv文件所遇到的程序开发问题。 如果觉得互联网集市技术教程内容还不错，欢迎将互联网集市网站推荐给程序员好友。

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