这次的程序是在上次的基础上进行修改,把持久化储存方式改成mysql,并增加了断点续爬功能.
import requests import re from fake_useragent import UserAgent import random import time import pymysql from hashlib import md5 from lxml import etree class DianyingtiantangSpider(object): def __init__(self): self.url = 'https://www.dytt8.net/html/gndy/dyzz/list_23_{}.html' self.db = pymysql.connect(host='127.0.0.1', port=3306, user='root', password='数据库密码', database='filmskydb', charset='utf8') self.cursor = self.db.cursor() def get_headers(self): """ 构建请求头 :return: """ ua = UserAgent() headers = { # "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3", # "Accept-Encoding": "gzip, deflate, br", # "Accept-Language": "zh-CN,zh;q=0.9", # "Cache-Control": "max-age=0", # "Connection": "keep-alive", # "Cookie": "UM_distinctid=16bdec86bc2679-07c211dd7aebc-15231708-1fa400-16bdec86bc3464; CNZZDATA1260535040=961678368-1562805532-https%253A%252F%252Fwww.baidu.com%252F%7C1562805532", # "Host": "www.dytt8.net", # "If-Modified-Since": "Thu, 19 Sep 2019 00:34:23 GMT", # "If-None-Match": "80d1b3fb816ed51:326", # "Sec-Fetch-Mode": "navigate", # "Sec-Fetch-Site": "none", # "Sec-Fetch-User": "?1", # "Upgrade-Insecure-Requests": "1", "User-Agent": ua.random } return headers def parse_page(self, url): """ 解析一级页面 :param url: :return: """ text = requests.get(url=url, headers=self.get_headers()) text.encoding = 'GBK' # 正则匹配第一页的二级页面链接 re_bds = r'<table width="100%".*?<td width="5%".*?<a href="(.*?)".*?ulink">.*?</table>' pattern = re.compile(re_bds, re.S) link_list = pattern.findall(text.text) for link in link_list: two_url = 'https://www.dytt8.net' + link # 生成指纹 s = md5() s.update(two_url.encode()) two_url_md5 = s.hexdigest() # 引入函数判断链接在数据库中是不是存在 if self.judge_repetition(two_url_md5): self.parse_two_page(two_url) # 将指纹保存在数据库中 ins = 'insert into request_finger values(%s)' self.cursor.execute(ins, [two_url_md5]) # 切记要提交至数据库执行 self.db.commit() # 随机产生爬取时间间隔 time.sleep(random.uniform(1, 3)) def judge_repetition(self, two_url_md5): """ 指纹判断 :param two_url_md5: :return: """ sel = 'select finger from request_finger where finger=%s' result = self.cursor.execute(sel, [two_url_md5]) if not result: return True def parse_two_page(self, two_url): """ 提取二级页面的信息 :param two_url: :return: """ text = requests.get(url=two_url, headers=self.get_headers()) text.encoding = 'GBK' html = etree.HTML(text.text) movie = html.xpath('//*[@id="header"]/div/div[3]/div[3]/div[1]/div[2]/div[1]/h1/font/text()') download = html.xpath('//tbody/tr/td/a/@href') # print(movie) # print(download) # return (movie[0], download[0]) ins = 'insert into filmtab values(%s,%s)' film_list = movie + download self.cursor.execute(ins, film_list) self.db.commit() print(film_list) def run(self): """ 主函数 :return: """ for page in range(1, 201): one_url = self.url.format(page) self.parse_page(one_url) time.sleep(random.uniform(1, 3)) if __name__ == '__main__': spider = DianyingtiantangSpider() spider.run()
数据库的话需要提前建好,代码如下:
create database filmskydb charset utf8; use filmskydb; create table request_finger( finger char(32) )charset=utf8; create table filmtab( name varchar(200), download varchar(500) )charset=utf8;
总结:1.增量爬取的原理其实很简单,就是将爬取过的url储存入库,然后在下次爬取的是后将url与库中的url进行比较,去掉已经爬过的url,从而实现断点续爬.这一点很重要,特别是如果在爬取大量数据的时候电脑突然扑街了,然后要从头开始爬取的话,那对工作效率的影响是很大的.
2.这里的指纹其实就是将爬过url用md5加密之后生成的唯一字符串,用于与后来的url进行比较