selenium +scrapy 实现网易新闻

目录

• selenium +scrapy 实现网易新闻
  • mongoDB 可视化：
  • 代理测试：
  • 在线测试代理：
• spider.py :
  • 中间件：
  • 网易配置

selenium +scrapy 实现网易新闻

mongoDB 可视化：

https://robomongo.org/download     Robo 3T

配置：
	https://www.jianshu.com/p/0578b636f1bf

代理测试：

import random
import requests
import re

'''
利用访问http://icanhazip.com/返回的IP进行测试
说明：利用的http://icanhazip.com/返回的IP进行校验，如返回的是代理池的IP，说明代理有效，否则实际代理无效
'''

# 代理ip池
PROXIES_NEW = {
    "https": [
        "https://113.226.18.243:80",
        "https://106.56.102.78:808"
    ]
}

lens = len(PROXIES_NEW['https'])
print(lens)
num = 1
while num <= lens:
    try:
        requests.adapters.DEFAULT_RETRIES = 3
        proxies = PROXIES_NEW['https']

        IP = random.choice(proxies)
        b = re.findall('//(d+.d+.d+.d+):', IP)[0]
        b = b.replace('.', '')
        res = requests.get(url="http://icanhazip.com/", timeout=8, proxies={"https": "https://113.140.1.82:53281"})
        proxyIP = res.text
        a = proxyIP.replace('.', '')
        print(a)
        if int(a) == int(b):
            print("代理IP:'" + proxyIP + "'有效！")
        else:
            print("返回不是代理池中的ip，代理IP无效！")
    except:
        print("代理IP无效！")
        print(111)
    num += 1

在线测试代理：

http://www.66ip.cn/yz/

婺源： 
	

spider.py :

class WangyiSpider(RedisSpider):
    name = 'wangyi'
    #allowed_domains = ['www.xxxx.com']
    start_urls = ['https://news.163.com']
    def __init__(self):
        #实例化一个浏览器对象(实例化一次)
        self.bro = webdriver.Chrome(executable_path='/Users/bobo/Desktop/chromedriver')

    #必须在整个爬虫结束后，关闭浏览器
    def closed(self,spider):
        print('爬虫结束')
        self.bro.quit()import scrapy
from wangyipro.items import WangyiproItem
from selenium import webdriver


class WangyiSpider(scrapy.Spider):
    name = 'wangyi'
    # allowed_domains = ['www.xxx.com']
    start_urls = ['https://news.163.com/']
    model_urls = []  # 里面放置的是四个版块对应的详情页URL

    def __init__(self):
        self.bro = webdriver.Chrome(executable_path=r"C:UsersAdministratorDesktop爬虫day06-爬虫chromedriver.exe")

    def news_content_parse(self, response):
        """
        用来解析新闻详情页的内容, 需要接收一下传递过来的item对象
        :param response:
        :return:
        """
        item = response.meta['item']
        # extract()方法获取到的是一个列表,列表里面存的是字符串
        content_list = response.xpath('//div[@id="endText"]//text()').extract()
        item['news_content'] = "".join(content_list)

        yield item

    def parse_detail(self, response):
        """
        用来解析这个版块对应页面的新闻数据, 在这里我们就只爬取新闻的名称
        :param response:
        :return:
        """
        div_list = response.xpath('//div[@class="data_row news_article clearfix "]')
        for div in div_list:
            # 当前只解析到了新闻标题，还没有解析到新闻内容
            item = WangyiproItem()
            news_title = div.xpath('./div/div[1]//a/text()').extract_first()
            news_detail_url = div.xpath('./div/div[1]//a/@href').extract_first()
            item['news_title'] = news_title

            # 发送请求，并获取新闻内容, 使用请求传参，将item传递给下一个解析方法
            yield scrapy.Request(url=news_detail_url, callback=self.news_content_parse, meta={'item': item})

    def parse(self, response):
        """
        解析四个版块对应的URL
        只有在取文本或取属性的时候才可以在xpath中调用extract操作
        :param response:
        :return:
        """
        li_list = response.xpath('//div[@class="ns_area list"]/ul/li')
        indexs = [3, 4, 6, 7]
        model_li_list = []  # 此列表放置四个版块对应的li标签
        for index in indexs:
            li = li_list[index]
            model_li_list.append(li)
        print(model_li_list)

        # 解析出四个版块对应的URL
        for li in model_li_list:
            model_url = li.xpath('./a/@href').extract_first()
            self.model_urls.append(model_url)
            # 接下来对每个版块的URL发起请求, 并获取详情页的页面源码数据
            yield scrapy.Request(url=model_url, callback=self.parse_detail)

中间件：

import time
from scrapy import signals
from scrapy.http import HtmlResponse

# -*- coding: utf-8 -*-

# Define here the models for your spider middleware
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/spider-middleware.html

import time
from scrapy import signals
from scrapy.http import HtmlResponse


class WangyiproDownloaderMiddleware(object):
    # Not all methods need to be defined. If a method is not defined,
    # scrapy acts as if the downloader middleware does not modify the
    # passed objects.

    def process_request(self, request, spider):
        return None

    # 该方法拦截到的是所有的响应对象(需求中要拦截的是部分响应对象)
    def process_response(self, request, response, spider):
        """
        找出指定的响应对象进行解析操作
        可以根据指定的请求对象定位到指定的响应对象
        指定的请求对象可以通过请求的URL进行定位
        定位到指定的URL spider.model_urls
        :param request:
        :param response:
        :param spider:
        :return:
        """
        bro = spider.bro
        if request.url in spider.model_urls:
            # 通过指定的URL就定位到了指定的request
            # 通过指定的requests就可以定位到指定的response(不符合要求的旧响应对象)
            # 自己手动创建四个符合要求的新响应对象(需要将符合要求的响应数据放置到新的响应对象中)
            # 使用新的响应对象替换原来原始的响应对象
            bro.get(request.url)  # 使用浏览器向对应的URL发起请求
            time.sleep(2)
            js = "window.scrollTo(0, document.body.scrollHeight)"
            bro.execute_script(js)
            time.sleep(2)
            page_text = bro.page_source  # 页面源码中就包含了动态加载出来的页面数据

            # 手动创建一个新的响应对象，将page_text作为响应数据封装到该对象中
            # body参数表示的就是响应数据
            return HtmlResponse(url=bro.current_url, body=page_text, encoding='utf-8', request=request)

        return response

    def process_exception(self, request, exception, spider):
        pass

    def spider_opened(self, spider):
        spider.logger.info('Spider opened: %s' % spider.name)

中间件文件

网易配置

BOT_NAME = 'wangyipro'

SPIDER_MODULES = ['wangyipro.spiders']
NEWSPIDER_MODULE = 'wangyipro.spiders'

# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.90 Safari/537.36'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
   'wangyipro.middlewares.WangyiproDownloaderMiddleware': 543,
}

# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   'wangyipro.pipelines.WangyiproPipeline': 300,
}
LOG_LEVEL = 'ERROR'

配置文件