scrapy+selenium爬取五个外国新闻网站关于“中国“的新闻，并分析

╰+哭是因爲堅強的太久メ 2023-01-03 01:58 173阅读 0赞

# 1.题目 #

> 爬取一下5家的加拿大新闻网站包含“China” /  
> "Chinese"的数据，时间范围为2020年1月日至今，分析每家媒体文章的词云图、情感趋势图等。  
> https://www.cbc.ca/  
> https://nationalpost.com/  
> https://www.thestar.com/?redirect=true  
> https://www.ctvnews.ca/  
> https://globalnews.ca/national/

# 2.scrapy+selenium爬取动态网站 #

以CBC网站爬取为例,spider编写如下

import scrapy
    from ..items import CbcItem
    from selenium import webdriver
    from selenium.webdriver import FirefoxOptions
    from threading import Thread, Lock
    class ChinaSpider(scrapy.Spider):
        name = 'china'
        allowed_domains = ['https://www.cbc.ca/']
        start_urls = ['https://www.cbc.ca/search?q=china&section=news']
    
        def __init__(self):
            # 在初始化时，创建driver
            super(ChinaSpider, self).__init__(name='china')
            option = FirefoxOptions()
            option.headless = True
            self.driver = webdriver.Firefox(options=option)
    
        def parse(self, response):
            tr_list = response.xpath("//div[@class='contentListCards']/a")
            for tr in tr_list:
                item = CbcItem()
                href = tr.xpath("./@href").extract_first()
                time = tr.xpath(
                        "./div/div/div[@class='card-content-bottom']/div/div/time/@datetime").extract_first()
                year = time[:4]
                month = time[5:7]
                print(year+month)
                if int(month) >=1 and int(year) == 2020:
                    if (href[1:5] == 'news'):
                        item["title"] = tr.xpath("./div/div/div[@class='card-content-top']/h3/text()").extract_first()
                        item["brief"] = tr.xpath(
                            "./div/div/div[@class='card-content-top']/div[@id='d-card-']/text()").extract_first()
                        item['herf'] = 'https://www.cbc.ca' + href
                        item['publish_date'] = tr.xpath(
                            "./div/div/div[@class='card-content-bottom']/div/div/time/@datetime").extract_first()
                       # 详情页爬取
                        yield scrapy.Request(
                            item['herf'],
                            callback=self.parse_detail,
                            meta={ "item": item},
                            dont_filter=True
                        )
               
        def parse_detail(self, response):
            item = response.meta['item']
            item["content"] = response.xpath("//div[@class='story']/span/p/text()").extract()
            item["content"] = "".join(item["content"])
            print(item)
            yield(item)

在middlewares中编写自己的Download方法,并在setting中修改  
主要是完成浏览器对js页面的解析

if spider.name == "china":
                    spider.driver.get(request.url)
                    # CBc爬虫的初始页面不断点击
                    if (request.url == "https://www.cbc.ca/search?q=china&section=news"):
                        print("我只运行了一次")
                        for i in range(70):
                            button = spider.driver.find_element_by_xpath(
                                "//*[@id='content']/div/div[4]/section/div[1]/div[2]/div/button")
                            spider.driver.execute_script("arguments[0].click();", button)
                            print("我已经点击了%d" % i)
                            time.sleep(2)
    
                    # 由于页面数据加载需要进行滚动，但并不是所有js动态数据都需要滚动。
                    for x in range(1, 11, 2):
                        height = float(x) / 10
                        js = "document.documentElement.scrollTop = document.documentElement.scrollHeight * %f" % height
                        spider.driver.execute_script(js)
                        time.sleep(0.2)
                    origin_code = spider.driver.page_source
                    # 将源代码构造成为一个Response对象，并返回。
                    res = HtmlResponse(url=request.url, encoding='utf8', body=origin_code, request=request)
                    # res = Response(url=request.url, body=bytes(origin_code), request=request)
                    return res

# 3.最终结果 #

3.1数据  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2k2MjIzNjcx_size_16_color_FFFFFF_t_70]  
3.2简单分析  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2k2MjIzNjcx_size_16_color_FFFFFF_t_70 1]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2k2MjIzNjcx_size_16_color_FFFFFF_t_70 2]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2k2MjIzNjcx_size_16_color_FFFFFF_t_70 3]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2k2MjIzNjcx_size_16_color_FFFFFF_t_70 4]  
**注意**  
1.用梯子  
2.解析js页面很慢  
3.需要占用本地资源,最好使用服务器,可以使用分布式

# 4.下载 #

链接：https://pan.baidu.com/s/1iJoEo8JoUPsz6aJE4de12A  
提取码：cua9

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