全站爬虫有时候做起来其实比较容易,因为规则相对容易建立起来,只需要做好反爬就可以了,今天咱们爬取知乎。继续使用
scrapy
当然对于这个小需求来说,使用scrapy确实用了牛刀,不过毕竟这个系列到这个阶段需要不断使用
scrapy
进行过度,so,我写了一会就写完了。
你第一步找一个爬取种子,算作爬虫入口
https://www.zhihu.com/people/zhang-jia-wei/following
我们需要的信息如下,所有的框图都是我们需要的信息。
获取用户关注名单
通过如下代码获取网页返回数据,会发现数据是由HTML+JSON拼接而成,增加了很多解析成本
class ZhihuSpider(scrapy.Spider):
name = 'Zhihu'
allowed_domains = ['www.zhihu.com']
start_urls = ['https://www.zhihu.com/people/zhang-jia-wei/following']
def parse(self, response):
all_data = response.body_as_unicode()
print(all_data)
首先配置一下基本的环境,比如间隔秒数,爬取的UA,是否存储cookies,启用随机UA的中间件
DOWNLOADER_MIDDLEWARES
middlewares.py
文件
from zhihu.settings import USER_AGENT_LIST # 导入中间件
import random
class RandomUserAgentMiddleware(object):
def process_request(self, request, spider):
rand_use = random.choice(USER_AGENT_LIST)
if rand_use:
request.headers.setdefault('User-Agent', rand_use)
Python资源分享qun 784758214 ,内有安装包,PDF,学习视频,这里是Python学习者的聚集地,零基础,进阶,都欢迎
setting.py
文件
BOT_NAME = 'zhihu'
SPIDER_MODULES = ['zhihu.spiders']
NEWSPIDER_MODULE = 'zhihu.spiders'
USER_AGENT_LIST=[ # 可以写多个,测试用,写了一个
"Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36"
]
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# See also autothrottle settings and docs
DOWNLOAD_DELAY = 2
# Disable cookies (enabled by default)
COOKIES_ENABLED = False
# Override the default request headers:
DEFAULT_REQUEST_HEADERS = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Language': 'en',
}
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
'zhihu.middlewares.RandomUserAgentMiddleware': 400,
}
# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
'zhihu.pipelines.ZhihuPipeline': 300,
}
主要爬取函数,内容说明
- start_requests 用来处理首次爬取请求,作为程序入口
- 下面的代码主要处理了2种情况,一种是HTML部分,一种是JSON部分
- JSON部分使用re模块进行匹配,在通过json模块格式化
-
extract_first()
获取xpath匹配数组的第一项 -
dont_filter=False
scrapy URL去重
# 起始位置
def start_requests(self):
for url in self.start_urls:
yield scrapy.Request(url.format("zhang-jia-wei"), callback=self.parse)
def parse(self, response):
print("正在获取 {} 信息".format(response.url))
all_data = response.body_as_unicode()
select = Selector(response)
# 所有知乎用户都具备的信息
username = select.xpath("//span[@class='ProfileHeader-name']/text()").extract_first() # 获取用户昵称
sex = select.xpath("//div[@class='ProfileHeader-iconWrapper']/svg/@class").extract()
if len(sex) > 0:
sex = 1 if str(sex[0]).find("male") else 0
else:
sex = -1
answers = select.xpath("//li[@aria-controls='Profile-answers']/a/span/text()").extract_first()
asks = select.xpath("//li[@aria-controls='Profile-asks']/a/span/text()").extract_first()
posts = select.xpath("//li[@aria-controls='Profile-posts']/a/span/text()").extract_first()
columns = select.xpath("//li[@aria-controls='Profile-columns']/a/span/text()").extract_first()
pins = select.xpath("//li[@aria-controls='Profile-pins']/a/span/text()").extract_first()
# 用户有可能设置了隐私,必须登录之后看到,或者记录cookie!
follwers = select.xpath("//strong[@class='NumberBoard-itemValue']/@title").extract()
item = ZhihuItem()
item["username"] = username
item["sex"] = sex
item["answers"] = answers
item["asks"] = asks
item["posts"] = posts
item["columns"] = columns
item["pins"] = pins
item["follwering"] = follwers[0] if len(follwers) > 0 else 0
item["follwers"] = follwers[1] if len(follwers) > 0 else 0
yield item
# 获取第一页关注者列表
pattern = re.compile('
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