利用 Scrapy 爬取知乎用户信息

Posted 2020-10-24 希希里之海

　　思路：通过获取知乎某个大V的关注列表和被关注列表，查看该大V和其关注用户和被关注用户的详细信息，然后通过层层递归调用，实现获取关注用户和被关注用户的关注列表和被关注列表，最终实现获取大量用户信息。

 

一、新建一个scrapy项目　　

scrapy startproject zhihuuser

　　移动到新建目录下：

cd zhihuuser

　　新建spider项目：

scrapy genspider zhihu zhihu.com

 

二、这里以爬取知乎大V轮子哥的用户信息来实现爬取知乎大量用户信息。

a) 定义 spdier.py 文件（定义爬取网址，爬取规则等）：

# -*- coding: utf-8 -*-
import json

from scrapy import Spider, Request

from zhihuuser.items import UserItem


class ZhihuSpider(Spider):
    name = \'zhihu\'
    allowed_domains = [\'zhihu.com\']
    start_urls = [\'http://zhihu.com/\']
#自定义爬取网址
    start_user = \'excited-vczh\'
    user_url = \'https://www.zhihu.com/api/v4/members/{user}?include={include}\'
    user_query = \'allow_message,is_followed,is_following,is_org,is_blocking,employments,answer_count,follower_count,articles_count,gender,badge[?(type=best_answerer)].topics\'
    follows_url = \'https://www.zhihu.com/api/v4/members/{user}/followees?include={include}&offset={offset}&limit={limit}\'
    follows_query = \'data[*].answer_count,articles_count,gender,follower_count,is_followed,is_following,badge[?(type=best_answerer)].topics\'

    followers_url = \'https://www.zhihu.com/api/v4/members/{user}/followees?include={include}&offset={offset}&limit={limit}\'
    followers_query = \'data[*].answer_count,articles_count,gender,follower_count,is_followed,is_following,badge[?(type=best_answerer)].topics\'
#定义请求爬取用户信息、关注用户和被关注用户的函数
    def start_requests(self):
        yield Request(self.user_url.format(user=self.start_user, include=self.user_query), callback=self.parseUser)
        yield Request(self.follows_url.format(user=self.start_user, include=self.follows_query, offset=0, limit=20), callback=self.parseFollows)
        yield Request(self.followers_url.format(user=self.start_user, include=self.followers_query, offset=0, limit=20), callback=self.parseFollowers)

#请求爬取用户详细信息
    def parseUser(self, response):
        result = json.loads(response.text)
        item = UserItem()

        for field in item.fields:
            if field in result.keys():
                item[field] = result.get(field)
        yield item
#定义回调函数，爬取关注用户与被关注用户的详细信息，实现层层迭代
        yield Request(self.follows_url.format(user=result.get(\'url_token\'), include=self.follows_query, offset=0, limit=20), callback=self.parseFollows)
        yield Request(self.followers_url.format(user=result.get(\'url_token\'), include=self.followers_query, offset=0, limit=20), callback=self.parseFollowers)

#爬取关注者列表
    def parseFollows(self, response):
        results = json.loads(response.text)

        if \'data\' in results.keys():
            for result in results.get(\'data\'):
                yield Request(self.user_url.format(user=result.get(\'url_token\'), include=self.user_query), callback=self.parseUser)

        if \'paging\' in results.keys() and results.get(\'paging\').get(\'is_end\') == False:
            next_page = results.get(\'paging\').get(\'next\')
            yield Request(next_page, callback=self.parseFollows)

#爬取被关注者列表
    def parseFollowers(self, response):
        results = json.loads(response.text)

        if \'data\' in results.keys():
            for result in results.get(\'data\'):
                yield Request(self.user_url.format(user=result.get(\'url_token\'), include=self.user_query), callback=self.parseUser)

        if \'paging\' in results.keys() and results.get(\'paging\').get(\'is_end\')    == False:
            next_page = results.get(\'paging\').get(\'next\')
            yield Request(next_page, callback=self.parseFollowers)

 

b) 定义 items.py 文件（定义爬取数据的信息，使其规整等）：

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

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

from scrapy import Field, Item


class UserItem(Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    allow_message = Field()
    answer_count = Field()
    articles_count = Field()
    avatar_url = Field()
    avatar_url_template = Field()
    badge = Field()
    employments = Field()
    follower_count = Field()
    gender = Field()
    headline = Field()
    id = Field()
    name = Field()
    type = Field()
    url = Field()
    url_token = Field()
    user_type = Field()

 

c) 定义 pipelines.py 文件（存储数据到MongoDB）:

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

# Define your item pipelines here
#
# Don\'t forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
import pymongo

#存储到MongoDB
class MongoPipeline(object):

    collection_name = \'users\'

    def __init__(self, mongo_uri, mongo_db):
        self.mongo_uri = mongo_uri
        self.mongo_db = mongo_db

    @classmethod
    def from_crawler(cls, crawler):
        return cls(
            mongo_uri=crawler.settings.get(\'MONGO_URI\'),
            mongo_db=crawler.settings.get(\'MONGO_DATABASE\')
        )

    def open_spider(self, spider):
        self.client = pymongo.MongoClient(self.mongo_uri)
        self.db = self.client[self.mongo_db]

    def close_spider(self, spider):
        self.client.close()

    def process_item(self, item, spider):
        self.db[self.collection_name].update({\'url_token\': item[\'url_token\']}, dict(item), True)        #执行去重操作
        return item

 

d) 定义settings.py 文件（开启MongoDB、定义请求头、不遵循 robotstxt 规则）：

# -*- coding: utf-8 -*-
BOT_NAME = \'zhihuuser\'

SPIDER_MODULES = [\'zhihuuser.spiders\']

# Obey robots.txt rules
ROBOTSTXT_OBEY = False  #是否遵守robotstxt规则，限制爬取内容。

# Override the default request headers（加载请求头）:
DEFAULT_REQUEST_HEADERS = {
  \'Accept\': \'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\',
  \'Accept-Language\': \'en\',
  \'User-agent\': \'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.140 Safari/537.36\',
  \'authorization\': \'oauth c3cef7c66a1843f8b3a9e6a1e3160e20\'
}

# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   \'zhihuuser.pipelines.MongoPipeline\': 300,
}


MONGO_URI = \'localhost\'
MONGO_DATABASE = \'zhihu\'

 

三、开启爬取：

scrapy crawl zhihu

 

部分爬取过程中的信息

 

存储到MongoDB的部分信息：