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Scrapy项目实战:爬取某社区用户详情

时间:2020-05-30 20:06:36      阅读:60      评论:0      收藏:0      [点我收藏+]

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get_cookies.py

from selenium import webdriver
from pymongo import MongoClient
from scrapy.crawler import overridden_settings
# from segmentfault import settings
import time
import settings

class GetCookies(object):
    def __init__(self):
        # 初始化组件
        # 设定webdriver选项
        self.opt = webdriver.ChromeOptions()
        # self.opt.add_argument("--headless")
        # 初始化用户列表
        self.user_list = settings.USER_LIST
        # 初始化MongoDB参数
        self.client = MongoClient(settings.MONGO_URI)
        self.db = self.client[settings.MONGO_DB]
        self.collection = self.db["cookies"]

    def get_cookies(self,username,password):
        """

        :param username:
        :param password:
        :return: cookies
        """
        # 使用webdriver选项创建driver
        driver = webdriver.Chrome(executable_path="/Users/Hank/scrapy/segmentfault/segmentfault/chromedriver",options=self.opt)
        driver.get("https://segmentfault.com/user/login")
        driver.find_element_by_name("username").send_keys(username)
        driver.find_element_by_name("password").send_keys(password)
        driver.find_element_by_xpath("//button[@type=‘submit‘]").click()
        time.sleep(2)
        driver.get("https://segmentfault.com/u/luwangmeilun/users/following")
        # 登陆之后获取页面cookies
        cookies = driver.get_cookies()
        driver.quit()

        return cookies

    def format_cookies(self,cookies):
        """

        :param cookies:
        从driver.get_cookies的形式为:
        [{‘domain‘: ‘segmentfault.com‘, ‘httpOnly‘: False, ‘name‘: ‘PHPSESSID‘,
        ‘path‘: ‘/‘, ‘secure‘: False, ‘value‘: ‘web2~5grmfa89j12eksub8hja3bvaq4‘},
        {‘domain‘: ‘.segmentfault.com‘, ‘expiry‘: 1581602940, ‘httpOnly‘: False,
        ‘name‘: ‘Hm_lvt_e23800c454aa573c0ccb16b52665ac26‘, ‘path‘: ‘/‘, ‘secure‘: False,
        ‘value‘: ‘1550066940‘},
        {‘domain‘: ‘.segmentfault.com‘, ‘httpOnly‘: False,
        ‘name‘: ‘Hm_lpvt_e23800c454aa573c0ccb16b52665ac26‘,
        ‘path‘: ‘/‘, ‘secure‘: False, ‘value‘: ‘1550066940‘},
        {‘domain‘: ‘.segmentfault.com‘, ‘expiry‘: 1550067000, ‘httpOnly‘: False,
        ‘name‘: ‘_gat‘, ‘path‘: ‘/‘, ‘secure‘: False, ‘value‘: ‘1‘},
        {‘domain‘: ‘.segmentfault.com‘, ‘expiry‘: 1550153340, ‘httpOnly‘: False,
        ‘name‘: ‘_gid‘, ‘path‘: ‘/‘, ‘secure‘: False, ‘value‘: ‘GA1.2.783265084.1550066940‘},
        {‘domain‘: ‘.segmentfault.com‘, ‘expiry‘: 1613138940, ‘httpOnly‘: False, ‘name‘: ‘_ga‘,
        ‘path‘: ‘/‘, ‘secure‘: False, ‘value‘: ‘GA1.2.1119166665.1550066940‘}]
        只需提取每一项的name与value即可

        :return:
        """
        c = dict()
        for item in cookies:
            c[item[‘name‘]] = item[‘value‘]

        return c

    def save(self):
        print("开始获取Cookies....")
        # 从用户列表中获取用户名与密码,分别登陆获取cookies
        for username,password in self.user_list:
            cookies = self.get_cookies(username,password)
            f_cookies = self.format_cookies(cookies)
            print("insert cookie:{}".format(f_cookies))
            # 将格式整理后的cookies插入MongoDB数据库
            self.collection.insert_one(f_cookies)

        # s = db[self.collection].find()
        # for i in s:
        #     print(i)


if __name__ == ‘__main__‘:

    cookies = GetCookies()
    for i in range(20):
        cookies.save()

item.py

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

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

import scrapy


class SegmentfaultItem(scrapy.Item):
    # define the fields for your item here like:
    # 个人属性
    # 姓名
    name = scrapy.Field()
    # 声望
    rank = scrapy.Field()
    # 学校
    school = scrapy.Field()
    # 专业
    majors = scrapy.Field()
    # 公司
    company = scrapy.Field()
    # 工作
    job = scrapy.Field()
    # blog
    blog = scrapy.Field()
    # 社交活动数据
    # 关注人数
    following = scrapy.Field()
    # 粉丝数
    fans = scrapy.Field()
    # 回答数
    answers = scrapy.Field()
    # 提问数
    questions = scrapy.Field()
    # 文章数
    articles = scrapy.Field()
    # 讲座数
    lives = scrapy.Field()
    # 徽章数
    badges = scrapy.Field()
    # 技能属性
    # 点赞数
    like = scrapy.Field()
    # 技能
    skills = scrapy.Field()
    # 注册日期
    register_date = scrapy.Field()
    # 问答统计
    # 回答最高得票数
    answers_top_score = scrapy.Field()
    # 得票数最高的回答对应的问题的标题
    answers_top_title = scrapy.Field()
    # 得票数最高的回答对应的问题的标签
    answers_top_tags = scrapy.Field()
    # 得票数最高的回答对应的问题的内容
    answers_top_question = scrapy.Field()
    # 得票数最高的回答对应的问题的内容
    answers_top_content = scrapy.Field()

pipeline.py

# -*- 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

class SegmentfaultPipeline(object):
    # 设定MongoDB集合名称
    collection_name = ‘userinfo‘

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

    # 通过crawler获取settings.py中设定的MongoDB连接信息
    @classmethod
    def from_crawler(cls,crawler):
        return cls(
            mongo_uri = crawler.settings.get(‘MONGO_URI‘),
            mongo_db = crawler.settings.get(‘MONGO_DB‘,‘segmentfault‘)
        )

    # 当爬虫启动时连接MongoDB
    def open_spider(self,spider):
        self.client = pymongo.MongoClient(self.mongo_uri)
        self.db = self.client[self.mongo_db]

    # 当爬虫关闭时断开MongoDB连接
    def close_spider(self,spider):
        self.client.close()

    # 将Item插入数据库保存
    def process_item(self, item, spider):
        self.db[self.collection_name].insert_one(dict(item))
        return item

settings.py

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

# Scrapy settings for segmentfault project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://doc.scrapy.org/en/latest/topics/settings.html
#     https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://doc.scrapy.org/en/latest/topics/spider-middleware.html

BOT_NAME = ‘segmentfault‘

SPIDER_MODULES = [‘segmentfault.spiders‘]
NEWSPIDER_MODULE = ‘segmentfault.spiders‘


# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = ‘Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36‘

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
CONCURRENT_REQUESTS = 100

# Configure a delay for requests for the same website (default: 0)
# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# DOWNLOAD_DELAY = 2
# The download delay setting will honor only one of:
# CONCURRENT_REQUESTS_PER_DOMAIN = 32
# CONCURRENT_REQUESTS_PER_IP = 32

# Disable cookies (enabled by default)
# COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

RETRY_ENABLED = False

REDIRECT_ENABLED = False

DOWNLOAD_TIMEOUT = 5

# HTTPALLOW

# 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‘,
#}


# Enable or disable spider middlewares
# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
   ‘segmentfault.middlewares.SegmentfaultSpiderMiddleware‘: 543,
}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
   # ‘segmentfault.middlewares.SegmentfaultHttpProxyMiddleware‘: 543,
   ‘segmentfault.middlewares.SegmentfaultUserAgentMiddleware‘:643,
   ‘segmentfault.middlewares.SegmentfaultCookiesMiddleware‘:743,
   ‘scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware‘: None,
   ‘scrapy.downloadermiddlewares.useragent.UserAgentMiddleware‘: None,
   # ‘scrapy.downloadermiddlewares.cookies.CookiesMiddleware‘:None,

}

# Enable or disable extensions
# See https://doc.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    ‘scrapy.extensions.telnet.TelnetConsole‘: None,
#}

# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   ‘segmentfault.pipelines.SegmentfaultPipeline‘: 300,
}

# Enable and configure the AutoThrottle extension (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/autothrottle.html
# AUTOTHROTTLE_ENABLED = True
# # The initial download delay
# AUTOTHROTTLE_START_DELAY = 5
# # The maximum download delay to be set in case of high latencies
# AUTOTHROTTLE_MAX_DELAY = 60
# # The average number of requests Scrapy should be sending in parallel to
# # each remote server
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# # Enable showing throttling stats for every response received:
# AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = ‘httpcache‘
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = ‘scrapy.extensions.httpcache.FilesystemCacheStorage‘

# 配置MONGODB
MONGO_URI = ‘localhost:27017‘
MONGO_DB = ‘segmentfault‘

# 用户列表
USER_LIST = [
   ("798549150@qq.com","guoqing1010"),
   ("learnscrapy@163.com","guoqing1010"),
]

# 配置代理列表
PROXY_LIST = [
   ‘http://115.182.212.169:8080‘,
   ‘http://121.61.25.149:9999‘,
   ‘http://180.118.247.189:9000‘,
   ‘http://115.151.3.12:9999‘,
   ‘http://183.154.213.160:9000‘,
   ‘http://113.128.9.106:9999‘,
   ‘http://124.42.68.152:90‘,
   ‘http://49.70.48.50:9999‘,
   ‘http://113.128.11.172:9999‘,
   ‘http://111.177.177.40:9999‘,
   ‘http://59.62.83.253:9999‘,
   ‘http://39.107.84.185:8123‘,
   ‘http://124.94.195.107:9999‘,
   ‘http://111.177.160.132:9999‘,
   ‘http://120.25.203.182:7777‘
]

USER_AGENT_LIST = [
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36 OPR/26.0.1656.60‘,
   ‘Opera/8.0 (Windows NT 5.1; U; en)‘,
   ‘Mozilla/5.0 (Windows NT 5.1; U; en; rv:1.8.1) Gecko/20061208 Firefox/2.0.0 Opera 9.50‘,
   ‘Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; en) Opera 9.50‘,
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64; rv:34.0) Gecko/20100101 Firefox/34.0‘,
   ‘Mozilla/5.0 (X11; U; Linux x86_64; zh-CN; rv:1.9.2.10) Gecko/20100922 Ubuntu/10.10 (maverick) Firefox/3.6.10‘,
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.71 Safari/537.36‘,
   ‘Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11‘,
   ‘Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US) AppleWebKit/534.16 (KHTML, like Gecko) Chrome/10.0.648.133 Safari/534.16‘,
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBBROWSER‘,
   ‘Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E; LBBROWSER)‘,
   ‘Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E)‘,
   ‘Mozilla/5.0 (Windows NT 5.1) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.84 Safari/535.11 SE 2.X MetaSr 1.0‘,
   ‘Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Trident/4.0; SV1; QQDownload 732; .NET4.0C; .NET4.0E; SE 2.X MetaSr 1.0)‘,
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Maxthon/4.4.3.4000 Chrome/30.0.1599.101 Safari/537.36‘,
   ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/38.0.2125.122 UBrowser/4.0.3214.0 Safari/537.36‘
]

userinfo.py

# -*- coding: utf-8 -*-
import scrapy
import time
from scrapy import Request
from pymongo import MongoClient
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider,Rule
from scrapy.http import FormRequest
from segmentfault.items import SegmentfaultItem


class UserinfoSpider(CrawlSpider):
    name = ‘userinfo‘
    allowed_domains = [‘segmentfault.com‘]
    start_urls = [‘https://segmentfault.com/u/mybigbigcat/users/following‘]

    rules = (
        # 用户主页地址,跟进并进行解析
        Rule(LinkExtractor(allow=r‘/u/\w+$‘),callback=‘parse_item‘,follow=True),
        # 用户关注列表,跟进列表页面,抓取用户主页地址进行后续操作
        # Rule(LinkExtractor(allow=r‘/users/followed$‘),follow=True),
        # 用户粉丝列表,跟进列表页面,抓取用户主页地址进行后续操作
        Rule(LinkExtractor(allow=r‘/users/following$‘),follow=True),
        # 跟进其他页面地址
        # Rule(LinkExtractor(allow=r‘/users/[followed|following]?page=\d+‘),follow=True),
    )

    def start_requests(self):
        # 从MongoDB中获取一条cookie,添加到开始方法
        client = MongoClient(self.crawler.settings[‘MONGO_URI‘])
        db = client[self.crawler.settings[‘MONGO_DB‘]]
        cookies_collection = db.cookies
        # 获取一条cookie
        cookies = cookies_collection.find_one()
        # cookie中的‘Hm_lpvt_e23800c454aa573c0ccb16b52665ac26‘参数是当前时间的10位表示法,因此重新填充
        cookies[‘Hm_lpvt_e23800c454aa573c0ccb16b52665ac26‘] = str(int(time.time()))

        return [Request("https://segmentfault.com",
                        cookies=cookies,
                        meta={‘cookiejar‘:1},
                        callback=self.after_login)]

    # 登录之后从start_url中开始抓取数据
    def after_login(self,response):
        for url in self.start_urls:
            return self.make_requests_from_url(url)
    # def after_login(self,response):
    #     yield Request(self.start_urls[0],
    #                    meta={‘cookiejar‘:response.meta[‘cookiejar‘]},
    #                    callback=self.parse_item)

    def parse_item(self, response):
        """
        :param response:
        :return:
        """
        item = SegmentfaultItem()
        # 个人属性模块
        profile_head = response.css(‘.profile__heading‘)
        # 姓名
        item[‘name‘] = profile_head.css(‘h2[class*=name]::text‘).re_first(r‘\w+‘)
        # 声望
        item[‘rank‘] = profile_head.css(‘.profile__rank-btn > span::text‘).extract_first()
        # 学校专业信息
        school_info = profile_head.css(‘.profile__school::text‘).extract()
        if school_info:
            # 学校
            item[‘school‘] = school_info[0]
            # 专业
            item[‘majors‘] = school_info[1].strip()
        else:
            item[‘school‘] = ‘‘
            item[‘majors‘] = ‘‘
        # 公司职位信息
        company_info = profile_head.css(‘.profile__company::text‘).extract()
        if company_info:
            # 公司
            item[‘company‘] = company_info[0]
            # 职位
            item[‘job‘] = company_info[1].strip()
        else:
            item[‘company‘] = ‘‘
            item[‘job‘] = ‘‘
        # 个人博客
        item[‘blog‘] = profile_head.css(‘a[class*=other-item-link]::attr(href)‘).extract_first()

        # 统计面板模块
        profile_active = response.xpath("//div[@class=‘col-md-2‘]")
        # 关注人数
        item[‘following‘] = profile_active.css(‘div[class*=info] a > .h5::text‘).re(r‘\d+‘)[0]
        # 粉丝人数
        item[‘fans‘] = profile_active.css(‘div[class*=info] a > .h5::text‘).re(r‘\d+‘)[1]
        # 回答问题数
        item[‘answers‘] = profile_active.css(‘a[href*=answer] .count::text‘).re_first(r‘\d+‘)
        # 提问数
        item[‘questions‘] = profile_active.css(‘a[href*=questions] .count::text‘).re_first(r‘\d+‘)
        # 文章数
        item[‘articles‘] = profile_active.css(‘a[href*=articles] .count::text‘).re_first(r‘\d+‘)
        # 讲座数
        item[‘lives‘] = profile_active.css(‘a[href*=lives] .count::text‘).re_first(r‘\d+‘)
        # 徽章数
        item[‘badges‘] = profile_active.css(‘a[href*=badges] .count::text‘).re_first(r‘\d+‘)
        # 徽章详细页面地址
        badge_url = profile_active.css(‘a[href*=badges]::attr(href)‘).extract_first()

        # 技能面板模块
        profile_skill = response.xpath("//div[@class=‘col-md-3‘]")
        # 技能标签列表
        item[‘skills‘] = profile_skill.css(‘.tag::text‘).re(r‘\w+‘)
        # 获得的点赞数
        item[‘like‘] = profile_skill.css(‘.authlist‘).re_first(r‘获得 (\d+) 次点赞‘)
        # 注册日期
        item[‘register_date‘] = profile_skill.css(‘.profile__skill--other p::text‘).extract_first()
        # if register_time:
        #     item[‘register_date‘] = ‘‘.join(re.findall(r‘\d+‘,register_time))
        # else:
        #     item[‘register_date‘] = ‘‘

        # 产出数据模块
        profile_work = response.xpath("//div[@class=‘col-md-7‘]")
        # 回答获得的最高分
        item[‘answers_top_score‘] = profile_work.css(‘#navAnswer .label::text‘).re_first(r‘\d+‘)
        # 最高分回答对应的问题的标题
        item[‘answers_top_title‘] = profile_work.css(‘#navAnswer div[class*=title-warp] > a::text‘).extract_first()
        # 最高分回答对应的问题的url
        answer_url = profile_work.css(‘#navAnswer div[class*=title-warp] > a::attr(href)‘).extract_first()

        # 将需要继续跟进抓取数据的url与item作为参数传递给相应方法继续抓取数据
        request = scrapy.Request(
            # 问题详细页url
            url=response.urljoin(answer_url),
            meta={
            # item需要传递
            ‘item‘:item,
            # 徽章的url
            ‘badge_url‘:response.urljoin(badge_url)},
            # 调用parse_ansser继续处理
            callback=self.parse_answer)
        yield request

    def parse_answer(self,response):
        # 取出传递的item
        item = response.meta[‘item‘]
        # 取出传递的徽章详细页url
        badge_url = response.meta[‘badge_url‘]
        # 问题标签列表
        item[‘answers_top_tags‘] = response.css(‘.question__title--tag .tag::text‘).re(r‘\w+‘)
        # 先获取组成问题内容的字符串列表
        question_content = response.css(‘.widget-question__item p‘).re(r‘>(.*?)<‘)
        # 拼接后传入item
        item[‘answers_top_question‘] = ‘‘.join(question_content)
        # 先获取组成答案的字符串列表
        answer_content = response.css(‘.qa-answer > article .answer‘).re(r‘>(.*?)<‘)
        # 拼接后传入item
        item[‘answers_top_content‘] = ‘‘.join(answer_content)

        # 问题页面内容抓取后继续抓取徽章页内容,并将更新后的item继续传递
        request = scrapy.Request(url=badge_url,
                                 meta={‘item‘:item},
                                 callback=self.parse_badge)
        yield request

    def parse_badge(self,response):
        item = response.meta[‘item‘]
        badge_name = response.css(‘span.badge span::text‘).extract()
        badge_count = response.css(‘span[class*=badges-count]::text‘).re(r‘\d+‘)
        name_count = {}
        for i in range(len(badge_count)):
            name_count[badge_name[i]] = badge_count[i]
        item[‘badges‘] = name_count
        yield item

middlewars.py

# -*- 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 random
import re
import datetime
import scrapy
import logging
import time
from scrapy.conf import settings
from pymongo import MongoClient
from scrapy.downloadermiddlewares.httpproxy import HttpProxyMiddleware
import pymongo
logger = logging.getLogger(__name__)


class SegmentfaultSpiderMiddleware(object):
    """
    处理Item中保存的三种类型注册日期数据:
    1. 注册于 2015年12月12日
    2. 注册于 3 天前
    3. 注册于 5 小时前
    """

    def process_spider_output(self,response,result,spider):

        """
        输出response时调用此方法处理item中register_date
        :param response:
        :param result: 包含item
        :param spider:
        :return:处理过注册日期的item
        """
        for item in result:
            # 判断获取的数据是否是scrapy.item类型
            if isinstance(item,scrapy.Item):
                # 获取当前时间
                now = datetime.datetime.now()
                register_date = item[‘register_date‘]
                logger.info("获取注册日志格式为{}".format(register_date))
                # 提取注册日期字符串,如‘注册于2015年12月12日‘ => ‘20151212‘
                day = ‘‘.join(re.findall(r‘\d+‘,register_date))
                # 如果提取数字字符串长度大于4位,则为‘注册于2015年12月12日‘形式
                if len(day) > 4:
                    date = day
                # 如果‘时’在提取的字符串中,则为‘注册于8小时前‘形式
                elif ‘时‘ in register_date:
                    d = now - datetime.timedelta(hours=int(day))
                    date = d.strftime("%Y%m%d")
                # 最后一种情况就是‘注册于3天前‘形式
                else:
                    d = now - datetime.timedelta(days=int(day))
                    date = d.strftime("%Y%m%d")

                # 更新register_date值
                item[‘register_date‘] = date
            yield item


class SegmentfaultHttpProxyMiddleware(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 __init__(self):
        self.proxy_list = settings[‘PROXY_LIST‘]

    def process_request(self, request, spider):
        proxy = random.choice(self.proxy_list)
        logger.info(‘使用代理:{}‘.format(proxy))
        request.meta[‘proxy‘] = proxy


class SegmentfaultUserAgentMiddleware(object):
    def __init__(self):
        self.useragent_list = settings[‘USER_AGENT_LIST‘]

    def process_request(self,request,spider):
        user_agent = random.choice(self.useragent_list)

        # logger.info(‘使用的USE USER-AGENT:{}‘.format(user_agent))
        request.headers[‘User-Agent‘] = user_agent



class SegmentfaultCookiesMiddleware(object):
    client = MongoClient(settings[‘MONGO_URI‘])
    db = client[settings[‘MONGO_DB‘]]
    collection = db[‘cookies‘]

    def get_cookies(self):
        """
        随机获取cookies
        :return:
        """
        cookies = random.choice([cookie for cookie in self.collection.find()])
        # 将不需要的"_id"与"_gat"参数删除
        cookies.pop(‘_id‘)
        cookies.pop(‘_gat‘)
        # 将"Hm_lpvt_e23800c454aa573c0ccb16b52665ac26"填充当前时间
        cookies[‘Hm_lpvt_e23800c454aa573c0ccb16b52665ac26‘] = str(int(time.time()))
        return cookies

    def remove_cookies(self,cookies):
        """
        删除已失效的cookies
        :param cookies:
        :return:
        """
        # 随机获取cookies中的一对键值,返回结果是一个元祖
        i = cookies.popitem()
        # 删除cookies
        try:
            logger.info("删除cookies{}".format(cookies))
            self.collection.remove({i[0]:i[1]})
        except Exception as e:
            logger.info("No this cookies:{}".format(cookies))

    def process_request(self,request,spider):
        """
        为每一个request添加一个cookie
        :param request:
        :param spider:
        :return:
        """
        cookies = self.get_cookies()
        request.cookies = cookies

    def process_response(self,request,response,spider):
        """
        对于登录失效的情况,可能会重定向到登录页面,这时添加新的cookies继续,将请求放回调度器
        :param request:
        :param response:
        :param spider:
        :return:
        """
        if response.status in [301,302]:
            logger.info("Redirect response:{}".format(response))
            redirect_url = response.headers[‘location‘]
            if b‘/user/login‘ in redirect_url:
                logger.info("Cookies失效")

                # 请求失败,重新获取一个cookie,添加到request,并停止后续中间件处理此request,将此request放入调度器
                new_cookie = self.get_cookies()
                logger.info("获取新cookie:{}".format(new_cookie))
                # 删除旧cookies
                self.remove_cookies(request.cookies)
                request.cookies = new_cookie
            return request
        #
        return response

run.py

from scrapy import cmdline
# from segmentfault.get_cookies import GetCookies
from get_cookies import GetCookies

if __name__ == ‘__main__‘:
    cookies = GetCookies()
    cookies.save()
    name = ‘userinfo‘
    ""
    cmd = ‘scrapy crawl {}‘.format(name)
    cmdline.execute(cmd.split())

Scrapy项目实战:爬取某社区用户详情

标签:each   current   make   models   open   cep   param   edr   ack   

原文地址:https://www.cnblogs.com/hankleo/p/12994207.html

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