今天的主要内容是爬取豆瓣电影短评,看一下网友是怎么评价最近的电影的,方便我们以后的分析,以以下三部电影:二十二,战狼,三生三世十里桃花为例。
由于豆瓣短评网页比较简单,且不存在动态加载的内容,我们下面就直接上代码。有一点需要注意的是,豆瓣短评的前几页不需要登录就可以看,但是后面的内容是是需要我们登录才能查看的,因此我们需要添加自己的cookie。
我们新创建一个项目,就叫comment吧。
项目代码
-
items.py
import scrapy
class CommentItem(scrapy.Item):
comments = scrapy.Field()
可以看到,我们只需要评价内容,因此我们的item就非常简单。
-
spider.py
from scrapy import Request,Spider
from lxml import etree
from comment.items import CommentItem
#你想爬取哪一部电影,将其余的两部注释即可。
class CommentSpider(Spider):
'''
这个是三生三世十里桃花
'''
name = 'comment'
def start_requests(self):
templateurl = 'https://movie.douban.com/subject/25823277/comments?start={}&limit=20&sort=new_score&status=P'
for i in range(3201):
url = templateurl.format(str(i * 20))
yield Request(url=url, callback=self.parse)
def parse(self, response):
selector = etree.HTML(response.text)
item = SanshengItem()
item['comments'] = selector.xpath('//div[@class="comment"]/p/text()')
yield item
# class CommentSpider(Spider):
# '''
# 这个是二十二
# '''
# name = 'comment'
#
# def start_requests(self):
# templateurl = 'https://movie.douban.com/subject/26430107/comments?start={}&limit=20&sort=new_score&status=P'
# for i in range(1601):
# url = templateurl.format(str(i * 20))
# yield Request(url=url, callback=self.parse)
#
# def parse(self, response):
# selector = etree.HTML(response.text)
# item = SanshengItem()
# item['comments'] = selector.xpath('//div[@class="comment"]/p/text()')
# yield item
#
# class CommentSpider(Spider):
# '''
# 这个是战狼
# '''
# name = 'comment'
#
# def start_requests(self):
# templateurl = 'https://movie.douban.com/subject/26363254/comments?start={}&limit=20&sort=new_score&status=P'
# for i in range(9001):
# url = templateurl.format(str(i * 20))
# yield Request(url=url, callback=self.parse)
#
# def parse(self, response):
# selector = etree.HTML(response.text)
# item = SanshengItem()
# item['comments'] = selector.xpath('//div[@class="comment"]/p/text()')
# yield item
-
pipelines.py
import pymongo
class MongoPipeline(object):
collection = 'sansheng' # 三生的数据表
# collection = 'ershier' # 二十二的数据表
# collection = 'zhanlang' # 战狼的数据表
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_RUI'),
mongo_db = crawler.settings.get('MONGO_DB')
)
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):
table = self.db[self.collection]
for com in item['comments']:
data = dict()
data['comment'] = com.strip().replace("\n", "")
table.insert_one(data)
return item
-
middlewares.py
import scrapy
from scrapy.downloadermiddlewares.useragent import UserAgentMiddleware
import random
class MyUseragentMiddleware(UserAgentMiddleware):
'''
设置User-Agent
'''
def __init__(self, user_agent):
self.user_agent = user_agent
@classmethod
def from_crawler(cls, crawler):
return cls(
user_agent=crawler.settings.get('USER_AGENTS')
)
def process_request(self, request, spider):
agent = random.choice(self.user_agent)
request.headers['User-Agent'] = agent
-
settings.py
BOT_NAME = 'comment'
SPIDER_MODULES = ['comment.spiders']
NEWSPIDER_MODULE = 'comment.spiders'
ROBOTSTXT_OBEY = False
DOWNLOAD_DELAY = 2
COOKIES_ENABLED = False
DEFAULT_REQUEST_HEADERS = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Language': '-CN,zh;q=0.8,en-US;q=0.5,en;q=0.3',
'Cookie':'浏览器复制粘贴你的cookie'
}
DOWNLOADER_MIDDLEWARES = {
'comment.middlewares.MyUseragentMiddleware': 400,
}
USER_AGENTS = [
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; AcooBrowser; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0; Acoo Browser; SLCC1; .NET CLR 2.0.50727; Media Center PC 5.0; .NET CLR 3.0.04506)",
"Mozilla/4.0 (compatible; MSIE 7.0; AOL 9.5; AOLBuild 4337.35; Windows NT 5.1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/5.0 (Windows; U; MSIE 9.0; Windows NT 9.0; en-US)",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 2.0.50727; Media Center PC 6.0)",
"Mozilla/5.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 1.0.3705; .NET CLR 1.1.4322)",
"Mozilla/4.0 (compatible; MSIE 7.0b; Windows NT 5.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; InfoPath.2; .NET CLR 3.0.04506.30)",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN) AppleWebKit/523.15 (KHTML, like Gecko, Safari/419.3) Arora/0.3 (Change: 287 c9dfb30)",
"Mozilla/5.0 (X11; U; Linux; en-US) AppleWebKit/527+ (KHTML, like Gecko, Safari/419.3) Arora/0.6",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.2pre) Gecko/20070215 K-Ninja/2.1.1",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9) Gecko/20080705 Firefox/3.0 Kapiko/3.0",
"Mozilla/5.0 (X11; Linux i686; U;) Gecko/20070322 Kazehakase/0.4.5",
"Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.0.8) Gecko Fedora/1.9.0.8-1.fc10 Kazehakase/0.5.6",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3) AppleWebKit/535.20 (KHTML, like Gecko) Chrome/19.0.1036.7 Safari/535.20",
"Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; fr) Presto/2.9.168 Version/11.52",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.11 TaoBrowser/2.0 Safari/536.11",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBBROWSER",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E; LBBROWSER)",
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E; LBBROWSER)",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.84 Safari/535.11 LBBROWSER",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E)",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E; QQBrowser/7.0.3698.400)",
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Trident/4.0; SV1; QQDownload 732; .NET4.0C; .NET4.0E; 360SE)",
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E)",
"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.89 Safari/537.1",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.89 Safari/537.1",
"Mozilla/5.0 (iPad; U; CPU OS 4_2_1 like Mac OS X; zh-cn) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8C148 Safari/6533.18.5",
"Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:2.0b13pre) Gecko/20110307 Firefox/4.0b13pre",
"Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:16.0) Gecko/20100101 Firefox/16.0",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11",
"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 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36",
]
ITEM_PIPELINES = {
'comment.pipelines.MongoPipeline': 300,
}
MONGO_URI = 'mongodb://localhost:27017'
MONGO_DB = "douban"
注意:
请把COOKIES_ENABLED
设置为 False,你可能觉得奇怪,为什么我们使用了cookie却需要把它设置为False,原因在于,我们直接把cookie放在了请求头里面,但是scrapy默认自己拥有一套处理cookie的中间件,当你把它设置为True的时候,两者会产生影响,从而请求失败,你可以自己尝试一下。那如果我执意要把他设置为True呢,难道就不能解决了么?当然是可以的,但是我们今天就不在深入的讨论这个问题,以后可以单独解释。
我们这里抓取评论数据是为了之后的分析所用。
你可以去github下载以上的代码和相应的评论数据。
github地址: https://github.com/cnkai/comment.git
声明:本文仅供学习交流所用。
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