Scrapy爬取猫眼电影并存入MongoDB数据库

之前入门了Scrapy，用Scrapy框架爬取了豆瓣电影TOP250，最近打算学习下scrapy-redis分布式爬虫，学习之前再重新温故下Scrapy，这个总结我缩写了很多内容，很多介绍可以看下我之前写的豆瓣movie

实战应用

打开CMD输入

scrapy startproject maoyan

C:.
│  scrapy.cfg
│
└─maoyan
    │  items.py
    │  middlewares.py
    │  pipelines.py
    │  settings.py
    │  __init__.py
    │
    └─spiders
            __init__.py

编辑 item.py

import scrapy


class MaoyanItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    movie_name = scrapy.Field()
    movie_ename = scrapy.Field()
    movie_type = scrapy.Field()
    movie_publish = scrapy.Field()
    movie_time = scrapy.Field()
    movie_star = scrapy.Field()
    movie_total_price = scrapy.Field()
    pass

• 首先，引入Scrapy
• 接着，创建一个类，继承自scrapy.item,这个是用来储存要爬下来的数据的存放容器，类似orm的写法
• 我们要记录的是：电影的名字、电影的评分、电影的上映时间、电影类型、电影英文名

获取网页数据

网页数据使用Xpath来索取元素非常方便，附上W3SCHOOL xpath学习 接下来，我们定义一下url的爬取规则

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http://maoyan.com/films?offset=30
用正则表达式定义下一页链接
r'http://maoyan.com/films?offset=\d+'

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我们真正要抓取电影详情页的是这个链接 http://maoyan.com/films/1170264

正则定义链接
r'http://maoyan.com/films/\d+'

好了，到这一步编辑spider

from scrapy.spiders import Rule, CrawlSpider
from scrapy.selector import Selector
from scrapy.linkextractors import LinkExtractor
from maoyan.items import MaoyanItem


class MaoyanmovieSpider(CrawlSpider):
    name = 'my'
    # allowed_domains = ['http://maoyan.com/']
    start_urls = ['http://maoyan.com/films']
    rules = (
        Rule(LinkExtractor(allow=(r'http://maoyan.com/films\?offset=\d+'))),
        Rule(LinkExtractor(allow=(r'http://maoyan.com/films/\d+')), callback='parse_item')
    )

    def parse_item(self, response):
        # print(response.body)
        sel = Selector(response)
        movie_name = sel.xpath('/html/body/div[3]/div/div[2]/div[1]/h3/text()').extract()
        movie_ename = sel.xpath('/html/body/div[3]/div/div[2]/div[1]/div/text()').extract()
        movie_type = sel.xpath('/html/body/div[3]/div/div[2]/div[1]/ul/li[1]/text()').extract()
        movie_publish = sel.xpath('/html/body/div[3]/div/div[2]/div[1]/ul/li[2]/text()').extract()
        movie_time = sel.xpath('/html/body/div[3]/div/div[2]/div[1]/ul/li[3]/text()').extract()
        movie_star = sel.xpath('/html/body/div[3]/div/div[2]/div[3]/div[1]/div/span/span/text()').extract()
        # movie_total_price = sel.xpath('/html/body/div[3]/div/div[2]/div[3]/div[2]/div/span[1]/text()').extract()
        # movie_introd = sel.xpath('//*[@id="app"]/div/div[1]/div/div[2]/div[1]/div[1]/div[2]/span/text()').extract()
        # print(movie_name)
        # print(movie_ename)
        # print(movie_type)
        # print(movie_publish)
        # print(movie_time)
        # print(movie_star)
        # print(movie_total_price)

        item = MaoyanItem()
        item['movie_name'] = movie_name
        item['movie_ename'] = movie_ename
        item['movie_type'] = movie_type
        item['movie_publish'] = movie_publish
        item['movie_time'] = movie_time
        item['movie_star'] = movie_star
        # item['movie_total_price'] = movie_total_price
        # item['movie_introd'] = movie_introd

        yield item

spider写完后我们要将数据存进MongoDB数据库内，编辑pipeline.py

import pymongo
from scrapy.conf import settings
from scrapy.exceptions import DropItem
from scrapy import log



class MongoDBPipeline(object):
    def __init__(self):
        client = pymongo.MongoClient(settings['MONGODB_SERVER'], settings['MONGODB_PORT'])
        db = client[settings['MONGODB_DB']]
        self.collection = db[settings['MONGODB_COLLECTION']]


    def process_item(self, item, spider):
        # item:  (Item 对象) – 被爬取的item
        # (Spider 对象) – 爬取该item的spider
        # 去重，删除重复的数据
        valid = True
        for data in item:
            if not data:
                valid = False
                raise DropItem('Missing %s of blogpost from %s' % (data, item['url']))
        if valid:
            movies = [{
                'movie_name': item['movie_name'],
                'movie_ename': item['movie_ename'],
                'movie_type': item['movie_type'],
                'movie_publish': item['movie_publish'],
                'movie_time': item['movie_time'],
                'movie_star': item['movie_star']
            }]
            # 插入数据库集合中
            self.collection.insert(movies)
            log.msg('Item wrote to MongoDB database %s/%s' % (settings['MONGODB_DB'], settings['MONGODB_COLLECTION']),
                    level=log.DEBUG, spider=spider)
        return item

配置文件
打开setting.py

BOT_NAME = 'maoyan'

SPIDER_MODULES = ['maoyan.spiders']
NEWSPIDER_MODULE = 'maoyan.spiders'
ROBOTSTXT_OBEY = False
COOKIES_ENABLED = True
DOWNLOAD_DELAY = 3
LOG_LEVEL = 'DEBUG'
RANDOMIZE_DOWNLOAD_DELAY = True
# 关闭重定向
REDIRECT_ENABLED = False
# 返回302时,按正常返回对待,可以正常写入cookie
HTTPERROR_ALLOWED_CODES = [302,]

ITEM_PIPELINES = {
    'maoyan.pipelines.MongoDBPipeline': 300,
}

MONGODB_SERVER = 'localhost'
MONGODB_PORT = 27017
MONGODB_DB = 'maoyan'
MONGODB_COLLECTION = 'movies'

好了，现在开启爬虫

scrapy crawl my

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写这个爬虫应该会遇到302重定向或者被网站发现是机器人操作，建议延长delay时间，不过爬取效率会非常低！！总共有23110页，每页有30条数据，总共693300条数据，就算不被ban掉，那得爬到猴年马月............................................................
不说了，赶紧学习分布式爬虫！！！！

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欢迎访问博客Treehl的博客
完整代码GitHub
简书
最后放一个爬虫集合，是我最近学习Python写的，喜欢的亲！给个Star呗！！！
SpiderList