Scrapy实战：爬取http://quotes.toscrape.com网站数据

需要学习的地方：

1.Scrapy框架流程梳理，各文件的用途等

2.在Scrapy框架中使用MongoDB数据库存储数据

3.提取下一页链接，回调自身函数再次获取数据

重点：从当前页获取下一页的链接，传给函数自身继续发起请求

        next = response.css('.pager .next a::attr(href)').extract_first() # 获取下一页的相对链接
        url = response.urljoin(next) # 生成完整的下一页链接
        yield scrapy.Request(url=url, callback=self.parse) # 把下一页的链接回调给自身再次请求

站点:http://quotes.toscrape.com

该站点网页结构比较简单，需要的数据都在div标签中

操作步骤：

1.创建项目

# scrapy startproject quotetutorial

此时目录结构如下：

2.生成爬虫文件

# cd quotetutorial
# scrapy genspider quotes quotes.toscrape.com # 若是有多个爬虫多次操作该命令即可

3.编辑items.py文件，获取需要输出的数据

import scrapy


class QuoteItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    text = scrapy.Field()
    author = scrapy.Field()
    tags = scrapy.Field()

4.编辑quotes.py文件，爬取网站数据

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

from quotetutorial.items import QuoteItem


class QuotesSpider(scrapy.Spider):
    name = 'quotes'
    allowed_domains = ['quotes.toscrape.com']
    start_urls = ['http://quotes.toscrape.com/']

    def parse(self, response):
        # print(response.status) # 200
        quotes = response.css('.quote')
        for quote in quotes:
            item = QuoteItem()

            text = quote.css('.text::text').extract_first()
            author = quote.css('.author::text').extract_first()
            tags = quote.css('.tags .tag::text').extract()

            item['text'] = text
            item['author'] = author
            item['tags'] = tags
            yield item

        next = response.css('.pager .next a::attr(href)').extract_first()  # 获取下一页的相对链接
        url = response.urljoin(next)  # 生成完整的下一页链接
        yield scrapy.Request(url=url, callback=self.parse)  # 把下一页的链接回调给自身再次请求

5.编写pipelines.py文件，进一步处理item数据，保存到mongodb数据库

# -*- 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

# 使用的话需要在settings文件中设置


import pymongo as pymongo
from scrapy.exceptions import DropItem


class TextPipeline(object):
    """对输出的item进行进一步的处理"""

    def __init__(self):
        self.limit = 50

    def process_item(self, item, spider):
        if item['text']:
            if len(item['text']) > self.limit:
                item['text'] = item['text'][0:self.limit].rstrip() + '......'
            return item
        else:
            return DropItem('Missing Text!')


class MongoPipeline(object):
    """把输出的item保存到MongoDB数据库"""

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

    @classmethod
    def from_crawler(cls, crawler):
        """从settings文件获取配置信息"""
        return cls(
            mongo_url=crawler.settings.get('MONGO_URI'),
            mongo_db=crawler.settings.get('MONGO_DB')
        )

    def open_spider(self, spider):
        """初始化mongodb"""
        self.client = pymongo.MongoClient(self.mongo_uri)
        self.db = self.client[self.mongo_db]  # 为啥用[],而不是()

    def process_item(self, item, spider):
        name = item.__class__.__name__  # 获取item的名称用作表名,也就是QuoteItem
        self.db[name].insert(dict(item))  # 为啥要用dict(item)
        return item

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

6.编辑配置文件，增加mongodb数据库参数，以及使用的pipeline管道参数

ITEM_PIPELINES = {
   # 'quotetutorial.pipelines.TextPipeline': 300,
   'quotetutorial.pipelines.MongoPipeline': 400,
}

MONGO_URI = 'localhost'
MONGO_DB = 'quotestutorial'

7.执行程序

# scrapy crawl quotes

8.保存到文件

# scrapy crawl quotes -o quotes.json # 保存成json文件
# scrapy crawl quotes -o quotes.csv # 保存成csv文件
# scrapy crawl quotes -o quotes.xml # 保存成xml文件
# scrapy crawl quotes -o quotes.jl # 保存成jl文件
# scrapy crawl quotes -o quotes.pickle # 保存成pickle文件
# scrapy crawl quotes -o quotes.marshal # 保存成marshal文件
# scrapy crawl quotes -o ftp://user:password@ftp.example.com/path/quotes.csv # 生成csv文件保存到远程FTP上

效果：

源码下载地址：https://files.cnblogs.com/files/sanduzxcvbnm/quotetutorial.7z

来源：oschina

链接：https://my.oschina.net/u/4305692/blog/3670517

标签

mongodb

def

crawl

Crawler