scrapy框架的另一种分页处理以及mongodb的持久化储存以及from_crawler类方法的使用

一.scrapy框架处理

　　1.分页处理

　　　　以爬取亚马逊为例

　　　　爬虫文件.py

# -*- coding: utf-8 -*-
import scrapy
from Amazon.items import AmazonItem

class AmazonSpider(scrapy.Spider):
    name = 'amazon'
    allowed_domains = ['www.amazon.cn']
    start_urls = ['www.amazon.cn']

    def start_requests(self):
        # 重写父类方法,拿到商品搜索页
        url = 'https://www.amazon.cn/s/ref=nb_sb_noss?__mk_zh_CN=亚马逊网站&url=search-alias%3Daps&field-keywords=iphone+-xs&rh=i%3Aaps%2Ck%3Aiphone+-xs&ajr=0'
        yield scrapy.Request(url=url, callback=self.parse)

    def parse(self, response):
        # 解析每一个商品的url
        links = response.xpath('//*[contains(@id,"result_")]/div/div[3]/div[1]/a/@href').extract()
        # 同时拿到下一页的连接
        next_page_url = response.xpath('//a[@id="pagnNextLink"]/@href').extract_first()
        print('>>>>>>>>>>>>>', next_page_url)
        # 再对这些每一个商品的url进行请求
        for link in links:
            yield scrapy.Request(url=link, callback=self.parse_detail)

        #分页处理
        # 把所有的商品详情遍历完了之后,再判断是否有下一页,有下一页就继续对下一页发起请求
        if next_page_url:
            scrapy.Request(url=next_page_url, callback=self.parse)

    def parse_detail(self, response):
        #每个商品的详情页解析出我们要的数据
        title = response.xpath('//*[@id="productTitle"]/text()').extract_first().strip()
        price = (response.xpath("//*[@id='priceblock_ourprice']/text()") or response.xpath(
            "//*[@id='priceblock_saleprice']/text()")).extract_first().strip()
        deliver = response.xpath('//*[@id="ddmMerchantMessage"]/*[1]/text()').extract_first().strip()

        #把数据装到容器里面
        item=AmazonItem()
        item['title']=title
        item['price']=price
        item['deliver']=deliver
        #记得返回,否则管道接不到
        yield item

　　2.mongodb持久化储存以及from_crawl的使用

　　　　pipelines.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 AmazonPipeline(object):

    @classmethod
    def from_crawler(cls, crawler):
        """
        Scrapy会先通过getattr判断我们是否自定义了from_crawler,有则调它来完
        成实例化,早于__init__方法执行
　　　　 自己要的参数要去settings.py文件配置　　　　
        """
        HOST = crawler.settings.get('HOST')
        PORT = crawler.settings.get('PORT')
        USER = crawler.settings.get('USER')
        PWD = crawler.settings.get('PWD')
        DB = crawler.settings.get('DB')
        TABLE = crawler.settings.get('TABLE')
        return cls(HOST, PORT, USER, PWD, DB, TABLE)

    def __init__(self,host,port,user,pwd,db,table):
        self.host=host
        self.port=port
        self.user=user
        self.pwd=pwd
        self.db=db
        self.table=table

    def open_spider(self,spider):
        #程序运行时执行一次
        self.client=pymongo.MongoClient(host=self.host,port=self.port)

    def process_item(self, item, spider):
        dic_item=dict(item)
        if dic_item:
            self.client[self.db][self.table].save(dic_item)
        return item
    def close_spider(self,spider):
        #程序关闭时候执行一次
        self.client.close()

　　settings.py

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

# Scrapy settings for Amazon 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 = 'Amazon'

SPIDER_MODULES = ['Amazon.spiders']
NEWSPIDER_MODULE = 'Amazon.spiders'

# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.26 Safari/537.36'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32

# 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 = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

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

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

# 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 = {
#    'Amazon.middlewares.AmazonSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
   'Amazon.middlewares.AmazonDownloaderMiddleware': 543,
}

# 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 = {
   'Amazon.pipelines.AmazonPipeline': 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'

###MONGODB的配置
HOST='127.0.0.1'
PORT=27017
USER='root'
PWD=''
DB='amazon'
TABLE='goods'

二.补充一个小技巧

　　一直在命令行启动爬虫文件就很累了,可以这么做

　　在爬虫项目的根目录直接写一个.py文件,加入如下内容

#第一个,第二不变,第三个是爬虫文件名称,也可以加第四个,--nolog不达意你日志
from scrapy.cmdline import execute
execute(['scrapy', 'crawl', 'amazon'])