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'])

巴特西

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

2.mongodb持久化储存以及from_crawl的使用

二.补充一个小技巧

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