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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

时间:2019-03-07 23:51:28      阅读:303      评论:0      收藏:0      [点我收藏+]

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

技术分享图片
# -*- 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
View Code

 

 

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])

 

  

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

原文:https://www.cnblogs.com/tjp40922/p/10493354.html

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