scrapy——图片数据爬取之 ImagesPipeline

2024-02-06 21:53:16

图片数据爬取之ImagesPipeline
- 基于scrapy爬取字符串类型的数据和爬取图片类型的数据的区别？
  - 字符串：只需要基于xpath进行解析且提交管道进行持久化存储。
  - 图片：xpath解析出图片src的属性值。单独的对图片地址发起请求获取图片二进制类型的数据
- xpath 提供了 imagespipeline 帮助我们处理图片的src，只需要将img的src的属性值进行解析，提交到管道，管道就会对图片的src属性值进行请求发送获取图片的二进制类型的数据，且还会帮助我们进行持久化存储
- 需求：爬取站长素材中的高清图片
- 使用流程：
  - 数据解析（图片的地址）
  - 将存储图片的item提交给指定的管道类
  - 在管道文件中自定制一个基于ImagesPipeLine的一个管道类，需要重写三个方法：
    - get_media_request()
    - file_path()
    - item_completed()
  - 在配置文件中（settings）：
    - 指定图片存储的目录：IMAGES_STORE = ‘./imgs’
    - 指定开启的管道：（基于自定制的管道类）

setting.py

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

# Scrapy settings for imgsPro 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 = 'imgsPro'

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

LOG_LEVEL = 'ERROR'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 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 = {
#    'imgsPro.middlewares.ImgsproSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'imgsPro.middlewares.ImgsproDownloaderMiddleware': 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 = {
   'imgsPro.pipelines.imgsPipeLine': 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'

#指定图片存储的目录
IMAGES_STORE = './imgs_lvxin'

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


# class ImgsproPipeline(object):
#     def process_item(self, item, spider):
#         return item
from scrapy.pipelines.images import ImagesPipeline
import scrapy
class imgsPipeLine(ImagesPipeline):

    #就是可以根据图片地址进行图片数据的请求
    def get_media_requests(self, item, info):

        yield scrapy.Request(item['src'])

    #指定图片存储的路径
    def file_path(self, request, response=None, info=None):
        imgName = request.url.split('/')[-1]
        return imgName

    def item_completed(self, results, item, info):
        return item #返回给下一个即将被执行的管道类

item.py

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

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html

import scrapy


class ImgsproItem(scrapy.Item):
    # define the fields for your item here like:
    src = scrapy.Field()
    # pass

img.py

# -*- coding: utf-8 -*-
import scrapy
from imgsPro.items import ImgsproItem

class ImgSpider(scrapy.Spider):
    name = 'img'
    # allowed_domains = ['www.xxx.com']
    start_urls = ['http://sc.chinaz.com/tupian/']

    def parse(self, response):
        div_list = response.xpath('//div[@id="container"]/div')
        for div in div_list:
            #注意：使用伪属性
            # 这里涉及到一个图片懒加载的反爬技术，即只有那些在网页的可视化界面中的图片的链接
            # 放在src属性值当中，而那些暂时还没有进入可视化界面的图片的链接都存放在伪属性src2
            # 中，我们使用scrapy框架爬取图片时，是没有任何可视化界面的的，所以所有的图片都以
            # 伪属性的形式存放在src2当中，因此在这里的xpath直接使用src2就可以了
            src = "http:" + div.xpath('./div/a/img/@src2').extract_first()

            item = ImgsproItem()
            item['src'] = src

            yield item

在 img.py 的parse（解析）方法中，这里涉及到一个图片懒加载的反爬技术，即只有那些在网页的可视化界面中的图片的链接放在src属性值当中，而那些暂时还没有进入可视化界面的图片的链接都存放在伪属性src2中，我们使用scrapy框架爬取图片时，是没有任何可视化界面的，所以所有的图片都以伪属性的形式存放在src2当中，因此在这里的xpath直接使用src2就可以了。

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