python爬虫Scrapy框架:媒体管道原理学习分析-巨人网络通讯

python爬虫Scrapy框架:媒体管道原理学习分析

一、媒体管道

1.1、媒体管道的特性

媒体管道实现了以下特性:

避免重新下载最近下载的媒体
指定存储位置（文件系统目录，Amazon S3 bucket，谷歌云存储bucket）

图像管道具有一些额外的图像处理功能:

将所有下载的图片转换为通用格式(JPG)和模式(RGB)
生成缩略图
检查图像的宽度/高度，进行最小尺寸过滤

1.2、媒体管道的设置

ITEM_PIPELINES = {'scrapy.pipelines.images.ImagesPipeline': 120}      启用
FILES_STORE = '/path/to/valid/dir'		   文件管道存放位置
IMAGES_STORE = '/path/to/valid/dir'		  图片管道存放位置
FILES_URLS_FIELD = 'field_name_for_your_files_urls'    自定义文件url字段
FILES_RESULT_FIELD = 'field_name_for_your_processed_files'   自定义结果字段
IMAGES_URLS_FIELD = 'field_name_for_your_images_urls'         自定义图片url字段
IMAGES_RESULT_FIELD = 'field_name_for_your_processed_images'      结果字段
FILES_EXPIRES = 90   文件过期时间   默认90天
IMAGES_EXPIRES = 90    图片过期时间   默认90天
IMAGES_THUMBS = {'small': (50, 50), 'big':(270, 270)}     缩略图尺寸
IMAGES_MIN_HEIGHT = 110     过滤最小高度
IMAGES_MIN_WIDTH = 110      过滤最小宽度
MEDIA_ALLOW_REDIRECTS = True    是否重定向

二、ImagesPipeline类简介

#解析settings里的配置字段
def __init__(self, store_uri, download_func=None, settings=None)
#图片下载
def image_downloaded(self, response, request, info)
#图片获取   图片大小的过滤  #缩略图的生成
def get_images(self, response, request, info)
#转化图片格式
def convert_image(self, image, size=None)
#生成媒体请求  可重写
def get_media_requests(self, item, info)
	return [Request(x) for x in item.get(self.images_urls_field, [])] #得到图片url  变成请求  发给引擎
#此方法获取文件名  进行改写
def item_completed(self, results, item, info)
#文件路径 
def file_path(self, request, response=None, info=None)
#缩略图的存储路径
def thumb_path(self, request, thumb_id, response=None, info=None):

三、小案例：使用图片管道爬取百度图片

（当然不使用图片管道的话也是可以爬取百度图片的，但这还需要我们去分析网页的代码，还是有点麻烦，使用图片管道就可以省去这个步骤了）

3.1、spider文件

注意：由于需要添加所有的请求头，所以我们要重写start_requests函数

import re
import scrapy
from ..items import DbimgItem
class DbSpider(scrapy.Spider):
    name = 'db'
    # allowed_domains = ['xxx.com']
    start_urls = ['https://image.baidu.com/search/index?tn=baiduimageipn=rct=201326592cl=2lm=-1st=-1fm=indexfr=hs=0xthttps=111110sf=1fmq=pv=ic=0nc=1z=se=1showtab=0fb=0width=height=face=0istype=2ie=utf-8word=%E7%8B%97oq=%E7%8B%97rsp=-1']
    def start_requests(self):  #因为需要添加所有的请求头，所以我们要重写start_requests函数
        # url = 'https://image.baidu.com/search/index?tn=baiduimageipn=rct=201326592cl=2lm=-1st=-1fm=indexfr=hs=0xthttps=111110sf=1fmq=pv=ic=0nc=1z=se=1showtab=0fb=0width=height=face=0istype=2ie=utf-8word=%E7%8B%97oq=%E7%8B%97rsp=-1'
        headers = {
            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9",
            "Accept-Encoding": "gzip, deflate, br",
            "Accept-Language": "zh-CN,zh;q=0.9",
            "Cache-Control": "max-age=0",
            "Connection": "keep-alive",
            "Cookie": "BIDUPSID=4B61D634D704A324E3C7E274BF11F280; PSTM=1624157516; BAIDUID=4B61D634D704A324C7EA5BA47BA5886E:FG=1; __yjs_duid=1_f7116f04cddf75093b9236654a2d70931624173362209; BAIDUID_BFESS=101022AEE931E08A9B9A3BA623709CFE:FG=1; BDORZ=B490B5EBF6F3CD402E515D22BCDA1598; BDRCVFR[dG2JNJb_ajR]=mk3SLVN4HKm; cleanHistoryStatus=0; H_PS_PSSID=34099_33969_34222_31660_34226_33848_34113_34073_33607_34107_34134_34118_26350_22159; delPer=0; PSINO=6; BA_HECTOR=24ak842ka421210koq1gdtj070r; BDRCVFR[X_XKQks0S63]=mk3SLVN4HKm; userFrom=www.baidu.com; firstShowTip=1; indexPageSugList=%5B%22%E7%8B%97%22%2C%22%E7%8C%AB%E5%92%AA%22%2C%22%E5%B0%8F%E9%80%8F%E6%98%8E%22%5D; ab_sr=1.0.1_OGYwMTZiMjg5ZTNiYmUxODIxOTgyYTllZGMyMzhjODE2ZWE5OGY4YmEyZWVjOGZhOWIxM2NlM2FhZTQxMmFjODY0OWZiNzQxMjVlMWIyODVlZWFiZjY2NTQyMTZhY2NjNTM5NDNmYTFmZjgxMTlkOGYxYTUzYTIzMzA0NDE3MGNmZDhkYTBkZmJiMmJhZmFkZDNmZTM1ZmI2MWZkNzYyYQ==",
            "Host": "image.baidu.com",
            "Referer": "https://image.baidu.com/",
            "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"',
            "sec-ch-ua-mobile": "?0",
            "Sec-Fetch-Dest": "document",
            "Sec-Fetch-Mode": "navigate",
            "Sec-Fetch-Site": "same-origin",
            "Sec-Fetch-User": "?1",
            "Upgrade-Insecure-Requests": "1",
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.106 Safari/537.36"
        }
        for url in self.start_urls:
            yield scrapy.Request(url,headers=headers,callback=self.parse,dont_filter=True)
    def parse(self, response):
        img_urls = re.findall('"thumbURL":"(.*?)"', response.text)
        # print(img_urls)
        item = DbimgItem()
        item['image_urls'] = img_urls
        yield item

3.2、items文件

import scrapy
class DbimgItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    image_urls = scrapy.Field()

3.3、settings文件

ROBOTSTXT_OBEY = False
#打开我们写的管道
ITEM_PIPELINES = {
   # 'dbimg.pipelines.DbimgPipeline': 300,
    'dbimg.pipelines.ImgPipe': 300,
}
#图片存放位置
IMAGES_STORE = 'D:/python test/爬虫/scrapy6/dbimg/imgs'

3.4、pipelines文件

import os
from itemadapter import ItemAdapter
from scrapy.pipelines.images import ImagesPipeline
import settings
"""
def item_completed(self, results, item, info):
    with suppress(KeyError):
        ItemAdapter(item)[self.images_result_field] = [x for ok, x in results if ok]
    return item
"""
class ImgPipe(ImagesPipeline):
    num=0
    #重写此函数修改获取的图片的名字  不然图片名称就是一串数字字母
    def item_completed(self, results, item, info):
        images_path = [x['path'] for ok, x in results if ok]
        #print('results: ',results)   先查看下results的数据格式，然后才能获取到我们需要的值
        for image_path in images_path:
            os.rename(settings.IMAGES_STORE + "/" + image_path, settings.IMAGES_STORE + "/" + str(self.num) + ".jpg")
            self.num += 1

结果：