scrapy进阶《封号码罗》之如何优雅的征服世界首富亚马逊(amazon.com)

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VIP免费原创最新推荐文章于 2026-07-09 15:49:56 发布 621 阅读 AI 写同款· GEO 优化 ›

Python批量采集商品数据并使用多线程（含完整源码）前言嗨喽，大家好，这里是魔王~ 本次目的: Python批量采集商品数据知识点: 爬虫基本流程非结构化数据解析 csv数据保存线程池的使用开发环境: python 3.8 pycharm requests >>> pip install requests parsel >>> pip install parsel 网站思路分析: 找到数据来源 https://www.amazon.cn/s?rh=n%3A106200071&fs=true&a 阅读详情

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关于亚马逊的爬虫，针对不同的使用场合，前前后后写了有六七个了，今天拿出其中一个爬虫，也是相对其他几个爬虫难度稍微大一些的，这个爬虫用到了我之前没有使用过的一个爬虫手法，虽然头疼了一天半的时间，不过最终还是写出来了！
先上爬到结果，一睹芳容！
在这里插入图片描述

# settings.py我也就是修改了一下请求头，没有别的什么参数好设置的
DEFAULT_REQUEST_HEADERS = {
   
   
    'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3',
    'accept-encoding': 'gzip, deflate, br',
    'accept-language': 'zh-CN,zh;q=0.9,en;q=0.8',
    # 'accept-language': 'q=0.9,en;q=0.8',
    'cookie': 'session-id=142-3668058-0487211; ubid-main=132-5736401-5537057; aws-priv=eyJ2IjoxLCJldSI6MCwic3QiOjB9; aws-target-static-id=1571291023940-335290; aws-target-data=%7B%22support%22%3A%221%22%7D; regStatus=pre-register; x-wl-uid=1LHDAujloWlUxmLRzSHozWKl4n+BjwQ2HAyx7BwxROqQZnIHpINHbdwLexNggVVlabqGiYHdV0mXMW5ff7gGrjphRIfQrPuY1K2hUDtmzEfxUq8TcFsULMzLCDQvtlRSLjglCTB2mI6s=; s_pers=%20s_fid%3D2A84D84A05E2C5F6-0DC9D42BD2FBEA5E%7C1730205389961%3B%20s_dl%3D1%7C1572354389963%3B%20gpv_page%3DUS%253AAS%253ASOA-overview-footer%7C1572354389971%3B%20s_ev15%3D%255B%255B%2527SCSOAlogin%2527%252C%25271571110956217%2527%255D%252C%255B%2527www.amz123.com%2527%252C%25271571446469054%2527%255D%252C%255B%2527SCSOAlogin%2527%252C%25271572352589980%2527%255D%255D%7C1730205389980%3B; s_fid=0AEE278A3A21C88C-034FF405EC91CDA6; s_vn=1602827024206%26vn%3D3; aws-target-visitor-id=1571291023943-752944.22_23; s_dslv=1572355541019; s_nr=1572355541021-Repeat; x-amz-captcha-1=1573628129095978; x-amz-captcha-2=py3BFrzl/i7mmCMvLgvRWQ==; session-id-time=2082787201l; x-main="ABFV62tSPQuPy5A0H2hXH2Nv6N?Zp0FnRoNywwX7sB3zYoSM94HI8tx5NgCAe1qG"; at-main=Atza|IwEBIBmgXA3krCYRAJ68T43x9IbC8ZiNWTKIS5uloe1JAnpwaOIQHK5jLLVgObHmiZ8UMEn8J5J7FK-bOFnwPodLFyBZYkW31uPz2dEqjRaK8PZrgpddmbTJ9KG4XhvcOoq0kMqfZUoBCL2QgV3ksB46tOO306Gf9BnmGk1_rTOMic7NFC9xsFzacybCm4RP4aAzuB-stwk7PoezghoWOQpT7zm3h5I8nsmK8kxUSz8iuouiG9v6gBPlyAetoPqa-3otO4yblvccuxYGaE-poYa3YrEsJRMRqAGrwpMskNgVQvNmw7E-7IkFyhCYknqjzt9P-HHs_bETzvXeCQOQteucpz3EXVBOeAf7-lAnWd4FtwA-7krD87ihhTiJANeB7yITUuXQGQP5IlHvSDcL9p37GQtI; sess-at-main="7/3eFhu1sYbjdEAn60gUzC3eSQSFPhjBNfi4dQuXwvs="; sst-main=Sst1|PQGB34zV-KtTdN4khU4KMMhpC-joyMrwsBrk4vA8n8M9ngDRZ0jZy68rXm0E8vH_CyBzoGL4W8x6XAsch693MoCyY5w1Aw2hIhCoafjkfOxhKrd9RHT0HDxZhQLAFTIs7DtW23UQkxccnPtletjCjGsCc8Cis27vApJr0p-0p6n-K9DOZzTFSV7O1l06ouOasxrVNOUjOXtxnsSRROguKnqoQSjCLUfJOnsiARe3ASEh_gRD13elbbBFrfH999dzBSL-A3UqGlXfiCXVTK3UGlWuKWftQGv6od-fjW7y5IQtE08VkOSKFIH28IsfstKJJZZ4TfVEniXGoDDGCuEexIzVeg; lc-main=en_US; i18n-prefs=USD; cdn-session=AK-608ed069117695d10fc5a061329ac781; session-token=wt43/36BLQUMTFbQvvH1QOKtBil240+5Mj4WSxFRfdFkcDCJPkc3ArqEArXxoq+VoWksSMKN62/Kq30lGL+yu/30jBNEmNBrYatWdHEBi3WCHskqtAkJsmiR0ZZdMYM6+1QSrCeiPejf7cnCLiaoyNHd0TXhurrBx5QAuBt/zOVNuSfAb13dr7TjZMHfkko4Bu0ytxEmXyMJYqI73S4b91kxLTlo4mmATe7Zx3XDNK9dl88aI5nbl9x+k1gbfilXToALWR8mIjDyYnaubUTkgQ==; skin=noskin; csm-hit=tb:CNZA0DXGWHXW3TBBB800+s-CNZA0DXGWHXW3TBBB800|1577070891800&t:1577070891800&adb:adblk_no',
    'referer': 'https://www.amazon.com/ref=nav_logo?language=en_US',
    'sec-fetch-mode': 'navigate',
    "sec-fetch-site": 'same-origin',
    'sec-fetch-user': '?1',
    'upgrade-insecure-requests': '1'
}
RANDOM_UA_TYPE = "chrome"  # 使用谷歌的浏览器ua头
DOWNLOADER_MIDDLEWARES = {
   
   
    # 'yamaxun.middlewares.ProxyMiddleWare': 541,
    'yamaxun.middlewares.YamaxunDownloaderMiddleware': 543,
    'yamaxun.middlewares.RandomUserAgentMiddlware': 542,
    'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware': None,  # 需要将原始的设置为none
}
ITEM_PIPELINES = {
   
   
    # 'yamaxun.pipelines.YamaxunPipeline': 300,
    # 'yamaxun.pipelines.YamaxunPlPipeline': 301,
    # 'yamaxun.pipelines.YamaxunImgPipeline': 302,
    # 'yamaxun.pipelines.YamaxunFbmPipeline': 303,
    'yamaxun.pipelines.YamaxunCjPipeline': 304,
}

其他的都是一些常规设置，如：ROBOTSTXT_OBEY = False，不再赘述

#items.py	刚开始没头绪，本来想分主体和变体的，后来在分析中发现，没那个必要，名字没有main_也可以通用
class YamaxunCjItem(scrapy.Item):
    main_id = scrapy.Field()                    # id
    main_url = scrapy.Field()                   # 主体url
    main_title = scrapy.Field()                 # 主体标题
    main_asin = scrapy.Field()                  # 主体ASIN
    main_price = scrapy.Field()                 # 主体价格
    main_color = scrapy.Field()                 # 主体颜色
    main_dimensions = scrapy.Field()            # 主体尺码大小
    main_hdimgs = scrapy.Field()                # 主体高清图URL
    main_info_one = scrapy.Field()              # 主体描述1
    main_info_two = scrapy.Field()              # 主体描述2
    main_info_three = scrapy.Field()            # 主体描述3
    main_info_four = scrapy.Field()             # 主体描述4
    main_info_five = scrapy.Field()             # 主体描述5
    main_description = scrapy.Field()           # 主体长描述
    main_weight = scrapy.Field()                # 主体重量
    main_material = scrapy.Field()              # 主体材质

爬虫的主程序如下：

# -*- coding: utf-8 -*-
import scrapy
from yamaxun.items import YamaxunCjItem


class YamaxuncjSpider(scrapy.Spider):
    name = 'yamaxuncj'
    # 需要手动开启setting里面的管道
    custom_settings = {
   
   "ITEM_PIPELINES": {
   
   'yamaxun.pipelines.YamaxunCjPipeline': 304}}
    # allowed_domains = ['amazon.com']
    # start_urls = ['http://amazon.com']
    # 整个店铺 https://www.amazon.com/s?me=AHSA6JF4V43Q1&marketplaceID=ATVPDKIKX0DER
    # 店铺中的搜索关键字 https://www.amazon.com/s?k=thermos+cup&me=A2AJJBXRGY125X&ref=nb_sb_noss
    start_url = []
    BASE_URL = "http://www.amazon.com"
    SUB_URL = "http://www.amazon.com/dp/"

    def __init__(self, *args, **kwargs):
        super(YamaxuncjSpider, self).__init__(*args, **kwargs)
        # goods_name = kwargs["goods_name"]
        # goods_name = "energy saving lamp"                           # 爬不同的数据，只需要修改这里，注意：保存文件名的修改，.txt和.json
        # self.url = "https://www.amazon.com/s?me=AHSA6JF4V43Q1&marketplaceID=ATVPDKIKX0DER"
        self.url = "https://www.amazon.com/s?k=thermos+cup&me=A2AJJBXRGY125X&ref=nb_sb_noss"

    def start_requests(self):
        print("当前链接是", self.url)
        yield scrapy.Request(url=self.url, callback=self.parse, dont_filter=True)

    def parse(self, response):
        print("---------------------------------进入到列表页------------------------------------------")
        # 进入到了列表页，不拿数据，主要在详情页拿数据
        # with open("asd.html", "w", encoding="utf-8") as f:
        #     f.write(response.text)
        detail_url = response.css('a[class="a-link-normal a-text-normal"]::attr(href)').extract()
        if "?k" in self.url:
            detail_url = detail_url[1:]
        else:
            detail_url = detail_url[0:]
        id = 0
        # 测试单个商品拿数据
        # detail_url = [
        #     "/Tulip-Cupcake-Liners-300-Pack-Restaurants/dp/B07V3Z8VLG/ref=sr_1_fkmr2_2?keywords=thermos+cup&m=A2AJJBXRGY125X&qid=1578100381&s=merchant-items&sr=1-2-fkmr2"]
        for i in detail_url:
            id += 1
            item = dict()  # 设置一个空字典
            item["main_id"] = id
            url = self.BASE_URL + i
            item["main_url"] = url
            print("当前是第%d个链接" % id, url)
            yield scrapy.Request(url=url, callback=self.detailParse, dont_filter=True, meta={
   
   "item"