Scrapy 框架采集亚马逊商品top数据

Scrapy的crawlSpider爬虫

1. crawlSpider 是什么?

crawlSpider是Scrapy的派生类,Spider类的设计原则是 只爬取start_url列表中的网页, 而crawlSpider类定义了一些规则(rule) 来提供跟进link的方便的机制。从爬取的网页中获取link并继续爬取
crawlSpider 能够匹配满足条件的url地址,组装成Request对象后自动发送给引擎,同时能够指定callback函数
即: CrawlSpider 爬虫可以按照规则自动获取连接

2. 创建crawlSpider爬虫:

scrapy genspider -t crawl 爬虫名 域名

即创建 amazon爬虫命令:
scrapy genspider -他crawl amzonTop amazon.com

import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule


class TSpider(CrawlSpider):
    name = 'amzonTop '
    allowed_domains = ['amazon.com']
    start_urls = ['https://amazon.com/']

    rules = (
        Rule(LinkExtractor(allow=r'Items/'), callback='parse_item', follow=True),
    )

    def parse_item(self, response):
        item = {}
        # item['domain_id'] = response.xpath('//input[@id="sid"]/@value').get()
        # item['name'] = response.xpath('//div[@id="name"]').get()
        # item['description'] = response.xpath('//div[@id="description"]').get()
        return item

rurles 是一个元组或者是列表,包含的是Rule对象
Rule 表示规则,其中包含LinkExtractor,callback和follow等参数

LinkExtractor:链接提取器,可以通过正则,xpath,css 来进行url地址的匹配
callback:提取出来的url地址响应的回调函数,可以没有,没有表示响应不会进行回调函数的处理
follow: 提取出来的url地址对应的响应是否还会继续被rules中的规则进行提取。True:表示会。False表示不会

3.爬取amazon商品数据:

1.创建amaozn爬虫:

scrapy genspider -t crawl amazonTop2 amazon.com
项目结构:
Scrapy 框架采集亚马逊商品top数据_第1张图片

  1. 提取商品列表页翻页的url和商品详情页的url

提取商品列表页所有商品Asin、rank(商品排名)------即获取所有蓝色框的Asin和rank
提取商品详情页所有的颜色Asin、规格的Asin ------ 即获取所有绿色框的Asin,绿色框包含了蓝色框的Asin

Scrapy 框架采集亚马逊商品top数据_第2张图片
绿色框:就好比购物网站衣服的 尺码 S M L XL XXL

爬虫文件:amzonTop2.py

import datetime
import re
import time
from copy import deepcopy

import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule


class Amazontop2Spider(CrawlSpider):
    name = 'amazonTop2'
    allowed_domains = ['amazon.com']
    # https://www.amazon.com/Best-Sellers-Tools-Home-Improvement-Wallpaper/zgbs/hi/2242314011/ref=zg_bs_pg_2?_encoding=UTF8&pg=1
    start_urls = ['https://amazon.com/Best-Sellers-Tools-Home-Improvement-Wallpaper/zgbs/hi/2242314011/ref=zg_bs_pg_2']
    # rule 提取url
    rules = [
        Rule(LinkExtractor(restrict_css=('.a-selected','.a-normal')), callback='parse_item', follow=True),
    ]

    def parse_item(self, response):
        asin_list_str = "".join(response.xpath('//div[@class="p13n-desktop-grid"]/@data-client-recs-list').extract())
        if asin_list_str:
            asin_list = eval(asin_list_str)
            for asinDict in asin_list:
                item = {}
                if "'id'" in str(asinDict):
                    listProAsin = asinDict['id']
                    pro_rank = asinDict['metadataMap']['render.zg.rank']
                    item['rank'] = pro_rank
                    item['ListAsin'] = listProAsin
                    # 产品详情页链接
                    item['rankAsinUrl'] =f"https://www.amazon.com/Textile-Decorative-Striped-Corduroy-Pillowcases/dp/{listProAsin}/ref=zg_bs_3732341_sccl_1/136-3072892-8658650?psc=1"

                    print("-"*30)
                    print(item)
                    print('-'*30)
                    yield scrapy.Request(item["rankAsinUrl"], callback=self.parse_list_asin,
                                         meta={"main_info": deepcopy(item)})


    def parse_list_asin(self, response):
        """
        获取单个产品的所有分类子asin
        :param response:
        :return:
        """
        news_info = response.meta["main_info"]
        list_ASIN_all_findall = re.findall('"colorToAsin":(.*?),"refactorEnabled":true,', str(response.text))
        try:
            try:
                parentASIN = re.findall(r',"parentAsin":"(.*?)",', str(response.text))[-1]
            except:
                parentASIN = re.findall(r'&parentAsin=(.*?)&', str(response.text))[-1]
        except:
            parentASIN = ''
        # parentASIN = parentASIN[-1] if parentASIN !=[] else ""
        print("parentASIN:",parentASIN)
        if list_ASIN_all_findall:
            list_ASIN_all_str = "".join(list_ASIN_all_findall)
            list_ASIN_all_dict = eval(list_ASIN_all_str)  # 转换为字典
            for asin_min_key, asin_min_value in list_ASIN_all_dict.items():
                if asin_min_value:
                    asin_min_value = asin_min_value['asin']
                    news_info['parentASIN'] = parentASIN
                    news_info['secondASIN'] = asin_min_value  # 单个产品分类的子asin
                    news_info['rankSecondASINUrl'] = f"https://www.amazon.com/Textile-Decorative-Striped-Corduroy-Pillowcases/dp/{asin_min_value}/ref=zg_bs_3732341_sccl_1/136-3072892-8658650?psc=1"
                    yield scrapy.Request(news_info["rankSecondASINUrl"], callback=self.parse_detail_info,meta={"news_info": deepcopy(news_info)})


    def parse_detail_info(self, response):
        """
        获取商品详情页信息
        :param response:
        :return:
        """
        item = response.meta['news_info']
        ASIN = item['secondASIN']
        # print('--------------------------------------------------------------------------------------------')
        # with open('amazon_h.html', 'w') as f:
        #     f.write(response.body.decode())
        # print('--------------------------------------------------------------------------------------------')
        pro_details = response.xpath('//table[@id="productDetails_detailBullets_sections1"]//tr')

        pro_detail = {}
        for pro_row in pro_details:
            pro_detail[pro_row.xpath('./th/text()').extract_first().strip()] = pro_row.xpath('./td//text()').extract_first().strip()

        print("pro_detail",pro_detail)
        ships_from_list = response.xpath(
            '//div[@tabular-attribute-name="Ships from"]/div//span//text()').extract()
        # 物流方
        try:
            delivery = ships_from_list[-1]
        except:
            delivery = ""
        seller = "".join(response.xpath('//div[@id="tabular-buybox"]//div[@class="tabular-buybox-text"][3]//text()').extract()).strip().replace("'", "")  # 卖家
        if seller == "":
            seller = "".join(response.xpath('//div[@class="a-section a-spacing-base"]/div[2]/a/text()').extract()).strip().replace("'", "")  # 卖家
        seller_link_str = "".join(response.xpath('//div[@id="tabular-buybox"]//div[@class="tabular-buybox-text"][3]//a/@href').extract())  # 卖家链接
        # if seller_link_str:
        #     seller_link = "https://www.amazon.com" + seller_link_str
        # else:
        #     seller_link = ''
        seller_link = "https://www.amazon.com" + seller_link_str if seller_link_str else ''

        brand_link = response.xpath('//div[@id="bylineInfo_feature_div"]/div[@class="a-section a-spacing-none"]/a/@href').extract_first()  # 品牌链接
        pic_link = response.xpath('//div[@id="main-image-container"]/ul/li[1]//img/@src').extract_first() # 图片链接
        title = response.xpath('//div[@id="titleSection"]/h1//text()').extract_first()  # 标题
        star = response.xpath('//div[@id="averageCustomerReviews_feature_div"]/div[1]//span[@class="a-icon-alt"]//text()').extract_first().strip()  # 星级
        # 售价
        try:
            price = response.xpath('//div[@class="a-section a-spacing-none aok-align-center"]/span[2]/span[@class="a-offscreen"]//text()').extract_first()
        except:
            try:
                price = response.xpath('//div[@class="a-section a-spacing-none aok-align-center"]/span[1]/span[@class="a-offscreen"]//text()').extract_first()
            except:
                price = ''
        size = response.xpath('//li[@class="swatchSelect"]//p[@class="a-text-left a-size-base"]//text()').extract_first()  # 尺寸
        # 颜色
        key_v = str(pro_detail.keys())
        brand = pro_detail['Brand'] if "Brand" in key_v else ''  # 品牌
        if brand == '':
            brand = response.xpath('//tr[@class="a-spacing-small po-brand"]/td[2]//text()').extract_first().strip()
        elif brand == "":
            brand = response.xpath('//div[@id="bylineInfo_feature_div"]/div[@class="a-section a-spacing-none"]/a/text()').extract_first().replace("Brand: ", "").replace("Visit the", "").replace("Store", '').strip()

        color = pro_detail['Color'] if "Color" in key_v else ""
        if color == "":
            color = response.xpath('//tr[@class="a-spacing-small po-color"]/td[2]//text()').extract_first()
        elif color == '':
            color = response.xpath('//div[@id="variation_color_name"]/div[@class="a-row"]/span//text()').extract_first()
        # 图案
        pattern = pro_detail['Pattern'] if "Pattern" in key_v else ""
        if pattern == "":
            pattern = response.xpath('//tr[@class="a-spacing-small po-pattern"]/td[2]//text()').extract_first().strip()
        # 材质 material
        try:
            material = pro_detail['Material']
        except:
            material = response.xpath('//tr[@class="a-spacing-small po-material"]/td[2]//text()').extract_first().strip()
        # 形状 shape
        shape = pro_detail['Shape'] if "Shape" in key_v else ""
        if shape == "":
            shape = response.xpath('//tr[@class="a-spacing-small po-item_shape"]/td[2]//text()').extract_first().strip()
        # style # 风格
        # 五点描述
        five_points =response.xpath('//div[@id="feature-bullets"]/ul/li[position()>1]//text()').extract_first().replace("\"", "'")
        size_num = len(response.xpath('//div[@id="variation_size_name"]/ul/li').extract())  # 尺寸数量
        color_num = len(response.xpath('//div[@id="variation_color_name"]//li').extract())  # 颜色数量
        # variant_num =  # 变体数量
        # style # 样式链接
        # manufacturer
        # 厂商
        try:
            Manufacturer = pro_detail['Manufacturer'] if "Manufacturer" in str(pro_detail) else " "
        except:
            Manufacturer = ""
        item_weight = pro_detail['Item Weight'] if "Weight" in str(pro_detail) else ''  # 商品重量
        product_dim = pro_detail['Product Dimensions'] if "Product Dimensions" in str(pro_detail) else ''  # 商品尺寸
        # product_material
        # 商品材质
        try:
            product_material = pro_detail['Material']
        except:
            product_material = ''
        # fabric_type
        # 织物成分
        try:
            fabric_type = pro_detail['Fabric Type'] if "Fabric Type" in str(pro_detail) else " "
        except:
            fabric_type = ""

        star_list = response.xpath('//table[@id="histogramTable"]//tr[@class="a-histogram-row a-align-center"]//td[3]//a/text()').extract()
        if star_list:
            try:
                star_1 = star_list[0].strip()
            except:
                star_1 = 0
            try:
                star_2 = star_list[1].strip()
            except:
                star_2 = 0
            try:
                star_3 = star_list[2].strip()
            except:
                star_3 = 0
            try:
                star_4 = star_list[3].strip()
            except:
                star_4 = 0
            try:
                star_5 = star_list[4].strip()
            except:
                star_5 = 0

        else:
            star_1 = 0
            star_2 = 0
            star_3 = 0
            star_4 = 0
            star_5 = 0

        if "Date First Available" in str(pro_detail):
            data_first_available = pro_detail['Date First Available']
            if data_first_available:
                data_first_available = datetime.datetime.strftime(
                    datetime.datetime.strptime(data_first_available, '%B %d, %Y'), '%Y/%m/%d')
            else:
                data_first_available = ""
        reviews_link = f'https://www.amazon.com/MIULEE-Decorative-Pillowcase-Cushion-Bedroom/product-reviews/{ASIN}/ref=cm_cr_arp_d_viewopt_fmt?ie=UTF8&reviewerType=all_reviews&formatType=current_format&pageNumber=1'
        # reviews_num, ratings_num  # 评论数量 ,评论星级
        scrap_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
        item['delivery']=delivery
        item['seller']=seller
        item['seller_link']= seller_link
        item['brand_link']= brand_link
        item['pic_link'] =pic_link
        item['title']=title
        item['brand']=brand
        item['star']=star
        item['price']=price
        item['color']=color
        item['pattern']=pattern
        item['material']=material
        item['shape']=shape
        item['five_points']=five_points
        item['size_num']=size_num
        item['color_num']=color_num
        item['Manufacturer']=Manufacturer
        item['item_weight']=item_weight
        item['product_dim']=product_dim
        item['product_material']=product_material
        item['fabric_type']=fabric_type
        item['star_1']=star_1
        item['star_2']=star_2
        item['star_3']=star_3
        item['star_4']=star_4
        item['star_5']=star_5
        # item['ratings_num'] = ratings_num
        # item['reviews_num'] = reviews_num
        item['scrap_time']=scrap_time
        item['reviews_link']=reviews_link
        item['size']=size
        item['data_first_available']=data_first_available

        yield item

采集数量达到一定量时,更换ip呀,识别验证码啥的

4. 下载中间件

Downloader Middlewares默认的方法:

  • process_request(self, request, spider):

    1.当每个request通过下载中间件时,该方法被调用
    2.返回None值:没有return也是返回None,该request对象传递给下载器,或通过引擎传递给其他权重低的process_request方法
    3.返回Response对象:不再请求,把response返回给引擎
    4.返回Request对象:把request对象通过引擎交给调度器,此时将不通过其他权重低的process_request方法

  • process_response(self, request, response, spider):

    1.当下载器完成http请求,传递响应给引擎的时候调用
    2.返回Resposne:通过引擎交给爬虫处理或交给权重更低的其他下载中间件的process_response方法
    3.返回Request对象:通过引擎交给调取器继续请求,此时将不通过其他权重低的process_request方法
    在settings.py中配置开启中间件,权重值越小越优先执行

middlewares.py

  1. 设置代理更换ip
class ProxyMiddleware(object):
    def process_request(self,request, spider):
        # 设置代理  根据具体使用填写
        request.meta['proxy'] = proxyServer
        # 设置认证
        request.header["Proxy-Authorization"] = proxyAuth

    # 检验代理ip是否可用
    def process_response(self, request, response, spider):
        if response.status != '200':
            request.dont_filter = True  # 重新发送的请求对象能够再次进入队列
            # 把对象返回给引擎,引擎再从头重新给第一个中间件的process_request
            return request  # 返回request,则中间件终止,该request返回引擎再给调度器
  1. 更换User-Agent或者是cookie
class AmazonspiderDownloaderMiddleware:
    # Not all methods need to be defined. If a method is not defined,
    # scrapy acts as if the downloader middleware does not modify the
    # passed objects.
    @classmethod
    def from_crawler(cls, crawler):
        # This method is used by Scrapy to create your spiders.
        s = cls()
        crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
        return s

    def process_request(self, request, spider):
    	# USER_AGENTS_LIST: setting.py
        user_agent = random.choice(USER_AGENTS_LIST)
        request.headers['User-Agent'] = user_agent
        cookies_str = '浏览器粘贴过来的cookie'
        # 将cookies_str转换为cookies_dict
        cookies_dict = {i[:i.find('=')]: i[i.find('=') + 1:] for i in cookies_str.split('; ')}
        request.cookies = cookies_dict
        # print("---------------------------------------------------")
        # print(request.headers)
        # print("---------------------------------------------------")
        return None

    def process_response(self, request, response, spider):
        return response

    def process_exception(self, request, exception, spider):
        pass

    def spider_opened(self, spider):
        spider.logger.info('Spider opened: %s' % spider.name)
  1. amazon的验证码

def captcha_verfiy(img_name):
    # 识别验证码
    reader = easyocr.Reader(['ch_sim', 'en'])
    # reader = easyocr.Reader(['en'], detection='DB', recognition = 'Transformer')
    # 读取图像
    result = reader.readtext(img_name, detail=0)[0]
    # result = reader.readtext('https://www.somewebsite.com/chinese_tra.jpg')
    if result:
        result = result.replace(' ', '')
    return result


def download_captcha(captcha_url):
    # 下载验证码图片
    response = requests.get(captcha_url, stream=True)
    try:
        with open(r'./captcha.png', 'wb') as logFile:
            for chunk in response:
                logFile.write(chunk)
            logFile.close()
            print("Download done!")
    except Exception as e:
        print("Download log error!")


class AmazonspiderVerifyMiddleware:
    # 验证码
    @classmethod
    def from_crawler(cls, crawler):
        s = cls()
        crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
        return s

    def process_request(self, request, spider):

        return None

    def process_response(self, request, response, spider):
        # print(response.url)
        if 'Captcha' in response.text:
            headers = {
                "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36"
            }
            session = requests.session()
            resp = session.get(url=response.url, headers=headers)
            response1 = etree.HTML(resp.text)
            # 获取验证码图像
            captcha_url = "".join(response1.xpath('//div[@class="a-row a-text-center"]/img/@src'))
            amzon = "".join(response1.xpath("//input[@name='amzn']/@value"))
            amz_tr = "".join(response1.xpath("//input[@name='amzn-r']/@value"))
            # 下载验证码图片并保存
            download_captcha(captcha_url)
            # 识别验证码字母
            captcha_text = captcha_verfiy('captcha.png')
            # 重新发送请求
            url_new = f"https://www.amazon.com/errors/validateCaptcha?amzn={amzon}&amzn-r={amz_tr}&field-keywords={captcha_text}"
            resp = session.get(url=url_new, headers=headers)
            if "Sorry, we just need to make sure you're not a robot" not in str(resp.text):
                response2 = HtmlResponse(url=url_new, headers=headers,body=resp.text, encoding='utf-8')
                if "Sorry, we just need to make sure you're not a robot" not in str(response2.text):
                    return response2
            else:
                return request
        else:
            return response

    def process_exception(self, request, exception, spider):
        pass

    def spider_opened(self, spider):
        spider.logger.info('Spider opened: %s' % spider.name)

初学scrapy,随便写写记录一下,写的有什么问题可以指出来。嘿嘿~~~

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