python爬虫爬取天猫胸罩销售数据并分析中国女性胸部大小 - Go语言中文社区

python爬虫爬取天猫胸罩销售数据并分析中国女性胸部大小

需要分析出大小，就需要获得尺码

1

首先要获取天猫上胸罩上的评论数据，其中会有尺码的数据

随机点开一个胸罩商品，查看商品的评价，有很多评价需要翻页，但是页面的链接并没有改变
所以去查看页面的源代码再去获取信息是不合适的。所以想到可能是通过Ajax加载的
然后打开Network选项卡，ctrl+f，随机选取评论的一段文本并查找 你可以看见数据
存在于list_detail_rate.htm下
在这里插入图片描述
搜索list_detail_rate.htm，获得url，评论数据就是有Ajax一次次请求得到的
在这里插入图片描述

找到这个链接之后，分析此链接你可以得到几个重要的参数

1.itemId：代表了商品的id

2.currentPage：代表了评论的页码

访问此页面得到相应的数据
代码

def get_json(itemId, currentPage):  # itemId代表商品的id，currentPage代表评论的页码
    url = 'https://rate.tmall.com/list_detail_rate.htm?'
    hd = {'User-Agent': 'Mozilla/5.0'}

    params = {'itemId': itemId,
              'sellerId': '111111111',  # 商家的id，这个是经过我的测试是无关紧要的，但是必须添这个字段，没有这个字段就会发生错误
              'order': '3',
              'currentPage': currentPage}
    try:
        r = requests.get(url, headers=hd, params=params)
        r.raise_for_status()
        # r.encoding=r.apparent_encoding   这不能再使用r.apparent_encoding 这样子编码会出现乱码
        # 将评论数据改为JSON格式,转变为一个字典或者是一个列表
        match = re.search(r'jsonpd*', r.text)
        a = match.group()
        result = r.text.replace(a, '')  # 将jsonp...去掉
        result = result.replace(')', '')
        result = result.replace('(', '')
        result = result.replace('false', '"false"')
        result = result.replace('true', '"true"')
        # print(type(result))测试 还是一个字符串
        result = json.loads(result)
        '''loads()方法将字符串转为JSON对象，由于最外层的花括号，所以最终类型是字典'''
        # print(type(result))测试 是一个字典

        return result
    except:
        print('1111')

这样我们需要的尺码数据就包含在里面了

2

我们怎么样才能获得商品的id？

首先选择一个品牌（选不选都可以），并且按照销量进行排序，然后分析网页，查看每一个商品id的位置并提取出来
代码

def goodList(page, list):  # 按照销量去爬去商品的id，page是页数 一页有60个商品
    hd = {'User-Agent': 'Mozilla/5.0'}
    url = 'https://list.tmall.com/search_product.htm?&brand=3524144&q=%D0%D8%D5%D6&sort=d&s=' + str((page - 1) * 60)
    try:
        r = requests.get(url, headers=hd)
        r.raise_for_status()
        r.encoding = r.apparent_encoding
        soup = BeautifulSoup(r.text, 'html.parser')
        for item in soup.select('div.product'):  # 利用CSS选择器
            list.append(item['data-id'])  # id在此属性中，向list中添加id
    except:
        print('aaa')

要注意的时url，brand代表品牌，q代表文胸，sort代表按照销量排序，s代表商品的个数

3

在第二步中我们可以得到商品的id，然后将id传给第一步，返回内容。
那么要怎么对返回的内容进行分析提取出想要的内容?
我们返回的是一个json对象
我们需要获取其中的尺码
代码

def size(json):
    items = json.get('rateDetail').get('rateList')#返回的是一个列表
    # print(items)
    for item in items:
        # print(type(item))
        sizelist.append(item['auctionSku'].split(':')[-1])
        #想要的属性在auctionSku中，然后分割取最后的尺码数据

完整的爬取代码

import requests
import json
import re
from bs4 import BeautifulSoup
import time


# 在一个店铺中找信息,按照销量进行排序，然后爬取每一个商品的信息

def get_json(itemId, currentPage):  # itemId代表商品的id，currentPage代表评论的页码
    url = 'https://rate.tmall.com/list_detail_rate.htm?'
    hd = {'User-Agent': 'Mozilla/5.0'}

    params = {'itemId': itemId,
              'sellerId': '111111111',  # 商家的id，这个是经过我的测试是无关紧要的，但是必须添这个字段，没有这个字段就会发生错误
              'order': '3',
              'currentPage': currentPage}
    try:
        r = requests.get(url, headers=hd, params=params)
        r.raise_for_status()
        # r.encoding=r.apparent_encoding   这不能再使用r.apparent_encoding 这样子编码会出现乱码
        # 将评论数据改为JSON格式,转变为一个字典或者是一个列表
        match = re.search(r'jsonpd*', r.text)
        a = match.group()
        result = r.text.replace(a, '')  # 将jsonp...去掉
        result = result.replace(')', '')
        result = result.replace('(', '')
        result = result.replace('false', '"false"')
        result = result.replace('true', '"true"')
        # print(type(result))测试 还是一个字符串
        result = json.loads(result)
        '''loads()方法将字符串转为JSON对象，由于最外层的花括号，所以最终类型是字典'''
        # print(type(result))测试 是一个字典

        return result
    except:
        print('1111')


def goodList(page, list):  # 按照销量去爬去商品的id，page是页数 一页有60个商品
    hd = {'User-Agent': 'Mozilla/5.0'}
    url = 'https://list.tmall.com/search_product.htm?&brand=3524144&q=%D0%D8%D5%D6&sort=d&s=' + str((page - 1) * 60)
    try:
        r = requests.get(url, headers=hd)
        r.raise_for_status()
        r.encoding = r.apparent_encoding
        soup = BeautifulSoup(r.text, 'html.parser')
        for item in soup.select('div.product'):  # 利用CSS选择器
            list.append(item['data-id'])  # id在此属性中
    except:
        print('aaa')


def size(json):
    items = json.get('rateDetail').get('rateList')
    # print(items)
    for item in items:
        # print(type(item))
        sizelist.append(item['auctionSku'].split(':')[-1])



idlist = []#存商品的id
sizelist = []#存尺码
goodList(1, idlist)#爬取按照销量排序的第一页的商品
for id in idlist:
    for i in range(1, 10):#取评论的前9页
        json_text = get_json(id, i)
        size(json_text)
    time.sleep(1)
print(sizelist)

部分输出结果

['75C', '75B', '75B', '80A', '75B', '85D', '80C', '75B', '70A', '70A', '75A', '75B', '70B', '80B', '80A', '80A', '80']

最后进行分析

list=['75C', '75B', '75B', '80A', '75B', '85D', '80C', '75B', '70A', '70A', '75A', '75B', '70B', '80B', '80A', '80A', '80D', '75B', '75A', '75B', '75B', '90D', '80B', '75A', '75B', '75A', '80A', '75C', '70A', '75B', '75B', '75B', '75E', '80D', '75A', '85E', '75A', '70B', '80A', '80A', '75C', '80B', '75B', '75B', '75D', '75A', '85E', '80B', '75C', '80A', '80B', '80B', '80B', '75A', '75B', '75B', '80D', '75B', '70B', '75B', '80A', '70A', '80D', '80D', '80B', '85E', '70A', '75B', '85E', '75B', '75C', '80C', '80B', '70B', '80C', '80D', '75A', '75B', '75B', '75A', '75A', '80C', '75A', '75B', '75B', '75B', '75B', '75A', '75A', '75A', '75A', '80A', '80A', '85C', '70A', '80C', '70B', '75B', '75D', '75B', '75C', '75B', '80A', '75D', '75A', '80A', '80C', '70B', '75A', '80D', '75B', '80E', '75B', '80D', '80C', '75C', '75B', '75C', '75B', '75A', '80A', '80A', '80C', '80D', '80B', '75B', '85D', '85D', '75B', '75B', '80C', '75A', '75B', '75B', '75B', '70B', '75A', '85B', '75B', '75A', '75B', '85D', '75B', '85B', '80A', '80D', '75B', '75B', '85C', '80D', '75A', '70B', '75A', '75A', '90E', '75B', '80B', '70A', '80B', '85D', '75A', '80C', '70B', '80A', '75B', '80B', '80A', '70B', '75B', '70B', '80D', '80A', '90E', '75B', '75B', '80D', '75B', '85D', '80B', '80A', '80C', '85D', '75B', '75A', '75C', '80B', '75C', '75A', '80B', '75C', '80A', '70A', '85E', '85D', '90E', '90E', '80C', '80B', '80C', '75B', '90E', '80A', '75B', '75B', '75B', '75B', '75B', '75C', '80C', '80B', '80B', '80B', '80D', '85E', '75C', '85C', '75B', '85B', '80C', '75B', '70A', '75A', '75D', '80B', '80A', '75B', '80A', '75B', '85D', '75B', '85E', '75B', '90E', '85E', '70B', '80A', '80C', '85E', '75A', '80C', '80A', '80C', '75B', '70B', '80A', '75A', '75B', '75C', '80B', '75B', '80B', '80C', '80C', '75B', '85D', '75C', '80B', '75B', '85C', '80D', '80C', '75B', '70B', '75A', '80B', '90D', '75B', '70A', '75B', '85D', '80C', '85D', '80A', '75B', '80D', '85C', '75B', '90E', '80B', '75B', '85D', '80D', '70B', '85D', '80C', '85C', '80D', '85D', '75B', '75B', '70B', '80B', '80A', '80B', '75A', '85E', '75A', '75A', '75C', '85D', '75B', '80C', '75C', '70C', '80C', '75B', '80C', '85C', '75B', '80C', '75A', '75A', '85D', '80C', '75B', '80C', '90E', '75B', '85D', '85C', '75B', '75C', '80C', '85D', '75B', '85D', '75B', '70A', '80C', '70C', '80C', '80C', '80C', '75A', '75B', '70B', '70B', '90D', '75C', '80A', '85D', '80C', '80C', '85C', '80C', '80C', '75A', '75A', '80B', '85D', '75A', '75B', '90E', '75B', '75B', '80C', '85E', '80C', '75D', '75B', '80B', '80B', '80A', '80B', '80B', '75C', '70A', '75B', '85C', '75B', '75A', '75C', '80A', '70B', '75B', '75C', '75C', '70B', '75B', '75B', '80A', '80C', '75C', '75B', '80B', '75B', '70B', '80A', '70A', '70A', '75A', '80B', '70A', '70A', '75A', '80B', '80A', '75B', '75B', '80C', '80B', '75A', '70B', '75C', '75B', '75B', '70B', '80B', '75B', '80C', '75B', '80B', '75B', '80C', '70B', '75B', '80B', '75A', '70A', '80C', '80C', '70B', '80B', '75B', '70A', '80B', '80B', '70B', '75B', '75B', '75B', '75B', '85C', '70A', '75C', '70B', '70B', '80B', '75A', '80B', '70B', '80A', '75B', '80A', '75A', '75B', '75B', '75C', '75A', '70B', '80B', '75C', '70A', '75B', '70A', '80B', '80B', '75B', '85C', '80C', '80B', '75B', '80A', '75B', '75B', '85C', '70A', '75B', '75B', '75B', '80B', '85C', '75B', '80A', '80C', '80B', '80C', '80B', '70A', '75B', '80C', '80C', '75B', '80C', '80B', '80C', '75B', '70A', '75A', '75B', '70A', '70A', '75B', '70A', '75A', '75A', '80B', '70A', '80A', '75B', '70B', '85C', '75A', '80B', '75B', '75B', '75B', '75B', '85C', '75B', '75A', '70A', '80C', '80B', '80B', '80B', '75B', '80B', '80B', '70A', '75B', '75A', '75A', '70A', '80B', '75A', '75B', '70B', '85C', '75C', '70A', '85C', '70B', '70B', '75A', '80C', '80A', '75B', '75A', '80B', '75B', '80A', '75B', '75A', '75A', '75B', '75A', '75B', '85C', '75B', '75B', '70B', '75B', '75B', '70B', '90D', '80B', '75B', '75B', '70B', '75B', '70A', '80B', '80B', '85B', '80A', '70B', '80A', '80A', '70A', '75B', '70A', '80A', '80D', '80B', '80B', '75B', '80B', '80A', '75B', '75B', '75B', '80B', '75B', '70A', '80B', '70A', '70B', '75B', '75A', '75B', '75B', '90C', '80B', '80A', '75B', '70A', '90D', '75B', '70B', '75A', '75A', '80A', '85B', '70A', '70A', '80A', '70A', '70B', '75B', '90C', '70B', '75B', '80B', '75B', '85D', '75B', '75A', '70A', '80A', '75B', '80B', '70A', '85D', '75A', '80B', '80B', '85C', '75B', '75B', '75B', '70B', '75B', '75B', '90D', '85C', '75B', '75B', '80B', '80A', '75B', '80A', '80A', '75B', '80B', '75B', '75B', '80A', '85C', '75B', '70A', '80B', '70A', '80B', '80B', '80B', '75B', '85C', '80B', '80B', '75A', '75B', '75A', '80B', '75B', '70A', '75B', '85D', '80B', '70A', '70B', '80B', '75B', '90C', '70A', '70B', '80B', '75A', '75A', '75B', '90D', '95C', '75B', '80B', '75B', '75B', '75B', '80B', '80A', '75B', '70A', '75B', '80B', '80A', '75B', '80B', '70B', '80B', '80D', '70B', '70A', '75B', '75A', '75B', '90C', '75B', '80B', '75B', '75A', '75B', '75A', '75B', '70A', '75B', '75B', '90C', '85B', '80B', '70B', '85B', '75B', '70B', '75B', '70A', '75A', '75B', '80A', '85C', '75A', '75A', '75C', '75A', '75B', '70A', '75B', '80A', '85C', '75B', '75C', '70A', '75A', '75B', '75B', '70B', '80B', '75B', '70B', '70B', '70A', '70A', '75A', '75A', '80B', '75B', '75B', '70A', '70A', '75A', '80B', '75B', '70B', '70A', '75A', '80B', '75B', '85C', '85C', '80B', '80A', '80B', '75B', '75B', '70A', '80B', '75C', '70A', '75A', '75A', '75C', '80A', '80B', '75B', '70B', '80A', '80C', '80B', '75B', '80B', '70B', '70A', '70B', '80A', '75A', '70B', '85C', '85C', '75A', '75A', '70A', '75A', '85C', '80B', '75B', '75C', '75C', '80C', '70A', '75A', '85C', '85C', '75A', '70A', '75A', '75B', '85C', '75B', '75B', '75A', '75A', '70B', '80B', '70B', '85C', '75C', '75B', '80B', '80B', '75B', '80A', '80A', '80B', '85C', '85C', '75C', '75A', '80B', '80B', '75B', '75B', '75A', '70B', '75A', '80C', '80A', '70A', '75A', '75A', '80C', '80B', '75C', '75B', '75A', '75A', '70A', '75C', '75A', '70B', '75B', '80A', '80C', '85C', '80C', '80B', '75B', '70B', '75A', '75B', '75C', '80C', '70A', '75B', '75B', '75B', '80B', '75C', '75C', '85C', '80C', '75A', '75A', '85C', '80B', '80B', '75B', '70B', '75B', '70A', '80B', '85C', '80B', '75B', '75A', '75C', '75A', '75B', '75A', '75B', '75B', '80B', '75A', '75B', '80C', '70B', '75B', '70B', '70B', '70B', '75B', '75B', '80C', '75B', '80C', '85C', '80B', '85C', '70B', '85C', '85C', '75B', '80D', '80B', '80B', '85D', '75B', '80C', '90D', '80B', '80B', '75B', '75C', '70B', '80C', '70B', '80B', '85C', '80C', '75B', '80C', '85D', '90D', '75B', '80B', '85D', '80C', '85D', '75C', '85C', '80B', '80B', '75B', '80B', '80B', '80B', '75B', '75B', '90D', '70B', '80B', '75B', '80B', '90D', '70B', '85C', '80B', '75B', '80B', '80B', '75C', '90D', '75C', '80D', '80C', '85C', '80B', '75B', '70B', '70B', '85D', '75B', '75B', '75C', '80B', '75B', '75B', '80C', '80C', '80C', '80B', '75C', '80C', '75B', '80B', '80C', '85C', '80B', '75B', '85D', '85D', '80B', '90D', 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版权声明：本文来源CSDN，感谢博主原创文章，遵循 CC 4.0 by-sa 版权协议，转载请附上原文出处链接和本声明。
原文链接：https://blog.csdn.net/Yk_0311/article/details/82797544
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