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这篇文章给大家分享的是有关python爬虫如何获取淘宝天猫商品详细参数的内容。小编觉得挺实用的，因此分享给大家做个参考，一起跟随小编过来看看吧。
首先我是从淘宝进去，爬取了按销量排序的所有（100页）女装的列表信息按综合、销量分别爬取淘宝女装列表信息，然后导出前100商品的 link，爬取其详细信息。这些商品有淘宝的，也有天猫的，这两个平台有些区别，处理的时候要注意。比如，有的说“面料”、有的说“材质成分”，其实是一个意思，等等。可以取不同的链接做一下测试。
import re from collections import OrderedDict from bs4 import BeautifulSoup from pyquery import PyQuery as pq #获取整个网页的源代码 from config import * #可引用congif的所有变量 import pymysql import urllib import json import bs4 import requests from selenium import webdriver from selenium.webdriver.support.ui import WebDriverWait from pyquery import PyQuery as pq #获取整个网页的源代码 import pandas as pd # 测试 淘宝+天猫，可完整输出及保存 browser = webdriver.Firefox() wait = WebDriverWait(browser,10) ####### 天猫上半部分详情 ############# def get_tianmao_header(url): browser.get(url) # wait.until(EC.presence_of_all_elements_located((By.CSS_SELECTOR,'#mainsrp-itemlist .items .item'))) #加载所有宝贝 html=browser.page_source doc = pq(html) # print(doc) info = OrderedDict() # 存放该商品所具有的全部信息 items = doc('#page') # info['店铺名'] = items.find('.slogo').find('.slogo-shopname').text() # info['ID'] = items.find('#LineZing').attr['itemid'] info['宝贝'] = items.find('.tb-detail-hd').find('h2').text() info['促销价'] = items.find('#J_PromoPrice').find('.tm-promo-price').find('.tm-price').text() info['原价'] = items.find('#J_StrPriceModBox').find('.tm-price').text() # '月销量' :items.find('.tm-ind-panel').find('.tm-ind-item tm-ind-sellCount').find('.tm-indcon').find('.tm-count').text(), info['月销量'] = items.find('.tm-ind-panel').find('.tm-indcon').find('.tm-count').text().split(' ',2)[0] info['累计评价'] = items.find('#J_ItemRates').find('.tm-indcon').find('.tm-count').text() # print(info) return info ######## 淘宝上半部分详情 ############### def get_taobao_header(url): browser.get(url) # wait.until(EC.presence_of_all_elements_located((By.CSS_SELECTOR,'#mainsrp-itemlist .items .item'))) #加载所有宝贝 html=browser.page_source doc = pq(html) # print(doc) info = OrderedDict() # 存放该商品所具有的全部信息 items = doc('#page') # info['店铺名'] = items.find('.tb-shop-seller').find('.tb-seller-name').text() # info['ID'] = items.find('#J_Pine').attr['data-itemid'] info['宝贝'] = items.find('#J_Title').find('h4').text() info['原价'] = items.find('#J_StrPrice').find('.tb-rmb-num').text() info['促销价'] = items.find('#J_PromoPriceNum').text() # '月销量' :items.find('.tm-ind-panel').find('.tm-ind-item tm-ind-sellCount').find('.tm-indcon').find('.tm-count').text(), info['月销量'] = items.find('#J_SellCounter').text() info['累计评价'] = items.find('#J_RateCounter').text() # print(info) return info ####################### 详情 ############################ # 抓取所有商品详情 def get_Details(attrs,info): # res = requests.get(url) # soup = BeautifulSoup(res.text, "html.parser") # # attrs = soup.select('.attributes-list li') # attrs= [<li title=" 薄">厚薄: 薄</li>, <li title=" 其他100%">材质成分: 其他100%</li>,<li ...</li>] attrs_name = [] attrs_value = [] ''''' [\s] 匹配空格，[\s]*,后面有 *，则可以为空 * : 匹配前面的子表达式任意次 ''' for attr in attrs: attrs_name.append(re.search(r'(.*?):[\s]*(.*)', attr.text).group(1)) attrs_value.append(re.search(r'(.*?):[\s]*(.*)', attr.text).group(2)) # print('attrs_name=',attrs_name) # attrs_name= ['厚薄', '材质成分', ...] # print('attrs_value=',attrs_value) # attrs_value= ['薄', '其他100%', ...] allattrs = OrderedDict() # 存放该产品详情页面所具有的属性 for k in range(0, len(attrs_name)): allattrs[attrs_name[k]] = attrs_value[k] # print('allattrs=',allattrs) # allattrs= OrderedDict([('厚薄', '薄'), ('材质成分', '其他100%'),...]) # info = OrderedDict() # 存放该商品所具有的全部信息 # info = get_headdetail2(url) # 下面三条语句获取描述、服务、物流的评分信息 # 下面的语句用来判断该商品具有哪些属性，如果具有该属性，将属性值插入有序字典，否则，该属性值为空 # 适用场景 if '材质成分' in attrs_name: info['材质成分'] = allattrs['材质成分'] elif '面料' in attrs_name: info['材质成分'] = allattrs['面料'] else: info['材质成分'] = 'NA' # 适用对象 if '流行元素' in attrs_name: info['流行元素'] = allattrs['流行元素'] else: info['流行元素'] = 'NA' #季节 if '年份季节' in attrs_name: info['年份季节'] = allattrs['年份季节'] else: info['年份季节'] = 'NA' # 款式 if '袖长' in attrs_name: info['袖长'] = allattrs['袖长'] else: info['袖长'] = 'NA' # 尺码 if '销售渠道类型' in attrs_name: info['销售渠道类型'] = allattrs['销售渠道类型'] else: info['销售渠道类型'] = 'NA' # 帽顶款式 if '货号' in attrs_name: info['货号'] = allattrs['货号'] else: info['货号'] = 'NA' # 帽檐款式 if '服装版型' in attrs_name: info['服装版型'] = allattrs['服装版型'] else: info['服装版型'] = 'NA' # 檐形 if '衣长' in attrs_name: info['衣长'] = allattrs['衣长'] else: info['衣长'] = 'NA' # 主要材质 if '领型' in attrs_name: info['领型'] = allattrs['领型'] else: info['领型'] = 'NA' # 人群 if '袖型' in attrs_name: info['袖型'] = allattrs['袖型'] else: info['袖型'] = 'NA' # 品牌 if '品牌' in attrs_name: info['品牌'] = allattrs['品牌'] else: info['品牌'] = 'NA' # 风格 if '图案' in attrs_name: info['图案'] = allattrs['图案'] elif '中老年女装图案' in attrs_name: info['图案'] = allattrs['中老年女装图案'] else: info['图案'] = 'NA' # 款式细节 if '服装款式细节' in attrs_name: info['服装款式细节'] = allattrs['服装款式细节'] else: info['服装款式细节'] = 'NA' # 适用年龄 if '适用年龄' in attrs_name: info['适用年龄'] = allattrs['适用年龄'] else: info['适用年龄'] = 'NA' # 风格 if '风格' in attrs_name: info['风格'] = allattrs['风格'] elif '中老年风格' in attrs_name: info['风格'] = allattrs['中老年风格'] else: info['风格'] = 'NA' #通勤 if '通勤' in attrs_name: info['通勤'] = allattrs['通勤'] else: info['通勤'] = 'NA' if '裙长' in attrs_name: info['裙长'] = allattrs['裙长'] else: info['裙长'] = 'NA' if '裙型' in attrs_name: info['裙型'] = allattrs['裙型'] else: info['裙型'] = 'NA' if '腰型' in attrs_name: info['腰型'] = allattrs['腰型'] else: info['腰型'] = 'NA' # 颜色分类 if '主要颜色' in attrs_name: info['主要颜色'] = allattrs['主要颜色'] else: info['主要颜色'] = 'NA' if '颜色分类' in attrs_name: info['主要颜色'] = allattrs['颜色分类'] else: info['主要颜色'] = 'NA' #尺码 if '尺码' in attrs_name: info['尺码'] = allattrs['尺码'] else: info['尺码'] = 'NA' if '组合形式' in attrs_name: info['组合形式'] = allattrs['组合形式'] else: info['组合形式'] = 'NA' if '裤长' in attrs_name: info['裤长'] = allattrs['裤长'] else: info['裤长'] = 'NA' return info import csv def main(): # 提取 列 with open('clothes_detai.csv', 'w', newline='', encoding='utf-8') as csvfile: # fieldnames = ['店铺ID','店铺名','链接','宝贝','原价','促销价','月销量','累计评价','材质成分','流行元素','袖长','年份季节','销售渠道类型','货号','服装版型','衣长','领型','袖型', # '裙型','裙长','腰型','裤长','组合形式','品牌','图案','服装款式细节', '适用年龄','风格','通勤','主要颜色','尺码'] fieldnames=[ 'Link','Brand','Title','Price','Sale price','Sales','Evaluations', 'Component', 'Fashion elements','Sleeve','Seasons','Sales channels', 'Number','Clothes_Style','Long','Collar type','Sleeve type', 'Skirt type','Skirt length','Waist','Combining form','Outseam', 'Design','Fashion pattern detail','Applicable age', 'Style','Commuter','color','Size'] # 'Shop','Data_id','Shop_id','Shop','Link','Data_id', writer = csv.DictWriter(csvfile, fieldnames = fieldnames) writer.writeheader() # urls = ['//detail.tmall.com/item.htm?spm=a230r.1.14.1.ebb2eb2eGyUw1&id=549177691667&ns=1&abbucket=4', # '//item.taobao.com/item.htm?id=548443640333&ns=1&abbucket=0#detail'] f = pd.read_csv('women_clothes_sales2.csv') urls = f['link'][0:100] # sh = f['shop_id'][0:3] # s = f['shop'][0:3] # for url in urls: # print(url) # writer.writerow({'店铺ID':f['shop_id'],'店铺名':f['shop']}) keys, values = [], [] # for url in urls: for i in urls: url = 'http:' + i # endswith 判断字符串是否以指定的字符串结尾 if url.endswith('detail'): info = get_taobao_header(url) res = requests.get(url) soup = BeautifulSoup(res.text, "html.parser") attrs = soup.select('.attributes-list li') # 淘宝 class else: info = get_tianmao_header(url) res = requests.get(url) soup = BeautifulSoup(res.text, "html.parser") attrs = soup.select('#J_AttrUL li') # 天猫 id # print('attrs=',attrs) d = get_Details(attrs,info) print(d) # for j in f[shop_id]: # d['店铺ID'] = j # for s in f['shop']: # d['店铺名'] = s #'Shop':d['店铺名'],'Data_id':d['ID'], writer.writerow({'Link':url,'Brand':d['品牌'],'Title':d['宝贝'], 'Price':d['原价'], 'Sale price':d['促销价'], 'Sales':d['月销量'], 'Evaluations':d['累计评价'], 'Component':d['材质成分'], 'Fashion elements':d['流行元素'], 'Sleeve':d['袖长'], 'Seasons':d['年份季节'], 'Sales channels':d['销售渠道类型'], 'Number':d['货号'],'Clothes_Style':d['服装版型'],'Long':d['衣长'],'Collar type':d['领型'], 'Sleeve type':d['袖型'], 'Skirt type':d['裙型'], 'Skirt length':d['裙长'], 'Waist':d['腰型'], 'Combining form':d['组合形式'], 'Outseam':d['裤长'], 'Design':d['图案'], 'Fashion pattern detail':d['服装款式细节'], 'Applicable age':d['适用年龄'], 'Style':d['风格'], 'Commuter':d['通勤'], 'color':d['主要颜色'], 'Size':d['尺码']}) if __name__=='__main__': main()
python的数据类型：1. 数字类型，包括int（整型）、long（长整型）和float（浮点型）。2.字符串，分别是str类型和unicode类型。3.布尔型，Python布尔类型也是用于逻辑运算，有两个值：True（真）和False（假）。4.列表，列表是Python中使用最频繁的数据类型，集合中可以放任何数据类型。5. 元组，元组用”()”标识，内部元素用逗号隔开。6. 字典，字典是一种键值对的集合。7. 集合，集合是一个无序的、不重复的数据组合。
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