宜配屋

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('h1').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('h3').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()

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持【听图阁-专注于Python设计】。