时间

import requests
from bs4 import  BeautifulSoup
import lxml
import re
import time
import random
import pymysql.cursors
from selenium import webdriver
import pandas
import numpy
connection = pymysql.connect(host='localhost',user='root',password='123',db='abc',charset='utf8mb4',cursorclass=pymysql.cursors.DictCursor)

with connection.cursor() as cursor:
    sql = "select * from 竞店"
    cursor.execute(sql)
    shop_id = cursor.fetchall()
connection.commit()
payload = {
    "Ancoding":"gzip, deflate, sdch, br",
"Accept-Language":"zh-CN,zh;q=0.8",
"Connection":"keep-alive",
"Cookie":"hng=; uss=UIMY14A%2B04Bbq%2BqRxS6C9OzJWudsw14Q1kb5mDDqxW%2BQ3YG%2BUcpgrDRWnRQ%3D; uc3=sg2=AC4AfXCJ7XkLw0gCUD1tD9ZxhXFdweN2A6VfybWadxI%3D&nk2=&id2=&lg2=; t=3c0787f77a28e0854ef28fc360b2c555; cookie2=1c912d33e44bdb2008763748702a61f4; _tb_token_=78577371d8136; l=AiQkmjyCyPnG7qTN1Iu5fBqvdCgWvUgn; isg=AvDwL_qYXdDeegACSXGXiIOKwb7f2NSDXgsSOepBvMsepZFPkkmkE0aNixo_; pnm_cku822=; cna=T7gREcWMLDsCAavWmjBJPJpS; Hm_lvt_c478afee593a872fd45cb9a0d7a9da3b=1495496950; Hm_lpvt_c478afee593a872fd45cb9a0d7a9da3b=1495496950",
"Host":"tanggulake.tmall.com",
"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36",
"X-Requested-With":"XMLHttpRequest"}
ues_age=["Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1","Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0,""Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50","Opera/9.80 (Windows NT 6.1; U; zh-cn) Presto/2.9.168 Version/11.50","Mozilla/5.0 (Windows; U; Windows NT 6.1; ) AppleWebKit/534.12 (KHTML, like Gecko) Maxthon/3.0 Safari/534.12","Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.3; .NET4.0C; .NET4.0E)","Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.3; .NET4.0C; .NET4.0E; SE 2.X MetaSr 1.0)","Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.3; .NET4.0C; .NET4.0E)","Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/13.0.782.41 Safari/535.1 QQBrowser/6.9.11079.201","Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)"]
def pig(url):
    url_re = requests.get(url + "1", params=payload)
    soup = BeautifulSoup(url_re.text, "lxml")
    pig = soup.select("div >  div > div > div > span:nth-of-type(1)")
    return (pig[2].text.split("/"))[1]
def xingxi(x):
    ids=[]
    pigg=[]
    dates1=[]
    for pig_id in range(1,int(pig(x))+1):
            ur1 = x + str(pig_id)
            url_re1 = requests.get(ur1, params=payload)
            time.sleep(random.randrange(1,5))
            soup = BeautifulSoup(url_re1.text, "lxml")
            date = soup.select("div > div > div > dl")
            for spid in date:
                ids.append(re.sub("D", "", spid.get("data-id")))

            date = soup.select("div > div > div > dl")
            imgs = soup.select("img")  # 图片
            for imgasd in imgs:
                w = imgasd.get("src")
                p = re.match(r".*//(.*?.jpg)", w)
                pigg.append(r"https://" + p.group(1))
            shuju2 = pandas.DataFrame(pigg)
            shuju2 = shuju2.rename(columns={0: "图片链接"})
            date = soup.select("div > div > div > dl")
            dated = soup.select("dl")  # 获取网页信息
            for i in dated:
                c = list(i.stripped_strings)  # 删除空格
                b = [elem for elem in c if elem != '￥']  # 过滤
                dates1.append([b[0], b[2]])
    shuju2 = pandas.DataFrame(pigg)
    shuju2 = shuju2.rename(columns={0: "图片链接"})
    shuju3 = pandas.DataFrame(ids)
    shuju3 = shuju3.rename(columns={0: "id"})
    shuju1 = pandas.DataFrame(dates1)  # 写入
    shuju1 = shuju1.rename(columns={0: "标题", 1: "价格"})
    return pandas.concat([shuju1, shuju2, shuju3], axis=1)
def how_much(ids,shop_id):
    driver = webdriver.PhantomJS(service_args=['--ignore-ssl-errors=true', '--load-images=false'])
    try:
        driver.get("http://item.taobao.com/item.htm?id=" + ids)
        time.sleep(random.randrange(1, 5))
        date = driver.page_source
    except:
        driver.quit()
        driver = webdriver.PhantomJS(service_args=['--ignore-ssl-errors=true', '--load-images=false'])
        driver.get("http://item.taobao.com/item.htm?id=" +ids)
        date = driver.page_source
    time.sleep(random.randrange(8,13))
    soup = BeautifulSoup(date, "lxml")
    a = [i for i in list(soup.select("script")) if len(str(i)) > 1000]
    new_time = re.findall(r".*dbst:(.d*)", str(a[0]).replace(" ", ""))[0][0:10]
    return time.strftime("%Y-%m-%d", time.localtime(int(new_time)))
for dress in shop_id:

    with connection.cursor() as cursors:
        # Create a new
        sql = 'select id from' + " " + dress["店铺名称"]
        cursors.execute(sql)
        fff = cursors.fetchall()
        fff = [i["id"] for i in fff]
        for i in fff:
            with connection.cursor() as cursorss:
                dates = how_much(i, dress["店铺名称"])
                sql = "UPDATE " + dress["店铺名称"] + " set 上架时间= '%s' where id = '%s'" % (dates,i)
                print(sql)
                cursorss.execute(sql)
            connection.commit()