Go微服务入门到容器化实践，落地可观测的微服务电商项目【完结】

概述download:Go微服务入门到容器化实践，落地可观测的微服务电商项目【完结】对于真正微服务项目来说，服务开发只是第一步，容器化、d性伸缩和可观测才是真正关键。本课程将通过电商项目实战，系统学习完全形态的微服务，掌握成熟闭环的落地方案。技术要求有Go实际开发经验掌握Linux *** 作 download:Go微服务入门到容器化实践，落地可观测的微服务电商项目【完结】

对于真正微服务项目来说，服务开发只是第一步，容器化、d性伸缩和可观测才是真正关键。本课程将通过电商项目实战，系统学习完全形态的微服务，掌握成熟闭环的落地方案。
技术要求
有Go实际开发经验 掌握linux *** 作 熟练掌握MysqL
环境参数
开发语言：Golang 开发平台：windows 10 开发工具：Goland

#!/usr/bin/python
from bs4 import BeautifulSoup
import requests
def getHouseList(url):
house =[]
headers = {'User-Agent':'Mozilla/5.0 (windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBbroWSER'}
#get从网页获取信息
res = requests.get(url,headers=headers)
#解析内容
soup = BeautifulSoup(res.content,'lxml')
#房源Title
housename_divs = soup.findall('div',class='Title')
for housename_div in housename_divs:
housename_as=housename_div.find_all('a')
for housename_a in housename_as:
housename=[]
#标题
housename.append(housename_a.get_text())
#超链接
housename.append(housename_a['href'])
house.append(housename)
huseinfo_divs = soup.findall('div',class='houseInfo')
for i in range(len(huseinfo_divs)):
info = huseinfo_divs[i].get_text()
infos = info.split('|')
#小区称号
house[i].append(infos[0])
#户型
house[i].append(infos[1])
#平米
house[i].append(infos[2])
#查询总价
house_prices = soup.findall('div',class='totalPrice')
for i in range(len(house_prices)):
#价钱
price = house_prices[i].get_text()
house[i].append(price)
return house
#爬取房屋细致信息：所在区域、套内面积
def houseinfo(url):
headers = {'User-Agent':'Mozilla/5.0 (windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBbroWSER'}
res = requests.get(url,headers=headers)
soup = BeautifulSoup(res.content,'lxml')
msg =[]
#所在区域
areainfos = soup.findall('span',class='info')
for areainfo in areainfos:
#只需求获取第一个a标签的内容即可
area = areainfo.find('a')
if(not area):
continue
hrefStr = area['href']
if(hrefStr.startswith('JavaScript')):
continue
msg.append(area.get_text())
break
#依据房屋户型计算套内面积
infoList = soup.find_all('div',ID='infoList')
num = []
for info in infoList:
cols = info.findall('div',class='col')
for i in cols:
Pingmi = i.get_text()
try:
a = float(Pingmi[:-2])
num.append(a)
except ValueError:
continue
msg.append(sum(num))
return msg
#将房源信息写入txt文件
def writefile(houseinfo):
f = open('d:/房源.txt','a',enCoding='utf8')

houseinfo.join('\n')

f.write(houseinfo+'\n')f.close()

#主函数
def main():
for i in range(1,100):
print('-----分隔符',i,'-------')
if i==1:
url ='https://sjz.lianjia.com/ershoufang/hy1f2f5sf1l3l2l4a2a3a4/'
else:
url='https://sjz.lianjia.com/ershoufang/pg'+str(i)+'hy1f2f5sf1l3l2l4a2a3a4/'
houses =getHouseList(url)
for house in houses:
link = house[1]
if(not link.startswith('http')):
continue
mianji = houseinfo(link)
#将套内面积、所在区域增加到房源信息
house.extend(mianji)
print(house)
info = " ".join([str(x) for x in house])
writefile(info)
if name == 'main':
main()
从链家网站查询到8849条房源信息，但是页面只能显现31（每页数量）*100（总页码）=3100条房源，其他没找到。

第二版:

获取某个小区的房源信息，并写入excel。

#!/usr/bin/python
from bs4 import BeautifulSoup
import requests
import xlwt
def getHouseList(url):
house =[]
headers = {'User-Agent':'Mozilla/5.0 (windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBbroWSER'}
#get从网页获取信息
res = requests.get(url,headers=headers)
#解析内容
soup = BeautifulSoup(res.content,'HTML.parser')
#房源Title
housename_divs = soup.findall('div',class='Title')
for housename_div in housename_divs:
housename_as=housename_div.find_all('a')
for housename_a in housename_as:
housename=[]
#标题
housename.append(housename_a.get_text())
#超链接
housename.append(housename_a.get('href'))
house.append(housename)
huseinfo_divs = soup.findall('div',class='houseInfo')
for i in range(len(huseinfo_divs)):
info = huseinfo_divs[i].get_text()
infos = info.split('|')
#小区称号
house[i].append(infos[0])
#户型
house[i].append(infos[1])
#平米
house[i].append(infos[2])
#查询总价
house_prices = soup.findall('div',class='totalPrice')
for i in range(len(house_prices)):
#价钱
price = house_prices[i].get_text()
house[i].append(price)
return house
#爬取房屋细致信息：所在区域、套内面积
def houseinfo(url):
headers = {'User-Agent':'Mozilla/5.0 (windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBbroWSER'}
res = requests.get(url,headers=headers)
soup = BeautifulSoup(res.content,'HTML.parser')
msg =[]
#所在区域
areainfos = soup.findall('span',class='info')
for areainfo in areainfos:
#只需求获取第一个a标签的内容即可
area = areainfo.find('a')
if(not area):
continue
hrefStr = area['href']
if(hrefStr.startswith('JavaScript')):
continue
msg.append(area.get_text())
break
#依据房屋户型计算套内面积
infoList = soup.find_all('div',ID='infoList')
num = []
for info in infoList:
cols = info.findall('div',class='col')
for i in cols:
Pingmi = i.get_text()
try:
a = float(Pingmi[:-2])
num.append(a)
except ValueError:
continue
msg.append(sum(num))
return msg
#将房源信息写入excel文件
def writeExcel(excelPath,houses):
workbook = xlwt.Workbook()
#获取第一个sheet页
sheet = workbook.add_sheet('git')
row0=['标题','链接地址','户型','面积','朝向','总价','所属区域','套内面积']
for i in range(0,len(row0)):
sheet.write(0,i,row0[i])
for i in range(0,len(houses)):
house = houses[i]
print(house)
for j in range(0,len(house)):
sheet.write(i+1,j,house[j])
workbook.save(excelPath)
#主函数
def main():

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