设计欣赏,玉堂娇,光盘行动图片
本人初学python是菜鸟级，写的不好勿喷。
python爬虫用了比较简单的urllib.parse和requests，把爬来的数据显示在地图上。接下里我们话不多说直接上代码:
1.安装python环境和编辑器（自行度娘）
2.本人以58品牌公寓为例，爬取在杭州地区价格在2000-4000的公寓。
#-*- coding:utf-8 -*- from bs4 import beautifulsoup from urllib.parse import urljoin import requests import csv import time
以上是需要引入的模块
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url = "http://hz.58.com/pinpaigongyu/pn/{page}/?minprice=2000_4000"
#已完成的页数序号，初时为0
page = 0
以上的全局变量
csv_file = open(r"c:\users\****\desktop\houosenew.csv","a+",newline='') csv_writer = csv.writer(csv_file, delimiter=',')
自定义某个位置来保存爬取得数据，本人把爬取得数据保存为csv格式便于编辑（其中”a+”表示可以多次累加编辑在后面插入数据，建议不要使用“wb”哦！newline=”表示没有隔行）
while true:
#为了防止网站屏蔽ip，设置了时间定时器每隔5秒爬一下。打完一局农药差不多都爬取过来了。
time.sleep(5)
page +=1
#替换url中page变量
print (url.format(page=page)+"ok")
response = requests.get(url.format(page=page))
html=beautifulsoup(response.text)
#寻找html中dom节点li
house_list = html.select(".list > li")
# 循环在读不到新的房源时结束
if not house_list:
break
for house in house_list:
#根据hml的dom节点获取自己需要的数据
house_title = house.select("h2")[0].string
house_url = urljoin(url, house.select("a")[0]["href"])
house_pic = urljoin(url, house.select("img")[0]["lazy_src"])
house_info_list = house_title.split()
# 如果第一列是公寓名 则取第二列作为地址
if "公寓" in house_info_list[0] or "青年社区" in house_info_list[0]:
house_location = house_info_list[0]
else:
house_location = house_info_list[1]
house_money = house.select(".money")[0].select("b")[0].string
csv_writer.writerow([house_title, house_location, house_money,house_pic ,house_url])
#最后不要忘记关闭节流
csv_file.close()
如果网站屏蔽了你的ip，你可以做一个ip地址数组放在http的头部具体度娘一下吧。
接下来我们写html
只是简单的写了一下写的不好见谅。用的是高德地图，具体的js api可以到高德开发者上去看。
<body>
<div id="container"></div>
<div class="control-panel">
<div class="control-entry">
<label>选择工作地点：</label>
<div class="control-input">
<input id="work-location" type="text">
</div>
</div>
<div class="control-entry">
<label>选择通勤方式：</label>
<div class="control-input">
<input type="radio" name="vehicle" value="subway,bus" onclick="takebus(this)" checked/> 公交+地铁
<input type="radio" name="vehicle" value="subway" onclick="takesubway(this)"/> 地铁
<input type="radio" name="vehicle" value="walk" onclick="takewalk(this)"/> 走路
<input type="radio" name="vehicle" value="bike" onclick="takebike(this)"/> 骑车
</div>
</div>
<div class="control-entry">
<label>导入房源文件：</label>
<div class="control-input">
<input type="file" name="file" id="filecsv"/>
<button style="margin-top: 10px;width: 50%;" onclick="changecsv()">开始</button>
</div>
</div>
</div>
<div id="transfer-panel"></div>
<script>
var map = new amap.map("container", {
resizeenable: true,
zoomenable: true,
center: [120.1256856402492, 30.27289264553506],
zoom: 12
});
//添加标尺
var scale = new amap.scale();
map.addcontrol(scale);
//公交到达圈对象
var arrivalrange = new amap.arrivalrange();
//经度，纬度，时间（用不到），通勤方式（默认是地铁＋公交+走路+骑车）
var x, y, t, vehicle = "subway,bus";
//工作地点，工作标记
var workaddress, workmarker;
//房源标记队列
var rentmarkerarray = [];
//多边形队列，存储公交到达的计算结果
var polygonarray = [];
//路径规划
var amaptransfer;
//信息窗体对象
var infowindow = new amap.infowindow({
offset: new amap.pixel(0, -30)
});
//地址补完的使用
var auto = new amap.autocomplete({
//通过id指定输入元素
input: "work-location"
});
//添加事件监听，在选择补完的地址后调用worklocationselected
amap.event.addlistener(auto, "select", worklocationselected);
function takebus(radio) {
vehicle = radio.value;
loadworklocation()
}
function takesubway(radio) {
vehicle = radio.value;
loadworklocation()
}
function takewalk(radio){
vehicle = radio.value;
loadworklocation()
}
function takebike(radio) {
vehicle = radio.value;
loadworklocation()
}
//获取加载的文件
function changecsv() {
$("#filecsv").csv2arr(function (res) {
$.each(res, function (k, p) {
if (res[k][1]) {
//addmarkerbyaddress(地址，价格，展示的图片)
addmarkerbyaddress(res[k][1], res[k][2],res[k][3])
}
})
});
}
function worklocationselected(e) {
workaddress = e.poi.name;
loadworklocation();
}
function loadworkmarker(x, y, locationname) {
workmarker = new amap.marker({
map: map,
title: locationname,
icon: 'http://webapi.amap.com/theme/v1.3/markers/n/mark_r.png',
position: [x, y]
});
}
function loadworkrange(x, y, t, color, v) {
arrivalrange.search([x, y], t, function (status, result) {
if (result.bounds) {
for (var i = 0; i < result.bounds.length; i++) {
//新建多边形对象
var polygon = new amap.polygon({
map: map,
fillcolor: color,
fillopacity: "0.4",
strokecolor: color,
strokeopacity: "0.8",
strokeweight: 1
});
//得到到达圈的多边形路径
polygon.setpath(result.bounds[i]);
polygonarray.push(polygon);
}
}
}, {
policy: v
});
}
function addmarkerbyaddress(address, money,imgurl) {
var geocoder = new amap.geocoder({
city: "杭州",
radius: 1000
});
geocoder.getlocation(address, function (status, result) {
var iconvalue = "";
var _money=money;
if (money.indexof("-") > -1) {
_money = money.split("-")[1];
}
//如果价格高于3000元/月在地图上显示红色，低于的话显示蓝色
if (parsefloat(_money) > 3000) {
iconvalue="http://webapi.amap.com/theme/v1.3/markers/n/mark_r.png";
}else{
iconvalue = "http://webapi.amap.com/theme/v1.3/markers/n/mark_b.png";
}
if (status === "complete" && result.info === 'ok') {
var geocode = result.geocodes[0];
rentmarker = new amap.marker({
map: map,
title: address,
icon:iconvalue,
animation:"amap_animation_drop",
position: [geocode.location.getlng(), geocode.location.getlat()]
})
;
rentmarkerarray.push(rentmarker);
//鼠标点击标记显示相应的内容
rentmarker.content = "<img src='"+imgurl+"'/><div>房源：<a target = '_blank' href='http://bj.58.com/pinpaigongyu/?key=" + address + "'>" + address + "</a><p>价格:"+money+"</p><div>"
rentmarker.on('click', function (e) {
infowindow.setcontent(e.target.content);
infowindow.open(map, e.target.getposition());
if (amaptransfer) amaptransfer.clear();
amaptransfer = new amap.transfer({
map: map,
policy: amap.transferpolicy.least_time,
city: "杭州市",
panel: 'transfer-panel'
});
amaptransfer.search([{
keyword: workaddress
}, {
keyword: address
}], function (status, result) {
})
});
}
})
}
function delworklocation() {
if (polygonarray) map.remove(polygonarray);
if (workmarker) map.remove(workmarker);
polygonarray = [];
}
function delrentlocation() {
if (rentmarkerarray) map.remove(rentmarkerarray);
rentmarkerarray = [];
}
function loadworklocation() {
//首先清空地图上已有的到达圈
delworklocation();
var geocoder = new amap.geocoder({
city: "杭州",
radius: 1000
});
geocoder.getlocation(workaddress, function (status, result) {
if (status === "complete" && result.info === 'ok') {
var geocode = result.geocodes[0];
x = geocode.location.getlng();
y = geocode.location.getlat();
//加载工作地点标记
loadworkmarker(x, y);
//加载60分钟内工作地点到达圈
loadworkrange(x, y, 60, "#3f67a5", vehicle);
//地图移动到工作地点的位置
map.setzoomandcenter(12, [x, y]);
}
})
}
</script>
</body>
想要获取完整的代码github：https://github.com/divibear/pythondemo.git
新手上路，老司机们勿喷！
以上所述是小编给大家介绍的python爬虫租房信息在地图上显示的方法详解整合，希望对大家有所帮助
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