租房问题一直是在外奋斗的人很头疼的问题，尤其对于刚毕业出校的大学生，如何在价格、舒适、上班距离等各方面因素中选择一个最适合自己的答案。之前以深圳为例，发过深圳租房简明分析，但在适用性方面还存在很多问题，在知乎上看到有分享高德api和python解决租房问题，因此记录下来，方便更多人学习，项目课地址：高德API+Python解决租房问题。
整体项目主要分为两部分，即使用python抓取租房数据和使用高德api及数据可视化查看租房信息。
一.python 代码
python代码使用了beautifulsoup、requests、csv库，最终会在本地生成rent.csv文件，保存抓取到的租房数据。
#-*- coding:utf-8 -*- from bs4 import BeautifulSoup from urlparse import urljoin import requests import csv ＃深圳租房信息地址，价格区间1000-4000，数据来源58品牌公寓 url = "http://sz.58.com/pinpaigongyu/pn/{page}/?minprice=1000_4000" #已完成的页数序号，初时为0 page = 0 ＃保存文件 csv_file = open("rent.csv","wb") csv_writer = csv.writer(csv_file, delimiter=',') while True: page += 1 print "fetch: ", url.format(page=page) response = requests.get(url.format(page=page)) html = BeautifulSoup(response.text) 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: house_title = house.select("h2")[0].string.encode("utf8") house_url = urljoin(url, house.select("a")[0]["href"]) house_info_list = house_title.split() # 如果第二列是公寓名则取第一列作为地址 if "公寓" in house_info_list[1] or "青年社区" in house_info_list[1]: house_location = house_info_list[0] else: house_location = house_info_list[1] house_money = house.select(".money")[0].select("b")[0].string.encode("utf8") csv_writer.writerow([house_title, house_location, house_money, house_url]) csv_file.close() 二.html及js代码index.html代码如下，通过调用高德api生成地图，在窗体上添加一个选择框体。
<html> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="initial-scale=1.0, user-scalable=no, width=device-width"> <title>毕业生租房</title> <link rel="stylesheet" href="http://cache.amap.com/lbs/static/main1119.css" /> <link rel="stylesheet" href="http://cache.amap.com/lbs/static/jquery.range.css" /> <script src="http://cache.amap.com/lbs/static/jquery-1.9.1.js"></script> <script src="http://cache.amap.com/lbs/static/es5.min.js"></script> <script src="http://webapi.amap.com/maps?v=1.3&key=5407348a92a67591a9f03dcfab278f0d&plugin=AMap.ArrivalRange,AMap.Scale,AMap.Geocoder,AMap.Transfer,AMap.Autocomplete"></script> <script src="http://cache.amap.com/lbs/static/jquery.range.js"></script> <style> .control-panel { position: absolute; top: 30px; right: 20px; } .control-entry { width: 280px; background-color: rgba(119, 136, 153, 0.8); font-family: fantasy, sans-serif; text-align: left; color: white; overflow: auto; padding: 10px; margin-bottom: 10px; } .control-input { margin-left: 120px; } .control-input input[type="text"] { width: 160px; } .control-panel label { float: left; width: 120px; } #transfer-panel { position: absolute; background-color: white; max-height: 80%; overflow-y: auto; top: 30px; left: 20px; width: 250px; } </style> </head> <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 </div> </div> <div class="control-entry"> <label>导入房源文件：</label> <div class="control-input"> <input type="file" name="file" onChange="importRentInfo(this)" /> </div> </div> </div> <div id="transfer-panel"></div> <script src="rent.js"></script> </body> </html>rent.js代码如下，完成对事件的监听和功能调用。
var map = new AMap.Map("container", { resizeEnable: true, zoomEnable: true, center: [114.085947, 22.547], zoom: 11 }); var scale = new AMap.Scale(); map.addControl(scale); var arrivalRange = new AMap.ArrivalRange(); var x, y, t, vehicle = "SUBWAY,BUS"; var workAddress, workMarker; var rentMarkerArray = []; var polygonArray = []; var amapTransfer; var infoWindow = new AMap.InfoWindow({ offset: new AMap.Pixel(0, -30) }); var auto = new AMap.Autocomplete({ input: "work-location" }); AMap.event.addListener(auto, "select", workLocationSelected); function takeBus(radio) { vehicle = radio.value; loadWorkLocation() } function takeSubway(radio) { vehicle = radio.value; loadWorkLocation() } function importRentInfo(fileInfo) { var file = fileInfo.files[0].name; loadRentLocationByFile(file); } 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++) { var polygon = new AMap.Polygon({ map: map, fillColor: color, fillOpacity: "0.4", strokeColor: color, strokeOpacity: "0.8", strokeWeight: 1 }); polygon.setPath(result.bounds[i]); polygonArray.push(polygon); } } }, { policy: v }); } function addMarkerByAddress(address) { var geocoder = new AMap.Geocoder({ city: "深圳", radius: 1000 }); geocoder.getLocation(address, function(status, result) { if (status === "complete" && result.info === 'OK') { var geocode = result.geocodes[0]; rentMarker = new AMap.Marker({ map: map, title: address, icon: 'http://webapi.amap.com/theme/v1.3/markers/n/mark_b.png', position: [geocode.location.getLng(), geocode.location.getLat()] }); rentMarkerArray.push(rentMarker); rentMarker.content = "<div>房源：<a target = '_blank' href='http://sz.58.com/pinpaigongyu/?key=" + address + "'>" + address + "</a><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: "深圳市", 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() { delWorkLocation(); var geocoder = new AMap.Geocoder({ city: "深圳", 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(); loadWorkMarker(x, y); loadWorkRange(x, y, 60, "#3f67a5", vehicle); map.setZoomAndCenter(12, [x, y]); } }) } function loadRentLocationByFile(fileName) { delRentLocation(); var rent_locations = new Set(); $.get(fileName, function(data) { data = data.split("\n"); data.forEach(function(item, index) { rent_locations.add(item.split(",")[1]); }); rent_locations.forEach(function(element, index) { addMarkerByAddress(element); }); }); }三.结果展示 使用本地的webstorm打开页面

输入工作地点为深圳北站，红色标记为工作地点，阴影为距离工作地点一小时的区域
倒入之前使用python得到的房源文件，蓝色为可选择的房源
点击任一蓝色标记，可查看其距离工作地点的路径及时长，点击房源即可跳转至58的房源链接
