python-爬虫58租房数据在高德地图上显示

先上图

我的环境python2.7
运行后生产csv文件rent.cvs,内容为58同城品牌合租爬取的合租房源数据
使用火狐浏览器访问（谷歌浏览器加载csv时显示跨域问题）

爬取网站：http://bj.58.com/pinpaigongyu/pn/5/?minprice=2000_4000

抓取代码：

#!usr/bin/python
# -*- coding: utf-8 -*-

from bs4 import BeautifulSoup
import requests
import csv
import codecs
import sys
reload(sys)
sys.setdefaultencoding('utf-8')

url = "http://bj.58.com/pinpaigongyu/pn/{page}/?minprice=2000_4000"

'''已完成的页数序号，初时为0'''
page = 0

csv_file = open("rent.csv","w")
csv_file.write(codecs.BOM_UTF8)
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, "html.parser")
    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
        house_url = "http://bj.58.com/%s"%(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
        print 'house_title=', house_title, 'house_location=', house_location
        csv_writer.writerow([house_title, house_location, house_money, house_url])

csv_file.close()

运行python脚本，抓取过程...

将抓取数据存入csv文件：

页面js代码：

var map = new AMap.Map("container", {
            resizeEnable: true,
            zoomEnable: true,
            center: [116.397428, 39.90923],
            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: "北京",
        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 = "
房源：" + address + "
"
            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: "北京市",
                    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: "北京",
        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) {
	//	console.log(data);
    //    data = data.split("\n");
    //    data.forEach(function(item, index) {
    //        rent_locations.add(item.split(",")[1]);
    //    });
    //    rent_locations.forEach(function(element, index) {
    //        addMarkerByAddress(element);
    //    });
    //});
	
	
	$.ajax({
               url: fileName,
               contentType: "text/plain; charset=utf-8",
                
                type: "post",
                dataType: 'text',
                success: function (data) {
                    console.log(data);
					data = data.split("\n");
					data.forEach(function(item, index) {
						rent_locations.add(item.split(",")[1]);
					});
					rent_locations.forEach(function(element, index) {
						addMarkerByAddress(element);
					});
                }
            });
}

全部源码下载：

https://download.csdn.net/download/ardo_pass/10648354