Python查询天气预报

一. 实现过程

1.1 查询外网IP

通过这个网址查询到外网IP http://ip.dnsexit.com/index.php

1.2 查询IP所在省份和城市

通过这个地址查询到IP所在省份和城市 http://int.dpool.sina.com.cn/iplookup/iplookup.php?format=json&ip=54.54.194.134

1.3 查询所在城市的天气URL

所在省份和城市, 查找到城市天气的URL

1.4 查询所在城市的天气情况.

通过这个网址查询天气的URL查询天气信息

http://m.weather.com.cn/data/101280101.html

(前面3个步骤都是为了这一步准备)

二. 实现技术

2.1 网页数据抓取与提取

所有网页数据通过Python抓取, 然后使用正则表达式或者BeautifulSoup或者json来解析.

2.2 城市天气URL的获取

利用这个网站上的信息http://www.weather.com.cn/

先获得城市的省份URL, 在通过省份信息获得该城市的URL

2.3 天气信息的获得

利用这个网站上的信息http://www.weather.com.cn/

使用json解析.

三. 实现

3.1 查询外网IP

这个简单

#!/usr/bin/env python# coding=utf-8# Python 2.7.3# File: GetIP.py# 获得外网IP地址import urllib2import httplibdef GetIP():response = urllib2.urlopen('http://ip.dnsexit.com/index.php')htmlStr = response.read()return htmlStr'''# 测试代码print GetIP()'''

3.2 获得IP所在省份和城市

这个也很简单

#!/usr/bin/env python# coding=utf-8# Python 2.7.3# File: GetCity.py# 获取IP所在国家/省份/城市import urllib2import httplibimport json'''返回信息的结构{"ret":1,"start":"54.52.163.0","end":"54.57.3.255","country":"美国","province":"新泽西州","city":"Woodbridge","district":"","isp":"联通","type":"","desc":""}'''def GetCity(ip, city):response = urllib2.urlopen('http://int.dpool.sina.com.cn/iplookup/iplookup.php?format=json&ip=' + ip)htmlStr = response.read()cityInfo = htmlStr.decode("unicode-escape");st = json.loads(cityInfo);city[0] = st["country"]city[1] = st["province"]city[2] = st["city"]'''# 测试代码city = ["", "", ""]GetCity("54.54.194.134", city)print city'''

3.3 获取城市的天气的URL

先获得省份信息, 在查找城市信息.

3.3.1 获得省份URL

看这个网址 http://www.weather.com.cn/textFC/hb.shtml

分析html(保存为GetCityID1.html)知道 <div class="lqcontentBoxheader">包含省份信息. 由于这个html比较复杂和有些字符不是唯一的, 所以这里使用的是BeautifulSoup分析.

3.3.2 获得城市URL

上面步骤获得省份URL后, 例如 http://www.weather.com.cn/textFC/xizang.shtml

分析html(保存为GetCityID2.html)知道 <div class="hanml"> 包含城市URL信息. 同样使用BeautifulSoup分析.

这里获得的URL是这样的格式 http://www.weather.com.cn/weather/101280101.shtml 你需要修改成这样的格式http://m.weather.com.cn/data/101280101.html

3.3.3 实现代码

这个代码有一个明显的缺点, 就是运行速度很慢(一个是网站数据比较多所以慢, 还有就是BeautifulSoup分析也有一点慢(HTML的数据太多了)). 所以动态或者这个就比较慢了, 先把这些URL下载再来保存到本地也是一个好方法.

#!/usr/bin/env python# coding=utf-8# Python 2.7.3# File: GetCityID.py# 获取城市的天气的URL地址import urllib2import HTMLParserimport httplibfrom bs4 import BeautifulSoupdef GetProvinceURL(province):response = urllib2.urlopen('http://www.weather.com.cn/textFC/hn.shtml')htmlByte = response.read()htmlStr = htmlByte.decode("utf8")soup2 = BeautifulSoup(htmlStr)div = soup2.find("div", class_ = "lqcontentBoxheader")lista = div.find_all("a")provinceURL = "http://www.weather.com.cn"for aItem in lista:if aItem.text == province:provinceURL = provinceURL + aItem["href"]breakreturn provinceURLdef GetCityURL(provinceURL, city):response = urllib2.urlopen(provinceURL)htmlByte = response.read()htmlStr = htmlByte.decode("utf8")soup2 = BeautifulSoup(htmlStr)div = soup2.find("div", class_ = "hanml")lista = div.find_all("a", text = city)cityURL = lista[0]["href"].replace("www.weather.com.cn/weather", "m.weather.com.cn/data")cityURL = cityURL.replace("shtml", "html")return cityURL'''# GetProvinceURL 测试代码print GetProvinceURL(u"广东")'''# GetProvinceURL 测试代码provinceURL = GetProvinceURL(u"广东")print provinceURLcityURL = GetCityURL(provinceURL, u"广州")print cityURL

3.4 天气数据的获取

3.4.1 天气数据的解析

从获http://m.weather.com.cn/data/101280101.html得到的数据是Json格式, 需要进行解析. (有了这些数据, 你喜欢怎么显示都可以了)

{"weatherinfo":{"city":"广州","city_en":"guangzhou","date_y":"2013年11月29日","date":"","week":"星期五","fchh":"11","cityid":"101280101","temp1":"18℃~5℃","temp2":"20℃~7℃","temp3":"21℃~8℃","temp4":"21℃~9℃","temp5":"22℃~10℃","temp6":"23℃~10℃","tempF1":"64.4℉~41℉","tempF2":"68℉~44.6℉","tempF3":"69.8℉~46.4℉","tempF4":"69.8℉~48.2℉","tempF5":"71.6℉~50℉","tempF6":"73.4℉~50℉","weather1":"晴","weather2":"晴","weather3":"晴","weather4":"晴","weather5":"晴","weather6":"晴","img1":"0","img2":"99","img3":"0","img4":"99","img5":"0","img6":"99","img7":"0","img8":"99","img9":"0","img10":"99","img11":"0","img12":"99","img_single":"0","img_title1":"晴","img_title2":"晴","img_title3":"晴","img_title4":"晴","img_title5":"晴","img_title6":"晴","img_title7":"晴","img_title8":"晴","img_title9":"晴","img_title10":"晴","img_title11":"晴","img_title12":"晴","img_title_single":"晴","wind1":"北风3-4级转微风","wind2":"微风","wind3":"微风","wind4":"微风","wind5":"微风","wind6":"微风","fx1":"北风","fx2":"微风","fl1":"3-4级转小于3级","fl2":"小于3级","fl3":"小于3级","fl4":"小于3级","fl5":"小于3级","fl6":"小于3级","index":"较冷","index_d":"建议着大衣、呢外套加毛衣、卫衣等服装。体弱者宜着厚外套、厚毛衣。因昼夜温差较大，注意增减衣服。","index48":"较冷","index48_d":"建议着大衣、呢外套加毛衣、卫衣等服装。体弱者宜着厚外套、厚毛衣。因昼夜温差较大，注意增减衣服。","index_uv":"中等","index48_uv":"中等","index_xc":"适宜","index_tr":"适宜","index_co":"舒适","st1":"16","st2":"6","st3":"19","st4":"8","st5":"20","st6":"9","index_cl":"不宜","index_ls":"适宜","index_ag":"易发"}}

#!/usr/bin/env python# coding=utf-8# Python 2.7.3# File: GetCityWeather.py# 获得城市天气数据import urllib2import httplibimport jsondef GetCityWeather(cityURL):response = urllib2.urlopen(cityURL)htmlByte = response.read()htmlStr = htmlByte.decode("utf8")st = json.loads(htmlStr);return st'''# http://m.weather.com.cn/data/101280101.html{"weatherinfo":{"city":"广州","city_en":"guangzhou","date_y":"2013年11月29日","date":"","week":"星期五","fchh":"11","cityid":"101280101","temp1":"18℃~5℃","temp2":"20℃~7℃","temp3":"21℃~8℃","temp4":"21℃~9℃","temp5":"22℃~10℃","temp6":"23℃~10℃","tempF1":"64.4℉~41℉","tempF2":"68℉~44.6℉","tempF3":"69.8℉~46.4℉","tempF4":"69.8℉~48.2℉","tempF5":"71.6℉~50℉","tempF6":"73.4℉~50℉","weather1":"晴","weather2":"晴","weather3":"晴","weather4":"晴","weather5":"晴","weather6":"晴","img1":"0","img2":"99","img3":"0","img4":"99","img5":"0","img6":"99","img7":"0","img8":"99","img9":"0","img10":"99","img11":"0","img12":"99","img_single":"0","img_title1":"晴","img_title2":"晴","img_title3":"晴","img_title4":"晴","img_title5":"晴","img_title6":"晴","img_title7":"晴","img_title8":"晴","img_title9":"晴","img_title10":"晴","img_title11":"晴","img_title12":"晴","img_title_single":"晴","wind1":"北风3-4级转微风","wind2":"微风","wind3":"微风","wind4":"微风","wind5":"微风","wind6":"微风","fx1":"北风","fx2":"微风","fl1":"3-4级转小于3级","fl2":"小于3级","fl3":"小于3级","fl4":"小于3级","fl5":"小于3级","fl6":"小于3级","index":"较冷","index_d":"建议着大衣、呢外套加毛衣、卫衣等服装。体弱者宜着厚外套、厚毛衣。因昼夜温差较大，注意增减衣服。","index48":"较冷","index48_d":"建议着大衣、呢外套加毛衣、卫衣等服装。体弱者宜着厚外套、厚毛衣。因昼夜温差较大，注意增减衣服。","index_uv":"中等","index48_uv":"中等","index_xc":"适宜","index_tr":"适宜","index_co":"舒适","st1":"16","st2":"6","st3":"19","st4":"8","st5":"20","st6":"9","index_cl":"不宜","index_ls":"适宜","index_ag":"易发"}}''''''# GetCityWeather测试代码# GetProvinceURL 测试代码cityURL = "http://m.weather.com.cn/data/101280101.html"st = GetCityWeather(cityURL)ss = st["weatherinfo"]print ss["city"]print ss["date_y"]print ss["week"]print ss["temp1"]print ss["weather1"]''''''# 输出广州2013年11月29日星期五18℃~5℃晴'''

3.5 主程序代码

#!/usr/bin/env python# coding=utf-8# Python 2.7.3import GetIPimport GetCityimport GetCityIDimport GetCityWeatherip = GetIP.GetIP()print ip# 国家/省份/城市city = ["", "", ""]GetCity.GetCity(ip, city)print city[0], city[1], city[2] provinceURL = GetCityID.GetProvinceURL(city[1])cityURL = GetCityID.GetCityURL(provinceURL, city[2])print provinceURLprint cityURLst = GetCityWeather.GetCityWeather(cityURL)ss = st["weatherinfo"]print ss["city"]print ss["date_y"]print ss["week"]print ss["temp1"]print ss["weather1"]

这两段代码运行的非常慢

provinceURL = GetCityID.GetProvinceURL(city[1])

cityURL = GetCityID.GetCityURL(provinceURL, city[2])

四. 小结

4.1 国外的城市可能查不到, 因为天气数据依赖于http://www.weather.com.cn/

4.2 获取城市url的速度实在太慢了. 的确先提取保存可能会更快吧.

4.3 通过实现这样的功能, 了解了json.

4.4 网上有很多有用的数据, 特别是一些动态的海量的数据, 你不可能手动去取, 就看你能不能抓, 找出规律, 两手抓, 两手都要硬

4.5 本文是参考http://blog.csdn.net/x_iya/article/details/8583015