这时网址为：http://flights.ctrip.com/booking/can-ctu-day-1.html?ddate1=2018-06-15
其中，can 表示广州，ctu 表示成都，日期 “2018-06-15”就比较明显了。一般的爬虫，只有替换这几个值，就可以遍历了。但观察发现，有个链接可以看到当前网页的所有json格式的数据。如下
同样可以看到城市和日期，该连接打开的是 json 文件，里面存储的就是当前页面的数据。显示如下，其中 "fis" 则是航班信息。
每一次爬取只要替换城市代码和日期即可，城市代码自己手动整理了一份：
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city={"yie":"阿尔山","aku":"阿克苏","rht":"阿拉善右旗","axf":"阿拉善左旗","aat":"阿勒泰","ngq":"阿里","mfm":"澳门"
,"aqg":"安庆","ava":"安顺","aog":"鞍山","rlk":"巴彦淖尔","aeb":"百色","bav":"包头","bsd":"保山","bhy":"北海","bjs":"北京"
,"dbc":"白城","nbs":"白山","bfj":"毕节","bpl":"博乐","ckg":"重庆","bpx":"昌都","cgd":"常德","czx":"常州"
,"chg":"朝阳","ctu":"成都","juh":"池州","cif":"赤峰","swa":"潮州","cgq":"长春","csx":"长沙","cih":"长治","cde":"承德"
,"cwj":"沧源","dax":"达州","dlu":"大理","dlc":"大连","dqa":"大庆","dat":"大同","ddg":"丹东","dcy":"稻城","doy":"东营"
,"dnh":"敦煌","dax":"达县","lum":"德宏","ejn":"额济纳旗","dsn":"鄂尔多斯","enh":"恩施","erl":"二连浩特","fuo":"佛山"
,"foc":"福州","fyj":"抚远","fug":"阜阳","kow":"赣州","goq":"格尔木","gyu":"固原","gys":"广元","can":"广州","kwe":"贵阳"
,"kwl":"桂林","hrb":"哈尔滨","hmi":"哈密","hak":"海口","hld":"海拉尔","hdg":"邯郸","hzg":"汉中","hgh":"杭州","hfe":"合肥"
,"htn":"和田","hek":"黑河","het":"呼和浩特","hia":"淮安","hjj":"怀化","txn":"黄山","huz":"惠州","jxa":"鸡西","tna":"济南"
,"jng":"济宁","jgd":"加格达奇","jmu":"佳木斯","jgn":"嘉峪关","swa":"揭阳","jic":"金昌","knh":"金门","jnz":"锦州"
,"cyi":"嘉义","jhg":"景洪","jsj":"建三江","jjn":"晋江","jgs":"井冈山","jdz":"景德镇","jiu":"九江","jzh":"九寨沟","khg":"喀什"
,"kjh":"凯里","kgt":"康定","kry":"克拉玛依","kca":"库车","krl":"库尔勒","kmg":"昆明","lxa":"拉萨","lhw":"兰州","hzh":"黎平"
,"ljg":"丽江","llb":"荔波","lyg":"连云港","lpf":"六盘水","lfq":"临汾","lzy":"林芝","lnj":"临沧","lyi":"临沂","lzh":"柳州"
,"lzo":"泸州","lya":"洛阳","llv":"吕梁","jmj":"澜沧","lcx":"龙岩","nzh":"满洲里","lum":"芒市","mxz":"梅州","mig":"绵阳"
,"ohe":"漠河","mdg":"牡丹江","mfk":"马祖" ,"khn":"南昌","nao":"南充","nkg":"南京","nng":"南宁","ntg":"南通","nny":"南阳"
,"ngb":"宁波","nlh":"宁蒗","pzi":"攀枝花","sym":"普洱","ndg":"齐齐哈尔","jiq":"黔江","iqm":"且末","bpe":"秦皇岛","tao":"青岛"
,"iqn":"庆阳","juz":"衢州","rkz":"日喀则","riz":"日照","syx":"三亚","xmn":"厦门","sha":"上海","szx":"深圳","hpg":"神农架"
,"she":"沈阳","sjw":"石家庄","tcg":"塔城","hyn":"台州","tyn":"太原","yty":"泰州","tvs":"唐山","tcz":"腾冲","tsn":"天津"
,"thq":"天水","tgo":"通辽","ten":"铜仁","tlq":"吐鲁番","wxn":"万州","weh":"威海","wef":"潍坊","wnz":"温州","wnh":"文山"
,"wua":"乌海","hlh":"乌兰浩特","urc":"乌鲁木齐","wux":"无锡","wuz":"梧州","wuh":"武汉","wus":"武夷山","sia":"西安","xic":"西昌"
,"xnn":"西宁","jhg":"西双版纳","xil":"锡林浩特","dig":"香格里拉(迪庆)","xfn":"襄阳","acx":"兴义","xuz":"徐州","hkg":"香港"
,"ynt":"烟台","eny":"延安","ynj":"延吉","ynz":"盐城","yty":"扬州","lds":"伊春","yin":"伊宁","ybp":"宜宾","yih":"宜昌"
,"yic":"宜春","yiw":"义乌","inc":"银川","llf":"永州","uyn":"榆林","yus":"玉树","ycu":"运城","zha":"湛江","dyg":"张家界"
,"zqz":"张家口","yzy":"张掖","zat":"昭通","cgo":"郑州","zhy":"中卫","hsn":"舟山","zuh":"珠海","wmt":"遵义(茅台)","zyi":"遵义(新舟)"}
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为了防止频繁请求出现 429，useragent 也找多一些让其随机取值。但是有时候太频繁则需要输入验证码，所以还是每爬取一个出发城市，暂停10秒钟吧。
先创建表用于存储数据，此处用的是 sql server：
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create table kkflight(
id int identity(1,1), --自增id
itinerardate date, --行程日期
airline varchar(100), --航空公司
airlinecode varchar(100), --航空公司代码
flightnumber varchar(20), --航班号
flightnumbers varchar(20), --航班号-共享(实际航班)
aircraft varchar(50), --飞机型号
aircraftsize char(2), --型号大小(l大;m中;s小)
airporttax decimal(10,2), --机场建设费
fueloiltax decimal(10,2), --燃油税
fromcity varchar(50), --出发城市
fromcitycode varchar(10), --出发城市代码
fromairport varchar(50), --出发机场
fromterminal varchar(20), --出发航站楼
fromdatetime datetime, --出发时间
tocity varchar(50), --到达城市
tocitycode varchar(10), --到达城市代码
toairport varchar(50), --到达机场
toterminal varchar(20), --到达航站楼
todatetime datetime, --到达时间
durationhour int, --时长(小时h)
durationminute int, --时长(分钟m)
duration varchar(20), --时长(字符串)
currency varchar(10), --币种
ticketprices decimal(10,2), --票价
discount decimal(4,2), --已打折扣
punctualityrate decimal(4,2), --准点率
aircraftcabin char(1), --仓位(f头等舱;c公务舱;y经济舱)
insertdate datetime default(getdate()), --添加时间
)
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因为是爬取所有城市，所以城市不限制，只限制日期，即爬取哪天至哪天的数据。全部脚本如下：
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#-*- coding: utf-8 -*-
# python 3.5.0
import json
import time
import random
import datetime
import sqlalchemy
import urllib.request
import pandas as pd
from operator import itemgetter
from dateutil.parser import parse
class flight(object):
def __init__(self):
self.airline = {} #航空公司代码
self.engine = sqlalchemy.create_engine("mssql+pymssql://kk:kk@hzc/myspider")
self.url = ''
self.headers = {}
self.city={"aat":"阿勒泰","acx":"兴义","aeb":"百色","aku":"阿克苏","aog":"鞍山","aqg":"安庆","ava":"安顺","axf":"阿拉善左旗","bav":"包头","bfj":"毕节","bhy":"北海"
,"bjs":"北京","bpe":"秦皇岛","bpl":"博乐","bpx":"昌都","bsd":"保山","can":"广州","cde":"承德","cgd":"常德","cgo":"郑州","cgq":"长春","chg":"朝阳","cif":"赤峰"
,"cih":"长治","ckg":"重庆","csx":"长沙","ctu":"成都","cwj":"沧源","cyi":"嘉义","czx":"常州","dat":"大同","dax":"达县","dbc":"白城","dcy":"稻城","ddg":"丹东"
,"dig":"香格里拉(迪庆)","dlc":"大连","dlu":"大理","dnh":"敦煌","doy":"东营","dqa":"大庆","dsn":"鄂尔多斯","dyg":"张家界","ejn":"额济纳旗","enh":"恩施"
,"eny":"延安","erl":"二连浩特","foc":"福州","fug":"阜阳","fuo":"佛山","fyj":"抚远","goq":"格尔木","gys":"广元","gyu":"固原","hak":"海口","hdg":"邯郸"
,"hek":"黑河","het":"呼和浩特","hfe":"合肥","hgh":"杭州","hia":"淮安","hjj":"怀化","hkg":"香港","hld":"海拉尔","hlh":"乌兰浩特","hmi":"哈密","hpg":"神农架"
,"hrb":"哈尔滨","hsn":"舟山","htn":"和田","huz":"惠州","hyn":"台州","hzg":"汉中","hzh":"黎平","inc":"银川","iqm":"且末","iqn":"庆阳","jdz":"景德镇"
,"jgd":"加格达奇","jgn":"嘉峪关","jgs":"井冈山","jhg":"西双版纳","jic":"金昌","jiq":"黔江","jiu":"九江","jjn":"晋江","jmj":"澜沧","jmu":"佳木斯","jng":"济宁"
,"jnz":"锦州","jsj":"建三江","juh":"池州","juz":"衢州","jxa":"鸡西","jzh":"九寨沟","kca":"库车","kgt":"康定","khg":"喀什","khn":"南昌","kjh":"凯里","kmg":"昆明"
,"knh":"金门","kow":"赣州","krl":"库尔勒","kry":"克拉玛依","kwe":"贵阳","kwl":"桂林","lcx":"龙岩","lds":"伊春","lfq":"临汾","lhw":"兰州","ljg":"丽江","llb":"荔波"
,"llf":"永州","llv":"吕梁","lnj":"临沧","lpf":"六盘水","lum":"芒市","lxa":"拉萨","lya":"洛阳","lyg":"连云港","lyi":"临沂","lzh":"柳州","lzo":"泸州"
,"lzy":"林芝","mdg":"牡丹江","mfk":"马祖","mfm":"澳门","mig":"绵阳","mxz":"梅州","nao":"南充","nbs":"白山","ndg":"齐齐哈尔","ngb":"宁波","ngq":"阿里"
,"nkg":"南京","nlh":"宁蒗","nng":"南宁","nny":"南阳","ntg":"南通","nzh":"满洲里","ohe":"漠河","pzi":"攀枝花","rht":"阿拉善右旗","riz":"日照","rkz":"日喀则"
,"rlk":"巴彦淖尔","sha":"上海","she":"沈阳","sia":"西安","sjw":"石家庄","swa":"揭阳","sym":"普洱","syx":"三亚","szx":"深圳","tao":"青岛","tcg":"塔城","tcz":"腾冲"
,"ten":"铜仁","tgo":"通辽","thq":"天水","tlq":"吐鲁番","tna":"济南","tsn":"天津","tvs":"唐山","txn":"黄山","tyn":"太原","urc":"乌鲁木齐","uyn":"榆林","wef":"潍坊"
,"weh":"威海","wmt":"遵义(茅台)","wnh":"文山","wnz":"温州","wua":"乌海","wuh":"武汉","wus":"武夷山","wux":"无锡","wuz":"梧州","wxn":"万州","xfn":"襄阳","xic":"西昌"
,"xil":"锡林浩特","xmn":"厦门","xnn":"西宁","xuz":"徐州","ybp":"宜宾","ycu":"运城","yic":"宜春","yie":"阿尔山","yih":"宜昌","yin":"伊宁","yiw":"义乌","ynj":"延吉"
,"ynt":"烟台","ynz":"盐城","yty":"扬州","yus":"玉树","yzy":"张掖","zat":"昭通","zha":"湛江","zhy":"中卫","zqz":"张家口","zuh":"珠海","zyi":"遵义(新舟)"}
"""{"kji":"布尔津"}"""
self.useragent = [
"mozilla/5.0 (windows nt 6.3; win64; x64) applewebkit/537.36 (khtml, like gecko) chrome/66.0.3359.139 safari/537.36",
"mozilla/5.0 (windows nt 6.1; wow64) applewebkit/535.7 (khtml, like gecko) chrome/16.0.912.36 safari/535.7",
"mozilla/5.0 (windows nt 6.2; win64; x64; rv:16.0) gecko/16.0 firefox/16.0",
"mozilla/5.0 (macintosh; intel mac os x 10_7_3) applewebkit/534.55.3 (khtml, like gecko) version/5.1.3 safari/534.53.10",
"mozilla/5.0 (compatible; msie 9.0; windows nt 6.1; win64; x64; trident/5.0; .net clr 3.5.30729; .net clr 3.0.30729; .net clr 2.0.50727; media center pc 6.0)",
"mozilla/5.0 (compatible; msie 8.0; windows nt 6.0; trident/4.0; wow64; trident/4.0; slcc2; .net clr 2.0.50727; .net clr 3.5.30729; .net clr 3.0.30729; .net clr 1.0.3705; .net clr 1.1.4322)",
"mozilla/5.0 (windows nt 6.2; wow64) applewebkit/537.36 (khtml, like gecko) chrome/27.0.1500.55 safari/537.36",
"mozilla/5.0 (macintosh; intel mac os x 10_8_2) applewebkit/537.17 (khtml, like gecko) chrome/24.0.1309.0 safari/537.17"
"mozilla/5.0 (windows nt 6.1; win64; x64; rv:2.0b13pre) gecko/20110307 firefox/4.0b13pre",
"mozilla/5.0 (x11; ubuntu; linux x86_64; rv:16.0) gecko/20100101 firefox/16.0",
"mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.11 (khtml, like gecko) chrome/23.0.1271.64 safari/537.11"
]
#遍历两个日期间的所有日期
def set_url_headers(self,startdate,enddate):
startdate=datetime.datetime.strptime(startdate,'%y-%m-%d')
enddate=datetime.datetime.strptime(enddate,'%y-%m-%d')
while startdate<=enddate:
today = startdate.strftime('%y-%m-%d')
for fromcode, fromcity in sorted(self.city.items(), key=itemgetter(0)):
for tocode, tocity in sorted(self.city.items(), key=itemgetter(0)):
if fromcode != tocode:
self.url = 'http://flights.ctrip.com/domesticsearch/search/searchfirstrouteflights?dcity1=%s&acity1=%s&searchtype=s&ddate1=%s&isnearairportrecommond=0&logtoken=027e478a47494975ad74857b18283e12&rk=4.381066884522498182534&ck=9fc7881e8f373585c0e5f89152bc143d&r=0.24149333708195565406316' % (fromcode,tocode,today)
self.headers = {
"host": "flights.ctrip.com",
"user-agent": random.choice(self.useragent),
"referer": "https://flights.ctrip.com/booking/%s-%s-day-1.html?ddate1=%s" % (fromcode,tocode,today),
"connection": "keep-alive",
}
print("%s : %s(%s) ==> %s(%s) " % (today,fromcity,fromcode,tocity,tocode))
self.get_parse_json_data(today)
time.sleep(10)
startdate+=datetime.timedelta(days=1)
#获取一个页面中的数据
def get_one_page_json_data(self):
req = urllib.request.request(self.url,headers=self.headers)
body = urllib.request.urlopen(req,timeout=30).read().decode('gbk')
jsondata = json.loads(body.strip("'<>() ").replace('\'', '\"'))
return jsondata
#获取一个页面中的数据，解析保存到数据库
def get_parse_json_data(self,today):
jsondata = self.get_one_page_json_data()
df = pd.dataframe(columns=['itinerardate','airline','airlinecode','flightnumber','flightnumbers','aircraft','aircraftsize'
,'airporttax','fueloiltax','fromcity','fromcitycode','fromairport','fromterminal','fromdatetime','tocity','tocitycode','toairport'
,'toterminal','todatetime','durationhour','durationminute','duration','currency','ticketprices','discount','punctualityrate','aircraftcabin'])
if bool(jsondata["fis"]):
#获取航空公司代码及公司名称
company = jsondata["als"]
for k in company.keys():
if k not in self.airline:
self.airline[k]=company[k]
index = 0
for data in jsondata["fis"]:
df.loc[index,'itinerardate'] = today #行程日期
#df.loc[index,'airline'] = self.airline[data["alc"].strip()] #航空公司
df.loc[index,'airline'] = self.airline[data["alc"].strip()] if (data["alc"].strip() in self.airline) else none #航空公司
df.loc[index,'airlinecode'] = data["alc"].strip() #航空公司代码
df.loc[index,'flightnumber'] = data["fn"] #航班号
df.loc[index,'flightnumbers'] = data["sdft"] #共享航班号(实际航班)
df.loc[index,'aircraft'] = data["cf"]["c"] #飞机型号
df.loc[index,'aircraftsize'] = data["cf"]["s"] #型号大小(l大;m中;s小)
df.loc[index,'airporttax'] = data["tax"] #机场建设费
df.loc[index,'fueloiltax'] = data["of"] #燃油税
df.loc[index,'fromcity'] = data["acn"] #出发城市
df.loc[index,'fromcitycode'] = data["acc"] #出发城市代码
df.loc[index,'fromairport'] = data["apbn"] #出发机场
df.loc[index,'fromterminal'] = data["asmsn"] #出发航站楼
df.loc[index,'fromdatetime'] = data["dt"] #出发时间
df.loc[index,'tocity'] = data["dcn"] #到达城市
df.loc[index,'tocitycode'] = data["dcc"] #到达城市代码
df.loc[index,'toairport'] = data["dpbn"] #到达机场
df.loc[index,'toterminal'] = data["dsmsn"] #到达航站楼
df.loc[index,'todatetime'] = data["at"] #到达时间
df.loc[index,'durationhour'] = int((parse(data["at"])-parse(data["dt"])).seconds/3600) #时长(小时h)
df.loc[index,'durationminute'] = int((parse(data["at"])-parse(data["dt"])).seconds%3600/60) #时长(分钟m)
df.loc[index,'duration'] = str(df.loc[index,'durationhour']) + 'h' + str(df.loc[index,'durationminute']) + 'm' #时长(字符串)
df.loc[index,'currency'] = none #币种
df.loc[index,'ticketprices'] = data["lp"] #票价
df.loc[index,'discount'] = none #已打折扣
df.loc[index,'punctualityrate'] = none #准点率
df.loc[index,'aircraftcabin'] = none #仓位(f头等舱;c公务舱;y经济舱)
index = index + 1
df.to_sql("kkflight", self.engine, index=false, if_exists='append')
print("done!~")
if __name__ == "__main__":
fly = flight()
fly.set_url_headers('2018-06-16','2018-06-16')
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总结
以上所述是小编给大家介绍的python 爬取携程所有机票，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对服务器之家网站的支持！
原文链接：https://blog.csdn.net/kk185800961/article/details/80638035