Python 爬取携程所有机票的实例代码
打开携程网，查询机票，如广州到成都。
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：
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)"}
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：
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 )
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：
#-*- 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')
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【听图阁-专注于Python设计】网站的支持！
