我使用trends/available
API获得了印度某个地点的可用趋势
{
'name': 'Bhopal',
'placeType': {
'code': 7,
'name': 'Town'
},
'url': 'http://where.yahooapis.com/v1/place/2295407',
'parentid': 23424848,
'country': 'India',
'woeid': 2295407,
'countryCode': 'IN'
},
{
'name': 'Indore',
'placeType': {
'code': 7,
'name': 'Town'
},
'url': 'http://where.yahooapis.com/v1/place/2295408',
'parentid': 23424848,
'country': 'India',
'woeid': 2295408,
'countryCode': 'IN'
},
{
'name': 'Thane',
'placeType': {
'code': 7,
'name': 'Town'
},
'url': 'http://where.yahooapis.com/v1/place/2295410',
'parentid': 23424848,
'country': 'India',
'woeid': 2295410,
'countryCode': 'IN'
},
{
'name': 'Mumbai',
'placeType': {
'code': 7,
'name': 'Town'
},
'url': 'http://where.yahooapis.com/v1/place/2295411',
'parentid': 23424848,
'country': 'India',
'woeid': 2295411,
'countryCode': 'IN'
},
{
'name': 'Pune',
'placeType': {
'code': 7,
'name': 'Town'
我在代码中传递了不同的 woeid, 它使用apitwitter_api.trends.place(_id=town_woeid)
为每个城镇 woeid 提供了相同的趋势主题/trends/place
这是执行此操作的代码的一部分。
woids = {'Nagpur':2295412, 'Lucknow':2295377,'Kanpur':2295378, 'Patna':2295381, 'Ranchi':2295383,'Kolkata':2295386, 'Srinagar':2295387, 'Amritsar':2295388,\
'Jaipur':2295401,'Ahmedabad':2295402, 'Rajkot':2295404, 'Surat':2295405, 'Bhopal':2295407, 'Indore':2295408, 'Thane':2295410, 'Mumbai':2295411, 'Pune':2295412,\
'Hyderabad':2295414, 'Bangalore':2295420, 'Chennai':2295424}
for key in woids.keys():
print(key, " id: ", woids[key])
trends = self.twitter_api.trends.place(_id=woids[key])
print("--------called api ---------- ", trends)
with open(key+"_Trending.txt", "w+") as f:
for trending in trends[0]['trends']:
print(trending['name'], '-----', trending['tweet_volume'])
f.write(trending['name']+ '-----'+str(trending['tweet_volume']))
f.write("\n")
这是每个城镇的相同结果。但它应该为每个城镇提供不同的热门话题,对吧?
#RiyazNaikoo ----- 69420
X Æ A-12 ----- 977101
#IUxSUGA ----- 1635605
#HumModiKeSathHain ----- 23887
#IndiaHealthHour ----- None
#सफूरा_जरगर_मेरी_बहन_है ----- 127206
Justice 4 Sea ----- None
मौत मारा ----- 14506
Joonie ----- 25503
slavery ----- 31570
Top Hizbul ----- None
Most Photogenic Star ----- None
Rs 1,610 ----- None
Mysuru ----- None
Anna Hazare ----- None
Kamal Hassan ----- None
#BeingHaangryy ----- 12197
#boislockeroom ----- None
#हंसराज_का_जीजा_कौन_है ----- 19033
#BJPTheRealAntiNational ----- 10857
#गद्दार_मोदी_लुटेरा_है ----- 72618
#पप्पू_तो_गद्दार_है ----- 81990
#GoldQuarantineAwards ----- None
#HizbulMujahideen ----- None
#SidHeartsWishHBDVinduSir ----- 51926
#EXWeek ----- None
#eightiscoming ----- 129374
#भगवा_शेर_योगी_जी ----- None
#SenaKaBadla ----- None
#Thalapathy65 ----- 17290
#MODIJI_HelpUs ----- 123497
#ArrestSwatiMaliwal ----- None
#TerrorismFreeKashmir ----- None
#NarasimhaJayanti ----- None
#TTVcondemnsTASMACopening ----- None
#HBDSundeepKishan ----- None
#आरक्षण_के_जनक ----- 60779
#ஊழலின்_புகலிடம்_அதிமுக ----- 12779
#JassieGill ----- None
#4YearsOfAwestruck24Movie ----- 50243
#भारतीय_सेना ----- None
#JaiHindKiSena ----- None
#ILoveRedmiNote ----- None
#ShameOnYouFadanvis ----- None
Lucknow id: 2295377
谁能告诉我我做错了什么?或者是twitter方面的缓存问题?谢谢。