I remember Efrain's presentation at PyDay in Mérida, where he talked about the tweepy library (here is Efrain's article on the subject), which lets you access a twitter account, update your status, among other things.
With the rise of twitter as a social network in the country, I set out to try another Python library for twitter called python-twitter; the library's documentation can be accessed from here. There is a series of examples of how to use the python-twitter library on github.
Install the twitter library:
Use the easy_install or pip command as root:
easy_install twitteror
pip install twitterThe code shown below lists the Country IDs, the ID number of each Country. You can see the original code at the following link (broken link): Run python:
(python2.7)ernesto@jewel:~/prueba$ python
Python 2.7.3 (default, Jan 2 2013, 16:53:07)
[GCC 4.7.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>>Import the python-twitter module:
>>> import twitterInstantiate the Twitter class, passing the domain (the url of the twitter api) and the api version, which in this case is version 1:
>>> twitter_api = twitter.Twitter(domain="api.twitter.com", api_version='1')Capture the available trends:
>>> trends1 = twitter_api.trends.available()List the Country IDs:
>>> for location in trends1:
... name = location["name"].encode('ascii', 'replace')
... print "(%d) %s" % (location["woeid"], name)
...
(1) Worldwide
(2972) Winnipeg
(3369) Ottawa
(3444) Quebec
(3534) Montreal
(4118) Toronto
(8676) Edmonton
(8775) Calgary
(9807) Vancouver
(12723) Birmingham
(13911) Brighton
(13963) Bristol
(15127) Cardiff
(19344) Edinburgh
(21125) Glasgow
(26042) Leeds
(26062) Leicester
(26734) Liverpool
(28218) Manchester
(30079) Newcastle
(30720) Nottingham
(32452) Portsmouth
(34503) Sheffield
(44418) London
(44544) Belfast
(76456) Santo Domingo
(116545) Mexico City
(124162) Guadalajara
(131068) Le?n
(134047) Monterrey
(137612) Puebla
(149361) Tijuana
(332471) Mendoza
(349859) Santiago
(349860) Concepcion
(349861) Valparaiso
(368148) Bogot?
(395269) Caracas
(395270) Maracaibo
(395272) Valencia
(418440) Lima
(455819) Bras?lia
(455820) Bel?m
(455821) Belo Horizonte
(455822) Curitiba
(455823) Porto Alegre
(455824) Recife
(455825) Rio de Janeiro
(455826) Salvador
(455827) S?o Paulo
(455828) Campinas
(455830) Fortaleza
(455831) Goi?nia
(455833) Manaus
(455834) S?o Lu?s
(455867) Guarulhos
(466861) C?rdoba
(466862) Rosario
(468382) Barquisimeto
(468739) Buenos Aires
(560743) Dublin
(580778) Bordeaux
(608105) Lille
(609125) Lyon
(610264) Marseille
(612977) Montpellier
(613858) Nantes
(615702) Paris
(619163) Rennes
(627791) Strasbourg
(628886) Toulouse
(638242) Berlin
(641142) Bremen
(645458) Dortmund
(645686) Dresden
(646099) Dusseldorf
(648820) Essen
(650272) Frankfurt
(656958) Hamburg
(667931) Cologne
(671072) Leipzig
(676757) Munich
(698064) Stuttgart
(718345) Milan
(719258) Naples
(721943) Rome
(725003) Turin
(726874) Den Haag
(727232) Amsterdam
(733075) Rotterdam
(753692) Barcelona
(766273) Madrid
(766356) Malaga
(774508) Seville
(776688) Valencia
(779063) Zaragoza
(906057) Stockholm
(1030077) Bekasi
(1044316) Surabaya
(1047180) Bandung
(1047378) Jakarta
(1062617) Singapore
(1098081) Perth
(1099805) Adelaide
(1100661) Brisbane
(1100968) Canberra
(1101597) Darwin
(1103816) Melbourne
(1105779) Sydney
(1110809) Kitakyushu
(1117034) Chiba
(1117099) Fukuoka
(1117227) Hiroshima
(1117502) Kawasaki
(1117545) Kobe
(1117817) Nagoya
(1118108) Sapporo
(1118129) Sendai
(1118285) Takamatsu
(1118370) Tokyo
(1118550) Yokohama
(1132447) Busan
(1132466) Daegu
(1132481) Gwangju
(1132496) Incheon
(1132567) Suwon
(1132578) Ulsan
(1132599) Seoul
(1154726) Klang
(1154781) Kuala Lumpur
(1167715) Calocan
(1199136) Davao City
(1199477) Manila
(1199682) Quezon City
(1398823) Lagos
(1582504) Johannesburg
(2077746) Samara
(2112237) Yekaterinburg
(2122265) Moscow
(2122471) Nizhny Novgorod
(2122541) Novosibirsk
(2122641) Omsk
(2123260) Saint Petersburg
(2282863) Nagpur
(2295377) Lucknow
(2295378) Kanpur
(2295386) Kolkata
(2295388) Amritsar
(2295401) Jaipur
(2295402) Ahmedabad
(2295408) Indore
(2295411) Mumbai
(2295412) Pune
(2295414) Hyderabad
(2295420) Bangalore
(2295424) Chennai
(2343678) Adana
(2343732) Ankara
(2343843) Bursa
(2344116) Istanbul
(2344117) Izmir
(2345896) Okinawa
(2345975) Daejeon
(2357024) Atlanta
(2357536) Austin
(2358820) Baltimore
(2359991) Baton Rouge
(2364559) Birmingham
(2367105) Boston
(2378426) Charlotte
(2379574) Chicago
(2380358) Cincinnati
(2381475) Cleveland
(2383660) Columbus
(2388929) Dallas-Ft. Worth
(2391279) Denver
(2391585) Detroit
(2414469) Greensboro
(2418046) Harrisburg
(2424766) Houston
(2427032) Indianapolis
(2428184) Jackson
(2436704) Las Vegas
(2442047) Los Angeles
(2449323) Memphis
(2450022) Miami
(2451822) Milwaukee
(2452078) Minneapolis
(2457170) Nashville
(2458410) New Haven
(2458833) New Orleans
(2459115) New York
(2460389) Norfolk
(2466256) Orlando
(2471217) Philadelphia
(2471390) Phoenix
(2473224) Pittsburgh
(2475687) Portland
(2477058) Providence
(2478307) Raleigh
(2480894) Richmond
(2486340) Sacramento
(2486982) St. Louis
(2487610) Salt Lake City
(2487796) San Antonio
(2487889) San Diego
(2487956) San Francisco
(2490383) Seattle
(2503713) Tallahassee
(2503863) Tampa
(2514815) Washington
(15015370) Osaka
(15015372) Kyoto
(20070458) Delhi
(23424738) United Arab Emirates
(23424747) Argentina
(23424748) Australia
(23424768) Brazil
(23424775) Canada
(23424782) Chile
(23424787) Colombia
(23424800) Dominican Republic
(23424801) Ecuador
(23424803) Ireland
(23424819) France
(23424829) Germany
(23424834) Guatemala
(23424846) Indonesia
(23424848) India
(23424853) Italy
(23424856) Japan
(23424868) Korea
(23424900) Mexico
(23424901) Malaysia
(23424908) Nigeria
(23424909) Netherlands
(23424916) New Zealand
(23424919) Peru
(23424922) Pakistan
(23424934) Philippines
(23424936) Russia
(23424942) South Africa
(23424948) Singapore
(23424950) Spain
(23424954) Sweden
(23424969) Turkey
(23424975) United Kingdom
(23424977) United States
(23424982) Venezuela
(56013632) Petaling
(56013645) Hulu LangatID 1 is for listing the worldwide trending topics; for Venezuela the ID is 23424982. The IDs of the Venezuelan cities are highlighted in bold.
Now the global (1) trending topic list will be displayed: Set WOE_ID to 1 to capture the global trending topics, instantiate the Twitter class with the domain api.twitter.com and set the api version to version 1. Next, capture the trending topics and show the top 10 topics in the world.
>>>WORLD_WOE_ID = 1
>>> twitter_api = twitter.Twitter(domain="api.twitter.com", api_version='1')
>>> world_trends = twitter_api.trends._(WORLD_WOE_ID)
>>> trends = world_trends()
>>> for i in range(10):
... print trends[0]['trends'][i][u'name']
...
#ILoveCheese
#CaprilesVenezuelayELMUNDOestácontigo
#MiMamáDice
#VamosMaravilla
#AJuicioCaprilesAsesino
Sara McMann
Rene de Calle 13
Sheila Gaff
RDMA
Rene
When the value of the WORLD_WOE_ID variable is changed to Venezuela's (23424982), you get:
>>> WORLD_WOE_ID = 23424982
>>> twitter_api = twitter.Twitter(domain="api.twitter.com", api_version='1')
>>> world_trends = twitter_api.trends._(WORLD_WOE_ID)
>>> trends = world_trends()
>>> for i in range(10):
... print trends[0]['trends'][i][u'name']
...
#CaprilesVenezuelayELMUNDOestácontigo
#AJuicioCaprilesAsesino
#MiMamáDice
#MeArrechoCuando
#QueVivan
Feliz Día del Diseñador Gráfico
Estuvimos 5
Dayana Mendoza
Omar Borkan Al Gala
Antonio Rivero
For the case of Valencia (395272):
>>> WORLD_WOE_ID = 395272
>>> twitter_api = twitter.Twitter(domain="api.twitter.com", api_version='1')
>>> world_trends = twitter_api.trends._(WORLD_WOE_ID)
>>> trends = world_trends()
>>> for i in range(10):
... print trends[0]['trends'][i][u'name']
...
#CaprilesVenezuelayELMUNDOestácontigo
#AJuicioCaprilesAsesino
#MeArrechoCuando
#MiMamáDice
Omar Borkan Al Gala
#TROPA
Feliz Día del Diseñador Gráfico
Estuvimos 5
Dayana Mendoza
Antonio Rivero
This way you can list the top 10 topics by Country or city using Python.
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