This project attempts to consolidate data.gov.sg data under a single unified python library.
Currently, we are linking just two individual libraries into this package but we are accepting pull requests for other wrappers of other datasets! Please feel free to fork and modify away!
Currently supported datasets are:
To use, all you need to do is to
$ pip install singapore
# python
from singapore import onemap
from singapore import nea_api
from singapore import datagovsg_api
>>>
>>> from singapore import onemap
>>> OM = onemap.OneMap("onemap_key")
>>>
>>> res = OM.search_address("city hall")
>>> type(res)
<class 'core.ext.onemap.OneMapResult'>
>>>
>>> res
[{u'searchval': u'CITY HALL', u'category': u'Building', u'y': u'30360.5886', u'x': u'30051.7694'}, {u'searchval': u'CITY HALL (MONUMENTS)', u'category': u'Culture', u'y': u'30339.5771', u'x': u'30047.6749'}, {u'searchval': u'CITY HALL (STREET AND PLACES)', u'category': u'Culture', u'y': u'30318.8100', u'x': u'30064.6100'}, {u'searchval': u'CITY HALL AND THE PADANG (HERITAGE SITES)', u'category': u'Culture', u'y': u'30340.3699', u'x': u'30049.0300'}, {u'searchval': u'CITY HALL MRT STATION', u'category': u'Building', u'y': u'30597.7817', u'x': u'30139.4704'}, {u'searchval': u'CITY HALL MRT STATION (EW13/NS25) (FRIENDLY BUILDINGS)', u'category': u'Community', u'y': u'30597.7817', u'x': u'30139.4704'}, {u'searchval': u'CITY HALL MRT STATION EXIT A', u'category': u'Building', u'y': u'30611.1767', u'x': u'30182.8492'}, {u'searchval': u'CITY HALL MRT STATION EXIT B', u'category': u'Building', u'y': u'30610.8982', u'x': u'30073.6413'}, {u'searchval': u'CITY HALL/ESPLANADE MRT STATION EXIT A', u'category': u'Building', u'y': u'30415.3350', u'x': u'30369.4938'}, {u'searchval': u'CITY HALL/ESPLANADE MRT STATION EXIT B', u'category': u'Building', u'y': u'30457.5147', u'x': u'30385.8054'}, {u'searchval': u'CITY HALL/ESPLANADE MRT STATION EXIT C', u'category': u'Building', u'y': u'30412.5744', u'x': u'30434.3890'}, {u'searchval': u'CITY HALL/ESPLANADE MRT STATION EXIT D', u'category': u'Building', u'y': u'30367.6908', u'x': u'30424.1965'}, {u'searchval': u'CITY HALL/ESPLANADE MRT STATION EXIT E', u'category': u'Building', u'y': u'30479.6293', u'x': u'30394.6855'}]
>>>
Queries return a OneMapResult object, containing one or more OneMapResultItems
>>> geo = OM.geocode("%s,%s" % (res[0]['x'], res[0]['y']))
>>> type(geo)
<class 'core.ext.onemap.OneMapResult'>
>>>
>>> geo
[{u'buildingname': u'CITY HALL', 'y': 30338.9616, u'block': u'3', u'postalcode': u'178958', 'x': 30047.2715, u'road': u"SAINT ANDREW'S ROAD"}, {u'buildingname': u'THE ADELPHI', 'y': 30398.6047, u'block': u'1', u'postalcode': u'179803', 'x': 29987.9521, u'road': u'COLEMAN STREET'}, {u'buildingname': u'THE OLD SUPREME COURT BUILDING', 'y': 30253.3835, u'block': u'1', u'postalcode': u'178957', 'x': 30025.5209, u'road': u"SAINT ANDREW'S ROAD"}, {u'buildingname': u'SUPREME COURT BUILDING', 'y': 30322.8247, u'block': u'1', u'postalcode': u'178879', 'x': 29938.7931, u'road': u'SUPREME COURT LANE'}, {u'buildingname': u'FORMER SUPREME COURT BUILDING', 'y': 30250.6217, u'block': u'1', u'postalcode': u'178957', 'x': 29985.2869, u'road': u"SAINT ANDREW'S ROAD"}]
>>>
For more information, check out the main README
Sample:
from nea_api import NEA
nea = NEA(api_key="<api key>")
results = nea.get_pm25()
# ipdb> results
OrderedDict([('channel', OrderedDict([('title', 'PM2.5 Update'), ('source', 'Airviro'), ('item', OrderedDict([('region', [OrderedDict([('id', 'rNO'), ('latitude', '1.41803'), ('longitude', '103.82000'), ('record', OrderedDict([('@timestamp', '20160406140000'), ('reading', OrderedDict([('@type', 'PM25_RGN_1HR'), ('@value', '17')]))]))]), OrderedDict([('id', 'rCE'), ('latitude', '1.35735'), ('longitude', '103.82000'), ('record', OrderedDict([('@timestamp', '20160406140000'), ('reading', OrderedDict([('@type', 'PM25_RGN_1HR'), ('@value', '27')]))]))]), OrderedDict([('id', 'rEA'), ('latitude', '1.35735'), ('longitude', '103.94000'), ('record', OrderedDict([('@timestamp', '20160406140000'), ('reading', OrderedDict([('@type', 'PM25_RGN_1HR'), ('@value', '19')]))]))]), OrderedDict([('id', 'rWE'), ('latitude', '1.35735'), ('longitude', '103.70000'), ('record', OrderedDict([('@timestamp', '20160406140000'), ('reading', OrderedDict([('@type', 'PM25_RGN_1HR'), ('@value', '26')]))]))]), OrderedDict([('id', 'rSO'), ('latitude', '1.29587'), ('longitude', '103.82000'), ('record', OrderedDict([('@timestamp', '20160406140000'), ('reading', OrderedDict([('@type', 'PM25_RGN_1HR'), ('@value', '30')]))]))])])]))]))])
For more information, check out the main README
Sample:
import datagovsg_api
sg_data = datagovsg_api.AllAPI('API_KEY')
# Get taxi availability
print(sg_data.taxi_availability().json())
# Get 2-hour weather forecast
print(sg_data.weather_forecast(duration='2-hour').json())For more information, check out the main README
- Setup an actual readthedocs
- Wrapper for Singaporepools, LTA dataset
- Ruiwen Chua
- David Chua We're not related!