udlai is a way of interacting with the UDL.AI platform for location intelligence using a convenient Python API.
Note, that to use the udlai, you will need to obtain an access token. See udl.ai for details.
udlai can be installed either from PyPI or conda-forge.
pip install udlaiOr
conda install -c conda-forge udlai
# or alternatively
mamba install -c conda-forge udlaiIn the near future, udlai will offer a convenient interface to all parts of the UDL.AI platform. At the moment, only the feature API module is available, allowing you to retrieve data from the UDL.AI data warehouse.
Using the token received from UDL you will be able to perform the following tasks:
Get a list of all of the attributes the user has access to, completed with their metadata and description.
>>> udlai.attributes(token)
id name ... year value_formatter
0 1 Buildings floorspace ... 2013 None
1 2 Buildings footprint ... 2013 None
2 3 Height ... 2013 None
3 4 Stories ... 2013 None
4 9 box_area ... 2013 None
.. ... ... ... ... ...
234 283 usefit_ind_old ... 0 None
235 288 Distance secondary school ... None None
236 294 Price 2 bedroom ... None None
237 295 Price 3 bedroom ... None None
238 296 Price 4 bedrooms ... None None
[239 rows x 22 columns]Get the properties, description and summary statistics of a specific attribute.
>>> udlai.attribute_detail(token, 22)
id 22
name obj_compact
description Compactness of object: C=obj_peri²/(4*box_area*π)
short_description None
unit -
tags.id 4
tags.name Morphology
main_tag.id 4
main_tag.name Morphology
data_version None
data_last_update None
data_processor UDL
source_provider Swiss Topo TLM
source_provider_link https://www.swisstopo.admin.ch/de/wissen-fakte...
coverage_general Switzerland
epsg_code 2056
min_value 0.960614
max_value 24.141694
standard_deviation 0.893447
mean 1.647733
year 2013
value_formatter None
dtype: objectGet the feature values for a provided coordinate location or locations.
>>> udlai.features(token, 47.37, 8.54, [10, 11, 22], index_by="name")
box_length 104
box_perim 335
obj_compact 2.2064113123322
Name: (47.37, 8.54), dtype: objectGet the summary statistics of an attribute within a specific area.
>>> udlai.aggregates(token, shapely_geom, [10, 12], index_by='name')
sum mean median min max std
box_length 12921.0 94.313869 94.0 19.0 135.0 30.600546
box_width 13118.0 95.751825 100.0 29.0 142.0 30.870646Martin Fleischmann (@martinfleis)