Powerfull wrapper around OSM Overpass Turbo to query regions of any size and shape
Project description
Powerfull wrapper around OSM Overpass Turbo to query regions of any size and shape
pip install osmpy
List precooked queries
osmpy.list_queries()
name docstring
0 Amenities Location of amenities within a boundary
1 AmentiesCount Number of amenities per type within a boundary
2 RoadLength Length of road by roadtype within a boundary
Get all amenities in a boundary
import osmpy
from shapely import wkt
boundary = wkt.loads('POLYGON((-46.63 -23.54,-46.6 -23.54,-46.62 -23.55,-46.63 -23.55,-46.63 -23.54))')
osmpy.get('Amenities', boundary)
type id lat lon tags
0 node 661212030 -23.544739 -46.626160 {'amenity': 'fuel', 'name': 'Posto NGM'}
1 node 661212089 -23.547450 -46.626073 {'amenity': 'fuel', 'name': 'Posto Maserati', ...
2 node 745733280 -23.541411 -46.613930 {'addr:city': 'São Paulo', 'addr:housenumber':...
3 node 745733292 -23.542070 -46.614916 {'addr:city': 'São Paulo', 'addr:housenumber':...
4 node 889763809 -23.542558 -46.620360 {'addr:housenumber': '110/C9', 'addr:street': ...
.. ... ... ... ... ...
84 node 5663737625 -23.540027 -46.605425 {'access': 'yes', 'addr:city': 'São Paulo', 'a...
85 node 5990269247 -23.540650 -46.607532 {'addr:city': 'São Paulo', 'addr:housenumber':...
86 node 6621564995 -23.543880 -46.626414 {'access': 'yes', 'addr:city': 'São Paulo', 'a...
87 node 6625433725 -23.546727 -46.623956 {'access': 'yes', 'addr:city': 'São Paulo', 'a...
88 node 6625433753 -23.547111 -46.624790 {'access': 'yes', 'addr:city': 'São Paulo', 'a...
Total road length by road type
osmpy.get('RoadLength', boundary)
count length
highway
bus_stop 1 82.624
corridor 2 482.195
cycleway 1 134.197
footway 116 5473.419
living_street 3 422.378
path 4 735.539
pedestrian 3 90.327
platform 3 239.206
primary 28 2067.562
primary_link 12 1123.544
You can use your own query
## Use `{boundary}` as a placeholder.
query = """
[out:json];
node["amenity"](poly:"{boundary}");
out body geom;
"""
osmpy.get(query, boundary)
Create a precooked query
class YourPrecookedQuery(osmpy.queries.QueryType):
query = """
<OSM Overpass Turbo Query>
"""
docstring = """
<Query description>
"""
def postprocess(self, df):
"""Post process API result
"""
return df['tags'].apply(pd.Series).groupby('amenity').sum()
osmpy.get(YourPrecookedQuery, boundary)
:point_right: Leave an issue or PR if you want to add a new query to the package
Credits
Free software: MIT license
Function katana
from @snorfalorpagus_.
Project details
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