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)
👉 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_.
1 maintainer
Metadata
1 maintainer
Release files for osmpy 0.2.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| osmpy-0.2.0.tar.gz | 5.4 kB | Without provenance | Details for osmpy-0.2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| osmpy-0.2.0-py3-none-any.whl | Python 3 | none | any | Details for osmpy-0.2.0-py3-none-any.whl |
Total release size: 10.5 kB
Release files / osmpy-0.2.0.tar.gz
| Download URL | osmpy-0.2.0.tar.gz |
|---|---|
| Size | 5.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / osmpy-0.2.0-py3-none-any.whl
| Download URL | osmpy-0.2.0-py3-none-any.whl |
|---|---|
| Size | 5.2 kB |
| Tags | Python 3 |
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