Package: osmxtract
OSMxtractDescriptionOSMxtractis a simple Python package that uses theOverpass APIto fetchOpenStreetMapfeatures and export them in a GeoJSON file.InstallationUsingpip:pipinstallosmxtractCommand-line interfaceUsageOSMxtractcan guess the extent of your query based on three different options:--fromfile: use the bounds from the input vector or raster file ;--latlonand--buffer: use the bounds of a buffer around a given point ;--addressand--buffer: use the bounds of a buffer around a geocoded address.Usage: osmxtract [OPTIONS] OUTPUT

  Extract GeoJSON features from OSM with the Overpass API.

Options:
  --fromfile PATH                 Bounding box from input file.
  --latlon FLOAT...               Space-separated lat/lon coordinates.
  --address TEXT                  Address to geocode.
  --buffer INTEGER                Buffer size in meters around lat/lon or
                                  address.
  --tag TEXT                      OSM tag of interest (ex: "highway").
  --values TEXT                   Comma-separated list of possible values (ex:
                                  "tertiary,primary").
  --case-insensitive              Make the first character of each value case
                                  insensitive.
  --geom [point|linestring|polygon|multipolygon]
                                  Output geometry type.
  --help                          Show this message and exit.Examples# buildings around the "Université Libre de Bruxelles" as polygons# save features in the file `buildings.geojson`. since no values# are provided, all non-null values are accepted for the tag# "highway" are accepted.osmxtract--address"Université Libre de Bruxelles"--buffer5000\--tagbuilding--geompolygonbuildings.geojson# primary, secondary and tertiary roads based on the extent# of an existing raster. save the result as linestrings in the# `major_roads.geojson` file. we use the `--case-insensitive`# flag to get roads tagged as "primary" as well as "Primary".osmxtract--fromfilemap.tif--taghighway\--values"primary,secondary,tertiary"\--case-insensitive--geomlinestring\major_roads.geojson# cafes and bars near "Atomium, Brussels"osmxtract--address"atomium, brussels"--buffer1000\--tagamenity--values"cafe,bar"--geompoint\cafes_and_bars.geojsonAPIimportjsonfromosmxtractimportoverpass,locationimportgeopandasasgpd# Get bounding box coordinates from a 2km buffer# around the Atomium in Brusselslat,lon=location.geocode('Atomium, Brussels')bounds=location.from_buffer(lat,lon,buffer_size=2000)# Build an overpass QL query and get the JSON responsequery=overpass.ql_query(bounds,tag='amenity',values=['cafe','bar'])response=overpass.request(query)# Process response manually...foreleminresponse['elements']:print(elem['tags'].get('name'))# Output:# Au Bon Coin# Aux 4 Coins du Monde# Excelsior# Welcome II# Heymbos# Games Café# Stadium# Le Beau Rivage# The Corner# None# Expo# Koning# Centrum# St. Amands# Bij Manu# ...or parse them as GeoJSONfeature_collection=overpass.as_geojson(response,'point')# Write as GeoJSONwithopen('cafes_and_bars.geojson','w')asf:json.dump(feature_collection,f)# To GeoPandas GeoDataFrame:geodataframe=gpd.GeoDataFrame.from_features(feature_collection)