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Description:

picogeojson 0.8.0

Straightforward and compliant GeoJSON parsing and serialization with
zero dependencies. Easily ingest or output GeoJSON adhering to RFC
7946.

Usage
GeoJSON files or strings are read using fromfile() or
fromstring() (alias loads()).
pt = picogeojson.fromstring('{"type": "Point", "coordinates": [1.0, 3.0]}')
# -> Point(coordinates=[1.0, 3.0])
Sometimes a particular type of GeoJSON object is expected (e.g. from an
API GET request), but for safety the type needs to be checked.
Alternatively, the result_fromstring() function can be used, which
returns an object with safe accessors for specific GeoJSON types.
result = picogeojson.result_fromstring(api_response.decode("utf-8"))

# Expecting one or more points or multipoints
for geom in result.points:
# do something with points
# ...

for geom in result.multilinestrings:
# do something with multilinestrings
# ...
This works for Features too, and we can filter by the .properties
member.
result = picogeojson.result_fromstring(api_response.decode("utf-8"))

for feature in result.features("Polygon", {"type": "Lake", "state": "Oregon"}):
# do something with lakes in Oregon
# ...
GeoJSON objects may be constructed in Python and composed (merge())
or split (burst()).
points = [picogeojson.Point((1, 2)),
picogeojson.Point((3, 4)),
picogeojson.Point((5, 6))]

merged_points = picogeojson.merge(points)
# -> MultiPoint(coordinates=[(1, 2), (3, 4), (5, 6)])

split_points = picogeojson.burst(merged_points)
# -> [Point((1, 2)), Point((3, 4)), Point((5, 6))]
GeoJSON objects are serialized with tostring() (alias dumps()).
picogeojson.tostring(
picogeojson.Point([1.0, 3.0])
)
# -> {"coordinates": [1.0, 3.0], "type": "Point"}'
Keyword arguments can be passed to tostring() that - enforce
Polygon/MultiPolygon rotation direction, with counterclockwise for
external rings and clockwise for internal rings
(enforce_poly_winding) - split objects that cross the international
dateline into multipart objects, for easier processing
(antimeridian_cutting) - control whether a bbox member is
computed and added to the JSON output (write_bbox)
picogeojson will leverage
ujson as a backend if it is
installed. Otherwise, it uses Python’s built-in json module.

Performance
The read benchmark involves reading a list of earthquake features. The
write benchmark involves serializing the continent of Australia.

Module
Read
Write

json
1.49
2.00

geojson
6.74
same

picogeojson
1.84
same*

picogeojson+ujson
1.63
0.31*

*antimeridian cutting and polygon winding check set to False
This is a standalone Python package extracted from the
Karta geojson submodule.