Convert STAC items to geoparquet.
This library helps convert STAC Items to geoparquet. It might be useful for you if you host a large number of STAC items through a STAC API, but want to provide a bulk API for users who need to access many items.
stac_geoparquet.to_dataframe does it all. You give it a list of (STAC Item) dictionaries. It just converts them to a geopandas.GeoDataFrame, which can be written to parquet with .to_parquet.
>>> import requests
>>> import stac_geoparquet
>>> item = requests.get("https://planetarycomputer.microsoft.com/api/stac/v1/collections/naip/items/ia_m_4209150_sw_15_060_20190828_20191105").json()
>>> df = stac_geoparquet.to_geodataframe([item])
>>> df.to_parquet("naip.parquet")Note that stac_geoparquet lifts the keys in the item properties up to the top level of the DataFrame, similar to geopandas.GeoDataFrame.from_features.
>>> list(df.columns)
['type',
'stac_version',
'stac_extensions',
'id',
'geometry',
'bbox',
'links',
'assets',
'collection',
'gsd',
'datetime',
'naip:year',
'proj:bbox',
'proj:epsg',
'naip:state',
'proj:shape',
'proj:transform']We also provide stac_geoparquet.to_dict and stac_geoparquet.to_item_collection helpers that can be used to convert from DataFrames back to the original STAC items.
stac_geoparquet.pgstac_reader has some helpers for working with items coming from a pgstac.items table. It takes care of
- Rehydrating the dehydrated items
- Partitioning by time
- Injecting dynamic links and assets from a STAC API