stac-static
Implements search for static STAC catalogs following the pystac-client API.
There are a whole bunch of static STAC catalogs listed at: https://stacindex.org/catalogs?access=public&type=static
Example
Pass a catalog object into the search function (slow)
import pystac
from stac_static import search
URL = "https://www.planet.com/data/stac/disasters/hurricane-harvey/catalog.json"
catalog = pystac.read_file(URL)
result = search(catalog, filter="platform = 'SS02'")
result.item_collection()Or pass a geodataframe representing some items (faster)
import geopandas
import pystac
import planetary_computer as pc
from stac_static import search
URL = "https://planetarycomputer.microsoft.com/api/stac/v1/collections/io-lulc-9-class"
collection = pystac.read_file(URL)
asset = pc.sign(collection.assets["geoparquet-items"])
df = geopandas.read_parquet(
asset.href, storage_options=asset.extra_fields["table:storage_options"]
)
result = search(df, datetime="2019")
list(result.items())If you are going to be searching the same catalog repeatedly and there is no predefined geoparquet file to download, then you can create one and cache it locally
import geopandas
import pystac
from stac_static import search, from_geoparquet, to_geoparquet, to_geodataframe
URL = "https://www.planet.com/data/stac/disasters/hurricane-harvey/catalog.json"
catalog = pystac.read_file(URL)
path = f"{catalog.id}.parq"
df = to_geodataframe(catalog)
to_geoparquet(df, path)Once you have cached the geodataframe you can search on that (fastest)
df = from_geoparquet(cache_path)
result = search(df, filter="view:azimuth < 200")
result.item_collection()What doesn't work yet
-
filtering with temporal filters.
- This work depends on pygeofilter which has not yet implemented temporal filters.
-
query: no plan to support this since it is redundant with filters