Searching¶
Search a STAC API with rustac.search.
In [4]:
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import contextily
import pandas
import rustac
from geopandas import GeoDataFrame
items = await rustac.search(
"https://stac.eoapi.dev", collections="MAXAR_Marshall_Fire_21_Update"
)
data_frame = GeoDataFrame.from_features(items)
data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"])
axis = data_frame.set_crs(epsg=4326).to_crs(epsg=3857).plot(alpha=0.5, edgecolor="k")
contextily.add_basemap(axis, source=contextily.providers.CartoDB.Positron)
axis.set_axis_off()
import contextily
import pandas
import rustac
from geopandas import GeoDataFrame
items = await rustac.search(
"https://stac.eoapi.dev", collections="MAXAR_Marshall_Fire_21_Update"
)
data_frame = GeoDataFrame.from_features(items)
data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"])
axis = data_frame.set_crs(epsg=4326).to_crs(epsg=3857).plot(alpha=0.5, edgecolor="k")
contextily.add_basemap(axis, source=contextily.providers.CartoDB.Positron)
axis.set_axis_off()
Search stac-geoparquet with DuckDB, no servers required!
In [5]:
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items = await rustac.search(
"../../data/100-sentinel-2-items.parquet",
datetime="2024-12-01T00:00:00Z/..",
)
data_frame = GeoDataFrame.from_features(items)
data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"])
data_frame[["datetime", "geometry"]]
items = await rustac.search(
"../../data/100-sentinel-2-items.parquet",
datetime="2024-12-01T00:00:00Z/..",
)
data_frame = GeoDataFrame.from_features(items)
data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"])
data_frame[["datetime", "geometry"]]
Out[5]:
| datetime | geometry | |
|---|---|---|
| 0 | 2024-12-03 17:46:29.024000+00:00 | POLYGON ((-105.36543 39.65938, -105.34153 39.7... |
| 1 | 2024-12-01 17:57:21.024000+00:00 | POLYGON ((-106.18317 40.64479, -104.88456 40.6... |
If you know you're going to a geopandas.GeoDataFrame(or something else that speaks arrow), you can use the arrow optional dependency for rustac (pip install 'rustac[arrow]') and search directly to arrow, which can be more efficient than going through JSON dictionaries.
In [6]:
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from rustac import DuckdbClient
client = DuckdbClient()
table = client.search_to_arrow(
"../../data/100-sentinel-2-items.parquet",
datetime="2024-12-01T00:00:00Z/..",
)
data_frame = GeoDataFrame.from_arrow(table)
data_frame[["datetime", "geometry"]]
from rustac import DuckdbClient
client = DuckdbClient()
table = client.search_to_arrow(
"../../data/100-sentinel-2-items.parquet",
datetime="2024-12-01T00:00:00Z/..",
)
data_frame = GeoDataFrame.from_arrow(table)
data_frame[["datetime", "geometry"]]
Out[6]:
| datetime | geometry | |
|---|---|---|
| 0 | 2024-12-03 10:46:29.024000-07:00 | POLYGON ((-105.36543 39.65938, -105.34153 39.7... |
| 1 | 2024-12-01 10:57:21.024000-07:00 | POLYGON ((-106.18317 40.64479, -104.88456 40.6... |