geodesic.boson.dataset.Dataset.count#

Dataset.count(bbox=None, datetime=None, intersects=None, collections=None, ids=None, filter=None, method='POST', extra_params={})[source]#

Count items the dataset matching a particular set of filters.

Parameters:

  • bbox (List | None) – The spatial extent for the query as a bounding box. Example: [-180, -90, 180, 90]

  • datetime (List | Tuple | None) – The temporal extent for the query formatted as a list: [start, end].

  • intersects (object | None) – a geometry to use in the query

  • collections (List[str] | None) – a list of collections to search

  • ids (List[str] | None) – a list of feature/item IDs to filter to

  • filter (CQLFilter | dict | None) – a CQL2 filter. This is supported by most datasets but will not work for others.

  • method (str | None) – the HTTP method - POST is default and usually should be left alone unless a server doesn’t support

  • extra_params (dict | None) – a dict of additional parameters that will be passed along on the request.

Returns:

The number of items in the dataset matching the query.

Return type:

int

Examples

A query on the sentinel-2-l2a dataset with a given bounding box and time range. Additionally, you can apply filters on the parameters in the items.

>>> import datetime
>>> from geodesic.cql import CQLFilter
>>> bbox = [
...     -75.552893, 39.719814, -74.778357, 40.220805
... ]  # roughly the city of Philadelphia, PA
>>> date_range = (datetime.datetime(2022, 12,1), datetime.datetime(2024,12,1))
>>> ds.count(
...          bbox=bbox,
...          datetime=date_range,
...          filter=CQLFilter.lte("properties.eo:cloud_cover", 10.0)
... )
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