sand.results

sand.results.Collection(selection: list[str], collec_table: DataFrame) → DataFrame

Extract a selection of collections from a reference table as pandas DataFrame

This function filters a reference table of collections to include only the requested collections, verifying that all requested collections exist.

Parameters:

• selection (list[str]) – List of collection names to select

• collec_table (pd.DataFrame) – Reference table containing collection information. Must have a ‘Name’ column containing collection names.

Returns:

Filtered table containing only the selected collections,

sorted by collection name

Return type:

pd.DataFrame

Raises:

AssertionError – If any requested collection name is not found in the reference table

Example

>>> ref_table = pd.DataFrame({
...     'Name': ['LANDSAT-5-TM', 'SENTINEL-2', 'VENUS'],
...     'Level': [1, 2, 1]
... })
>>> selected = Collection(['LANDSAT-5-TM', 'VENUS'], ref_table)
>>> print(selected['Name'])
0    LANDSAT-5-TM
1    VENUS

class sand.results.SandProduct(product_id: str, date: str, metadata: dict, index: str = None)

Bases: object

date: str

index: str = None

metadata: dict

product_id: str

to_dict()

class sand.results.SandQuery(json_values: list[SandProduct])

Bases: object

Format a list of product dictionaries.

This class is fully serializable using pickle for saving and loading query results.

Parameters:

json_value (list[dict]) – List of dictionaries, each representing a product with keys like ‘id’, ‘name’, ‘links’, etc.

equals(obj)