Merge pull request #2952 from bsipocz/ENH_irsa_list_collection

ENH: adding list_collections to IRSA

CHANGES.rst

@@ -26,7 +26,10 @@ ipac.irsa
   ``columns``, and the ``cache`` and ``verbose`` kwargs have been
   deprecated as they have no effect. [#2823]
 
-- Method to run SIAv2 VO queries is added. [#2837]
+- Method to run SIAv2 VO queries, ``query_sia``, is added. [#2837]
+
+- Method to list available collections for SIA queries,
+  ``list_collections``, is added. [#2952]
 
 gaia
 ^^^^

astroquery/ipac/irsa/core.py

@@ -126,6 +126,19 @@ def query_sia(self, *, pos=None, band=None, time=None, pol=None,
                                                             f'pyvo.dam.obscore.{var}')
     query_sia.__doc__ = query_sia.__doc__.replace('_SIA2_PARAMETERS', SIA2_PARAMETERS_DESC)
 
+    def list_collections(self):
+        """
+        Return information of available IRSA SIAv2 collections to be used in ``query_sia`` queries.
+
+        Returns
+        -------
+        collections : A `~astropy.table.Table` object.
+            A table listing all the possible collections for IRSA SIA queries.
+        """
+        query = "SELECT DISTINCT collection from caom.observation ORDER by collection"
+        collections = self.query_tap(query=query)
+        return collections.to_table()
+
     @deprecated_renamed_argument(("selcols", "cache", "verbose"), ("columns", None, None), since="0.4.7")
     def query_region(self, coordinates=None, *, catalog=None, spatial='Cone',
                      radius=10 * u.arcsec, width=None, polygon=None,

astroquery/ipac/irsa/tests/test_irsa_remote.py

@@ -71,6 +71,14 @@ def test_list_catalogs(self):
         # (at the time of writing there are 933 tables in the list).
         assert len(catalogs) > 900
 
+    def test_list_collections(self):
+        collections = Irsa.list_collections()
+        # Number of available collections may change over time, test only for significant drop.
+        # (at the time of writing there are 110 collections in the list).
+        assert len(collections) > 100
+        assert 'spitzer_seip' in collections['collection']
+        assert 'wise_allwise' in collections['collection']
+
     def test_tap(self):
         query = "SELECT TOP 5 ra,dec FROM cosmos2015"
         with pytest.warns(expected_warning=DALOverflowWarning,

docs/ipac/irsa/irsa.rst

@@ -236,6 +236,31 @@ Enhanced Imaging products in the centre of the COSMOS field as an `~astropy.tabl
    >>> coord = SkyCoord('150.01d 2.2d', frame='icrs')
    >>> spitzer_images = Irsa.query_sia(pos=(coord, 1 * u.arcmin), collection='spitzer_seip').to_table()
 
+To list available collections for SIA queries, the
+`~astroquery.ipac.irsa.IrsaClass.list_collections` method is provided, and
+will return a `~astropy.table.Table`:
+
+.. doctest-remote-data::
+
+   >>> from astroquery.ipac.irsa import Irsa
+   >>> Irsa.list_collections()
+   <Table length=110>
+         collection
+           object
+   ---------------------
+        akari_allskymaps
+                   blast
+             bolocam_gps
+              bolocam_lh
+       bolocam_planck_sz
+                     ...
+             wise_allsky
+            wise_allwise
+             wise_prelim
+   wise_prelim_2bandcryo
+             wise_unwise
+              wise_z0mgs
+
 Now open a cutout image for one of the science images. You could either use
 the the IRSA on-premise data or the cloud version of it using the
 ``access_url`` or ``cloud_access`` columns. For more info about fits