Merge pull request #2648 from bsipocz/MAINT_fixing_23Q1_remotes

bsipocz · web-flow · commit 8b24c19057bd · 2023-01-26T15:06:29.000-08:00
MAINT: fixing numerous remote test failures
diff --git a/astroquery/eso/tests/test_eso_remote.py b/astroquery/eso/tests/test_eso_remote.py
@@ -10,7 +10,7 @@
                    u'hawki', u'isaac', u'naco', u'visir', u'vircam', u'apex',
                    u'giraffe', u'uves', u'xshooter', u'muse', u'crires',
                    u'kmos', u'sinfoni', u'amber', u'midi', u'pionier',
-                   u'gravity', u'espresso', u'wlgsu', u'matisse']
+                   u'gravity', u'espresso', u'wlgsu', u'matisse', u'eris']
 
 # Some tests take too long, leading to travis timeouts
 # TODO: make this a configuration item
diff --git a/astroquery/mpc/tests/test_mpc_remote.py b/astroquery/mpc/tests/test_mpc_remote.py
@@ -9,31 +9,33 @@
 @pytest.mark.remote_data
 class TestMPC:
 
-    @pytest.mark.parametrize('type, name', [
+    @pytest.mark.parametrize('target_type, name', [
         ('asteroid', 'ceres'),
         ('asteroid', 'eros'),
-        ('asteroid', 'vesta')])
-    def test_query_object_valid_object_by_name(self, type, name):
-        response = mpc.MPC.query_object_async(target_type=type, name=name)
+        ('asteroid', 'vesta'),
+        ('asteroid', 'pallas'),
+        ('asteroid', 'piszkesteto')])
+    def test_query_object_valid_object_by_name(self, target_type, name):
+        # Keep all 3 of the objects in the tests, too that used to cause issue
+        # https://github.com/astropy/astroquery/issues/2531
+        response = mpc.MPC.query_object_async(target_type=target_type, name=name)
         assert response.status_code == requests.codes.ok
         assert len(response.json()) == 1
         assert response.json()[0]['name'].lower() == name
 
-    @pytest.mark.parametrize('type, number', [
+    @pytest.mark.parametrize('target_type, number', [
         ('comet', '103P')])
-    def test_query_object_valid_object_by_number(self, type, number):
-        response = mpc.MPC.query_object_async(
-            target_type=type, number=number)
+    def test_query_object_valid_object_by_number(self, target_type, number):
+        response = mpc.MPC.query_object_async(target_type=target_type, number=number)
         assert response.status_code == requests.codes.ok
         assert len(response.json()) == 1
         assert str(response.json()[0]['number']) + \
             response.json()[0]['object_type'] == number
 
-    @pytest.mark.parametrize('type, designation', [
+    @pytest.mark.parametrize('target_type, designation', [
         ('comet', 'C/2012 S1')])
-    def test_query_object_valid_object_by_designation(self, type, designation):
-        response = mpc.MPC.query_object_async(
-            target_type=type, designation=designation)
+    def test_query_object_valid_object_by_designation(self, target_type, designation):
+        response = mpc.MPC.query_object_async(target_type=target_type, designation=designation)
         assert response.status_code == requests.codes.ok
         assert len(response.json()) == 1
         assert response.json()[0]['designation'].lower() == designation.lower()
diff --git a/astroquery/utils/commons.py b/astroquery/utils/commons.py
@@ -36,9 +36,7 @@
 ASTROPY_LT_4_3 = not minversion('astropy', '4.3')
 ASTROPY_LT_5_0 = not minversion('astropy', '5.0')
 
-ASTROPY_LT_5_1 = not minversion('astropy', '5.1dev197')
-# Update the line above once 5.1 is released
-# ASTROPY_LT_5_1 = not minversion('astropy', '5.1')
+ASTROPY_LT_5_1 = not minversion('astropy', '5.1')
 
 
 def radius_to_unit(radius, unit='degree'):
diff --git a/docs/cadc/cadc.rst b/docs/cadc/cadc.rst
@@ -41,7 +41,7 @@ these collections:
     TESS : {'Description': 'The TESS collection at the CADC', 'Bands': ['Optical']}
     UKIRT : {'Description': 'The UKIRT collection at the CADC', 'Bands': ['Infrared|Optical', '', 'Optical', 'Infrared']}
     VGPS : {'Description': 'The VGPS collection at the CADC', 'Bands': ['Radio']}
-    VLASS : {'Description': 'The VLASS collection at the CADC', 'Bands': ['', 'Radio']}
+    VLASS : {'Description': 'The VLASS collection at the CADC', 'Bands': ['Radio']}
     WALLABY : {'Description': 'The WALLABY collection at the CADC', 'Bands': ['Radio']}
     XMM : {'Description': 'The XMM collection at the CADC', 'Bands': ['Optical', 'UV', 'X-ray']}
 
@@ -51,7 +51,7 @@ region or by name. The following example queries CADC for Canada
 France Hawaii Telescope (CFHT) data for a given region and resolves
 the URLs for downloading the corresponding data.
 
-
+.. Remove IGNORE_WARNINGS once https://github.com/astropy/astroquery/issues/2523 is fixed
 .. doctest-remote-data::
 
     >>> from astroquery.cadc import Cadc
@@ -73,7 +73,7 @@ the URLs for downloading the corresponding data.
     caom:CFHT/2583703        2583703 ... 2021-02-26T10:37:42.355
     caom:CFHT/2376828        2376828 ... 2021-09-01T23:48:18.790
     caom:CFHT/2376828        2376828 ... 2021-09-01T23:48:18.790
-    >>> urls = cadc.get_data_urls(result)
+    >>> urls = cadc.get_data_urls(result)  # doctest: +IGNORE_WARNINGS
     >>> for url in urls:
     ...     print(url)   #doctest: +IGNORE_OUTPUT
     ...
@@ -92,14 +92,14 @@ the results on the name of the target (as an example - any other
 filtering possible) and resolves the URLs for both the primary and
 auxiliary data (in this case preview files)
 
-
+.. Remove IGNORE_WARNINGS once https://github.com/astropy/astroquery/issues/2523 is fixed
 .. doctest-remote-data::
 
     >>> from astroquery.cadc import Cadc
     >>> cadc = Cadc()
     >>> result = cadc.query_region('08h45m07.5s +54d18m00s')
     >>> urls = cadc.get_data_urls(result[result['target_name'] == 'Nr3491_1'],
-    ...                           include_auxiliaries=True)
+    ...                           include_auxiliaries=True)  # doctest: +IGNORE_WARNINGS
     >>> for url in urls:
     ...    print(url)  # doctest: +IGNORE_OUTPUT
     ...
@@ -136,15 +136,15 @@ the CADC metadata.
 If only a subsection of the FITS file is needed, CADC can query an
 area and resolve the cutout of a result.
 
-
+.. Remove IGNORE_WARNINGS once https://github.com/astropy/astroquery/issues/2523 is fixed
 .. doctest-remote-data::
 
     >>> from astropy import units as u
     >>> from astroquery.cadc import Cadc
     >>> cadc = Cadc()
     >>> coords = '01h45m07.5s +23d18m00s'
     >>> radius = 0.01*u.deg
-    >>> images = cadc.get_images(coords, radius, collection='CFHT')
+    >>> images = cadc.get_images(coords, radius, collection='CFHT')  # doctest: +IGNORE_WARNINGS
     >>> images  # doctest: +IGNORE_OUTPUT
     [<astropy.io.fits.hdu.image.PrimaryHDU object at 0x7f3805a06ef0>]
     [<astropy.io.fits.hdu.image.PrimaryHDU object at 0x7f3805b23b38>]
@@ -153,7 +153,7 @@ area and resolve the cutout of a result.
 Alternatively, if the query result is large and data does not need to be
 in memory, lazy access to the downloaded FITS file can be used.
 
-
+.. Remove IGNORE_WARNINGS once https://github.com/astropy/astroquery/issues/2523 is fixed
 .. doctest-remote-data::
 
     >>> from astropy import units as u
@@ -162,7 +162,7 @@ in memory, lazy access to the downloaded FITS file can be used.
     >>> cadc = Cadc()
     >>> coords = SkyCoord(10, 20, unit='deg')
     >>> radius = 0.01*u.deg
-    >>> readable_objs = cadc.get_images_async(coords, radius, collection='CFHT')
+    >>> readable_objs = cadc.get_images_async(coords, radius, collection='CFHT')  # doctest: +IGNORE_WARNINGS
     >>> readable_objs  # doctest: +IGNORE_OUTPUT
     Downloaded object from URL https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2234132o.fits.fz&RUNID=pot39nwwtaht03wc&POS=CIRCLE+26.2812589776878+23.299999818906816+0.01 with ID 140045451168112
     Downloaded object from URL https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368279p.fits.fz&RUNID=pot39nwwtaht03wc&POS=CIRCLE+26.2812589776878+23.299999818906816+0.01 with ID 140045451142576
@@ -181,7 +181,7 @@ are needed, the result table can be passed into the
 `~astroquery.cadc.CadcClass.get_image_list` function, along with the
 cutout coordinates and radius.
 
-
+.. Remove IGNORE_WARNINGS once https://github.com/astropy/astroquery/issues/2523 is fixed
 .. doctest-remote-data::
 
     >>> from astroquery.cadc import Cadc
@@ -191,7 +191,7 @@ cutout coordinates and radius.
     >>> radius = 0.1*u.deg
     >>> results = cadc.query_region(coords, radius, collection='CFHT')
     >>> filtered_results = results[results['time_exposure'] > 120.0]
-    >>> image_list = cadc.get_image_list(filtered_results, coords, radius)
+    >>> image_list = cadc.get_image_list(filtered_results, coords, radius)  # doctest: +IGNORE_WARNINGS
     >>> print(image_list)   # doctest: +IGNORE_OUTPUT
     ['https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368278o.fits.fz&RUNID=dbuswaj4zwruzi92&POS=CIRCLE+26.2812589776878+23.299999818906816+0.1',
     'https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368278p.fits.fz&RUNID=dbuswaj4zwruzi92&POS=CIRCLE+26.2812589776878+23.299999818906816+0.1',
diff --git a/docs/esa/iso/iso.rst b/docs/esa/iso/iso.rst
@@ -1,8 +1,8 @@
 .. _astroquery.esa.iso:
 
-****************************************
+**************************************
 ESA ISO Archive (`astroquery.esa.iso`)
-****************************************
+**************************************
 The Infrared Space Observatory (ISO) was a space telescope for infrared light designed and
 operated by the European Space Agency (ESA), in cooperation with ISAS (now part of JAXA) and NASA.
 The ISO was designed to study infrared light at wavelengths of 2.5 to 240 micrometres and operated
@@ -20,9 +20,9 @@ ESA experts at ESAC.
 Examples
 ========
 
-------------------------------
+--------------------
 1. Querying ISO data
-------------------------------
+--------------------
 
 .. doctest-remote-data::
 
@@ -79,9 +79,9 @@ print(table).
 Once we have the observations identifiers (TDT) we can invoke the data download. To discover the tables
 provided by this service, see section 'Getting Tables Details'.
 
-------------------------------
+-------------------
 2. Getting ISO data
-------------------------------
+-------------------
 
 .. doctest-remote-data::
 
@@ -153,33 +153,27 @@ we can loop on the observations to download the best products (DEFAULT_DATA_SET)
   INFO: http://nida.esac.esa.int/...
 
 
--------------------------------
-2. Getting ISO postcards
--------------------------------
+------------------------
+3. Getting ISO postcards
+------------------------
+
+This will download the ISO postcard for the observation '80001538' and it will stored in a PNG called
+'postcard.png'.
 
 .. doctest-remote-data::
 
   >>> from astroquery.esa.iso import ISO
-  >>> from IPython.display import Image
-  >>> from IPython.core.display import HTML
-  >>>
   >>> ISO.get_postcard('80001538', filename="postcard")   # doctest: +IGNORE_OUTPUT
   Downloading URL http://nida.esac.esa.int/nida-sl-tap/data?retrieval_type=POSTCARD&DATA_RETRIEVAL_ORIGIN=astroquery&tdt=80001538 to /Users...
-  >>> Image(filename = "postcard.png", width=400, height=100)
-  <IPython.core.display.Image object>
-
 
 .. figure:: images/campostcard.png
    :scale: 100%
    :alt: Postcard image for observation 80001538
 
-   The resulting plot from the example above
-
-This will download the ISO postcard for the observation '80001538' and it will stored in a PNG called
-'postcard.png'. Then, we display the postcard inside the python interface.
+   The postcard downloaded in the example above
 
 ------------------------------------------
-3. Getting ISO Tables Details through TAP
+4. Getting ISO Tables Details through TAP
 ------------------------------------------
 
 .. doctest-remote-data::
@@ -207,7 +201,7 @@ This will download the ISO postcard for the observation '80001538' and it will s
 This will show the available tables in ISO TAP service in the ISO Data Archive.
 
 -------------------------------------
-4. Getting columns details of ISO TAP
+5. Getting columns details of ISO TAP
 -------------------------------------
 
 .. doctest-remote-data::
@@ -231,9 +225,9 @@ This will show the column details of the table 'ida.observations' in ISO TAP ser
 in the ISO Data Archive.
 
 
--------------------------------------
-4. Working with ISO VO tables
--------------------------------------
+-----------------------------
+6. Working with ISO VO tables
+-----------------------------
 
 ISO provides Virtual Observatory compatible products and tables. Three different VO
 compatible tables are provided:
@@ -298,9 +292,10 @@ Same can be done to discover images M31 images:
   ISO CAM01 Image Target: M31_LW6 10.68375 41.26945 http://nida.esac.esa.int/nida-sl-tap/data?RETRIEVAL_TYPE=STANDALONE&obsno=583023050
   ISO CAM01 Image Target: M31_LW3 10.68375 41.26945 http://nida.esac.esa.int/nida-sl-tap/data?RETRIEVAL_TYPE=STANDALONE&obsno=583027030
 
--------------------------------------
-4. Working with ISO VO products
--------------------------------------
+-------------------------------
+7. Working with ISO VO products
+-------------------------------
+
 Either by invocation of the URL provided in every row of previous section or using the STANDALONE retrieval level, VO compatible products can be open using python astropy FITS module.
 
 Images can be displayed by using the following code:
diff --git a/docs/esasky/esasky.rst b/docs/esasky/esasky.rst
@@ -36,7 +36,8 @@ If you know the names of all the available catalogs you can use :meth:`~astroque
     'XMM-EPIC-STACK', 'XMM-EPIC', 'XMM-OM', 'XMM-SLEW', 'Tycho-2', 'Gaia-DR3', 'Hipparcos-2', 'HSC',
     'Herschel-HPPSC-070', 'Herschel-HPPSC-100', 'Herschel-HPPSC-160', 'Herschel-SPSC-250', 'Herschel-SPSC-350',
     'Herschel-SPSC-500', 'Planck-PGCC', 'Planck-PCCS2E-HFI', 'Planck-PCCS2-HFI', 'Planck-PCCS2-LFI', 'Planck-PSZ2',
-    'Icecube', 'Fermi_4FGL-DR2', 'Fermi_3FHL', 'Fermi_4LAC-DR2', '2WHSP', '2RXS', 'OU_Blazars']
+    'Icecube', 'Fermi_4FGL-DR2', 'Fermi_3FHL', 'Fermi_4LAC-DR2', '2WHSP', '2RXS', 'OU_Blazars',
+    'eROSITA-eFEDS-hard', 'eROSITA-eFEDS-main', 'eROSITA-etaCha-hard', 'eROSITA-etaCha-main']
 
 Get the available maps mission names
 ------------------------------------
@@ -48,7 +49,7 @@ If you know the names of all the available maps missions you can use :meth:`~ast
     >>> maps_list = ESASky.list_maps()
     >>> print(maps_list)
     ['INTEGRAL', 'XMM', 'Chandra', 'SUZAKU', 'XMM-OM-OPTICAL', 'XMM-OM-UV', 'HST-UV', 'HST-OPTICAL', 'HST-IR',
-    'ISO-IR', 'Herschel', 'AKARI', 'JWST-MID-IR', 'JWST-NEAR-IR', 'Spitzer', 'ALMA']
+    'ISO-IR', 'Herschel', 'AKARI', 'JWST-MID-IR', 'JWST-NEAR-IR', 'Spitzer', 'ALMA', 'eROSITA']
 
 Get the available spectra mission names
 ---------------------------------------
diff --git a/docs/eso/eso.rst b/docs/eso/eso.rst
@@ -110,7 +110,7 @@ list of available instrument-specific queries can be obtained with the
     >>> from astroquery.eso import Eso
     >>> eso = Eso()
     >>> eso.list_instruments()
-    ['fors1', 'fors2', 'sphere', 'vimos', 'omegacam', 'hawki', 'isaac', 'naco', 'visir',
+    ['fors1', 'fors2', 'sphere', 'vimos', 'omegacam', 'eris', 'hawki', 'isaac', 'naco', 'visir',
      'vircam', 'apex', 'giraffe', 'uves', 'xshooter', 'espresso', 'muse', 'crires',
      'kmos', 'sinfoni', 'amber', 'gravity', 'matisse', 'midi', 'pionier', 'wlgsu']
 
diff --git a/docs/ipac/ned/ned.rst b/docs/ipac/ned/ned.rst
@@ -27,9 +27,9 @@ instance if you want to query NGC 224
     >>> result_table = Ned.query_object("NGC 224")
     >>> print(result_table) # an astropy.table.Table
     No. Object Name     RA     ... Redshift Points Diameter Points Associations
-                     degrees   ...                                             
+                     degrees   ...
     --- ----------- ---------- ... --------------- --------------- ------------
-      1 MESSIER 031   10.68479 ...              38              13            2
+      1 MESSIER 031   10.68479 ...              39              13            2
 
 
 Query a region
@@ -240,7 +240,7 @@ for the specified object. We look at a simple example:
     No.       RA       ... Published Frequence Mode         Qualifiers
                        ...
     --- -------------- ... ------------------------ -------------------------
-      0 12h29m06.6997s ...                                                   
+      0 12h29m06.6997s ...
       1 12h29m06.7000s ...                                   Uncertain origin
       2 12h29m06.7000s ...                                   Uncertain origin
       3 12h29m06.7000s ...                                   Uncertain origin
@@ -251,17 +251,17 @@ for the specified object. We look at a simple example:
       8 12h29m06.7001s ...                                   Uncertain origin
       9 12h29m06.7001s ...                                   Uncertain origin
     ...            ... ...                      ...                       ...
-    123   12h29m07.55s ...   Broad-band measurement From reprocessed raw data
-    124   12h29m06.05s ...   Broad-band measurement        From new, raw data
-    125    12h29m06.5s ...   Broad-band measurement        From new, raw data
-    126    12h29m06.5s ...   Broad-band measurement From reprocessed raw data
-    127    12h29m09.0s ...                                   Uncertain origin
-    128    12h29m08.9s ...                                   Uncertain origin
-    129    12h29m07.9s ...                                   Uncertain origin
-    130      12h29m04s ...                                   Uncertain origin
-    131      12h29m06s ...                                   Uncertain origin
-    132      12h29m08s ...                                   Uncertain origin
-    Length = 133 rows
+    138   12h29m06.05s ...   Broad-band measurement        From new, raw data
+    139    12h29m06.5s ...   Broad-band measurement        From new, raw data
+    140    12h29m06.5s ...   Broad-band measurement From reprocessed raw data
+    141    12h29m09.0s ...                                   Uncertain origin
+    142    12h29m08.9s ...                                   Uncertain origin
+    143    12h29m07.9s ...                                   Uncertain origin
+    144      12h29m04s ...                                   Uncertain origin
+    145      12h29m06s ...                                   Uncertain origin
+    146      12h29m08s ...                                   Uncertain origin
+    147      12h29m06s ...                                   Uncertain origin
+    Length = 148 rows
 
 
 Reference/API
diff --git a/docs/jplhorizons/jplhorizons.rst b/docs/jplhorizons/jplhorizons.rst
diff --git a/docs/jplsbdb/jplsbdb.rst b/docs/jplsbdb/jplsbdb.rst
