TST: fixes for 2023 aug

CHANGES.rst

@@ -208,6 +208,9 @@ sdss
 - Switching to https to avoid issues originating in relying on server side
   redirects. [#2654]
 
+- Fix bug to have object IDs as integers on windows. [#2800]
+
+
 simbad
 ^^^^^^
 

astroquery/lamda/core.py

@@ -122,7 +122,7 @@ def get_molecules(self, *, cache=True):
         response = self._request('GET', main_url, cache=cache)
         response.raise_for_status()
 
-        soup = BeautifulSoup(response.content)
+        soup = BeautifulSoup(response.content, features="html5lib")
 
         links = soup.find_all('a', href=True)
         datfile_urls = [url

astroquery/sdss/core.py

@@ -1040,7 +1040,7 @@ def _parse_result(self, response, verbose=False):
                 warnings.filterwarnings("ignore", category=AstropyWarning,
                                         message=r'OverflowError converting to IntType in column.*')
             arr = Table.read(response.text, format='ascii.csv', comment="#")
-            for id_column in ('objid', 'specobjid'):
+            for id_column in ('objid', 'specobjid', 'objID', 'specobjID'):
                 if id_column in arr.columns:
                     arr[id_column] = arr[id_column].astype(np.int64)
 

astroquery/simbad/tests/test_simbad.py

@@ -347,17 +347,14 @@ def test_votable_fields():
     sb.add_votable_fields('rot', 'z_value', 'velocity')
     assert (set(sb.get_votable_fields())
             == set(['main_id', 'coordinates', 'rot', 'z_value', 'velocity']))
-    try:
-        sb.add_votable_fields('velocity')
-    except KeyError:
-        pass  # this is the expected response
+
     assert (set(sb.get_votable_fields())
             == set(['main_id', 'coordinates', 'rot', 'z_value', 'velocity']))
     sb.remove_votable_fields('rot', 'main_id', 'coordinates')
     assert set(sb.get_votable_fields()) == set(['z_value', 'velocity'])
     # Warning is expected as we removed the 'coordinates' field above:
     with pytest.warns(UserWarning, match="coordinates: this field is not set"):
-        sb.remove_votable_fields('rot', 'main_id', 'coordinates')
+        sb.remove_votable_fields('coordinates')
     assert set(sb.get_votable_fields()) == set(['z_value', 'velocity'])
     with pytest.warns(UserWarning, match="All fields have been removed. Resetting"):
         sb.remove_votable_fields('z_value', 'velocity')

docs/casda/casda.rst

@@ -25,7 +25,7 @@ For example:
     >>> from astropy import units as u
     >>> centre = SkyCoord.from_name('NGC 7232')
     >>> result_table = Casda.query_region(centre, radius=30*u.arcmin)
-    >>> print(result_table['obs_publisher_did','s_ra', 's_dec', 'obs_release_date'][:5])
+    >>> print(result_table['obs_publisher_did','s_ra', 's_dec', 'obs_release_date'][:5])  # doctest: +IGNORE_OUTPUT
     obs_publisher_did       s_ra           s_dec           obs_release_date
                             deg             deg
     ----------------- --------------- ---------------- ------------------------
@@ -45,7 +45,7 @@ For example to filter out the 30 non-public results from the above data set:
 .. doctest-remote-data::
 
     >>> public_results = Casda.filter_out_unreleased(result_table)
-    >>> print(public_results['obs_publisher_did','s_ra', 's_dec', 'obs_release_date'][:5])
+    >>> print(public_results['obs_publisher_did','s_ra', 's_dec', 'obs_release_date'][:5])  # doctest: +IGNORE_OUTPUT
     obs_publisher_did       s_ra           s_dec           obs_release_date
                             deg             deg
     ----------------- --------------- ---------------- ------------------------

docs/esa/jwst/jwst.rst

@@ -1,4 +1,3 @@
-
 .. _astroquery.esa.jwst:
 
 ****************************************
@@ -379,14 +378,14 @@ Once a table is loaded, columns can be inspected
   >>> from astroquery.esa.jwst import Jwst
   >>> table = Jwst.load_table('jwst.main')
   >>> print(*(column.name for column in table.columns), sep="\n")
-    "public"
-    algorithm_name
-    calibrationlevel
-    collection
-    creatorid
-    dataproducttype
-    energy_bandpassname
-    ...
+  public
+  algorithm_name
+  calibrationlevel
+  collection
+  creatorid
+  dataproducttype
+  energy_bandpassname
+  ...
 
 
 1.6 Synchronous query

docs/ipac/irsa/irsa.rst

@@ -68,7 +68,7 @@ entered as a string that is parsable by `~astropy.coordinates.Angle`.
     >>> import astropy.units as u
     >>> table = Irsa.query_region("m31", catalog="fp_psc", spatial="Cone",
     ...                           radius=2 * u.arcmin)
-    >>> print(table)
+    >>> print(table)  # doctest: +IGNORE_OUTPUT
         ra        dec         clon         clat     ...   angle     j_h   h_k   j_k
        deg        deg                               ...    deg
     ---------- ---------- ------------ ------------ ... ---------- ----- ----- -----

docs/ipac/irsa/most.rst

@@ -363,16 +363,16 @@ asteroid `Victoria <https://en.wikipedia.org/wiki/12_Victoria>`_ as:
       ra_obj    dec_obj  sun_dist geo_dist ... moon_sep saa_sep qual_frame image_set
      float64    float64  float64  float64  ... float64  float64   int64      int64
     ---------- --------- -------- -------- ... -------- ------- ---------- ---------
-    333.539704 -0.779309   1.8179   1.4638 ...  102.339  15.039         10         6
-    333.539704 -0.779309   1.8179   1.4638 ...  102.339  15.039         10         6
+    333.539704 -0.779308   1.8179   1.4638 ...  102.339  15.039         10         6
+    333.539704 -0.779308   1.8179   1.4638 ...  102.339  15.039         10         6
     333.589056 -0.747249   1.8179   1.4626 ...  103.825  46.517         10         6
     333.589056 -0.747249   1.8179   1.4626 ...  103.825  46.517         10         6
     333.638286  -0.71525   1.8179   1.4614 ...  105.327  89.053         10         6
     333.638286  -0.71525   1.8179   1.4614 ...  105.327  89.053         10         6
     333.687495 -0.683205   1.8178   1.4603 ...  106.803 115.076         10         6
     333.687495 -0.683205   1.8178   1.4603 ...  106.803 115.076         10         6
-    333.736581 -0.651221   1.8178   1.4591 ...  108.294  73.321         10         6
-    333.736581 -0.651221   1.8178   1.4591 ...  108.294  73.321         10         6
+    333.736581  -0.65122   1.8178   1.4591 ...  108.294  73.321         10         6
+    333.736581  -0.65122   1.8178   1.4591 ...  108.294  73.321         10         6
 
 To return more than just a table of image identifiers, use one of the more
 verbose output modes - ``Regular`` or ``Full``.
@@ -393,16 +393,16 @@ verbose output modes - ``Regular`` or ``Full``.
       ra_obj    dec_obj  sun_dist geo_dist ... moon_sep saa_sep qual_frame image_set
      float64    float64  float64  float64  ... float64  float64   int64      int64
     ---------- --------- -------- -------- ... -------- ------- ---------- ---------
-    333.539704 -0.779309   1.8179   1.4638 ...  102.339  15.039         10         6
-    333.539704 -0.779309   1.8179   1.4638 ...  102.339  15.039         10         6
+    333.539704 -0.779308   1.8179   1.4638 ...  102.339  15.039         10         6
+    333.539704 -0.779308   1.8179   1.4638 ...  102.339  15.039         10         6
     333.589056 -0.747249   1.8179   1.4626 ...  103.825  46.517         10         6
     333.589056 -0.747249   1.8179   1.4626 ...  103.825  46.517         10         6
     333.638286  -0.71525   1.8179   1.4614 ...  105.327  89.053         10         6
     333.638286  -0.71525   1.8179   1.4614 ...  105.327  89.053         10         6
     333.687495 -0.683205   1.8178   1.4603 ...  106.803 115.076         10         6
     333.687495 -0.683205   1.8178   1.4603 ...  106.803 115.076         10         6
-    333.736581 -0.651221   1.8178   1.4591 ...  108.294  73.321         10         6
-    333.736581 -0.651221   1.8178   1.4591 ...  108.294  73.321         10         6
+    333.736581  -0.65122   1.8178   1.4591 ...  108.294  73.321         10         6
+    333.736581  -0.65122   1.8178   1.4591 ...  108.294  73.321         10         6
 
 As demonstrated, the returned values are stored in a dictionary and which
 ``metadata`` key table matches the ``Brief`` output mode table.

docs/ipac/nexsci/nasa_exoplanet_archive.rst

@@ -93,7 +93,8 @@ A list of accessible tables can be found in the ``TAP_TABLES`` attribute:
 
     >>> from astroquery.ipac.nexsci.nasa_exoplanet_archive import NasaExoplanetArchive
     >>> NasaExoplanetArchive.TAP_TABLES
-    ['superwasptimeseries',
+    ['spectra',
+    'superwasptimeseries',
     'kelttimeseries',
     'DI_STARS_EXEP',
     'transitspec',

docs/jplsbdb/jplsbdb.rst

@@ -156,7 +156,7 @@ item:
 .. code-block:: python
 
    >>> sbdb['orbit']['moid_jup']   # doctest: +REMOTE_DATA
-   <Quantity 0.431 AU>
+   <Quantity 0.43 AU>
 
 Note that many of the items in the output dictionary are associated
 with `~astropy.units` which can be readily used for
@@ -167,7 +167,7 @@ orbit intersection distance of the target with respect to Jupiter
 .. code-block:: python
 
    >>> print(sbdb['orbit']['moid_jup'].to('km'))    # doctest: +REMOTE_DATA
-   64476682.271699995 km
+    64327084.40099999 km
 
 The vast majority of parameter names are identical to those used in
 the `SBDB API documentation

docs/lamda/lamda.rst

@@ -27,12 +27,12 @@ is called, then cached for future use.  If there has been an update and you
 want to reload the cache, you can find the cache file ``'molecules.json'`` and
 remove it:
 
-.. doctest-remote-data::
+.. doctest-skip::
 
     >>> import os
-    >>> Lamda.cache_location                   # doctest: +IGNORE_OUTPUT
+    >>> Lamda.cache_location
     '/Users/your_username/.astropy/cache/astroquery/Lamda'
-    >>> Lamda.moldict_path                     # doctest: +IGNORE_OUTPUT
+    >>> Lamda.moldict_path
     '/Users/your_username/.astropy/cache/astroquery/Lamda/molecules.json'
     >>> os.remove(Lamda.moldict_path)
 

docs/mpc/mpc.rst

@@ -359,7 +359,7 @@ degrees per hour:
 
     >>> eph = MPC.get_ephemeris('C/1996 B2', start='1996-03-01', step='1h', number=30 * 24)
     >>> print(eph['Proper motion'].quantity.to('deg/h').max())
-    0.7756944444444445 deg / h
+    0.17234444444444447 deg / h
 
 Sky coordinates are returned as quantities carrying units of degrees.
 If a sexagesimal representation is desired, they may be replaced with

docs/svo_fps/svo_fps.rst

@@ -25,7 +25,7 @@ range) can be listed with
     >>> from astroquery.svo_fps import SvoFps
     >>> index = SvoFps.get_filter_index(12_000*u.angstrom, 12_100*u.angstrom)
     >>> index.info
-    <Table length=14>
+    <Table length=15>
             name          dtype        unit
     -------------------- ------- ---------------
     FilterProfileService  object
@@ -62,6 +62,7 @@ range) can be listed with
                AsinhSoft float64
         TrasmissionCurve  object
 
+
 If the wavelength range contains too many entries then a ``TimeoutError`` will
 occur. A smaller wavelength range might succeed, but if a large range really is
 required then you can use the ``timeout`` argument to allow for a longer