remove deprecated skip_fits_update

src/stdatamodels/fits_support.py

@@ -573,18 +573,10 @@ def _schema_has_fits_hdu(schema):
     return has_fits_hdu[0]
 
 
-def _load_from_schema(hdulist, schema, tree, context, skip_fits_update=False):
+def _load_from_schema(hdulist, schema, tree, context):
     known_keywords = {}
     known_datas = set()
 
-    # Check if there are any table HDU's. If not, this whole process
-    # can be skipped.
-    if skip_fits_update:
-        if not any(isinstance(hdu, fits.BinTableHDU) for hdu in hdulist if hdu.name != 'ASDF'):
-            log.debug('Skipping FITS updating completely.')
-            return known_keywords, known_datas
-        log.debug('Skipping FITS keyword updating except for BinTableHDU and its associated header keywords.')
-
     # Determine maximum EXTVER that could be used in finding named HDU's.
     # This is needed to constrain the loop over HDU's when resolving arrays.
     max_extver = max(hdu.ver for hdu in hdulist) if len(hdulist) else 0
@@ -597,7 +589,7 @@ def _load_from_schema(hdulist, schema, tree, context, skip_fits_update=False):
 
     def callback(schema, path, combiner, ctx, recurse):
         result = None
-        if not skip_fits_update and 'fits_keyword' in schema:
+        if 'fits_keyword' in schema:
             fits_keyword = schema['fits_keyword']
             result = _fits_keyword_loader(
                 hdulist, fits_keyword, schema,
@@ -683,7 +675,7 @@ def _load_history(hdulist, tree):
         history['entries'].append(HistoryEntry({'description': entry}))
 
 
-def from_fits(hdulist, schema, context, skip_fits_update=None, **kwargs):
+def from_fits(hdulist, schema, context, **kwargs):
     """Read model information from a FITS HDU list
 
     Parameters
@@ -696,32 +688,16 @@ def from_fits(hdulist, schema, context, skip_fits_update=None, **kwargs):
 
     context: DataModel
         The `DataModel` to update
-
-    skip_fits_update : bool or None
-        DEPRECATED
-        When `False`, models opened from FITS files will proceed
-        and load the FITS header values into the model.
-        When `True` and the FITS file has an ASDF extension, the
-        loading/validation of the FITS header will be skipped, loading
-        the model only from the ASDF extension.
-        When `None`, the value is taken from the environmental SKIP_FITS_UPDATE.
-        Otherwise, the default is `False`
     """
     try:
         ff = from_fits_asdf(hdulist, **kwargs)
     except Exception as exc:
         raise exc.__class__("ERROR loading embedded ASDF: " + str(exc)) from exc
 
-    # Determine whether skipping the FITS loading can be done.
-    skip_fits_update = _verify_skip_fits_update(
-        skip_fits_update, hdulist, ff, context
-    )
-
     known_keywords, known_datas = _load_from_schema(
-        hdulist, schema, ff.tree, context, skip_fits_update=skip_fits_update
+        hdulist, schema, ff.tree, context
     )
-    if not skip_fits_update:
-        _load_extra_fits(hdulist, known_keywords, known_datas, ff.tree)
+    _load_extra_fits(hdulist, known_keywords, known_datas, ff.tree)
 
     _load_history(hdulist, ff.tree)
 
@@ -810,67 +786,6 @@ def from_fits_hdu(hdu, schema):
     return data
 
 
-def _verify_skip_fits_update(skip_fits_update, hdulist, asdf_struct, context):
-    """Ensure all conditions for skipping FITS updating are true
-
-    Returns True if either 1) the FITS hash in the asdf structure matches the input
-    FITS structure. Or 2) skipping has been explicitly asked for in `skip_fits_update`.
-
-    Parameters
-    ----------
-    skip_fits_update : bool
-        Regardless of FIT hash check, attempt to skip if requested.
-
-    hdulist : astropy.io.fits.HDUList
-        The input FITS information
-
-    asdf_struct : asdf.ASDFFile
-        The associated ASDF structure
-
-    context : DataModel
-        The DataModel being built.
-
-    Returns
-    -------
-    skip_fits_update : bool
-        All conditions are satisfied for skipping FITS updating.
-    """
-    if skip_fits_update is None:
-        skip_fits_update = util.get_envar_as_boolean('SKIP_FITS_UPDATE', None)
-    if skip_fits_update is not None:
-        # warn if the value was not None (defined by the user)
-        warnings.warn("skip_fits_update is deprecated and will be removed", DeprecationWarning)
-
-    # If skipping has been explicitly disallowed, indicate as such.
-    if skip_fits_update is False:
-        return False
-
-    # Skipping has either been requested or has been left to be determined automatically.
-    # Continue checking conditions necessary for skipping.
-
-    # Need an already existing ASDF. If not, cannot skip.
-    if not len(asdf_struct.tree):
-        log.debug('No ASDF information found. Cannot skip updating from FITS headers.')
-        return False
-
-    # Ensure model types match
-    hdulist_model_type = util.get_model_type(hdulist)
-    if hdulist_model_type != context.__class__.__name__:
-        log.debug(f'Input model type {hdulist_model_type} does not match the'
-                  f' requested model {type(context)}.'
-                  ' Cannot skip updating from FITS headers.')
-        return False
-
-    # Check for FITS hash and compare to current. If equal, automatically skip.
-    if asdf_struct.tree.get(FITS_HASH_KEY, None) is not None:
-        if asdf_struct.tree[FITS_HASH_KEY] == fits_hash(hdulist):
-            log.debug('FITS hash matches. Skipping FITS updating.')
-            return True
-
-    # If skip only if explicitly requested.
-    return False if skip_fits_update is None else True
-
-
 def fits_hash(hdulist):
     """Calculate a hash based on all HDU headers
 

src/stdatamodels/jwst/datamodels/tests/test_models.py

@@ -27,31 +27,6 @@
 ASN_FILE = os.path.join(ROOT_DIR, 'association.json')
 
 
-@pytest.fixture
-def make_models(tmp_path):
-    """Create basic models
-
-    Returns
-    -------
-    path_just_fits, path_model : (str, str)
-        `path_just_fits` is a FITS file of `JwstDataModel` without the ASDF extension.
-        `path_model` is a FITS file of `JwstDataModel` with the ASDF extension.
-    """
-    path_just_fits = tmp_path / 'just_fits.fits'
-    path_model = tmp_path / 'model.fits'
-    primary_hdu = fits.PrimaryHDU()
-    primary_hdu.header['EXP_TYPE'] = 'NRC_IMAGE'
-    primary_hdu.header['DATAMODL'] = "JwstDataModel"
-    hduls = fits.HDUList([primary_hdu])
-    hduls.writeto(path_just_fits)
-    model = JwstDataModel(hduls)
-    model.save(path_model)
-    return {
-        'just_fits': path_just_fits,
-        'model': path_model
-    }
-
-
 def test_init_from_pathlib(tmp_path):
     """Test initializing model from a Path object"""
     path = tmp_path / "pathlib.fits"
@@ -62,52 +37,6 @@ def test_init_from_pathlib(tmp_path):
         assert isinstance(model, ImageModel)
 
 
-@pytest.mark.parametrize('which_file, skip_fits_update, expected_exp_type',
-                         [
-                             ('just_fits', None, 'FGS_DARK'),
-                             ('just_fits', False, 'FGS_DARK'),
-                             ('just_fits', True, 'FGS_DARK'),
-                             ('model', None, 'FGS_DARK'),
-                             ('model', False, 'FGS_DARK'),
-                             ('model', True, 'NRC_IMAGE')
-                         ]
-                         )
-@pytest.mark.parametrize('use_env', [False, True])
-def test_skip_fits_update(jail_environ,
-                          use_env,
-                          make_models,
-                          which_file,
-                          skip_fits_update,
-                          expected_exp_type):
-    """Test skip_fits_update setting"""
-    # Setup the FITS file, modifying a header value
-    path = make_models[which_file]
-    with fits.open(path) as hduls:
-        hduls[0].header['exp_type'] = 'FGS_DARK'
-
-        # Decide how to skip. If using the environmental,
-        # set that and pass None to the open function.
-        try:
-            del os.environ['SKIP_FITS_UPDATE']
-        except KeyError:
-            # No need to worry, environmental doesn't exist anyways
-            pass
-
-        if skip_fits_update is not None:
-            ctx = pytest.warns(DeprecationWarning, match="skip_fits_update is deprecated")
-        else:
-            ctx = contextlib.nullcontext()
-
-        if use_env:
-            if skip_fits_update is not None:
-                os.environ['SKIP_FITS_UPDATE'] = str(skip_fits_update)
-                skip_fits_update = None
-
-        with ctx:
-            with datamodels.open(hduls, skip_fits_update=skip_fits_update) as model:
-                assert model.meta.exposure.type == expected_exp_type
-
-
 def test_asnmodel_table_size_zero():
     with AsnModel() as dm:
         assert len(dm.asn_table) == 0

src/stdatamodels/jwst/datamodels/tests/test_multislit.py

@@ -113,7 +113,7 @@ def test_multislit_copy(tmp_path):
     path = tmp_path / "multislit.fits"
     with MultiSlitModel() as input:
         for i in range(4):
-            input.slits.append(input.slits.item(data=np.empty((50, 50))))
+            input.slits.append(input.slits.item(data=np.empty((50, 50), dtype='f4')))
 
         assert len(input.slits) == 4
         input.save(path)

src/stdatamodels/jwst/datamodels/util.py

@@ -70,14 +70,6 @@ def open(init=None, guess=True, memmap=False, **kwargs):
              If `True`, arrays will be validated against ndim, max_ndim, and datatype
              validators in the schemas.
 
-        - FITS
-
-           skip_fits_update :  bool or None
-              DEPRECATED
-              `True` to skip updating the ASDF tree from the FITS headers, if possible.
-              If `None`, value will be taken from the environmental SKIP_FITS_UPDATE.
-              Otherwise, the default value is `True`.
-
     Returns
     -------
     model : DataModel instance

src/stdatamodels/model_base.py

@@ -128,15 +128,7 @@ def __init__(self, init=None, schema=None, memmap=False,
 
         kwargs : dict
             Additional keyword arguments passed to lower level functions. These arguments
-            are generally file format-specific. Arguments of note are:
-
-            - FITS
-
-              skip_fits_update - bool or None
-                  DEPRECATED
-                  `True` to skip updating the ASDF tree from the FITS headers, if possible.
-                  If `None`, value will be taken from the environmental SKIP_FITS_UPDATE.
-                  Otherwise, the default value is `True`.
+            are generally file format-specific.
         """
 
         # Override value of validation parameters if not explicitly set.

tests/test_fits.py

@@ -9,6 +9,7 @@
 
 from stdatamodels import DataModel
 from stdatamodels import fits_support
+from stdatamodels.jwst import datamodels
 
 from models import FitsModel, PureFitsModel
 
@@ -381,58 +382,23 @@ def test_ensure_ascii():
         fits_support.ensure_ascii(inp) == "ABCDEFG"
 
 
-@pytest.mark.parametrize(
-    'which_file, skip_fits_update, expected_exp_type',
-    [
-        ('just_fits', None,  'FGS_DARK'),
-        ('just_fits', False, 'FGS_DARK'),
-        ('just_fits', True,  'FGS_DARK'),
-        ('model',     None,  'FGS_DARK'),
-        ('model',     False, 'FGS_DARK'),
-        ('model',     True,  'NRC_IMAGE')
-    ]
-)
-@pytest.mark.parametrize(
-    'use_env',
-    [False, True]
-)
-def test_skip_fits_update(tmp_path,
-                          monkeypatch,
-                          use_env,
-                          which_file,
-                          skip_fits_update,
-                          expected_exp_type):
-    """Test skip_fits_update setting"""
+def test_fits_update(tmp_path):
+    """Test that FITS changes are seen when datamodels are opened"""
     file_path = tmp_path/"test.fits"
+    expected_exp_type = 'FGS_DARK'
 
     # Setup the FITS file, modifying a header value
-    if which_file == "just_fits":
-        primary_hdu = fits.PrimaryHDU()
-        primary_hdu.header['EXP_TYPE'] = 'NRC_IMAGE'
-        primary_hdu.header['DATAMODL'] = "FitsModel"
-        hduls = fits.HDUList([primary_hdu])
-        hduls.writeto(file_path)
-    else:
-        model = FitsModel()
-        model.meta.exposure.type = 'NRC_IMAGE'
-        model.save(file_path)
-
-    with fits.open(file_path) as hduls:
-        hduls[0].header['EXP_TYPE'] = 'FGS_DARK'
-
-        if skip_fits_update is not None:
-            ctx = pytest.warns(DeprecationWarning, match="skip_fits_update is deprecated")
-        else:
-            ctx = contextlib.nullcontext()
-
-        if use_env:
-            if skip_fits_update is not None:
-                monkeypatch.setenv("SKIP_FITS_UPDATE", str(skip_fits_update))
-                skip_fits_update = None
-
-        with ctx:
-            model = FitsModel(hduls, skip_fits_update=skip_fits_update)
-            assert model.meta.exposure.type == expected_exp_type
+    model = datamodels.ImageModel()
+    model.meta.exposure.type = 'NRC_IMAGE'
+    model.save(file_path)
+    del model
+
+    with fits.open(file_path) as hdulist:
+        hdulist['PRIMARY'].header['EXP_TYPE'] = expected_exp_type
+        hdulist.writeto(file_path, overwrite=True)
+
+    with datamodels.open(file_path) as model:
+        assert model.meta.exposure.type == expected_exp_type
 
 
 def test_from_hdulist(tmp_path):