Make asdf standard 1.6.0 stable (default)

[braingram]

Description

I milestoned this PR for asdf 4.0 because it's a rather major change.

Making 1.6.0 stable will require:
Phase 0 (at any time):

• switch tag keywords for external tags to wildcards spacetelescope/rad#370
• Decomission package asdf-unit-schemas#34

Phase 1:

• remove test check for tag in fits schema #1749

Phase 2:

• Remove the last tag in the schemas asdf-standard#421

Phase 3:

• Update core for ASDF standard 1.6.0 asdf-standard#422
• release asdf-standard with above PR
• Update schemas for ASDF standard 1.6.0 asdf-coordinates-schemas#55
• Update schemas for ASDF standard 1.6.0 asdf-transform-schemas#110
• release asdf-transform-schemas asdf-coordinates-schemas with above PRs
• update Update schemas for ASDF standard 1.6.0 asdf-wcs-schemas#59 to add pins for asdf-transform-schemas and asdf-coordinates-schemas
• release asdf-wcs-schemas

Unfortunately at this point most of the schema repo CIs will be broken (as will asdf-astropy CI) due to the intertwined nature of these packages.

Phase 4:

• update below asdf-astropy PR with new asdf-standard, asdf-coordinates-schemas, asdf-transform-schemas
• Update for ASDF standard 1.6.0 astropy/asdf-astropy#219
• release asf-astropy
• Add asdf resources test and update schemas for new transform schemas spacetelescope/stdatamodels#258
• Update schemas for upcoming ASDF standard 1.6.0 sunpy/sunpy#7432
• updates for upcoming ASDF standard 1.6.0 DKISTDC/dkist#324
• Schema updates for current and upcoming asdf changes BAMWelDX/weldx#910
• update lower pin for asdf-wcs-schemas in gwcs: Increase asdf-wcs-schemas version spacetelescope/gwcs#491

Phase 5:

• this PR

Much of the above is due to updates to the ndarray schema:

• Update ndarray schema to 1.1 to fix issue 345 asdf-standard#350
• add float16 support to version 1.6.0 asdf-standard#411

All schemas that $ref ndarray (like quantity) then need a version bump and so on...

This is further complicated by quantity-1.1.0 currently existing in 2 released packages:

• asdf-standard
• asdf-unit-schemas

(because of an incomplete effort to split unit fits table and time out of the core).
The approach taken here is to decomission asdf-unit-schemas. asdf-standard will continue to provide updates to the unit (and other non-core) schemas. This seems sensible as these schemas are highly interdependent. More details can be found in: asdf-format/asdf-standard#422

One question that occupied a lot of my thought was "should we change some of the $refs to tags?" On one hand this could make migrations like this easier (if every ndarray $ref was instead a wildcard tag (ndarray-1.*) most of these schemas would not need to be updated. However, this links the tag to the schema which has a few downsides:

• as tags depend on the extension version, we have effectively added a second version to the schema (a tag might only appear say in asdf-standard 1.6.0 which means that a schema that contains a tag link to that tag will only be valid for asdf-standard 1.6.0).
• tag links make "duck typing" with a schema very difficult if not impossible.

For example unit/quantity contains a $ref link to unit/unit. This means that asdf-astropy can use a differently tagged unit (astropy/unint for non-vo units) and still produce a valid unit/quantity (see the wfi schema in rad as an example). If instead unit/quantity used a tag link to unit/unit, this same "duck typing" would not work with a differently tagged unit. asdf-astropy would have to instead:

• use a different schema for the unit/unit tag (this would break the tag-schema mapping defined in the standard unit manifest making any file produced with this approach likely to be incompatible with any other implementation or with other libraries that might choose to implement units)
• define a new astropy/quantity for non-vo units (and so on up the tree of schema references...)
• add the astropy/unit tag to the quantity schema (further linking tags and schemas and requiring addition standard schema updates for "downstream" libraries).

At the moment I am of the mind that keeping the schemas as separate from the tags as possible is the better option (so $ref instead of tag). This allows the schemas to function even if they are treated as normal "jsonschema"s. Additionally the tag validator behavior seems loosely defined in the standard where it states "Implementation of this validator is optional and depends on details of the YAML parser." For similar reasons the above asdf-transform-schemas PR did not rely on the feature in asdf to use multiple schemas in a tag definition (to allow the many transforms that $ref the transform schema to instead include them in the manifest).

Both stdatamodels (datamodels) and rad use metaschemas based off of asdf-schema-1.0.0 (which is updated to 1.1.0 in asdf-format/asdf-standard#422). As neither of these packages version schemas updating the metaschema version will force these packages to use exclusively the 1.6.0 standard (which will almost certainly cause issues if old versions of asdf/asdf-standard are used). Instead, I suggest we not update the metaschemas (and keep them using the old asdf-schema-1.0.0 metaschema). The only downside is the lack of float16 support in the datatype keyword validator. This seems like an acceptable limitation for the time being. Once asdf standard 1.6.0 is stable and the asdf version that sets it as the default agrees with the minimum required version for each of those packages the metaschemas can be updated.

Closes: #1866

Checklist:

• pre-commit checks ran successfully
• tests ran successfully
• for a public change, a changelog entry was added
• for a public change, documentation was updated
• for any new features, unit tests were added

[braingram]

Reserving a comment for regression tests.

Roman 1 expected and unrelated failure:
https://github.com/spacetelescope/RegressionTests/actions/runs/11562256445
JWST all pass:
https://github.com/spacetelescope/RegressionTests/actions/runs/11562239771

[braingram]

The weldx downstream failure is real. I rebased the open PR and added a comment that the development branch will soon be moving to asdf 4.0. We will need to keep in mind that the asdf downstream test will fail after this PR is merged.

[braingram]

#1866 to track adding this change to "what's new"

EDIT: pushed commit that adds this to docs

[perrygreenfield]

Both stdatamodels (datamodels) and rad use metaschemas based off of asdf-schema-1.0.0 (which is updated to 1.1.0 in asdf-format/asdf-standard#422). As neither of these packages version schemas updating the metaschema version will force these packages to use exclusively the 1.6.0 standard (which will almost certainly cause issues if old versions of asdf/asdf-standard are used). Instead, I suggest we not update the metaschemas (and keep them using the old asdf-schema-1.0.0 metaschema). The only downside is the lack of float16 support in the datatype keyword validator. This seems like an acceptable limitation for the time being. Once asdf standard 1.6.0 is stable and the asdf version that sets it as the default agrees with the minimum required version for each of those packages the metaschemas can be updated.

Does this mean that use of float16 in datatype won't pass validation until 1.6.0 becomes default? I want to make sure I understand the consequence (not that I disagree with it).

[braingram]

Both stdatamodels (datamodels) and rad use metaschemas based off of asdf-schema-1.0.0 (which is updated to 1.1.0 in asdf-format/asdf-standard#422). As neither of these packages version schemas updating the metaschema version will force these packages to use exclusively the 1.6.0 standard (which will almost certainly cause issues if old versions of asdf/asdf-standard are used). Instead, I suggest we not update the metaschemas (and keep them using the old asdf-schema-1.0.0 metaschema). The only downside is the lack of float16 support in the datatype keyword validator. This seems like an acceptable limitation for the time being. Once asdf standard 1.6.0 is stable and the asdf version that sets it as the default agrees with the minimum required version for each of those packages the metaschemas can be updated.

Does this mean that use of float16 in datatype won't pass validation until 1.6.0 becomes default? I want to make sure I understand the consequence (not that I disagree with it).

float16 support is available in 1.6.0. We could start using it in (for example) romancal once 1.6.0 is "stable" (which I'm considering the same as making it the default). The metaschema issues won't prevent using float16 arrays in (for example) roman datamodels (schemas aren't checked against metaschemas as part of validation).

However the metaschema issue will mean that adding a datatype validator to the float16 array would cause the call to check_schema that pytest-asdf runs to fail.

To provide an example. Let's say we want to change ImageModel.data to use float16. We could change this line:
https://github.com/spacetelescope/rad/blob/f2d7af769ec0fd77283cdcbe020cca96f026a5a4/src/rad/resources/schemas/wfi_image-1.0.0.yaml#L45
to:

datatype: float16

and save files without issue (no validation errors as long as we assign a float16 array to data). However the following would fail (and is equivalent to a check that pytest-asdf runs on schema files):

>> asdf.schema.check_schema(asdf.schema.load_schema("asdf://stsci.edu/datamodels/roman/schemas/wfi_image-1.0.0"))
ValidationError: 'float16' is not valid under any of the given schemas

due to the wfi_image-1.0.0 using the asdf://stsci.edu/datamodels/roman/schemas/rad_schema-1.0.0 metaschema which refs http://stsci.edu/schemas/asdf/asdf-schema-1.0.0 which refs http://stsci.edu/schemas/asdf/core/ndarray-1.0.0#/definitions/datatype which doesn't define float16 as a valid datatype.

Note that this only prevents adding something like:

datatype: float16

to the schemas that extend asdf-schema-1.0.0. Files can contain float16 arrays (as long as they use ASDF 1.6.0).

[perrygreenfield]

So this only affects validation of schemas against the metaschema I take it. OK, that isn't so serious.

[perrygreenfield]

LGTM