deb-python-jsonschema/docs/faq.rst

Frequently Asked Questions

Why doesn't my schema that has a default property actually set the default on my instance?

The basic answer is that the specification does not require that default actually do anything.

For an inkling as to why it doesn't actually do anything, consider that none of the other validators modify the instance either. More importantly, having default modify the instance can produce quite peculiar things. It's perfectly valid (and perhaps even useful) to have a default that is not valid under the schema it lives in! So an instance modified by the default would pass validation the first time, but fail the second!

Still, filling in defaults is a thing that is useful. jsonschema allows you to define your own validators <creating>, so you can easily create a IValidator that does do default setting. Here's some code to get you started:

from jsonschema import Draft4Validator, validators


def extend_with_default(validator_class):
    validate_properties = validator_class.VALIDATORS["properties"]

    def set_defaults(validator, properties, instance, schema):
        for error in validate_properties(
            validator, properties, instance, schema,
        ):
            yield error

        for property, subschema in properties.iteritems():
            if "default" in subschema:
                instance.setdefault(property, subschema["default"])

    return validators.extend(
        validator_class, {"properties" : set_defaults},
    )


DefaultValidatingDraft4Validator = extend_with_default(Draft4Validator)


# Example usage:
obj = {}
schema = {'properties': {'foo': {'default': 'bar'}}}
# Note jsonschem.validate(obj, schema, cls=DefaultValidatingDraft4Validator)
# will not work because the metaschema contains `default` directives.
DefaultValidatingDraft4Validator(schema).validate(obj)
assert obj == {'foo': 'bar'}

See the above-linked document for more info on how this works, but basically, it just extends the properties validator on a Draft4Validator to then go ahead and update all the defaults.

If you're interested in a more interesting solution to a larger class of these types of transformations, keep an eye on Seep, which is an experimental data transformation and extraction library written on top of jsonschema.

How do jsonschema version numbers work?

jsonschema tries to follow the Semantic Versioning specification.

This means broadly that no backwards-incompatible changes should be made in minor releases (and certainly not in dot releases).

The full picture requires defining what constitutes a backwards-incompatible change.

The following are simple examples of things considered public API, and therefore should not be changed without bumping a major version number:

• module names and contents, when not marked private by Python convention (a single leading underscore)
• function and object signature (parameter order and name)

The following are not considered public API and may change without notice:

• the exact wording and contents of error messages; typical reasons to do this seem to involve unit tests. API users are encouraged to use the extensive introspection provided in ~jsonschema.exceptions.ValidationErrors instead to make meaningful assertions about what failed.
• the order in which validation errors are returned or raised
• anything marked private

With the exception of the last of those, flippant changes are avoided, but changes can and will be made if there is improvement to be had. Feel free to open an issue ticket if there is a specific issue or question worth raising.