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Schema Resources

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The schema-resource package is a simple library for loading jsonschema schemas using pkg_resources. This means that Python packages utilizing the schema-resource package can bundle schemas for validating API or user configuration as separate files with the package source. Further, those schemas may then reference other schema files within the package.

Simple Usage

The simplest way to use schema-resource begins by understanding the resource URI. A resource URI is a URI with the scheme “res”. The “network location”–the part that appears after the “//” in a URI–is the package name, as understood by pkg_resources. The path is then interpreted relative to the root directory of the package. For instance, if the package “spam” has a schema named “schema.yaml”, the resource URI would be “res://spam/schema.yaml”. This schema can then be loaded using schema_res.load_schema(), which takes the resource URI as its first argument; the result will be an object conforming to the jsonschema.IValidator interface documented in the jsonschema documentation.

This schema could, of course, be loaded by using a combination of jsonschema and pkg_resources directly; however, schema-resource creates the schema with a special jsonschema.RefResolver that understands these resource URIs; this enhancement allows one schema to refer to another, or part of another, resource schema directly.

Class Attributes

Often, a class needs to use a particular schema in order to validate input, often from an API or a configuration file. This can be simplified through the use of schema_res.SchemaDescriptor. This class implements the Python “descriptor” protocol, meaning that, when assigned to a class attribute, references to the value of the attribute will cause a method of schema_res.SchemaDescriptor to be called. That method implements an on-demand loading of a schema resource, constructing the resource URI if needed from the class’s __module__ attribute. For instance, assume that the Spam class below needs to validate data fed to a class method:

class Spam(object):
    schema = schema_res.SchemaDescriptor("spam.yaml")

    @classmethod
    def from_data(cls, data):
        cls.schema.validate(data)

        return cls(**data)

    ...

This class first validates the data against the schema loaded from the “spam.yaml” file bundled with the package sources, loading the schema the first time the method is called. (The jsonschema.IValidator.validate() method raises a jsonschema.ValidationError exception if the data doesn’t match the requirements of the schema.)

Validating Schemas

It is a good idea for the test suite for a package to verify that the schemas it bundles are valid. This could be done by simply using the schema_res.load_schema() function, calling it for each resource URI and passing validate=True, within the package’s test suite. However, there’s also a simple helper: schema_res.validate() takes one or more resource URIs and calls schema_res.load_schema() on each, passing validate=True. This means that this entire test can be written as a single function call, like so:

class TestSchemas(object):
    def test_valid(self):
        schema_res.validate(
            "res://spam/schema1.yaml",
            "res://spam/schema2.yaml",
            "res://spam/schema3.yaml",
        )

Schema Format

In all the examples so far, the schema filenames have had the “.yaml” extension. There is no specific need to use this extension, nor even for the files to be in YAML format: JSON is a subset of YAML, so the schema files can be written in regular JSON. However, by using a YAML parser to load the schema files, they may be expressed in YAML format, which this programmer finds easier to write and to read than strict JSON syntax.

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