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JSCK can create validators from multiple schemas, but this requires that each schema be identified with a URI in a top-level "id" field. In many cases, only a single schema is needed, and there is no need to uniquely identify the schema.
This is the easiest way to use JSCK, as it is a common pattern. See these advanced usage examples for help working with multiple schemas.
That is, JSCK generates the tree of functions needed to validate a particular schema when you construct a validator.
The schema is thus traversed only during preparation, and most of the work of interpreting the schema is done at this time, rather than for every document submitted for validation.
This minimizes the work required during validation, which leads to substantial performance improvements over non-compiling validators.
Currently passing the canonical test suite for draft3 except for these items:. Scope manipulation is a controversial topic, and with JSCK we have chosen to play it safe, supporting "id" declarations only in cases that will probably not lead to any ambiguity.
Specifically, JSCK uses "id" declarations only in these cases:. To run all tests for all versions:. See this document for more information on working with JSCK tests.
Pull requests welcome, of course. Because performance varies at very least based on the complexity of the schema being validated, we run benchmarks against several different schemas, ranging from quite simple to moderately complex.
On the trivial schema , our benchmarks produce this relative performance for these validators lower is better :.
For the schema of medium complexity , our benchmarks produce this relative performance for the tested validators lower is better :.
For the schema of higher complexity , our benchmarks produce this relative performance for the tested validators lower is better :.
As the complexity of the schema increases, the performance benefits of the compilation model become more evident. See this document for detailed results and information on running and creating benchmarks.
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Skip to content. The schema is thus traversed only during preparation, and most of the work of interpreting the schema is done at this time, rather than for every document submitted for validation.
This minimizes the work required during validation, which leads to substantial performance improvements over non-compiling validators.
Currently passing the canonical test suite for draft3 except for these items:. Scope manipulation is a controversial topic, and with JSCK we have chosen to play it safe, supporting "id" declarations only in cases that will probably not lead to any ambiguity.
Specifically, JSCK uses "id" declarations only in these cases:. To run all tests for all versions:. See this document for more information on working with JSCK tests.
Pull requests welcome, of course. Because performance varies at very least based on the complexity of the schema being validated, we run benchmarks against several different schemas, ranging from quite simple to moderately complex.
On the trivial schema , our benchmarks produce this relative performance for these validators lower is better :. For the schema of medium complexity , our benchmarks produce this relative performance for the tested validators lower is better :.
For the schema of higher complexity , our benchmarks produce this relative performance for the tested validators lower is better :.
As the complexity of the schema increases, the performance benefits of the compilation model become more evident.
See this document for detailed results and information on running and creating benchmarks. Git github.

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