Object

com.snowplowanalytics.iglu.schemaddl.jsonschema

SanityLinter

Related Doc: package jsonschema

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object SanityLinter

Contains Schema validation logic for JSON AST to find nonsense (impossible) JSON Schemas, ie. Schemas which cannot validate ANY value, yet syntactically correct. This doesn't have logic to validate accordance to JSON Schema specs such as non-empty required or numeric maximum. Separate validator should be used for that.

See also

https://github.com/snowplow/iglu/issues/164

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Type Members

  1. type LintProperty = Validation[String, Unit]

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    Check of single property

  2. type LintSchema = Validation[NonEmptyList[String], Unit]

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    Aggregated property lints

  3. type Linter = (Schema) ⇒ LintProperty

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    Function able to lint Schema AST

  4. trait SeverityLevel extends AnyRef

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. object FirstLevel extends SeverityLevel with Product with Serializable

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  5. object SecondLevel extends SeverityLevel with Product with Serializable

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. def lint(schema: Schema, severityLevel: SeverityLevel): LintSchema

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    Main working function, traversing JSON Schema It lints all properties on current level, then tries to extract all subschemas from properties like items, additionalItems etc and recursively lint them as well

    Main working function, traversing JSON Schema It lints all properties on current level, then tries to extract all subschemas from properties like items, additionalItems etc and recursively lint them as well

    schema

    parsed JSON AST

    returns

    non-empty list of summed failures (all, including nested) or unit in case of success

  15. val lintArrayProperties: Linter

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    Check that Schema with non-object type doesn't contain object properties

  16. val lintMaxLength: Linter

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    Check that schema with type string contains maxLength property or has other possibility to extract length

  17. val lintMinMaxItems: Linter

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    Check that array's minItems property isn't greater than maxItems

  18. val lintMinMaxLength: Linter

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    Check that string's minLength property isn't greater than maxLength

  19. val lintMinMaxPresent: Linter

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    Check that schema with type number or integer contains both minimum and maximum properties

  20. val lintMinimumMaximum: Linter

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    Check that number's minimum property isn't greater than maximum

  21. val lintNumberProperties: Linter

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    Check that Schema with non-numeric type doesn't contain numeric properties

  22. val lintObjectProperties: Linter

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    Check that Schema with non-object type doesn't contain object properties

  23. val lintPossibleKeys: Linter

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    Check that all required keys listed in properties

    Check that all required keys listed in properties

    To do

    take patternProperties in account

  24. val lintStringProperties: Linter

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    Check that Schema with non-string type doesn't contain string properties

  25. final def ne(arg0: AnyRef): Boolean

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  26. final def notify(): Unit

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  27. final def notifyAll(): Unit

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  28. val propertySuccess: Validation[String, Unit]

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    Some property was processed successfully

  29. val schemaSuccess: ValidationNel[String, Unit]

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    Whole subschema was processed successfully

  30. final def synchronized[T0](arg0: ⇒ T0): T0

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  31. def toString(): String

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  32. final def wait(): Unit

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  33. final def wait(arg0: Long, arg1: Int): Unit

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  34. final def wait(arg0: Long): Unit

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