Schema Validation

The Basics

The simplest way to validate an instance under a given schema is to use the validate() function.

jsonschema.validate(instance, schema, cls=None, *args, **kwargs)[source]

Validate an instance under the given schema.

>>> validate([2, 3, 4], {"maxItems": 2})
Traceback (most recent call last):
    ...
ValidationError: [2, 3, 4] is too long

validate() will first verify that the provided schema is itself valid, since not doing so can lead to less obvious error messages and fail in less obvious or consistent ways. If you know you have a valid schema already or don’t care, you might prefer using the IValidator.validate method directly on a specific validator (e.g. Draft6Validator.validate).

Parameters:
  • instance – The instance to validate
  • schema – The schema to validate with
  • cls (IValidator) – The class that will be used to validate the instance.

If the cls argument is not provided, two things will happen in accordance with the specification. First, if the schema has a $schema property containing a known meta-schema [1] then the proper validator will be used. The specification recommends that all schemas contain $schema properties for this reason. If no $schema property is found, the default validator class is Draft6Validator.

Any other provided positional and keyword arguments will be passed on when instantiating the cls.

Raises:
  • `jsonschema.exceptions.ValidationError` if the instance – is invalid
  • `jsonschema.exceptions.SchemaError` if the schema itself – is invalid

Footnotes

[1]known by a validator registered with jsonschema.validators.validates
[2]For information on creating JSON schemas to validate your data, there is a good introduction to JSON Schema fundamentals underway at Understanding JSON Schema

The Validator Interface

jsonschema defines an (informal) interface that all validator classes should adhere to.

class jsonschema.IValidator(schema, types=(), resolver=None, format_checker=None)
Parameters:
  • schema (dict) – the schema that the validator object will validate with. It is assumed to be valid, and providing an invalid schema can lead to undefined behavior. See IValidator.check_schema to validate a schema first.
  • resolver – an instance of RefResolver that will be used to resolve $ref properties (JSON references). If unprovided, one will be created.
  • format_checker – an instance of FormatChecker whose FormatChecker.conforms method will be called to check and see if instances conform to each format property present in the schema. If unprovided, no validation will be done for format. Certain formats require additional packages to be installed (ipv5, uri, color, date-time). The required packages can be found at the bottom of this page.
  • types

    Deprecated since version 3.0.0: Use TypeChecker.redefine and jsonschema.validators.extend instead of this argument.

    If used, this overrides or extends the list of known types when validating the type property.

    What is provided should map strings (type names) to class objects that will be checked via isinstance.

META_SCHEMA

An object representing the validator’s meta schema (the schema that describes valid schemas in the given version).

VALIDATORS

A mapping of validator names (strs) to functions that validate the validator property with that name. For more information see Creating or Extending Validator Classes.

TYPE_CHECKER

A TypeChecker that will be used when validating type properties in JSON schemas.

schema

The schema that was passed in when initializing the object.

DEFAULT_TYPES

Deprecated since version 3.0.0: Use of this attribute is deprecated in favor of the new type checkers.

See Validating With Additional Types for details.

For backwards compatibility on existing validator classes, a mapping of JSON types to Python class objects which define the Python types for each JSON type.

Any existing code using this attribute should likely transition to using TypeChecker.is_type.

classmethod check_schema(schema)

Validate the given schema against the validator’s META_SCHEMA.

Raises:jsonschema.exceptions.SchemaError if the schema is invalid
is_type(instance, type)

Check if the instance is of the given (JSON Schema) type.

Return type:bool
Raises:jsonschema.exceptions.UnknownType if type is not a known type.
is_valid(instance)

Check if the instance is valid under the current schema.

Return type:bool
>>> schema = {"maxItems" : 2}
>>> Draft3Validator(schema).is_valid([2, 3, 4])
False
iter_errors(instance)

Lazily yield each of the validation errors in the given instance.

Return type:an collections.Iterable of jsonschema.exceptions.ValidationErrors
>>> schema = {
...     "type" : "array",
...     "items" : {"enum" : [1, 2, 3]},
...     "maxItems" : 2,
... }
>>> v = Draft3Validator(schema)
>>> for error in sorted(v.iter_errors([2, 3, 4]), key=str):
...     print(error.message)
4 is not one of [1, 2, 3]
[2, 3, 4] is too long
validate(instance)

Check if the instance is valid under the current schema.

Raises:jsonschema.exceptions.ValidationError if the instance is invalid
>>> schema = {"maxItems" : 2}
>>> Draft3Validator(schema).validate([2, 3, 4])
Traceback (most recent call last):
    ...
ValidationError: [2, 3, 4] is too long

All of the versioned validators that are included with jsonschema adhere to the interface, and implementers of validator classes that extend or complement the ones included should adhere to it as well. For more information see Creating or Extending Validator Classes.

Type Checking

To handle JSON Schema’s type property, a IValidator uses an associated TypeChecker. The type checker provides an immutable mapping between names of types and functions that can test if an instance is of that type. The defaults are suitable for most users - each of the versioned validators that are included with jsonschema have a TypeChecker that can correctly handle their respective versions.

See also

Validating With Additional Types

For an example of providing a custom type check.

class jsonschema.TypeChecker(type_checkers=pmap({}))[source]

A type property checker.

A TypeChecker performs type checking for an IValidator. Type checks to perform are updated using TypeChecker.redefine or TypeChecker.redefine_many and removed via TypeChecker.remove or TypeChecker.remove_many. Each of these return a new TypeChecker object.

Parameters:type_checkers (dict) – The initial mapping of types to their checking functions.
is_type(instance, type)[source]

Check if the instance is of the appropriate type.

Parameters:
  • instance (object) – The instance to check
  • type (str) – The name of the type that is expected.
Returns:

Whether it conformed.

Return type:

bool

Raises:

jsonschema.exceptions.UndefinedTypeCheck – if type is unknown to this object.

redefine(type, fn)[source]

Redefine the checker for type to the function fn.

Parameters:
  • type (str) – The name of the type to check.
  • fn (callable) – A function taking exactly two parameters - the type checker calling the function and the instance to check. The function should return true if instance is of this type and false otherwise.
Returns:

A new TypeChecker instance.

redefine_many(definitions=())[source]

Redefine multiple type checkers.

Parameters:definitions (dict) – A dictionary mapping types to their checking functions.
Returns:A new TypeChecker instance.
remove(type)[source]

Remove the type from the checkers that this object understands.

Parameters:type (str) – The name of the type to remove.
Returns:A new TypeChecker instance
Raises:jsonschema.exceptions.UndefinedTypeCheck – if type is unknown to this object
remove_many(types)[source]

Remove multiple types from the checkers that this object understands.

Parameters:types (Iterable) – An iterable of types to remove.
Returns:A new TypeChecker instance
Raises:jsonschema.exceptions.UndefinedTypeCheck – if any of the types are unknown to this object
exception jsonschema.exceptions.UndefinedTypeCheck(type)[source]

Raised when trying to remove a type check that is not known to this TypeChecker, or when calling jsonschema.TypeChecker.is_type directly.

Validating With Additional Types

Occasionally it can be useful to provide additional or alternate types when validating the JSON Schema’s type property.

jsonschema tries to strike a balance between performance in the common case and generality. For instance, JSON Schema defines a number type, which can be validated with a schema such as {"type" : "number"}. By default, this will accept instances of Python numbers.Number. This includes in particular ints and floats, along with decimal.Decimal objects, complex numbers etc. For integer and object, however, rather than checking for numbers.Integral and collections.abc.Mapping, jsonschema simply checks for int and Dictionary displays, since the more general instance checks can introduce significant slowdown, especially given how common validating these types are.

If you do want the generality, or just want to add a few specific additional types as being acceptable for a validator object, then you should update an existing TypeChecker or create a new one. You may then create a new IValidator via jsonschema.validators.extend.

class MyInteger(object):
    pass

def is_my_int(checker, instance):
    return (
        Draft3Validator.TYPE_CHECKER.is_type(instance, "number") or
        isinstance(instance, MyInteger)
    )

type_checker = Draft3Validator.TYPE_CHECKER.redefine("number", is_my_int)

CustomValidator = extend(Draft3Validator, type_checker=type_checker)
validator = CustomValidator(schema={"type" : "number"})
exception jsonschema.exceptions.UnknownType(type, instance, schema)[source]

Versioned Validators

jsonschema ships with validator classes for various versions of the JSON Schema specification. For details on the methods and attributes that each validator class provides see the IValidator interface, which each included validator class implements.

class jsonschema.Draft6Validator(schema, types=(), resolver=None, format_checker=None)
class jsonschema.Draft4Validator(schema, types=(), resolver=None, format_checker=None)
class jsonschema.Draft3Validator(schema, types=(), resolver=None, format_checker=None)

For example, if you wanted to validate a schema you created against the Draft 6 meta-schema, you could use:

from jsonschema import Draft6Validator

schema = {
    "$schema": "http://json-schema.org/schema#",

    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "email": {"type": "string"},
    },
    "required": ["email"]
}
Draft6Validator.check_schema(schema)

Validating Formats

JSON Schema defines the format property which can be used to check if primitive types (strings, numbers, booleans) conform to well-defined formats. By default, no validation is enforced, but optionally, validation can be enabled by hooking in a format-checking object into an IValidator.

>>> validate("localhost", {"format" : "hostname"})
>>> validate(
...     "-12", {"format" : "hostname"}, format_checker=FormatChecker(),
... )
Traceback (most recent call last):
    ...
ValidationError: "-12" is not a "hostname"

Note

Since fully validating an email address requires checking that it is formatted correctly, as well as that it belongs to the correct recipient, the email format validator only provides a sanity check, not full rfc5322 validation.

class jsonschema.FormatChecker(formats=None)[source]

A format property checker.

JSON Schema does not mandate that the format property actually do any validation. If validation is desired however, instances of this class can be hooked into validators to enable format validation.

FormatChecker objects always return True when asked about formats that they do not know how to validate.

To check a custom format using a function that takes an instance and returns a bool, use the FormatChecker.checks or FormatChecker.cls_checks decorators.

Parameters:formats (Iterable) – The known formats to validate. This argument can be used to limit which formats will be used during validation.
checkers

A mapping of currently known formats to tuple of functions that validate them and errors that should be caught. New checkers can be added and removed either per-instance or globally for all checkers using the FormatChecker.checks or FormatChecker.cls_checks decorators respectively.

classmethod cls_checks(format, raises=())

Register a decorated function as globally validating a new format.

Any instance created after this function is called will pick up the supplied checker.

Parameters:
  • format (str) – the format that the decorated function will check
  • raises (Exception) – the exception(s) raised by the decorated function when an invalid instance is found. The exception object will be accessible as the jsonschema.exceptions.ValidationError.cause attribute of the resulting validation error.
check(instance, format)[source]

Check whether the instance conforms to the given format.

Parameters:
  • instance (any primitive type, i.e. str, number, bool) – The instance to check
  • format (str) – The format that instance should conform to
Raises:

FormatError – if the instance does not conform to format

checks(format, raises=())[source]

Register a decorated function as validating a new format.

Parameters:
  • format (str) – The format that the decorated function will check.
  • raises (Exception) –

    The exception(s) raised by the decorated function when an invalid instance is found.

    The exception object will be accessible as the jsonschema.exceptions.ValidationError.cause attribute of the resulting validation error.

conforms(instance, format)[source]

Check whether the instance conforms to the given format.

Parameters:
  • instance (any primitive type, i.e. str, number, bool) – The instance to check
  • format (str) – The format that instance should conform to
Returns:

whether it conformed

Return type:

bool

exception jsonschema.FormatError(message, cause=None)[source]

There are a number of default checkers that FormatCheckers know how to validate. Their names can be viewed by inspecting the FormatChecker.checkers attribute. Certain checkers will only be available if an appropriate package is available for use. The available checkers, along with their requirement (if any,) are listed below.

Note

If the following packages are not installed when using a checker that requires it, validation will succeed without throwing an error, as specified by the JSON Schema specification.

Checker Notes
hostname  
ipv4  
ipv6 OS must have socket.inet_pton function
email  
uri requires rfc3987
date-time requires strict-rfc3339 [2]
date  
time  
regex  
color requires webcolors