In a simple way, JSON schema is an object with validation keywords.
The keywords and their values define what rules the data should satisfy to be valid.
- type
- Keywords for numbers
- Keywords for strings
- Keywords for arrays
- Keywords for objects
- Keywords for all types
type
keyword requires that the data is of certain type (or some of types). Its value can be a string (the allowed type) or an array of strings (multiple allowed types).
Type can be: number, integer, string, boolean, array, object or null.
Examples
-
schema:
{ "type": "number" }
valid:
1
,1.5
invalid:
"abc"
,"1"
,[]
,{}
,null
,true
-
schema:
{ "type": "integer" }
valid:
1
,2
invalid:
"abc"
,"1"
,1.5
,[]
,{}
,null
,true
-
schema:
{ "type": ["number", "string"] }
valid:
1
,1.5
,"abc"
,"1"
invalid:
[]
,{}
,null
,true
All examples above are JSON schemas that only require data to be of certain type to be valid.
Most other keywords apply only to a particular type of data. If the data is of different type, the keyword will not apply and the data will be considered valid.
The value of keyword maximum
(minimum
) should be a number. This value is the maximum (minimum) allowed value for the data to be valid.
The value of keyword exclusiveMaximum
(exclusiveMinimum
) should be a boolean value. These keyword cannot be used without maximum
(minimum
). If this keyword value is equal to true
, the data should not be equal to the value in maximum
(minimum
) keyword to be valid.
Examples
-
schema:
{ "maximum": 5 }
valid:
4
,5
, any non-number ("abc"
,[]
,{}
,null
,true
)invalid:
6
,7
-
schema:
{ "minimum": 5 }
valid:
5
,6
, any non-number ("abc"
,[]
,{}
,null
,true
)invalid:
4
,4.5
-
schema:
{ "minimum": 5, "exclusiveMinimum": true }
valid:
6
,7
, any non-number ("abc"
,[]
,{}
,null
,true
)invalid:
4.5
,5
The value of the keyword should be a number. The data to be valid should be a multiple of the keyword value (i.e. the result of division of the data on the value should be integer).
Examples
-
schema:
{ "multipleOf": 5 }
valid:
5
,10
, any non-number ("abc"
,[]
,{}
,null
,true
)invalid:
1
,4
-
schema:
{ "multipleOf": 2.5 }
valid:
2.5
,5
,7.5
, any non-number ("abc"
,[]
,{}
,null
,true
)invalid:
1
,4
The value of the keywords should be a number. The data to be valid should have length satisfying this rule. Unicode pairs are counted as a single character.
Examples
-
schema:
{ "maxLength": 5 }
valid:
"abc"
,"abcde"
, any non-string (1
,[]
,{}
,null
,true
)invalid:
"abcdef"
-
schema:
{ "minLength": 2 }
valid:
"ab"
,"😀😀"
, any non-string (1
,[]
,{}
,null
,true
)invalid:
"a"
,"😀"
The value of the keyword should be a string. The data to be valid should match the regular expression defined by the keyword value.
Ajv uses new RegExp(value)
to create the regular expression that will be used to test data.
Example
schema: { "pattern": "[abc]+" }
valid: "a"
, "abcd"
, "cde"
, any non-string (1
, []
, {}
, null
, true
)
invalid: "def"
, ""
The value of the keyword should be a string. The data to be valid should match the format with this name.
Ajv defines these formats: date, date-time, uri, email, hostname, ipv4, ipv6, regex.
Example
schema: { "format": "ipv4" }
valid: "192.168.0.1"
, any non-string (1
, []
, {}
, null
, true
)
invalid: "abc"
The value of keyword formatMaximum
(formatMinimum
) should be a string. This value is the maximum (minimum) allowed value for the data to be valid as determined by format
keyword.
Ajv defines comparison rules for formats "date"
, "time"
and `"date-time".
The value of keyword formatExclusiveMaximum
(formatExclusiveMinimum
) should be a boolean value. These keyword cannot be used without formatMaximum
(formatMinimum
). If this keyword value is equal to true
, the data to be valid should not be equal to the value in formatMaximum
(formatMinimum
) keyword.
Example
schema:
{
"format": "date",
"formatMaximum": "2016-02-06",
"formatExclusiveMaximum": true
}
valid: 2015-12-31
, "2016-02-05"
, any non-string
invalid: "2016-02-06"
, "2016-02-07"
, "abc"
The value of the keywords should be a number. The data array to be valid should not have more (less) items than the keyword value.
Example
schema: { "maxItems": 3 }
valid: []
, [1]
, ["1", 2, "3"]
, any non-array ("abc"
, 1
, {}
, null
, true
)
invalid: [1, 2, 3, 4]
The value of the keyword should be a boolean. If the keyword value is true
, the data array to be valid should have unique items.
Example
schema: { "uniqueItems": true }
valid: []
, [1]
, ["1", 2, "3"]
, any non-array ("abc"
, 1
, {}
, null
, true
)
invalid: [1, 2, 1]
, [{ "a": 1, "b": 2 }, { "b": 2, "a": 1 }]
The value of the keyword should be an object or an array of objects.
If the keyword value is an object, then for the data array to be valid each item of the array should be valid according to the schema in this value. In this case the "additionalItems" keyword is ignored.
If the keyword value is an array, then items with indeces less than the number of items in the keyword should be valid according to the schemas with the same indeces. Whether additional items are valid will depend on "additionalItems" keyword.
Examples
-
schema:
{ "items": { "type": "integer" } }
valid:
[1,2,3]
,[]
, any non-array (1
,"abc"
,{}
,null
,true
)invalid:
[1,"abc"]
-
schema:
{ "items": [ { "type": "integer" }, { "type": "string" } ] }
valid:
[1]
,[1, "abc"]
,[1, "abc", 2]
,[]
, any non-array (1
,"abc"
,{}
,null
,true
)invalid:
["abc", 1]
,["abc"]
The value of the keyword should be a boolean or an object.
If "items" keyword is not present or it is an object, "additionalItems" keyword is ignored regardless of its value.
If "items" keyword is an array and data array has not more items than the length of "items" keyword value, "additionalItems" keyword is also ignored.
If the length of data array is bigger than the length of "items" keyword value than the result of the validation depends on the value of "additionalItems" keyword:
false
: data is invalidtrue
: data is valid- an object: data is valid if all additional items (i.e. items with indeces greater or equal than "items" keyword value length) are valid according to the schema in "assitionalItems" keyword.
Examples
-
schema:
{ "additionalItems": { "type": "integer" } }
any data is valid against such schema - "additionalItems" is ignored.
-
schema:
{ "items": { "type": "integer" }, "additionalItems": { "type": "string" } }
valid:
[]
,[1, 2]
, any non-array ("additionalItems" is ignored)invalid:
[1, "abc"]
, (any array with some items other than integers) -
schema:
{ "items": [ { "type": "integer" }, { "type": "integer" } ], "additionalItems": true }
valid:
[]
,[1, 2]
,[1, 2, 3]
,[1, 2, "abc"]
, any non-arrayinvalid:
["abc"]
,[1, "abc", 3]
-
schema:
{ "items": [ { "type": "integer" }, { "type": "integer" } ], "additionalItems": { "type": "string" } }
valid:
[]
,[1, 2]
,[1, 2, "abc"]
, any non-arrayinvalid:
["abc"]
,[1, 2, 3]
The value of the keyword is a JSON-schema. The array is valid if it contains at least one item that is valid according to this schema.
Example
schema: { "contains": { "type": "integer" } }
valid: [1]
, [1, "foo"]
, any array with at least one integer, any non-array
invalid: []
, ["foo", "bar"]
, any array without integers
The same can be expressed using only draft 4 keywords but it is quite verbose. The schema from the example above is equivalent to:
{
"not": {
"type": "array",
"items": {
"not": { "type": "integer" }
}
}
}
The value of the keywords should be a number. The data object to be valid should have not more (less) properties than the keyword value.
Example
schema: { "maxProperties": 2 }
valid: {}
, {"a": 1}
, {"a": "1", "b": 2}
, any non-object
invalid: {"a": 1, "b": 2, "c": 3}
The value of the keyword should be an array of unique strings. The data object to be valid should contain all properties with names equal to the elements in the keyword value.
Example
schema: { "required": ["a", "b"] }
valid: {"a": 1, "b": 2}
, {"a": 1, "b": 2, "c": 3}
, any non-object
invalid: {}
, {"a": 1}
, {"c": 3, "d":4}
The value of the keyword should be a map with keys equal to data object properties. Each value in the map should be a JSON schema. For data object to be valid the corresponding values in data object properties should be valid according to these schemas.
Please note: properties
keyword does not require that the properties mentioned in it are present in the object (see examples).
Example
schema:
{
"properties": {
"foo": { "type": "string" },
"bar": {
"type": "number",
"minimum": 2
}
}
}
valid: {}
, {"foo": "a"}
, {"foo": "a", "bar": 2}
, any non-object
invalid: {"foo": 1}
, {"foo": "a", "bar": 1}
The value of this keyword should be a map where keys should be regular expressions and the values should be JSON schemas. For data object to be valid the values in data object properties that match regular expression(s) should be valid according to the corresponding schema(s).
When the value in data object property matches multiple regular expressions it should be valid according to all the schemas for all matched regular expressions.
Please note: patternProperties
keyword does not require that properties matching patterns are present in the object (see examples).
Example
schema:
{
"patternProperties": {
"^fo.*$": { "type": "string" },
"^ba.*$": { "type": "number" }
}
}
valid: {}
, {"foo": "a"}
, {"foo": "a", "bar": 1}
, any non-object
invalid: {"foo": 1}
, {"foo": "a", "bar": "b"}
The value of the keyword should be either a boolean or a JSON schema.
If the value is true
the keyword is ignored.
If the value is false
the data object to be valid should not have "additional properties" (i.e. properties other than those used in "properties" keyword and those that match patterns in "patternProperties" keyword).
If the value is a schema for the data object to be valid the values in all "additional properties" should be valid according to this schema.
Examples
-
schema:
{ "properties": { "foo": { "type": "number" } }, "patternProperties": { "^.*r$": { "type": "number" } }, "additionalProperties": false }
valid:
{}
,{"foo": 1}
,{"foo": 1, "bar": 2}
, any non-objectinvalid:
{"a": 3}
,{"foo": 1, "baz": 3}
-
schema:
{ "properties": { "foo": { "type": "number" } }, "patternProperties": { "^.*r$": { "type": "number" } }, "additionalProperties": { "type": "string" } }
valid:
{}
,{"a": "b"}
,{"foo": 1}
,{"foo": 1, "bar": 2}
,{"foo": 1, "bar": 2, "a": "b"}
, any non-objectinvalid:
{"a": 3}
,{"foo": 1, "baz": 3}
-
schema:
{ "properties": { "foo": { "type": "number" } }, "additionalProperties": false, "anyOf": [ "properties": { "bar": { "type": "number" } }, "properties": { "baz": { "type": "number" } } ] }
valid:
{}
,{"foo": 1}
, any non-objectinvalid:
{"bar": 2}
,{"baz": 3}
,{"foo": 1, "bar": 2}
, etc.
The value of the keyword is a map with keys equal to data object properties. Each value in the map should be either an array of unique property names ("property dependency") or a JSON schema ("schema dependency").
For property dependency, if the data object contains a property that is a key in the keyword value, then to be valid the data object should also contain all properties from the array of properties.
For schema dependency, if the data object contains a property that is a key in the keyword value, then to be valid the data object itself (NOT the property value) should be valid according to the schema.
Examples
-
schema (property dependency):
{ "dependencies": { "foo": ["bar", "baz"] } }
valid:
{"foo": 1, "bar": 2, "baz": 3}
,{}
,{"a": 1}
, any non-objectinvalid:
{"foo": 1}
,{"foo": 1, "bar": 2}
,{"foo": 1, "baz": 3}
-
schema (schema dependency):
{ "dependencies": { "foo": { "properties": { "bar": { "type": "number" } } } } }
valid:
{}
,{"foo": 1}
,{"foo": 1, "bar": 2}
,{"a": 1}
, any non-objectinvalid:
{"foo": 1, "bar": "a"}
The value of this keyword should be a map where keys should be regular expressions and the values should be objects with the following properties:
schema
(required) - should be a JSON schema. For data object to be valid the values in data object properties that match regular expression(s) should be valid according to the correspondingschema
(s).maximum
/minimum
(optional) - should be integers. For data object to be valid the number of properties that match regular expression(s) should be within limits set byminimum
(s) andmaximum
(s).
Example
schema:
{
"patternGroups": {
"^[a-z]+$": {
"minimum": 1,
"schema": { "type": "string" }
},
"^[0-9]+$": {
"minimum": 1,
"schema": { "type": "integer" }
}
}
}
valid: { "foo": "bar", "1": "2" }
, any non-object
invalid: {}
, { "foo": "bar" }
, { "1": "2" }
The value of this keyword should be an array of strings, each string being a regular expression. For data object to be valid each regular expression in this array should match at least one property name in the data object.
If the array contains multiple regular expressions, more than one expression can match the same property name.
Examples
-
schema:
{ "patternRequired": [ "f.*o" ] }
valid:
{ "foo": 1 }
,{ "-fo-": 1 }
,{ "foo": 1, "bar": 2 }
, any non-objectinvalid:
{}
,{ "bar": 2 }
,{ "Foo": 1 }
, -
schema:
{ "patternRequired": [ "f.*o", "b.*r" ] }
valid:
{ "foo": 1, "bar": 2 }
,{ "foobar": 3 }
, any non-objectinvalid:
{}
,{ "foo": 1 }
,{ "bar": 2 }
The value of the keyword should be an array of unique items of any types. The data is valid if it is deeply equal to one of items in the array.
Example
schema: { "enum": [ 2, "foo", {"foo": "bar" }, [1, 2, 3] ] }
valid: 2
, "foo"
, {"foo": "bar"}
, [1, 2, 3]
invalid: 1
, "bar"
, {"foo": "baz"}
, [1, 2, 3, 4]
, any value not in the array
The value of this keyword can be anything. The data is valid if it is deeply equal to the value of the keyword.
Example
schema: { "constant": "foo" }
valid: "foo"
invalid: any other value
The same can be achieved with enum
keyword using the array with one item. But constant
keyword is more than just a syntax sugar for enum
. In combination with the $data reference it allows to define equality relations between different parts of the data. This cannot be achieved with enum
keyword even with $data
reference because $data
cannot be used in place of one item - it can only be used in place of the whole array in enum
keyword.
Example
schema:
{
"properties": {
"foo": { "type": "number" },
"bar": { "constant": { "$data": "1/foo" } }
}
}
valid: { "foo": 1, "bar": 1 }
, {}
invalid: { "foo": 1 }
, { "bar": 1 }
, { "foo": 1, "bar": 2 }
The value of the keyword should be a JSON schema. The data is valid if it is invalid according to this schema.
Examples
-
schema:
{ "not": { "minimum": 3 } }
valid:
1
,2
invalid:
3
,4
, any non-number -
schema:
{ "not": { "items": { "not": { "type": "string" } } } }
valid:
["a"]
,[1, "a"]
, any array containing at least one stringinvalid:
[]
,[1]
, any non-array, any array not containing strings
The value of the keyword should be an array of JSON schemas. The data is valid if it matches exactly one JSON schema from this array. Validators have to validate data against all schemas to establish validity according to this keyword.
Example
schema:
{
"oneOf": [
{ "maximum": 3 },
{ "type": "integer" }
]
}
valid: 1.5
, 2.5
, 4
, 5
, any non-number
invalid: 2
, 3
, 4.5
, 5.5
The value of the keyword should be an array of JSON schemas. The data is valid if it is valid according to one or more JSON schemas in this array. Validators only need to validate data against schemas in order until the first schema matches (or until all schemas have been tried). For this reason validating against this keyword is faster than against "oneOf" keyword in most cases.
Example
schema:
{
"anyOf": [
{ "maximum": 3 },
{ "type": "integer" }
]
}
valid: 1.5
, 2
, 2.5
, 3
, 4
, 5
, any non-number
invalid: 4.5
, 5.5
The value of the keyword should be an array of JSON schemas. The data is valid if it is valid according to all JSON schemas in this array.
Example
schema:
{
"allOf": [
{ "maximum": 3 },
{ "type": "integer" }
]
}
valid: 2
, 3
invalid: 1.5
, 2.5
, 4
, 4.5
, 5
, 5.5
, any non-number
The value of the keyword is the array of if/then clauses. Each clause is the object with the following properties:
if
(optional) - the value is JSON-schemathen
(required) - the value is JSON-schema or booleancontinue
(optional) - the value is boolean
The validation process is dynamic; all clauses are executed sequentially in the following way:
if
:if
property is JSON-schema according to which the data is:- valid => go to step 2.
- invalid => go to the NEXT clause, if this was the last clause the validation of
switch
SUCCEEDS.
if
property is absent => go to step 2.
then
:then
property istrue
or it is JSON-schema according to which the data is valid => go to step 3.then
property isfalse
or it is JSON-schema according to which the data is invalid => the validation ofswitch
FAILS.
continue
:continue
property istrue
=> go to the NEXT clause, if this was the last clause the validation ofswitch
SUCCEEDS.continue
property isfalse
or absent => validation ofswitch
SUCCEEDS.
Examples
-
schema:
{ "switch": [ { "if": { "properties": { "power": { "minimum": 9000 } } }, "then": { "required": [ "disbelief" ] }, "continue": true }, { "then": { "required": [ "confidence" ] } } ] }
valid:
{ "power": 9000, "disbelief": true, "confidence": true }
{ "confidence": true }
{ "power": 1000, "confidence": true }
invalid:
{ "power": 9000 }
(disbelief
&confidence
are required){ "power": 9000, "disbelief": true }
(confidence
is always required){ "power": 1000 }
{}
-
schema:
{ "type": "integer", "switch": [ { "if": { "not": { "minimum": 1 } }, "then": false }, { "if": { "maximum": 10 }, "then": true }, { "if": { "maximum": 100 }, "then": { "multipleOf": 10 } }, { "if": { "maximum": 1000 }, "then": { "multipleOf": 100 } }, { "then": false } ] }
valid:
1
,5
,10
,20
,50
,100
,200
,500
,1000
invalid:
-1
,0
(<1)2000
(>1000)11
,57
,123
(any number with more than one non-zero digit)- non-integers