# Validation

Tapir supports validation for primitive types. Validation of composite values, whole data structures, business rules enforcement etc. should be done as part of the server logic of the endpoint, using the dedicated error output (the E in Endpoint[A, I, E, O, S]) to report errors.

For some guidelines as to where to perform a specific type of validation, see the “Validation analysis paralysis” article. A good indicator as to where to place particular validation logic might be if the property that we are checking is a format error, or a business-level error? The validation capabilities described in this section are intended only for format errors.

Validation rules added using the built-in validators are translated to OpenAPI documentation.

A validator is always part of a Schema, which is part of a Codec. It can validate either the top-level object, or some nested component (such as a field value).

If you are using automatic or semi-automatic schema derivation, validators for such schemas, and their nested components, including collections and options, can be added as described in schema customisation.

Validators can also be added to individual inputs/outputs. Behind the scenes, this modifies the schema, but it’s easier to add top-level validators this way, rather than modifying the implicit schemas, for example:

import sttp.tapir._

val e = endpoint.in(
query[Int]("amount")
.validate(Validator.min(0))
.validate(Validator.max(100)))


For optional/iterable inputs/outputs, to validate the contained value(s), use:

import sttp.tapir._

query[Option[Int]]("item").validateOption(Validator.min(0))
query[List[Int]]("item").validateIterable(Validator.min(0)) // validates each repeated parameter


Finally, if you are creating a reusable codec, a validator can be added to it as well:

import sttp.tapir._
import sttp.tapir.CodecFormat.TextPlain

case class MyId(id: String)

implicit val myIdCodec: Codec[String, MyId, TextPlain] = Codec.string
.map(MyId(_))(_.id)
.validate(Validator.pattern("^[A-Z].*").contramap(_.id))


## Decode failures

The validators are run when a value is being decoded from its low-level representation. This is done using the Codec.decode method, which returns a DecodeResult. Such a result can be successful, or a decoding failure.

Keep in mind that the validator mechanism described here is meant for input/output values which are in an incorrect low-level format. Validation and more generally decoding failures should be reported only for format failures. Business validation errors, which are often contextual, should use the error output instead.

To customise error messages that are returned upon validation/decode failures by the server, see error handling.

## Enumeration validators

Validators for enumerations can be created using:

• for arbitrary types, using Validator.enumeration, which takes the list of possible values

• for sealed hierarchies, where all implementations are objects, using Validator.derivedEnumeration[T]. This method is a macro which determines the possible values.

• for Scala3 enums, where all implementation don’t have parameters, using Validator.derivedEnumeration[T] as above

• for Scala2 Enumeration#Value, automatically derived Schemas have the validator added (see Schema.derivedEnumerationValue)

The enumeration schemas and codecs that are created by tapir-provided methods already have the enumeration validator added. See the section on enumerations for more information.

### Enumeration values in documentation

To properly represent possible values in documentation, the enum validator additionally needs an encode method, which converts the enum value to a raw type (typically a string). This can be specified by:

• explicitly providing it using the overloaded enumeration method with an encode parameter

• by using one of the .encode methods on the Validator.Enumeration instance

• when the values possible values are of a basic type (numbers, strings), the encode function is inferred if not present

• by adding the validator directly to a codec using .validate (the encode function is then taken from the codec)

For example:

import sttp.tapir._

sealed trait Color
case object Blue extends Color
case object Red extends Color

// providing the enum values by hand
implicit def colorSchema: Schema[Color] = Schema.string.validate(
Validator.enumeration(List(Blue, Red), (c: Color) => Some(c.toString.toLowerCase)))


## Validation of unrepresentable values

Note that validation is run on a fully decoded values. That is, during decoding, first all the provided decoding functions are run, followed by validations. If you’d like to validate before decoding, e.g. because the value isn’t representable unless validator conditions are met due to preconditions, you can use .mapValidate. However, this will cause the validator function to be run twice if there are no validation error.