RSchema

Schema-based validation and coercion for Ruby data structures. Heavily inspired by Prismatic/schema.

Meet RSchema

RSchema provides a way to describe, validate, and coerce the "shape" of data.

First you create a schema:

blog_post_schema = RSchema.define_hash {{
  title: _String,
  tags: array(_Symbol),
  body: _String,
}}

Then you can use the schema to validate data:

input = {
  title: "One Weird Trick Developers Don't Want You To Know!",
  tags: [:trick, :developers, :unbeleivable],
  body: '<p>blah blah</p>'
}
blog_post_schema.valid?(input) #=> true

What Is A Schema?

Schemas are objects that describe and validate a value.

The simplest schemas are Type schemas, which just check the type of a value.

schema = RSchema.define { _Integer }
schema.class #=> RSchema::Schemas::Type

schema.valid?(1234) #=> true
schema.valid?('hi') #=> false

Then there are composite schemas, which are schemas composed of subschemas.

Array schemas are composite schemas:

schema = RSchema.define { array(_Integer) }
schema.valid?([10, 11, 12])  #=> true
schema.valid?([10, 11, :hi]) #=> false

And so are hash schemas:

schema = RSchema.define_hash {{
  fname: _String,
  age: _Integer,
}}

schema.valid?({ fname: 'Jane', age: 27 }) #=> true
schema.valid?({ fname: 'Johnny no age' }) #=> false

Schema objects are composable – they are designed to be combined. This allows schemas to describe complex, nested data structures.

schema = RSchema.define_hash {{
  fname: maybe(_String),
  favourite_foods: set(_Symbol),
  children_by_age: variable_hash(_Integer => _String)
}}

input = {
  fname: nil,
  favourite_foods: Set[:bacon, :cheese, :onion],
  children_by_age: {
    7 => 'Jenny',
    5 => 'Simon',
  },
}

schema.valid?(input) #=> true

RSchema provides many different kinds of schema classes for common tasks, but you can also write custom schema classes if you need to.

The DSL

Schemas are usually created and composed via a DSL using RSchema.define. Schemas can be created without the DSL, but the DSL is much more succinct.

For example, the following two schemas are identical. schema1 is created via the DSL, and schema2 is created manually.

schema1 = RSchema.define { array(_Symbol) }

schema2 = RSchema::Schemas::Convenience.wrap(
  RSchema::Schemas::VariableLengthArray.new(
    RSchema::Schemas::Type.new(Symbol)
  )
)

You will probably not need to create schemas manually unless you are doing something advanced.

For a full list of DSL methods, see the API documentation for RSchema::DSL.

Errors (When Validation Fails)

When something fails validation, it is often important to know exactly which values were invalid, and why. RSchema provides details about every failure within a result object.

schema = RSchema.define do
  array(
    fixed_hash(
      name: _String,
      hair: enum([:red, :brown, :blonde, :black])
    )
  )
end

input = [
  { name: 'Dane', hair: :black },
  { name: 'Tom', hair: :brown },
  { name: 'Effie', hair: :blond },
  { name: 'Chris', hair: :red },
]

result = schema.validate(input)

result.class  #=> RSchema::Result
result.valid? #=> false
result.error  #=> { 2 => { :hair => #<RSchema::Error> } }

The error above says that the value :blond, which exists at location input[2][:hair], is not a valid enum member. Looking back at the schema, we see that there is a typo, and it should be :blonde instead of :blond.

Error objects contain a lot of information, which can be used to generate error messages for developers or users.

error = result.error[2][:hair]
error.class #=> RSchema::Error

error.value #=> :blond
error.symbolic_name #=> :not_a_member
error.schema #=> #<RSchema::Schemas::Enum ...>
error.schema.members #=> [:red, :brown, :blonde, :black]
error.to_s #=> "RSchema::Schemas::Enum/not_a_member"
error.inspect
  #=> "<RSchema::Error RSchema::Schemas::Enum/not_a_member value=:blond>"

Type Schemas

The most basic kind of schema is a Type schema. Type schemas validate the class of a value using is_a?.

schema = RSchema.define { type(String) }
schema.valid?('hi') #=> true
schema.valid?(1234) #=> false

Type schemas are so common that the RSchema DSL provides a shorthand way to create them, using an underscore prefix:

schema1 = RSchema.define { _Integer }
# is exactly the same as
schema2 = RSchema.define { type(Integer) }

Because type schemas use is_a?, they handle subclasses, and can also be used to check for included modules like Enumerable:

schema = RSchema.define { _Enumerable }
schema.valid?([1, 2, 3]) #=> true
schema.valid?({ a: 12 }) #=> true

Variable-length Array Schemas

There are two types of array schemas. The first type are VariableLengthArray schemas, which check that all elements in the array conform to a single subschema:

schema = RSchema.define { array(_Symbol) }

schema.valid?([:a, :b, :c]) #=> true
schema.valid?([:a]) #=> true
schema.valid?([]) #=> true

Fixed-length Array Schemas

There are also FixedLengthArray schemas, where the array must have a specific length, and each element of the array has a separate subschema:

schema = RSchema.define { array(_Integer, _String) }

schema.valid?([10, 'hello']) #=> true
schema.valid?(['heyoo', 33]) #=> false

Fixed Hash Schemas

There are also two kinds of hash schemas.

FixedHash schemas describe hashes where they keys are known constants:

schema = RSchema.define do
  fixed_hash(
    name: _String,
    age: _Integer,
  )
end

schema.valid?({ name: 'George', age: 2 }) #=> true

Elements can be optional:

schema = RSchema.define do
  fixed_hash(
    name: _String,
    optional(:age) => _Integer,
  )
end

schema.valid?({ name: 'Lucy', age: 21 }) #=> true
schema.valid?({ name: 'Ageless Tommy' }) #=> true

FixedHash schemas are common, so the RSchema.define_hash method exists to make their creation more convenient:

schema = RSchema.define_hash {{
  name: _String,
  optional(:age) => _Integer,
}}

Variable Hash Schemas

VariableHash schemas are for hashes where the keys are not known ahead of time. They contain one subschema for keys, and another subschema for values.

schema = RSchema.define { variable_hash(_Symbol => _Integer) }
schema.valid?({}) #=> true
schema.valid?({ a: 1 }) #=> true
schema.valid?({ a: 1, b: 2 }) #=> true

Other Schema Types

RSchema provides a few other schema types through its DSL:

# boolean (only true or false)
boolean_schema = RSchema.define { boolean }
boolean_schema.valid?(true)  #=> true
boolean_schema.valid?(false) #=> true
boolean_schema.valid?(nil)   #=> false

# anything (literally any value)
anything_schema = RSchema.define { anything }
anything_schema.valid?('Hi')  #=> true
anything_schema.valid?(true)  #=> true
anything_schema.valid?(1234)  #=> true
anything_schema.valid?(nil)   #=> true

# either (sum types)
either_schema = RSchema.define { either(_String, _Integer, _Float) }
either_schema.valid?('hi') #=> true
either_schema.valid?(5555) #=> true
either_schema.valid?(77.2) #=> true

# maybe (allows nil)
maybe_schema = RSchema.define { maybe(_Integer) }
maybe_schema.valid?(5)   #=> true
maybe_schema.valid?(nil) #=> true

# enum (a set of valid values)
enum_schema = RSchema.define { enum([:a, :b, :c]) }
enum_schema.valid?(:a) #=> true
enum_schema.valid?(:z) #=> false

# predicate (block returns true for valid values)
predicate_schema = RSchema.define do
  predicate { |x| x.even? }
end
predicate_schema.valid?(4) #=> true
predicate_schema.valid?(5) #=> false

# pipeline (apply multiple schemas to a single value, in order)
pipeline_schema = RSchema.define do
  pipeline(
    either(_Integer, _Float),
    predicate { |x| x.positive? },
  )
end
pipeline_schema.valid?(123) #=> true
pipeline_schema.valid?(5.1) #=> true
pipeline_schema.valid?(-24) #=> false

For a full list of built-in schema types, see the API documentation for all classes in the RSchema::Schemas module.

Extending The DSL

To add methods to the default DSL, first create a module:

module MyCustomMethods
  def palendrome
    pipeline(
      _String,
      predicate { |s| s == s.reverse },
    )
  end
end

Then include your module into RSchema::DefaultDSL:

RSchema::DefaultDSL.include(MyCustomMethods)

And your methods will be available via RSchema.define:

schema = RSchema.define { palendrome }

schema.valid?('racecar') #=> true
schema.valid?('ferrari') #=> false

This is the preferred way for you, and other gems, to extend RSchema with new DSL methods.

Creating Your Own DSL

The default DSL is designed to be extended (i.e. modified) by you, and third-party gems. If you want a DSL that isn't affected by external factors, you can create one yourself.

Create a new class, and include RSchema::DSL if you want have all the standard DSL methods that come built-in to RSchema. You can define your own custom methods on this class.

class MyCustomDSL
  include RSchema::DSL # this is optional

  def palendrome
    pipeline(
      _String,
      predicate { |s| s == s.reverse },
    )
  end
end

Then pass an instance of your DSL class into RSchema.define:

dsl = MyCustomDSL.new
schema = RSchema.define(dsl) { palendrome }
schema.valid?('racecar') #=> true

Coercion

Coercers convert invalid data into valid data where possible, according to a schema.

Take HTTP params as an example. Web forms often contain database IDs, which are integers, but are submitted as strings by the browser. Param hash keys are often expected to be Symbols, but are also strings. RSchema can automatically convert these strings into the appropriate type, based on a schema.

# Input keys and values are all strings
input_params = {
  'whatever_id' => '5',
  'amount' => '123.45',
}

# The schema expects symbol keys, an integer value, and a float value
schema = RSchema.define_hash {{
  whatever_id: _Integer,
  amount: _Float,
}}

# A coercer is created by wrapping the schema
coercer = RSchema::CoercionWrapper::RACK_PARAMS.wrap(schema)

# Use the coercer like a normal schema object
result = coercer.validate(input_params)

# The result object contains the coerced value
result.valid? #=> true
result.value #=> { :whatever_id => 5, :amount => 123.45 }

Custom Coercion

Coercion is designed to be totally extensible. You'll have to take my word for it, because there isn't much documentation at the moment.

See lib/rschema/coercion_wrapper/rack_params.rb for an example of how to make a coercion wrapper.

See all the classes in lib/rschema/coercers/ for examples of how to make individual coercers.

If you have any problems or questions about implementing custom coercion, feel free to contact me (Tom Dalling).

Implementing Your Own Schema Types

Schemas are objects that conform to a certain interface (i.e. a duck type). To create your own schema types, you just need to implement this interface.

The interface consists of two methods: call and with_wrapped_subschemas. The call method is the interface for validating values. The with_wrapped_subschemas is necessary for coercion to work. If you have any problems or questions regarding this schema interface, feel free to contact me (Tom Dalling).

Below is a custom schema for pairs – arrays with two elements of the same type. This is already possible using existing schemas (e.g. array(_String, _String)), and is only shown here for the purpose of demonstration.

class PairSchema
  def initialize(subschema)
    @subschema = subschema
  end

  #
  # This method is mandatory.
  #
  # `pair` is the value to validate.
  # `options` is an `RSchema::Options` object.
  # This method must return a `RSchema::Result` object
  #
  def call(pair, options)
    return not_an_array_failure(pair) unless pair.is_a?(Array)
    return not_a_pair_failure(pair) unless pair.size == 2

    # pass both array elements to `@subschema.call`
    subresults = pair.map { |x| @subschema.call(x, options) }

    # check if both elements are valid according to @subschema
    if subresults.all?(&:valid?)
      RSchema::Result.success(subresults.map(&:value))
    else
      RSchema::Result.failure(subschema_error(subresults))
    end
  end

  #
  # This method is necessary for coercion to work
  #
  def with_wrapped_subschemas(wrapper)
    PairSchema.new(wrapper.wrap(@subschema))
  end

  private

    def not_an_array_failure(pair)
      RSchema::Result.failure(
        RSchema::Error.new(
          symbolic_name: :not_an_array,
          schema: self,
          value: pair,
        )
      )
    end

    def not_a_pair_failure(pair)
      RSchema::Result.failure(
        RSchema::Error.new(
          symbolic_name: :not_a_pair,
          schema: self,
          value: pair,
        )
      )
    end

    #
    # Returns a hash of index => error
    #
    def subschema_error(subresults)
      subresults
        .each_with_index
        .select { |(result, idx)| result.invalid? }
        .map { |(result, idx)| [idx, result.error] }
        .to_h
    end
end

Add your new schema class to the default DSL:

module PairSchemaDSL
  def pair(subschema)
    PairSchema.new(subschema)
  end
end

RSchema::DefaultDSL.include(PairSchemaDSL)

Then your schema is accessible from RSchema.define:

gps_coordinate_schema = RSchema.define { pair(_Float) }
gps_coordinate_schema.valid?([1.2, 3.4]) #=> true

Coercion should work, as long as #with_wrapped_subschemas was implemented correctly.

coercer = RSchema::CoercionWrapper::RACK_PARAMS.wrap(gps_coordinate_schema)
result = coercer.validate(["1", "2"])
result.valid? #=> true
result.value #=> [1.0, 2.0]

tomdalling / rschema Goto Github PK

rschema's Introduction

RSchema

Meet RSchema

What Is A Schema?

The DSL

Errors (When Validation Fails)

Type Schemas

Variable-length Array Schemas

Fixed-length Array Schemas

Fixed Hash Schemas

Variable Hash Schemas

Other Schema Types

Extending The DSL

Creating Your Own DSL

Coercion

Custom Coercion

Implementing Your Own Schema Types

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