Skip to content
This repository

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
tree: b33b45c7b8

Fetching latest commit…

Cannot retrieve the latest commit at this time

README.md

Membrane

Membrane provides an easy to use DSL for specifying validators declaratively. It's intended to be used to validate data received from external sources, such as API endpoints or config files. Use it at the edges of your process to decide what data to let in and what to keep out.

Overview

The core concept behind Membrane is the schema. A schema represents an invariant about a piece of data (similar to a type) and is capable of verifying whether or not a supplied datum satisfies the invariant. Schemas may be composed to produce more expressive constructs.

Membrane provides a handful of useful schemas out of the box. You should be able to construct the majority of your schemas using only what is provided by default.

Any

The Any schema accepts all values; use it sparingly. It is synonymous to the Object class in Ruby.

Bool

The Bool schema accepts only the values true and false.

Class

The Class schema is parameterized by an instance of Class. It accepts any values that are instances of the supplied class. This is verified using kind_of?.

Dictionary

The Dictionary schema is parameterized by a key schema and a value schema. It accepts hashes whose keys and values validate against their respective schemas.

Enum

The Enum parameterized by an arbitrary number of value schemas. It accepts any values that are accepted by at least one of the supplied schemas.

List

The List schema is parameterized by a single element schema. It accepts arrays whose elements are accepted by the supplied schema.

Record

The Record schema is parameterized by a set of known keys and their respective schemas. It accepts hashes that contain all the supplied keys, assuming the corresponding values are accepted by their respective schemas.

Regexp

The Regexp schema is parameterized by a regular expression. It accepts strings that match the supplied regular expression.

Tuple

The Tuple schema is parameterized by a fixed number of schemas. It accepts arrays of the same length, where each element is accepted by its associated schema.

Value

The Value schema is parameterized by a single value. It accepts values who are equal to the parameterizing value using ==.

DSL

Membrane schemas are typically created using a concise DSL. The aforementioned schemas are represented in the DSL as follows:

Any

The Any schema is represented by the keyword any.

Bool

The Bool schema is represented by the keyword bool.

Class

The Class schema is represented by the parameterizing instance of Class. For example, an instance of the Class schema that validates strings would be represented as String.

Dictionary

The Dictionary schema is represented by dict(key_schema, value_schema, where key_schema is the schema used to validate keys, and value_schema is the schema used to validate values.

Enum

The Enum schema is represented by enum(schema1, ..., schemaN) where schema1 through schemaN are the possible value schemas.

List

The List schema is represented by [elem_schema], where elem_schema is the schema that all list elements must validate against.

Record

The Record schema is represented as follows:

{ "key1"           => value1_schema,
  optional("key2") => value2_schema,
  ...
}

Here key1 must be contained in the hash and the corresponding value must be accepted by value1_schema. Note that key2 is marked as optional. If present, its corresponding value must be accepted by value2_schema.

Regexp

The Regexp schema is represented by regexp literals. For example, /foo|bar/ matches strings containing "foo" or "bar".

Tuple

The Tuple schema is represented as tuple(schema0, ..., schemaN), where the Ith element of an array must be accepted by schemaI.

Value

The Value schema is represented by the value to be validated. For example, "foo" accepts only the string "foo".

Usage

While the previous section was a bit abstract, the DSL is fairly intuitive. For example, the following creates a schema that will validate a hash where the key "ints" maps to a list of integers and the key "string" maps to a string.

schema = Membrane::SchemaParser.parse do
  { "ints"   => [Integer],
    "string" => String,
  }
end

# Validates successfully
schema.validate({
  "ints"   => [1],
  "string" => "hi",
})

# Fails validation. The key "string" is missing and the value for "ints"
# isn't the correct type.
schema.validate({
  "ints" => "invalid",
})

This is a more complicated example that illustrate the entire DSL. Hopefully it is self-explanatory:

Membrane::SchemaParser.parse do
  { "ints"          => [Integer]
    "true_or_false" => bool,
    "anything"      => any, # You can also use Object instead.
    optional("_")   => any,
    "one_or_two"    => enum(1, 2),
    "strs_to_ints"  => dict(String, Integer),
    "foo_prefix"    => /^foo/,
    "three_ints"    => tuple(Integer, Integer, Integer),
  }
end

Adding new schemas

Adding a new schema is trivial. Any class implementing the following "interface" can be used as a schema:

# @param [Object] The object being validated.
#
# @raise [Membrane::SchemaValidationError] Raised when a supplied object is
# invalid.
#
# @return [nil]
def validate(object)

If you wish to include your new schema as part of the DSL, you'll need to modify membrane/schema_parser.rb and have your class inherit from


## File a Bug

To file a bug against Cloud Foundry Open Source and its components, sign up and use our
bug tracking system: [http://cloudfoundry.atlassian.net](http://cloudfoundry.atlassian.net)
Something went wrong with that request. Please try again.