Spectra

A data validation library for Erlang inspired by Pydantic. Point it to your erlang types (records and type specs) and it will validate and convert JSON data to/from your types, generate json schemas and help you generate openapi schemas.

Installation

Add spectra to your rebar.config dependencies:

{deps, [
    {spectra, "~> 0.1.2"}
]}.

Data (de)serialization

Spectra provides type-safe data serialization and deserialization for Erlang records and all Erlang types that can be converted to that type. Currently the focus is on JSON.

• Type-safe conversion: Convert typed erlang values to/from external formats such as JSON, making sure the data conforms to the type.
• Detailed errors: Get error messages with location information when validation fails
• Support for complex scenarios: Handles unions, records, atoms, nested structures, ...

Basic Usage

Here's how to use spectra for JSON serialization and deserialization:

-module(demo).

-export([json_to_contacts/1, contacts_to_json/1, json_schema/0, binary_to_quality/1]).

-record(email_contact, {address, verified, domain}).
-record(phone_contact, {number, verified, sms_capable}).

-type quality() :: 1..5.
-type verified() ::
    #{source := one_time_code | gut_feeling,
      quality => quality(),
      binary() => binary()} | undefined.
-type email_contact() ::
    #email_contact{address :: nonempty_binary(),
                   verified :: verified(),
                   domain :: nonempty_binary()}.
-type phone_contact() ::
    #phone_contact{number :: binary(),
                   verified :: verified(),
                   sms_capable :: boolean()}.
-type contacts() :: [email_contact() | phone_contact()].

%% Some helper functions

-spec json_to_contacts(binary()) -> {ok, contacts()} | {error, [spectra:error()]}.
json_to_contacts(Json) ->
    spectra:decode(json, ?MODULE, contacts, Json).

-spec contacts_to_json(contacts()) -> {ok, binary()} | {error, [spectra:error()]}.
contacts_to_json(Contacts) ->
    case spectra:encode(json, ?MODULE, contacts, Contacts) of
        {ok, JsonIoList} -> {ok, iolist_to_binary(JsonIoList)};
        {error, _} = Error -> Error
    end.

-spec binary_to_quality(binary()) -> {ok, quality()} | {error, [spectra:error()]}.
binary_to_quality(Bin) ->
    spectra:decode(binary_string, ?MODULE, quality, Bin).

json_schema() ->
    {ok, IoSchema} = spectra:schema(json_schema, ?MODULE, contacts),
    iolist_to_binary(IoSchema).

Using the demo module in the shell

%% Compile the demo module (note: You need debug info)
c("demo.erl", [debug_info]).

%% Load the record defs into the shell.
rr(demo).

%% Create some data
Contacts = [
    #email_contact{
        address = <<"john.doe@example.com">>,
        verified = #{source => one_time_code, quality => 2, <<"code">> => <<"123456">>},
        domain = <<"example.com">>
    },
    #phone_contact{
        number = <<"+1-555-123-4567">>,
        verified = #{source => gut_feeling, <<"confidence">> => <<"high">>},
        sms_capable = true
    },
    #email_contact{
        address = <<"alice@company.org">>,
        domain = <<"company.org">>
    }
].

%% Convert to JSON
{ok, Json} = demo:contacts_to_json(Contacts).

%% Convert back from JSON
demo:json_to_contacts(Json).

%% If you get quality as a query parameter, you can do:
demo:binary_to_quality(<<"4">>).

%% Generate the json schema
demo:json_schema().

Data Serialization API

These are the main functions for JSON serialization and deserialization:

spectra:encode(Format, Module, Type, Value) ->
    {ok, iolist()} | {error, [spectra:error()]}.
spectra:decode(Format, Module, Type, JsonBinary) ->
    {ok, Value} | {error, [spectra:error()]}.

Where:

• Format is json, binary_string or string
• Module is the module where the type/record is defined (or a type_info() for advanced usage)
• Type is either:
  • an atom: spectra will look for a type of arity 0 or a record with that name
  • {type, TypeName, Arity} for user-defined types (e.g., {type, my_type, 0})
  • {record, RecordName} for records (e.g., {record, user})
  • An actual sp_type() structure (for advanced usage)

Schema API

spectra:schema(Format, Module, Type) ->
    {ok, Schema :: map()} | {error, [spectra:error()]}.

Where:

• Format is json_schema (for now)

And the rest of the arguments are the same as for the data serialization API.

OpenAPI Spec

Spectra can generate complete OpenAPI 3.0 specifications for your REST APIs. This provides interactive documentation, client generation, and API testing tools.

OpenAPI Builder API

The API for building endpoints is very experimental and will probably change a lot. It is meant to be used by developers of web servers / web frameworks. See elli_openapi for an example of how to use it in a web server.

%% Create a base endpoint
spectra_openapi:endpoint(Method, Path) ->
    endpoint_spec().

%% Add responses
spectra_openapi:with_response(Endpoint, StatusCode, Description, Module, Schema) ->
    endpoint_spec().

%% Add request body
spectra_openapi:with_request_body(Endpoint, Module, Schema) ->
    endpoint_spec().

%% Add parameters (path, query, header, cookie)
spectra_openapi:with_parameter(Endpoint, Module, ParameterSpec) ->
    endpoint_spec().

%% Generate complete OpenAPI spec
spectra_openapi:endpoints_to_openapi(Metadata, Endpoints) ->
    {ok, json:encode_value()} | {error, [spectra:error()]}.

Requirements

• Modules must be compiled with debug_info for spectra to extract type information.

Error Handling

Spectra uses two different error handling strategies depending on the type of error:

Returned Errors ({error, [spectra:error()]})

Data validation errors are returned as {error, [#sp_error{}]} tuples. These occur when input data doesn't match the expected type during encoding/decoding.

Example:

BadSourceJson = <<"[{\"number\":\"+1-555-123-4567\",\"verified\":{\"source\":\"a_bad_source\",\"confidence\":\"high\"},\"sms_capable\":true}]">>.

{error, [#sp_error{...}]} = json_to_contacts(BadSourceJson).

#error{} contains:

• location - List showing the path to where the error occurred
• type - Error type: type_mismatch, no_match, missing_data, missing_type, type_not_supported, not_matched_fields, not_implemented
• ctx - Context information about the error

Raised Exceptions

Configuration and structural errors raise exceptions. These occur when:

• Module not found, not loaded, or not compiled with debug_info
• Type or record not found in module (e.g., {type_or_record_not_found, TypeName})
• Unsupported type used (e.g., pid(), port(), tuple())

These errors indicate a problem with your application's configuration or type definitions, not with the data being processed.

Special Handling

undefined Values

In records and mandatory map fields (with the := operator), the value undefined will be used when the value is missing if the type includes undefined.

For example, integer() | undefined will become undefined in records and maps mandatory fields if the value is missing, and the value will not be present in the JSON.

term() | any()

When using types with term, spectra_json will not reject any data, which means it can return data that json.erl cannot convert to JSON.

Char

Char is currently handled as integer, which is probably not what you want. Try to not use the char type for now. This is documented in test/char_test.erl.

Unsupported Types

Each format supports a subset of Erlang types. For JSON serialization and schema, the following are not supported:

• maybe_improper_list() - Currently returns an error
• pid(), port(), reference() - Cannot be serialized to JSON
• tuple(), bitstring(), nonempty_bitstring() - Not JSON-compatible
• Function types - Cannot be serialized

It would be interesting to add support for key value lists, but as it isn't a native type in erlang, I haven't gotten around to it yet.

Configuration

Application Environment Variables

You can configure spectra behavior using application environment variables:

use_module_types_cache

• Type: boolean()
• Default: false
• Description: When set to true, enables caching of extracted type information for modules using persistent terms. This can improve performance when repeatedly processing the same modules.
• Note: When only changing types and not code, the module vsn (used for caching) is not updated, so the types will not be updated.
• Recommendation: Enable this in production systems where no hot code reloading is done.

check_unicode

• Type: boolean()
• Default: false
• Description: When set to true, enables additional Unicode validation for string data. This validates that list-type string data contains valid Unicode characters. When disabled, string conversion still works correctly but skips the additional validation step for better performance.
• Note: Required type conversions (e.g., binary to list, list to binary) always use Unicode functions regardless of this setting.
• Recommendation: Enable this if you need strict Unicode validation, or keep disabled for better performance when Unicode validity is guaranteed by other means.

Example configuration in sys.config:

{spectra, [
    {use_module_types_cache, true},
    {check_unicode, false}
]}.

Related Projects

• elli_openapi - Elli middleware for automatic OpenAPI spec generation and validation using spectra
• exdantic - Elixir port of spectra for data validation and JSON serialization

Development Status

This library is under active development. APIs and error messages will probably change.

Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.