Fields

Applies to: DDD · CQRS · Event Sourcing

Fields define the structure and behavior of data within domain elements — Aggregates, Entities, Value Objects, Commands, and Events. They encapsulate data properties, enforce validation, manage defaults, and express relationships between domain concepts.

Protean provides a set of field functions (String, Integer, Float, HasMany, etc.) that let you declare fields using domain-friendly vocabulary. Under the hood, Protean uses Pydantic v2 as its validation and serialization engine, so domain elements benefit from Rust-core validation performance, JSON Schema generation, and native serialization — without requiring you to learn Pydantic's API.

Defining fields

Protean supports three styles for declaring fields: annotation style (recommended), assignment style, and raw Pydantic style. All three are fully supported and can be mixed within a single class.

@domain.aggregate
class Product:
    name: String(max_length=50, required=True)   # annotation (recommended)
    price: Float(min_value=0)                    # assignment

Read more in Defining fields.

Field arguments

Protean fields come with various options to model real-world scenarios effectively. These include required, default, choices, and unique, among others, which allow for a highly customizable and robust domain model definition.

Read more in Arguments section.

Types of fields

Simple fields

Simple fields handle basic data types like strings, integers, and dates. They are the building blocks for defining straightforward data attributes in models. Options like max_length for String or max_value and min_value for numeric fields like Integer and Float allow you to specify constraints directly in the model's definition.

Container fields

Container fields are used for data types that hold multiple values, such as lists and dictionaries. These fields support complex structures and provide options such as content_type for List fields to ensure type consistency within the collection. Protean optimizes storage and retrieval operations for these fields by leveraging database-specific features when available.

Association fields

Association fields define relationships between different domain models, such as one-to-one, one-to-many, and many-to-many associations. These fields help in mapping complex domain relationships and include functionalities to manage related objects efficiently, preserving data integrity across the domain.