One To Many Relationships

Imagine our social network for trail runners 🏃🏃🏾‍♀️ allows runners to upload their runs as activities.

In this model, the ActivityData only pertains on one TrailRunner

While the Trail Runner has many such activities.

Note In our charts we use dotted lines for singular relationships and thick solid lines for collection relationships.

Let's workout!

There are two ways we can model this relationship: bidirectionally with managed inverses, or unidirectionally without managed inverses.

In the bidirectional configuration, changes to one side of the relationship change the other side as well. This includes both updates from remote state (a payload for the resource received from the API) as well as mutations to the local state (application code setting a new, unsaved value for the relationship).

In the unidirectional configuration, we effectively have two separate distinct relationships.

A many-to-none relationship from TrailRunner to ActivityData.

And a one-to-none relationship from ActivityData to TrailRunner.

With distinct relationships, we may edit one side without affecting the state of the inverse. This is particularly useful in two situations.

First, it may be the case that the user has thousands or tens of thousands of activities. In this case, you likely don't want whichever individual activities you happen to load to create an incomplete list of the TrailRunner's activities. It's better to load and work with the activities list in isolation, ideally in a paginated manner.

Second, it may be the case that runner is able to share the activity data with another runner that forgot to record. By not coupling the relationship, the ActivityData can still be owned by the first runner by included in the second runner's list of activities as well.

Head over to many-to-none and one-to-none if this is the setup that is best for you. Else, here's how we can define such a relationship via various mechanisms.

• Using @warp-drive/legacy/model
• Using json schemas
• Using ReactiveResource schemas
• 🚧 Using @warp-drive/schema-dsl
  • Legacy Compat Mode

---

Using @warp-drive/legacy/model

Note Models are currently the primary way that users of WarpDrive define "schema".

Models are not the only way to define schema today, but they are the most immediately available ergonomic way to do so.

When using Models, WarpDrive parses schema from them at runtime, converting static information defined on the class into the json schema format needed by the rest of the system.

This is handled by the implementation of the SchemaService provided by the @warp-drive/legacy/model package. The service converts the class definitions into the json definitions described in the next section.

🏃🏾‍♀️ ActivityData

import Model, { belongsTo } from '@warp-drive/legacy/model';

export default class ActivityData extends Model {
  @belongsTo('trail-runner', { inverse: 'activities', async: false })
  runner;
}

🌲 TrailRunner

import Model, { hasMany } from '@warp-drive/legacy/model';

export default class TrailRunner extends Model {
  @hasMany('activity-data', { inverse: 'runner', async: false })
  activities;
}

---

Using JSON Schemas

WarpDrive doesn't care where your schemas come from, how they are authored, or how you load them into the system so long as when it asks the SchemaService for information it gets back field definitions in the right json shape.

Here, we show how the above trail runner relationship is described by a field definition.

Current

🏃🏾‍♀️ ActivityData

{
  "kind": "belongsTo",
  "name": "runner",
  "options": { "async": false, "inverse": "activities" },
  "type": "trail-runner",
}

🌲 TrailRunner

{
  "kind": "hasMany",
  "name": "activities",
  "options": { "async": false, "inverse": "runner" },
  "type": "activity-data",
}

🚧 Coming Soon

Because we deprecated implicit option values in 4.x, we are now able to change defaults.

This means that the next iteration of Schema will be able to reliably use the lack of an option like "async" or "inverse" as a false-y value.

We also are shifting the value for "kind" from "belongsTo" to "resource" to make it more readily clear that relationships do not (by default) have directionality or ownership over their inverse.

🏃🏾‍♀️ ActivityData

{
  "kind": "resource",
  "name": "runner",
  "options": { "inverse": "activities" },
  "type": "trail-runner",
}

🌲 TrailRunner

{
  "kind": "collection",
  "name": "activities",
  "options": { "inverse": "runner" },
  "type": "activity-data",
}

---

Using ReactiveResource Schemas

ReactiveResource reads these same field definitions from a ResourceSchema. Define one in LegacyMode, the recommended mode today. Its withDefaults helper sets legacy: true, adds the id identity field, and appends the derived and local fields that emulate Model. The relationship field is the JSON above, unchanged.

🏃🏾‍♀️ ActivityData

import { withDefaults } from '@warp-drive/legacy/model/migration-support';

export const ActivityDataSchema = withDefaults({
  type: 'activity-data',
  fields: [
    {
      kind: 'belongsTo',
      name: 'runner',
      options: { async: false, inverse: 'activities' },
      type: 'trail-runner',
    },
  ],
});

🌲 TrailRunner

import { withDefaults } from '@warp-drive/legacy/model/migration-support';

export const TrailRunnerSchema = withDefaults({
  type: 'trail-runner',
  fields: [
    {
      kind: 'hasMany',
      name: 'activities',
      options: { async: false, inverse: 'runner' },
      type: 'activity-data',
    },
  ],
});

If you did not create the store with useLegacyStore, call registerDerivations once on the schema service, as shown in Configuration. Defining Legacy Schemas shows how to type the records these schemas produce.

---

Using @warp-drive/schema-dsl (🚧 Coming Soon)

Note The LegacyCompat Mode samples below use @warp-drive/schema-dsl, a private package in this repository that has not been published to npm. The samples before them import from @warp-drive/schema, a schema parser and scaffolding CLI that exports no decorators, and no package exports their resource or collection decorators yet. None of these samples run today.

Working with schemas in a raw json format is far more flexible, lightweight and performant than working with bulky classes that need to be shipped across the wire, parsed, and instantiated. Even relatively small apps can quickly find themselves shipping large quantities of JS just to describe their data.

No one wants to author schemas in raw JSON though (we hope 😬), and the ergonomics of typed data and editor autocomplete based on your schemas are vital to productivity and code quality. For this, we offer a way to express schemas as TypeScript using types, classes and decorators which are then compiled into json schemas and TypeScript interfaces for use by your project.

🏃🏾‍♀️ ActivityData

import { resource } from '@warp-drive/schema';
import { TrailRunner } from './trail-runner';

export class ActivityData {
  @resource(TrailRunner, { inverse: "activities" })
  runner;
}

🌲 TrailRunner

import { collection } from '@warp-drive/schema';
import { ActivityData } from './activity-data';

export class TrailRunner {
  @collection(ActivityData, { inverse: "runner" })
  activities;
}

LegacyCompat Mode

Support for migrating from @warp-drive/legacy/model on a more granular basis is provided by decorators that preserve the semantics of the quirks of that class. This allows you to begin eliminating models and adopting other features of schemas sooner.

🏃🏾‍♀️ ActivityData

import { Resource, belongsTo } from '@warp-drive/schema-dsl';
import type { TrailRunner } from './trail-runner';

@Resource({ legacy: true })
export class ActivityData {
  @belongsTo({ type: 'trail-runner', inverse: 'activities', async: false })
  declare runner: TrailRunner | null;
}

🌲 TrailRunner

import { Resource, hasMany } from '@warp-drive/schema-dsl';
import type { ActivityData } from './activity-data';

@Resource({ legacy: true })
export class TrailRunner {
  @hasMany({ type: 'activity-data', inverse: 'runner', async: false })
  declare activities: ActivityData[];
}