synesia-data-schema

Synesia data schema toolkit: define your data once, validate it, generate defaults, and convert to/from JSON Schema.

Why synesia-data-schema?

• Single source of truth: strong types for your schema, shared across apps.
• Built-in validation: validateData with precise messages and error paths.
• Smart defaults: generateDefaultData using enum, formats, min/max, etc.
• JSON Schema interop: bidirectional conversion toJSONSchema / fromJSONSchema.
• TypeScript native: autocomplete and type safety.

DataSchema is a simplified, opinionated adaptation of JSON Schema tailored to Synesia’s needs. It keeps the essentials (types, enum, formats, min/max/step, objects/arrays) for clear, robust application use, while remaining convertible to/from JSON Schema when needed.

Installation

pnpm add synesia-data-schema

Quick Start

import { validateData, generateDefaultData } from "synesia-data-schema";
import { DataSchema } from "synesia-data-schema";

const userSchema: DataSchema = {
  id: "user",
  name: "User",
  type: "object",
  required: true,
  schema: [
    {
      id: "email",
      name: "email",
      type: "text",
      required: true,
      format: "email",
    },
    { id: "age", name: "age", type: "number", required: false, min: 0 },
    {
      id: "roles",
      name: "roles",
      type: "array",
      required: false,
      childSchema: { id: "role", name: "role", type: "text", required: true },
    },
  ],
};

const defaults = generateDefaultData(userSchema, true);

const result = validateData({ email: "bad", age: -1 }, userSchema);

JSON Schema conversion

import { toJSONSchema, fromJSONSchema } from "synesia-data-schema";

const jsonSchema = toJSONSchema({
  type: "object",
  properties: {
    title: { type: "string", format: "email" },
    count: { type: "number", minimum: 0 },
  },
  required: ["title"],
});

const backToJsonSchema = fromJSONSchema({
  id: "root",
  name: "root",
  type: "object",
  schema: [
    {
      id: "title",
      name: "title",
      type: "text",
      required: true,
      format: "email",
    },
    { id: "count", name: "count", type: "number", required: false, min: 0 },
  ],
});

API

• generateDefaultData(schema, includeOptional?) => unknown
  • Generates default values based on defaultValue, enum, format, min/max/step.
• validateData(data, schema, strict?) => { isValid: boolean; errors: { message: string; path: string[] }[] }
  • Recursively validates input and returns precise error paths.
  • When strict=true, every field must be present even if required=false.
• toJSONSchema(json, name?) => DataSchema
  • Converts a JSON Schema into a strongly typed DataSchema.
• fromJSONSchema(schema, strict?) => any
  • Converts a DataSchema to JSON Schema. strict forces all object keys to be required.

Supported formats

email, uuid, date, time, datetime (mapped to date-time in JSON Schema). Patterns are backed by TEXT_VALIDATION_REGEX and covered by tests.

Types

Exposed types: DataSchema, TextDataSchema, NumberDataSchema, BooleanDataSchema, ArrayDataSchema, ObjectDataSchema, EmptyDataSchema, and InputEnum<T>.

Tests & Quality

pnpm run test
pnpm run test:coverage

High coverage (~95%) with unit tests covering validation, default generation, and conversions.

Contributing

• Fork, create a feature branch, open a PR with a clear description
• Keep strict TypeScript style and high coverage

License

MIT