Reid  Rohan

Reid Rohan


Generate json-schema From Your Typescript Sources


Generate json-schemas from your Typescript sources.


  • Compiles your Typescript program to get complete type information.
  • Translates required properties, extends, annotation keywords, property initializers as defaults. You can find examples for these features in the api doc or the test examples.


Command line

  • Install with npm install typescript-json-schema -g
  • Generate schema from a typescript type: typescript-json-schema project/directory/tsconfig.json TYPE

To generate files for only some types in tsconfig.json specify filenames or globs with the --include option. This is especially useful for large projects.

In case no tsconfig.json is available for your project, you can directly specify the .ts files (this in this case we use some built-in compiler presets):

  • Generate schema from a typescript type: typescript-json-schema "project/directory/**/*.ts" TYPE

The TYPE can either be a single, fully qualified type or "*" to generate the schema for all types.

Usage: typescript-json-schema <path-to-typescript-files-or-tsconfig> <type>

  --refs                Create shared ref definitions.                               [boolean] [default: true]
  --aliasRefs           Create shared ref definitions for the type aliases.          [boolean] [default: false]
  --topRef              Create a top-level ref definition.                           [boolean] [default: false]
  --titles              Creates titles in the output schema.                         [boolean] [default: false]
  --defaultProps        Create default properties definitions.                       [boolean] [default: false]
  --noExtraProps        Disable additional properties in objects by default.         [boolean] [default: false]
  --propOrder           Create property order definitions.                           [boolean] [default: false]
  --required            Create required array for non-optional properties.           [boolean] [default: false]
  --strictNullChecks    Make values non-nullable by default.                         [boolean] [default: false]
  --esModuleInterop     Use esModuleInterop when loading typescript modules.         [boolean] [default: false]
  --useTypeOfKeyword    Use `typeOf` keyword ( for functions.  [boolean] [default: false]
  --out, -o             The output file, defaults to using stdout
  --validationKeywords  Provide additional validation keywords to include            [array]   [default: []]
  --include             Further limit tsconfig to include only matching files        [array]   [default: []]
  --ignoreErrors        Generate even if the program has errors.                     [boolean] [default: false]
  --excludePrivate      Exclude private members from the schema                      [boolean] [default: false]
  --uniqueNames         Use unique names for type symbols.                           [boolean] [default: false]
  --rejectDateType      Rejects Date fields in type definitions.                     [boolean] [default: false]
  --id                  Set schema id.                                               [string]  [default: ""]
  --defaultNumberType   Default number type.                                         [choices: "number", "integer"] [default: "number"]
  --tsNodeRegister      Use ts-node/register (needed for require typescript files).  [boolean] [default: false]

Programmatic use

import { resolve } from "path";

import * as TJS from "typescript-json-schema";

// optionally pass argument to schema generator
const settings: TJS.PartialArgs = {
    required: true,

// optionally pass ts compiler options
const compilerOptions: TJS.CompilerOptions = {
    strictNullChecks: true,

// optionally pass a base path
const basePath = "./my-dir";

const program = TJS.getProgramFromFiles(

// We can either get the schema for one file and one type...
const schema = TJS.generateSchema(program, "MyType", settings);

// ... or a generator that lets us incrementally get more schemas

const generator = TJS.buildGenerator(program, settings);

// generator can be also reused to speed up generating the schema if usecase allows:
const schemaWithReusedGenerator = TJS.generateSchema(program, "MyType", settings, [], generator);

// all symbols
const symbols = generator.getUserSymbols();

// Get symbols for different types from generator.
// In larger projects type names may not be unique,
// while unique names may be enabled.
const settings: TJS.PartialArgs = {
    uniqueNames: true,

const generator = TJS.buildGenerator(program, settings);

// A list of all types of a given name can then be retrieved.
const symbolList = generator.getSymbols("MyType");

// Choose the appropriate type, and continue with the symbol's unique name.

// Also it is possible to get a list of all symbols.
const fullSymbolList = generator.getSymbols();

getSymbols('<SymbolName>') and getSymbols() return an array of SymbolRef, which is of the following format:

type SymbolRef = {
    name: string;
    typeName: string;
    fullyQualifiedName: string;
    symbol: ts.Symbol;

getUserSymbols and getMainFileSymbols return an array of string.


The schema generator converts annotations to JSON schema properties.

For example

export interface Shape {
     * The size of the shape.
     * @minimum 0
     * @TJS-type integer
    size: number;

will be translated to

    "$ref": "#/definitions/Shape",
    "$schema": "",
    "definitions": {
        "Shape": {
            "properties": {
                "size": {
                    "description": "The size of the shape.",
                    "minimum": 0,
                    "type": "integer"
            "type": "object"

Note that we needed to use @TJS-type instead of just @type because of an issue with the typescript compiler.

You can also override the type of array items, either listing each field in its own annotation or one annotation with the full JSON of the spec (for special cases). This replaces the item types that would have been inferred from the TypeScript type of the array elements.


export interface ShapesData {
     * Specify individual fields in items.
     * @items.type integer
     * @items.minimum 0
    sizes: number[];

     * Or specify a JSON spec:
     * @items {"type":"string","format":"email"}
    emails: string[];


    "$ref": "#/definitions/ShapesData",
    "$schema": "",
    "definitions": {
        "Shape": {
            "properties": {
                "sizes": {
                    "description": "Specify individual fields in items.",
                    "items": {
                        "minimum": 0,
                        "type": "integer"
                    "type": "array"
                "emails": {
                    "description": "Or specify a JSON spec:",
                    "items": {
                        "format": "email",
                        "type": "string"
                    "type": "array"
            "type": "object"

This same syntax can be used for contains and additionalProperties.

integer type alias

If you create a type alias integer for number it will be mapped to the integer type in the generated JSON schema.


type integer = number;
interface MyObject {
    n: integer;

Note: this feature doesn't work for generic types & array types, it mainly works in very simple cases.

require a variable from a file

(for requiring typescript files is needed to set argument tsNodeRegister to true)

When you want to import for example an object or an array into your property defined in annotation, you can use require.


export interface InnerData {
    age: number;
    name: string;
    free: boolean;

export interface UserData {
     * Specify required object
     * @examples require("./example.ts").example
    data: InnerData;

file example.ts

export const example: InnerData[] = [{
  age: 30,
  name: "Ben",
  free: false


    "$schema": "",
    "properties": {
        "data": {
            "description": "Specify required object",
            "examples": [
                    "age": 30,
                    "name": "Ben",
                    "free": false
            "type": "object",
            "properties": {
                "age": { "type": "number" },
                "name": { "type": "string" },
                "free": { "type": "boolean" }
            "required": ["age", "free", "name"]
    "required": ["data"],
    "type": "object"

Also you can use require(".").example, which will try to find exported variable with name 'example' in current file. Or you can use require("./someFile.ts"), which will try to use default exported variable from 'someFile.ts'.

Note: For examples a required variable must be an array.


Inspired and builds upon Typson, but typescript-json-schema is compatible with more recent Typescript versions. Also, since it uses the Typescript compiler internally, more advanced scenarios are possible. If you are looking for a library that uses the AST instead of the type hierarchy and therefore better support for type aliases, have a look at vega/ts-json-schema-generator.


npm run debug -- test/programs/type-alias-single/main.ts --aliasRefs true MyString

And connect via the debugger protocol.

Author: YousefED
Source Code: 
License: BSD-3-Clause License

#typescript #json 

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Generate json-schema From Your Typescript Sources
Brain  Crist

Brain Crist


SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master


This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,

A glimpse of previous articles
Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2
  • We learned to create a database and maintain it using SQL statements.
  • Best practice methods were also mentioned.

#sql server #benefits of schemas #create schema in sql #database schemas #how to create schema in sql server #schemas #schemas in sql server #sql server schemas #what is schema in sql server

Brandon  Adams

Brandon Adams


What is JSON? | JSON Objects and JSON Arrays | Working with JSONs Tutorial

In this video, we work with JSONs, which are a common data format for most web services (i.e. APIs). Thank you for watching and happy coding!

Need some new tech gadgets or a new charger? Buy from my Amazon Storefront

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#jsons #json arrays #json objects #what is json #jsons tutorial #blondiebytes

The Definitive Guide to TypeScript & Possibly The Best TypeScript Book

TypeScript Deep Dive

I've been looking at the issues that turn up commonly when people start using TypeScript. This is based on the lessons from Stack Overflow / DefinitelyTyped and general engagement with the TypeScript community. You can follow for updates and don't forget to ★ on GitHub 🌹


  • Thanks for the wonderful book. Learned a lot from it. (link)
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  • This gitbook got my project going pronto. Fluent easy read 5 stars. (link)
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Get Started

If you are here to read the book online get started.


Book is completely free so you can copy paste whatever you want without requiring permission. If you have a translation you want me to link here. Send a PR.

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Special Thanks

All the amazing contributors 🌹


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Author: Basarat
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Dicanio Rol

Dicanio Rol


JSON Schema,, JSON-LD: What’s the Difference?

Recently, I have seen several questions like “what’s the difference between JSON-LD and JSON Schema” or “can I use JSON Schema and”. I come from a linked data background (which is close to the world of but have recently started using JSON Schema a lot and I have to admit that there is no trivial answer to these questions. There is the obvious similarity in the standard names like “Schema” and “JSON”. If you compare the page for  Person to this  example on the JSON Schema page, you have to admit that they kind of look alike. Combine this with the fact that touts JSON-LD, which — by design — very much looks like regular JSON completes the confusion. So there definitely are enough reasons to write this article.

JSON Schema

JSON Schema is to JSON what XML Schema is to XML. It allows you to specify the structure of a JSON document. You can state that the field “email” must follow a certain regular expression or that an address has “street_name”, “number”, and “street_type” fields.  Michael Droettboom’s book  “Understanding JSON Schema” illustrates validation quite nicely with red & green examples.

The main use case for JSON Schema seems to be in JSON APIs where it plays two major roles:

  1. Clients and servers can validate request and response objects in a generic way. This makes development a lot easier, since the implementation can “outsource” these checks to a standard component. Once a message passed the validation, you can safely assume that the document adheres to the rules.
  2. As with any API, documentation is key when developers write code that uses it. JSON Schema is increasingly used to describe the structure of requests and responses by embedding it in an overall API description. Swagger is probably the most prominent example of this paradigm. Consider the pet-store example. Scroll all the way down on the page and you see this JSON Schema definition of “Pet”, which is a basic element in requests and responses of this API (you can find the actual JSON Schema embedded in the raw Swagger file — note that currently there are still some differences between the OpenAPI specification and JSON Schema which will be resolved with OpenAPI 3.1).

Image for post

As with all things related to code, reuse is a good idea. JSON Schema has the ability to import schemas using the $ref keyword. There are also efforts to share schemas.  JSON Schema Store is one example. Its main use case is to support syntax highlighting for editors, for instance when editing a swagger file. At the time of writing, it contains over 250 schemas including — drum-roll please / you certainly guessed it — These describe things like  Action and  Place. So the idea could be to centrally define JSON Schema building blocks that can be re-used in different APIs, making it easier to consume them, maybe even to the point where intelligent software can interact with APIs automatically. But before we get carried away, let’s have a look at

#schema #swagger #json-ld #json-schema

Reid  Rohan

Reid Rohan


Generate JSON Schema From Your TypeScript Sources


Inspired by YousefED/typescript-json-schema. Here's the differences list:

  • this implementation avoids the use of typeChecker.getTypeAtLocation() (so probably it keeps correct type aliases)
  • processing AST and formatting JSON schema have been split into two independent steps
  • not exported types, interfaces, enums are not exposed in the definitions section in the JSON schema


This project is made possible by a community of contributors. We welcome contributions of any kind (issues, code, documentation, examples, tests,...). Please read our code of conduct.

CLI Usage

npm install --save ts-json-schema-generator
./node_modules/.bin/ts-json-schema-generator --path 'my/project/**/*.ts' --type 'My.Type.Name'

Note that different platforms (e.g. Windows) may use different path separators so you may have to adjust the command above.

Programmatic Usage

// main.js

const tsj = require("ts-json-schema-generator");
const fs = require("fs");

/** @type {import('ts-json-schema-generator/dist/src/Config').Config} */
const config = {
    path: "path/to/source/file",
    tsconfig: "path/to/tsconfig.json",
    type: "*", // Or <type-name> if you want to generate schema for that one type only

const output_path = "path/to/output/file";

const schema = tsj.createGenerator(config).createSchema(config.type);
const schemaString = JSON.stringify(schema, null, 2);
fs.writeFile(output_path, schemaString, (err) => {
    if (err) throw err;

Run the schema generator via node main.js.

Custom formatting

Extending the built-in formatting is possible by creating a custom formatter and adding it to the main formatter:

  1. First we create a formatter, in this case for formatting function types:
// my-function-formatter.ts
import { BaseType, Definition, FunctionType, SubTypeFormatter } from "ts-json-schema-generator";
import ts from "typescript";

export class MyFunctionTypeFormatter implements SubTypeFormatter {
    // You can skip this line if you don't need childTypeFormatter
    public constructor(private childTypeFormatter: TypeFormatter) {}

    public supportsType(type: FunctionType): boolean {
        return type instanceof FunctionType;

    public getDefinition(type: FunctionType): Definition {
        // Return a custom schema for the function property.
        return {
            type: "object",
            properties: {
                isFunction: {
                    type: "boolean",
                    const: true,

    // If this type does NOT HAVE children, generally all you need is:
    public getChildren(type: FunctionType): BaseType[] {
        return [];

    // However, if children ARE supported, you'll need something similar to
    // this (see src/TypeFormatter/{Array,Definition,etc}.ts for some examples):
    public getChildren(type: FunctionType): BaseType[] {
        return this.childTypeFormatter.getChildren(type.getType());
  1. Then we add the formatter as a child to the core formatter using the augmentation callback:
import { createProgram, createParser, SchemaGenerator, createFormatter } from "ts-json-schema-generator";
import { MyFunctionTypeFormatter } from "./my-function-formatter.ts";
import fs from "fs";

const config = {
    path: "path/to/source/file",
    tsconfig: "path/to/tsconfig.json",
    type: "*", // Or <type-name> if you want to generate schema for that one type only

// We configure the formatter an add our custom formatter to it.
const formatter = createFormatter(config, (fmt, circularReferenceTypeFormatter) => {
    // If your formatter DOES NOT support children, e.g. getChildren() { return [] }:
    fmt.addTypeFormatter(new MyFunctionTypeFormatter());
    // If your formatter DOES support children, you'll need this reference too:
    fmt.addTypeFormatter(new MyFunctionTypeFormatter(circularReferenceTypeFormatter));

const program = createProgram(config);
const parser = createParser(program, config);
const generator = new SchemaGenerator(program, parser, formatter, config);
const schema = generator.createSchema(config.type);

const schemaString = JSON.stringify(schema, null, 2);
fs.writeFile(output_path, schemaString, (err) => {
    if (err) throw err;

Custom parsing

Similar to custom formatting, extending the built-in parsing works practically the same way:

  1. First we create a parser, in this case for parsing construct types:
// my-constructor-parser.ts
import { Context, StringType, ReferenceType, BaseType, SubNodeParser } from "ts-json-schema-generator";
import ts from "typescript";

export class MyConstructorParser implements SubNodeParser {
    supportsNode(node: ts.Node): boolean {
        return node.kind === ts.SyntaxKind.ConstructorType;
    createType(node: ts.Node, context: Context, reference?: ReferenceType): BaseType | undefined {
        return new StringType(); // Treat constructors as strings in this example
  1. Then we add the parser as a child to the core parser using the augmentation callback:
import { createProgram, createParser, SchemaGenerator, createFormatter } from "ts-json-schema-generator";
import { MyConstructorParser } from "./my-constructor-parser.ts";
import fs from "fs";

const config = {
    path: "path/to/source/file",
    tsconfig: "path/to/tsconfig.json",
    type: "*", // Or <type-name> if you want to generate schema for that one type only

const program = createProgram(config);

// We configure the parser an add our custom parser to it.
const parser = createParser(program, config, (prs) => {
    prs.addNodeParser(new MyConstructorParser());

const formatter = createFormatter(config);
const generator = new SchemaGenerator(program, parser, formatter, config);
const schema = generator.createSchema(config.type);

const schemaString = JSON.stringify(schema, null, 2);
fs.writeFile(output_path, schemaString, (err) => {
    if (err) throw err;


-p, --path 'index.ts'
    The path to the TypeScript source file. If this is not provided, the type will be searched in the project specified in the `.tsconfig`.

-t, --type 'My.Type.Name'
    The type the generated schema will represent. If omitted, the generated schema will contain all
    types found in the files matching path. The same is true if '*' is specified.

-i, --id 'generatedSchemaId'
    The `$id` of the generated schema. If omitted, there will be no `$id`.

-e, --expose <all|none|export>
    all: Create shared $ref definitions for all types.
    none: Do not create shared $ref definitions.
    export (default): Create shared $ref definitions only for exported types (not tagged as `@internal`).

-f, --tsconfig 'my/project/tsconfig.json'
    Use a custom tsconfig file for processing typescript (see instead of the default:
        "compilerOptions": {
            "noEmit": true,
            "emitDecoratorMetadata": true,
            "experimentalDecorators": true,
            "target": "ES5",
            "module": "CommonJS",
            "strictNullChecks": false,

-j, --jsDoc <extended|none|basic>
    none: Do not use JsDoc annotations.
    basic: Read JsDoc annotations to provide schema properties.
    extended (default): Also read @nullable, and @asType annotations.

    Do not sort properties.

    Do not allow additional items on tuples.

    Do not create a top-level $ref definition.

    Skip type checks for better performance.

    Do not encode references. According to the standard, references must be valid URIs but some tools do not support encoded references.

    Provide additional validation keywords to include.

-o, --out
    Specify the output file path. Without this option, the generator logs the response in the console.

--additional-properties <true|false>
    Controls whether or not to allow additional properties for objects that have no index signature.

    true: Additional properties are allowed
    false (default): Additional properties are not allowed

    Minify generated schema (default: false)

Current state

  • interface types
  • enum types
  • union, tuple, type[] types
  • Date, RegExp types
  • string, boolean, number types
  • "value", 123, true, false, null, undefined literals
  • type aliases
  • generics
  • typeof
  • keyof
  • conditional types

Run locally

yarn --silent run run --path 'test/valid-data/type-mapped-array/*.ts' --type 'MyObject'


yarn --silent run debug --path 'test/valid-data/type-mapped-array/*.ts' --type 'MyObject'

And connect via the debugger protocol.

AST Explorer is amazing for developers of this tool!


Publishing is handled by a 2-branch pre-release process, configured in publish-auto.yml. All changes should be based off the default next branch, and are published automatically.

  • PRs made into the default branch are auto-deployed to the next pre-release tag on NPM. The result can be installed with npm install ts-json-schema-generator@next
    • When merging into next, please use the squash and merge strategy.
  • To release a new stable version, open a PR from next into stable using this compare link.
    • When merging from next into stable, please use the create a merge commit strategy.

Extended version of

Author: Vega
Source Code: 
License: MIT License

#typescript #json