README.mz

# SendScript

Write JS code that you can run on servers, browsers or other clients.

[![NPM](https://img.shields.io/npm/v/sendscript?color=blue&style=flat-square)](https://www.npmjs.com/package/sendscript)
[![100% Code Coverage](https://img.shields.io/badge/coverage-100%25-brightgreen?style=flat-square)](#tests)
[![Standard Code Style](https://img.shields.io/badge/code_style-standard-brightgreen.svg?style=flat-square)](https://standardjs.com)
[![License](https://img.shields.io/npm/l/sendscript?color=brightgreen&style=flat-square)](./LICENSE.txt)

<!-- toc -->

## Introduction

There has been interest in improving APIs by allowing aggregations in a
single request. Examples include

- [JSON-RPC](https://json-rpc.dev/) which allows you to do multiple requests
  but it does not allow you to compose the return value of one endpoint to be the
  input/arguments of another.

- [GraphQL](https://graphql.org/) is very cool but also introduces a new languages and the
  tooling that is required to wield it.

What SendScript attempts is to allow for very expressive queries and mutations to be performed
that read and write like ordinary JS. That means that the queries and complete programs
that are sent to the server from a client can also just run on the server as is. The only
limitation being the serialization which by default is limited by JSON and could be extended by
using more advanced (de)serialization libraries.

SendScript produces an intermediate JSON representation of the program. Let's see what that looks like.

```js|json node --input-type=module | tee /tmp/sendscript.json
import stringify from 'sendscript/stringify.mjs'
import module from 'sendscript/module.mjs'

const { add } = module(['add'])

console.log(stringify(add(1,2)))
```

We can then parse that JSON and it will evaluate down to a value.

```js|json node --input-type=module
import Parse from 'sendscript/parse.mjs'

const module = {
  add(a, b) {
    return a + b
  }
}

const parse = Parse(module)

const program = '["call",["ref","add"],[1,2]]'

console.log(parse(program))
```

SendScript does more than a simple function call. It supports function
composition and even await.

This package is nothing more than the absolute core of sendscript. It
includes:

- The `module` function to create stubs to write the programs.
- `stringify` which takes the program and returns a JSON string.
- `parse` which takes the `stringify` JSON string and a real module and returns the result.

The naming could use more love and there are many things to solve either in the core or around it.
Things like supporting more complex (de)serializers, errors and maybe mixing client functions with
sendscript programs. Contact me if I have piqued your interest.

---

SendScript leaves it up to you to choose HTTP, web-sockets or any other
method of communication between servers and clients that best fits your
needs.

## Socket example

For this example we'll use [socket.io][socket.io].

### Module

We write a simple module.

```js cat - > ./example/math.mjs
// ./example/math.mjs

export const add = (a, b) => a + b
export const square = a => a * a
```

### Server

Here a socket.io server that runs SendScript programs.

```js cat - > ./example/server.socket.io.mjs
// ./example/server.socket.io.mjs

import { Server } from 'socket.io'
import Parse from 'sendscript/parse.mjs'
import * as math from './math.mjs'

const parse = Parse(math)
const server = new Server()
const port = process.env.PORT || 3000

server.on('connection', (socket) => {
  socket.on('message', async (program, callback) => {
    try {
      const result = parse(program)
      callback(null, result) // Pass null as the first argument to indicate success
    } catch (error) {
      callback(error) // Pass the error to the callback
    }
  })
})

server.listen(port)
process.title = 'sendscript'
```

### Client

Now for a client that sends a program to the server.

```js cat - > ./example/client.socket.io.mjs
// ./example/client.socket.io.mjs

import socketClient from 'socket.io-client'
import stringify from 'sendscript/stringify.mjs'
import module from 'sendscript/module.mjs'
import * as math from './math.mjs'
import assert from 'node:assert'

const port = process.env.PORT || 3000
const client = socketClient(`http://localhost:${port}`)

const send = program => {
  return new Promise((resolve, reject) => {
    client.emit('message', stringify(program), (error, result) => {
      error
        ? reject(error)
        : resolve(result)
    })
  })
}

const { add, square } = module(math)

// The program to be sent over the wire
const program = square(add(1, add(add(2, 3), 4)))

const result = await send(program)

console.log('Result: ', result)

assert.equal(result, 100)

process.exit(0)
```

Now we run this server and a client script.

```bash bash
set -e

# Run the server
node ./example/server.socket.io.mjs&

# Run the client example
node ./example/client.socket.io.mjs

pkill sendscript
```

## Repl

Sendscript ships with a barebones (no-dependencies) node-repl script. One can run it by simply typing `sendscript` in their console.

> Use the `DEBUG='*'` to enable all logs or `DEBUG='sendscript:*'` for printingonly sendscript logs.

## Async/Await

SendScript supports async/await seamlessly within a single request. This avoids the performance pitfalls of waterfall-style messaging, which can be especially slow on high-latency networks.

While it's possible to chain promises manually or use utility functions, native async/await support makes your code more readable, modern, and easier to reason about — aligning SendScript with today’s JavaScript best practices.

```js
const userId = 'user-123'
const program = {
  unread: await fetchUnreadMessages(userId),
  emptyTrash: await emptyTrash(userId),
  archived: await archiveMessages(selectMessages({ old: true }))
}

const result = await send(program)
```

This operation is done in a single round-trip. The result is an object with the defined properties and returned values.

## TypeScript

There is a good use-case to write a module in TypeScript.

1. Obviously the module would have the benefits that TypeScript offers when
   coding.
2. You can use tools like [typedoc][typedoc] to generate docs from your types to
   share with consumers of your API.
3. You can use the types of the module to coerce your client to adopt the
   module's type.

Let's say we have this module which we use on the server.

```bash|ts bash
cat ./example/typescript/math.ts
```

We want to use this module on the client. We create a client version of that module and coerce the types to match those of the server.

```bash|ts bash
cat ./example/typescript/math.client.ts
```

We now use the client version of this module.

```bash|ts bash
cat ./example/typescript/client.ts
```

We'll also generate the docs for this module.

```bash bash 1>&2
npm install --no-save \
  typedoc \
  typedoc-plugin-markdown

npx typedoc --plugin typedoc-plugin-markdown --out ./example/typescript/docs ./example/typescript/math.ts
```

You can see the docs [here](./example/typescript/docs/globals.md)

> [!NOTE]
> Although type coercion on the client side can improve the development
> experience, it does not represent the actual type.
> Values are subject to serialization and deserialization.


## Schema and Nested Modules

Sendscript allows you to define your API as a **nested object of functions**, making it easy to organize your DSL into modules and submodules. Each function is instrumented so that when serialized, it produces a structured reference that can be safely sent and executed elsewhere.

### Defining a Nested Module

You can define a schema as either:

1. **An object with nested objects** – submodules.
2. **An array of function names** – automatically instrumented.

```js
import module from 'sendscript/module.mjs'

const myModule = module({
  math: ['add', 'sub'],

  // Use an object with keys and true value
  vector: {
    add: true,
    multiply: true
  },

  // or use an array.
  utils: ['identity', 'always'],
})
```

Functions are referenced via their **path in the module tree**:

```js
const { math, vector } = myModule

math.add(
  1,
  vector.length(
    vector.multiply([1,2], 3)
  )
)
```

## Validation (using Zod)

SendScript focuses on program serialization and execution. For runtime input validation, you can use [Zod](https://zod.dev).

### Validating structured input

```js
const userSchema = z.object({
  id: z.string().uuid(),
  name: z.string(),
  roles: z.array(z.string())
})

export function createUser(user) {
  userSchema.parse(user)

  return { success: true }
}
```

**Benefits**:

- Ensures arguments match expected types and shapes.
- Throws structured errors that can be propagated to clients.
- Works with TypeScript for automatic type inference.

## Leaf Serializer

By default, SendScript uses JSON for serialization, which limits support to primitives and plain objects/arrays. To support richer JavaScript types like `Date`, `RegExp`, `BigInt`, `Map`, `Set`, and `undefined`, you can provide custom serialization functions.

The `stringify` function accepts an optional `leafSerializer` parameter, and `parse` accepts an optional `leafDeserializer` parameter. These functions control how non-SendScript values (leaves) are encoded and decoded.

### Example with superjson

Here's how to use [superjson](https://github.com/blitz-js/superjson) to support extended types:

```js
import SuperJSON from 'superjson'
import stringify from 'sendscript/stringify.mjs'
import Parse from 'sendscript/parse.mjs'
import module from 'sendscript/module.mjs'

const leafSerializer = (value) => {
  if (value === undefined) return JSON.stringify({ __undefined__: true })
  return JSON.stringify(SuperJSON.serialize(value))
}

const leafDeserializer = (text) => {
  const parsed = JSON.parse(text)
  if (parsed && parsed.__undefined__ === true) return undefined
  return SuperJSON.deserialize(parsed)
}

const { processData } = module(['processData'])

// Program with Date, RegExp, and other types
const program = {
  createdAt: new Date('2020-01-01T00:00:00.000Z'),
  pattern: /foo/gi,
  count: BigInt('9007199254740992'),
  items: new Set([1, 2, 3]),
  mapping: new Map([['a', 1], ['b', 2]])
}

// Serialize with custom leaf serializer
const json = stringify(processData(program), leafSerializer)

// Parse with custom leaf deserializer
const parse = Parse({
  processData: (data) => ({
    success: true,
    received: data
  })
})

const result = parse(json, leafDeserializer)
```

The leaf wrapper format is `['leaf', serializedPayload]`, making it unambiguous and safe from colliding with SendScript operators.

## Tests

Tests with 100% code coverage.

```bash bash
npm t -- -R silent
npm t -- report text-summary
```

## Formatting

Standard because no config.

```bash bash
npx standard
```

## Changelog

The [changelog][changelog] is generated using the useful
[auto-changelog][auto-changelog] project.

```bash bash > /dev/null
npx auto-changelog -p
```

## Dependencies

Check if packages are up to date on release.

```bash bash
npm outdated && echo 'No outdated packages found'
```

## License

See the [LICENSE.txt][license] file for details.

## Roadmap

- [ ] Support for simple lambdas to compose functions more easily.

[license]:./LICENSE.txt
[socket.io]:https://socket.io/
[changelog]:./CHANGELOG.md
[auto-changelog]:https://www.npmjs.com/package/auto-changelog
[typedoc]:https://github.com/TypeStrong/typedoc