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)
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[![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 references from 'sendscript/references.mjs'

const { add } = references(['add'])
const stringify = Stringify()

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(['add'], 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 `references` 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.

## Reference

<!-- Reference -->

## Socket example

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.

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 schema = Object.keys(math)
const parse = Parse(schema, 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 references from 'sendscript/references.mjs'
import assert from 'node:assert'

const { add, square } = references(['add', 'square'])
const stringify = Stringify()

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)
    })
  })
}

// 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.

## Functions

SendScript as of `v2.4` supports functions to do basic templating. It does not
support async functions and will throw an error when you define one.

Under the hood the function is called when it is being parsed. Make sure you
understand what you are doing when mixing client and server functions.

```js
map((a) => add(a, 1))([1, 2, 3]))
```

It also supports nested functions.

```js
map(call)(map((a) => () => add(a, 1))([1, 2, 3]))
```

## Promises

### .then / .catch

Supported since vs `v2.3`.

```js
const getOrCreatePost = send(createPost(title).catch(createPost(title)))
```

You will likely need to define better helpers that makes it safer to handle
rejections and work with promises. It is however sensible to have this basic
behavior for the sendscript DSL and parser.

### 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 can then coerce the types of the instrumented stubs.

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

We'll also generate the docs for this module.

```bash bash 1>&2
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 **an array of function names**

```js

const schema = [
  'help',
  'version',

  ['math', [
    'add',
    'sub'
  ]],
  ['vector', [
    'add',
    'multiply'
  ]],
  ['utils', [
    'identity',
    'always'
  ]],
})
```

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

```js
const { math, vector } = references(schema)

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 references from 'sendscript/references.mjs'
import Parse from 'sendscript/parse.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 schema = ['processData']

const { processData } = references(schema)
const stringify = Stringify(leafSerializer)

// 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))

// The environment
const env = {
  processData: (data) => ({
    success: true,
    received: data,
  }),
}

// Parse with custom leaf deserializer
const parse = Parse(schema, env, leadDeserializer)

const result = parse(json)
```

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

## Changelog

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

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

## License

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

## Issues

See [issues][issues] for roadmap and known bugs.

[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
[issues]: https://github.com/bas080/sendscript/issues