Functional TypeScript
TypeScript standard for rock solid serverless functions. (sponsored by Saasify)
Features
- Robust: Type-safe serverless functions!
- Simple: Quick to setup and integrate
- Standard: Just TypeScript + JSON Schema
- Compatible: Supports all major serverless providers (AWS, GCP, Azure, Now, etc)
- Explicit: Easily generate serverless function docs
- Fast: Uses ajv for schema validation
- Lightweight: Focused http handler optimized for serverless environments
- Robust: Used in production at Saasify
Contents
What is Functional TypeScript (FTS)?
FTS transforms standard TypeScript functions like this:
/**
* This is a basic TypeScript function.
*/
export function hello(name: string = 'World'): string {
return `Hello ${name}!`
}
Into type-safe serverless functions that can be called over HTTP like this (GET):
https://example.com/hello?name=GitHub
Or like this (POST):
{
"name": "GitHub"
}
And returns a result like this:
"Hello GitHub!"
All parameters and return values are type-checked by a standard Node.js HTTP handler, so you can invoke your TypeScript functions remotely with the same confidence as calling them directly.
Usage
You can use this package as either a CLI or as a module.
CLI
npm install -g fts
This will install the fts
CLI program globally.
Generates an FTS Definition schema given a TS input file.
Usage: fts [options] <file.ts>
Options:
-p, --project <project> Path to 'tsconfig.json'.
-h, --help output usage information
Module
npm install --save fts
# (optional) add support for http transport
npm install --save fts-http
Here is an end-to-end example using HTTP (examples/hello-world).
const fts = require('fts')
const ftsHttp = require('fts-http')
async function example() {
const tsFilePath = './hello-world.ts'
const jsFilePath = './hello-world.js'
// Parse a TS file's main function export into a Definition schema.
const definition = await fts.generateDefinition(tsFilePath)
console.log(JSON.stringify(definition, null, 2))
// Create a standard http handler function `(req, res) => { ... }` that will
// invoke the compiled JS function, performing type checking and conversions
// between http and json for the function's parameters and return value.
const handler = ftsHttp.createHttpHandler(definition, jsFilePath)
// Create a `micro` http server that uses our HttpHandler to respond to
// incoming http requests.
await ftsHttp.createHttpServer(handler, 'http://localhost:3000')
// You could alternatively use your `handler` with any Node.js server
// framework, such as express, koa, @now/node, etc.
}
example().catch((err) => {
console.error(err)
process.exit(1)
})
Once you have a server running, you can invoke your type-safe function over HTTP:
$ curl -s 'http://localhost:3000?name=GET'
Hello GET!
$ curl -s 'http://localhost:3000' -d 'name=POST'
Hello POST!
Note that in this example, we're generating the FTS Definition and serving it together, but in practice we recommend that you generate these definitions during your build step, alongside your normal TS => JS compilation. The definitions should be viewed as json build artifacts that are referenced at runtime in your server or serverless function.
Definition Format
Given our "hello world" example from earlier, FTS generates the following JSON definition that fully specifies the hello
function export.
{
"title": "hello",
"version": "0.0.1",
"config": {
"language": "typescript",
"defaultExport": false,
"namedExport": "hello"
},
"params": {
"context": false,
"order": ["name"],
"schema": {
"type": "object",
"properties": {
"name": {
"type": "string",
"default": "World"
}
},
"additionalProperties": false,
"required": ["name"],
"$schema": "http://json-schema.org/draft-07/schema#"
}
},
"returns": {
"async": false,
"schema": {
"type": "object",
"properties": {
"result": {
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}
}
}
In addition to some metadata, this definition contains a JSON Schema for the function's parameters and a JSON Schema for the function's return type.
Note that this definition allows for easy type checking, documentation generation, and automated testing via tools like json-schema-faker.
Status
FTS is stable and is actively used in production by Saasify.
FAQ
Why Serverless?
Serverless functions allow your code to run on-demand and scale automatically both infinitely upwards and down to zero. They are great at minimizing cost in terms of infrastructure and engineering time, largely due to removing operational overhead and reducing the surface area for potential errors.
For more information, see Why Serverless?, and an excellent breakdown on the Tradeoffs that come with Serverless.
Why FTS?
The serverless space has seen such rapid growth that tooling, especially across different cloud providers, has struggled to keep up. One of the major disadvantages of using serverless functions at the moment is that each cloud provider has their own conventions and gotchas, which can quickly lead to vendor lock-in.
For example, take the following Node.js serverless function defined across several cloud providers:
AWS
exports.handler = (event, context, callback) => {
const name = event.name || 'World'
callback(null, `Hello ${name}!`)
}
Azure
module.exports = function(context, req) {
const name = req.query.name || (req.body && req.body.name) || 'World'
context.res = { body: `Hello ${name}!` }
context.done()
}
GCP
const escapeHtml = require('escape-html')
exports.hello = (req, res) => {
const name = req.query.name || req.body.name || 'World'
res.send(`Hello ${escapeHtml(name)}!`)
}
FTS
export function hello(name: string = 'World'): string {
return `Hello ${name}!`
}
FTS allows you to define provider-agnostic serverless functions while also giving you strong type checking and built-in documentation for free.
How is FTS different from other RPC standards?
Functional TypeScript is a standard for declaring and invoking remote functions. This type of invocation is known as an RPC or remote procedure call.
Some other notable RPC standards include SOAP, Apache Thrift, and gRPC.
So how does FTS fit into this picture?
First off, FTS is fully compatible with these other RPC standards, with a gRPC transport layer on the roadmap.
The default HTTP handler with JSON Schema validation is the simplest way of using FTS, but it's pretty straightforward to interop with other RPC standards. For example, to use FTS with gRPC, we need to convert the JSON Schemas into protocol buffers (both of which describe the types and format of data) and add a gRPC handler which calls our compiled target JS function. Of course, there are pros and cons to using HTTP vs gRPC, with HTTP being easier to use and debug and gRPC being more efficient and scalable.
The real benefit of FTS is that the remote function definitions are just standard TypeScript, without you having to worry about the complexities of gRPC, protocol buffers, or other RPC formats. You only need to understand and write TypeScript.
Couple that with the simplicity and scalability of serverless functions, and FTS starts to become really powerful, enabling any TypeScript developer to create rock solid serverless functions easier than ever before.
How is FTS related to FaaSLang?
Functional TypeScript builds off of and shares many of the same design goals as FaaSLang. The main difference is that FaaSLang's default implementation uses JavaScript + JSDoc to generate custom schemas for function definitions, whereas FTS uses TypeScript to generate JSON Schemas for function definitions.
In our opinion, the relatively mature JSON Schema specification provides a more solid and extensible base for the core schema validation layer. JSON Schema also provides interop with a large ecosystem of existing tools and languages. For example, it would be relatively simple to extend FTS beyond TypeScript to generate JSON Schemas from any language that is supported by Quicktype (Go, Objective-C, C++, etc).
FTS also exposes a standard Node.js http handler for invoking FTS functions (req, res) => { ... }
. This makes it extremely easy to integrate with popular Node.js server frameworks such as express, koa, and micro. While FaaSLang could potentially be extended to support more general usage, the default implementation currently only supports a custom API gateway server... which makes me a sad panda.
How are primitive types like Date and Buffer handled?
These are both very common and useful types that are built into TypeScript and JavaScript, but they're not supported by JSON or JSON Schema.
To resolve this, FTS uses two custom JSON Schema keywords (convertTo
and convertFrom
) to handle encoding and decoding these types as strings. Dates are encoded as ISO utf8 strings and Buffers are encoded as base64 strings.
All of these conversions are handled transparently and efficiently by the FTS wrappers so you can just focus on writing TypeScript.
How do I use FTS with my Serverless Provider (AWS, GCP, Azure, Now, OpenWhisk, etc)?
Great question -- this answer will be updated once we have a good answer...
Related
- Saasify - Uses FTS for serverless TS support.
- FaaSLang - Similar in spirit to this project but uses JS instead of TypeScript.
- FastAPI - Similar functionality but for Python.
- JSON RPC - Similar JSON RPC standard.
- AWS TypeScript Template - Default TypeScript template for AWS serverless functions.
- Serverless Plugin TypeScript - Serverless plugin for zero-config Typescript support.
- typescript-json-schema - Used under the hood to convert TypeScript types to JSON Schema.
- Quicktype - Very useful utility which uses JSON Schema as a common standard for converting between different type systems.
License
MIT © Saasify
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