unfort

1.3.0 • Public • Published

unfort

A build tool for the web that prioritises performance during development. Fundamentally, this project is a greenfield reimplementation of a subset of webpack's features.

Does some novel stuff:

  • Hot swaps in milliseconds, regardless of the codebase size
  • Persistent caching to optimize build time
  • Live bindings that automatically update module imports during hot swaps

Does some standard stuff:

  • Built-in support for JS, JSON, CSS and binary (image/font/etc) files
  • Exposes a babel & postcss pipeline by default - but happily accepts overrides

Some stuff that I'm currently using it for:

  • Replacing webpack in development environments
  • Enabling a REPL-like experience for prototyping
  • Providing asset hot-swaps when hacking on non-JS systems

Note: this is both an experimental and personal project. The docs are intentionally high-level as changes to the API are frequent and (often) breaking. You probably shouldn't use this unless you're happy to read code and hack on stuff.

Some of the write-ups are a bit hand-wavy and simplified, so if you've got any questions, feel free to open an issue and ask.

Documentation


Installation

npm install --save unfort

Design Goals

Aim for:

  • Rapid feedback loops during development. Changes should be applied in milliseconds, regardless of the codebase size. Enable a REPL-like experience from the comfort of a text editor.
  • Improve build times with persistent caching. Write the expensive data to disk. Repeated builds should reuse the data. Cache invalidation should be smart, but when it fails, allow all the data to be easily nuked.
  • Code over configuration. Provide a minimal set of options for hard-coded wiring. Expose the entire pipeline and allow any part to be overridden. Enable experimentation.
  • Support for modern tooling out of the box. Ship with support for babel and postcss.
  • Support for the most common file formats. Support JS, JSON and CSS. Assume all other formats are plain-text or binary and can be streamed from disk.
  • A focused codebase. Reduce bloat and complexity by only providing support for the simple and common use-case.

Things to explicitly avoid:

  • Abstractions: config files, CLIs, plugins, loaders, etc. Make the most minimal amount of abstractions necessary for the common use-case. Whenever possible, push boilerplate into user-space. Avoid one-liners.
  • Support for production environments. Production environments require an entirely different set of features from a development environment. Supporting the needs of both is well outside of scope. Just use webpack or browserify.
  • Support for tool X or file format Y. Integrating other tooling or file formats should be left entirely up to the user.
  • Support older versions of X. Aim to support evergreen browsers and the latest version of Node.

Background

Webpack and browserify are pretty amazing when you get started on a project, but performance tends to drop sharply as your codebase grows and incremental builds become a pain-point. I've previously tried exploring improvements for webpack's performance, with some limited success.

Hopefully this project's research and discoveries will enable improvements to the experience provided by comparable build tools.

Performance Wins (Compared to Webpack)

No Bundling

Probably the biggest performance win that unfort has over webpack is a lack of a bundling phase. Unfort skips the need for a bundle by constructing simple shims that allow the entire codebase to be streamed directly out of memory and into the browser.

A single browser global is used by unfort to expose a module system with hooks for modules to register themselves. This enables modules to be simply appended to a document, in an execution context such as a script element or an eval statement. The module system also exposes hooks to execute from any entry point.

This module system - while somewhat hacky - allows unfort to avoid the entire CPU-, IO- and memory-intensive bundling phase. Without a bundling phase, incremental rebuilds become much faster as we only need to recompile single files, rather than the entire codebase.

Parsing and Code Generation

On the parsing side, unfort's faster when handling files that are transformed with babel as it re-uses the AST for dependency analysis. It also avoids the multiple code-generation phases that webpack implicitly requires when using loaders.

Initial Builds

Unlike webpack's slow initial builds, unfort's reuse of cached data can enable much faster builds. After a small period of reading in and validating data, the build will complete. As unfort stores data on a per-file basis, initial builds with only a partial set of valid data will still complete in a fraction of the usual time.

Performance Losses (Compared to Webpack)

On larger projects, unfort's initial builds without cached data can be somewhat slower.

I suspect this would be a combination of:

  • Parsing with babylon. Acorn is much faster, but would require us to expand our infrastructure to handle more AST formats. By standardising on babel's AST, we get a lot of things for free.
  • IO reads for missing data in the file cache. Could probably remove these as we'd know ahead of time that there is no data.
  • babel-generator's overhead for rendering code and source maps. We're not manipulating the majority of files, so we could probably just remove babel-generator and generate the source maps by hand.

In general, I suspect there will be still be a lot of low-hanging fruit in this project as it hasn't been profiled for some time.

Reflections

Coming into the project I had assumed that reimplementing webpack with a combination of worker processes, re-use of ASTs, and persistent caching would provide significant wins. As is usual, some of these assumptions were correct and some proved incorrect.

Worker processes

I initially started this project with the intent to use worker processes to run jobs in parallel. After trying them on a couple of smaller projects I realized that they had a negative impact on performance and removed them from the codebase.

Nonetheless, I've kept musing over them, and here are some notes in case anyone else wants to implement something with them:

  • There's a large cost associated with transporting data in and out of workers. So you'll probably want to build your pipeline such that each file is handled by a specific worker that doesn't require much context or interactions from the master process.
  • There's a large cost to spawning child processes. Node's pretty fast to boot, but it's not so fast to read in large amounts of modules. You'd only want workers if you had build times greater than 15 seconds where the spawn overhead is justified by the performance improvements of parallel jobs
  • Spawn workers early so that you're job requests aren't blocked while the worker process boots and initializes.
  • Spreading jobs around different processes limits the ability of v8's JIT to optimize code accurately. You might want to try limiting the number of workers and/or using particular workers for particular code paths.
  • Debugging workers is a pain. If you're going to implement a worker pipeline, make sure that everything goes through an interface which enables you to force execution within the master process. By consolidating execution within the foreground process, it improves your ability to introspect, in particular it enables you to use node's debugger.

Reuse of ASTs

Webpack's loader pipeline works on a low-level primitive: strings of code. This becomes a performance issue when each loader needs to individually parse the code, manipulate the AST and then generate more code and source maps. Once each loader has been applied, webpack then parses the code (again) and starts all of its magic. While a lot of projects will only use a single loader for JS files (typically babel-loader), the re-parsing is still a performance issue.

To get around this, we simply re-use the AST that babel generates during transformation so that we only need to parse files once, while preserving the ability to introspect dependency identifiers. In cases where we are not applying babel's transforms, we simply use babel's parser (babylon) directly to generate an AST. Consolidating on babel's pipeline ensures that we only need a single code-path to handle dependency analysis of JS files.

Looking into the future, hopefully all parsers and tools will converge on the ESTree spec. This would enable build tools to simply pass ASTs around.

Persistent caching

Persistent caching has proven to work quite well. It adds a small overhead to initial builds, but massively reduces the total time when repeating a build.

For cache read and writes unfort defaults to kv-cache which enables us to store each file's data in separate files. The primary advantage of multiple files is that it removes any overhead associated with reading and discarding stale data. A downside is that IO overhead increases with the number of files that are used in the build. If IO overhead ever becomes too much of an issue, it may be worthwhile investigating a proper DB, such as SQLite, as a replacement store.

Our pipeline generates cache keys that are composed of the file's path and modified time. For textual files, we also generate a murmur hash of the content so that we can get around OS limitations on file-system accuracy.

Cache invalidation can be a pain. To get around it we use env-hash to namespace all cached data during the boot process. The namespace reflects key factors in the environment and enables us to discard cached data when a new library is installed, when changes are made to a build script, or when environmental files (such as package.json or .babelrc) are changed.

Immutable data

Internally, unfort makes heavy use of immutable data structures provided by the immutable package. These structures provide a number of key benefits:

  • we can easily determine deep equality, enabling us to drop out of build phases when the graph no longer equals what we started with.
  • we can orchestrate complicated asynchronous flows with the simple understanding that sub-systems will never be able to mutate our data.

While I've used immutable data in a couple of different projects, unfort has been at a much larger scale. The experience has been extremely positive - there is a bit more boilerplate, but the safety guarantees make it extremely trivial to reason about what something can and can't do.

If anyone is considering tooling for a build tool, I would strongly recommend starting with immutable data and only dropping to low-level JS objects when performance is required. The Record class in immutable is particularly useful, as it allows you to expose named properties so that you can use it as a drop-in replacement for read-only objects.


Bootstrap Runtime

The bootstrap runtime provides a module system that mimics the commonjs system used by Node. It exposes a global variable __modules that allows modules to be injected into a registry and executed.

The bootstrap's API:

// An object used as the runtime's registry of modules
__modules.modules
 
// Injects a module into the runtime
__modules.defineModule(mod)
 
// Extends the module object with properties used
// for bookkeeping
__modules.extendModule(mod)
 
// Invokes the specified module
__modules.executeModule('name')
 
// Returns the values that a module exported
__modules.getModuleExports(mod)
 
// Builds the `require` function for a specific module
__modules.buildRequire(mod)

Note: The bootstrap is designed to be monkey-patched. The hooks exposed are intended to enable experimental features during runtime.


Hot Runtime

The hot runtime monkey-patches the bootstrap to add support for hot swapping of assets.

Live Bindings

To provide an improved development workflow, the hot runtime slips proxies between module bindings so that imports are automatically updated when hot swaps occur. In effect, updates to one part of a codebase immediately change the entire system's behaviour.

Mindful of the more dynamic system that live bindings enable, there are a number of methods available on the module.hot object which provide more control over module life-cycles during hot swaps.

module.hot API

To hook into the hot swap system, JS assets are provided with a module.hot API that loosely resembles Webpack's HMR.

Note: As CSS and JSON files should be considered stateless, they are automatically swapped when changes occur.

module.hot.accept()

Allows you to denote that a file can be hot swapped.

module.hot.accept();

Accepts an optional callback that will be executed after the module has been removed.

module.hot.accept(() => {
  // ...
});

module.hot.changes

Allows you to specify a callback that will be triggered each time that the hot swap phase completes. This enables you to re-render a tree or recalculate data using proxy bindings that use the most recent code.

function render() {
  // ...
}
 
module.hot.changes(render);

Note: If the module that specified the callback is one of the modules that is swapped, the changes callback will not be called.

module.hot.exit

Allows you to pass data from one version of a module to the next. When a module is about to be swapped, the callback passed to module.hot.exit will be executed and the return value will be stored for the next version.

let state = {
  // ...
};
 
module.hot.exit(() => state);

Note: module.hot.exit automatically accepts hot swaps, so you don't need to call module.hot.accept as well.

module.hot.enter

Allows you to read in data from previous versions of the module. When a new version of a module is being executed, callbacks passed to module.hot.enter will be synchronously called with one argument: the value returned from the previous version's module.hot.exit callback.

let state;
 
module.hot.enter(prevState => {
  state = prevState;
  // ...
});
 
if (!state) {
  state = createState();
}

Note: callbacks passed to module.hot.enter will only be called when a new version is entering. They will not be called when a module first initializes.

Configuring the Hot Runtime

Defaults:

{
  SILENT_HOT_RUNTIME: false,
  SOCKET_IO_URL: undefined,
  SOCKET_IO_OPTIONS: undefined
}

You can override them by binding to the browser global __UNFORT__. for example:

<script>
  window.__UNFORT__ = {
    SOCKET_IO_URL: 'http://127.0.0.1:3000'
  };
</script> 

The Build Process at a High-Level

Given a set of files that represent entry points to a codebase, the dependency graph will trace the graph by recursively asking the pipeline for the resolved dependencies of each file encountered.

For the pipeline to produce a list of resolved dependencies, the following steps will typically occur:

  • read the file into memory
  • produce an AST by parsing the file
  • apply transforms to the AST (eg: babel or postcss plugins)
  • traverse the AST and look for dependency identifiers
  • inspect the file-system and resolve each identifier to a specific file

As dependencies are resolved, the graph creates nodes and edges that represent the connections between files. Once all nodes have been identified and traced, the graph emits a signal that indicates the end of the tracing process, and we enter the code generation phase.

Code generation involves a number of processes that include:

  • rendering ASTs to code
  • generating source maps
  • generating module shims that enable the code to function with unfort's bootstrap

The completion of the code generation signals the end of the build, at which point we can start sending signals to the front-end to update its assets.


The Pipeline

Unfort's pipeline mostly revolves around a record-store instance that enables us to define a collection of jobs that can be applied to a file to produce some result.

The record store is asynchronous and makes heavy use of promises. Asynchronous jobs enable us to split up CPU-intensive tasks so that we avoid blocking Node's event-loop. Promises enable the record store to both memoize a job's result and merge job requests together so we only generate data once per file.

If you want to interact, override or tinker with the pipeline, you can use the extendJobs hook. The current list of jobs that are used are in src/jobs.js. If you need extra clarity, you can either check the job tests in src/tests/jobs.js or check how the jobs are used the other parts of the system.

For example, to remove source map annotations from all files:

const unfort = require('unfort');
 
const build = unfort.createBuild({
  // ...
});
 
build.extendJobs(defaults => {
  return {
    sourceMapAnnotation(ref, store) {
      return null;
    }
  };
});
 
build.start();

If you wanted to override the cache key for files in a particular directory:

build.extendJobs(defaults => {
  return {
    cacheKey(ref, store) {
      if (ref.name.indexOf('/some/dir') === 0) {
        return 'some cache key';
      } else {
        return defaults.cacheKey(ref, store);
      }
    }
  };
});

If you want to add postcss plugins for specific files:

build.extendJobs(defaults => {
  return {
    postcssPlugins(ref, store) {
      if (ref.name.indexOf('/some/dir') === 0) {
        return [
          // an array of plugins
          // ...
        ];
      } else {
        return defaults.postcssPlugins(ref, store);
      }
    }
  };
});

Development Notes

Status

npm version Build Status codecov.io Dependency Status devDependency Status

Scripts

The following commands are available to interact with unfort's code-base:

  • npm run build builds the project into a form that node can interpret.

    Once Node reaches parity with the ES2015 spec, the build process will be removed.

  • npm test runs the test suite with source maps.
  • npm run _test runs the test suite without source maps. Sometimes the stack traces get a bit messed up with the source maps, so this can help to debug.
  • npm run lint runs eslint over the project.
  • npm run coverage runs the test suite and generates a coverage report in the "coverage" directory.

Related Packages

These packages used to live in unfort, but have been externalized, you may find it useful to read or improve their codebases:

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Version

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