Refactoring with Codemods to Automate API Adjustments

Clear a Stale Function Toggle

Let’s begin with a easy but sensible instance to reveal the
energy of codemods. Think about you’re utilizing a function
toggle in your
codebase to regulate the discharge of unfinished or experimental options.
As soon as the function is dwell in manufacturing and dealing as anticipated, the following
logical step is to scrub up the toggle and any associated logic.

As an example, take into account the next code:

const knowledge = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;

As soon as the function is totally launched and not wants a toggle, this
might be simplified to:

const knowledge = { identify: 'Product' };

The duty entails discovering all situations of featureToggle within the
codebase, checking whether or not the toggle refers to
feature-new-product-list, and eradicating the conditional logic surrounding
it. On the identical time, different function toggles (like
feature-search-result-refinement, which can nonetheless be in improvement)
ought to stay untouched. The codemod must perceive the construction
of the code to use adjustments selectively.

Understanding the AST

Earlier than we dive into writing the codemod, let’s break down how this
particular code snippet appears to be like in an AST. You should utilize instruments like AST
Explorer to visualise how supply code and AST
are mapped. It’s useful to know the node sorts you are interacting
with earlier than making use of any adjustments.

The picture under exhibits the syntax tree when it comes to ECMAScript syntax. It
accommodates nodes like Identifier (for variables), StringLiteral (for the
toggle identify), and extra summary nodes like CallExpression and
ConditionalExpression.

Determine 2: The Summary Syntax Tree illustration of the function toggle verify

On this AST illustration, the variable knowledge is assigned utilizing a
ConditionalExpression. The check a part of the expression calls
featureToggle('feature-new-product-list'). If the check returns true,
the consequent department assigns { identify: 'Product' } to knowledge. If
false, the alternate department assigns undefined.

For a activity with clear enter and output, I want writing exams first,
then implementing the codemod. I begin by defining a destructive case to
guarantee we don’t unintentionally change issues we need to depart untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy situation, implement it, then add a variation (like checking if
featureToggle is named inside an if assertion), implement that case, and
guarantee all exams go.

This method aligns nicely with Check-Pushed Growth (TDD), even
when you don’t observe TDD usually. Figuring out precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

With jscodeshift, you possibly can write exams to confirm how the codemod
behaves:

const remodel = require("../remove-feature-new-product-list");

defineInlineTest(
  remodel,
  {},
  `
  const knowledge = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;
  `,
  `
  const knowledge = { identify: 'Product' };
  `,
  "delete the toggle feature-new-product-list in conditional operator"
);

The defineInlineTest perform from jscodeshift means that you can outline
the enter, anticipated output, and a string describing the check’s intent.
Now, operating the check with a traditional jest command will fail as a result of the
codemod isn’t written but.

The corresponding destructive case would make sure the code stays unchanged
for different function toggles:

defineInlineTest(
  remodel,
  {},
  `
  const knowledge = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;
  `,
  `
  const knowledge = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;
  `,
  "don't change different function toggles"
);

Writing the Codemod

Let’s begin by defining a easy remodel perform. Create a file
referred to as remodel.js with the next code construction:

module.exports = perform(fileInfo, api, choices) {
  const j = api.jscodeshift;
  const root = j(fileInfo.supply);

  // manipulate the tree nodes right here

  return root.toSource();
};

This perform reads the file right into a tree and makes use of jscodeshift’s API to
question, modify, and replace the nodes. Lastly, it converts the AST again to
supply code with .toSource().

Now we are able to begin implementing the remodel steps:

1. Discover all situations of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Exchange your entire conditional expression with the consequent half,
   successfully eradicating the toggle.

Right here’s how we obtain this utilizing jscodeshift:

module.exports = perform (fileInfo, api, choices) {
  const j = api.jscodeshift;
  const root = j(fileInfo.supply);

  // Discover ConditionalExpression the place the check is featureToggle('feature-new-product-list')
  root
    .discover(j.ConditionalExpression, {
      check: {
        callee: { identify: "featureToggle" },
        arguments: [{ value: "feature-new-product-list" }],
      },
    })
    .forEach((path) => {
      // Exchange the ConditionalExpression with the 'consequent'
      j(path).replaceWith(path.node.consequent);
    });

  return root.toSource();
};

The codemod above:

• Finds ConditionalExpression nodes the place the check calls
  featureToggle('feature-new-product-list').
• Replaces your entire conditional expression with the ensuing (i.e., {
identify: 'Product' }), eradicating the toggle logic and leaving simplified code
  behind.

This instance demonstrates how simple it’s to create a helpful
transformation and apply it to a big codebase, considerably lowering
guide effort.

You’ll want to put in writing extra check circumstances to deal with variations like
if-else statements, logical expressions (e.g.,
!featureToggle('feature-new-product-list')), and so forth to make the
codemod sturdy in real-world situations.

As soon as the codemod is prepared, you possibly can try it out on a goal codebase,
such because the one you are engaged on. jscodeshift supplies a command-line
instrument that you need to use to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, verify that each one useful exams nonetheless
go and that nothing breaks—even when you’re introducing a breaking change.
As soon as glad, you possibly can commit the adjustments and lift a pull request as
a part of your regular workflow.

Codemods Enhance Code High quality and Maintainability

Codemods aren’t simply helpful for managing breaking API adjustments—they will
considerably enhance code high quality and maintainability. As codebases
evolve, they typically accumulate technical debt, together with outdated function
toggles, deprecated strategies, or tightly coupled parts. Manually
refactoring these areas might be time-consuming and error-prone.

By automating refactoring duties, codemods assist preserve your codebase clear
and freed from legacy patterns. Usually making use of codemods means that you can
implement new coding requirements, take away unused code, and modernize your
codebase with out having to manually modify each file.

Refactoring an Avatar Part

Now, let’s take a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar element tightly coupled with a
Tooltip. At any time when a person passes a identify prop into the Avatar, it
robotically wraps the avatar with a tooltip.

Determine 3: A avatar element with a tooltip

Right here’s the present Avatar implementation:

import { Tooltip } from "@design-system/tooltip";

const Avatar = ({ identify, picture }: AvatarProps) => {
  if (identify) {
    return (
      <Tooltip content material={identify}>
        <CircleImage picture={picture} />
      </Tooltip>
    );
  }

  return <CircleImage picture={picture} />;
};

The aim is to decouple the Tooltip from the Avatar element,
giving builders extra flexibility. Builders ought to be capable of determine
whether or not to wrap the Avatar in a Tooltip. Within the refactored model,
Avatar will merely render the picture, and customers can apply a Tooltip
manually if wanted.

Right here’s the refactored model of Avatar:

const Avatar = ({ picture }: AvatarProps) => {
  return <CircleImage picture={picture} />;
};

Now, customers can manually wrap the Avatar with a Tooltip as
wanted:

import { Tooltip } from "@design-system/tooltip";
import { Avatar } from "@design-system/avatar";

const UserProfile = () => {
  return (
    <Tooltip content material="Juntao Qiu">
      <Avatar picture="/juntao.qiu.avatar.png" />
    </Tooltip>
  );
};

The problem arises when there are lots of of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion could be extremely
inefficient, so we are able to use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we are able to
examine the element and see which nodes characterize the Avatar utilization
we’re concentrating on. An Avatar element with each identify and picture props
is parsed into an summary syntax tree as proven under:

Determine 4: AST of the Avatar element utilization

Writing the Codemod

Let’s break down the transformation into smaller duties:

• Discover Avatar utilization within the element tree.
• Verify if the identify prop is current.
• If not, do nothing.
• If current:
• Create a Tooltip node.
• Add the identify to the Tooltip.
• Take away the identify from Avatar.
• Add Avatar as a baby of the Tooltip.
• Exchange the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all situations of Avatar (I’ll omit a number of the
exams, however it is best to write comparability exams first).

defineInlineTest(
    { default: remodel, parser: "tsx" },
    {},
    `
    <Avatar identify="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
    `,
    `
    <Tooltip content material="Juntao Qiu">
      <Avatar picture="/juntao.qiu.avatar.png" />
    </Tooltip>
    `,
    "wrap avatar with tooltip when identify is offered"
  );

Much like the featureToggle instance, we are able to use root.discover with
search standards to find all Avatar nodes:

root
  .discover(j.JSXElement, {
    openingElement: { identify: { identify: "Avatar" } },
  })
  .forEach((path) => {
    // now we are able to deal with every Avatar occasion
  });

Subsequent, we verify if the identify prop is current:

root
  .discover(j.JSXElement, {
    openingElement: { identify: { identify: "Avatar" } },
  })
  .forEach((path) => {
    const avatarNode = path.node;

    const nameAttr = avatarNode.openingElement.attributes.discover(
      (attr) => attr.identify.identify === "identify"
    );

    if (nameAttr) {
      const tooltipElement = createTooltipElement(
        nameAttr.worth.worth,
        avatarNode
      );
      j(path).replaceWith(tooltipElement);
    }
  });

For the createTooltipElement perform, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip and the Avatar
element as a baby. Lastly, we name replaceWith to
substitute the present path.

Right here’s a preview of the way it appears to be like in
Hypermod, the place the codemod is written on
the left. The highest half on the appropriate is the unique code, and the underside
half is the reworked consequence:

Determine 5: Run checks inside hypermod earlier than apply it to your codebase

This codemod searches for all situations of Avatar. If a
identify prop is discovered, it removes the identify prop
from Avatar, wraps the Avatar inside a
Tooltip, and passes the identify prop to the
Tooltip.

By now, I hope it’s clear that codemods are extremely helpful and
that the workflow is intuitive, particularly for large-scale adjustments the place
guide updates could be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear a number of the challenges
and the way we are able to deal with these less-than-ideal points.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods must be used alongside different
methods. As an example, just a few years in the past, I participated in a design
system parts rewrite challenge at Atlassian. We addressed this subject by
first looking out the supply graph, which contained nearly all of inner
element utilization. This allowed us to know how parts have been used,
whether or not they have been imported beneath totally different names, or whether or not sure
public props have been steadily used. After this search section, we wrote our
check circumstances upfront, making certain we coated nearly all of use circumstances, and
then developed the codemod.

In conditions the place we could not confidently automate the improve, we
inserted feedback or “TODOs” on the name websites. This allowed the
builders operating the script to deal with particular circumstances manually. Often,
there have been solely a handful of such situations, so this method nonetheless proved
useful for upgrading variations.

Using Current Code Standardization Instruments

As you possibly can see, there are many edge circumstances to deal with, particularly in
codebases past your management—similar to exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
overview of the outcomes.

Nevertheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a selected coding fashion, you possibly can leverage these
instruments to scale back edge circumstances. By implementing a constant construction, instruments
like linters assist slender down the variations in code, making the
transformation simpler and minimizing surprising points.

As an example, you would use linting guidelines to limit sure patterns,
similar to avoiding nested conditional (ternary) operators or implementing named
exports over default exports. These guidelines assist streamline the codebase,
making codemods extra predictable and efficient.

Moreover, breaking down complicated transformations into smaller, extra
manageable ones means that you can sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
adjustments extra possible.

Codemod Composition

Let’s revisit the function toggle removing instance mentioned earlier. Within the code snippet
we’ve a toggle referred to as feature-convert-new have to be eliminated:

import { featureToggle } from "./utils/featureToggle";

const convertOld = (enter: string) => {
  return enter.toLowerCase();
};

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const consequence = featureToggle("feature-convert-new")
  ? convertNew("Hey, world")
  : convertOld("Hey, world");

console.log(consequence);

The codemod for take away a given toggle works high-quality, and after operating the codemod,
we wish the supply to appear like this:

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const consequence = convertNew("Hey, world");

console.log(consequence);

Nevertheless, past eradicating the function toggle logic, there are further duties to
deal with:

• Take away the unused convertOld perform.
• Clear up the unused featureToggle import.

In fact, you would write one massive codemod to deal with every little thing in a
single go and check it collectively. Nevertheless, a extra maintainable method is
to deal with codemod logic like product code: break the duty into smaller,
unbiased items—identical to how you’d usually refactor manufacturing
code.

Breaking It Down

We are able to break the large transformation down into smaller codemods and
compose them. The benefit of this method is that every transformation
might be examined individually, overlaying totally different circumstances with out interference.
Furthermore, it means that you can reuse and compose them for various
functions.

As an example, you may break it down like this:

• A metamorphosis to take away a particular function toggle.
• One other transformation to scrub up unused imports.
• A metamorphosis to take away unused perform declarations.

By composing these, you possibly can create a pipeline of transformations:

import { removeFeatureToggle } from "./remove-feature-toggle";
import { removeUnusedImport } from "./remove-unused-import";
import { removeUnusedFunction } from "./remove-unused-function";

import { createTransformer } from "./utils";

const removeFeatureConvertNew = removeFeatureToggle("feature-convert-new");

const remodel = createTransformer([
  removeFeatureConvertNew,
  removeUnusedImport,
  removeUnusedFunction,
]);

export default remodel;

On this pipeline, the transformations work as follows:

1. Take away the feature-convert-new toggle.
2. Clear up the unused import assertion.
3. Take away the convertOld perform because it’s not used.

Determine 6: Compose transforms into a brand new remodel

You may as well extract further codemods as wanted, combining them in
varied orders relying on the specified final result.

Determine 7: Put totally different transforms right into a pipepline to type one other remodel

The createTransformer Operate

The implementation of the createTransformer perform is comparatively
easy. It acts as a higher-order perform that takes a listing of
smaller remodel features, iterates by means of the checklist to use them to
the foundation AST, and at last converts the modified AST again into supply
code.

import { API, Assortment, FileInfo, JSCodeshift, Choices } from "jscodeshift";

sort TransformFunction = { (j: JSCodeshift, root: Assortment): void };

const createTransformer =
  (transforms: TransformFunction[]) =>
  (fileInfo: FileInfo, api: API, choices: Choices) => {
    const j = api.jscodeshift;
    const root = j(fileInfo.supply);

    transforms.forEach((remodel) => remodel(j, root));
    return root.toSource(choices.printOptions || { quote: "single" });
  };

export { createTransformer };

For instance, you would have a remodel perform that inlines
expressions assigning the function toggle name to a variable, so in later
transforms you don’t have to fret about these circumstances anymore:

const shouldEnableNewFeature = featureToggle('feature-convert-new');

if (!shouldEnableNewFeature && someOtherLogic) {
  //...
}

Turns into this:

if (!featureToggle('feature-convert-new') && someOtherLogic) {
  //...
}

Over time, you may construct up a set of reusable, smaller
transforms, which may vastly ease the method of dealing with tough edge
circumstances. This method proved extremely efficient in our work refining design
system parts. As soon as we transformed one bundle—such because the button
element—we had just a few reusable transforms outlined, like including feedback
firstly of features, eradicating deprecated props, or creating aliases
when a bundle is already imported above.

Every of those smaller transforms might be examined and used independently
or mixed for extra complicated transformations, which accelerates subsequent
conversions considerably. Consequently, our refinement work grew to become extra
environment friendly, and these generic codemods at the moment are relevant to different inner
and even exterior React codebases.

Since every remodel is comparatively standalone, you possibly can fine-tune them
with out affecting different transforms or the extra complicated, composed ones. For
occasion, you may re-implement a remodel to enhance efficiency—like
lowering the variety of node-finding rounds—and with complete check
protection, you are able to do this confidently and safely.