Refactoring with Codemods to Automate API Modifications

Clear a Stale Function Toggle

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

For example, take into account the next code:

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

As soon as the characteristic is absolutely launched and not wants a toggle, this
will be simplified to:

const knowledge = { identify: 'Product' };

The duty entails discovering all cases 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 similar time, different characteristic 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 modifications selectively.

Understanding the AST

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

The picture under reveals the syntax tree by way of ECMAScript syntax. It
comprises 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 characteristic toggle examine

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 process with clear enter and output, I favor writing assessments first,
then implementing the codemod. I begin by defining a adverse case to
guarantee we don’t unintentionally change issues we wish to go away 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 known as inside an if assertion), implement that case, and
guarantee all assessments cross.

This strategy aligns nicely with Take a look at-Pushed Improvement (TDD), even
in the event you don’t apply TDD recurrently. Understanding precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

With jscodeshift, you may write assessments 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 operate from jscodeshift lets you outline
the enter, anticipated output, and a string describing the check’s intent.
Now, working the check with a standard jest command will fail as a result of the
codemod isn’t written but.

The corresponding adverse case would make sure the code stays unchanged
for different characteristic 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 characteristic toggles"
);

Writing the Codemod

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

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

  // manipulate the tree nodes right here

  return root.toSource();
};

This operate 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 will begin implementing the remodel steps:

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

Right here’s how we obtain this utilizing jscodeshift:

module.exports = operate (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 all the 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 may check it out on a goal codebase,
such because the one you are engaged on. jscodeshift supplies a command-line
device that you should utilize to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, examine that each one purposeful assessments nonetheless
cross and that nothing breaks—even in the event you’re introducing a breaking change.
As soon as happy, you may commit the modifications 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 modifications—they’ll
considerably enhance code high quality and maintainability. As codebases
evolve, they typically accumulate technical debt, together with outdated characteristic
toggles, deprecated strategies, or tightly coupled parts. Manually
refactoring these areas will 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 lets you
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 advanced instance. Suppose you’re working with
a design system that features an Avatar part tightly coupled with a
Tooltip. At any time when a person passes a identify prop into the Avatar, it
routinely wraps the avatar with a tooltip.

Determine 3: A avatar part 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 part,
giving builders extra flexibility. Builders ought to be capable to 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 tons of of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion can be extremely
inefficient, so we will use a codemod to automate this course of.

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

Determine 4: AST of the Avatar part utilization

Writing the Codemod

Let’s break down the transformation into smaller duties:

• Discover Avatar utilization within the part 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 cases of Avatar (I’ll omit among the
assessments, however it’s best to write comparability assessments 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 will use root.discover with
search standards to find all Avatar nodes:

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

Subsequent, we examine 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 operate, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip and the Avatar
part as a baby. Lastly, we name replaceWith to
change the present path.

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

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

This codemod searches for all cases 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 modifications the place
guide updates can be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we will handle these less-than-ideal points.

Leveraging Supply Graphs and Take a look at-Pushed Codemods

To deal with these complexities, codemods must be used alongside different
strategies. For example, just a few years in the past, I participated in a design
system parts rewrite venture at Atlassian. We addressed this problem by
first looking out the supply graph, which contained nearly all of inside
part utilization. This allowed us to grasp how parts have been used,
whether or not they have been imported beneath completely different names, or whether or not sure
public props have been ceaselessly used. After this search part, 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 working the script to deal with particular circumstances manually. Often,
there have been solely a handful of such cases, so this strategy nonetheless proved
useful for upgrading variations.

Using Current Code Standardization Instruments

As you may see, there are many edge circumstances to deal with, particularly in
codebases past your management—comparable to exterior dependencies. This
complexity signifies that utilizing codemods requires cautious supervision and a
evaluation of the outcomes.

Nevertheless, in case your codebase has standardization instruments in place, comparable to a
linter that enforces a selected coding model, you may leverage these
instruments to cut back edge circumstances. By implementing a constant construction, instruments
like linters assist slender down the variations in code, making the
transformation simpler and minimizing sudden points.

For example, you might use linting guidelines to limit sure patterns,
comparable 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 advanced transformations into smaller, extra
manageable ones lets you sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with advanced
modifications extra possible.

Codemod Composition

Let’s revisit the characteristic toggle removing instance mentioned earlier. Within the code snippet
we now have a toggle known 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 outcome = featureToggle("feature-convert-new")
  ? convertNew("Hi there, world")
  : convertOld("Hi there, world");

console.log(outcome);

The codemod for take away a given toggle works advantageous, and after working the codemod,
we would like the supply to appear like this:

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

const outcome = convertNew("Hi there, world");

console.log(outcome);

Nevertheless, past eradicating the characteristic toggle logic, there are extra duties to
deal with:

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

After all, you might write one massive codemod to deal with all the pieces in a
single cross and check it collectively. Nevertheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—identical to how you’ll 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 strategy is that every transformation
will be examined individually, masking completely different circumstances with out interference.
Furthermore, it lets you reuse and compose them for various
functions.

For example, you may break it down like this:

• A change to take away a selected characteristic toggle.
• One other transformation to scrub up unused imports.
• A change to take away unused operate declarations.

By composing these, you may 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 operate because it’s not used.

Determine 6: Compose transforms into a brand new remodel

You can even extract extra codemods as wanted, combining them in
varied orders relying on the specified final result.

Determine 7: Put completely different transforms right into a pipepline to kind one other remodel

The createTransformer Operate

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

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

kind 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 might have a remodel operate that inlines
expressions assigning the characteristic 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 group of reusable, smaller
transforms, which may tremendously ease the method of dealing with difficult edge
circumstances. This strategy proved extremely efficient in our work refining design
system parts. As soon as we transformed one package deal—such because the button
part—we had just a few reusable transforms outlined, like including feedback
initially of features, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms will be examined and used independently
or mixed for extra advanced transformations, which accelerates subsequent
conversions considerably. In consequence, our refinement work grew to become extra
environment friendly, and these generic codemods are actually relevant to different inside
and even exterior React codebases.

Since every remodel is comparatively standalone, you may fine-tune them
with out affecting different transforms or the extra advanced, 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.