Refactoring with Codemods to Automate API Modifications

Clear a Stale Function Toggle

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

As an illustration, think about the next code:

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

As soon as the characteristic is totally launched and now not wants a toggle, this
may be simplified to:

const information = { identify: 'Product' };

The duty includes 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 adjustments selectively.

Understanding the AST

Earlier than we dive into writing the codemod, let’s break down how this
particular code snippet seems to be in an AST. You need to use 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 adjustments.

The picture under reveals the syntax tree when it comes to 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 verify

On this AST illustration, the variable information 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 information. If
false, the alternate department assigns undefined.

For a activity with clear enter and output, I desire writing exams first,
then implementing the codemod. I begin by defining a detrimental case to
guarantee we don’t by accident change issues we wish 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 known as inside an if assertion), implement that case, and
guarantee all exams go.

This strategy aligns effectively with Take a look at-Pushed Improvement (TDD), even
in the event you don’t observe TDD repeatedly. Realizing 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 rework = require("../remove-feature-new-product-list");

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

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

The corresponding detrimental case would make sure the code stays unchanged
for different characteristic toggles:

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

Writing the Codemod

Let’s begin by defining a easy rework perform. Create a file
referred to as rework.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 will begin implementing the rework steps:

1. Discover all cases of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Exchange the whole 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 the whole conditional expression with the resultant (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
handbook effort.

You’ll want to jot down extra check instances 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 gives a command-line
device that you should use to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, verify that every one useful exams nonetheless
go and that nothing breaks—even in the event you’re introducing a breaking change.
As soon as happy, 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’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 elements. Manually
refactoring these areas may be time-consuming and error-prone.

By automating refactoring duties, codemods assist hold your codebase clear
and freed from legacy patterns. Often making use of codemods permits you to
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 have a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar part tightly coupled with a
Tooltip. Each time a consumer 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 (
      
        
      
    );
  }

  return ;
};

The aim is to decouple the Tooltip from the Avatar part,
giving builders extra flexibility. Builders ought to have the ability to resolve
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 ;
};

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 (
    
      
    
  );
};

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 characterize 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 a number of the
exams, however you must write comparability exams first).

defineInlineTest(
    { default: rework, parser: "tsx" },
    {},
    `
    
    `,
    `
    
      
    
    `,
    "wrap avatar with tooltip when identify is offered"
  );

Just 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 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
part as a baby. Lastly, we name replaceWith to
exchange the present path.

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

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 adjustments the place
handbook updates can be an enormous burden. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear a number of the challenges
and the way we will handle these less-than-ideal features.

Leveraging Supply Graphs and Take a look at-Pushed Codemods

To deal with these complexities, codemods must be used alongside different
strategies. As an illustration, a number of years in the past, I participated in a design
system elements rewrite mission at Atlassian. We addressed this situation by
first looking the supply graph, which contained the vast majority of inside
part utilization. This allowed us to grasp how elements have been used,
whether or not they have been imported beneath totally different names, or whether or not sure
public props have been continuously used. After this search part, we wrote our
check instances upfront, making certain we lined the vast majority of use instances, 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 instances manually. Normally,
there have been solely a handful of such cases, so this strategy nonetheless proved
helpful for upgrading variations.

Using Present Code Standardization Instruments

As you possibly can see, there are many edge instances 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.

Nonetheless, in case your codebase has standardization instruments in place, comparable to a
linter that enforces a specific coding model, you possibly can leverage these
instruments to scale back edge instances. By imposing a constant construction, instruments
like linters assist slim down the variations in code, making the
transformation simpler and minimizing surprising points.

As an illustration, you can use linting guidelines to limit sure patterns,
comparable to avoiding nested conditional (ternary) operators or imposing 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 permits you to 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 characteristic toggle removing instance mentioned earlier. Within the code snippet
we’ve got a toggle referred to as feature-convert-new must 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("Hi there, world")
  : convertOld("Hi there, world");

console.log(consequence);

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

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

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

console.log(consequence);

Nonetheless, past eradicating the characteristic toggle logic, there are further duties to
deal with:

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

In fact, you can write one huge codemod to deal with all the things in a
single go and check it collectively. Nonetheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
unbiased items—similar to how you’ll usually refactor manufacturing
code.

Breaking It Down

We will break the large transformation down into smaller codemods and
compose them. The benefit of this strategy is that every transformation
may be examined individually, overlaying totally different instances with out interference.
Furthermore, it permits you to reuse and compose them for various
functions.

As an illustration, you would possibly 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 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 rework = createTransformer([
  removeFeatureConvertNew,
  removeUnusedImport,
  removeUnusedFunction,
]);

export default rework;

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 now not used.

Determine 6: Compose transforms into a brand new rework

You may also extract further codemods as wanted, combining them in
numerous orders relying on the specified end result.

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

The createTransformer Operate

The implementation of the createTransformer perform is comparatively
simple. It acts as a higher-order perform that takes an inventory of
smaller rework features, iterates by way of the record to use them to
the basis AST, and eventually 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((rework) => rework(j, root));
    return root.toSource(choices.printOptions || { quote: "single" });
  };

export { createTransformer };

For instance, you can have a rework perform that inlines
expressions assigning the characteristic toggle name to a variable, so in later
transforms you don’t have to fret about these instances anymore:

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

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

Turns into this:

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

Over time, you would possibly construct up a set of reusable, smaller
transforms, which may enormously ease the method of dealing with tough edge
instances. This strategy proved extremely efficient in our work refining design
system elements. As soon as we transformed one bundle—such because the button
part—we had a number of 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 may 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 inside
and even exterior React codebases.

Since every rework is comparatively standalone, you possibly can fine-tune them
with out affecting different transforms or the extra complicated, composed ones. For
occasion, you would possibly re-implement a rework 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.