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 manage the discharge of unfinished or experimental options.
As soon as the characteristic is reside in manufacturing and dealing as anticipated, the subsequent
logical step is to scrub up the toggle and any associated logic.

As an illustration, take into account the next code:

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

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

const information = { 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 growth)
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 should utilize instruments like AST
Explorer to visualise how supply code and AST
are mapped. It’s useful to grasp the node varieties 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
incorporates 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 test

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

For a process with clear enter and output, I desire writing assessments first,
then implementing the codemod. I begin by defining a adverse case to
guarantee we don’t by chance 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 known as inside an if assertion), implement that case, and
guarantee all assessments move.

This strategy aligns properly with Check-Pushed Improvement (TDD), even
in the event you don’t observe TDD often. 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 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 means that you can outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, working the take a look at 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 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 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 cases of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Exchange your complete 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 take a look at is featureToggle('feature-new-product-list')   root     .discover(j.ConditionalExpression, {       take a look at: {         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 take a look at calls
  featureToggle('feature-new-product-list').
• Replaces your complete 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 decreasing
handbook effort.

You’ll want to put in writing extra take a look at 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 strong in real-world eventualities.

As soon as the codemod is prepared, you may try it out on a goal codebase,
such because the one you are engaged on. jscodeshift gives 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, test that every one purposeful assessments nonetheless
move and that nothing breaks—even in the event you’re introducing a breaking change.
As soon as happy, you may 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 usually accumulate technical debt, together with outdated characteristic
toggles, deprecated strategies, or tightly coupled elements. Manually
refactoring these areas could 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 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 Element

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. Every time 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 (                            );   }   return ; }; 

The purpose 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 are able to use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we are able to
examine the part and see which nodes symbolize the Avatar utilization
we’re focusing 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 few of the
assessments, however it’s best to write comparability assessments first).

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

Just 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 test 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 appropriate is the unique code, and the underside
half is the remodeled end result:

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 few of the challenges
and the way we are able to handle these less-than-ideal facets.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods must be used alongside different
methods. As an illustration, a number of years in the past, I participated in a design
system elements rewrite venture at Atlassian. We addressed this concern by
first looking out the supply graph, which contained nearly all of inner
part utilization. This allowed us to grasp how elements have been used,
whether or not they have been imported below totally different names, or whether or not sure
public props have been incessantly used. After this search section, we wrote our
take a look at 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. Normally,
there have been solely a handful of such cases, so this strategy nonetheless proved
helpful 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—similar to exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
evaluation of the outcomes.

Nonetheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a specific coding model, you may leverage these
instruments to cut back edge circumstances. By implementing 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 may 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 advanced transformations into smaller, extra
manageable ones means that you can deal with particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with advanced
adjustments extra possible.

Codemod Composition

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

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

const convertNew = (enter: string) => {   return enter.toUpperCase(); }; const end result = convertNew("Hi there, world"); console.log(end result); 

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

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

In fact, you may write one huge codemod to deal with every thing in a
single move and take a look at it collectively. Nonetheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—identical to how you’d 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
could be examined individually, protecting totally different circumstances with out interference.
Furthermore, it means that you can reuse and compose them for various
functions.

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

• A metamorphosis to take away a particular characteristic toggle.
• One other transformation to scrub up unused imports.
• A metamorphosis to take away unused perform 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 perform because it’s not used.

Determine 6: Compose transforms into a brand new remodel

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

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

The createTransformer Perform

The implementation of the createTransformer perform is comparatively
simple. It acts as a higher-order perform that takes a listing of
smaller remodel features, iterates via the listing to use them to
the basis AST, and at last 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 may have a remodel perform 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 might drastically ease the method of dealing with tough edge
circumstances. This strategy proved extremely efficient in our work refining design
system elements. As soon as we transformed one package deal—such because the button
part—we had a number of reusable transforms outlined, like including feedback
at first of features, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms could be examined and used independently
or mixed for extra advanced transformations, which quickens subsequent
conversions considerably. Consequently, our refinement work turned 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 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
decreasing the variety of node-finding rounds—and with complete take a look at
protection, you are able to do this confidently and safely.