As a library developer, you might create a well-liked utility that tons of of
1000’s of builders depend on every day, reminiscent of lodash or React. Over time,
utilization patterns may emerge that transcend your preliminary design. When this
occurs, you might want to increase an API by including parameters or modifying
perform signatures to repair edge circumstances. The problem lies in rolling out
these breaking adjustments with out disrupting your customers’ workflows.
That is the place codemods are available in—a robust software for automating
large-scale code transformations, permitting builders to introduce breaking
API adjustments, refactor legacy codebases, and preserve code hygiene with
minimal guide effort.
On this article, we’ll discover what codemods are and the instruments you possibly can
use to create them, reminiscent of jscodeshift, hypermod.io, and codemod.com. We’ll stroll via real-world examples,
from cleansing up characteristic toggles to refactoring part hierarchies.
You’ll additionally discover ways to break down complicated transformations into smaller,
testable items—a observe referred to as codemod composition—to make sure
flexibility and maintainability.
By the top, you’ll see how codemods can turn out to be a significant a part of your
toolkit for managing large-scale codebases, serving to you retain your code clear
and maintainable whereas dealing with even probably the most difficult refactoring
duties.
Breaking Adjustments in APIs
Returning to the state of affairs of the library developer, after the preliminary
launch, new utilization patterns emerge, prompting the necessity to lengthen an
API—maybe by including a parameter or modifying a perform signature to
make it simpler to make use of.
For easy adjustments, a fundamental find-and-replace within the IDE may work. In
extra complicated circumstances, you may resort to utilizing instruments like sed
or awk
. Nonetheless, when your library is extensively adopted, the
scope of such adjustments turns into more durable to handle. You may’t be certain how
extensively the modification will affect your customers, and the very last thing
you need is to interrupt current performance that doesn’t want
updating.
A typical strategy is to announce the breaking change, launch a brand new
model, and ask customers emigrate at their very own tempo. However this workflow,
whereas acquainted, usually would not scale nicely, particularly for main shifts.
Take into account React’s transition from class elements to perform elements
with hooks—a paradigm shift that took years for giant codebases to totally
undertake. By the point groups managed emigrate, extra breaking adjustments had been
usually already on the horizon.
For library builders, this example creates a burden. Sustaining
a number of older variations to help customers who haven’t migrated is each
pricey and time-consuming. For customers, frequent adjustments threat eroding belief.
They could hesitate to improve or begin exploring extra steady alternate options,
which perpetuating the cycle.
However what should you may assist customers handle these adjustments robotically?
What should you may launch a software alongside your replace that refactors
their code for them—renaming capabilities, updating parameter order, and
eradicating unused code with out requiring guide intervention?
That’s the place codemods are available in. A number of libraries, together with React
and Subsequent.js, have already embraced codemods to easy the trail for model
bumps. For instance, React offers codemods to deal with the migration from
older API patterns, just like the outdated Context API, to newer ones.
So, what precisely is the codemod we’re speaking about right here?
What’s a Codemod?
A codemod (code modification) is an automatic script used to remodel
code to observe new APIs, syntax, or coding requirements. Codemods use
Summary Syntax Tree (AST) manipulation to use constant, large-scale
adjustments throughout codebases. Initially developed at Fb, codemods helped
engineers handle refactoring duties for giant initiatives like React. As
Fb scaled, sustaining the codebase and updating APIs grew to become
more and more tough, prompting the event of codemods.
Manually updating 1000’s of recordsdata throughout completely different repositories was
inefficient and error-prone, so the idea of codemods—automated scripts
that rework code—was launched to deal with this drawback.
The method sometimes entails three predominant steps:
- Parsing the code into an AST, the place every a part of the code is
represented as a tree construction. - Modifying the tree by making use of a metamorphosis, reminiscent of renaming a
perform or altering parameters. - Rewriting the modified tree again into the supply code.
Through the use of this strategy, codemods be sure that adjustments are utilized
persistently throughout each file in a codebase, lowering the possibility of human
error. Codemods also can deal with complicated refactoring situations, reminiscent of
adjustments to deeply nested buildings or eradicating deprecated API utilization.
If we visualize the method, it could look one thing like this:

Determine 1: The three steps of a typical codemod course of
The concept of a program that may “perceive” your code after which carry out
computerized transformations isn’t new. That’s how your IDE works while you
run refactorings like
Primarily, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the consequence again into your
recordsdata.
For contemporary IDEs, many issues occur below the hood to make sure adjustments
are utilized accurately and effectively, reminiscent of figuring out the scope of
the change and resolving conflicts like variable title collisions. Some
refactorings even immediate you to enter parameters, reminiscent of when utilizing
order of parameters or default values earlier than finalizing the change.
Use jscodeshift in JavaScript Codebases
Let’s have a look at a concrete instance to know how we may run a
codemod in a JavaScript venture. The JavaScript group has a number of
instruments that make this work possible, together with parsers that convert supply
code into an AST, in addition to transpilers that may rework the tree into
different codecs (that is how TypeScript works). Moreover, there are
instruments that assist apply codemods to whole repositories robotically.
Probably the most standard instruments for writing codemods is jscodeshift, a toolkit maintained by Fb.
It simplifies the creation of codemods by offering a robust API to
manipulate ASTs. With jscodeshift, builders can seek for particular
patterns within the code and apply transformations at scale.
You should utilize jscodeshift
to establish and exchange deprecated API calls
with up to date variations throughout a complete venture.
Let’s break down a typical workflow for composing a codemod
manually.
Clear a Stale Characteristic 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 wash up the toggle and any associated logic.
As an illustration, take into account the next code:
const knowledge = featureToggle('feature-new-product-list') ? { title: 'Product' } : undefined;
As soon as the characteristic is totally launched and not wants a toggle, this
might be simplified to:
const knowledge = { title: '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 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 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 varieties 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 title), 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 knowledge
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 { title: 'Product' }
to knowledge
. If
false
, the alternate department assigns undefined
.
For a job with clear enter and output, I choose writing assessments first,
then implementing the codemod. I begin by defining a unfavourable case to
guarantee we don’t by accident change issues we wish to go away untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy state of affairs, implement it, then add a variation (like checking if
featureToggle is known as inside an if assertion), implement that case, and
guarantee all assessments go.
This strategy aligns nicely with Take a look at-Pushed Growth (TDD), even
should you don’t observe TDD commonly. Understanding 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 assessments to confirm how the codemod
behaves:
const rework = require("../remove-feature-new-product-list"); defineInlineTest( rework, {}, ` const knowledge = featureToggle('feature-new-product-list') ? { title: 'Product' } : undefined; `, ` const knowledge = { title: '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 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 unfavourable case would make sure the code stays unchanged
for different characteristic toggles:
defineInlineTest( rework, {}, ` const knowledge = featureToggle('feature-search-result-refinement') ? { title: 'Product' } : undefined; `, ` const knowledge = featureToggle('feature-search-result-refinement') ? { title: 'Product' } : undefined; `, "don't change different characteristic toggles" );
Writing the Codemod
Let’s begin by defining a easy rework perform. Create a file
known 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:
- Discover all situations of
featureToggle
. - Confirm that the argument handed is
'feature-new-product-list'
. - Substitute 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 take a look at is featureToggle('feature-new-product-list') root .discover(j.ConditionalExpression, { take a look at: { callee: { title: "featureToggle" }, arguments: [{ value: "feature-new-product-list" }], }, }) .forEach((path) => { // Substitute 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 the whole conditional expression with the ensuing (i.e.,
{
), eradicating the toggle logic and leaving simplified code
title: 'Product' }
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 jot down 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 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 offers a command-line
software that you should utilize to use the codemod and report the outcomes.
$ jscodeshift -t transform-name src/
After validating the outcomes, verify that each one practical assessments nonetheless
go and that nothing breaks—even should 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’ll
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 might be time-consuming and error-prone.
By automating refactoring duties, codemods assist preserve your codebase clear
and freed from legacy patterns. Repeatedly 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
. Every time a person passes a title
prop into the Avatar
, it
robotically 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 = ({ title, picture }: AvatarProps) => { if (title) { return ( <Tooltip content material={title}> <CircleImage picture={picture} /> </Tooltip> ); } return <CircleImage picture={picture} />; };
The purpose 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 characterize the Avatar
utilization
we’re concentrating on. An Avatar
part with each title
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
title
prop is current. - If not, do nothing.
- If current:
- Create a
Tooltip
node. - Add the
title
to theTooltip
. - Take away the
title
fromAvatar
. - Add
Avatar
as a baby of theTooltip
. - Substitute the unique
Avatar
node with the brand newTooltip
.
To start, we’ll discover all situations of Avatar (I’ll omit a few of the
assessments, however it is best to write comparability assessments first).
defineInlineTest(
{ default: rework, parser: "tsx" },
{},
`
<Avatar title="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
`,
`
<Tooltip content material="Juntao Qiu">
<Avatar picture="/juntao.qiu.avatar.png" />
</Tooltip>
`,
"wrap avatar with tooltip when title 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: { title: { title: "Avatar" } }, }) .forEach((path) => { // now we will deal with every Avatar occasion });
Subsequent, we verify if the title
prop is current:
root
.discover(j.JSXElement, {
openingElement: { title: { title: "Avatar" } },
})
.forEach((path) => {
const avatarNode = path.node;
const nameAttr = avatarNode.openingElement.attributes.discover(
(attr) => attr.title.title === "title"
);
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 title
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 appears to be like 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 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
title
prop is discovered, it removes the title
prop
from Avatar
, wraps the Avatar
inside a
Tooltip
, and passes the title
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 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 will deal with these less-than-ideal points.
Fixing Widespread Pitfalls of Codemods
As a seasoned developer, you recognize the “comfortable path” is simply a small half
of the complete image. There are quite a few situations to contemplate when writing
a metamorphosis script to deal with code robotically.
Builders write code in quite a lot of types. For instance, somebody
may import the Avatar
part however give it a special title as a result of
they may have one other Avatar
part from a special bundle:
import { Avatar as AKAvatar } from "@design-system/avatar"; const UserInfo = () => ( <AKAvatar title="Juntao Qiu" picture="/juntao.qiu.avatar.png" /> );
A easy textual content seek for Avatar
received’t work on this case. You’ll want
to detect the alias and apply the transformation utilizing the right
title.
One other instance arises when coping with Tooltip
imports. If the file
already imports Tooltip
however makes use of an alias, the codemod should detect that
alias and apply the adjustments accordingly. You may’t assume that the
part named Tooltip
is all the time the one you’re on the lookout for.
Within the characteristic toggle instance, somebody may use
if(featureToggle('feature-new-product-list'))
, or assign the results of
the toggle perform to a variable earlier than utilizing it:
const shouldEnableNewFeature = featureToggle('feature-new-product-list'); if (shouldEnableNewFeature) { //... }
They could even use the toggle with different situations or apply logical
negation, making the logic extra complicated:
const shouldEnableNewFeature = featureToggle('feature-new-product-list'); if (!shouldEnableNewFeature && someOtherLogic) { //... }
These variations make it tough to foresee each edge case,
rising the danger of unintentionally breaking one thing. Relying solely
on the circumstances you possibly can anticipate just isn’t sufficient. You want thorough testing
to keep away from breaking unintended components of the code.
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, just a few years in the past, I participated in a design
system elements rewrite venture at Atlassian. We addressed this problem by
first looking the supply graph, which contained the vast majority of inner
part utilization. This allowed us to know how elements had been used,
whether or not they had been imported below completely different names, or whether or not sure
public props had been regularly used. After this search part, we wrote our
take a look at circumstances upfront, making certain we lined the vast majority 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 situations, so this strategy nonetheless proved
helpful for upgrading variations.
Using Present Code Standardization Instruments
As you possibly can see, there are many edge circumstances to deal with, particularly in
codebases past your management—reminiscent of exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
assessment of the outcomes.
Nonetheless, in case your codebase has standardization instruments in place, reminiscent of a
linter that enforces a specific coding model, you possibly can leverage these
instruments to scale back edge circumstances. 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 may use linting guidelines to limit sure patterns,
reminiscent of 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 deal with 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 elimination instance mentioned earlier. Within the code snippet
we now have a toggle known as feature-convert-new
should 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 superb, 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.
After all, you may write one massive codemod to deal with every little thing in a
single go 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—similar 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
might be examined individually, protecting completely different circumstances with out interference.
Furthermore, it permits you to 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 wash 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 rework = createTransformer([ removeFeatureConvertNew, removeUnusedImport, removeUnusedFunction, ]); export default rework;
On this pipeline, the transformations work as follows:
- Take away the
feature-convert-new
toggle. - Clear up the unused
import
assertion. - Take away the
convertOld
perform because it’s not used.

Determine 6: Compose transforms into a brand new rework
You may also extract further codemods as wanted, combining them in
varied orders relying on the specified consequence.

Determine 7: Put completely 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 capabilities, iterates via 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((rework) => rework(j, root)); return root.toSource(choices.printOptions || { quote: "single" }); }; export { createTransformer };
For instance, you may 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 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 tough edge
circumstances. 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 just a few reusable transforms outlined, like including feedback
in the beginning of capabilities, 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 hurries up subsequent
conversions considerably. Because of this, 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 rework 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 rework to enhance efficiency—like
lowering the variety of node-finding rounds—and with complete take a look at
protection, you are able to do this confidently and safely.