As a library developer, it’s possible you’ll create a well-liked utility that tons of of
1000’s of builders depend on each day, corresponding to lodash or React. Over time,
utilization patterns may emerge that transcend your preliminary design. When this
occurs, it’s possible you’ll want to increase an API by including parameters or modifying
operate signatures to repair edge instances. The problem lies in rolling out
these breaking adjustments with out disrupting your customers’ workflows.
That is the place codemods are available—a strong instrument for automating
large-scale code transformations, permitting builders to introduce breaking
API adjustments, refactor legacy codebases, and keep code hygiene with
minimal handbook effort.
On this article, we’ll discover what codemods are and the instruments you may
use to create them, corresponding to jscodeshift, hypermod.io, and codemod.com. We’ll stroll via real-world examples,
from cleansing up function toggles to refactoring part hierarchies.
You’ll additionally discover ways to break down advanced transformations into smaller,
testable items—a follow often called codemod composition—to make sure
flexibility and maintainability.
By the tip, you’ll see how codemods can turn into an important a part of your
toolkit for managing large-scale codebases, serving to you retain your code clear
and maintainable whereas dealing with even essentially 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 operate signature to
make it simpler to make use of.
For easy adjustments, a fundamental find-and-replace within the IDE may work. In
extra advanced instances, you may resort to utilizing instruments like sed
or awk
. Nonetheless, when your library is broadly adopted, the
scope of such adjustments turns into tougher to handle. You possibly can’t ensure how
extensively the modification will influence your customers, and the very last thing
you need is to interrupt present performance that doesn’t want
updating.
A standard 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 properly, particularly for main shifts.
Take into account React’s transition from class parts to operate parts
with hooks—a paradigm shift that took years for big codebases to completely
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
expensive and time-consuming. For customers, frequent adjustments threat eroding belief.
They could hesitate to improve or begin exploring extra secure alternate options,
which perpetuating the cycle.
However what in the event you may assist customers handle these adjustments routinely?
What in the event you may launch a instrument alongside your replace that refactors
their code for them—renaming features, updating parameter order, and
eradicating unused code with out requiring handbook intervention?
That’s the place codemods are available. 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 rework
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 big tasks 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 information 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 downside.
The method sometimes entails three most important 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, corresponding to renaming a
operate or altering parameters. - Rewriting the modified tree again into the supply code.
By utilizing this strategy, codemods be certain that adjustments are utilized
constantly throughout each file in a codebase, decreasing the prospect of human
error. Codemods may also deal with advanced refactoring situations, corresponding to
adjustments to deeply nested constructions or eradicating deprecated API utilization.
If we visualize the method, it might look one thing like this:
Determine 1: The three steps of a typical codemod course of
The thought of a program that may “perceive” your code after which carry out
computerized transformations isn’t new. That’s how your IDE works once you
run refactorings like
Basically, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the outcome again into your
information.
For contemporary IDEs, many issues occur below the hood to make sure adjustments
are utilized appropriately and effectively, corresponding to figuring out the scope of
the change and resolving conflicts like variable title collisions. Some
refactorings even immediate you to enter parameters, corresponding to 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 undertaking. The JavaScript neighborhood 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 total repositories routinely.
One of the vital widespread instruments for writing codemods is jscodeshift, a toolkit maintained by Fb.
It simplifies the creation of codemods by offering a strong API to
manipulate ASTs. With jscodeshift, builders can seek for particular
patterns within the code and apply transformations at scale.
You need to use jscodeshift
to establish and change deprecated API calls
with up to date variations throughout a whole undertaking.
Let’s break down a typical workflow for composing a codemod
manually.
Clear a Stale Function Toggle
Let’s begin with a easy but sensible instance to show the
energy of codemods. Think about you’re utilizing a function
toggle in your
codebase to manage the discharge of unfinished or experimental options.
As soon as the function is dwell 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 knowledge = featureToggle('feature-new-product-list') ? title: 'Product' : undefined;
As soon as the function is absolutely launched and now not wants a toggle, this
may be simplified to:
const knowledge = title: '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 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 in an AST. You need to use 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 beneath reveals the syntax tree by way of ECMAScript syntax. It
comprises 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 function toggle test
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 activity with clear enter and output, I desire writing checks first,
then implementing the codemod. I begin by defining a unfavourable case to
guarantee we don’t by chance change issues we need 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 known as inside an if assertion), implement that case, and
guarantee all checks go.
This strategy aligns properly with Check-Pushed Improvement (TDD), even
in the event you don’t follow TDD commonly. 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 may write checks 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
operate 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 traditional 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 function 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 function toggles" );
Writing the Codemod
Let’s begin by defining a easy rework operate. Create a file
known as rework.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 are able to begin implementing the rework steps:
- Discover all cases of
featureToggle
. - Confirm that the argument handed is
'feature-new-product-list'
. - Change the whole 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 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) => // Change 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 resultant (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 decreasing
handbook effort.
You’ll want to jot down extra take a look at 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 may check it out on a goal codebase,
such because the one you are engaged on. jscodeshift offers a command-line
instrument that you should utilize to use the codemod and report the outcomes.
$ jscodeshift -t transform-name src/
After validating the outcomes, test that every one useful checks nonetheless
go 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’ll
considerably enhance code high quality and maintainability. As codebases
evolve, they usually accumulate technical debt, together with outdated function
toggles, deprecated strategies, or tightly coupled parts. 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. Commonly 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 have 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
. Each time a consumer passes a title
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 = ( 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 have the ability 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 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 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 beneath:

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. - Examine 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 toddler of theTooltip
. - Change the unique
Avatar
node with the brand newTooltip
.
To start, we’ll discover all cases of Avatar (I’ll omit among the
checks, however it’s best to write comparability checks 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 are able to use root.discover
with
search standards to find all Avatar nodes:
root .discover(j.JSXElement, openingElement: title: title: "Avatar" , ) .forEach((path) => // now we are able to deal with every Avatar occasion );
Subsequent, we test 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
operate, 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 toddler. 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 appropriate 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
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
handbook updates can be an enormous burden. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we are able to deal with these less-than-ideal points.
Fixing Frequent Pitfalls of Codemods
As a seasoned developer, you realize the “completely happy path” is just a small half
of the complete image. There are quite a few situations to contemplate when writing
a metamorphosis script to deal with code routinely.
Builders write code in quite a lot of kinds. For instance, somebody
may import the Avatar
part however give it a distinct title as a result of
they may have one other Avatar
part from a distinct package deal:
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
gained’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 possibly can’t assume that the
part named Tooltip
is at all times the one you’re on the lookout for.
Within the feature toggle example, somebody may use
if(featureToggle('feature-new-product-list'))
, or assign the results of
the toggle operate to a variable earlier than utilizing it:
const shouldEnableNewFeature = featureToggle('feature-new-product-list'); if (shouldEnableNewFeature) //...
They may even use the toggle with different circumstances or apply logical
negation, making the logic extra advanced:
const shouldEnableNewFeature = featureToggle('feature-new-product-list'); if (!shouldEnableNewFeature && someOtherLogic) //...
These variations make it tough to foresee each edge case,
growing the chance of unintentionally breaking one thing. Relying solely
on the instances you may anticipate is just not sufficient. You want thorough testing
to keep away from breaking unintended components of the code.
Leveraging Supply Graphs and Check-Pushed Codemods
To deal with these complexities, codemods ought to be used alongside different
methods. As an illustration, just a few years in the past, I participated in a design
system parts rewrite undertaking at Atlassian. We addressed this subject by
first looking the supply graph, which contained the vast majority of inside
part utilization. This allowed us to know how parts had been used,
whether or not they had been imported below completely different names, or whether or not sure
public props had been continuously used. After this search section, we wrote our
take a look at instances upfront, guaranteeing we coated 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
useful for upgrading variations.
Using Current Code Standardization Instruments
As you may see, there are many edge instances to deal with, particularly in
codebases past your management—corresponding 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, corresponding to a
linter that enforces a selected coding model, you may leverage these
instruments to cut back edge instances. 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 possibly can use linting guidelines to limit sure patterns,
corresponding 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 function toggle removing instance mentioned earlier. Within the code snippet
we now have a toggle known 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 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 high quality, and after working the codemod,
we wish the supply to appear to be this:
const convertNew = (enter: string) => return enter.toUpperCase(); ; const outcome = convertNew("Hi there, world"); console.log(outcome);
Nonetheless, past eradicating the function toggle logic, there are further duties to
deal with:
- Take away the unused
convertOld
operate. - Clear up the unused
featureToggle
import.
After all, you possibly can write one huge codemod to deal with every 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—identical to how you’ll usually refactor manufacturing
code.
Breaking It Down
We are able to break the massive transformation down into smaller codemods and
compose them. The benefit of this strategy is that every transformation
may be examined individually, protecting completely different instances 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 function toggle.
- One other transformation to scrub up unused imports.
- A metamorphosis 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 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
operate because it’s now not used.

Determine 6: Compose transforms into a brand new rework
You can even 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
Perform
The implementation of the createTransformer
operate is comparatively
easy. It acts as a higher-order operate that takes a listing of
smaller rework 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"; sort TransformFunction = (j: JSCodeshift, root: Assortment): void ; const createTransformer = (transforms: TransformFunction[]) => (fileInfo: FileInfo, api: API, choices: Choices) => quote: "single" ); ; export createTransformer ;
For instance, you possibly can have a rework operate that inlines
expressions assigning the function 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 may construct up a group of reusable, smaller
transforms, which might tremendously ease the method of dealing with difficult edge
instances. 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
in the beginning of features, eradicating deprecated props, or creating aliases
when a package deal is already imported above.
Every of those smaller transforms may be examined and used independently
or mixed for extra advanced transformations, which hastens 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 inside
and even exterior React codebases.
Since every rework 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 rework 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.