As a library developer, it’s possible you’ll create a well-liked utility that lots of of
1000’s of builders depend on each day, similar 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 robust instrument for automating
large-scale code transformations, permitting builders to introduce breaking
API adjustments, refactor legacy codebases, and keep code hygiene with
minimal guide effort.
On this article, we’ll discover what codemods are and the instruments you’ll be able to
use to create them, similar to jscodeshift, hypermod.io, and codemod.com. We’ll stroll by real-world examples,
from cleansing up characteristic toggles to refactoring element hierarchies.
You’ll additionally discover ways to break down complicated transformations into smaller,
testable items—a follow often known as codemod composition—to make sure
flexibility and maintainability.
By the top, you’ll see how codemods can grow 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 essentially the most difficult refactoring
duties.
Breaking Modifications in APIs
Returning to the situation 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 complicated instances, you may resort to utilizing instruments like sed
or awk
. Nevertheless, when your library is broadly adopted, the
scope of such adjustments turns into more durable to handle. You possibly can’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 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, typically does not scale properly, particularly for main shifts.
Think about 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
typically already on the horizon.
For library builders, this case creates a burden. Sustaining
a number of older variations to assist customers who haven’t migrated is each
pricey and time-consuming. For customers, frequent adjustments danger eroding belief.
They might hesitate to improve or begin exploring extra secure alternate options,
which perpetuating the cycle.
However what in case you might assist customers handle these adjustments mechanically?
What in case you might launch a instrument 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. A number of libraries, together with React
and Subsequent.js, have already embraced codemods to easy the trail for model
bumps. For instance, React supplies codemods to deal with the migration from
older API patterns, just like the previous 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 comply with 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 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 remodel code—was launched to sort out this downside.
The method usually includes 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 change, similar to renaming a
operate 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, decreasing the prospect of human
error. Codemods also can deal with complicated refactoring situations, similar to
adjustments to deeply nested constructions or eradicating deprecated API utilization.
If we visualize the method, it will 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 if you
run refactorings like
Primarily, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the outcome again into your
recordsdata.
For contemporary IDEs, many issues occur beneath the hood to make sure adjustments
are utilized accurately and effectively, similar to figuring out the scope of
the change and resolving conflicts like variable identify collisions. Some
refactorings even immediate you to enter parameters, similar to when utilizing
order of parameters or default values earlier than finalizing the change.
Use jscodeshift in JavaScript Codebases
Let’s take a look at a concrete instance to know how we might run a
codemod in a JavaScript challenge. 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 remodel the tree into
different codecs (that is how TypeScript works). Moreover, there are
instruments that assist apply codemods to total repositories mechanically.
One of the in style 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 change deprecated API calls
with up to date variations throughout a whole challenge.
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 dwell in manufacturing and dealing as anticipated, the following
logical step is to scrub up the toggle and any associated logic.
For example, contemplate the next code:
const information = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;
As soon as the characteristic is absolutely launched and now not wants a toggle, this
will 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 appears 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 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
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 job with clear enter and output, I choose writing checks first,
then implementing the codemod. I begin by defining a destructive case to
guarantee we don’t unintentionally 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 named inside an if assertion), implement that case, and
guarantee all checks cross.
This strategy aligns properly with Check-Pushed Improvement (TDD), even
in case you don’t follow TDD often. 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’ll be able to write checks 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
operate from jscodeshift lets you outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, operating the take a look at with a standard jest
command will fail as a result of the
codemod isn’t written but.
The corresponding destructive 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 operate. Create a file
known as remodel.js
with the next code construction:
module.exports = operate(fileInfo, api, choices) { const j = api.jscodeshift; const root = j(fileInfo.supply); // manipulate the tree nodes right here return root.toSource(); };
This operate reads the file right into a tree and makes use of jscodeshift’s API to
question, modify, and replace the nodes. Lastly, it converts the AST again to
supply code with .toSource()
.
Now we will begin implementing the remodel steps:
- Discover all cases of
featureToggle
. - Confirm that the argument handed is
'feature-new-product-list'
. - Exchange your complete 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: { 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.,
{
), eradicating the toggle logic and leaving simplified code
identify: 'Product' }
behind.
This instance demonstrates how simple it’s to create a helpful
transformation and apply it to a big codebase, considerably decreasing
guide effort.
You’ll want to write 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’ll be able to check it out on a goal codebase,
such because the one you are engaged on. jscodeshift supplies 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 useful checks nonetheless
cross and that nothing breaks—even in case you’re introducing a breaking change.
As soon as happy, you’ll be able to 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 parts. Manually
refactoring these areas will be time-consuming and error-prone.
By automating refactoring duties, codemods assist preserve your codebase clear
and freed from legacy patterns. Frequently making use of codemods lets you
implement new coding requirements, take away unused code, and modernize your
codebase with out having to manually modify each file.
Refactoring an Avatar Element
Now, let’s take a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar
element tightly coupled with a
Tooltip
. Every time a person passes a identify
prop into the Avatar
, it
mechanically wraps the avatar with a tooltip.

Determine 3: A avatar element 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
element,
giving builders extra flexibility. Builders ought to be capable of 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 lots 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 element and see which nodes symbolize the Avatar
utilization
we’re concentrating on. An Avatar
element with each identify
and picture
props
is parsed into an summary syntax tree as proven beneath:

Determine 4: AST of the Avatar element utilization
Writing the Codemod
Let’s break down the transformation into smaller duties:
- Discover
Avatar
utilization within the element tree. - Verify if the
identify
prop is current. - If not, do nothing.
- If current:
- Create a
Tooltip
node. - Add the
identify
to theTooltip
. - Take away the
identify
fromAvatar
. - Add
Avatar
as a toddler of theTooltip
. - Exchange the unique
Avatar
node with the brand newTooltip
.
To start, we’ll discover all cases of Avatar (I’ll omit among the
checks, however you need to write comparability checks first).
defineInlineTest( { default: remodel, 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 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
operate, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip
and the Avatar
element 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 remodeled outcome:

Determine 5: Run checks inside hypermod earlier than apply it to your codebase
This codemod searches for all cases of Avatar
. If a
identify
prop is discovered, it removes the identify
prop
from Avatar
, wraps the Avatar
inside a
Tooltip
, and passes the identify
prop to the
Tooltip
.
By now, I hope it’s clear that codemods are extremely helpful and
that the workflow is intuitive, particularly for large-scale adjustments the place
guide updates can be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we will handle these less-than-ideal points.
Fixing Frequent Pitfalls of Codemods
As a seasoned developer, you already know the “pleased path” is just a small half
of the complete image. There are quite a few situations to think about when writing
a change script to deal with code mechanically.
Builders write code in a wide range of types. For instance, somebody
may import the Avatar
element however give it a special identify as a result of
they could have one other Avatar
element from a special package deal:
import { Avatar as AKAvatar } from "@design-system/avatar"; const UserInfo = () => ( <AKAvatar identify="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 proper
identify.
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
element named Tooltip
is all the time the one you’re searching for.
Within the characteristic toggle instance, 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 could even use the toggle with different circumstances 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,
growing the chance of unintentionally breaking one thing. Relying solely
on the instances you’ll be able to anticipate will not be sufficient. You want thorough testing
to keep away from breaking unintended elements of the code.
Leveraging Supply Graphs and Check-Pushed Codemods
To deal with these complexities, codemods needs to be used alongside different
strategies. For example, just a few years in the past, I participated in a design
system parts rewrite challenge at Atlassian. We addressed this concern by
first looking out the supply graph, which contained nearly all of inside
element utilization. This allowed us to know how parts had been used,
whether or not they had been imported beneath completely different names, or whether or not sure
public props had been regularly used. After this search section, we wrote our
take a look at instances upfront, making certain we lined nearly all 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 operating 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’ll be able to see, there are many edge instances to deal with, particularly in
codebases past your management—similar to exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
assessment of the outcomes.
Nevertheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a specific coding fashion, you’ll be able to leverage these
instruments to scale 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.
For example, you possibly can 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 complicated transformations into smaller, extra
manageable ones lets you sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
adjustments extra possible.
Codemod Composition
Let’s revisit the characteristic toggle removing instance mentioned earlier. Within the code snippet
we have now a toggle known as feature-convert-new
have to be eliminated:
import { featureToggle } from "./utils/featureToggle"; const convertOld = (enter: string) => { return enter.toLowerCase(); }; const convertNew = (enter: string) => { return enter.toUpperCase(); }; const outcome = featureToggle("feature-convert-new") ? convertNew("Howdy, world") : convertOld("Howdy, world"); console.log(outcome);
The codemod for take away a given toggle works high quality, and after operating the codemod,
we would like the supply to appear to be this:
const convertNew = (enter: string) => { return enter.toUpperCase(); }; const outcome = convertNew("Howdy, world"); console.log(outcome);
Nevertheless, past eradicating the characteristic toggle logic, there are further duties to
deal with:
- Take away the unused
convertOld
operate. - Clear up the unused
featureToggle
import.
In fact, you possibly can write one huge codemod to deal with every thing in a
single cross and take a look at it collectively. Nevertheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
unbiased items—identical to how you’d 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
will be examined individually, masking completely different instances with out interference.
Furthermore, it lets you reuse and compose them for various
functions.
For example, you may break it down like this:
- A change to take away a particular characteristic toggle.
- One other transformation to scrub up unused imports.
- A change to take away unused operate declarations.
By composing these, you’ll be able to 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:
- 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 remodel
You too can extract further codemods as wanted, combining them in
varied orders relying on the specified final result.

Determine 7: Put completely different transforms right into a pipepline to type one other remodel
The createTransformer
Operate
The implementation of the createTransformer
operate is comparatively
easy. It acts as a higher-order operate that takes a listing of
smaller remodel capabilities, iterates by the listing to use them to
the foundation 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 possibly can have a remodel operate that inlines
expressions assigning the characteristic toggle name to a variable, so in later
transforms you don’t have to fret about these 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 may tremendously ease the method of dealing with tough 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
element—we had just a few reusable transforms outlined, like including feedback
firstly of capabilities, eradicating deprecated props, or creating aliases
when a package deal is already imported above.
Every of those smaller transforms will be examined and used independently
or mixed for extra complicated transformations, which hurries up subsequent
conversions considerably. In consequence, 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 remodel is comparatively standalone, you’ll be able to fine-tune them
with out affecting different transforms or the extra complicated, 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.
Codemods in Different Languages
Whereas the examples we’ve explored to this point concentrate on JavaScript and JSX
utilizing jscodeshift, codemods can be utilized to different languages. For
occasion, JavaParser presents an identical
mechanism in Java, utilizing AST manipulation to refactor Java code.
Utilizing JavaParser in a Java Codebase
JavaParser will be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated manner.
Assume we have now the next code in FeatureToggleExample.java
, which
checks the toggle feature-convert-new
and branches accordingly:
public class FeatureToggleExample { public void execute() { if (FeatureToggle.isEnabled("feature-convert-new")) { newFeature(); } else { oldFeature(); } } void newFeature() { System.out.println("New Characteristic Enabled"); } void oldFeature() { System.out.println("Outdated Characteristic"); } }
We are able to outline a customer to seek out if
statements checking for
FeatureToggle.isEnabled
, after which change them with the corresponding
true department—just like how we dealt with the characteristic toggle codemod in
JavaScript.
// Customer to take away characteristic toggles class FeatureToggleVisitor extends VoidVisitorAdapter{ @Override public void go to(IfStmt ifStmt, Void arg) { tremendous.go to(ifStmt, arg); if (ifStmt.getCondition().isMethodCallExpr()) { MethodCallExpr methodCall = ifStmt.getCondition().asMethodCallExpr(); if (methodCall.getNameAsString().equals("isEnabled") && methodCall.getScope().isPresent() && methodCall.getScope().get().toString().equals("FeatureToggle")) { BlockStmt thenBlock = ifStmt.getThenStmt().asBlockStmt(); ifStmt.change(thenBlock); } } } }
This code defines a customer sample utilizing
JavaParser to traverse and manipulate the AST. The
FeatureToggleVisitor
appears for if
statements
that decision FeatureToggle.isEnabled()
and replaces your complete
if
assertion with the true department.
You too can outline guests to seek out unused strategies and take away
them:
class UnusedMethodRemover extends VoidVisitorAdapter{ non-public Set calledMethods = new HashSet<>(); non-public Checklist methodsToRemove = new ArrayList<>(); // Acquire all known as strategies @Override public void go to(MethodCallExpr n, Void arg) { tremendous.go to(n, arg); calledMethods.add(n.getNameAsString()); } // Acquire strategies to take away if not known as @Override public void go to(MethodDeclaration n, Void arg) { tremendous.go to(n, arg); String methodName = n.getNameAsString(); if (!calledMethods.incorporates(methodName) && !methodName.equals("predominant")) { methodsToRemove.add(n); } } // After visiting, take away the unused strategies public void removeUnusedMethods() { for (MethodDeclaration methodology : methodsToRemove) { methodology.take away(); } } }
This code defines a customer, UnusedMethodRemover
, to detect and
take away unused strategies. It tracks all known as strategies within the calledMethods
set and checks every methodology declaration. If a technique isn’t known as and isn’t
predominant
, it provides it to the listing of strategies to take away. As soon as all strategies are
processed, it removes any unused strategies from the AST.
Composing Java Guests
You possibly can chain these guests collectively and apply them to your codebase
like so:
public class FeatureToggleRemoverWithCleanup { public static void predominant(String[] args) { strive { String filePath = "src/take a look at/java/com/instance/Instance.java"; CompilationUnit cu = StaticJavaParser.parse(new FileInputStream(filePath)); // Apply transformations FeatureToggleVisitor toggleVisitor = new FeatureToggleVisitor(); cu.settle for(toggleVisitor, null); UnusedMethodRemover remover = new UnusedMethodRemover(); cu.settle for(remover, null); remover.removeUnusedMethods(); // Write the modified code again to the file strive (FileOutputStream fos = new FileOutputStream(filePath)) { fos.write(cu.toString().getBytes()); } System.out.println("Code transformation accomplished efficiently."); } catch (IOException e) { e.printStackTrace(); } } }
Every customer is a unit of transformation, and the customer sample in
JavaParser makes it simple to compose them.
OpenRewrite
One other in style possibility for Java initiatives is OpenRewrite. It makes use of a special format of the
supply code tree known as Lossless Semantic Bushes (LSTs), which
present extra detailed info in comparison with conventional AST (Summary
Syntax Tree) approaches utilized by instruments like JavaParser or jscodeshift.
Whereas AST focuses on the syntactic construction, LSTs seize each syntax and
semantic that means, enabling extra correct and complex
transformations.
OpenRewrite additionally has a strong ecosystem of open-source refactoring
recipes for duties similar to framework migrations, safety fixes, and
sustaining stylistic consistency. This built-in library of recipes can
save builders vital time by permitting them to use standardized
transformations throughout massive codebases while not having to write down customized
scripts.
For builders who want personalized transformations, OpenRewrite permits
you to create and distribute your individual recipes, making it a extremely versatile
and extensible instrument. It’s broadly used within the Java group and is
steadily increasing into different languages, due to its superior
capabilities and community-driven strategy.
Variations Between OpenRewrite and JavaParser or jscodeshift
The important thing distinction between OpenRewrite and instruments like JavaParser or
jscodeshift lies of their strategy to code transformation:
- OpenRewrite’s Lossless Semantic Bushes (LSTs) seize each the
syntactic and semantic that means of the code, enabling extra correct
transformations. - JavaParser and jscodeshift depend on conventional ASTs, which focus
totally on the syntactic construction. Whereas highly effective, they could not all the time
seize the nuances of how the code behaves semantically.
Moreover, OpenRewrite presents a big library of community-driven
refactoring recipes, making it simpler to use widespread transformations with out
needing to write down customized codemods from scratch.
Different Instruments for Codemods
Whereas jscodeshift and OpenRewrite are highly effective instruments, there are
different choices value contemplating, relying in your wants and the ecosystem
you are working in.
Hypermod
Hypermod introduces AI help to the codemod writing course of.
As an alternative of manually crafting the codemod logic, builders can describe
the specified transformation in plain English, and Hypermod will generate
the codemod utilizing jscodeshift. This makes codemod creation extra
accessible, even for builders who is probably not aware of AST
manipulation.
You possibly can compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It might probably run the codemod and generate a pull
request with the proposed adjustments, permitting you to assessment and approve
them. This integration makes your complete course of from codemod improvement
to deployment way more streamlined.
Codemod.com
Codemod.com is a community-driven platform the place builders
can share and uncover codemods. If you happen to want a particular codemod for a
widespread refactoring job or migration, you’ll be able to seek for current
codemods. Alternatively, you’ll be able to publish codemods you’ve created to assist
others within the developer group.
If you happen to’re migrating an API and wish a codemod to deal with it,
Codemod.com can prevent time by providing pre-built codemods for
many widespread transformations, decreasing the necessity to write one from
scratch.
Conclusion
Codemods are highly effective instruments that permit builders to automate code
transformations, making it simpler to handle API adjustments, refactor legacy
code, and keep consistency throughout massive codebases with minimal guide
intervention. Through the use of instruments like jscodeshift, Hypermod, or
OpenRewrite, builders can streamline every thing from minor syntax
adjustments to main element rewrites, enhancing total code high quality and
maintainability.
Nevertheless, whereas codemods provide vital advantages, they aren’t
with out challenges. One of many key considerations is dealing with edge instances,
notably when the codebase is numerous or publicly shared. Variations
in coding types, import aliases, or surprising patterns can result in
points that codemods could not deal with mechanically. These edge instances
require cautious planning, thorough testing, and, in some cases, guide
intervention to make sure accuracy.
To maximise the effectiveness of codemods, it’s essential to interrupt
complicated transformations into smaller, testable steps and to make use of code
standardization instruments the place potential. Codemods will be extremely efficient,
however their success will depend on considerate design and understanding the
limitations they could face in additional various or complicated codebases.
As a library developer, it’s possible you’ll create a well-liked utility that lots of of
1000’s of builders depend on each day, similar 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 robust instrument for automating
large-scale code transformations, permitting builders to introduce breaking
API adjustments, refactor legacy codebases, and keep code hygiene with
minimal guide effort.
On this article, we’ll discover what codemods are and the instruments you’ll be able to
use to create them, similar to jscodeshift, hypermod.io, and codemod.com. We’ll stroll by real-world examples,
from cleansing up characteristic toggles to refactoring element hierarchies.
You’ll additionally discover ways to break down complicated transformations into smaller,
testable items—a follow often known as codemod composition—to make sure
flexibility and maintainability.
By the top, you’ll see how codemods can grow 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 essentially the most difficult refactoring
duties.
Breaking Modifications in APIs
Returning to the situation 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 complicated instances, you may resort to utilizing instruments like sed
or awk
. Nevertheless, when your library is broadly adopted, the
scope of such adjustments turns into more durable to handle. You possibly can’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 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, typically does not scale properly, particularly for main shifts.
Think about 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
typically already on the horizon.
For library builders, this case creates a burden. Sustaining
a number of older variations to assist customers who haven’t migrated is each
pricey and time-consuming. For customers, frequent adjustments danger eroding belief.
They might hesitate to improve or begin exploring extra secure alternate options,
which perpetuating the cycle.
However what in case you might assist customers handle these adjustments mechanically?
What in case you might launch a instrument 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. A number of libraries, together with React
and Subsequent.js, have already embraced codemods to easy the trail for model
bumps. For instance, React supplies codemods to deal with the migration from
older API patterns, just like the previous 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 comply with 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 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 remodel code—was launched to sort out this downside.
The method usually includes 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 change, similar to renaming a
operate 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, decreasing the prospect of human
error. Codemods also can deal with complicated refactoring situations, similar to
adjustments to deeply nested constructions or eradicating deprecated API utilization.
If we visualize the method, it will 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 if you
run refactorings like
Primarily, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the outcome again into your
recordsdata.
For contemporary IDEs, many issues occur beneath the hood to make sure adjustments
are utilized accurately and effectively, similar to figuring out the scope of
the change and resolving conflicts like variable identify collisions. Some
refactorings even immediate you to enter parameters, similar to when utilizing
order of parameters or default values earlier than finalizing the change.
Use jscodeshift in JavaScript Codebases
Let’s take a look at a concrete instance to know how we might run a
codemod in a JavaScript challenge. 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 remodel the tree into
different codecs (that is how TypeScript works). Moreover, there are
instruments that assist apply codemods to total repositories mechanically.
One of the in style 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 change deprecated API calls
with up to date variations throughout a whole challenge.
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 dwell in manufacturing and dealing as anticipated, the following
logical step is to scrub up the toggle and any associated logic.
For example, contemplate the next code:
const information = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;
As soon as the characteristic is absolutely launched and now not wants a toggle, this
will 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 appears 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 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
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 job with clear enter and output, I choose writing checks first,
then implementing the codemod. I begin by defining a destructive case to
guarantee we don’t unintentionally 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 named inside an if assertion), implement that case, and
guarantee all checks cross.
This strategy aligns properly with Check-Pushed Improvement (TDD), even
in case you don’t follow TDD often. 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’ll be able to write checks 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
operate from jscodeshift lets you outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, operating the take a look at with a standard jest
command will fail as a result of the
codemod isn’t written but.
The corresponding destructive 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 operate. Create a file
known as remodel.js
with the next code construction:
module.exports = operate(fileInfo, api, choices) { const j = api.jscodeshift; const root = j(fileInfo.supply); // manipulate the tree nodes right here return root.toSource(); };
This operate reads the file right into a tree and makes use of jscodeshift’s API to
question, modify, and replace the nodes. Lastly, it converts the AST again to
supply code with .toSource()
.
Now we will begin implementing the remodel steps:
- Discover all cases of
featureToggle
. - Confirm that the argument handed is
'feature-new-product-list'
. - Exchange your complete 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: { 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.,
{
), eradicating the toggle logic and leaving simplified code
identify: 'Product' }
behind.
This instance demonstrates how simple it’s to create a helpful
transformation and apply it to a big codebase, considerably decreasing
guide effort.
You’ll want to write 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’ll be able to check it out on a goal codebase,
such because the one you are engaged on. jscodeshift supplies 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 useful checks nonetheless
cross and that nothing breaks—even in case you’re introducing a breaking change.
As soon as happy, you’ll be able to 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 parts. Manually
refactoring these areas will be time-consuming and error-prone.
By automating refactoring duties, codemods assist preserve your codebase clear
and freed from legacy patterns. Frequently making use of codemods lets you
implement new coding requirements, take away unused code, and modernize your
codebase with out having to manually modify each file.
Refactoring an Avatar Element
Now, let’s take a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar
element tightly coupled with a
Tooltip
. Every time a person passes a identify
prop into the Avatar
, it
mechanically wraps the avatar with a tooltip.

Determine 3: A avatar element 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
element,
giving builders extra flexibility. Builders ought to be capable of 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 lots 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 element and see which nodes symbolize the Avatar
utilization
we’re concentrating on. An Avatar
element with each identify
and picture
props
is parsed into an summary syntax tree as proven beneath:

Determine 4: AST of the Avatar element utilization
Writing the Codemod
Let’s break down the transformation into smaller duties:
- Discover
Avatar
utilization within the element tree. - Verify if the
identify
prop is current. - If not, do nothing.
- If current:
- Create a
Tooltip
node. - Add the
identify
to theTooltip
. - Take away the
identify
fromAvatar
. - Add
Avatar
as a toddler of theTooltip
. - Exchange the unique
Avatar
node with the brand newTooltip
.
To start, we’ll discover all cases of Avatar (I’ll omit among the
checks, however you need to write comparability checks first).
defineInlineTest( { default: remodel, 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 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
operate, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip
and the Avatar
element 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 remodeled outcome:

Determine 5: Run checks inside hypermod earlier than apply it to your codebase
This codemod searches for all cases of Avatar
. If a
identify
prop is discovered, it removes the identify
prop
from Avatar
, wraps the Avatar
inside a
Tooltip
, and passes the identify
prop to the
Tooltip
.
By now, I hope it’s clear that codemods are extremely helpful and
that the workflow is intuitive, particularly for large-scale adjustments the place
guide updates can be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we will handle these less-than-ideal points.
Fixing Frequent Pitfalls of Codemods
As a seasoned developer, you already know the “pleased path” is just a small half
of the complete image. There are quite a few situations to think about when writing
a change script to deal with code mechanically.
Builders write code in a wide range of types. For instance, somebody
may import the Avatar
element however give it a special identify as a result of
they could have one other Avatar
element from a special package deal:
import { Avatar as AKAvatar } from "@design-system/avatar"; const UserInfo = () => ( <AKAvatar identify="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 proper
identify.
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
element named Tooltip
is all the time the one you’re searching for.
Within the characteristic toggle instance, 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 could even use the toggle with different circumstances 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,
growing the chance of unintentionally breaking one thing. Relying solely
on the instances you’ll be able to anticipate will not be sufficient. You want thorough testing
to keep away from breaking unintended elements of the code.
Leveraging Supply Graphs and Check-Pushed Codemods
To deal with these complexities, codemods needs to be used alongside different
strategies. For example, just a few years in the past, I participated in a design
system parts rewrite challenge at Atlassian. We addressed this concern by
first looking out the supply graph, which contained nearly all of inside
element utilization. This allowed us to know how parts had been used,
whether or not they had been imported beneath completely different names, or whether or not sure
public props had been regularly used. After this search section, we wrote our
take a look at instances upfront, making certain we lined nearly all 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 operating 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’ll be able to see, there are many edge instances to deal with, particularly in
codebases past your management—similar to exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
assessment of the outcomes.
Nevertheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a specific coding fashion, you’ll be able to leverage these
instruments to scale 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.
For example, you possibly can 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 complicated transformations into smaller, extra
manageable ones lets you sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
adjustments extra possible.
Codemod Composition
Let’s revisit the characteristic toggle removing instance mentioned earlier. Within the code snippet
we have now a toggle known as feature-convert-new
have to be eliminated:
import { featureToggle } from "./utils/featureToggle"; const convertOld = (enter: string) => { return enter.toLowerCase(); }; const convertNew = (enter: string) => { return enter.toUpperCase(); }; const outcome = featureToggle("feature-convert-new") ? convertNew("Howdy, world") : convertOld("Howdy, world"); console.log(outcome);
The codemod for take away a given toggle works high quality, and after operating the codemod,
we would like the supply to appear to be this:
const convertNew = (enter: string) => { return enter.toUpperCase(); }; const outcome = convertNew("Howdy, world"); console.log(outcome);
Nevertheless, past eradicating the characteristic toggle logic, there are further duties to
deal with:
- Take away the unused
convertOld
operate. - Clear up the unused
featureToggle
import.
In fact, you possibly can write one huge codemod to deal with every thing in a
single cross and take a look at it collectively. Nevertheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
unbiased items—identical to how you’d 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
will be examined individually, masking completely different instances with out interference.
Furthermore, it lets you reuse and compose them for various
functions.
For example, you may break it down like this:
- A change to take away a particular characteristic toggle.
- One other transformation to scrub up unused imports.
- A change to take away unused operate declarations.
By composing these, you’ll be able to 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:
- 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 remodel
You too can extract further codemods as wanted, combining them in
varied orders relying on the specified final result.

Determine 7: Put completely different transforms right into a pipepline to type one other remodel
The createTransformer
Operate
The implementation of the createTransformer
operate is comparatively
easy. It acts as a higher-order operate that takes a listing of
smaller remodel capabilities, iterates by the listing to use them to
the foundation 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 possibly can have a remodel operate that inlines
expressions assigning the characteristic toggle name to a variable, so in later
transforms you don’t have to fret about these 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 may tremendously ease the method of dealing with tough 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
element—we had just a few reusable transforms outlined, like including feedback
firstly of capabilities, eradicating deprecated props, or creating aliases
when a package deal is already imported above.
Every of those smaller transforms will be examined and used independently
or mixed for extra complicated transformations, which hurries up subsequent
conversions considerably. In consequence, 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 remodel is comparatively standalone, you’ll be able to fine-tune them
with out affecting different transforms or the extra complicated, 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.
Codemods in Different Languages
Whereas the examples we’ve explored to this point concentrate on JavaScript and JSX
utilizing jscodeshift, codemods can be utilized to different languages. For
occasion, JavaParser presents an identical
mechanism in Java, utilizing AST manipulation to refactor Java code.
Utilizing JavaParser in a Java Codebase
JavaParser will be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated manner.
Assume we have now the next code in FeatureToggleExample.java
, which
checks the toggle feature-convert-new
and branches accordingly:
public class FeatureToggleExample { public void execute() { if (FeatureToggle.isEnabled("feature-convert-new")) { newFeature(); } else { oldFeature(); } } void newFeature() { System.out.println("New Characteristic Enabled"); } void oldFeature() { System.out.println("Outdated Characteristic"); } }
We are able to outline a customer to seek out if
statements checking for
FeatureToggle.isEnabled
, after which change them with the corresponding
true department—just like how we dealt with the characteristic toggle codemod in
JavaScript.
// Customer to take away characteristic toggles class FeatureToggleVisitor extends VoidVisitorAdapter{ @Override public void go to(IfStmt ifStmt, Void arg) { tremendous.go to(ifStmt, arg); if (ifStmt.getCondition().isMethodCallExpr()) { MethodCallExpr methodCall = ifStmt.getCondition().asMethodCallExpr(); if (methodCall.getNameAsString().equals("isEnabled") && methodCall.getScope().isPresent() && methodCall.getScope().get().toString().equals("FeatureToggle")) { BlockStmt thenBlock = ifStmt.getThenStmt().asBlockStmt(); ifStmt.change(thenBlock); } } } }
This code defines a customer sample utilizing
JavaParser to traverse and manipulate the AST. The
FeatureToggleVisitor
appears for if
statements
that decision FeatureToggle.isEnabled()
and replaces your complete
if
assertion with the true department.
You too can outline guests to seek out unused strategies and take away
them:
class UnusedMethodRemover extends VoidVisitorAdapter{ non-public Set calledMethods = new HashSet<>(); non-public Checklist methodsToRemove = new ArrayList<>(); // Acquire all known as strategies @Override public void go to(MethodCallExpr n, Void arg) { tremendous.go to(n, arg); calledMethods.add(n.getNameAsString()); } // Acquire strategies to take away if not known as @Override public void go to(MethodDeclaration n, Void arg) { tremendous.go to(n, arg); String methodName = n.getNameAsString(); if (!calledMethods.incorporates(methodName) && !methodName.equals("predominant")) { methodsToRemove.add(n); } } // After visiting, take away the unused strategies public void removeUnusedMethods() { for (MethodDeclaration methodology : methodsToRemove) { methodology.take away(); } } }
This code defines a customer, UnusedMethodRemover
, to detect and
take away unused strategies. It tracks all known as strategies within the calledMethods
set and checks every methodology declaration. If a technique isn’t known as and isn’t
predominant
, it provides it to the listing of strategies to take away. As soon as all strategies are
processed, it removes any unused strategies from the AST.
Composing Java Guests
You possibly can chain these guests collectively and apply them to your codebase
like so:
public class FeatureToggleRemoverWithCleanup { public static void predominant(String[] args) { strive { String filePath = "src/take a look at/java/com/instance/Instance.java"; CompilationUnit cu = StaticJavaParser.parse(new FileInputStream(filePath)); // Apply transformations FeatureToggleVisitor toggleVisitor = new FeatureToggleVisitor(); cu.settle for(toggleVisitor, null); UnusedMethodRemover remover = new UnusedMethodRemover(); cu.settle for(remover, null); remover.removeUnusedMethods(); // Write the modified code again to the file strive (FileOutputStream fos = new FileOutputStream(filePath)) { fos.write(cu.toString().getBytes()); } System.out.println("Code transformation accomplished efficiently."); } catch (IOException e) { e.printStackTrace(); } } }
Every customer is a unit of transformation, and the customer sample in
JavaParser makes it simple to compose them.
OpenRewrite
One other in style possibility for Java initiatives is OpenRewrite. It makes use of a special format of the
supply code tree known as Lossless Semantic Bushes (LSTs), which
present extra detailed info in comparison with conventional AST (Summary
Syntax Tree) approaches utilized by instruments like JavaParser or jscodeshift.
Whereas AST focuses on the syntactic construction, LSTs seize each syntax and
semantic that means, enabling extra correct and complex
transformations.
OpenRewrite additionally has a strong ecosystem of open-source refactoring
recipes for duties similar to framework migrations, safety fixes, and
sustaining stylistic consistency. This built-in library of recipes can
save builders vital time by permitting them to use standardized
transformations throughout massive codebases while not having to write down customized
scripts.
For builders who want personalized transformations, OpenRewrite permits
you to create and distribute your individual recipes, making it a extremely versatile
and extensible instrument. It’s broadly used within the Java group and is
steadily increasing into different languages, due to its superior
capabilities and community-driven strategy.
Variations Between OpenRewrite and JavaParser or jscodeshift
The important thing distinction between OpenRewrite and instruments like JavaParser or
jscodeshift lies of their strategy to code transformation:
- OpenRewrite’s Lossless Semantic Bushes (LSTs) seize each the
syntactic and semantic that means of the code, enabling extra correct
transformations. - JavaParser and jscodeshift depend on conventional ASTs, which focus
totally on the syntactic construction. Whereas highly effective, they could not all the time
seize the nuances of how the code behaves semantically.
Moreover, OpenRewrite presents a big library of community-driven
refactoring recipes, making it simpler to use widespread transformations with out
needing to write down customized codemods from scratch.
Different Instruments for Codemods
Whereas jscodeshift and OpenRewrite are highly effective instruments, there are
different choices value contemplating, relying in your wants and the ecosystem
you are working in.
Hypermod
Hypermod introduces AI help to the codemod writing course of.
As an alternative of manually crafting the codemod logic, builders can describe
the specified transformation in plain English, and Hypermod will generate
the codemod utilizing jscodeshift. This makes codemod creation extra
accessible, even for builders who is probably not aware of AST
manipulation.
You possibly can compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It might probably run the codemod and generate a pull
request with the proposed adjustments, permitting you to assessment and approve
them. This integration makes your complete course of from codemod improvement
to deployment way more streamlined.
Codemod.com
Codemod.com is a community-driven platform the place builders
can share and uncover codemods. If you happen to want a particular codemod for a
widespread refactoring job or migration, you’ll be able to seek for current
codemods. Alternatively, you’ll be able to publish codemods you’ve created to assist
others within the developer group.
If you happen to’re migrating an API and wish a codemod to deal with it,
Codemod.com can prevent time by providing pre-built codemods for
many widespread transformations, decreasing the necessity to write one from
scratch.
Conclusion
Codemods are highly effective instruments that permit builders to automate code
transformations, making it simpler to handle API adjustments, refactor legacy
code, and keep consistency throughout massive codebases with minimal guide
intervention. Through the use of instruments like jscodeshift, Hypermod, or
OpenRewrite, builders can streamline every thing from minor syntax
adjustments to main element rewrites, enhancing total code high quality and
maintainability.
Nevertheless, whereas codemods provide vital advantages, they aren’t
with out challenges. One of many key considerations is dealing with edge instances,
notably when the codebase is numerous or publicly shared. Variations
in coding types, import aliases, or surprising patterns can result in
points that codemods could not deal with mechanically. These edge instances
require cautious planning, thorough testing, and, in some cases, guide
intervention to make sure accuracy.
To maximise the effectiveness of codemods, it’s essential to interrupt
complicated transformations into smaller, testable steps and to make use of code
standardization instruments the place potential. Codemods will be extremely efficient,
however their success will depend on considerate design and understanding the
limitations they could face in additional various or complicated codebases.