In Mule 4, reusable “global” DataWeave functions are declared in a custom .dwl module and imported by each script that needs them. “Global” is a convenient description—not a DataWeave declaration keyword: a function is available where its module is imported, and the import style determines whether you call it with a module qualifier.
What a custom function module does
Mule 4 uses DataWeave 2.x. DataWeave 2 introduced typed reusable functions and modules, which let you keep declarations separate from the transformations that use them. MuleSoft’s Mule 4.3 introduction describes these capabilities.
A custom module is for reusable declarations. It can contain functions, variables, types, and namespaces, but it is not a complete transformation: it must not contain an output directive, executable mapping body, or the --- separator. A mapping file, by contrast, is an executable DataWeave script. When a complete mapping is imported, its body is exposed through main. See MuleSoft’s custom module guide.
Create a declaration-only module
For the Mule project workflow in MuleSoft’s custom-module guide, save a file named MyModule.dwl under src/main/resources/modules. The declarations in it can be used by scripts that import modules::MyModule.
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%dw 2.0
fun appendUnderscore(value: String): String = value ++ "_"The module contains the function declaration only. Do not add an output directive or mapping body to this file.
Import and call the function
Use a module import when you want calls to show which module supplies the function. The module path in the import must match the module’s location in the project.
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%dw 2.0
import modules::MyModule
output application/json
---
MyModule::appendUnderscore("dataweave")To call the function without the module qualifier, import that function by name:
%dw 2.0
import appendUnderscore from modules::MyModule
output application/json
---
appendUnderscore("dataweave")A wildcard import can also make all declarations from the module available without qualifying each call. Named and wildcard imports are useful for concise code; a qualified call can make the function’s origin more apparent. MuleSoft documents these import forms in its DataWeave function reference and custom module guide.
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You can use as to alias an imported module or element when names would otherwise clash. The built-in dw::Core module is imported automatically; other built-in modules require an explicit import. For example, importing dw::core::Strings allows a qualified call such as Strings::pluralize("box"). The same qualified, named, and wildcard import patterns apply to custom modules.
Choose the file location for your workflow
There is not one universal module directory across all DataWeave workflows. Follow the layout documented for the kind of project you are building.
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| Workflow | Documented locations | How it is used |
|---|---|---|
| Mule project custom module | src/main/resources/modules (MuleSoft custom module guide) |
Import a module such as modules::MyModule from a DataWeave script. |
| DataWeave library extension project | src/main/dw for mappings and modules; src/test/dw for module tests (MuleSoft extension guide) |
Build and test a reusable DataWeave library using the extension workflow. |
The locations and workflows are described in MuleSoft’s custom module guide and DataWeave extension guide. Do not assume an import path or directory from one workflow automatically applies to another.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test or distribute a DataWeave library
The current DataWeave extension workflow supports previewing module functions through an integration mapping and testing modules with the DataWeave Testing Framework. It also documents deploying a library to Anypoint Exchange, then consuming it by adding the library’s group ID, artifact ID, version, and classifier to a Maven dependency. These are library-project steps; use the extension documentation that matches your environment rather than treating them as requirements for every Mule project.
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Check compatibility before using newer visibility features
The versioned DataWeave 2.3 module and function-reference pages explain the module and import patterns above. The current extension and scope-visibility documentation covers newer library capabilities. MuleSoft says the visibility model involving internal and @VisibleTo was introduced in DataWeave 2.12.0, so it should not be projected back onto DataWeave 2.0. The visibility documentation also says those modifiers have no practical effect in inline Mule transformation mappings. Check your target Mule runtime and DataWeave version before relying on newer visibility behavior: scope visibility and the extension guide.
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