A collection of useful macros that extend Laravel's Collection class with additional functionality.
Spatie Laravel Collection Macros is a PHP package that extends Laravel's Collection class with over 40 additional macros for enhanced data manipulation. It provides methods for conditional logic, data transformation, indexing, pagination, and error handling, filling gaps in the native Collection API. The package simplifies complex operations and makes working with collections more expressive and efficient.
Laravel developers who frequently work with collections and need more advanced data manipulation capabilities beyond Laravel's built-in methods. It's particularly useful for backend developers handling datasets, APIs, or complex business logic.
Developers choose this package because it seamlessly integrates with Laravel's Collection class, follows Laravel's elegant syntax, and provides a comprehensive set of utilities that save time and reduce boilerplate code. It's maintained by Spatie, a reputable agency known for high-quality Laravel packages.
A set of useful Laravel collection macros
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Adds over 40 macros like 'after', 'before', and 'chunkBy' that fill gaps in Laravel's native Collection API, as listed in the README, reducing boilerplate for common tasks.
Includes 'if', 'ifAny', and 'ifEmpty' macros enabling expressive logic within collection chains, demonstrated with examples for branching based on conditions.
Provides 'try'/'catch' macros that allow graceful exception handling within collection operations, preventing chain breaks without manual intervention.
Offers 'paginate' and 'simplePaginate' macros to easily paginate collection data, useful for API responses or cached datasets without querying the database.
Macros are dynamically added, so they may not be recognized by IDEs like PHPStorm without plugins or configuration, reducing developer experience.
Exclusively depends on Laravel's Collection class, making it useless for non-Laravel projects or when migrating away from the framework.
Macros add abstraction layers; for large datasets, native array functions or custom methods might be faster due to reduced method resolution overhead.