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Validator: Simple Rust Struct Validation

Validator simplifies struct validation in Rust by providing a derive macro for easy integration and a range of built-in validators.
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Validator provides a derive macro that simplifies validation logic for structs in Rust. It allows developers to define validation rules directly on struct fields using attributes. This makes it easier to ensure data integrity and correctness. It is inspired by libraries such as Marshmallow and Django's validators. The core problem addressed is reducing boilerplate code associated with manual validation, especially for complex data structures.

Validator offers a concise and declarative way to define validation rules for struct fields. It supports a variety of built-in validators for common data types and patterns. Its derive macro is easy to use and integrates seamlessly with existing Rust code. It's particularly beneficial for scenarios requiring data sanitization and schema enforcement, promoting cleaner and more maintainable code.

  • Derive Macro: Simplifies validation by adding validation logic to struct fields with minimal code.
  • Built-in Validators: Offers a wide range of validators for common types (email, URL, length, range, etc.) and patterns (regex, credit card).
  • Custom Validators: Enables defining custom validation logic through functions and using custom validation functions with arguments.
  • Flexible Validation: Supports validation on Option<_> fields, nested structs, and vectors of structs.
  • Clear Error Reporting: Provides detailed validation errors with field names and error codes.

The project is actively maintained with recent commits and a growing community. Extensive documentation and examples are available. The crate has a stable API and a solid track record of reliability. The library is well-tested and includes a comprehensive set of validators.

Validator benefits Rust developers by streamlining data validation, reducing boilerplate, and improving code readability. It’s valuable for applications requiring data integrity, API validation, and data sanitization across various domains. It offers a more maintainable approach compared to manual validation implementations.

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Created
9 years ago
Commit
1 month ago
License
MIT
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Updated 16 days ago

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