Getting Started

📢 v1.0.0-dev Documentation

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Welcome to Validasi! This guide will help you get started with the most flexible and type-safe validation library for Dart and Flutter.

What is Validasi?

Validasi is a powerful validation library that brings type safety, composability, and elegance to data validation in Dart and Flutter applications. Whether you're validating user input, API responses, or configuration files, Validasi makes it simple and maintainable.

Key Features

Type Safety First

Validasi is built with Dart's type system in mind, providing full type safety throughout your validation logic. No more runtime surprises!

Composable & Reusable

Create complex validation schemas from simple, reusable rules. Mix and match rules to build exactly what you need.

Performance Optimized

Through a series of optimizations, your validations run fast, even when validating thousands of objects.

Why Choose Validasi?

🎯 Intuitive API

final schema = Validasi.string([
  Rules.string.minLength(3),
  Rules.string.maxLength(20),
]);

final result = schema.validate('Hello');

Simple, readable, and self-documenting code.

🔧 Comprehensive Rules

Built-in rules for every common validation scenario:

• String validation (length, patterns, formats)
• Number validation (ranges, comparisons)
• Collection validation (lists, maps)
• Custom validation (inline rules, transformations)

🌲 Nested Validation

Validate complex, nested data structures with ease:

final userSchema = Validasi.map<dynamic>([
  Rules.map.hasFields({
    'profile': FieldRules<Map<String, dynamic>>([
      Rules.map.hasFields({
        'name': FieldRules<String>([Rules.string.minLength(2)]),
        'age': FieldRules<int>([Rules.number.moreThan(0)]),
      }),
    ]),
  }),
]);

🎨 Flexible Transformations

Transform data during validation:

final schema = Validasi.string([
  Rules.transform<String>((value) => value?.trim().toLowerCase()),
  Rules.string.minLength(3),
]);

✅ Type-Safe Input Handling

Validasi uses dual generics to enforce input type safety at compile time. When you need to accept different input types (e.g., strings from APIs), use withPreprocess:

// Accept String input, validate as int
final ageSchema = Validasi.number<int>([
  Rules.number.moreThan(0),
  Rules.number.lessThan(150),
]).withPreprocess((String value) => int.parse(value));

// validate() now only accepts String at compile time
final result = ageSchema.validate('25'); // ✓ Correct type
// ageSchema.validate(25);               // ✗ Compile error

When to use withPreprocess:

• Accepting data from JSON, APIs, or form inputs (usually strings)
• Converting between types in a type-safe way
• Building flexible schemas that accept specific input types

Read more in the Transformations Guide and Engine Architecture.

Companion Packages

Validasi also ships with two companion packages:

• validasi_annotation + validasi_gen (experimental) — annotation-based code generation. Decorate your model with @ValidateClass() and @Validate(), and the generator produces a typed XFields<V> hierarchy plus validate() / validateAsync() extension. No Runtime codegen — the generator runs at build time via build_runner.
• validasi_ui (experimental) — headless form management for Flutter. A ValidasiFormController<T> bridges generated schemas to the widget tree with hooks-style ergonomics: watchValue, watch, setError, formErrors. Pair it with validasi_gen using generateFields: true, generateSchema: true, and generateValidateForm: true for a fully type-safe form experience.

Experimental

Both validasi_gen and validasi_ui are in active development. APIs may change without a major version bump. Feedback and contributions are welcome!

See the dedicated guides for detailed usage:

• Code Generation — using validasi_annotation + validasi_gen
• Form Management — using validasi_ui for Flutter forms
• Agent Skills — if you use an AI coding agent (Claude Code, Cursor, Codex, and others all support the open SKILL.md format), these ship with the same guidance baked in so it writes correct validasi/validasi_gen/validasi_ui code by default. Install with npx skills add albetnov/validasi --all

Community & Support

• GitHub: albetnov/validasi
• Issues: Report bugs or request features
• Pub.dev: Package documentation

LLM Support

This documentation has support for LLMS, you can click the button at the bottom right corner to copy or download the current page as markdown file for your LLM processing. Or you can visit llms-full.txt or llms.txt files.