Advanced Schema Documentation

Can be used to validate more complex schemas, custom validation rules, transformations, and more.

`inferType`

inferType({ required dynamic Function(Map<String, dynamic>) fromMap, required Schema<Map<String, dynamic>> mapSchema });

Can return a custom classe based on the data provided.

Example:


final userSchema = z.inferType(
    fromMap: (json) => User.fromMap(json), // Custom class fromMap method
    mapSchema: z.map({
        'name': z.string().min(3),
        'email': z.string().email(),
    }),
);
 
final user = userSchema.parse({
    'name': 'John Doe',
    'email': 'john.doe@example.com',
});
// user is an instance of User class
 
print('User created: ${user.name}, ${user.email}');

`transformTyped`

transformTyped(R Function(T value) transformer);

Can return a custom classe based on the data provided.

Example:


final schema = z.interface({
    'name': z.string().min(3).max(20),
    'email': z.string().email(),
}).transformTyped((json) => User.fromMap(json)) // Custom class fromMap method
 
final user = schema.parse({
    'name': 'John Doe',
    'email': 'john.doe@example.com',
});
// user is an instance of User class
 
print('User created: ${user.name}, ${user.email}');

`lazy`

lazy(Schema Function() schemaThunk);

Can use lazy schema to avoid circular dependencies.

Example:


Schema<User> getUserSchema() {
    return z.interface({
        'name': z.string().min(3).max(20),
        'email': z.string().email(),
        'friends?': z.lazy(() => getUserSchema().list()), // Lazy schema
    }).transformTyped((json) => User.fromMap(json));
}
 
  final user = getUserSchema().parse({
    'name': 'John Doe',
    'email': 'john.doe@example.com',
    'friends': [
      {
        'name': 'Jane Doe',
        'email': 'jane.doe@example.com',
        'friends': [
          {
            'name': 'Evan Doe',
            'email': 'john.doe@example.com',
          },
        ],
      },
    ],
  });
// user is an instance of User class
 
print(user?.friends.first.friends.first.name);

z.lazy(() => getUserSchema().list()) use the same instance of the schema and convert key to z.list(z.map({'name': z.string().min(3).max(20), 'email': z.string().email()})).

`transform`

transform(dynamic Function(T value) transformer);

Can return a custom classe based on the data provided.

Example:


final schema = z.string().transform((value) => value.toUpperCase());
final result = schema.parse('hello'); // returns 'HELLO'

`refine`

refine(bool Function(T value) predicate, {String? message});

Validates that the value satisfies the provided predicate function.

Example:


final schema = z.string().refine((value) => value.length > 5);
final result = schema.parse('hello'); // returns 'HELLO'
final result = schema.parse('hi'); // returns ZardError

`coerce`

coerce({String? message});

Converts the value to a schema type definition.

Example:


z.coerce.double().parse("25"); // returns 25.0
z.coerce.string().parse(123); // returns '123'
z.coerce.boolean().parse(""); // returns false
z.coerce.int().parse(1000); // returns 1000
z.coerce.date().parse("2021-10-05"); // returns DateTime

Full Example:


import 'package:zard/zard.dart';
 
final userSchema = z.map({
    'name': z.string().transform((value) => value.toUpperCase()),
    'age': z.int(),
    'sallary': z.double(),
    'email': z.string().email(message: 'Deve ser um email válido'),
    'tags': z.list(z.string().transform((value) => '#$value')),
    'birthday': z.date().optional(),
    'addresses': z.list(
      z.map({
        'street': z.string(),
        'city': z.string().transform((value) => value.toUpperCase()),
      }),
    ),
  });
 
  final user = userSchema.parse({
    'name': 'John Doe',
    'age': 30,
    'sallary': 5000.0,
    'email': 'john.doe@example.com',
    'tags': ['#dart', '#flutter'],
    'birthday': DateTime.now(),
    'addresses': [
      {'street': '123 Main St', 'city': 'SPRINGFIELD'},
      {'street': '456 Elm St', 'city': 'SHELBYVILLE'},
    ],
  });
 
  print(user);