Comments (4)
Thank you for creating this issue. What is the difference with multiple keys? It already works the way you want if you specify only one key. Check it out in our playground.
import * as v from 'valibot';
const VariantSchema = v.variant('type', [
v.object({
type: v.literal('email'),
email: v.literal('[email protected]'),
urls: v.array(v.string([v.url()])),
}),
v.object({
type: v.literal('url'),
email: v.literal('[email protected]'),
url: v.picklist(['https://', 'https://this.com']),
}),
v.object({
type: v.literal('date'),
email: v.literal('[email protected]'),
ip: v.picklist(['12.2.2.2', '2.2.2.2']),
date: v.string([v.isoDate()]),
}),
]);
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I want to apologize for any confusion my previous message may have caused. Upon further reflection, I realize that the example I provided did not accurately represent the complexity of my use case, particularly concerning the handling of null values within the variant schema . n my project, I am dealing with a complex form that has numerous cases, each dependent on specific conditions. These conditions are not just based on a single discriminator key but require a combination of keys to determine the correct validation schema. This complexity is crucial for my application, as it needs to accurately validate data based on multiple criteria.
this is fake example
import * as v from 'valibot';
// Define the userType variant schema
const userType = v.variant('userType',[
v.object({
userType: v.literal('administrator'),
requirement: v.array(v.string())
}),
v.object({
userType: v.literal('user'),
description: v.string()
})
]);
// Define the typeEmails variant schema
const typeEmails = v.variant('email',[
v.object({
email: v.literal('[email protected]'),
expired: v.date()
}),
v.object({
email: v.literal('[email protected]'),
description: v.string()
})
]);
// Define the typeUrl variant schema
const typeUrl = v.variant('url',[
v.object({
url: v.literal('https://a.com'),
domainName: v.string()
}),
v.object({
url: v.literal('https://b.com'), // Corrected the typo here
description: v.string()
})
]);
// Define the VariantSchema that combines multiple conditions and handles null values
const VariantSchema = v.variant(['type', 'email'], [
v.object({
type: v.literal('email'),
urls: v.array(v.string([v.url()])),
email: v.literal('[email protected]'),
// Include typeEmails.entries for more complex validation scenarios
// Note: This is a conceptual example, as direct usage like this might not be supported
// Consider using custom validation logic or nested schemas for complex scenarios
}),
v.object({
type: v.literal('url'),
email: v.literal('[email protected]'),
url: v.picklist(['https://', 'https://this.com']),
}),
v.object({
type: v.literal('date'),
email: v.literal('[email protected]'),
ip: v.picklist(['12.2.2.2', '2.2.2.2']),
date: v.string([v.isoDate()]),
}),
// Adding an object to handle null values for type
v.object({
type: v.literal(null), // This is crucial for handling null values
email: v.string([v.email()]), // This field can be any string or null
url: v.string([v.url()]), // This field can be any URL or null
}),
]);
from valibot.
It looks like union
is the right schema for your use case:
from valibot.
It is now possible to deeply nest multiple variant
schemas to achieve this goal.
from valibot.
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