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Type safety

The generated code for Prisma Client contains several helpful types and utilities that you can use to make your application more type-safe. This page describes patterns for leveraging them.

Note: If you're interested in advanced type safety topics with Prisma ORM, be sure to check out this blog post about improving your Prisma Client workflows with the new TypeScript satisfies keyword.

Importing generated types​

You can import the Prisma namespace and use dot notation to access types and utilities. The following example shows how to import the Prisma namespace and use it to access and use the Prisma.UserSelect generated type:

import { Prisma } from '@prisma/client'

// Build 'select' object
const userEmail: Prisma.UserSelect = {
  email: true,
}

// Use select object
const createUser = await prisma.user.create({
  data: {
    email: '[email protected]',
  },
  select: userEmail,
})

See also: Using the Prisma.UserCreateInput generated type

What are generated types?​

Generated types are TypeScript types that are derived from your models. You can use them to create typed objects that you pass into top-level methods like prisma.user.create(...) or prisma.user.update(...), or options such as select or include.

For example, select accepts an object of type UserSelect. Its object properties match those that are supported by select statements according to the model.

The first tab below shows the UserSelect generated type and how each property on the object has a type annotation. The second tab shows the resulting schema model.

type Prisma.UserSelect = {
    id?: boolean | undefined;
    email?: boolean | undefined;
    name?: boolean | undefined;
    posts?: boolean | Prisma.PostFindManyArgs | undefined;
    profile?: boolean | Prisma.ProfileArgs | undefined;
}

In TypeScript the concept of type annotations is when you declare a variable and add a type annotation to describe the type of the variable. See the below example.

const myAge: number = 37
const myName: string = 'Rich'

Both of these variable declarations have been given a type annotation to specify what primitive type they are, number and string respectively. Most of the time this kind of annotation is not needed as TypeScript will infer the type of the variable based on how its initialized. In the above example myAge was initialized with a number so TypeScript guesses that it should be typed as a number.

Going back to the UserSelect type, if you were to use dot notation on the created object userEmail, you would have access to all of the fields on the User model that can be interacted with using a select statement.

model User {
  id      Int      @id @default(autoincrement())
  email   String   @unique
  name    String?
  posts   Post[]
  profile Profile?
}
import { Prisma } from '@prisma/client'

const userEmail: Prisma.UserSelect = {
  email: true,
}

// properties available on the typed object
userEmail.id
userEmail.email
userEmail.name
userEmail.posts
userEmail.profile

In the same mould, you can type an object with an include generated type then your object would have access to those properties on which you can use an include statement.

import { Prisma } from '@prisma/client'

const userPosts: Prisma.UserInclude = {
  posts: true,
}

// properties available on the typed object
userPosts.posts
userPosts.profile

See the model query options reference for more information about the different types available.

Generated UncheckedInput types​

The UncheckedInput types are a special set of generated types that allow you to perform some operations that Prisma Client considers "unsafe", like directly writing relation scalar fields. You can choose either the "safe" Input types or the "unsafe" UncheckedInput type when doing operations like create, update, or upsert.

For example, this Prisma schema has a one-to-many relation between User and Post:

model Post {
  id       Int     @id @default(autoincrement())
  title    String  @db.VarChar(255)
  content  String?
  author   User    @relation(fields: [authorId], references: [id])
  authorId Int
}

model User {
  id    Int     @id @default(autoincrement())
  email String  @unique
  name  String?
  posts Post[]
}

The first tab shows the PostUncheckedCreateInput generated type. It contains the authorId property, which is a relation scalar field. The second tab shows an example query that uses the PostUncheckedCreateInput type. This query will result in an error if a user with an id of 1 does not exist.

type PostUncheckedCreateInput = {
  id?: number
  title: string
  content?: string | null
  authorId: number
}

The same query can be rewritten using the "safer" PostCreateInput type. This type does not contain the authorId field but instead contains the author relation field.

type PostCreateInput = {
  title: string
  content?: string | null
  author: UserCreateNestedOneWithoutPostsInput
}

type UserCreateNestedOneWithoutPostsInput = {
  create?: XOR<
    UserCreateWithoutPostsInput,
    UserUncheckedCreateWithoutPostsInput
  >
  connectOrCreate?: UserCreateOrConnectWithoutPostsInput
  connect?: UserWhereUniqueInput
}

This query will also result in an error if an author with an id of 1 does not exist. In this case, Prisma Client will give a more descriptive error message. You can also use the connectOrCreate API to safely create a new user if one does not already exist with the given id.

We recommend using the "safe" Input types whenever possible.

Type utilities​

info

This feature is available from Prisma ORM version 4.9.0 upwards.

To help you create highly type-safe applications, Prisma Client provides a set of type utilities that tap into input and output types. These types are fully dynamic, which means that they adapt to any given model and schema. You can use them to improve the auto-completion and developer experience of your projects.

This is especially useful in validating inputs and shared Prisma Client extensions.

The following type utilities are available in Prisma Client:

  • Exact<Input, Shape>: Enforces strict type safety on Input. Exact makes sure that a generic type Input strictly complies with the type that you specify in Shape. It narrows Input down to the most precise types.
  • Args<Type, Operation>: Retrieves the input arguments for any given model and operation. This is particularly useful for extension authors who want to do the following:
    • Re-use existing types to extend or modify them.
    • Benefit from the same auto-completion experience as on existing operations.
  • Result<Type, Arguments, Operation>: Takes the input arguments and provides the result for a given model and operation. You would usually use this in conjunction with Args. As with Args, Result helps you to re-use existing types to extend or modify them.
  • Payload<Type, Operation>: Retrieves the entire structure of the result, as scalars and relations objects for a given model and operation. For example, you can use this to determine which keys are scalars or objects at a type level.

As an example, here's a quick way you can enforce that the arguments to a function matches what you will pass to a post.create:

type PostCreateBody = Prisma.Args<typeof prisma.post, 'create'>['data']

const addPost = async (postBody: PostCreateBody) => {
  const post = await prisma.post.create({ data: postBody })
  return post
}

await addPost(myData)
//              ^ guaranteed to match the input of `post.create`