Dealing with errors

There are multiple different types of errors in GraphQL and each can be handled differently.

In this guide we will outline the different types of errors that you will encounter when building a GraphQL server.

Note: By default Strawberry will log all execution errors to a strawberry.execution logger: /docs/types/schema#handling-execution-errors.

GraphQL validation errors

GraphQL is strongly typed and so Strawberry validates all queries before executing them. If a query is invalid it isn’t executed and instead the response contains an errors list:

{
  hi
}

{
  "data": null,
  "errors": [
    {
      "message": "Cannot query field 'hi' on type 'Query'.",
      "locations": [
        {
          "line": 2,
          "column": 3
        }
      ],
      "path": null
    }
  ]
}

Each error has a message, line, column and path to help you identify what part of the query caused the error.

The validation rules are part of the GraphQL specification and built into Strawberry, so there’s not really a way to customize this behavior. You can disable all validation by using the DisableValidation extension.

GraphQL type errors

When a query is executed each field must resolve to the correct type. For example non-null fields cannot return None.

import strawberry

@strawberry.type
class Query:
    @strawberry.field
    def hello() -> str:
        return None

schema = strawberry.Schema(query=Query)

{
  hello
}

{
  "data": null,
  "errors": [
    {
      "message": "Cannot return null for non-nullable field Query.hello.",
      "locations": [
        {
          "line": 2,
          "column": 3
        }
      ],
      "path": [
        "hello"
      ]
    }
  ]
}

Each error has a message, line, column and path to help you identify what part of the query caused the error.

Unhandled execution errors

Sometimes a resolver will throw an unexpected error due to a programming error or an invalid assumption. When this happens Strawberry catches the error and exposes it in the top level errors field in the response.

import strawberry

@strawberry.type
class User:
    name: str

@strawberry.type
class Query:
    @strawberry.field
    def user() -> User:
        raise Exception("Can't find user")

schema = strawberry.Schema(query=Query)

{
  user {
    name
  }
}

{
  "data": null,
  "errors": [
    {
      "message": "Can't find user",
      "locations": [
        {
          "line": 2,
          "column": 2
        }
      ],
      "path": [
        "user"
      ]
    }
  ]
}

Expected errors

If an error is expected then it is often best to express it in the schema. This allows the client to deal with the error in a robust way.

This could be achieved by making the field optional when there is a possibility that the data won’t exist:

from typing import Optional
import strawberry

@strawberry.type
class Query:
    @strawberry.field
    def get_user(self, id: str) -> Optional[User]:
        try:
            user = # get a user by their ID
            return user
        except UserDoesNotExist:
            return None

When the expected error is more complicated it’s a good pattern to instead return a union of types that either represent an error or a success response. This pattern is often adopted with mutations where it’s important to be able to return more complicated error details to the client.

For example, say you have a registerUser mutation where you need to deal with the possibility that a user tries to register with a username that already exists. You might structure your mutation type like this:

import strawberry

@strawberry.type
class RegisterUserSuccess:
    user: User

@strawberry.type
class UsernameAlreadyExistsError:
    username: str
    alternative_username: str

# Create a Union type to represent the 2 results from the mutation
Response = strawberry.union(
    "RegisterUserResponse",
    [RegisterUserSuccess, UsernameAlreadyExistsError]
)

@strawberry.mutation
def register_user(username: str, password: str) -> Response:
    if username_already_exists(username):
        return UsernameAlreadyExistsError(
            username=username,
            alternative_username=generate_username_suggestion(username)
        )

    user = create_user(username, password)
    return RegisterUserSuccess(
        user=user
    )

Then your client can look at the __typename of the result to determine what to do next:

mutation RegisterUser($username: String!, $password: String!) {
  registerUser(username: $username, password: $password) {
    __typename
    ... on UsernameAlreadyExistsError {
      alternativeUsername
    }
    ... on RegisterUserSuccess {
      id
      username
    }
  }
}

This approach allows you to express the possible error states in the schema and so provide a robust interface for your client to account for all the potential outcomes from a mutation.

Additional resources:

A Guide to GraphQL Errors | productionreadygraphql.com

200 OK! Error Handling in GraphQL | sachee.medium.com