Response

You can use ormar Models in fastapi response_model instead of pydantic models.

You can of course also mix ormar.Models with pydantic ones if you need to.

One of the most common tasks in responses is excluding certain fields that you do not want to include in response data.

This can be achieved in several ways in ormar so below you can review your options and select the one most suitable for your situation.

Excluding fields in response

Optional fields

Note that each field that is optional is not required, that means that Optional fields can be skipped both in response and in requests.

Field is not required if (any/many/all) of following:

• Field is marked with nullable=True
• Field has default value or function provided, i.e. default="Test"
• Field has a server_default value set
• Field is an autoincrement=True primary_key field (note that ormar.Integer primary_key is autoincrement by default)

Example:

class User(ormar.Model):
    class Meta:
        tablename: str = "users"
        metadata = metadata
        database = database

    id: int = ormar.Integer(primary_key=True)
    email: str = ormar.String(max_length=255)
    password: str = ormar.String(max_length=255)
    first_name: str = ormar.String(max_length=255, nullable=True)
    last_name: str = ormar.String(max_length=255)
    category: str = ormar.String(max_length=255, default="User")

In above example fields id (is an autoincrement Integer), first_name ( has nullable=True) and category (has default) are optional and can be skipped in response and model will still validate.

If the field is nullable you don't have to include it in payload during creation as well as in response, so given example above you can:

# note that app is an FastApi app
@app.post("/users/", response_model=User) # here we use ormar.Model in response
async def create_user(user: User):  # here we use ormar.Model in request parameter
    return await user.save()

That means that if you do not pass i.e. first_name in request it will validate correctly (as field is optional), save in the database and return the saved record without this field (which will also pass validation).

Note

Note that although you do not pass the field value, the field itself is still present in the response_model that means it will be present in response data and set to None.

If you want to fully exclude the field from the result read on.

FastApi response_model_exclude

Fastapi has response_model_exclude that accepts a set (or a list) of field names.

That has it's limitation as ormar and pydantic accepts also dictionaries in which you can set exclude/include columns also on nested models (more on this below)

Warning

Note that you cannot exclude required fields when using response_model as it will fail during validation.

@app.post("/users/", response_model=User, response_model_exclude={"password"})
async def create_user(user: User):
    return await user.save()

Above endpoint can be queried like this:

from starlette.testclient import TestClient

client = TestClient(app)

with client as client:
        # note there is no pk
        user = {
            "email": "test@domain.com",
            "password": "^*^%A*DA*IAAA",
            "first_name": "John",
            "last_name": "Doe",
        }
        response = client.post("/users/", json=user)
        # note that the excluded field is fully gone from response
        assert "password" not in response.json()
        # read the response and initialize model out of it
        created_user = User(**response.json())
        # note pk is populated by autoincrement
        assert created_user.pk is not None
        # note that password is missing in initialized model too
        assert created_user.password is None

Note

Note how in above example password field is fully gone from the response data.

Note that you can use this method only for non-required fields.

Nested models excludes

Despite the fact that fastapi allows passing only set of field names, so simple excludes, when using response_model_exclude, ormar is smarter.

In ormar you can exclude nested models using two types of notations.

One is a dictionary with nested fields that represents the model tree structure, and the second one is double underscore separated path of field names.

Assume for a second that our user's category is a separate model:

class BaseMeta(ormar.ModelMeta):
    metadata = metadata 
    database = database

class Category(ormar.Model):
    class Meta(BaseMeta):
        tablename: str = "categories"

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=255)    
    priority: int = ormar.Integer(nullable=True)


class User(ormar.Model):
    class Meta(BaseMeta):
        tablename: str = "users"

    id: int = ormar.Integer(primary_key=True)
    email: str = ormar.String(max_length=255)
    password: str = ormar.String(max_length=255)
    first_name: str = ormar.String(max_length=255, nullable=True)
    last_name: str = ormar.String(max_length=255)
    category: Optional[Category] = ormar.ForeignKey(Category, related_name="categories")

If you want to exclude priority from category in your response, you can still use fastapi parameter.

@app.post("/users/", response_model=User, response_model_exclude={"category__priority"})
async def create_user(user: User):
    return await user.save()

Note that you can go in deeper models with double underscore, and if you want to exclude multiple fields from nested model you need to prefix them with full path. In example response_model_exclude={"category__priority", "category__other_field", category__nested_model__nested_model_field} etc.

Note

To read more about possible excludes and how to structure your exclude dictionary or set visit fields section of documentation

Note

Note that apart from response_model_exclude parameter fastapi supports also other parameters inherited from pydantic. All of them works also with ormar, but can have some nuances so best to read dict part of the documentation.

Exclude in Model.dict()

Alternatively you can just return a dict from ormar.Model and use .

Like this you can also set exclude/include as dict and exclude fields on nested models too.

Warning

Not using a response_model will cause api documentation having no response example and schema since in theory response can have any format.

@app.post("/users2/", response_model=User)
async def create_user2(user: User):
    user = await user.save()
    return user.dict(exclude={'password'})
    # could be also something like return user.dict(exclude={'category': {'priority'}}) to exclude category priority

Note

Note that above example will nullify the password field even if you pass it in request, but the field will be still there as it's part of the response schema, the value will be set to None.

If you want to fully exclude the field with this approach simply don't use response_model and exclude in Model's dict()

Alternatively you can just return a dict from ormar model. Like this you can also set exclude/include as dict and exclude fields on nested models.

Note

In theory you loose validation of response here but since you operate on ormar.Models the response data have already been validated after db query (as ormar model is pydantic model).

So if you skip response_model altogether you can do something like this:

@app.post("/users4/") # note no response_model
async def create_user4(user: User):
    user = await user.save()
    return user.dict(exclude={'last_name'})

Note

Note that when you skip the response_model you can now exclude also required fields as the response is no longer validated after being returned.

The cost of this solution is that you loose also api documentation as response schema in unknown from fastapi perspective.

Generate pydantic model from ormar.Model

Since task of excluding fields is so common ormar has a special way to generate pydantic models from existing ormar.Models without you needing to retype all the fields.

That method is get_pydantic() method available on all models classes.

# generate a tree of models without password on User and without priority on nested Category
ResponseUser = User.get_pydantic(exclude={"password": ..., "category": {"priority"}})
@app.post("/users3/", response_model=ResponseUser) # use the generated model here
async def create_user3(user: User):
    return await user.save()

Note

To see more examples and read more visit get_pydantic part of the documentation.

Warning

The get_pydantic method generates all models in a tree of nested models according to an algorithm that allows to avoid loops in models (same algorithm that is used in dict(), select_all() etc.)

That means that nested models won't have reference to parent model (by default ormar relation is bidirectional).

Note also that if given model exists in a tree more than once it will be doubled in pydantic models (each occurrence will have separate own model). That way you can exclude/include different fields on different leafs of the tree.

Separate pydantic model

The final solution is to just create separate pydantic model manually. That works exactly the same as with normal fastapi application so you can have different models for response and requests etc.

Sample:

import pydantic

class UserBase(pydantic.BaseModel):
    class Config:
        orm_mode = True

    email: str
    first_name: str
    last_name: str


@app.post("/users3/", response_model=UserBase) # use pydantic model here
async def create_user3(user: User): #use ormar model here (but of course you CAN use pydantic also here)
    return await user.save()