Serialization with model_dump and Aliases
Control how Pydantic models convert to and from data using model_dump, field aliases, computed fields, and serialization options for clean API payloads.
Serialization with model_dump and Aliases is a free FastAPI Backend Development Bootcamp lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the FastAPI Backend Development Bootcamp learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Serialization vs Validation
Pydantic does two jobs: validation (untrusted input becomes a typed model) and serialization (a model becomes a dict or JSON to send out). This lesson focuses on controlling the output side precisely.
model_dump Basics
In Pydantic v2, model_dump() turns a model into a dict and model_dump_json() into a JSON string.
from pydantic import BaseModel
class User(BaseModel):
name: str
age: int
u = User(name='Ada', age=36)
print(u.model_dump())
print(u.model_dump_json())Including and Excluding Fields
Trim the output with include or exclude to hide internal or sensitive fields from a payload.
u.model_dump(exclude={'age'})
u.model_dump(include={'name'})Dropping Defaults and None
Use exclude_none=True or exclude_defaults=True to produce leaner payloads that omit empty values.
class Profile(BaseModel):
name: str
bio: str | None = None
Profile(name='Ada').model_dump(exclude_none=True)Field Aliases
External APIs often use names like userName while Python prefers user_name. An alias maps between them.
from pydantic import BaseModel, Field
class User(BaseModel):
user_name: str = Field(alias='userName')Serializing by Alias
By default model_dump uses the Python field names. Pass by_alias=True to output the alias names instead.
u = User(userName='ada')
print(u.model_dump())
print(u.model_dump(by_alias=True))populate_by_name
Set model_config = ConfigDict(populate_by_name=True) to accept either the field name or the alias when parsing input, giving you flexibility on both ends.
from pydantic import ConfigDict
class User(BaseModel):
model_config = ConfigDict(populate_by_name=True)
user_name: str = Field(alias='userName')Computed Fields
Expose derived values in the output with @computed_field. They appear in model_dump but are not part of the input.
from pydantic import computed_field
class Person(BaseModel):
first: str
last: str
@computed_field
@property
def full(self) -> str:
return self.first + ' ' + self.lastCustom Field Serializers
Use @field_serializer to control how a specific field is rendered, for example formatting a datetime or masking a secret.
from pydantic import field_serializer
class Account(BaseModel):
card: str
@field_serializer('card')
def mask(self, v: str) -> str:
return '****' + v[-4:]Alias Mapping in Plain Python
The by_alias transform is just key renaming. Here is the concept without Pydantic.
data = {'user_name': 'ada', 'user_age': 36}
alias = {'user_name': 'userName', 'user_age': 'userAge'}
out = {alias[k]: v for k, v in data.items()}
print(out)FastAPI Response Integration
FastAPI serializes return values through your response_model. Set response_model_by_alias and exclusion flags on the route to shape the JSON your API emits.
@app.get('/user', response_model=User, response_model_by_alias=True)
async def get_user():
return User(user_name='ada')Quick Check
Your model has user_name: str = Field(alias='userName'). What does model_dump(by_alias=True) produce for the key?
Recap
You mastered Pydantic serialization:
model_dump/model_dump_jsonwith include, exclude, and exclude_none.- Aliases plus
by_aliasandpopulate_by_name. - Computed fields and custom field serializers.
- Wiring it into FastAPI response models.
Frequently asked questions
Is the “Serialization with model_dump and Aliases” lesson free?
Yes — the full text of “Serialization with model_dump and Aliases” is free to read here on the web, and the FastAPI Backend Development Bootcamp course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the FastAPI Backend Development Bootcamp course, upgrade to CoddyKit PRO.
What will I learn in “Serialization with model_dump and Aliases”?
Control how Pydantic models convert to and from data using model_dump, field aliases, computed fields, and serialization options for clean API payloads. You practise FastAPI Backend Development Bootcamp with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start FastAPI Backend Development Bootcamp?
No prior experience is required. FastAPI Backend Development Bootcamp on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Serialization with model_dump and Aliases” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this FastAPI Backend Development Bootcamp lesson?
Yes. Every FastAPI Backend Development Bootcamp lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Pydantic Field Validation & Validators
- Custom Data Types & Settings
- Nested Models & Recursive Structures
- Serialization with model_dump and Aliases