Some of the important concept on Fast API are covered on this blog.

Which are useful in  different scenario while doing the FastAPI Projects.

# pip install fastapi pydantic pydantic[email]
from pydantic import BaseModel,Field,EmailStr
from datetime import datetime,timezone
from fastapi.encoders import jsonable_encoder
class User(BaseModel):
    name: str = Field(..., alias="username")
    email:EmailStr
    age:int
    created_time: datetime | None = datetime.now(timezone.utc)
    read_time: datetime | None = None
    active:bool=True

1.jsonable_encoder(...) — from FastAPI / Pydantic Utils

jsonable_encoder is a utility function (from FastAPI, not directly Pydantic) that:

 Converts any Python object (like a Pydantic model, datetime, UUID, Decimal, etc.) into a JSON-compatible format — ready to be sent in a JSON response or stored as JSON.

Why use jsonable_encoder?

Because Python data types like datetime, UUID, etc., are not JSON serializable by default.

from fastapi.encoders import jsonable_encoder
from datetime import datetime

jsonable_encoder({"time": datetime.utcnow()})
# Output: {"time": "2025-05-05T12:34:56.789Z"}
# it will convert the datetime object into jsonable string

If you try to directly use json.dumps() without this encoder, it will raise a TypeError.

user=User(username="panta",email="[email protected]",age=25,active=False)
print(jsonable_encoder(user))
# it will convert complex data type (pydantic model into jsonable)

Output:

{'username': 'panta', 'email': '[email protected]', 'age': 25, 'created_time': '2025-05-05T07:02:11.523594Z', 'read_time': None, 'active': False}

2.skip_defaults=True (deprecated in Pydantic v2)

This flag is used when initializing a Pydantic model to tell it:

Don't include fields that have default values unless explicitly passed.

skip_defaults=True was previously used with .dict(skip_defaults=True) in Pydantic v1 — now deprecated in Pydantic v2.

So what should be done?

If you want to exclude default values when serializing, use:

In Pydantic v1:

user.dict(skip_defaults=True)

In Pydantic v2

user.model_dump(exclude_defaults=True)

user=User(username="panta",email="[email protected]",age=25,active=False)
print(user.model_dump(exclude_defaults=True))
# print(type(user.model_dump()))  #dict
# print(type(user.model_dump_json())) #str

Output:

{'name': 'panta', 'email': '[email protected]', 'age': 25, 'active': False}