devtools

Note

Admission: I (the primary developer of Pydantic) also develop python-devtools.

python-devtools (pip install devtools) provides a number of tools which are useful during Python development, including debug() an alternative to print() which formats output in a way which should be easier to read than print as well as giving information about which file/line the print statement is on and what value was printed.

Pydantic integrates with devtools by implementing the __pretty__ method on most public classes.

In particular debug() is useful when inspecting models:

from datetime import datetime

from devtools import debug

from pydantic import BaseModel


class Address(BaseModel):
    street: str
    country: str
    lat: float
    lng: float


class User(BaseModel):
    id: int
    name: str
    signup_ts: datetime
    friends: list[int]
    address: Address


user = User(
    id='123',
    name='John Doe',
    signup_ts='2019-06-01 12:22',
    friends=[1234, 4567, 7890],
    address=dict(street='Testing', country='uk', lat=51.5, lng=0),
)
debug(user)
print('\nshould be much easier read than:\n')
print('user:', user)

Will output in your terminal:

devtools_example.py:30 <module>
    user: User(
        id=123,
        name='John Doe',
        signup_ts=datetime.datetime(2019, 6, 1, 12, 22),
        friends=[
            1234,
            4567,
            7890,
        ],
        address=Address(
            street='Testing',
            country='uk',
            lat=51.5,
            lng=0.0,
        ),
    ) (User)

should be much easier read than:

user: id=123 name='John Doe' signup_ts=datetime.datetime(2019, 6, 1, 12, 22) friends=[1234, 4567, 7890] address=Address(street='Testing', country='uk', lat=51.5, lng=0.0)

debug() is a development-time tool: it prints to the terminal of a process you're watching. The closest equivalent for a deployed application is Logfire, where models and validations show up as structured output you can browse and query.