Pydantic is a Python library for data parsing and validation. It uses the type hinting mechanism of the newer versions of Python (version 3.6 onwards) and validates the types during the runtime. Pydantic defines BaseModel class. It acts as the base class for creating user defined models.

Following code defines a Student class as a model based on BaseModel.

from typing import List
from pydantic import BaseModel
class Student(BaseModel):
   id: int
   name :str
   subjects: List[str] = []

The attributes of the Student class are declared with type hints. Note that the subjects attribute is of List type defined in typing module and of builtin list type.

We can populate an object of Student class with a dictionary with matching structure as follows −

>>> data = {
   ''id'': 1,
   ''name'': ''Ravikumar'',
   ''subjects'': ["Eng", "Maths", "Sci"],
}
>>> s1=Student(**data)
>>> print (s1)
id=1 name=''Ravikumar'' subjects=[''Eng'', ''Maths'', ''Sci'']
>>> s1
Student(id=1, name=''Ravikumar'', subjects=[''Eng'', ''Maths'', ''Sci''])
>>> s1.dict()
{''id'': 1, ''name'': ''Ravikumar'', ''subjects'': [''Eng'', ''Maths'', ''Sci'']}

Pydantic will automatically get the data types converted whenever possible. For example, even if the id key in the dictionary is assigned a string representation of a number (such as ”123”), it will coerce it into an integer. But whenever not possible, an exception will be raised.

>>> data = {
   ''id'': [1,2],
   ''name'': ''Ravikumar'',
   ''subjects'': ["Eng", "Maths", "Sci"],
}
>>> s1=Student(**data)
Traceback (most recent call last):
   File "<pyshell#13>", line 1, in <module>
      s1=Student(**data)
   File "pydanticmain.py", line 406, in
pydantic.main.BaseModel.__init__
pydantic.error_wrappers.ValidationError: 1 validation error
for Student
id
   value is not a valid integer (type=type_error.integer)

Pydantic also contains a Field class to declare metadata and validation rules for the model attributes. First modify the Student class to apply Field type on “name” attribute as follows −

from typing import List
from pydantic import BaseModel, Field
class Student(BaseModel):
   id: int
   name :str = Field(None, title="The description of the item", max_length=10)
   subjects: List[str] = []

Populate the data as shown below. The name here is exceeding the max_length stipulated. Pydantic throws ValidationError as expected.

>>> data = {
   ''id'': 1,
   ''name'': ''Ravikumar Sharma'',
   ''subjects'': ["Eng", "Maths", "Sci"],
}
>>> s1=Student(**data)
Traceback (most recent call last):
   File "<pyshell#28>", line 1, in <module>
      s1=Student(**data)
   File "pydanticmain.py", line 406, in
pydantic.main.BaseModel.__init__
pydantic.error_wrappers.ValidationError: 1 validation error for Student
name
   ensure this value has at most 10 characters
   (type=value_error.any_str.max_length; limit_value=10)

Pydantic models can be used to map with ORM models like SQLAlchemy or Peewee.