SimpleModel offers a simple way to handle data using classes instead of a plenty of lists and dicts.
It has simple objectives:
- Define your fields easily (just a tuple, nor dicts or instances of type classes whatever)
- Support for field validation
- Conversion to dict
That's it. If you want something more complex there are plenty of libraries and frameworks that does a lot of cool stuff.
Table of Contents
pip install pysimplemodelfrom simple_model import Model
from simple_model.exceptions import ValidationError
class Person(Model):
age: int
height: float
name: str
weight: float
class Meta:
allow_empty = ('height', 'weight')
def clean_name(self, name):
return name.strip()
def validate_age(self, age):
if age < 0 or age > 150:
raise ValidationError('Invalid value for age "{!r}"'.format(age))
def validate_height(self, height):
if height <= 0:
raise ValidationError('Invalid value for height "{!r}"'.format(age))>>> person = Person(age=18.0, name='John Doe ')
>>> person.name
'John Doe '
>>> person.clean()
>>> person.name
'John Doe'
>>> person.age
18
>>> person.validate(raise_exception=False)
True
>>> dict(person)
{
'age': 18,
'height': '',
'name': 'John Doe',
'weight': '',
}Model values aren't validated until the validated method is called:
>>> person = Person() # no exception
>>> person.validate()
...
EmptyField: name field cannot be empty
>>> person = Person(name='Jane Doe', age=60)
>>> person.validate() # now it's ok!You may change the validate method to return a boolean instead of raising an exception:
>>> person = Person()
>>> person.validate(raise_exception=False)
False
>>> person = Person(name='Jane Doe', age=60)
>>> person.validate(raise_exception=False)
TrueSometimes it is necessary to clean some values of your models, this can be easily done using simple-model:
class CleanPerson(Model):
age: int
name: str
def clean_name(self, name):
return name.strip()
>>> person = CleanPerson(name='John Doe \n', age='10')
>>> person.name, person.age
('John Doe \n', '10')
>>> person.clean()
>>> person.name, person.age
('John Doe', 10)It's possible to build many models in a single step, it can be done by passing an iterable to the build_many method.
>>> people = [
{'name': 'John Doe'},
{'name': 'John Doe II'},
]
>>> models = Person.build_many(people)To convert to dict is pretty straight-forward task:
>>> person = Person(name='Jane Doe', age=60)
>>> dict(person)
{
'age': 60,
'height': None,
'name': 'Jane Doe',
'weight': None,
}Simple model also supports dict conversion of nested models:
class SocialPerson(Model):
friend: Person
name: str
>>> person = Person(name='Jane Doe', age=60)
>>> other_person = SocialPerson(name='John Doe', friend=person)
>>> dict(other_person)
{
'friend': {
'age': 60,
'height': None,
'name': 'Jane Doe',
'weight': None,
},
'name': 'John Doe',
}It also supports nested models as lists:
import typing
class MoreSocialPerson(Model):
friends: typing.List[Friend]
name: str
>>> person = Person(name='Jane Doe', age=60)
>>> other_person = Person(name='John Doe', age=15)
>>> social_person = MoreSocialPerson(name='Foo Bar', friends=[person, other_person])
>>> dict(social_person)
{
'name': 'Foo Bar',
'friends': [
{
'age': 60,
'height': None,
'name': 'Jane Doe',
'weight': None,
},
{
'age': 15,
'height': None,
'name': 'John Doe',
'weight': None,
}
]
}
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