Skip to main content

Data handling made easy

Project description

https://badge.fury.io/py/pysimplemodel.svg https://img.shields.io/badge/python-3.6-blue.svg https://img.shields.io/github/license/lamenezes/simple-model.svg https://travis-ci.org/lamenezes/simple-model.svg?branch=master https://coveralls.io/repos/github/lamenezes/simple-model/badge.svg?branch=master

SimpleModel offers a simple way to handle data using classes instead of a plenty of lists and dicts.

It has simple objectives:

  • Define models and its fields easily using class attributes, type annotations or tuples (whatever suits your needs)

  • Support for field validation, cleaning and type conversion

  • Easy model conversion to dict

Quickstart

Installing

Open your favorite shell and run the following command:

pip install pysimplemodel

Example

Define your models using type annotations:

from simple_model import Model


class Person(Model):
    age: int
    height: float
    is_active: bool = True
    name: str

Simple model automatically creates an initializer for your model and you all set to create instances:

>> person = Person(age=18, height=1.67, name='John Doe')
>> person.name
'John Doe'

As you have noticed we haven’t informed a value for field is_active, but the model was still created. That’s becaused we’ve set a default value of True for it and the model takes care of assinging it automatically to the field:

>> person.is_active
True

Simple model also offers model validation. Empty fields are considered invalid and will raise errors upon validation. Let’s perform some tests using the previous Person model:

>> person = Person()
>> print(person.name)
None
>> person.validate()
Traceback (most recent call last):
    ...
EmptyField: 'height' field cannot be empty

Let’s say we want the height and age fields to be optional, that can be achieved with the following piece of code:

from simple_model import Model


class Person(Model):
    age: int = None
    height: float = None
    is_active: bool = True
    name: str

Now let’s test it:

>> person = Person(name='Jane Doe', is_active=False)
>> person.is_active
False
>> person.validate(raise_exception=False)
True

The last line won’t raise an exception which means the model instance is valid! In case you need the validation to return True or False instead of raising an exception that’s possible by doing the following:

>> person.validate(raise_exception=False)
True

You can also add custom validations by writing class methods prefixed by validate followed by the attribute name, e.g.

class Person:
    age: int
    height: float
    name: str

    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))

Let’s test it:

>> person = Person(name='John Doe', age=190)
>> person.validate()
Traceback (most recent call last):
    ...
ValidationError: Invalid value for age 190
>> other_person = Person(name='Jane Doe', height=-1.67)
>> other_person.validate()
Traceback (most recent call last):
    ...
ValidationError: Invalid value for height -1.67

It is important to note that models don’t validate types. Currently types are used for field value conversion. This is going to be explained later.

Simple model also supports cleaning the field values by defining custom methods named clean_ followed by the attribute name:

class Person:
    age: int
    name: str

    def clean_name(self, name):
        return name.strip()

>>> person = Person(age=18.0, name='John Doe ')
>>> person.name
'John Doe '
>> person.age
18.0
>>> person.clean()
>>> person.name
'John Doe'
>>> person.age  # all attributes are converted to its type before cleaning
18  # converted from float (18.0) to int (18)

Finally, simple model allows you to easily convert your model to dict type using python built-in function dict():

>>> dict(person)
{
    'age': 18,
    'name': 'John Doe'
}

Documentation

Docs on simple-model.rtfd.io

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pysimplemodel-2.0.1.tar.gz (8.5 kB view details)

Uploaded Source

File details

Details for the file pysimplemodel-2.0.1.tar.gz.

File metadata

File hashes

Hashes for pysimplemodel-2.0.1.tar.gz
Algorithm Hash digest
SHA256 b76efa91d9ed5633cf24b1471e6db10fa52c3e42195b59e62f2c7aaaacd83d8c
MD5 18d9c2175ca443fdc046976e75b31af6
BLAKE2b-256 a589e7d78695cf2e1eed0b4775bac19e4f7408d5303ae3ca57eb3c450613a66b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page