modelity

modelity

Data parsing and validation library for Python.

About

Modelity is a data parsing and validation library, written purely in Python, and based on the idea that data parsing and validation should be separated from each other, but being a part of single toolkit for ease of use.

In Modelity, data parsing is executed automatically once data model is instantiated or modified, while model validation needs to be explicitly called by the user. Thanks to this approach, models can be feed with data progressively (f.e. in response to user’s input), while still being able to validate at any time.

Features

• Declare models using type annotations
• Uses slots, not descriptors, making reading from a model as fast as possible
• Clean separation between data parsing stage (executed when model is created or modified) and model validation stage (executed on demand)
• Clean differentiation between unset fields (via special Unset sentinel) and optional fields set to None
• Easily customizable via pre- and postprocessors (executed during data parsing), model-level validators, and field-level validators (both executed during model validation)
• Ability do access any field via root model (the one for each validation is executed) from any custom validator, allowing to implement complex cross-field validation logic
• Ability to add custom validation context for even more complex validation strategies (like having different validators when model is created, when model is updated or when model is fetched over the API).
• Use of predefined error codes instead of error messages for easier customization of error reporting (if needed)
• Ease of providing custom types simply by defining __modelity_type_descriptor__ static method in user-defined type.

Rationale

Why I have created this library?

First reason is that I didn’t find such clean separation in known data parsing tools, and found myself needing such freedom in several projects - both private, and commercial ones. Separation between parsing and validation steps simplifies validators, as validators in models can assume that they are called when model is instantiated, therefore they can access all model’s fields without any extra checks.

Second reason is that I often found myself writing validation logic from the scratch for various reasons, especially for large models with lots of dependencies. Each time I had to validate some complex logic manually I was asking myself, why don’t merge all these ideas and make a library that already has these kind of helpers? For example, I sometimes needed to access parent model when validating field that itself is another, nested model. With Modelity, it is easy, as root model (the one that is validated) is populated to all nested models' validators recursively.

Third reason is that I wanted to finish my over 10 years old, abandoned project Formify (the name is already in use, so I have chosen new name for new project) which I was developing in free time at the beginning of my professional work during learning of Python. That project was originally made to handle form parsing and validation to be used along with web framework. Although the project was never finished, I’ve resurrected some ideas from it, especially parsing and validation separation. You can still find source code on my GH profile.

And last, but not least… I made this project for fun with a hope that maybe someone will find it useful :-)

Example

Here's an example data model created with Modelity:

import datetime
import typing

from modelity.model import Model

class Address(Model):
    address_line1: str
    address_line2: typing.Optional[str]
    city: str
    state_province: typing.Optional[str]
    postal_code: str
    country_code: str

class Person(Model):
    name: str
    second_name: typing.Optional[str]
    surname: str
    dob: datetime.date

Documentation

Please visit project's ReadTheDocs site: https://modelity.readthedocs.io/en/latest/.

License

This project is released under the terms of the MIT license.

Author

Maciej Wiatrzyk [e-mail]