saytosid/attrs-strict

Provides runtime validation of attributes specified in Python 'attr'-based data classes.

attrs runtime validation

attrs-strict is a Python package that contains runtime validation for attrs data classes based on the types existing in the typing module.

Menu

• Rationale
• Quick start
• Building
• Installation
• Contributions
• License
• Code of Conduct
• Security Vulnerability Reporting

Rationale

The purpose of the library is to provide runtime validation for attributes specified in attrs data classes. The types supported are all the builtin types and most of the ones defined in the typing library. For Python 2, the typing module is available through the backport found here.

Quick Start

Type enforcement is based on the type attribute set on any field specified in an attrs dataclass. If the type argument is not specified no validation takes place.

pip install attrs-strict

from typing import List

import attr

from attrs_strict import type_validator

>>> @attr.s
... class SomeClass(object):
...     list_of_numbers = attr.ib(
...         validator=type_validator(),
...         type=List[int]
...     )
...

>>> sc = SomeClass([1,2,3,4])
>>> sc
SomeClass(list_of_numbers=[1, 2, 3, 4])

>>> try:
...    other = SomeClass([1,2,3,'four'])
... except ValueError as error:
...    print(repr(error))
attrs_strict._error.AttributeTypeError: list_of_numbers must be
typing.List[int] (got four that is a <class 'str'>) in [1, 2, 3, 'four']

Nested type exceptions are validated acordingly, and a backtrace to the initial container is maintained to ease with debugging. This means that if an exception occurs because a nested element doesn't have the correct type, the representation of the exception will contain the path to the specific element that caused the exception.

from typing import List, Tuple

import attr

from attrs_strict import type_validator

>>> @attr.s
... class SomeClass(object):
...     names = attr.ib(
...        validator=type_validator(), type=List[Tuple[str, str]]
...     )

>>> sc = SomeClass(names=[('Moo', 'Moo'), ('Zoo',123)])

attrs_strict._error.AttributeTypeError: names must be
    typing.List[typing.Tuple[str, str]] (got 123 that is a <class 'int'>) in
    ('Zoo', 123) in [('Moo', 'Moo'), ('Zoo', 123)]

What is currently supported ?

Currently there's support for simple types and types specified in the typing module: List, Dict, DefaultDict, Set, Union, Tuple and any combination of them. This means that you can specify nested types like List[List[Dict[int, str]]] and the validation would check if attribute has the specific type.

Callables, TypeVars or Generics are not supported yet but there are plans to support this in the future.

Building

For development, the project uses tox in order to install dependencies, run tests and generate documentation. In order to be able to do this, you need tox pip install tox and after that invoke tox in the root of the project.

Installation

Run pip install attrs-strict to install the latest stable version from PyPi. Documentation is hosted on readthedocs.

For the latest version, on github pip install git+https://github.com/bloomberg/attrs-strict.

Contributions

We ❤️ contributions.

Have you had a good experience with this project? Why not share some love and contribute code, or just let us know about any issues you had with it?

We welcome issue reports here; be sure to choose the proper issue template for your issue, so that we can be sure you're providing the necessary information.

Before sending a Pull Request, please make sure you read our Contribution Guidelines.

License

Please read the LICENSE file.

Code of Conduct

This project has adopted a Code of Conduct. If you have any concerns about the Code, or behavior which you have experienced in the project, please contact us at [email protected].

Security Vulnerability Reporting

If you believe you have identified a security vulnerability in this project, please send email to the project team at [email protected], detailing the suspected issue and any methods you've found to reproduce it.

Please do NOT open an issue in the GitHub repository, as we'd prefer to keep vulnerability reports private until we've had an opportunity to review and address them.