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https://github.com/bloomberg/attrs-strict
Provides runtime validation of attributes specified in Python 'attr'-based data classes.
https://github.com/bloomberg/attrs-strict
attributes python-attrs
Last synced: 1 day ago
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Provides runtime validation of attributes specified in Python 'attr'-based data classes.
- Host: GitHub
- URL: https://github.com/bloomberg/attrs-strict
- Owner: bloomberg
- License: apache-2.0
- Created: 2019-09-20T13:41:16.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2024-03-08T19:54:49.000Z (10 months ago)
- Last Synced: 2024-12-18T16:15:21.101Z (15 days ago)
- Topics: attributes, python-attrs
- Language: Python
- Homepage:
- Size: 136 KB
- Stars: 55
- Watchers: 8
- Forks: 19
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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# attrs runtime validation
`attrs-strict` is a Python package which contains runtime validation for
[`attrs`](https://github.com/python-attrs/attrs) data classes based on the types existing in the typing module.
## Menu
- [Rationale](#rationale)
- [Quick start](#quick-start)
- [Building](#building)
- [Installation](#installation)
- [Contributions](#contributions)
- [License](#license)
- [Code of Conduct](#code-of-conduct)
- [Security Vulnerability Reporting](#security-vulnerability-reporting)
## Rationale
The purpose of the library is to provide runtime validation for attributes specified in
[`attrs`](https://www.attrs.org/en/stable/) 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`](https://pypi.org/project/typing/).
## 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`
```python
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])
print(sc)
SomeClass(list_of_numbers=[1, 2, 3, 4])
try:
SomeClass([1, 2, 3, "four"])
except ValueError as exception:
print(repr(exception))
```
```console
SomeClass(list_of_numbers=[1, 2, 3, 4])
) in [1, 2, 3, 'four']>
```
Nested type exceptions are validated accordingly, 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.
```python
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]])
try:
SomeClass(names=[("Moo", "Moo"), ("Zoo", 123)])
except ValueError as exception:
print(exception)
```
```console
names must be typing.List[typing.Tuple[str, str]] (got 123 that is a ) 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`, `NewType` `Callable`, `Literal` 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.
`Callable` will validate if the callable function's annotation matches the type definition. If type does not specify any
annotations then all callables will pass the validation against it. Support for `Callable` is not available for
`python2`.
`Literal` only allows using instances of `int`, `str`, `bool`, `Enum` or valid `Literal` types. Type checking `Literal`
with any other type as argument raises `attrs_strict._error.UnsupportedLiteralError`.
```python
def fully_annotated_function(self, a: int, b: int) -> str:
...
def un_annonated_function(a, b):
...
@attr.s
class Something(object):
a = attr.ib(
validator=type_validator(), type=typing.Callable
) # Will work for any callable
b = attr.ib(validator=type_validator(), type=typing.Callable[[int, int], str])
Something(a=un_annonated_function, b=fully_annotated_function)
```
`TypeVars` or `Generics` are not supported yet but there are plans to support this in the future.
## Building
For development, the project uses [`tox`](http://tox.readthedocs.org/) 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](https://pypi.org/project/attrs-strict/).
Documentation is hosted on [readthedocs](https://attrs-strict.readthedocs.io/en/latest/).
For the latest version, on github `pip install git+https://github.com/bloomberg/attrs-strict`.
## Contributions
We :heart: 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](../../issues); 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](../../pulls), please make sure you read our
[Contribution Guidelines](https://github.com/bloomberg/.github/blob/main/CONTRIBUTING.md).
## License
Please read the [LICENSE](LICENSE) file.
## Code of Conduct
This project has adopted a [Code of Conduct](https://github.com/bloomberg/.github/blob/main/CODE_OF_CONDUCT.md). 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.