attrs-strict
is a Python package which contains runtime validation for
attrs
data classes based on the types existing in the typing module.
- Rationale
- Quick start
- Building
- Installation
- Contributions
- License
- Code of Conduct
- Security Vulnerability Reporting
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
.
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])
print(sc)
SomeClass(list_of_numbers=[1, 2, 3, 4])
try:
SomeClass([1, 2, 3, "four"])
except ValueError as exception:
print(repr(exception))
SomeClass(list_of_numbers=[1, 2, 3, 4])
<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 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.
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)
names must be typing.List[typing.Tuple[str, str]] (got 123 that is a <class 'int'>) in ('Zoo', 123) in [('Moo', 'Moo'), ('Zoo', 123)]
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
.
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.
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.
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
.
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.
Please read the LICENSE file.
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].
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.