Validating detailed types in python dataclasses
Python 3.7 was released a while ago, and I wanted to test some of the fancy new dataclass+typing features. Getting hints to work right is easy enough, with both native types and those from the typing module:
>>> import dataclasses
>>> import typing as ty
>>>
... @dataclasses.dataclass
... class Structure:
... a_str: str
... a_str_list: ty.List[str]
...
>>> my_struct = Structure(a_str='test', a_str_list=['t', 'e', 's', 't'])
>>> my_struct.a_str_list[0]. # IDE suggests all the string methods :)
But one other thing that I wanted to try was forcing the type hints as conditions during runtime, i.e. it should not be possible for a dataclass with incorrect types to exist. It can be implemented nicely with __post_init__:
>>> @dataclasses.dataclass
... class Structure:
... a_str: str
... a_str_list: ty.List[str]
...
... def validate(self):
... ret = True
... for field_name, field_def in self.__dataclass_fields__.items():
... actual_type = type(getattr(self, field_name))
... if actual_type != field_def.type:
... print(f"\t{field_name}: '{actual_type}' instead of '{field_def.type}'")
... ret = False
... return ret
...
... def __post_init__(self):
... if not self.validate():
... raise ValueError('Wrong types')
This kind of validate function works for native types and custom classes, but not those specified by the typing module:
>>> my_struct = Structure(a_str='test', a_str_list=['t', 'e', 's', 't'])
Traceback (most recent call last):
a_str_list: '<class 'list'>' instead of 'typing.List[str]'
ValueError: Wrong types
Is there a better approach to validate an untyped list with a typing-typed one? Preferably one that doesn't include checking the types of all elements in any list, dict, tuple, or set that is a dataclass' attribute.
Answer
Instead of checking for type equality, you should use isinstance. But you cannot use a parametrized generic type (typing.List[int]) to do so, you must use the "generic" version (typing.List). So you will be able to check for the container type but not the contained types. Parametrized generic types define an __origin__ attribute that you can use for that.
Contrary to Python 3.6, in Python 3.7 most type hints have a useful __origin__ attribute. Compare:
# Python 3.6
>>> import typing
>>> typing.List.__origin__
>>> typing.List[int].__origin__
typing.List
and
# Python 3.7
>>> import typing
>>> typing.List.__origin__
<class 'list'>
>>> typing.List[int].__origin__
<class 'list'>
Python 3.8 introduce even better support with the typing.get_origin() introspection function:
# Python 3.8
>>> import typing
>>> typing.get_origin(typing.List)
<class 'list'>
>>> typing.get_origin(typing.List[int])
<class 'list'>
Notable exceptions being typing.Any, typing.Union and typing.ClassVar… Well, anything that is a typing._SpecialForm does not define __origin__. Fortunately:
>>> isinstance(typing.Union, typing._SpecialForm)
True
>>> isinstance(typing.Union[int, str], typing._SpecialForm)
False
>>> typing.get_origin(typing.Union[int, str])
typing.Union
But parametrized types define an __args__ attribute that store their parameters as a tuple; Python 3.8 introduce the typing.get_args() function to retrieve them:
# Python 3.7
>>> typing.Union[int, str].__args__
(<class 'int'>, <class 'str'>)
# Python 3.8
>>> typing.get_args(typing.Union[int, str])
(<class 'int'>, <class 'str'>)
So we can improve type checking a bit:
for field_name, field_def in self.__dataclass_fields__.items():
if isinstance(field_def.type, typing._SpecialForm):
# No check for typing.Any, typing.Union, typing.ClassVar (without parameters)
continue
try:
actual_type = field_def.type.__origin__
except AttributeError:
# In case of non-typing types (such as <class 'int'>, for instance)
actual_type = field_def.type
# In Python 3.8 one would replace the try/except with
# actual_type = typing.get_origin(field_def.type) or field_def.type
if isinstance(actual_type, typing._SpecialForm):
# case of typing.Union[…] or typing.ClassVar[…]
actual_type = field_def.type.__args__
actual_value = getattr(self, field_name)
if not isinstance(actual_value, actual_type):
print(f"\t{field_name}: '{type(actual_value)}' instead of '{field_def.type}'")
ret = False
This is not perfect as it won't account for typing.ClassVar[typing.Union[int, str]] or typing.Optional[typing.List[int]] for instance, but it should get things started.
Next is the way to apply this check.
Instead of using __post_init__, I would go the decorator route: this could be used on anything with type hints, not only dataclasses:
import inspect
import typing
from contextlib import suppress
from functools import wraps
def enforce_types(callable):
spec = inspect.getfullargspec(callable)
def check_types(*args, **kwargs):
parameters = dict(zip(spec.args, args))
parameters.update(kwargs)
for name, value in parameters.items():
with suppress(KeyError): # Assume un-annotated parameters can be any type
type_hint = spec.annotations[name]
if isinstance(type_hint, typing._SpecialForm):
# No check for typing.Any, typing.Union, typing.ClassVar (without parameters)
continue
try:
actual_type = type_hint.__origin__
except AttributeError:
# In case of non-typing types (such as <class 'int'>, for instance)
actual_type = type_hint
# In Python 3.8 one would replace the try/except with
# actual_type = typing.get_origin(type_hint) or type_hint
if isinstance(actual_type, typing._SpecialForm):
# case of typing.Union[…] or typing.ClassVar[…]
actual_type = type_hint.__args__
if not isinstance(value, actual_type):
raise TypeError('Unexpected type for \'{}\' (expected {} but found {})'.format(name, type_hint, type(value)))
def decorate(func):
@wraps(func)
def wrapper(*args, **kwargs):
check_types(*args, **kwargs)
return func(*args, **kwargs)
return wrapper
if inspect.isclass(callable):
callable.__init__ = decorate(callable.__init__)
return callable
return decorate(callable)
Usage being:
@enforce_types
@dataclasses.dataclass
class Point:
x: float
y: float
@enforce_types
def foo(bar: typing.Union[int, str]):
pass
Appart from validating some type hints as suggested in the previous section, this approach still have some drawbacks:
type hints using strings (
class Foo: def __init__(self: 'Foo'): pass) are not taken into account byinspect.getfullargspec: you may want to usetyping.get_type_hintsandinspect.signatureinstead;a default value which is not the appropriate type is not validated:
@enforce_type def foo(bar: int = None): pass foo()does not raise any
TypeError. You may want to useinspect.Signature.bindin conjuction withinspect.BoundArguments.apply_defaultsif you want to account for that (and thus forcing you to definedef foo(bar: typing.Optional[int] = None));variable number of arguments can't be validated as you would have to define something like
def foo(*args: typing.Sequence, **kwargs: typing.Mapping)and, as said at the beginning, we can only validate containers and not contained objects.
###Update
After this answer got some popularity and a library heavily inspired by it got released, the need to lift the shortcomings mentioned above is becoming a reality. So I played a bit more with the typing module and will propose a few findings and a new approach here.
For starter, typing is doing a great job in finding when an argument is optional:
>>> def foo(a: int, b: str, c: typing.List[str] = None):
... pass
...
>>> typing.get_type_hints(foo)
{'a': <class 'int'>, 'b': <class 'str'>, 'c': typing.Union[typing.List[str], NoneType]}
This is pretty neat and definitely an improvement over inspect.getfullargspec, so better use that instead as it can also properly handle strings as type hints. But typing.get_type_hints will bail out for other kind of default values:
>>> def foo(a: int, b: str, c: typing.List[str] = 3):
... pass
...
>>> typing.get_type_hints(foo)
{'a': <class 'int'>, 'b': <class 'str'>, 'c': typing.List[str]}
So you may still need extra strict checking, even though such cases feels very fishy.
Next is the case of typing hints used as arguments for typing._SpecialForm, such as typing.Optional[typing.List[str]] or typing.Final[typing.Union[typing.Sequence, typing.Mapping]]. Since the __args__ of these typing._SpecialForms is always a tuple, it is possible to recursively find the __origin__ of the hints contained in that tuple. Combined with the above checks, we will then need to filter any typing._SpecialForm left.
Proposed improvements:
import inspect
import typing
from functools import wraps
def _find_type_origin(type_hint):
if isinstance(type_hint, typing._SpecialForm):
# case of typing.Any, typing.ClassVar, typing.Final, typing.Literal,
# typing.NoReturn, typing.Optional, or typing.Union without parameters
return
actual_type = typing.get_origin(type_hint) or type_hint # requires Python 3.8
if isinstance(actual_type, typing._SpecialForm):
# case of typing.Union[…] or typing.ClassVar[…] or …
for origins in map(_find_type_origin, typing.get_args(type_hint)):
yield from origins
else:
yield actual_type
def _check_types(parameters, hints):
for name, value in parameters.items():
type_hint = hints.get(name, typing.Any)
actual_types = tuple(_find_type_origin(type_hint))
if actual_types and not isinstance(value, actual_types):
raise TypeError(
f"Expected type '{type_hint}' for argument '{name}'"
f" but received type '{type(value)}' instead"
)
def enforce_types(callable):
def decorate(func):
hints = typing.get_type_hints(func)
signature = inspect.signature(func)
@wraps(func)
def wrapper(*args, **kwargs):
parameters = dict(zip(signature.parameters, args))
parameters.update(kwargs)
_check_types(parameters, hints)
return func(*args, **kwargs)
return wrapper
if inspect.isclass(callable):
callable.__init__ = decorate(callable.__init__)
return callable
return decorate(callable)
def enforce_strict_types(callable):
def decorate(func):
hints = typing.get_type_hints(func)
signature = inspect.signature(func)
@wraps(func)
def wrapper(*args, **kwargs):
bound = signature.bind(*args, **kwargs)
bound.apply_defaults()
parameters = dict(zip(signature.parameters, bound.args))
parameters.update(bound.kwargs)
_check_types(parameters, hints)
return func(*args, **kwargs)
return wrapper
if inspect.isclass(callable):
callable.__init__ = decorate(callable.__init__)
return callable
return decorate(callable)
Thanks to @Aran-Fey that helped me improve this answer.