While working with dataclasses, type hints are good but what I'm looking also for is a Validation of passed values (such as string of max length 50, int with upper limit of 100 etc)
Is there anyway to validate passed value ? For example, Pydantic has these Validators. I'm looking for something native without adding external libraries. My only solution is:
from dataclasses import dataclass
def validate_str(max_length):
def _validate(f):
def wrapper(self, value):
if type(value) is not str:
raise TypeError(f"Expected str, got: {type(value)}")
elif len(value) > max_length:
raise ValueError(
f"Expected string of max length {max_length}, got string of length {len(value)} : {value}" # noqa
)
else:
return f(self, value)
return wrapper
return _validate
@dataclass
class Example:
"""Class for keeping track of an item in inventory."""
@property
def name(self):
return self._name
@name.setter
@validate_str(max_length=50)
def name(self, value):
self._name = value
where validate_str
is just a custom decorator method to check length of provided value, but then I repeat myself.
I would like to pass validator somehow in same row of dataclass attribute as:
@dataclass
class InventoryItem:
"""Class for keeping track of an item in inventory."""
name: str = validate_somehow()
unit_price: float = validate_somehow()
quantity_on_hand: int = 0
CodePudding user response:
The ideal approach would be to use a modified version of the Validator
example from the Python how-to guide on descriptors.
For example:
from abc import ABC, abstractmethod
from dataclasses import dataclass, MISSING
class Validator(ABC):
def __set_name__(self, owner, name):
self.private_name = '_' name
def __get__(self, obj, obj_type=None):
return getattr(obj, self.private_name)
def __set__(self, obj, value):
self.validate(value)
setattr(obj, self.private_name, value)
@abstractmethod
def validate(self, value):
"""Note: subclasses must implement this method"""
class String(Validator):
# You may or may not want a default value
def __init__(self, default: str = MISSING, minsize=None, maxsize=None, predicate=None):
self.default = default
self.minsize = minsize
self.maxsize = maxsize
self.predicate = predicate
# override __get__() to return a default value if one is not passed in to __init__()
def __get__(self, obj, obj_type=None):
return getattr(obj, self.private_name, self.default)
def validate(self, value):
if not isinstance(value, str):
raise TypeError(f'Expected {value!r} to be an str')
if self.minsize is not None and len(value) < self.minsize:
raise ValueError(
f'Expected {value!r} to be no smaller than {self.minsize!r}'
)
if self.maxsize is not None and len(value) > self.maxsize:
raise ValueError(
f'Expected {value!r} to be no bigger than {self.maxsize!r}'
)
if self.predicate is not None and not self.predicate(value):
raise ValueError(
f'Expected {self.predicate} to be true for {value!r}'
)
@dataclass
class A:
y: str = String(default='DEFAULT', minsize=5, maxsize=10, predicate=str.isupper) # Descriptor instance
x: int = 5
a = A()
print(a)
a = A('TESTING!!')
print(a)
try:
a.y = 'testing!!'
except Exception as e:
print('Error:', e)
try:
a = A('HEY')
except Exception as e:
print('Error:', e)
try:
a = A('HELLO WORLD!')
except Exception as e:
print('Error:', e)
try:
a.y = 7
except Exception as e:
print('Error:', e)
Output:
A(y='DEFAULT', x=5)
A(y='TESTING!!', x=5)
Error: Expected <method 'isupper' of 'str' objects> to be true for 'testing!!'
Error: Expected 'HEY' to be no smaller than 5
Error: Expected 'HELLO WORLD!' to be no bigger than 10
Error: Expected 7 to be an str