Dataclass Type Validator Library
Project description
dataclass-type-validator
The dataclass-type-validator
is a type validation library for the properties of dataclasses.dataclass
using Python type hint information.
Installation
pip install dataclass-type-validator
or add dataclass-type-validator
line to requirements.txt
A Simple Example
Explicitly calling dataclass_type_validator from within your dataclass
from dataclasses import dataclass
from typing import List
from dataclass_type_validator import dataclass_type_validator
from dataclass_type_validator import TypeValidationError
@dataclass()
class User:
id: int
name: str
friend_ids: List[int]
def __post_init__(self):
dataclass_type_validator(self)
# Valid User
User(id=10, name='John Smith', friend_ids=[1, 2])
# => User(id=10, name='John Smith', friend_ids=[1, 2])
# Invalid User
try:
User(id='a', name=['John', 'Smith'], friend_ids=['a'])
except TypeValidationError as e:
print(e)
# => TypeValidationError: Dataclass Type Validation (errors = {
# 'id': "must be an instance of <class 'int'>, but received <class 'str'>",
# 'name': "must be an instance of <class 'str'>, but received <class 'list'>",
# 'friend_ids': 'must be an instance of typing.List[int], but there are some errors:
# ["must be an instance of <class \'int\'>, but received <class \'str\'>"]'})
The same, but using the class decorator instead
from dataclasses import dataclass
from typing import List
from dataclass_type_validator import dataclass_validate
from dataclass_type_validator import TypeValidationError
@dataclass_validate
@dataclass()
class User:
id: int
name: str
friend_ids: List[int]
# Valid User
User(id=10, name='John Smith', friend_ids=[1, 2])
# => User(id=10, name='John Smith', friend_ids=[1, 2])
# Invalid User
try:
User(id='a', name=['John', 'Smith'], friend_ids=['a'])
except TypeValidationError as e:
print(e)
# => TypeValidationError: Dataclass Type Validation (errors = {
# 'id': "must be an instance of <class 'int'>, but received <class 'str'>",
# 'name': "must be an instance of <class 'str'>, but received <class 'list'>",
# 'friend_ids': 'must be an instance of typing.List[int], but there are some errors:
# ["must be an instance of <class \'int\'>, but received <class \'str\'>"]'})
You can also pass the strict
param (which defaults to False) to the decorator:
@dataclass_validate(strict=True)
@dataclass(frozen=True)
class SomeList:
values: List[str]
# Invalid item contained in typed List
try:
SomeList(values=["one", "two", 3])
except TypeValidationError as e:
print(e)
# => TypeValidationError: Dataclass Type Validation Error (errors = {
# 'x': 'must be an instance of typing.List[str], but there are some errors:
# ["must be an instance of <class \'str\'>, but received <class \'int\'>"]'})
You can also pass the before_post_init
param (which defaults to False) to the decorator,
to force the type validation to occur before __post_init__()
is called. This can be used
to ensure the types of the field values have been validated before your higher-level semantic
validation is performed in __post_init__()
.
@dataclass_validate(before_post_init=True)
@dataclass
class User:
id: int
name: str
def __post_init__(self):
# types of id and name have already been checked before this is called.
# Otherwise, the following check will throw a TypeError if user passed
# `id` as a string or other type that cannot be compared to int.
if id < 1:
raise ValueError("superuser not allowed")
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