Decorator for validating arguments and/or result of functions and methods of a class against annotations.
Can be used in synchronous or asynchronous version.
Validation is supported using pydantic.BaseModel and validated_dc.ValidatedDC.
You can easily add support for any other validator. To do this, you need to write your own validator-function and specify it in the settings for decorator (how to do this - see the examples below).
Note: if the result of the function has no annotation, the result is expected to be None.
pip install valdecBased on the validator pydantic.BaseModel:
pip install pydanticfrom typing import List, Optional
from pydantic import BaseModel, StrictInt, StrictStr
from valdec.decorators import validate
# from valdec.decorators import async_validate # Use for async functions
@validate # all arguments with annotations and return
def func(i: StrictInt, s: StrictStr) -> StrictInt:
return i
assert func(1, "s") == 1
@validate("i", exclude=True) # exclude "i" (only "s" and return)
def func(i: StrictInt, s: StrictStr) -> StrictInt:
return int(i)
assert func("1", "s") == 1
# For example, an Api got a json-string and decoded it:
data_for_group = [
{"name": "Peter", "profile": {"age": 22, "city": "Samara"}},
{"name": "Elena", "profile": {"age": 20, "city": "Kazan"}},
]
class Profile(BaseModel):
age: StrictInt
city: StrictStr
class Student(BaseModel):
name: StrictStr
profile: Profile
@validate("s", "group") # only "s" and "group"
def func(i: StrictInt, s: StrictStr, group: Optional[List[Student]] = None):
assert i == "i not int" # because "i" is not validated
assert isinstance(s, str)
for student in group:
# `student` is now an instance of `Student`
# (This conversion can be disabled!)
assert isinstance(student, Student)
assert isinstance(student.name, str)
assert isinstance(student.profile.age, int)
return group
result = func("i not int", "string", data_for_group)
# The result can be any, because it is not validated.., now this is a list:
assert isinstance(result, list)It is possible to enable validation with validated_dc.ValidatedDC. To do this, change the reference to the validator-function in the decorator settings:
pip install validated-dcfrom dataclasses import dataclass
from typing import List, Optional
from valdec.data_classes import Settings
from valdec.decorators import validate as _validate
from valdec.validator_validated_dc import validator
from validated_dc import ValidatedDC
custom_settings = Settings(
validator=validator, # function for validation
is_replace_args=True, # default
is_replace_result=True, # default
extra={} # default
)
def validate(*args, **kwargs): # define new decorator
kwargs["settings"] = custom_settings
return _validate(*args, **kwargs)
# The new decorator can now be used:
@validate # all arguments with annotations and return
def func(i: int, s: str) -> int:
return i
assert func(1, "s") == 1
@validate("s") # only "s"
def func(i: int, s: str) -> int:
return i
assert func("not int", "s") == "not int"
@validate("s", "return") # only "s" and return
def func(i: int, s: str) -> int:
return int(i)
assert func("1", "s") == 1
@validate("i", exclude=True) # exclude "i" (only "s" and return)
def func(i: int, s: str) -> int:
return int(i)
assert func("1", "s") == 1
data_for_group = [
{"name": "Peter", "profile": {"age": 22, "city": "Samara"}},
{"name": "Elena", "profile": {"age": 20, "city": "Kazan"}},
]
@dataclass
class Profile(ValidatedDC):
age: int
city: str
@dataclass
class Student(ValidatedDC):
name: str
profile: Profile
@validate("s", "group") # only "s" and "group"
def func(i: int, s: str, group: Optional[List[Student]] = None):
assert i == "i not int" # because "i" is not validated
assert isinstance(s, str)
for student in group:
# `student` is now an instance of `Student`
# (This behavior can be changed by is_replace_args=False in the
# Settings instance)
assert isinstance(student, Student)
assert isinstance(student.name, str)
assert isinstance(student.profile.age, int)
return group
result = func("i not int", "string", data_for_group)
# The result can be any, because it is not validated.., now this is a list:
assert isinstance(result, list)ValidationArgumentsError is raised on an arguments validation error, and a ValidationReturnError on a result validation error:
from typing import Optional
from pydantic import StrictInt, StrictStr
from valdec.decorators import validate
from valdec.errors import ValidationArgumentsError, ValidationReturnError
class Foo:
@validate # all arguments with annotations and return
def bar_1(self, i: StrictInt, s: Optional[StrictStr] = None):
pass
@validate("return") # only "return"
def bar_2(self, i: StrictInt, s: Optional[StrictStr] = None):
return i
foo = Foo()
foo.bar_1(1, "2") # ok
try:
foo.bar_1(1, 2)
except ValidationArgumentsError as error:
print(type(error), error, "\n")
foo.bar_2(None, 1) # ok
try:
foo.bar_2(1, 2)
except ValidationReturnError as error:
print(type(error), error)