Python 3.5+ library for integration testing and data validation through configurable and optional runtime type hint enforcement.
| Branch | Status |
|---|---|
| Master: |     |
| Dev: |    |
Enforce.py is a Python 3.5+ library for integration testing and data validation through configurable and optional runtime type hint enforcement. It uses the standard type hinting syntax (defined in PEP 484).
NOTICE: Python versions 3.5.2 and earlier (3.5.0-3.5.2) are now deprecated. Only Python versions 3.5.3+ would be supported. Deprecated versions will no longer be officially supported in Enforce.py version 0.4.x.
Stable 0.3.x - Stable and ready for every day use version
pip install enforce
Dev current - "Bleeding edge" features that, while are fairly consistent, may change.
pip install git+https://github.com/RussBaz/enforce.git@dev
Type enforcement is done using decorators around functions that you desire to be checked. By default, this decorator will ensure that any variables passed into the function call matches its declaration (invariantly by default). This includes integers, strings, etc. as well as lists, dictionaries, and more complex objects. Currently, the type checking is eager.
Note, eager means that for a large nested structure, every item in that structure will be checked. This may be a nightmare for performance! See caveats for more details.
You can also apply the runtime_validation decorator around a class, and it
will enforce the types of every method in that class.
Note: this is a development feature and is not as thoroughly tested as the function decorators.
>>> import enforce
>>>
>>> @enforce.runtime_validation
... def foo(text: str) -> None:
... print(text)
>>>
>>> foo('Hello World')
Hello World
>>>
>>> foo(5)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/william/.local/lib/python3.5/site-packages/enforce/decorators.py", line 106, in universal
_args, _kwargs = enforcer.validate_inputs(parameters)
File "/home/william/.local/lib/python3.5/site-packages/enforce/enforcers.py", line 69, in validate_inputs
raise RuntimeTypeError(exception_text)
enforce.exceptions.RuntimeTypeError:
The following runtime type errors were encountered:
Argument 'text' was not of type <class 'str'>. Actual type was <class 'int'>.
>>>
@runtime_validation
def foo(a: typing.Callable[[int, int], str]) -> str:
return a(5, 6)
def bar(a: int, b: int) -> str:
return str(a * b)
class Baz:
def __call__(self, a: int, b: int) -> str:
return bar(a, b)
foo(bar)
foo(Baz())
T = typing.TypeVar('T', int, str)
@runtime_validation
class Sample(typing.Generic[T]):
def get(self, data: T) -> T:
return data
@runtime_validation
def foo(data: Sample[int], arg: int) -> int:
return data.get(arg)
@runtime_validation
def bar(data: T, arg: int) -> T:
return arg
sample_good = Sample[int]()
sample_bad = Sample()
with self.assertRaises(TypeError):
sample = Sample[list]()
foo(sample_good, 1)
with self.assertRaises(RuntimeTypeError):
foo(sample_bad, 1)
bar(1, 1)
with self.assertRaises(RuntimeTypeError):
bar('str', 1)
Applying this decorator to a class will automatically apply the decorator to every method in the class.
@runtime_validation
class DoTheThing(object):
def __init__(self):
self.do_the_stuff(5, 6.0)
def do_the_stuff(self, a: int, b: float) -> str:
return str(a * b)
Enforce.py supports typed NamedTuples.
MyNamedTuple = typing.NamedTuple('MyNamedTuple', [('param', int)])
# Optionally making a NamedTuple typed
# It will now enforce its type signature
# and will throw exceptions if there is a type mismatch
# MyNamedTuple(param='str') will now throw an exception
MyNamedTuple = runtime_validation(MyNamedTuple)
# This function now accepts only NamedTuple arguments
@runtime_validation
def foo(data: MyNamedTuple):
return data.param
You can assign functions to groups, and apply options on the group level.
'None' leaves previous value unchanged.
All available global settings:
default_options = {
# Global enforce.py on/off switch
'enabled': None,
# Group related settings
'groups': {
# Dictionary of type {<name: str>: <status: bool>}
# Sets the status of specified groups
# Enable - True, disabled - False, do not change - None
'set': {},
# Sets the status of all groups to False before updating
'disable_previous': False,
# Sets the status of all groups to True before updating
'enable_previous': False,
# Deletes all the existing groups before updating
'clear_previous': False,
# Updating the default group status - default group is not affected by other settings
'default': None
},
# Sets the type checking mode
# Available options: 'invariant', 'covariant', 'contravariant', 'bivariant' and None
'mode': None
}
# Basic Example
@runtime_validation(group='best_group')
def foo(a: List[str]):
pass
foo(1) # No exception as the 'best_group' was not explicitly enabled
# Group Configuration
enforce.config({'groups': {'set': {'best_group': True}}}) # Enabling group 'best_group'
with self.assertRaises(RuntimeTypeError):
foo(1)
enforce.config({
'groups': {
'set': {
'foo': True
},
'disable_previous': True,
'default': False
}
}) # Disable everything but the 'foo' group
# Using foo's settings
@runtime_validation(group='foo')
def test1(a: str): return a
# Using foo's settings but locally overriding it to stay constantly enabled
@runtime_validation(group='foo', enabled=False)
def test2(a: str): return a
# Using bar's settings - deactivated group -> no type checking is performed
@runtime_validation(group='bar')
def test3(a: str): return a
# Using bar's settings but overriding locally -> type checking enabled
@runtime_validation(group='bar', enabled=True)
def test4(a: str): return a
with self.assertRaises(RuntimeTypeError):
test1(1)
test2(1)
test3(1)
with self.assertRaises(RuntimeTypeError):
test4(1)
foo(1)
enforce.config({'enabled': False}) # Disables enforce.py
test1(1)
test2(1)
test3(1)
test4(1)
foo(1)
enforce.config({'enabled': True}) # Re-enables enforce.py
enforce.config(reset=True) # Resets global settings to their default state
Currently, iterators, generators and coroutines type checks are not supported (mostly). However, it is still possible to check if an object is iterable.
We are still working on the best approach for lazy type checking (checking list items only when accessed) and lazy type evaluation (accepting strings as type hints).
Currently, the type checker will examine every object in a list. This means that for large structures performance can be a nightmare.
Class decorators are not as well tested, and you may encounter a bug or two. Please report an issue if you do find one and we'll try to fix it as quickly as possible.
Please check out our active issues on our Github page to see what work needs to be done, and feel free to create a new issue if you find a bug.
Actual development is done in the 'dev' branch, which is merged to master at milestones.
FAQs
Python 3.5+ library for integration testing and data validation through configurable and optional runtime type hint enforcement.
We found that enforce demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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