def auto_pytest_magic(
auto_function_: Callable,
*args,
auto_allow_exceptions_: Union[Tuple[BaseException], Tuple] = (),
auto_runs_: int = 50,
auto_verify_: Optional[Callable[[Scenario], Any]] = None,
**kwargs,
) -> None:
"""A convenience function that builds a new test function inside the calling module and
passes into it test cases using the `auto_pytest` decorator. The least effort and most magical
way to integrate with pytest.
By default auto_pytest_magic uses type annotations to automatically decide on strategies via the
hypothesis builds strategy. You can override individual strategies by passing them in under
the corresponding `*arg` or `**kwarg` OR you can pass in specific values that must be used for
certain parameters while letting others be auto generated.
All `*arg` and `**kwargs` are automatically passed along to
`hypothesis.strategies.builds` to enable this. Non strategies are automatically converted
to strategies using `hypothesis.strategies.just`.
Except for the following options:
- *auto_allow_exceptions_*: A tuple of exceptions that are acceptable for the function to raise
and will no be considered a test error.
- *auto_runs_*: Number of strategies combinations to run the given function against.
- *auto_verify_*: An optional callback function that will be called to allow custom verification
of the functions return value. The callback function should raise an AssertionError if the
return value does not match expectations.
Example:
def my_function(number_1: int, number_2: int) -> int:
return number_1 + number_2
auto_pytest_magic(my_function)
"""
called_from = inspect.stack()[1]
module = inspect.getmodule(called_from[0])
def test_function(test_case):
test_case()
uuid = str(uuid4()).replace("-", "")
test_function.__name__ = f"test_auto_{auto_function_.__name__}_{uuid}"
setattr(module, test_function.__name__, test_function)
pytest.mark.parametrize(
"test_case",
auto_test_cases(
auto_function_,
*args,
auto_allow_exceptions_=auto_allow_exceptions_,
auto_limit_=auto_runs_,
auto_verify_=auto_verify_,
**kwargs,
),
)(test_function)
def auto_pytest(
auto_function_: Callable,
*args,
auto_allow_exceptions_: Union[Tuple[BaseException], Tuple] = (),
auto_runs_: int = 50,
auto_verify_: Optional[Callable[[Scenario], Any]] = None,
**kwargs,
) -> None:
"""A decorator that marks a parameterized pytest function passing along a callable test case.
The function should take a `test_case` parameter.
By default auto_pytest uses type annotations to automatically decide on strategies via the
hypothesis builds strategy. You can override individual strategies by passing them in under
the corresponding `*arg` or `**kwarg` OR you can pass in specific values that must be used for
certain parameters while letting others be auto generated.
All `*arg` and `**kwargs` are automatically passed along to
`hypothesis.strategies.builds` to enable this. Non strategies are automatically converted
to strategies using `hypothesis.strategies.just`.
Except for the following options:
- *auto_allow_exceptions_*: A tuple of exceptions that are acceptable for the function to raise
and will no be considered a test error.
- *auto_runs_*: Number of strategies combinations to run the given function against.
- *auto_verify_*: An optional callback function that will be called to allow custom verification
of the functions return value. The callback function should raise an AssertionError if the
return value does not match expectations.
Example:
def my_function(number_1: int, number_2: int) -> int:
return number_1 + number_2
@auto_pytest(my_function)
def test_auto_pytest(test_case):
test_case()
-----
"""
return pytest.mark.parametrize(
"test_case",
auto_test_cases(
auto_function_,
*args,
auto_allow_exceptions_=auto_allow_exceptions_,
auto_limit_=auto_runs_,
auto_verify_=auto_verify_,
**kwargs,
),
)