recursive-decorator 1.0.7

Description:

recursivedecorator 1.0.7

Decorator to apply a given decorator recursively on all function, inside a function/method, recursively.

What is recursive_decorator?
recursive_decorator is a decorator that allows us to decorate/trasform all functions along the stack call at runtime, motivated by the need to add/transform logics, to knownunknown functions, along the stack calls.

Notes:

Functions/Methods will not be replaced, new instances will be returned.
Function/Methods cannot be wrapped more then once with same transformer/decorator.




Installing
$ pip install recursive_decorator


Usage
import recursive_decorator
from recursive_decorator import recursive_decorator
define your decorator to apply recursively on all functions.
>>> def decorator(f):
...: def wrapper(*args, **kwargs):
...: print(f.__name__)
...: return f(*args, **kwargs)
...: return wrapper
Now using your decorator on function without using recursive_decorator will leads to the following output
>>> @decorator
...:def main_function():
...: sub_function()

>>> main_function()
main_function
Using recursive_decorator leads to
>>> @recursive_decorator(decorator)
...:def main_function():
...: sub_function()

>>> main_function()
main_function
sub_function
Furthermore, if sub_function has function calls, they will decorated to
>>> def sub_function():
...: another_function()

>>> @recursive_decorator(decorator)
...:def main_function():
...: sub_function()

>>> main_function()
main_function
sub_function
another_function
and so on…


Examples

Stop on Execption
We can wrap all functions with try except…
>>> import sys
>>> import ipdb
>>> from recursive_decorator import recursive_decorator

>>> def wrap_function_with_try_except(f):
...: def transformed_func(*args, **kwargs):
...: try:
...: return f(*args, **kwargs)
...: except:
...: ipdb.set_trace(sys._getframe().f_back)
...: return transformed_func

>>> def throws_exception():
...: raise Exception


>>> @recursive_decorator(wrap_function_with_try_except)
...:def function():
...: throws_exception()
...: pass

>>> function()
21 throws_exception()
---> 22 pass
23
If function will throw an error… ipdb session will start.


Profiler
We can set time profiler for all running functions.
>>> import time

>>> from recursive_decorator import recursive_decorator


>>> def duration_transformer(f):
...: def transformed_func(*args, **kwargs):
...: start_time = time.time()
...: value = f(*args, **kwargs)
...: end_time = time.time()
...: print("function {} duration is {} minutes"
...: .format(f.__name__, end_time - start_time))
...: return value
...: return transformed_func


>>> def waiting_function():
...: time.sleep(5)


>>> @recursive_decorator(duration_transformer)
...:def function():
...: waiting_function()

>>> function()
function waiting_function duration is 5.00511908531189 minutes
function function duration is 5.006134510040283 minutes