I am trying to use some AOP in my Python programming, but I do not have any experience of the various libraries that exist.
So my question are:
What AOP support exists for Python? And what are the advantages of the differents libraries between them?
I've found some, but I don't know how they compare:
In which context will I use these?
I have two applications, written in Python, which have typically methods which compute taxes and other money things. I'd like to be able to write a "skeleton" of a functionality, and customize it at runtime, for example changing the way local taxes are applied (by country, or state, or city, etc.) without having to overload the full stack.
See S.Lott's link about Python decorators for some great examples, and see the defining PEP for decorators.
Python had AOP since the beginning, it just didn't have an impressive name. In Python 2.4 the decorator syntax was added, which makes applying decorators very nice syntactically.
Maybe if you want to apply decorators based on rules you would need a library, but if you're willing to mark the relevant functions/methods when you declare them you probably don't.
Here's an example for a simple caching decorator (I wrote it for this question):
import pickle, functools
def cache(f):
_cache = {}
def wrapper(*args, **kwargs):
key = pickle.dumps((args, kwargs))
if key not in _cache:
_cache[key] = f(*args, **kwargs) # call the wrapped function, save in cache
return _cache[key] # read value from cache
functools.update_wrapper(wrapper, f) # update wrapper's metadata
return wrapper
import time
@cache
def foo(n):
time.sleep(2)
return n*2
foo(10) # first call with parameter 10, sleeps
foo(10) # returns immediately