FunctionWrapper is a design pattern used when dealing with relatively complicated functions. The wrapper function typically performs some prologue and epilogue tasks like
- allocating and disposing resources
- checking pre- and post-conditions
- caching / recycling a result of a slow computation
but otherwise it should be fully compatible with the wrapped function, so it can be used instead of it. (This is related to the DecoratorPattern.)
As of Python 2.1 and the introduction of nested scopes, wrapping a function is easy:
{{{#python def wrap(func, pre, post):
- def call(*args, **kwargs):
- pre(func, *args, **kwargs) result = func(*args, **kwargs) post(func, *args, **kwargs) return result
}}}
Now, let's wrap something up:
{{{#python def trace_in(func, *args, **kwargs):
print "Entering function", func.name
def trace_out(func, *args, **kwargs):
print "Leaving function", func.name
def calc(x, y):
- return x + y
}}}
The wrapping effect is:
>>> f = wrap(calc, trace_in, trace_out) >>> print calc(1, 2) 3 >>> print f(1, 2) Entering function calc Leaving function calc 3
Of course, a wrapper would normally perform some more useful task. Have a look [http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/412719 here] for a recipe how to wrap a function that processes files so that the result is recycled from a cache file if appropriate.