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:

   1 def wrap(pre, post):
   2     def decorate(func):
   3         def call(*args, **kwargs):
   4             pre(func, *args, **kwargs)
   5             result = func(*args, **kwargs)
   6             post(func, *args, **kwargs)
   7            return result
   8         return call
   9     return decorate

The additional decorate function is needed to work with the Python 2.4 decorator syntax.

Now, let's wrap something up:

   1 def trace_in(func, *args, **kwargs):
   2    print "Entering function",  func.__name__
   3 
   4 def trace_out(func, *args, **kwargs):
   5    print "Leaving function", func.__name__
   6 
   7 @wrap(trace_in, trace_out)
   8 def calc(x, y):
   9    return x + y

The wrapping effect is:

   1 >>> print calc(1, 2)
   2 Entering function calc
   3 Leaving function calc
   4 3

Of course, a wrapper would normally perform some more useful task. Have a look here for a recipe how to wrap a function that processes files so that the result is recycled from a cache file if appropriate.