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POA more elegant way for this python decorator
 

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  1. POA more elegant way for this python decorator
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    <p>Basically I want a decorator with an argument list that contains more than just a function to be able to be called from both the @- and regular forms. I've "designed" a quick workaround, but it's ugly and executes a function in @-form immediately, which is an undesired side-effect (that's due to return body_two() of course).</p> <pre><code>def status_display_with_comment(comment, closure = None): def body_one(function = None): def body_two(): print(comment) #an ugly workaround to be able to run both the @- and regular forms if function != None: print("Entering", function.__name__) function() print("Exited", function.__name__) elif closure != None: print("Entering", closure.__name__) closure() print("Exited", closure.__name__) return body_two() return body_one def a_function(): print('a_function executes') @status_display_with_comment(comment = 'some comment') def a_function_with_comment(): print('a_function_with_comment executes') a_function_status_display_with_comment = status_display_with_comment(closure = a_function, comment = 'a comment') a_function_status_display_with_comment() </code></pre> <p>Thanks in advance.</p> <p>P.S.: I have to wrap my head around that whole closure thing. Which is fun considering it could be done recursively like in Scheme (a long time ago for me).</p>
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    1. COBe careful going too far with the Scheme analogies. You _can_ write anything recursively in Python, just as in Scheme… but Python doesn't have tail-call optimization, so you often don't want to. For a half-dozen levels of recursion, that's not a problem, but when you start thinking of recursive folding to map over a list of arbitrary length, you're probably doing it wrong.
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    2. CO@abarnert, so how do you deal with tree structures then? A list, contained within a list, which is in itself an embedded list and so on, the one of arbitrary depth? My solution for now: def tree_printer(a_tree): for item in a_tree: if type(item) is list or type(item) is tuple: tree_printer(item) else: print(item, end=' ')
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    3. COIn Scheme, if your trees are known to be not very deep, you can use naive recursion, but if they may be arbitrarily deep, you have to transform that into tail recursion. In Python, transforming to tail recursion doesn't help, so you instead have to transform into iterative code. (That's the most important difference, but not the only one. For example, Python has comprehensions, iterative map/filter/reduce, all the stuff in itertools, etc. to make it easier to write iterative code, so often, even when recursion would work, it's not the easiest way to do it.)
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