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javapythondynamic-languages

top gotchas for someone moving from a static lang (java/c#) to dynamic language like python


What are the top gotchas for someone moving from a static lang (java/c#) to dynamic language like python?

It seems cool how things can be done, but renaming a method, or adding/removing parameters seems so risky!

Is the only solution to write tests for each method?


Solution

  • I would say that the number one gotcha is trying to write statically typed code in a dynamic language.

    Dont hesitate to use an identifier to point to a string and then a list in self-contained sections of code

    keys = 'foo bar foobar' # Imagine this coming in as an argument
    keys = keys.split() # Now the semantically chose name for the argument can be 
                        # reused As the semantically chosen name for a local variable
    

    don't hesitate to treat functions like regular values: they are. Take the following parser. Suppose that we want to treat all header tags alike and ul tags like ol tags.

    class Parser(HTMLParser):
        def __init__(self, html):
            self.feed(html)
    
        def handle_starttag(self, tag, attrs):
            parse_method = 'parse_' + tag    
            if hasattr(self, parse_method):  
                getattr(self, parse_method)(attrs)
    
    
        def parse_list(self, attrs):
            # generic code
    
        def parse_header(self, attrs):
           # more generic code
    
        parse_h1 = parse_h2 = parse_h3 = parse_h4 = parse_h5 = parse_h6 = parse_header
        parse_ol = parse_ul = parse_list
    

    This could be done by using less generic code in the handle_starttag method in a language like java by keeping track of which tags map to the same method but then if you decide that you want to handle div tags, you have to add that into the dispatching logic. Here you just add the method parse_div and you are good to go.

    Don't typecheck! Duck-type!

    def funtion(arg):
        if hasattr(arg, 'attr1') and hasattr(arg, 'attr2'):
             foo(arg):
        else:
             raise TypeError("arg must have 'attr1' and 'attr2'")
    

    as opposed to isinstance(arg, Foo). This lets you pass in any object with attr1 and attr2. This allows you to for instance pass in a tracing class wrapped around an object for debugging purposes. You would have to modify the class to do that in Java AFAIK.

    As pointed out by THC4k, another (more pythonic) way to do this is the EAPF idiom. I don't like this because I like to catch errors as early as possible. It is more efficient if you expect for the code to rarely fail though. Don't tell anybody I don't like it though our they'll stop thinking that I know how to write python. Here's an example courtesy of THC4k.

    try: 
        foo(arg): 
    except (AttributeError, TypeError): 
        raise InvalidArgumentError(foo, arg)
    

    It's a tossup as to if we should be catching the AttributeError and TypeError or just let them propagate to somewhere that knows how to handle them but this is just an example so we'll let it fly.