[Python-Dev] PEP 8 updates/clarifications

Barry Warsaw barry at python.org
Mon Dec 12 17:26:28 CET 2005

On Sun, 2005-12-11 at 11:20 -0500, Jim Fulton wrote:

> This seems outdated.  My impression, in part from time spent
> working with the Python Labs guys, is that it is fine to have public
> data sttributes even for non-"record" types.  In fact, I would argue that
> any time you would be tempted to provide "getFoo()" and "setFoo(v)"
> for some "private attribute _foo", it would be better to make it
> public.  I certainly find "blah.foo" and "blah.foo = v" to be much
> better than "blah.getFoo()" and blah.setFoo(v)".
> Certainly, properties provide a safety belt.  I would argue it this
> way: Python APIs can include attributes as well as methods.
> Exposure of an attribute need not constrain the implementation, thanks
> to properties.  OTOH, I wouldn't bother with a property unless it's needed.

Let me know what you think about this language (from my in-progress
update of PEP 8):

    Designing for inheritance

      Always decide whether a class's methods and instance variables
      (collectively: "attributes") should be public or non-public.  Public
      attributes are those that you expect unrelated clients of your class to
      use, with your commitment to avoid backward incompatible changes.
      Non-public attributes are those that are not intended to be used by
      third parties; you make no guarantees that non-pubic attributes won't
      change or even be removed.

      We don't use the term "private" here, since no attribute is really
      private in Python (without a generally unnecessary amount of work).
      However, another category of attribute are those which, while not being
      public, are intended for use by subclasses (often called "protected" in
      other languages).  Some classes are designed to be inherited from,
      either to extend or modify aspects of the class's behavior.  When
      designing such a class, take care to make explicit decisions about which
      attributes are public, which are non-public but useful for subclasses, and
      which are truly only to be used by your base class.

      With this in mind, here are the Pythonic guidelines:

      - Public attributes should have no leading underscores.

      - If your public attribute name collides with a reserved keyword, append
        a single trailing underscore to your attribute name.  This is
        preferable to an abbreviation or corrupted spelling.  E.g. "class_"
        is preferable to "cls" or "klass".

        Note 1: See the argument name recommendation above for class methods.

[BAW: I'll include this new text in a later followup]

      - For simple public data attributes, it is fine to expose just the
        attribute name, without complicated accessor/mutator methods.  Keep in
        mind that Python provides an easy path to future enhancement, should
        you find that a simple data attribute needs to grow functional
        behavior.  In that case, use properties to hide functional
        implementation behind simple data attribute access syntax.

        Note 1: Properties only work on new-style classes.

        Note 2: Try to keep the functional behavior side-effect free, although
        side-effects such as caching are generally fine.

      - If your class is intended to be subclassed, and you have attributes
        that you do not want subclasses to use, consider naming them with
        double leading underscores and no trailing underscores.  This invokes
        Python's name mangling algorithm, where the name of the class is
        mangled into the attribute name.  This helps avoid attribute name
        collisions should subclasses inadvertently contain attributes with the
        same name.

        Note 1: Note that only the simple class name is used in the mangled
        name, so if a subclass chooses both the same class name and attribute
        name, you can still get name collisions.

        Note 2: Name mangling can make certain uses, such as debugging, less
        convenient.  However the name mangling algorithm is well documented
        and easy to perform manually.


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