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Python Coding Conventions
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   currently under development, your input appreciated
 
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Indentation and formatting
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  * 4 spaces of indentation
  * do not use tabs for source code formatting
  * tabs are okay within strings, but using \t is preferred


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Coding Principles
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  *  Class __init__ methods should return completed valid objects with all 
     fields initialized to a valid state.  If more fields are later added to the 
     object it is better for the constructor to fail due to insufficient 
     parameters than for code to "work" until later code makes reference to a 
     not-completely-initialized object.

     This is bad:
        o = gpObject()           # object still uninitialized
        o.setObjectName('hello')
        o.setObjectValue('world')

    This is better:
        o = gpObject(name='hello', value='world')

  * default values for parameters should be used responsibly.
   (this needs to be better defined)

    Never set a default value for the fundamental aspects of a class.

    This is bad:
        class GpDB():
            def __init__(self, dbid=-1, ...):
                self.dbid = dbid  # ^^ Setting the core aspects of the class

  * Where possible functions should have relatively few parameters. While it 
    is not always possible to keep the number of parameters low it leads to 
	clearer code.

  * If a function has more 5 or more parameters it is better to call that
    function with parameters set by name for clarity.

    This is unclear:
        db = GpDB(-1, 'p', 0, 'm', 's', 'u', 'localhost', 'localhost', 5432,
		          datadir, None)

    This is better:
        db = GpDB(content = -1, preferred_role = 'p', dbid = 0, role = 'p',
				  mode = 's', status = 'u', hostname = 'localhost',
				  address = 'localhost', port = 5432, datadir = '/gpdata/gp-1',
				  replicationPort = None)

  * Avoid masking functions in the builtin namespace:

    This is bad:
      def foo(name):
          str = "test"     # masks the builtin str() function
          x = str(name)    # this is an error due to the above

    This is better:
      def foo(name):
          test_string = "test"
          ...

  * Generic code should be placed in a generic location.
    If you have a generic class that turns an xml file into a generic python 
    xml object, don't place it in a file called gpcheckosXml.py.

  * Exceptions
    (need to develop some convention guidance)


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Commenting
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  *  Extensive commenting of code is encouraged.

  *  Comments should be informative and add value

     This is bad:
         x = 5      # Set the value to five

     This is better:
         x = 5      # The index of "hostname" in the above select statement

  *  When comment a function it is better to use comments that can be recognised
     by pydoc than ones that can are not recognised.  This means using strings
     for commenting rather than "#".

     This is bad:
     
       def foo():
           # Function description, not recognized by pydoc

     This is good:

       def foo():
           "Function desciption"

     or

       def foo()
           """
           Longer description
           With multiple lines
           """


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Naming Conventions
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  * Within the gppylib module class names should begin with the prefix Gp and 
    use camel-case rather than underscores:

      class GpExampleClass():
  
  * Function names should begin with a lowercase letter and use camel-case 
    rather than underscores:

      def doSomethingAmazing():

  * Function parameters should begin with a lowercase letter and use camel-case 
    rather than underscores:

      def doSomethingAmazing(usingSomeParameter):

  * Class member variables should be private (named prefixed with __).  
    By keeping class variables private and exposing them via accessor function 
    it allows the classes to be more easily modified in the future.   

      class GpExampleClass:
          def __init__(self, name):
              self.__name = name

          def getExampleName(self):
              return self.__name

  * Class member functions should be descriptive of the class.
    Since python is an interpreted dynamically typed language it can be 
    difficult to keep track of what calls what, having easily distinguished 
    function names makes it easier to track call graphs so that modifications 
    can be done more easily.

    This is bad, the function name is too generic which makes identifying 
    callers more difficult.

      class GpExampleClass:
          def getData():
              ...

    This is better, the function name is more distinct. 

      class GpExampleClass:
          def getExampleData():
              ...

  * Global variables should be named with a leading "g" prefix:

      gMyGlobalData = None

  * Global constant values should be all-caps separated by _:

      MY_GLOBAL_CONSTANT = 5