No. You cannot strictly speaking, overload Python functions. One reason being is that types are not specified in function definitions (the language is Dynamically Typed anyway, and accepts optional function arguments.)

If you want different function behaviour based on different types, you have to introduce some conditional logic. I wanted to ‘overload’ this function so it was either supplied a filepath to a raster, which it then converted to an array, or would be supplied a NumPy array directly:

def DrapedOverHillshade(FileName, DrapeName, thiscmap='gray',drape_cmap='gray',
                            colorbarlabel='Elevation in meters',clim_val = (0,0),
                            drape_alpha = 0.6, ShowColorbar = False):

So DrapeName could either be type numpy.ndarray or str. At the appropriate point in the function, I added a check to find what type had actually been passed, then called a relevant function if a file -> array conversion was needed.

if isinstance(DrapeName, str):
  raster_drape = LSDMap_IO.ReadRasterArrayBlocks(DrapeName)
elif isinstance(DrapeName, np.ndarray):
  raster_drape = DrapeName
  print "DrapeName supplied is of type: ", type(DrapeName)
  raise ValueError('DrapeName must either be a string to a filename, \
  or a numpy ndarray type. Please try again.')

Not this uses isinstance(object, type) rather than something which might be more intuitive like if type(DrapeName) is type for example. This is because type() only checks for the exact type specified - and would ignore any subtype or subclass of the object specified.

It would also have been possible to not check the type at all, and just use a try, catch statement, first treating DrapeArray as a string, then as an array. (And actually, some people might consider this to be the more pythonic way of doing it…)