What is the difference between Geoprocessing Map object vs. MapDocument object in Python

Question

I have the following code:

mxd["C1"] = arcpy.mapping.MapDocument(os.path.join(fRoot, filename))
mxd["C2"] = [arcpy.mapping.MapDocument(os.path.join(fRoot, filename))]

C1 creates a geoprocessing Map object

C2 creates a MapDocument object

What is the difference between them in terms of functionality and/or limitations?

http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//00s30000000n000000

UPDATE: Still not really sure what the difference is but found out in order to run my program I required to have geoprocessing Map objects and not MapDocument objects.

Things like mxd.save(), and assigning the dataframe only seem to work with the geoprocessing object.

Answer 1

You're getting the same exact thing in both instances. Nothing to see here, move along.

When you print an object in Python, it runs the str operator on it*. str(MapDocument) says something like Geoprocessing Map Object or whatever. When you do str(list) it will use the repr operator on each item in it, so it will get something like [<arcpy.MapDocument object at 0x00000000>] where the <...> part is what repr returned. Both str and repr are simply string representations (with different implicit semantics) of the same thing, this object implements both and returns something slightly different for either.

*Note: As an implementation detail, in CPython it will actually go through the native tp_print method in most cases which is functionally the same thing.

Answer 2

Not an answer, just an example of the output of str() and repr() given a MapDocument object:

>>> mxd = arcpy.mapping.MapDocument(r"c:\Program Files\ArcGIS\DeveloperKit10.0\Samples\data\BloomfieldTownship\BloomfieldTownship.mxd")
>>> repr(mxd)
'<MapDocument object at 0xde68d0[0x53fa520]>'
>>> str(mxd)
'<geoprocessing Map object object at 0x053FA520>'

And for the map (data frame) object:

>>> df = arcpy.mapping.ListDataFrames(mxd)[0]
>>> repr(df)
'<DataFrame object at 0x5420670[0x5434688]>'
>>> str(df)
'<geoprocessing Data Frame object object at 0x05434688>'