human
Solve the following python programming problem given the following code:
def _calc_concat_over(datasets, dim, data_vars, coords) : 
    '
    Determine which dataset variables need to be concatenated in the result,
    and which can simply be taken from the first dataset.
    ' 
    def process_subset_opt(opt, subset) : 
        if (subset == 'coords') : 
            subset_long_name = 'coordinates' 
else : 
            subset_long_name = 'data variables' 
if isinstance (opt, basestring) : 
            if (opt == 'different') : 
                def differs(vname) : 
                    v = datasets [0].variables [vname] 
                    return any (((not ds.variables [vname].equals (v)) for ds in datasets [1 :])) 
concat_new = set ((k for k in getattr (datasets [0], subset) if ((k not in concat_over) and differs (k)))) 
else : 
                if (opt == 'all') : 
                    concat_new = (set (getattr (datasets [0], subset)) - set (datasets [0].dims)) 
else : 
                    if (opt == 'minimal') : 
                        concat_new = set () 
else : 
                        raise ValueError (('unexpected value for concat_%s: %s' % (subset, opt))) 
else : 
            invalid_vars = [k for k in opt if (k not in getattr (datasets [0], subset))] 
            if invalid_vars : 
                raise ValueError (('some variables in %s are not %s on the first dataset: %s' % (subset, subset_long_name, invalid_vars))) 
concat_new = set (opt) 
return concat_new 
concat_over = set () 
    for ds in process_subset_opt : 
        concat_over.update ((k for (k, v) in ds.variables.items () if (dim in v.dims))) 
concat_over.update (process_subset_opt (data_vars, 'data_vars')) 
    concat_over.update (process_subset_opt (coords, 'coords')) 
    if (dim in datasets [0]) : 
        concat_over.add (dim) 
return concat_over 

    
    

    Fix the buggy line: for ds in process_subset_opt :
assistant
#Here is Python program to determine which dataset variables need to be concatenated in the result,
.

for ds in datasets :