Merge pull request #961 from Unidata/issue959

have Variable.setncattr fail when setting _FillValue

Changelog

@@ -9,6 +9,7 @@
  * remove underline ANSI in Dataset string representation (pull request #956).
  * remove newlines from string representation (pull request #960).
  * fix for issue #957 (size of scalar var is a float since numpy.prod(())=1.0).
+ * make sure Variable.setncattr fails to set _FillValue (issue #959).
 
  version 1.5.1.2 (tag v1.5.1.2rel)
 ==================================

netCDF4/_netCDF4.pyx

@@ -4112,6 +4112,13 @@ netCDF attribute with the same name as one of the reserved python
 attributes."""
         cdef nc_type xtype
         xtype=-99
+        # issue #959 - trying to set _FillValue results in mysterious
+        # error when close method is called so catch it here. It is
+        # already caught in __setattr__.
+        if name == '_FillValue':
+            msg='_FillValue attribute must be set when variable is '+\
+            'created (using fill_value keyword to createVariable)'
+            raise AttributeError(msg)
         if self._grp.data_model != 'NETCDF4': self._grp._redef()
         _set_att(self._grp, self._varid, name, value, xtype=xtype, force_ncstring=self._ncstring_attrs__)
         if self._grp.data_model != 'NETCDF4': self._grp._enddef()

test/tst_atts.py

@@ -91,6 +91,19 @@ def setUp(self):
         v1.seqatt = SEQATT
         v1.stringseqatt = STRINGSEQATT
         v1.setncattr_string('stringseqatt_array',STRINGSEQATT) # array of NC_STRING
+        # issue #959: should not be able to set _FillValue after var creation
+        try:
+            v1._FillValue(-999.)
+        except AttributeError:
+            pass
+        else:
+            raise ValueError('This test should have failed.')
+        try:
+            v1.setncattr('_FillValue',-999.)
+        except AttributeError:
+            pass
+        else:
+            raise ValueError('This test should have failed.')
         # issue #485 (triggers segfault in C lib
         # with version 1.2.1 without pull request #486)
         f.foo = NP.array('bar','S')