.travis.yml

 language: python
-dist: xenial
+dist: bionic
 cache: pip
 
 addons:

Changelog

- version 1.5.2 (not yet released)
+ version 1.5.3 (tag v1.5.3rel)
+==============================
+ * make sure arrays are masked that are not filled when auto_fill is off 
+   (issue #972).
+ * python 3.8 binary wheels.
+
+ version 1.5.2 (tag v1.5.2rel)
 ==============================
  * fix for scaling bug when _Unsigned attribute is set and byteorder of data
    does not match native byteorder (issue #930).

README.md

@@ -10,6 +10,10 @@
 ## News
 For details on the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
 
+10/27/2019: Version [1.5.3](https://pypi.python.org/pypi/netCDF4/1.5.3) released]. Fix for
+[issue #972](https://github.com/Unidata/netcdf4-python/issues/972), plus binary wheels for
+python 3.8.
+
 09/03/2019: Version [1.5.2](https://pypi.python.org/pypi/netCDF4/1.5.2) released. Bugfixes, no new features.
 
 05/06/2019: Version [1.5.1.2](https://pypi.python.org/pypi/netCDF4/1.5.1.2) released. Fixes another slicing

debian/changelog

-netcdf4-python (1.5.2-2) UNRELEASED; urgency=medium
+netcdf4-python (1.5.3-1) unstable; urgency=medium
 
+  * New upstream release.
   * Bump Standards-Version to 4.4.1, no changes.
 
- -- Bas Couwenberg <sebastic@debian.org>  Mon, 30 Sep 2019 19:28:16 +0200
+ -- Bas Couwenberg <sebastic@debian.org>  Wed, 23 Oct 2019 09:21:45 +0200
 
 netcdf4-python (1.5.2-1) unstable; urgency=medium
 

netCDF4/_netCDF4.pyx

 """
-Version 1.5.2
+Version 1.5.3
 ---------------
 - - -
 
@@ -1206,7 +1206,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.5.2"
+__version__ = "1.5.3"
 
 # Initialize numpy
 import posixpath
@@ -4581,7 +4581,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # type, signed or unsigned, because the byte ranges are too
             # small to assume one of the values should appear as a missing
             # value unless a _FillValue attribute is set explicitly."
-            if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']:
+            if no_fill != 1 or self.dtype.str[1:] not in ['u1','i1']:
                 fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
                 has_fillval = data == fillval
                 # if data is an array scalar, has_fillval will be a boolean.

setup.py

@@ -596,7 +596,7 @@ else:
 
 setup(name="netCDF4",
       cmdclass=cmdclass,
-      version="1.5.2",
+      version="1.5.3",
       long_description="netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project is hosted on a `GitHub repository <https://github.com/Unidata/netcdf4-python>`_ where you may access the most up-to-date source.",
       author="Jeff Whitaker",
       author_email="jeffrey.s.whitaker@noaa.gov",

test/tst_masked.py

@@ -7,12 +7,14 @@ from numpy import ma
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from numpy.random.mtrand import uniform
 import netCDF4
+from numpy.ma import masked_all
 
 # test automatic conversion of masked arrays, and
 # packing/unpacking of short ints.
 
 # create an n1dim by n2dim random ranarr.
 FILE_NAME = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
+FILE_NAME2 = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
 ndim = 10
 ranarr = 100.*uniform(size=(ndim))
 ranarr2 = 100.*uniform(size=(ndim))
@@ -38,6 +40,7 @@ class PrimitiveTypesTestCase(unittest.TestCase):
 
     def setUp(self):
         self.file = FILE_NAME
+        self.file2 = FILE_NAME2
         file = netCDF4.Dataset(self.file,'w')
         file.createDimension('n', ndim)
         foo = file.createVariable('maskeddata', 'f8', ('n',))
@@ -71,9 +74,21 @@ class PrimitiveTypesTestCase(unittest.TestCase):
         v = file.createVariable('v',NP.float,'x',fill_value=-9999)
         file.close()
 
+        # issue #972: when auto_fill off byte arrays (u1,i1) should
+        # not be masked, but other datatypes should.
+        dataset = netCDF4.Dataset(self.file2, "w")
+        dataset.set_fill_off()
+        dim = dataset.createDimension("dim", 10)
+        var1 = dataset.createVariable("var1", "f8", (dim.name,))
+        var1[:] = masked_all((10,), "f8")
+        var2 = dataset.createVariable("var2", "u1", (dim.name,))
+        var2[:] = masked_all((10,), "u1")
+        dataset.close()
+
     def tearDown(self):
         # Remove the temporary files
         os.remove(self.file)
+        os.remove(self.file2)
 
     def runTest(self):
         """testing auto-conversion of masked arrays and packed integers"""
@@ -118,6 +133,13 @@ class PrimitiveTypesTestCase(unittest.TestCase):
         f['variable'][:] = NP.nan
         data = f['variable'][:] # should not raise an error
         f.close()
+        # issue #972
+        dataset = netCDF4.Dataset(self.file2, "r")
+        var1 = dataset.variables["var1"]
+        var2 = dataset.variables["var2"]
+        assert var1[:].mask.all()
+        assert var2[:].mask.any() == False
+        dataset.close()
 
 if __name__ == '__main__':
     unittest.main()