Update requirements, prepare 3.0.0

CHANGELOG.md

@@ -29,6 +29,9 @@
   passed to ``DynamicTable.get``, then nested DataFrames will be returned, one DataFrame per row of the original
   resulting DataFrame. @rly (#579)
 
+### Minor improvements
+- Updated requirements and tests. @rly (#640)
+
 ### Bug fixes
 - Update the validator to allow extensions to data types which only define data_type_inc. @dsleiter (#609)
 - Fix error when validating lazy-loaded datasets containing references. @dsleiter (#609)

requirements-dev.txt

@@ -2,9 +2,9 @@
 # compute coverage, and create test environments
 codecov==2.1.11
 coverage==5.5
-flake8==3.9.1
+flake8==3.9.2
 flake8-debugger==4.0.0
 flake8-print==4.0.0
-importlib-metadata==4.0.1
+importlib-metadata==4.6.1
 python-dateutil==2.8.1
-tox==3.23.0
+tox==3.23.1

requirements.txt

@@ -1,8 +1,8 @@
 # pinned dependencies to reproduce an entire development environment to use HDMF
-h5py==3.2.1
-numpy==1.19.3
-scipy==1.5.4
-pandas==1.1.5
-ruamel.yaml==0.17.4
+h5py==3.3.0
+numpy==1.21.0
+scipy==1.7.0
+pandas==1.3.0
+ruamel.yaml==0.17.10
 jsonschema==3.2.0
-setuptools==56.0.0
+setuptools==57.1.0

setup.py

@@ -13,7 +13,7 @@
 
 reqs = [
     'h5py>=2.10,<4',
-    'numpy>=1.16,<1.21',
+    'numpy>=1.16,<1.22',
     'scipy>=1.1,<2',
     'pandas>=1.0.5,<2',
     'ruamel.yaml>=0.16,<1',

src/hdmf/backends/hdf5/h5_utils.py

@@ -452,7 +452,7 @@ def __init__(self, **kwargs):
                                      self.__allow_plugin_filters):
             msg = "%s compression may not be supported by this version of h5py." % str(self.__iosettings['compression'])
             if not self.__allow_plugin_filters:
-                msg += "Set `allow_plugin_filters=True` to enable the use of dynamically-loaded plugin filters."
+                msg += " Set `allow_plugin_filters=True` to enable the use of dynamically-loaded plugin filters."
             raise ValueError(msg)
         # Check possible parameter collisions
         if isinstance(self.data, Dataset):

tests/unit/test_io_hdf5_h5tools.py

@@ -556,22 +556,28 @@ def test_warning_on_non_gzip_compression(self):
             self.assertEqual(len(w), 0)
             self.assertEqual(dset.io_settings['compression'], 'gzip')
         # Make sure a warning is issued when using szip (even if installed)
+        warn_msg = ("szip compression may not be available on all installations of HDF5. Use of gzip is "
+                    "recommended to ensure portability of the generated HDF5 files.")
         if "szip" in h5py_filters.encode:
-            with warnings.catch_warnings(record=True) as w:
+            with self.assertWarnsWith(UserWarning, warn_msg):
                 dset = H5DataIO(np.arange(30),
                                 compression='szip',
                                 compression_opts=('ec', 16))
-                self.assertEqual(len(w), 1)
-                self.assertEqual(dset.io_settings['compression'], 'szip')
+            self.assertEqual(dset.io_settings['compression'], 'szip')
         else:
             with self.assertRaises(ValueError):
-                H5DataIO(np.arange(30), compression='szip', compression_opts=('ec', 16))
+                with self.assertWarnsWith(UserWarning, warn_msg):
+                    dset = H5DataIO(np.arange(30),
+                                    compression='szip',
+                                    compression_opts=('ec', 16))
+                self.assertEqual(dset.io_settings['compression'], 'szip')
         # Make sure a warning is issued when using lzf compression
-        with warnings.catch_warnings(record=True) as w:
+        warn_msg = ("lzf compression may not be available on all installations of HDF5. Use of gzip is "
+                    "recommended to ensure portability of the generated HDF5 files.")
+        with self.assertWarnsWith(UserWarning, warn_msg):
             dset = H5DataIO(np.arange(30),
                             compression='lzf')
-            self.assertEqual(len(w), 1)
-            self.assertEqual(dset.io_settings['compression'], 'lzf')
+        self.assertEqual(dset.io_settings['compression'], 'lzf')
 
     def test_error_on_unsupported_compression_filter(self):
         # Make sure gzip does not raise an error
@@ -584,7 +590,8 @@ def test_error_on_unsupported_compression_filter(self):
                     "recommended to ensure portability of the generated HDF5 files.")
         if "szip" not in h5py_filters.encode:
             with self.assertRaises(ValueError):
-                H5DataIO(np.arange(30), compression='szip', compression_opts=('ec', 16))
+                with self.assertWarnsWith(UserWarning, warn_msg):
+                    H5DataIO(np.arange(30), compression='szip', compression_opts=('ec', 16))
         else:
             try:
                 with self.assertWarnsWith(UserWarning, warn_msg):

tests/unit/utils_test/test_utils.py

@@ -170,29 +170,29 @@ def test_strict_no_data_load(self):
 class TestToUintArray(TestCase):
 
     def test_ndarray_uint(self):
-        arr = np.array([0, 1, 2], dtype=np.uint)
+        arr = np.array([0, 1, 2], dtype=np.uint32)
         res = to_uint_array(arr)
         np.testing.assert_array_equal(res, arr)
 
     def test_ndarray_int(self):
-        arr = np.array([0, 1, 2], dtype=np.int)
+        arr = np.array([0, 1, 2], dtype=np.int32)
         res = to_uint_array(arr)
         np.testing.assert_array_equal(res, arr)
 
     def test_ndarray_int_neg(self):
-        arr = np.array([0, -1, 2], dtype=np.int)
+        arr = np.array([0, -1, 2], dtype=np.int32)
         with self.assertRaisesWith(ValueError, 'Cannot convert negative integer values to uint.'):
             to_uint_array(arr)
 
     def test_ndarray_float(self):
-        arr = np.array([0, 1, 2], dtype=np.float)
+        arr = np.array([0, 1, 2], dtype=np.float64)
         with self.assertRaisesWith(ValueError, 'Cannot convert array of dtype float64 to uint.'):
             to_uint_array(arr)
 
     def test_list_int(self):
         arr = [0, 1, 2]
         res = to_uint_array(arr)
-        expected = np.array([0, 1, 2], dtype=np.uint)
+        expected = np.array([0, 1, 2], dtype=np.uint32)
         np.testing.assert_array_equal(res, expected)
 
     def test_list_int_neg(self):

tests/unit/validator_tests/test_validate.py

@@ -424,7 +424,7 @@ def test_int64_for_numeric(self):
     def test_bool_for_numeric(self):
         """Test that validator does not allow bool data where numeric is specified."""
         self.set_up_spec('numeric')
-        value = np.bool(1)
+        value = True
         bar_builder = GroupBuilder('my_bar',
                                    attributes={'data_type': 'Bar', 'attr1': value},
                                    datasets=[DatasetBuilder('data', value)])