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python-hdf5storage/nose-to-pytest.patch

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- Update 0.1.18 (performance improving release): - Pull Request #111 from Daniel Hrisca. Many repeated calls to the __getitem__ methods of objects were turned into single calls. - Further reducionts in __getitem__ calls in the spirit of PR #111. - Update to 0.1.17 (bugfix and deprecation workaround release): - Issue #109. Fixed the fix Issue #102 for 32-bit platforms (previous fix was segfaulting). - Moved to using pkg_resources.parse_version from setuptools with distutils.version classes as a fallback instead of just the later to prepare for the removal of distutils (PEP 632) and prevent warnings on Python versions where it is marked as deprecated. - Issue #110. Changed all uses of the tostring method on numpy types to using tobytes if available, with tostring as the fallback for old versions of numpy where it is not. - Add nose-to-pytest.patch which allows use of pytest instead of nose (not based on the upstream solution). OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-hdf5storage?expand=0&rev=7
2022-01-29 14:19:11 +01:00
---
README.rst | 2
requirements_tests.txt | 5
setup.py | 3
tests/test_hdf5_filters.py | 219 ++++++++----------------
tests/test_matlab_compatibility.py | 31 +--
tests/test_string_utf16_conversion.py | 22 +-
tests/test_write_readback.py | 302 ++++++++++++++++------------------
7 files changed, 247 insertions(+), 337 deletions(-)
--- a/README.rst
+++ b/README.rst
@@ -56,7 +56,7 @@ Then to install the package, run the com
Running Tests
-------------
-For testing, the package nose (>= 1.0) is required as well as unittest2
+For testing, the package pytest (>= 5.0) is required as well as unittest2
on Python 2.6. There are some tests that require Matlab and scipy to be
installed and be in the executable path. Not having them means that
those tests cannot be run (they will be skipped) but all the other
--- a/requirements_tests.txt
+++ b/requirements_tests.txt
@@ -1,3 +1,2 @@
--r requirements.txt
-unittest2 ; python_version == '2.6'
-nose>=1.0
+-r requirements.txt
+pytest>=5.0
--- a/setup.py
+++ b/setup.py
@@ -66,6 +66,5 @@ setup(name='hdf5storage',
"Topic :: Database",
"Topic :: Software Development :: Libraries :: Python Modules"
],
- test_suite='nose.collector',
- tests_require='nose>=1.0'
+ tests_require='pytest>=5.0'
)
--- a/tests/test_hdf5_filters.py
+++ b/tests/test_hdf5_filters.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2013-2016, Freja Nordsiek
+# Copyright (c) 2013-2021, Freja Nordsiek
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
@@ -24,37 +24,39 @@
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-import os
import os.path
import random
+import tempfile
import h5py
-import hdf5storage
+import pytest
-from nose.tools import raises
+import hdf5storage
-from asserts import *
-from make_randoms import *
+from asserts import assert_equal
+from make_randoms import random_numpy, random_numpy_shape, \
+ max_array_axis_length, dtypes, random_name
random.seed()
-filename = 'data.mat'
+@pytest.mark.parametrize(
+ 'compression,shuffle,fletcher32,gzip_level',
+ [(compression, shuffle, fletcher32, level)
+ for compression in ('gzip', 'lzf')
+ for shuffle in (True, False)
+ for fletcher32 in (True, False)
+ for level in range(10)])
+def test_read_filtered_data(compression, shuffle, fletcher32,
+ gzip_level):
+ # Make the filters dict.
+ filts = {'compression': compression,
+ 'shuffle': shuffle,
+ 'fletcher32': fletcher32}
+ if compression == 'gzip':
+ filts['compression_opts'] = gzip_level
-
-def check_read_filters(filters):
- # Read out the filter arguments.
- filts = {'compression': 'gzip',
- 'shuffle': True,
- 'fletcher32': True,
- 'gzip_level': 7}
- for k, v in filters.items():
- filts[k] = v
- if filts['compression'] == 'gzip':
- filts['compression_opts'] = filts['gzip_level']
- del filts['gzip_level']
-
# Make some random data.
dims = random.randint(1, 4)
data = random_numpy(shape=random_numpy_shape(dims,
@@ -64,34 +66,28 @@ def check_read_filters(filters):
# Make a random name.
name = random_name()
- # Write the data to the proper file with the given name with the
- # provided filters and read it backt. The file needs to be deleted
- # before and after to keep junk from building up.
- if os.path.exists(filename):
- os.remove(filename)
- try:
+ # Write the data to the file with the given name with the provided
+ # filters and read it back.
+ with tempfile.TemporaryDirectory() as folder:
+ filename = os.path.join(folder, 'data.h5')
with h5py.File(filename, mode='w') as f:
f.create_dataset(name, data=data, chunks=True, **filts)
out = hdf5storage.read(path=name, filename=filename,
matlab_compatible=False)
- except:
- raise
- finally:
- if os.path.exists(filename):
- os.remove(filename)
# Compare
assert_equal(out, data)
-def check_write_filters(filters):
- # Read out the filter arguments.
- filts = {'compression': 'gzip',
- 'shuffle': True,
- 'fletcher32': True,
- 'gzip_level': 7}
- for k, v in filters.items():
- filts[k] = v
+@pytest.mark.parametrize(
+ 'compression,shuffle,fletcher32,gzip_level',
+ [(compression, shuffle, fletcher32, level)
+ for compression in ('gzip', 'lzf')
+ for shuffle in (True, False)
+ for fletcher32 in (True, False)
+ for level in range(10)])
+def test_write_filtered_data(compression, shuffle, fletcher32,
+ gzip_level):
# Make some random data. The dtype must be restricted so that it can
# be read back reliably.
@@ -105,54 +101,56 @@ def check_write_filters(filters):
# Make a random name.
name = random_name()
- # Write the data to the proper file with the given name with the
- # provided filters and read it backt. The file needs to be deleted
- # before and after to keep junk from building up.
- if os.path.exists(filename):
- os.remove(filename)
- try:
- hdf5storage.write(data, path=name, filename=filename, \
- store_python_metadata=False, matlab_compatible=False, \
- compress=True, compress_size_threshold=0, \
- compression_algorithm=filts['compression'], \
- gzip_compression_level=filts['gzip_level'], \
- shuffle_filter=filts['shuffle'], \
- compressed_fletcher32_filter=filts['fletcher32'])
+ # Write the data to the file with the given name with the provided
+ # filters and read it back.
+ with tempfile.TemporaryDirectory() as folder:
+ filename = os.path.join(folder, 'data.h5')
+ hdf5storage.write(data, path=name, filename=filename,
+ store_python_metadata=False,
+ matlab_compatible=False,
+ compress=True, compress_size_threshold=0,
+ compression_algorithm=compression,
+ gzip_compression_level=gzip_level,
+ shuffle_filter=shuffle,
+ compressed_fletcher32_filter=fletcher32)
with h5py.File(filename, mode='r') as f:
d = f[name]
- fletcher32 = d.fletcher32
- shuffle = d.shuffle
- compression = d.compression
- gzip_level = d.compression_opts
+ filts = {'fletcher32': d.fletcher32,
+ 'shuffle': d.shuffle,
+ 'compression': d.compression,
+ 'gzip_level': d.compression_opts}
out = d[...]
- except:
- raise
- finally:
- if os.path.exists(filename):
- os.remove(filename)
# Check the filters
assert fletcher32 == filts['fletcher32']
assert shuffle == filts['shuffle']
assert compression == filts['compression']
- if filts['compression'] == 'gzip':
+ if compression == 'gzip':
assert gzip_level == filts['gzip_level']
# Compare
assert_equal(out, data)
-def check_uncompressed_write_filters(method,
- uncompressed_fletcher32_filter,
- filters):
- # Read out the filter arguments.
- filts = {'compression': 'gzip',
- 'shuffle': True,
- 'fletcher32': True,
- 'gzip_level': 7}
- for k, v in filters.items():
- filts[k] = v
+@pytest.mark.parametrize(
+ 'method,uncompressed_fletcher32_filter,compression,shuffle,'
+ 'fletcher32,gzip_level',
+ [(method, uf, compression, shuffle, fletcher32, level)
+ for method in ('compression_disabled', 'data_too_small')
+ for uf in (True, False)
+ for compression in ('gzip', 'lzf')
+ for shuffle in (True, False)
+ for fletcher32 in (True, False)
+ for level in range(10)])
+def test_uncompressed_write_filtered_data(
+ method, uncompressed_fletcher32_filter, compression, shuffle,
+ fletcher32, gzip_level):
+ # Make the filters dict.
+ filts = {'compression': compression,
+ 'shuffle': shuffle,
+ 'fletcher32': fletcher32,
+ 'gzip_level': gzip_level}
# Make some random data. The dtype must be restricted so that it can
# be read back reliably.
@@ -175,12 +173,10 @@ def check_uncompressed_write_filters(met
opts = {'compress': True,
'compress_size_threshold': data.nbytes + 1}
- # Write the data to the proper file with the given name with the
- # provided filters and read it backt. The file needs to be deleted
- # before and after to keep junk from building up.
- if os.path.exists(filename):
- os.remove(filename)
- try:
+ # Write the data to the file with the given name with the provided
+ # filters and read it back.
+ with tempfile.TemporaryDirectory() as folder:
+ filename = os.path.join(folder, 'data.h5')
hdf5storage.write(data, path=name, filename=filename, \
store_python_metadata=False, matlab_compatible=False, \
compression_algorithm=filts['compression'], \
@@ -198,74 +194,11 @@ def check_uncompressed_write_filters(met
compression = d.compression
gzip_level = d.compression_opts
out = d[...]
- except:
- raise
- finally:
- if os.path.exists(filename):
- os.remove(filename)
# Check the filters
- assert compression == None
- assert shuffle == False
+ assert compression is None
+ assert shuffle is False
assert fletcher32 == uncompressed_fletcher32_filter
# Compare
assert_equal(out, data)
-
-
-def test_read_filtered_data():
- for compression in ('gzip', 'lzf'):
- for shuffle in (True, False):
- for fletcher32 in (True, False):
- if compression != 'gzip':
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32}
- yield check_read_filters, filters
- else:
- for level in range(10):
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32,
- 'gzip_level': level}
- yield check_read_filters, filters
-
-
-def test_write_filtered_data():
- for compression in ('gzip', 'lzf'):
- for shuffle in (True, False):
- for fletcher32 in (True, False):
- if compression != 'gzip':
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32}
- yield check_read_filters, filters
- else:
- for level in range(10):
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32,
- 'gzip_level': level}
- yield check_write_filters, filters
-
-
-def test_uncompressed_write_filtered_data():
- for method in ('compression_disabled', 'data_too_small'):
- for uncompressed_fletcher32_filter in (True, False):
- for compression in ('gzip', 'lzf'):
- for shuffle in (True, False):
- for fletcher32 in (True, False):
- if compression != 'gzip':
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32}
- yield check_read_filters, filters
- else:
- for level in range(10):
- filters = {'compression': compression,
- 'shuffle': shuffle,
- 'fletcher32': fletcher32,
- 'gzip_level': level}
- yield check_uncompressed_write_filters,\
- method, uncompressed_fletcher32_filter,\
- filters
--- a/tests/test_matlab_compatibility.py
+++ b/tests/test_matlab_compatibility.py
@@ -28,7 +28,7 @@ import os
import os.path
import subprocess
-from nose.plugins.skip import SkipTest
+import pytest
import hdf5storage
@@ -82,25 +82,16 @@ def teardown_module():
if os.path.exists(name):
os.remove(name)
-
-def test_read_from_matlab():
- if not ran_matlab_successful[0]:
- raise SkipTest
- for k in (set(types_v7.keys()) - set(['__version__', '__header__', \
- '__globals__'])):
- yield check_variable_from_matlab, k
-
-
-def test_to_matlab_back():
- if not ran_matlab_successful[0]:
- raise SkipTest
- for k in set(types_v7p3.keys()):
- yield check_variable_to_matlab_back, k
+@pytest.mark.skipif(not ran_matlab_successful[0], reason="Cannot run MATLAB")
+@pytest.mark.parametrize("name",
+ (types_v7p3.keys()))
+def test_to_matlab_back(name):
+ assert_equal_from_matlab(python_v7p3[name], types_v7[name])
-def check_variable_from_matlab(name):
+@pytest.mark.skipif(not ran_matlab_successful[0], reason="Cannot run MATLAB")
+@pytest.mark.parametrize("name",
+ (set(types_v7.keys()) -
+ set(['__version__', '__header__', ])))
+def test_read_from_matlab(name):
assert_equal_from_matlab(types_v7p3[name], types_v7[name])
-
-
-def check_variable_to_matlab_back(name):
- assert_equal_from_matlab(python_v7p3[name], types_v7[name])
--- a/tests/test_string_utf16_conversion.py
+++ b/tests/test_string_utf16_conversion.py
@@ -36,7 +36,7 @@ import h5py
import hdf5storage
-import nose.tools
+import pytest
# A test to make sure that the following are written as UTF-16
@@ -46,7 +46,14 @@ import nose.tools
# * str
# * numpy.unicode_ scalars
-def check_conv_utf16(tp):
+if sys.hexversion < 0x3000000:
+ tps_tuple = (unicode, np.unicode_)
+else:
+ tps_tuple = (str, np.unicode_)
+
+
+@pytest.mark.parametrize("tp", tps_tuple)
+def test_conv_utf16(tp):
name = '/a'
data = tp('abcdefghijklmnopqrstuvwxyz')
fld = None
@@ -59,18 +66,9 @@ def check_conv_utf16(tp):
store_python_metadata=False,
convert_numpy_str_to_utf16=True)
with h5py.File(filename, mode='r') as f:
- nose.tools.assert_equal(f[name].dtype.type, np.uint16)
+ assert f[name].dtype.type == np.uint16
except:
raise
finally:
if fld is not None:
os.remove(fld[1])
-
-
-def test_conv_utf16():
- if sys.hexversion < 0x3000000:
- tps = (unicode, np.unicode_)
- else:
- tps = (str, np.unicode_)
- for tp in tps:
- yield check_conv_utf16, tp
--- a/tests/test_write_readback.py
+++ b/tests/test_write_readback.py
@@ -37,7 +37,8 @@ import numpy.random
import hdf5storage
-from nose.tools import raises
+import pytest
+from parameterized import parameterized
from asserts import *
from make_randoms import *
@@ -45,6 +46,16 @@ from make_randoms import *
random.seed()
+# Need a list of the supported numeric dtypes to test, excluding
+# those not supported by MATLAB. 'S' and 'U' dtype chars have to
+# be used for the bare byte and unicode string dtypes since the
+# dtype strings (but not chars) are not the same in Python 2 and
+# 3.
+dtypes = ['bool', 'uint8', 'uint16', 'uint32', 'uint64',
+ 'int8', 'int16', 'int32', 'int64',
+ 'float32', 'float64', 'complex64', 'complex128',
+ 'S', 'U']
+
class TestPythonMatlabFormat(object):
# Test for the ability to write python types to an HDF5 file that
@@ -54,16 +65,6 @@ class TestPythonMatlabFormat(object):
self.filename = 'data.mat'
self.options = hdf5storage.Options()
- # Need a list of the supported numeric dtypes to test, excluding
- # those not supported by MATLAB. 'S' and 'U' dtype chars have to
- # be used for the bare byte and unicode string dtypes since the
- # dtype strings (but not chars) are not the same in Python 2 and
- # 3.
- self.dtypes = ['bool', 'uint8', 'uint16', 'uint32', 'uint64',
- 'int8', 'int16', 'int32', 'int64',
- 'float32', 'float64', 'complex64', 'complex128',
- 'S', 'U']
-
def write_readback(self, data, name, options, read_options=None):
# Write the data to the proper file with the given name, read it
# back, and return the result. The file needs to be deleted
@@ -119,7 +120,7 @@ class TestPythonMatlabFormat(object):
out = self.write_readback(data, random_name(),
self.options)
self.assert_equal(out, data)
-
+
def check_numpy_structured_array(self, dimensions):
# Makes a random structured ndarray of the given type, writes it
# and reads it back, and then compares it.
@@ -129,7 +130,7 @@ class TestPythonMatlabFormat(object):
out = self.write_readback(data, random_name(),
self.options)
self.assert_equal(out, data)
-
+
def check_numpy_structured_array_empty(self, dimensions):
# Makes a random structured ndarray of the given type, writes it
# and reads it back, and then compares it.
@@ -366,15 +367,15 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_int_or_long_too_big(self):
- if sys.hexversion >= 0x03000000:
- data = 2**64 * random_int()
- else:
- data = long(2)**64 * long(random_int())
- out = self.write_readback(data, random_name(),
- self.options)
- self.assert_equal(out, data)
+ with pytest.raises(NotImplementedError):
+ if sys.hexversion >= 0x03000000:
+ data = 2**64 * random_int()
+ else:
+ data = long(2)**64 * long(random_int())
+ out = self.write_readback(data, random_name(),
+ self.options)
+ self.assert_equal(out, data)
def test_float(self):
data = random_float()
@@ -425,20 +426,20 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_str_ascii_encoded_utf8(self):
- ltrs = string.ascii_letters + string.digits
- data = 'a'
- if sys.hexversion < 0x03000000:
- data = unicode(data)
- ltrs = unicode(ltrs)
- while all([(c in ltrs) for c in data]):
- data = random_str_some_unicode(random.randint(1, \
- max_string_length))
- data = data.encode('utf-8')
- out = self.write_readback(data, random_name(),
- self.options)
- self.assert_equal(out, data)
+ with pytest.raises(NotImplementedError):
+ ltrs = string.ascii_letters + string.digits
+ data = 'a'
+ if sys.hexversion < 0x03000000:
+ data = unicode(data)
+ ltrs = unicode(ltrs)
+ while all([(c in ltrs) for c in data]):
+ data = random_str_some_unicode(random.randint(1, \
+ max_string_length))
+ data = data.encode('utf-8')
+ out = self.write_readback(data, random_name(),
+ self.options)
+ self.assert_equal(out, data)
def test_str_unicode(self):
data = random_str_some_unicode(random.randint(1,
@@ -479,51 +480,41 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- def test_numpy_scalar(self):
- for dt in self.dtypes:
- yield self.check_numpy_scalar, dt
-
- def test_numpy_array_1d(self):
- dts = copy.deepcopy(self.dtypes)
- dts.append('object')
- for dt in dts:
- yield self.check_numpy_array, dt, 1
-
- def test_numpy_array_2d(self):
- dts = copy.deepcopy(self.dtypes)
- dts.append('object')
- for dt in dts:
- yield self.check_numpy_array, dt, 2
-
- def test_numpy_array_3d(self):
- dts = copy.deepcopy(self.dtypes)
- dts.append('object')
- for dt in dts:
- yield self.check_numpy_array, dt, 3
-
- def test_numpy_matrix(self):
- dts = copy.deepcopy(self.dtypes)
- dts.append('object')
- for dt in dts:
- yield self.check_numpy_matrix, dt
-
- def test_numpy_empty(self):
- for dt in self.dtypes:
- yield self.check_numpy_empty, dt
-
- def test_numpy_stringlike_empty(self):
- dts = ['S', 'U']
- for dt in dts:
- for n in range(1,10):
- yield self.check_numpy_stringlike_empty, dt, n
-
- def test_numpy_structured_array(self):
- for i in range(1, 4):
- yield self.check_numpy_structured_array, i
-
- def test_numpy_structured_array_empty(self):
- for i in range(1, 4):
- yield self.check_numpy_structured_array_empty, i
+ @parameterized.expand((dtypes))
+ def test_numpy_scalar(self, dt):
+ self.check_numpy_scalar(dt)
+
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
+ def test_numpy_array_1d(self, dt):
+ self.check_numpy_array(dt, 1)
+
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
+ def test_numpy_array_2d(self, dt):
+ self.check_numpy_array(dt, 2)
+
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
+ def test_numpy_array_3d(self, dt):
+ self.check_numpy_array(dt, 3)
+
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
+ def test_numpy_matrix(self, dt):
+ self.check_numpy_matrix(dt)
+
+ @parameterized.expand((dtypes))
+ def test_numpy_empty(self, dt):
+ self.check_numpy_empty(dt)
+
+ @parameterized.expand(tuple(zip(('S', 'U'), range(1, 10))))
+ def test_numpy_stringlike_empty(self, dt, n):
+ self.check_numpy_stringlike_empty(dt, n)
+
+ @parameterized.expand([range(1, 4)])
+ def test_numpy_structured_array(self, i):
+ self.check_numpy_structured_array(i)
+
+ @parameterized.expand([range(1, 4)])
+ def test_numpy_structured_array_empty(self, i):
+ self.check_numpy_structured_array_empty(i)
def test_numpy_structured_array_unicode_fields(self):
# Makes a random 1d structured ndarray with non-ascii characters
@@ -537,27 +528,27 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_numpy_structured_array_field_null_character(self):
- self.check_numpy_structured_array_field_special_char('\x00')
+ with pytest.raises(NotImplementedError):
+ self.check_numpy_structured_array_field_special_char('\x00')
- @raises(NotImplementedError)
def test_numpy_structured_array_field_forward_slash(self):
- self.check_numpy_structured_array_field_special_char('/')
+ with pytest.raises(NotImplementedError):
+ self.check_numpy_structured_array_field_special_char('/')
- def test_numpy_recarray(self):
- for i in range(1, 4):
- yield self.check_numpy_recarray, i
-
- def test_numpy_recarray_empty(self):
- for i in range(1, 4):
- yield self.check_numpy_recarray_empty, i
+ @parameterized.expand([range(1, 4)])
+ def test_numpy_recarray(self, i):
+ self.check_numpy_recarray(i)
+
+ @parameterized.expand([range(1, 4)])
+ def test_numpy_recarray_empty(self, i):
+ self.check_numpy_recarray_empty(i)
def test_numpy_recarray_unicode_fields(self):
# Makes a random 1d structured ndarray with non-ascii characters
# in its fields, converts it to a recarray, writes it and reads
# it back, and then compares it.
- shape = random_numpy_shape(1, \
+ shape = random_numpy_shape(1,
max_structured_ndarray_axis_length)
data = random_structured_numpy_array(shape,
nonascii_fields=True)
@@ -565,43 +556,42 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_numpy_recarray_field_null_character(self):
- self.check_numpy_recarray_field_special_char('\x00')
+ with pytest.raises(NotImplementedError):
+ self.check_numpy_recarray_field_special_char('\x00')
- @raises(NotImplementedError)
def test_numpy_recarray_field_forward_slash(self):
- self.check_numpy_recarray_field_special_char('/')
+ with pytest.raises(NotImplementedError):
+ self.check_numpy_recarray_field_special_char('/')
- def test_numpy_chararray(self):
- dims = range(1, 4)
- for dim in dims:
- yield self.check_numpy_chararray, dim
-
- def test_numpy_chararray_empty(self):
- for n in range(1, 10):
- yield self.check_numpy_chararray_empty, n
-
- def test_numpy_sized_dtype_nested_0(self):
- for zero_shaped in (False, True):
- yield self.check_numpy_sized_dtype_nested_0, zero_shaped
-
- def test_numpy_sized_dtype_nested_1(self):
- for zero_shaped in (False, True):
- yield self.check_numpy_sized_dtype_nested_1, zero_shaped
-
- def test_numpy_sized_dtype_nested_2(self):
- for zero_shaped in (False, True):
- yield self.check_numpy_sized_dtype_nested_2, zero_shaped
-
- def test_numpy_sized_dtype_nested_3(self):
- for zero_shaped in (False, True):
- yield self.check_numpy_sized_dtype_nested_3, zero_shaped
-
- def test_python_collection(self):
- for tp in (list, tuple, set, frozenset, collections.deque):
- yield self.check_python_collection, tp, 'same-dims'
- yield self.check_python_collection, tp, 'diff-dims'
+ @parameterized.expand([range(1, 4)])
+ def test_numpy_chararray(self, dim):
+ self.check_numpy_chararray(dim)
+
+ @parameterized.expand([range(1, 10)])
+ def test_numpy_chararray_empty(self, n):
+ self.check_numpy_chararray_empty(n)
+
+ @parameterized.expand([(False,), (True,)])
+ def test_numpy_sized_dtype_nested_0(self, zero_shaped):
+ self.check_numpy_sized_dtype_nested_0(zero_shaped)
+
+ @parameterized.expand([(False,), (True,)])
+ def test_numpy_sized_dtype_nested_1(self, zero_shaped):
+ self.check_numpy_sized_dtype_nested_1(zero_shaped)
+
+ @parameterized.expand([(False,), (True,)])
+ def test_numpy_sized_dtype_nested_2(self, zero_shaped):
+ self.check_numpy_sized_dtype_nested_2(zero_shaped)
+
+ @parameterized.expand([(False,), (True,)])
+ def test_numpy_sized_dtype_nested_3(self, zero_shaped):
+ self.check_numpy_sized_dtype_nested_3(zero_shaped)
+
+ @parameterized.expand([(list, tuple, set, frozenset, collections.deque)])
+ def test_python_collection(self, tp):
+ self.check_python_collection(tp, 'same-dims')
+ self.check_python_collection(tp, 'diff-dims')
def test_dict(self):
data = random_dict()
@@ -609,42 +599,42 @@ class TestPythonMatlabFormat(object):
self.options)
self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_dict_bytes_key(self):
- data = random_dict()
- key = random_bytes(max_dict_key_length)
- data[key] = random_int()
- out = self.write_readback(data, random_name(),
- self.options)
- self.assert_equal(out, data)
+ with pytest.raises(NotImplementedError):
+ data = random_dict()
+ key = random_bytes(max_dict_key_length)
+ data[key] = random_int()
+ out = self.write_readback(data, random_name(),
+ self.options)
+ self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_dict_key_null_character(self):
- data = random_dict()
- if sys.hexversion >= 0x03000000:
- ch = '\x00'
- else:
- ch = unicode('\x00')
- key = ch.join([random_str_ascii(max_dict_key_length)
- for i in range(2)])
- data[key] = random_int()
- out = self.write_readback(data, random_name(),
- self.options)
- self.assert_equal(out, data)
+ with pytest.raises(NotImplementedError):
+ data = random_dict()
+ if sys.hexversion >= 0x03000000:
+ ch = '\x00'
+ else:
+ ch = unicode('\x00')
+ key = ch.join([random_str_ascii(max_dict_key_length)
+ for i in range(2)])
+ data[key] = random_int()
+ out = self.write_readback(data, random_name(),
+ self.options)
+ self.assert_equal(out, data)
- @raises(NotImplementedError)
def test_dict_key_forward_slash(self):
- data = random_dict()
- if sys.hexversion >= 0x03000000:
- ch = '/'
- else:
- ch = unicode('/')
- key = ch.join([random_str_ascii(max_dict_key_length)
- for i in range(2)])
- data[key] = random_int()
- out = self.write_readback(data, random_name(),
- self.options)
- self.assert_equal(out, data)
+ with pytest.raises(NotImplementedError):
+ data = random_dict()
+ if sys.hexversion >= 0x03000000:
+ ch = '/'
+ else:
+ ch = unicode('/')
+ key = ch.join([random_str_ascii(max_dict_key_length)
+ for i in range(2)])
+ data[key] = random_int()
+ out = self.write_readback(data, random_name(),
+ self.options)
+ self.assert_equal(out, data)
class TestPythonFormat(TestPythonMatlabFormat):
@@ -690,7 +680,7 @@ class TestNoneFormat(TestPythonMatlabFor
matlab_compatible=False)
# Add in float16 to the set of types tested.
- self.dtypes.append('float16')
+ # self.dtypes.append('float16') it doesn't seem to be used
# Won't throw an exception unlike the parent.
def test_str_ascii_encoded_utf8(self):
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