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python-hdf5storage
hdf5storage-pr134-numpy2.patch
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File hdf5storage-pr134-numpy2.patch of Package python-hdf5storage
From 9814bc28874a56757e16479186523b2b77d5c553 Mon Sep 17 00:00:00 2001 From: Jesse R Codling <codling@umich.edu> Date: Wed, 14 Aug 2024 12:34:47 -0400 Subject: [PATCH 2/3] Numpy 2.0: Remove all np.unicode_ for np.str_ --- doc/source/storage_format.rst | 6 ++-- pyproject.toml | 2 +- hdf5storage/Marshallers.py | 20 +++++++------ hdf5storage/__init__.py | 6 ++-- hdf5storage/utilities.py | 40 ++++++++++++------------- tests/asserts.py | 14 ++++----- tests/make_randoms.py | 4 +-- tests/test_dict_like_storage_methods.py | 6 ++-- tests/test_str_conv_utils.py | 8 ++--- tests/test_string_utf16_conversion.py | 4 +-- tests/test_write_readback.py | 6 ++-- 11 files changed, 59 insertions(+), 57 deletions(-) Index: hdf5storage-0.1.19/tests/make_randoms.py =================================================================== --- hdf5storage-0.1.19.orig/tests/make_randoms.py +++ hdf5storage-0.1.19/tests/make_randoms.py @@ -156,7 +156,7 @@ def random_numpy(shape, dtype, allow_nan chars = random_str_some_unicode(length) else: chars = random_str_ascii(length) - data[index] = np.unicode_(chars) + data[index] = np.str_(chars) return data elif dtype == 'object': data = np.zeros(shape=shape, dtype='object') Index: hdf5storage-0.1.19/tests/test_string_utf16_conversion.py =================================================================== --- hdf5storage-0.1.19.orig/tests/test_string_utf16_conversion.py +++ hdf5storage-0.1.19/tests/test_string_utf16_conversion.py @@ -44,12 +44,12 @@ import pytest # convert_numpy_str_to_utf16 option is set. # # * str -# * numpy.unicode_ scalars +# * numpy.str_ scalars if sys.hexversion < 0x3000000: - tps_tuple = (unicode, np.unicode_) + tps_tuple = (unicode, np.str_) else: - tps_tuple = (str, np.unicode_) + tps_tuple = (str, np.str_) @pytest.mark.parametrize("tp", tps_tuple) Index: hdf5storage-0.1.19/hdf5storage/Marshallers.py =================================================================== --- hdf5storage-0.1.19.orig/hdf5storage/Marshallers.py +++ hdf5storage-0.1.19/hdf5storage/Marshallers.py @@ -480,7 +480,7 @@ class NumpyScalarArrayMarshaller(TypeMar 'MATLAB_int_decode', 'MATLAB_fields']) # As np.str_ is the unicode type string in Python 3 and the bare - # bytes string in Python 2, we have to use np.unicode_ which is + # bytes string in Python 2, we have to use np.str_ which is # or points to the unicode one in both versions. self.types = [np.ndarray, np.matrix, np.chararray, np.core.records.recarray, @@ -489,7 +489,7 @@ class NumpyScalarArrayMarshaller(TypeMar np.int8, np.int16, np.int32, np.int64, np.float32, np.float64, np.complex64, np.complex128, - np.bytes_, np.unicode_, np.object_] + np.bytes_, np.str_, np.object_] self._numpy_types = list(self.types) # Using Python 3 type strings. self.python_type_strings = ['numpy.ndarray', 'numpy.matrix', @@ -525,7 +525,7 @@ class NumpyScalarArrayMarshaller(TypeMar np.complex64: 'single', np.complex128: 'double', np.bytes_: 'char', - np.unicode_: 'char', + np.str_: 'char', np.object_: 'cell'} # Make a dict to look up the opposite direction (given a matlab @@ -542,7 +542,7 @@ class NumpyScalarArrayMarshaller(TypeMar 'int64': np.int64, 'single': np.float32, 'double': np.float64, - 'char': np.unicode_, + 'char': np.str_, 'cell': np.object_, 'canonical empty': np.float64, 'struct': np.object_} @@ -601,18 +601,7 @@ class NumpyScalarArrayMarshaller(TypeMar raise NotImplementedError( \ 'Can''t write non-ASCII numpy.bytes_.') - # As of 2013-12-13, h5py cannot write numpy.str_ (UTF-32 - # encoding) types (its numpy.unicode_ in Python 2, which is an - # alias for it in Python 3). If the option is set to try to - # convert them to UTF-16, then an attempt at the conversion is - # made. If no conversion is to be done, the conversion throws an - # exception (a UTF-32 character had no UTF-16 equivalent), or a - # UTF-32 character gets turned into a UTF-16 doublet (the - # increase in the number of columns will be by a factor more - # than the length of the strings); then it will be simply - # converted to uint32's byte for byte instead. - - if data.dtype.type == np.unicode_: + if data.dtype.type == np.str_: new_data = None if options.convert_numpy_str_to_utf16: try: @@ -620,7 +609,7 @@ class NumpyScalarArrayMarshaller(TypeMar data_to_store) except: pass - if new_data is None or (type(data_to_store) == np.unicode_ \ + if new_data is None or (type(data_to_store) == np.str_ \ and len(data_to_store) != len(new_data)) \ or (isinstance(data_to_store, np.ndarray) \ and new_data.shape[-1] != data_to_store.shape[-1] \ @@ -1049,7 +1038,7 @@ class NumpyScalarArrayMarshaller(TypeMar str_attrs[attr_name] = value elif isinstance(value, bytes): str_attrs[attr_name] = value.decode() - elif isinstance(value, np.unicode_): + elif isinstance(value, np.str_): str_attrs[attr_name] = str(value) elif isinstance(value, np.bytes_): str_attrs[attr_name] = value.decode() @@ -1313,7 +1302,7 @@ class NumpyScalarArrayMarshaller(TypeMar elif underlying_type.startswith('str') \ or matlab_class == 'char': if underlying_type == 'str': - data = np.unicode_('') + data = np.str_('') elif underlying_type.startswith('str'): data = convert_to_numpy_str(data, \ length=int(underlying_type[3:])//32) @@ -1344,7 +1333,7 @@ class NumpyScalarArrayMarshaller(TypeMar data = data.flatten()[0] elif underlying_type.startswith('str'): if python_empty == 1: - data = np.unicode_('') + data = np.str_('') elif isinstance(data, np.ndarray): data = data.flatten()[0] else: @@ -1511,7 +1500,7 @@ class PythonStringMarshaller(NumpyScalar if (sys.hexversion >= 0x03000000 and isinstance(data, str)) \ or (sys.hexversion < 0x03000000 \ and isinstance(data, unicode)): - cdata = np.unicode_(data) + cdata = np.str_(data) else: cdata = np.bytes_(data) Index: hdf5storage-0.1.19/hdf5storage/utilities.py =================================================================== --- hdf5storage-0.1.19.orig/hdf5storage/utilities.py +++ hdf5storage-0.1.19/hdf5storage/utilities.py @@ -408,7 +408,7 @@ def convert_to_str(data): # assuming it is in UTF-8. Otherwise, data has to be returned as is. if isinstance(data, (np.ndarray, np.uint8, np.uint16, np.uint32, - np.bytes_, np.unicode_)): + np.bytes_, np.str_)): if data.dtype.name == 'uint8': return numpy_to_bytes(data.flatten()).decode('UTF-8') elif data.dtype.name == 'uint16': @@ -477,7 +477,7 @@ def convert_to_numpy_str(data, length=No """ # The method of conversion depends on its type. - if isinstance(data, np.unicode_) or (isinstance(data, np.ndarray) \ + if isinstance(data, np.str_) or (isinstance(data, np.ndarray) \ and data.dtype.char == 'U'): # It is already an np.str_ or array of them, so nothing needs to # be done. @@ -486,16 +486,16 @@ def convert_to_numpy_str(data, length=No or (sys.hexversion < 0x03000000 \ and isinstance(data, unicode)): # Easily converted through constructor. - return np.unicode_(data) + return np.str_(data) elif isinstance(data, (bytes, bytearray, np.bytes_)): # All of them can be decoded and then passed through the # constructor. - return np.unicode_(data.decode('UTF-8')) + return np.str_(data.decode('UTF-8')) elif isinstance(data, (np.uint8, np.uint16)): # They are single UTF-8 or UTF-16 scalars, and are easily # converted to a UTF-8 string and then passed through the # constructor. - return np.unicode_(convert_to_str(data)) + return np.str_(convert_to_str(data)) elif isinstance(data, np.uint32): # It is just the uint32 version of the character, so it just # needs to be have the dtype essentially changed by having its @@ -507,7 +507,7 @@ def convert_to_numpy_str(data, length=No new_data = np.zeros(shape=data.shape, dtype='U' + str(data.dtype.itemsize)) for index, x in np.ndenumerate(data): - new_data[index] = np.unicode_(x.decode('UTF-8')) + new_data[index] = np.str_(x.decode('UTF-8')) return new_data elif isinstance(data, np.ndarray) \ and data.dtype.name in ('uint8', 'uint16', 'uint32'): @@ -559,7 +559,7 @@ def convert_to_numpy_str(data, length=No dtype=new_data.dtype, buffer=numpy_to_bytes(chunk))[()] else: - new_data[i] = np.unicode_(convert_to_str(chunk)) + new_data[i] = np.str_(convert_to_str(chunk)) # Only thing is left is to reshape it. return new_data.reshape(tuple(new_shape)) @@ -896,7 +896,7 @@ def get_attribute_string(target, name): return value elif isinstance(value, bytes): return value.decode() - elif isinstance(value, np.unicode_): + elif isinstance(value, np.str_): return str(value) elif isinstance(value, np.bytes_): return value.decode()
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