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What happens if I push all of nixpkgs
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4.9 kB · 92 lines
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See: https://numpy.org/devdocs/numpy_2_0_migration_guide.html#adapting-to-changes-in-the-copy-keyword--- hickle/legacy_v3/loaders/load_numpy.py | 2 +- hickle/loaders/load_builtins.py | 4 ++-- hickle/loaders/load_numpy.py | 2 +- hickle/tests/test_02_hickle_lookup.py | 6 +++--- 4 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/hickle/legacy_v3/loaders/load_numpy.py b/hickle/legacy_v3/loaders/load_numpy.pyindex 0fd6c0a4..d17044bc 100644--- a/hickle/legacy_v3/loaders/load_numpy.py+++ b/hickle/legacy_v3/loaders/load_numpy.py@@ -115,7 +115,7 @@ def load_np_scalar_dataset(h_node): def load_ndarray_dataset(h_node): py_type, data = get_type_and_data(h_node)- return np.array(data, copy=False)+ return np.asarray(data) def load_ndarray_masked_dataset(h_node): py_type, data = get_type_and_data(h_node)diff --git a/hickle/loaders/load_builtins.py b/hickle/loaders/load_builtins.pyindex 7cfbf281..53b74429 100644--- a/hickle/loaders/load_builtins.py+++ b/hickle/loaders/load_builtins.py@@ -170,7 +170,7 @@ def create_listlike_dataset(py_obj, h_group, name,list_len = -1,item_dtype = Non # strings and bytes are stored as array of bytes with strings encoded # using utf8 encoding string_data = bytearray(py_obj,"utf8") if isinstance(py_obj,str) else memoryview(py_obj)- string_data = np.array(string_data,copy=False)+ string_data = np.asarray(string_data) string_data.dtype = 'S1' dataset = h_group.create_dataset( name, data = string_data,shape = (1,string_data.size), **kwargs) dataset.attrs["str_type"] = py_obj.__class__.__name__.encode("ascii")@@ -385,7 +385,7 @@ def load_list_dataset(h_node,base_type,py_obj_type): if h_node.dtype.itemsize > 1 and 'bytes' in h_node.dtype.name: # string dataset 4.0.x style convert it back to python string- content = np.array(content, copy=False, dtype=str).tolist()+ content = np.asarray(content, dtype=str).tolist() else: # decode bytes representing python string before final conversiondiff --git a/hickle/loaders/load_numpy.py b/hickle/loaders/load_numpy.pyindex a4c76e91..bff98187 100644--- a/hickle/loaders/load_numpy.py+++ b/hickle/loaders/load_numpy.py@@ -232,7 +232,7 @@ def load_ndarray_dataset(h_node,base_type,py_obj_type): # not converted to list of string but saved as ar consequently # itemsize of dtype is > 1 string_data = bytes(string_data).decode("utf8")- return np.array(string_data,copy=False,dtype=dtype)+ return np.asarray(string_data,dtype=dtype) if issubclass(py_obj_type,np.matrix): return py_obj_type(data=h_node[()],dtype=dtype) # TODO how to restore other ndarray derived object_typesdiff --git a/hickle/tests/test_02_hickle_lookup.py b/hickle/tests/test_02_hickle_lookup.pyindex 628a2b12..dd91ffd1 100644--- a/hickle/tests/test_02_hickle_lookup.py+++ b/hickle/tests/test_02_hickle_lookup.py@@ -816,7 +816,7 @@ def test_ReferenceManager_get_root(h5_data): content = data_group.create_dataset('mydata',data=12) type_table = root_group.create_group('hickle_types_table') int_pickle_string = bytearray(pickle.dumps(int))- int_np_entry = np.array(int_pickle_string,copy=False)+ int_np_entry = np.asarray(int_pickle_string) int_np_entry.dtype = 'S1' int_entry = type_table.create_dataset(str(len(type_table)),data = int_np_entry,shape =(1,int_np_entry.size)) int_base_type = b'int'@@ -878,7 +878,7 @@ def test_ReferenceManager(h5_data): with pytest.raises(lookup.ReferenceError): reference_manager = lookup.ReferenceManager(false_root) int_pickle_string = bytearray(pickle.dumps(int))- int_np_entry = np.array(int_pickle_string,copy=False)+ int_np_entry = np.asarray(int_pickle_string) int_np_entry.dtype = 'S1' int_entry = type_table.create_dataset(str(len(type_table)),data = int_np_entry,shape =(1,int_np_entry.size)) int_base_type = b'int'@@ -1052,7 +1052,7 @@ def test_ReferenceManager_store_type(h5_data,compression_kwargs): @pytest.mark.no_compression def test_ReferenceManager_get_manager(h5_data): h_node = h5_data.create_group('some_list')- item_data = np.array(memoryview(b'hallo welt lore grueszet dich ipsum aus der lore von ipsum gelort in ipsum'),copy=False)+ item_data = np.asarray(memoryview(b'hallo welt lore grueszet dich ipsum aus der lore von ipsum gelort in ipsum')) item_data.dtype = 'S1' h_item = h_node.create_dataset('0',data=item_data,shape=(1,item_data.size)) with lookup.ReferenceManager.create_manager(h5_data) as memo: