unpin numpy to enable working with numpy version 2 as well

pyproject.toml

@@ -27,7 +27,7 @@ dependencies = [
     "h5py>=3.6.0",
     "xarray>=0.20.2",
     "PyYAML>=6.0",
-    'numpy>=1.22.4,<2.0.0',
+    'numpy',
     "pandas>=1.3.2",
     "ase>=3.19.0",
     "mergedeep",
@@ -140,7 +140,7 @@ select = [
     "UP", # pyupgrade
     # "F401", # remove unused import
     "I001", # sort imports
-    # "NPY201", # reactivate when np>2.0 is used
+    "NPY201", # upgrade to numpy>2
 ]
 ignore = [
     "E402", # Module level import not at top of file

src/pynxtools/dataconverter/hdfdict.py

@@ -7,7 +7,6 @@
 
 import h5py
 import yaml
-from numpy import string_
 
 TYPE = "_type_"
 
@@ -45,7 +44,8 @@ def unpack_dataset(item):
 
     """
     value = item[()]
-    type_id = item.attrs.get(TYPE, string_()).astype(str)
+    type_id = item.attrs.get(TYPE, "")
+
     if type_id == "datetime":
         if hasattr(value, "__iter__"):
             value = [datetime.fromtimestamp(ts) for ts in value]
@@ -62,7 +62,7 @@ def unpack_dataset(item):
         value = tuple(value)
 
     elif type_id == "str":
-        value = string_(value).astype(str)
+        value = value.decode("utf-8") if isinstance(value, bytes) else value
 
     return value
 
@@ -181,15 +181,16 @@ def pack_dataset(hdfobject, key, value):
             attr_data = None
 
         if attr_data:
-            ds.attrs.create(name=TYPE, data=string_(attr_data))
+            ds.attrs.create(name=TYPE, data=attr_data.encode("utf-8"))
 
     except (TypeError, ValueError):
         # Obviously the data was not serializable. To give it
         # a last try; serialize it to yaml
         # and save it to the hdf file:
-        ds = hdfobject.create_dataset(name=key, data=string_(yaml.safe_dump(value)))
-
-        ds.attrs.create(name=TYPE, data=string_("yaml"))
+        ds = hdfobject.create_dataset(
+            name=key, data=yaml.safe_dump(value).encode("utf-8")
+        )
+        ds.attrs.create(name=TYPE, data=b"yaml")
         # if this fails again, restructure your data!
 
 

tests/dataconverter/test_validation.py

@@ -32,6 +32,12 @@
 
 from .test_helpers import alter_dict  # pylint: disable=unused-import
 
+# Workaround for different str representation of np.bool
+if np.lib.NumpyVersion(np.__version__) >= "2.0.0":
+    np_bool = "numpy.bool"
+else:
+    np_bool = "numpy.bool_"
+
 
 def set_to_none_in_dict(data_dict: Optional[Template], key: str, optionality: str):
     """Helper function to forcefully set path to 'None'"""
@@ -468,8 +474,7 @@ def format_error_message(msg: str) -> str:
                 "NOT_TRUE_OR_FALSE",
             ),
             [
-                "The value at /ENTRY[my_entry]/NXODD_name[nxodd_name]/bool_value should be one of the following Python types: "
-                "(<class 'bool'>, <class 'numpy.bool_'>), as defined in the NXDL as NX_BOOLEAN."
+                f"The value at /ENTRY[my_entry]/NXODD_name[nxodd_name]/bool_value should be one of the following Python types: (<class 'bool'>, <class '{np_bool}'>), as defined in the NXDL as NX_BOOLEAN."
             ],
             id="string-instead-of-bool",
         ),
@@ -1906,7 +1911,7 @@ def format_error_message(msg: str) -> str:
             alter_dict(
                 TEMPLATE,
                 "/ENTRY[my_entry]/NXODD_name[nxodd_name]/int_value",
-                {"compress": np.int64(2), "strength": 11},
+                {"compress": 2, "strength": 11},
             ),
             [
                 "Compression strength for /ENTRY[my_entry]/NXODD_name[nxodd_name]/int_value = "
@@ -2015,7 +2020,7 @@ def test_validate_data_dict(data_dict, error_messages, caplog, request):
             ),
             [
                 "The value at /my_entry/nxodd_name/bool_value should be one of the following Python types: "
-                "(<class 'bool'>, <class 'numpy.bool_'>), as defined in the NXDL as NX_BOOLEAN."
+                f"(<class 'bool'>, <class '{np_bool}'>), as defined in the NXDL as NX_BOOLEAN."
             ],
             id="string-instead-of-bool",
         ),