fix: add compatibility for NumPy bool_ type in variable explorer

FilipPyrek · FilipPyrek · commit bde9f363b98f · 2025-11-03T14:06:35.000+01:00
This update introduces a new function, _get_type_name, to ensure that the type name for NumPy's bool_ is consistently returned as 'bool_' across different Python versions, particularly for Python 3.13. The variable type retrieval in _get_variable_dict_entry has been updated to use this new function.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -11,13 +11,13 @@ repos:
     hooks:
       - id: flake8
         name: flake8
-        entry: poetry run flake8 -j auto
+        entry: mise exec -- poetry run flake8 -j auto
         language: system
         types: [python]
 
       - id: isort
         name: isort
-        entry: poetry run isort
+        entry: mise exec -- poetry run isort
         language: system
         types: [python]
         args: ["--filter-files"]
diff --git a/deepnote_toolkit/variable_explorer.py b/deepnote_toolkit/variable_explorer.py
@@ -407,6 +407,27 @@ def _to_int(x):
     return int(x) if x else None
 
 
+def _get_type_name(v):
+    """
+    Get the normalized type name for a variable with backwards compatibility.
+
+    In Python 3.13, NumPy's bool_ type may report as 'bool' instead of 'bool_'.
+    This function ensures we always return 'bool_' for NumPy bool types to maintain
+    compatibility with older Python versions.
+    """
+    # Check for NumPy bool_ type first (most reliable check)
+    # This handles the case where Python 3.13 reports np.bool_ as 'bool'
+    try:
+        if np is not None and isinstance(v, np.bool_):
+            return "bool_"
+    except (AttributeError, TypeError):
+        # If numpy types change or there's an issue with the comparison
+        pass
+
+    # Fall back to standard type name
+    return type(v).__name__
+
+
 def _get_variable_dict_entry(var_name, v):
     try:
         shape = _get_shape(v)
@@ -415,7 +436,7 @@ def _get_variable_dict_entry(var_name, v):
         underlying_data_type = _get_underlying_data_type(v)
         var_result = {
             "varName": var_name,
-            "varType": type(v).__name__,
+            "varType": _get_type_name(v),
             "varSize": _to_int(_get_size(v)),
             "varShape": shape,
             "varContent": _get_content(v),
