Incorporated dataframe_to_np_structured_array(df: pd.DataFrame) from another module.

src/g5505_utils.py

@@ -105,4 +105,26 @@ def created_at():
     created_at = now_tz_aware.strftime('%Y-%m-%d')+'_UTC-OFST_' + tz
     # Make created at timestamp with tz information
     #created_at = now.isoformat()
-    return created_at
+    return created_at
+
+def dataframe_to_np_structured_array(df: pd.DataFrame):
+
+     # Define the dtype for the structured array, ensuring compatibility with h5py
+    dtype = []
+    for col in df.columns:
+        col_dtype = df[col].dtype
+        if pd.api.types.is_string_dtype(col_dtype):
+            # Convert string dtype to fixed-length strings
+            max_len = df[col].str.len().max()
+            dtype.append((col, f'S{max_len}'))
+        elif pd.api.types.is_integer_dtype(col_dtype):
+            dtype.append((col, 'i4'))  # Assuming 32-bit integer
+        elif pd.api.types.is_float_dtype(col_dtype):
+            dtype.append((col, 'f4'))  # Assuming 32-bit float
+        else:
+            raise ValueError(f"Unsupported dtype: {col_dtype}")
+
+    # Convert the DataFrame to a structured array
+    structured_array = np.array(list(df.itertuples(index=False, name=None)), dtype=dtype)
+
+    return structured_array