Added method to reformat columns containing datetime byte strings into a desired datetime formated object

src/hdf5_data_extraction.py

@@ -5,6 +5,7 @@ import os
 import src.hdf5_vis as hdf5_vis
 import src.g5505_utils as utils
 import logging
+import datetime
 
 class HDF5DataOpsManager():
     def __init__(self, file_path, mode = 'r+') -> None:
@@ -14,6 +15,7 @@ class HDF5DataOpsManager():
         self.file_path = file_path        
         self.file_obj = None
         self._open_file()
+        self.list_of_datasets = []        
 
     # Define private methods
     
@@ -78,6 +80,38 @@ class HDF5DataOpsManager():
         self.file_obj[group_name].create_dataset(dataset_dict['name'], data=dataset_dict['data'])
         self.file_obj[group_name][dataset_dict['name']].attrs.update(dataset_dict['attributes'])
 
+    def reformat_datetime_column(self, dataset_name, column_name, src_format, desired_format = '%Y-%m-%d %H:%M:%S.%f'):
+
+        dataset = self.file_obj[dataset_name]
+   
+        dt_column_data = dataset[column_name][:]
+    
+        # Convert byte strings to datetime objects
+        timestamps = [datetime.datetime.strptime(a.decode(), src_format).strftime(desired_format) for a in dt_column_data]    
+        
+        #datetime.strptime('31/01/22 23:59:59.999999',
+        #          '%d/%m/%y %H:%M:%S.%f')
+        
+        #pd.to_datetime(
+        #    np.array([a.decode() for a in dt_column_data]),
+        #    format=src_format,
+        #    errors='coerce'
+        #)
+    
+
+        # Standardize the datetime format
+        #standardized_time = datetime.strftime(desired_format)
+
+        # Convert to byte strings to store back in the HDF5 dataset
+        #standardized_time_bytes = np.array([s.encode() for s in timestamps])
+
+        # Update the column in the dataset (in-place update)
+        # TODO: make this a more secure operation
+        #dataset[column_name][:] = standardized_time_bytes
+
+        return np.array(timestamps)
+        
+
 
 
 def read_dataset_from_hdf5file(hdf5_file_path, dataset_path):