Update all file readers with command line interface so we can run them as a subprocess. Added also registry.yaml to decouple code from user-based instrument adaptations or extensions.

instruments/readers/acsm_flag_reader.py

@@ -0,0 +1,101 @@
+import sys
+import os
+
+try:
+    thisFilePath = os.path.abspath(__file__)
+except NameError:
+    print("Error: __file__ is not available. Ensure the script is being run from a file.")
+    print("[Notice] Path to DIMA package may not be resolved properly.")
+    thisFilePath = os.getcwd()  # Use current directory or specify a default
+
+dimaPath = os.path.normpath(os.path.join(thisFilePath, "..",'..','..'))  # Move up to project root
+
+if dimaPath not in sys.path:  # Avoid duplicate entries
+    sys.path.insert(0,dimaPath)
+    
+import pandas as pd
+import collections
+import json
+import h5py
+import argparse
+import logging
+
+import utils.g5505_utils as utils
+
+
+
+def read_jsonflag_as_dict(path_to_file):
+
+
+    file_dict = {}
+    path_tail, path_head = os.path.split(path_to_file)
+
+    file_dict['name'] = path_head
+    # TODO: review this header dictionary, it may not be the best way to represent header data
+    file_dict['attributes_dict'] = {}
+    file_dict['datasets'] = []
+
+    try:
+        with open(path_to_file, 'r') as stream:
+            flag = json.load(stream)#, Loader=json.FullLoader)
+    except (FileNotFoundError, json.JSONDecodeError) as exc:
+        print(exc)
+
+    dataset = {}
+    dataset['name'] = 'data_table'#_numerical_variables'
+    dataset['data'] = utils.convert_attrdict_to_np_structured_array(flag) #df_numerical_attrs.to_numpy()
+    dataset['shape'] = dataset['data'].shape
+    dataset['dtype'] = type(dataset['data'])  
+
+    file_dict['datasets'].append(dataset)
+
+    return file_dict
+
+if __name__ == "__main__":
+
+    from src.hdf5_ops import save_file_dict_to_hdf5
+    from utils.g5505_utils import created_at
+
+    # Set up argument parsing
+    parser = argparse.ArgumentParser(description="Data ingestion process to HDF5 files.")
+    parser.add_argument('dst_file_path', type=str, help="Path to the target HDF5 file.")
+    parser.add_argument('src_file_path', type=str, help="Relative path to source file to be saved to target HDF5 file.")
+    parser.add_argument('dst_group_name', type=str, help="Group name '/instFolder/[category]/fileName' in the target HDF5 file.")
+
+    args = parser.parse_args()
+
+    hdf5_file_path = args.dst_file_path
+    src_file_path = args.src_file_path
+    dst_group_name = args.dst_group_name
+    default_mode = 'r+'
+
+    try:
+        # Read source file and return an internal dictionary representation
+        idr_dict = read_jsonflag_as_dict(src_file_path)
+
+        if not os.path.exists(hdf5_file_path):
+            default_mode = 'w'
+
+        print(f'Opening HDF5 file: {hdf5_file_path} in mode {default_mode}')
+        
+        with h5py.File(hdf5_file_path, mode=default_mode, track_order=True) as hdf5_file_obj:
+            try:
+                # Create group if it does not exist
+                if dst_group_name not in hdf5_file_obj:
+                    hdf5_file_obj.create_group(dst_group_name)
+                    hdf5_file_obj[dst_group_name].attrs['creation_date'] = created_at().encode('utf-8')
+                    print(f'Created new group: {dst_group_name}')
+                else:
+                    print(f'Group {dst_group_name} already exists. Proceeding with data transfer...')
+
+            except Exception as inst:
+                logging.error('Failed to create group %s in HDF5: %s', dst_group_name, inst)
+
+            # Save dictionary to HDF5
+            save_file_dict_to_hdf5(hdf5_file_obj, dst_group_name, idr_dict)
+            print(f'Completed saving file dict with keys: {idr_dict.keys()}')
+
+    except Exception as e:
+        logging.error('File reader failed to process %s: %s', src_file_path, e)
+        print(f'File reader failed to process {src_file_path}. See logs for details.')
+