import re import json import pandas as pd import pprint from copy import deepcopy def debug_print_db_struct(db_struct): pprint.pprint( db_struct, width=80, indent=2 ) # Ajusta el parámetro 'width' según necesidad def expand_udt_references(db_struct, udts): """ Recursively expand UDT references in the given DB structure using the UDT definitions. This function specifically expands fields designated as 'type' which reference UDTs. """ if isinstance(db_struct, dict): for key, value in list(db_struct.items()): if isinstance(value, dict): # Recurse into dictionaries expand_udt_references(value, udts) elif isinstance(value, str) and key == "type": # Only expand 'type' fields type_name = value.strip( '"' ) # Remove quotes which may wrap UDT names with spaces if type_name in udts: # Replace the UDT reference with its deeply copied definition db_struct["fields"] = deepcopy(udts[type_name]) print(f"Expanded UDT '{type_name}' at field '{key}'") elif isinstance(db_struct, list): for item in db_struct: expand_udt_references(item, udts) def handle_array_types(db_struct): """ Handle array types to expand them into multiple fields as sub-elements while preserving comments. Modifies the structure in place by expanding array definitions within their original field. """ if isinstance(db_struct, dict): for key, value in list(db_struct.items()): if isinstance(value, dict): # Recursively process nested dictionaries handle_array_types(value) if isinstance(value, dict) and "type" in value: match = re.match(r"Array\[(\d+)\.\.(\d+)\] of (\w+)", value["type"]) if match: lower_bound, upper_bound, base_type = ( int(match.group(1)), int(match.group(2)), match.group(3), ) comment = value.get("comment", "") # Instead of popping the original key, initialize a sub-dictionary value["Array"] = ( {} ) # Initialize a sub-dictionary for array elements for i in range(lower_bound, upper_bound + 1): element_key = f"[{i}]" value["Array"][element_key] = { "type": base_type, "comment": comment, "is_array_element": True, } # Optionally, modify or remove the original type designation if necessary # value.pop('type', None) # Uncomment this if you want to remove the 'type' from the original # Continue the recursive handling if it's not an array definition elif isinstance(value, dict): handle_array_types(value) type_sizes = { "Int": 2, "DInt": 4, "Word": 2, "Real": 4, "Bool": 2, # We'll adjust this dynamically based on context (1 byte if alone, 1 bit if grouped) "String": 1, # This will be multiplied by the specified size in brackets [n] } def calculate_plc_address(type_name, byte_offset, bit_offset=None): """ Calculate the PLC address notation based on byte size, byte offset and bit offset. """ byte_size = type_sizes.get(type_name, 0) if type_name == "Bool": if bit_offset is not None: return f"DBX{byte_offset}.{bit_offset}" # Address for single bits return f"DBB{byte_offset}" # Address for single bytes elif byte_size == 2: return f"DBW{byte_offset}" # Address for two-byte words elif byte_size == 4: return f"DBD{byte_offset}" # Address for four-byte double words else: return f"DBX{byte_offset}.0" # Default to bit address for types longer than 4 bytes (e.g., strings) def calculate_offsets(db_struct, current_offset=0): """ Recursively calculate byte offsets for each field in the DB structure considering special types. """ is_array_element = False last_key_was_bool = False last_bit_offset = 0 # To track bit offsets within a byte if isinstance(db_struct, dict): for key, value in db_struct.items(): # Skip 'fields' and 'Struct' keys in the name path # if ( isinstance(value, dict) and "type" in value ): # Directly a field with 'type' type_name = value["type"] is_array_element = value.get("is_array_element", False) size = type_sizes.get( type_name, 0 ) # Default to 1 byte if type is not recognized if not is_array_element and current_offset % 2 != 0: current_offset += ( 1 # Align to the next even offset if it's not an array element ) last_bit_offset = 0 plc_address = calculate_plc_address( type_name, current_offset, last_bit_offset ) # Special handling for String types if "String" in type_name: match = re.match(r"String\[(\d+)\]", type_name) last_bit_offset = 0 if match: length = int(match.group(1)) size = ( length + 2 ) # Account for null-termination and string length prefix else: size = type_sizes.get( type_name, 1 ) # Default to generic size if not an array # Adjusting Bool sizes based on grouping if type_name == "Bool": if last_key_was_bool: # This is a grouped bool last_bit_offset += 1 # One bit per Bool if grouped else: size = 2 # Bools use a full byte if not grouped last_bit_offset = 0 last_key_was_bool = True else: last_key_was_bool = False value["offset"] = current_offset value["plc_address"] = plc_address # Store the calculated PLC address # print(f"Offset '{current_offset}' at field '{key}' ") current_offset += size # Recursively handle nested dictionaries and lists if isinstance(value, dict) or isinstance(value, list): current_offset = calculate_offsets(value, current_offset) elif isinstance(db_struct, list): for index, item in enumerate(db_struct): for item in db_struct: current_offset = calculate_offsets(item, current_offset) return current_offset def expand_dbs(udts, dbs): """ Expand all UDT references in all DBs and then handle array types. """ for db_name, db_content in dbs.items(): print(f"Expanding DB: {db_name}") expand_udt_references(db_content, udts) handle_array_types(db_content) calculate_offsets(db_content) print(f"Completed expansion for DB: {db_name}")