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