import re

def like_processing_content_preprocess(content):

content_modified = []

for line in content:

# Split the line into the part to be processed and the part to be ignored (comment)

parts = line.split("//", 1)

process_part = parts[0] # Part to be processed

comment_part = "//" + parts[1] if len(parts) > 1 else "" # Comment part with slashes

# Mockup function to process the part to be processed

processed_part, reverse_info = process_like_statements(process_part)

if reverse_info != "":

content_modified.append(reverse_info)

# Reassemble both parts into a single line

modified_line = processed_part + comment_part

content_modified.append(modified_line)

return content_modified

def like_processing_content_restore(content_modified):

restored_content = []

processing_info_found = False

processing_info = ""

for line in content_modified:

if line.strip().startswith("// LIKEPROCESSING_INFO:"):

# Found a line containing 'LIKEPROCESSING_INFO'

processing_info_found = True

processing_info = line.strip()[len("// LIKEPROCESSING_INFO:"):].split(",")

continue

if processing_info_found:

# Restore the original content

original_line = revert_like_statements(line, processing_info)

restored_content.append(original_line)

processing_info_found = False

else:

restored_content.append(line)

return restored_content

def revert_like_statements(line, processing_info):

restored_line = line

equals_positions = [i for i, char in enumerate(restored_line) if char == '=']

offset = 0

for equals_to_skip in processing_info:

equals_to_skip = int(equals_to_skip)

# Ensure the equals_to_skip is within the range of equals positions

if 0 <= equals_to_skip < len(equals_positions):

replacement_index = equals_positions[equals_to_skip]

restored_line = restored_line[:replacement_index + offset] + 'like' + restored_line[replacement_index + 1 + offset:]

# like as 3 chars more than = so advance

offset = offset + 3

return restored_line

def process_like_statements(part):

# Regular expression pattern to find all occurrences of 'like' (case insensitive)

pattern = r'\blike\b'

# Find all occurrences of 'like' (case insensitive) and replace them with '='

processed_part = re.sub(pattern, '=', part, flags=re.IGNORECASE)

# Initialize the reverse info

reverse_info = ""

found_likes = 0

# If 'like' processing occurred

if re.search(pattern, part, flags=re.IGNORECASE):

# Create a string to facilitate reverse replacement

# This string will be a comment with slashes starting with 'LIKEPROCESSING_INFO'

# Each 'like' replacement is indicated by the number of '=' to be skipped

# So that the reverse function knows where a '=' should be replaced by a 'like'

reverse_info = "// LIKEPROCESSING_INFO: "

like_positions = [m.start() for m in re.finditer(pattern, part, flags=re.IGNORECASE)]

for pos in like_positions:

# Count the number of '=' to skip

equals_to_skip = part.count('=', 0, pos)

reverse_info += str(equals_to_skip + found_likes) + ","

# each processed like makes a extra skip for restoring

found_likes = found_likes + 1

# Remove the last comma

reverse_info = reverse_info[:-1]

# make a full comment line if like is found

if found_likes > 0:

reverse_info = reverse_info + '\n'

# Return both the processed part and the reverse info

return processed_part, reverse_info

if __name__ == '__main__':

import chardet

def detect_encoding(file_path):

with open(file_path, 'rb') as f:

result = chardet.detect(f.read())

return result['encoding']

filename = "tests/test_like_handling.pas"

# Example usage:

source_encoding = detect_encoding(filename)

# Modify the file content

with open(filename, 'r', encoding=source_encoding, errors='ignore') as original_file:

content = original_file.readlines()

for line in content:

print(repr(line))

content_modified = like_processing_content_preprocess(content)

for line in content_modified:

print(repr(line))

restored_content = like_processing_content_restore(content_modified)

for line in restored_content:

print(repr(line))