test.py

# # import subprocess
# # import tempfile
# # import os
# # import re
# # import myers

# # def get_similarity_index(old: str, new: str) -> tuple[str, float]:
# #     def get_lines(text: str) -> list[str]:
# #         return text.replace('\r\n', '\n').strip().splitlines()

# #     def get_changes(old: list[str], new: list[str]) -> list[tuple[str, str]]:
# #         changes = myers.diff(old, new)
# #         return changes
# #     old_lines = get_lines(old)
# #     new_lines = get_lines(new)
# #     changes = get_changes(old_lines, new_lines)
# #     print(changes)
    
# #     num_unchanged_lines = sum(1 for op, _ in changes if op == 'k')
    
# #     # Calculate similarity
# #     total_lines = len(old_lines) + len(new_lines)
# #     if total_lines == 0:
# #         similarity = 100.0
# #     else:
# #         similarity = round(2 * num_unchanged_lines / total_lines * 100, 2)

# #     return similarity
# # # Example usage
# # code1 = """
# # def hello():
# #     print("Hello, World!")
# #     return True
# # """

# # code2 = """
# # def hello():
# #     print("Hello, Python!")
# #     return True
# # """

# # similarity = get_similarity_index(code1, code2)
# # print(f"Similarity index: {similarity}%")

# # # Test with more different codes
# # code3 = """
# # def calculate(x, y):
# #     return x + y
# # """

# # code4 = """
# # def multiply(a, b):
# #     return a * b
# # """

# # similarity2 = get_similarity_index(code3, code4)
# # print(f"Similarity index for different functions: {similarity2}%")

# import pandas as pd

# df = pd.read_csv("data/migrations_36_file_version.csv")
# print(df.info())

# import difflib


# # Example usage:
# old_code = """def hello():
#     print("Hello")
#     return True"""

# new_code = """def hello():
#     print("Hello, World!")
#     return True
#     """

# compare_code_snippets(old_code, new_code)