Treffer: Improving efficiency in list creation: Utilizing Python's list comprehension.

Performance optimization is a crucial aspect of software development, particularly in interpreted languages like Python. This paper explores the optimization of Python programs, focusing on the comparison of for loops and list comprehensions. We analyze the performance of these constructs on Google Colab. Our results indicate that list comprehensions outperform for loops in terms of execution time, providing valuable insights for Python developers seeking to enhance the efficiency of their code, particularly in the context of data science and artificial intelligence (AI) applications, where performance is critical. [ABSTRACT FROM AUTHOR]