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Profile Your Codeīefore attempting to optimize your code, it’s essential to profile it to identify performance bottlenecks. Using generators can help you optimize memory usage and improve performance. This can be particularly useful when working with large data sets or when generating an infinite sequence. Generators are a powerful feature in Python that allow you to iterate over a sequence of values without creating a full list in memory. Using list comprehensions can help you write more readable and efficient code. They can be more efficient than using loops and appending items to a list, especially for large data sets. List comprehensions provide a concise way to create lists in Python. Instead, pass variables as function arguments or use classes to encapsulate state. They can lead to unintended side effects and make your functions less modular. Global variables can make your code harder to understand and maintain. Using built-in functions and libraries can save time, reduce the chance of errors, and improve code readability. Before reinventing the wheel, check if there’s already a built-in solution that can handle the task. Python comes with a rich set of built-in functions and standard libraries that can help you accomplish tasks more efficiently. Photo by David Clode on Unsplash Use Built-in Functions and Libraries