What are some performance tips for using the standard library?

What are some performance tips for using the standard library?

To improve performance when using the standard library, consider the following tips: 1. Use built-in functions as they are optimized. 2. Avoid unnecessary data copying by using references. 3. Leverage lazy evaluation where possible. 4. Profile your code to identify bottlenecks.

Can you explain how lazy evaluation works?

Lazy evaluation means that an expression is not evaluated until its value is actually needed. This can save time and resources, especially when dealing with large datasets or complex calculations.

What built-in functions should I prioritize for performance?

Focus on functions like map(), filter(), and reduce(), as they are optimized for performance and can handle large datasets efficiently.

How can I profile my code to find bottlenecks?

You can use profiling tools like cProfile in Python or the built-in profiler in your IDE. These tools help you identify which parts of your code are consuming the most time.