![]() ![]() Accept these possibilities and move on to the next candidate. Others you may need to pass over and accept either because there is no quick and easy solution or because the code is already well optimised and no significant improvement is possible. Some you will not get to because you’ve met your goal. This means you will not eliminate all bottlenecks. To enforce this advice, you should set a goal time for your code and optimise only up to that goal. Be pragmatic: don’t spend hours of your time to save seconds of computer time. Don’t! Your time is valuable and is better spent analysing your data, not eliminating possible inefficiencies in your code. ![]() It’s easy to get caught up in trying to remove all bottlenecks. I’ll also suggest a general strategy for performance optimisation that helps ensure that your faster code is still correct. It’s difficult to provide general advice on improving performance, but I try my best with four techniques that can be applied in many situations. Once you’ve used profiling to identify a bottleneck, you need to make it faster. The critical code but only after that code has been identified. Into complacency by such reasoning, he will be wise to look carefully at Premature optimization is the root of all evil. We should forget about small efficiencies, say about 97% of the time: ![]()
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