Elevate your code optimisation techniques. Explore profiling, JIT compilation, concurrency, and more to enhance your code's performance and efficiency.
Python is a highly popular programming language, widely used in various fields like software development, data analysis, AI, and machine learning. Its simple syntax and structure make it easy to learn and work with. With such a broad applications, code optimization – ensuring efficient and effective functioning of software – is a critical requirement.
It is important to recognize and address this issue, choosing more efficient data structures, algorithms, and external libraries for performance-critical sections. Common Performance Bottlenecks in Python Common Performance Bottlenecks in Python The typical bottleneck areas described below can significantly impact runtime efficiency, and understanding them is key to enhancing overall performance.
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