Python's performance is influenced by its interpreter processing code line-by-line, offering rapid development but with speed trade-offs, emphasizing efficient data structures and algorithms for better performance.
Common performance bottlenecks in Python include I/O operations, which can significantly impact runtime efficiency, stressing the importance of optimizing code in various fields like software development, AI, and data analysis.
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