<ul><li>Python's performance is affected by being interpreted and not compiled like C or Java.</li><li>Using Just-In-Time (JIT) compilation, such as PyPy, can improve performance by compiling parts of the code at runtime.</li><li>Python's Global Interpreter Lock (GIL) restricts true parallel execution of Python threads, hindering CPU-bound applications.</li><li>The dynamic typing feature in Python, while providing flexibility and expressiveness, incurs a performance cost.</li></ul>

The Dark Side of Python: Why It’s Slower Than You Think

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