It is of cause possible to write a faster Python, as PyPy proves, but some of the design choices in Python does make it hard to optimize. This is not inherently

It is of cause possible to write a faster Python, as PyPy proves, but some of the design choices in Python does make it hard to optimize. This is not inherently a problem with dynamic languages as the development of Julia proves. In Julia it is easy to write programs that is in the same ballpark as C efficiency wise, while still feeling very dynamic and having a REPL. Pythons problem is that both the interpreter and the language is quite old, and existed before modern JIT technology was developed, so that was not considered when designing the language and the interpreter. That said, Python emphasis on fast development as opposed to fast running code is very often the right tradeoff, and is why it is so popular.