However, Python’s methods for parallelizing operations often require data to be serialized and deserialized between threads or nodes, while Julia’s parallelization is more refined.

His argument against Python is that a person using it for data science needs to learn about extra Python packages, like NumPy, which brings Matlab-like data-analysis powers to Python.

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