[typon]

I don't understand this logic. The users are learning Python, not C++ when they're trying to learn data science or implement a machine learning model. Should I say Tensor flow isn't written in C++ but CUDA or OpenCL? Any self respecting researcher is training their models on GPU or FPGA, not CPU.

The point is that Python is the entry point for large majority of data scientists currently and its absolutely disingenuous to try to dispute that reality.

[_underfl0w_]

> The users are learning Python, not C++

The key word here is "users". Python is fantastic for users. It allows users to get things done without having to worry about types or memory or the underlying hardware in any way.

[wwright]

I’d say it’s very disingenuous to claim that Python users don’t have to care about types. Many types are directly related to semantics, so of course they have to care about types!

I think Python made some really good choices with their types from UX that lead to you having to care more about your logic than the machine. Only one integer type, for example! For most users it’s perfect UX.

However, I think (possibly due to the early time when a Python was made) some of the decisions made practical but regrettable trade offs. Duck typing is ultimately just type inference with strong performance penalties and really weak static tooling, for example. _Many_ static type systems are still very far from the user’s actual domain, but the core techniques don’t have to be.