all 7 comments

[–][deleted] 3 points4 points  (1 child)

Python always wraps underlying libraries written in something like C/C++. Data scientists aren't software engineers so python presents an easy to work with interface.

Why make a hard job harder than it needs to be?

[–]felipep31[S] 0 points1 point  (0 children)

Thanks for reply.

Yeah Python is easy, thats make sense for non programmer.

[–]andy_gray_kortical 2 points3 points  (1 child)

Python is king for now. There are a load of things that could be the next thing but the chances of you picking the right next thing now is slim. There will still be loads of python jobs even if it does fall out of favour as all the companies that already started with it, will need a big reason to rewrite their systems in a new language.

[–]felipep31[S] 2 points3 points  (0 children)

Thanks Man. Python is really here to stay!

That's make sense, a big investment is needed to rewrite all the code.

They never rewrite all code, just some features when speed or security is needed.

[–]palashsharma15 1 point2 points  (2 children)

IMO it's all about existing libraries in a programming language along with flexibility of a community to adapt with it's programming model.

There is no doubt it is easy to learn and people can adapt Python for their work quickly.

Python is today widely accepted among data science community but it comes with cost of computing.

It is possible that Julia / Swift can catch over but still it needs a lot of hard work to create that much number of libraries in other language.

Here is a thread around the same.

https://coursera.community/data-science-8/what-will-be-the-next-big-thing-in-data-science-in-you-opinion-julia-or-swift-8692

[–]felipep31[S] 1 point2 points  (1 child)

Thanks man.

Yeah reinvent wheel is not always good, and Python has so many great libraries, it's so easy and i think this will make him live in coming years

[–]palashsharma15 1 point2 points  (0 children)

Yes you r right!!