![]() I even developed a custom package to make debugging easier. This is Wolframs strengths, and really powerful, but makes debugging not fun. I don’t miss all the and at all.Īlso with Wolfram debugging was a nightmare, especially since everything is a symbol and a function can take everything from an image to a sound or an integer as input. I just like how readable the code is and how easy it is to maintain large code bases. So this time the focus is more on the perspective of a past Mathematica user, while the last one was from a Mathematica user who tried a little bit of Python. All I know is that Python is free for all use cases.Īs a disclaimer and spoiler up front: I did not use Mathematica beyond 11 and transitioned to 100% Python. ![]() I don’t know all the details about Wolframs licensing scheme and don’t want to read all the fine print. Although, the free Engine is a nice idea and opens up the ecosystem a bit it is still not free for production or even research. On the Wolfram side Mathematica 13.2 is released and the ecosystem became a bit more open with Python integration and even a “free” Wolfram Engine. Also new packages like streamlit and FastAPI help to get your data science projects out there even faster. Python gained a lot in popularity especially due to the influx of data scientist. So I think it deserves an update.įour years is a long time and a lot has changed. Also, I got some direct enquires by Wolfram employees and an enquire to write a book. It gained quite some popularity and reached place one on the google search. It has been now almost four years since my last post about Mathematica vs Python.
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