flatbield

I think it depends on how good your Numpy build is. Lot of Numpys are not that well built so Numba seems to help there too in that case.

For a python library to be fast it needs to be compiled for your specific hardware, vectorized, with fast math, and auto parallel. Most are probably not unless you build them youself.

Yes we know who Musk is… and it is a very mixed bag. Some where around the time he became the world’s richest person I feel like something changed and he went over the top or over the edge. Not sure which.

People use Python a lot as a Matlab, Excel/VBA, or R alternative. That was my use for many years. Some of these are compute focused problems and if the dataset is large enough and the computations complex enough then speed can be an issue.

As far as loading packages and printing. Who cares. These are not computationally intensive and are typically IO bound.

Yes, I hate indentation as structure but I hate tracking brackets even more.

Same for me. I have used Python for most things since the late 1990s. Love Python. Have always hated the poor performance… but in my case mostly it was good enough. When it was not good enough, I wrote C code.

Python is good for problems where time to code is the limiting factor. It sucks for compute bound problems where time to execute is the limiting factor. Most problems in my world are time to code limited but some are not.

Python compute performance has always sucked.

Just remember that an optimized C program will run about 100x faster then a similar Python program in a compute bound problem. So yes Python is slow but often good enough.

Reason you do not need Typescript for Python is that it is a real language. JavaScript was a crap extension language that people have been trying to get around forever with preprocessors…

As far as needing types… One of the big advantages of Python is not needing types. I have used Python for 25 years and never used types or missed them.

What I do occasionally miss is speed. That is a combination of lack of typing and crap implementations and there are various ways around it.

Yes Numba is the way. Well that or fully optimized, vectorized, and parallelized C.

You get an IT staff that is MS and Windows certified, what sort of answer do you expect them to give? As far as IT staff where I worked, they often had issues with resolving Windows problems say nothing about Linux. Generally for Windows, I had to get to level 3 support before they knew anything. Even then I often had to tell them what needed to be done rather then them actually knowing. Some of this is lack of skill, some if it is under staffing, some of it is restrictive processes, and some organizational issues. You had to know how to work the system on one hand, and which issues just to not waste time on. Not saying they did not try hard, but without facilitation their results were often insufficient.

That does not mean you cannot use Linux however. Just means the main IT group does not support. We had a separate group that ran the Linux compute cluster we used. I also typically always had a Linux VM on my workstation too to use FOSS tools. Not sure that would be allowed these days since IT has gotten nuts about security, and with that they have generally grabbed a lot of power regarding what can and cannot be done on “their” hardware and on “their” networks. You can also get exceptions to a lot of those rules if you can justify it and if your management is willing to run it up the flag pole. If not, your working for the wrong people.

Pick and choose. I actually like most of the Python Doc. Learned Python originally from their tutorial. Then learned key parts of the library. So I like those two documents. The other docs though can be deep. The language reference for example. Never read that except parts.

I also had a book about Tkinter and another about Win32 Python programming. So I learned from those too. My first app was a data acquisition too with a Tkinter GUI. So I think a few books are good but maybe people do not do that now.

For me, learned Python in a day mostly from their tutorial and the standard library reference, then it took me the next 9 months to actually get good at it. Then still learning stuff 25 years later. I did have an advantage. I had been programming for 20 years before I learned Python and had used half a dozen other languages.

LibreOffice already has Python support along with some other choices.