For anything I want to distribute in executable form. Pretty sure Python has figured out that story now after all these years but who knows.
But why do you need to distribute anything when trading your own account and I assume your programs are command-based.
The big advantage of Python is the business logic reads very clearly, and that is important when you're developing systems. You don't want the code and syntax to get in the way of actually doing the job. I've built my trading systems in Python using the following packages: Pandas (mainly for getting data in/out and human analysis) Numpy (for processing of data once loaded into memory, I tend not to use Pandas) Numba (When I have to iterate through large datasets that would take too long using native Python) scikit-learn (for data analysis) matplotlib (for visualising and charting) Regarding Pandas, I don't tend to use it for the actual algorithmic part. Instead I find it easier to convert everything to integers and use a numpy array. However, after my backtesting has run, all the results are put into a Pandas dataframe and then I can analyse that, usually in a Jupyter notebook. As an aside, Quantopian uses Python so if you ever wanted to code on there, Python is a good language to learn.
If you are a newbie youtube videos of "Sentdex"(for python in finance) and "Darwinex"(live data feed from MT4 to your python program) would be very useful. https://pasteboard.co/IR9FAJY.jpg That is what i come up with thanks to those channels...
Been there, done that. What you will find is python is more than suitable for this task IF you define with precision what you mean by "price action". If you do this exercise though it will be like peeling an onion. You just strip off layers and layers until there is nothing left of what you started with as far as "price action" because the concept is vague and lacking precision. Then you either start looking for ideas that can be precisely defined or start reading trader psychology books and other types of magical thinking.