Closed DaveSkender closed 2 years ago
@August1328 Please let us know, if you'd like to contribute on this. We can wait for it, if you need time to learn GitHub.
Might be good to also add a note in the Guide about dataframe conversion. That seems to be a common thing. @LeeDongGeon1996 is dataframe something we want to accept as an alternative input form?
Right. In most of use-cases in Python, people use Pandas dataframe, so It would be good to add in Guide. Actually, I'm worrying about performance to convert them, so thinking about C-extension for Python to convert them faster.
While Python is a great language and a pleasure to code in, its dynamic nature results in overhead that can cause some code ( i.e. raw computations inside of for loops) to be up 10-100 times slower than equivalent code written in a static compiled language. From Numpy docs: https://numpy.org/doc/stable/user/c-info.python-as-glue.html#calling-other-compiled-libraries-from-python)
dataframe
consists of1D-array
of Numpy internally.
Do you think it is the case of above? or is it too much? (like a dtype
feature we've discussed about before)
I think we can just start with some guidance in docs. I suspect Python users simply know and accept that it’s slower in some aspects than compiled code. Exploring a C or C# extension is also a good idea.
Documented KVO method should be fixed and not reflect Keltner. Typo. We'll need to also review the parameters and for other missing items while we taking a look.
Originally posted by @August1328 in https://github.com/DaveSkender/Stock.Indicators/discussions/446#discussioncomment-2707700