embedPy: q list imported as numpy array

[simon_watson_sj]

Hey Team,

I've been using an object in Python with Q via embedPy.

In using this, I've found that it appears that lists of floats from Q is represented by embedPy in Python as a numpy array of floats.

This was an issue in my case because the object I used was a little picky and wanted a vanilla python list.

I got around this by use of a function in Python that I called from Q in such a way asIn the end to convert the numpy array back to a list after the data had been projected into Python from Q.

The work I'm doing is not particularly reliant on speed so this isn't a big deal. However, it struck me this seems a little convoluted. Is there any functionality available to default the projection of the list of floats in Q to a list of floats in Python when using embedPy?

Regards,

Simon

[LeahS]

Hello Simon, 

Great observation here! Thank you for sharing this with the community. 🙌

We're working on an update for you and will relay the feedback as soon as possible. 

Kind regards,

Leah 

[davidcrossey · Accepted solution]

Hi Simon,

Please find some insight from our team as follows;

embedpy defaults to numpy arrays because that makes a lot more sense for the typical usage pattern.

numpy arrays behave enough like lists that this is usually not a problem.

In a rare case that it is, it's reasonable to do explicit conversion by calling list(). it's exposed to q as .p.list, so e.g. to pass a float vector to print() as a python list instead of a numpy array,

q).p.print .p.list 1 2 3f
[1.0, 2.0, 3.0]

That's exactly the same as doing that in python, but saves defining a function

q).p.eval["lambda x:print(list(x))";1 2 3f]
[1.0, 2.0, 3.0]

Thanks for adding your question on the portal!

Kind regards,

David

[simon_watson_sj]

Thanks David and Leah - a good result. As you say not normally a problem but for a fussy application on the python side.