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embedPy: q list imported as numpy array

simon_watson_sj
New Contributor III

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

1 ACCEPTED SOLUTION

davidcrossey
Moderator Moderator
Moderator

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

View solution in original post

3 REPLIES 3

LeahS
Moderator Moderator
Moderator

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
Moderator Moderator
Moderator

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
New Contributor III

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