[scikit-learn] Is there any official position on PEP484/mypy?

Daniel Moisset dmoisset at machinalis.com
Wed Jul 27 15:17:31 EDT 2016


[If you're also on the numpy mailing list and get a similar version of the
message, I apologise for that]

I work at Machinalis were we use a lot of scikit-learn (and the pydata
stack in general). Recently we've also been getting involved with mypy,
which is a tool to type check (not on runtime, think of it as a linter)
annotated python code (the way of annotating python types has been recently
standarized in PEP 484).

As part of that involvement we've started creating type annotations for the
Python libraries we use most, which include both numpy and scikit-learn.
Mypy provides a way to specify types with annotations in separate files in
case you don't have control over a library, so we have created an initial
proof of concept for numpy at [1], and we are actively improving it. You
can find some additional information about it and some problems we've found
on the way at this blogpost [2]. We were planning to also start some work
on scikit-learn (which has a much larger surface area than numpy, so
probably focusing on small parts for now); we had to start with numpy
anyway given that SKL depends on it.

What I wanted to ask is if the people involved on the SKL project are aware
of PEP484 annotations and if you have some interest in starting using them.
The main benefit is that annotations serve as clear (and automatically
testable) documentation for users, and secondary benefits is that users
discovers bugs more quickly and that some IDEs (like pycharm) are starting
to use this information for smart editor features (autocompletion, online
checking, refactoring tools); eventually tools like jupyter could take
advantage of these annotations in the future. And the cost of writing and
including these are relatively low.

We're doing the work anyway, but contributing our typespecs back could make
it easier for users to benefit from this, and for us to maintain it and
keep it in sync with future releases.

If you've never heard about PEP484 or mypy (it happens a lot) I'll be happy
to clarify anything about it that might helpunderstand this situation



[1] https://github.com/machinalis/mypy-data
[2] http://www.machinalis.com/blog/writing-type-stubs-for-numpy/

Daniel F. Moisset - UK Country Manager
Skype: @dmoisset
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20160727/d47d3802/attachment.html>

More information about the scikit-learn mailing list