[Numpy-discussion] Is there any official position on PEP484/mypy?

[Sebastian Berg]

On Mi, 2016-07-27 at 20:07 +0100, Daniel Moisset wrote:
> 
> Hi, 
> 
> I work at Machinalis were we use a lot of numpy (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 numpy. 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 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].
> 
> What I wanted to ask is if the people involved on the numpy project
> are aware of PEP484 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.
> 

There is currently no plan to do it as far as I know, but with these
things it is often more of a problem that someone volunteers to
maintain it then to convince everyone that it is a good idea.
If there is enough interest we could talk about hosting it on the numpy
github group as a separate project to make it a bit more
visible/obvious that such a project exists.

For inclusion in numpy, it seems to me that currently this would
probably be better of improved separately? In the long run, would it be
possible to do something like run all numpy tests and then check
whether the definitions cover (almost) everything, or test against the
documentation or so? Otherwise it might get tricky to keep things quite
up to date, at least until these type checks are very widely used. Also
I wonder if all or most of numpy can be easily put into it.

Anyway, it seems like a great project to have as much support for type
annotations as possible. I have never used them, but with editors
picking up on these things it sounds like it could be very useful in
the future.

- Sebastian


> 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
> 
> Thanks!
> 
> D.
> 
> 
> [1] https://github.com/machinalis/mypy-data 
> [2] http://www.machinalis.com/blog/writing-type-stubs-for-numpy/
> 
> -- 
> Daniel F. Moisset - UK Country Manager
> www.machinalis.com
> Skype: @dmoisset
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