OK, in that case let's get to work over in
https://github.com/numpy/numpy_stubs!
On Tue, Dec 5, 2017 at 2:43 PM Fernando Perez wrote:
> On Tue, Dec 5, 2017 at 2:19 PM, Nathaniel Smith wrote:
>
>> On Tue, Dec 5, 2017 at 10:04 AM, Stephan Hoyer wrote:
>> > This discussion has died down, but I do
On Tue, Dec 5, 2017 at 2:19 PM, Nathaniel Smith wrote:
> On Tue, Dec 5, 2017 at 10:04 AM, Stephan Hoyer wrote:
> > This discussion has died down, but I don't want to lose momentum .
> >
> > It sounds like there is at least strong interest from a subset of our
> > community in type annotations. A
On Tue, Dec 5, 2017 at 10:04 AM, Stephan Hoyer wrote:
> This discussion has died down, but I don't want to lose momentum .
>
> It sounds like there is at least strong interest from a subset of our
> community in type annotations. Are there any objections to the first part of
> my plan, to start de
This discussion has died down, but I don't want to lose momentum .
It sounds like there is at least strong interest from a subset of our
community in type annotations. Are there any objections to the first part
of my plan, to start developing type stubs for NumPy in separate repository?
We'll com
(a) it would be good if NumPy type annotations could include an
“array_like” type that allows lists, tuples, etc.
I think that would be a sequence — already supported by the Typing system.
(b) I’ve always thought (since PEP561) that it would be cool for type
annotations to replace compiler type
On Nov 25, 2017, at 3:35 PM, Matthew Rocklin wrote:
Thoughts on basing this on a more generic Array type rather than the
np.ndarray?
This would actually be more consistent with the current python typing
approach.
I can imagine other nd-array libraries (XArray, Tensorflow, Dask.array)
wanting t
Here's the code: https://github.com/rmcgibbo/numpy-mypy.
It's not 100% working yet, but it can do simple stuff, like inferring the
shape of arrays created from np.zeros(literal_tuple), and fixing out the
shape of the result of an indexing operation (i.e.
https://github.com/rmcgibbo/numpy-mypy/blob
On Tue, Nov 28, 2017 at 5:11 PM Robert T. McGibbon
wrote:
> I'm strongly in support of this proposal. Type annotations have really
> helped me write more correct code.
>
> I started working on numpy type stubs a few months ago. I needed a mypy
> plugin to support shape-aware functions. Those who
I'm strongly in support of this proposal. Type annotations have really
helped me write more correct code.
I started working on numpy type stubs a few months ago. I needed a mypy
plugin to support shape-aware functions. Those whole thing is pretty
tricky. Still very WIP, but I'll clean them up a l
On Sat, Nov 25, 2017 at 3:34 PM Matthew Rocklin wrote:
> Thoughts on basing this on a more generic Array type rather than the
> np.ndarray? I can imagine other nd-array libraries (XArray, Tensorflow,
> Dask.array) wanting to reuse this work. For dask.array in particular we
> would want to copy
2017-11-26 6:00 GMT-05:00 Kirill Balunov :
> Hi!
>
> 2017-11-26 4:31 GMT+03:00 Juan Nunez-Iglesias :
>
>>
>> On 26 Nov 2017, 12:27 PM +1100, Nathaniel Smith , wrote:
>>
>> It turns out that the PEP 484 type system is *mostly* not useful for
>> this. They're really designed for checking consistency
Hi!
2017-11-26 4:31 GMT+03:00 Juan Nunez-Iglesias :
>
> On 26 Nov 2017, 12:27 PM +1100, Nathaniel Smith , wrote:
>
> It turns out that the PEP 484 type system is *mostly* not useful for
> this. They're really designed for checking consistency across a large
> code-base, not for enabling compiler
On 26 Nov 2017, 12:27 PM +1100, Nathaniel Smith , wrote:
> It turns out that the PEP 484 type system is *mostly* not useful for
> this. They're really designed for checking consistency across a large
> code-base, not for enabling compiler speedups. For example, if you
> annotate something as an in
On Sat, Nov 25, 2017 at 3:09 PM, Juan Nunez-Iglesias wrote:
> This is a complete outsider’s perspective but
>
> (a) it would be good if NumPy type annotations could include an “array_like”
> type that allows lists, tuples, etc.
I'm sure this will exist.
> (b) I’ve always thought (since PEP561) t
Thoughts on basing this on a more generic Array type rather than the
np.ndarray? I can imagine other nd-array libraries (XArray, Tensorflow,
Dask.array) wanting to reuse this work. For dask.array in particular we
would want to copy this entirely, but we probably can't specify that
dask.arrays are
Can you make a case for the usefulness numpy annotations? What benefits to
you want to achieve and how will annotation aid in getting there.
1. Error checking on large codebases with systems like MyPy
2. Hinting and error checking at code-writing time with systems like
Jedi "Hey, this fu
On Sat, Nov 25, 2017 at 7:21 AM Marten van Kerkwijk <
m.h.vankerkw...@gmail.com> wrote:
> A question of perhaps broader scope than what you were asking for, and
> more out of curiosity than anything else, but can one mix type
> annotations with others? E.g., in astropy, we have a decorator that
>
This is a complete outsider’s perspective but
(a) it would be good if NumPy type annotations could include an “array_like”
type that allows lists, tuples, etc.
(b) I’ve always thought (since PEP561) that it would be cool for type
annotations to replace compiler type annotations for e.g. Cython a
On Sat, Nov 25, 2017 at 1:14 AM, Stephan Hoyer wrote:
> There's been growing interest in supporting PEP-484 style type annotations
> in NumPy: https://github.com/numpy/numpy/issues/7370
>
> This would allow NumPy users to add type-annotations to their code that
> uses NumPy, which they could chec
Hi Stephan,
A question of perhaps broader scope than what you were asking for, and
more out of curiosity than anything else, but can one mix type
annotations with others? E.g., in astropy, we have a decorator that
looks for units in the annotations (not dissimilar from dtype, I
guess). Could one m
There's been growing interest in supporting PEP-484 style type annotations
in NumPy: https://github.com/numpy/numpy/issues/7370
This would allow NumPy users to add type-annotations to their code that
uses NumPy, which they could check with mypy, pycharm or pytype. For
example:
def f(x: np.ndarray
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