[Numpy-discussion] ANN: numtraits v0.2

[Thomas Robitaille]

Hi everyone,

We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait
class that can be used to validate properties such as:

* number of dimension (for arrays)
* shape (for arrays)
* domain (e.g. positive, negative, range of values)
* units (with support for astropy.units, pint, and quantities)

The idea is to be able to write a class like:

class Sphere(HasTraits):

radius = NumericalTrait(domain='strictly-positive', ndim=0)
position = NumericalTrait(shape=(3,))

and all the validation will then be done automatically when the user
sets 'radius' or 'position'.

In addition, tuples and lists can get automatically converted to
arrays, and default values can be specified. You can read more about
the package and see examples of it in use here:

https://github.com/astrofrog/numtraits

and it can be easily installed with

pip install numtraits

The package supports both Python 3.3+ and Legacy Python (2.7) :)

At this point, we would be very interested in feedback - the package
is still very young and we can still change the API if needed. Please
open issues with suggestions!

Cheers,

Tom and Francesco

[Stefan van der Walt]

Hi Thomas

Post by Thomas Robitaille
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait

This looks great! At the moment, a pip install tries to install a
different version of NumPy, even though I already have the development
version on my tree. In scikit-image, we use something like the
following in setup.py to prevent that from happening:

# Do not try and upgrade larger dependencies
INSTALL_REQUIRES = ['numpy', 'traitlets']
try:
__import__('numpy')
INSTALL_REQUIRES = ['traitlets']
except ImportError:
pass

Stéfan

[Nathaniel Smith]

On Wed, Sep 23, 2015 at 5:10 PM, Stefan van der Walt

Post by Stefan van der Walt
Hi Thomas

Post by Thomas Robitaille
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait

This looks great! At the moment, a pip install tries to install a
different version of NumPy, even though I already have the development
version on my tree.

FYI the alternative solution is to fix your local numpy install to
give pip an accurate picture of what you have installed. The key thing
is to make sure you have a .egg-info / .dist-info for your numpy --
that's what pip looks for to figure out what's installed. (python
setupegg.py egg_info will generate one IIRC).

-n

[Stefan van der Walt]

Post by Nathaniel Smith

Post by Stefan van der Walt
This looks great! At the moment, a pip install tries to install a
different version of NumPy, even though I already have the development
version on my tree.

FYI the alternative solution is to fix your local numpy install to
give pip an accurate picture of what you have installed. The key thing
is to make sure you have a .egg-info / .dist-info for your numpy --
that's what pip looks for to figure out what's installed. (python
setupegg.py egg_info will generate one IIRC).

Looks like 'pip install -e .' in the numpy directory also fixed it.
Good to know, thanks.

Stéfan

[Sylvain Corlay]

Hi Thomas,

This is great news!

FYI, the traitlets module has been undergoing significant refactoring
lately, improving the API to favor a broader usage in the community. One
reason for this is that several projects outside of the Jupyter
organization are considering adopting traitlets. You can find a summary of
the ongoing work and API changes here:
https://github.com/ipython/traitlets/issues/48

One of the items in this discussion is about what would be the best place
for a repository of trait types for standard data structures of the scipy
stack (numpy array, pandas series and dataframes, etc...) It is unlikely
that such trait types would be accepted in those libraries at this moment,
and the main traitlets package might not be the right place for it either -
hence the need for another repo. However, if we don't work on a centralized
project, we will probably see a number of competing implementations in
different libraries that are clients of traitlets.

Hence the idea would be to propose a new project in the Jupyter incubator
with a reference implementation. What would be cool would be to join forces
and work on a specification or start a discussion of what the ideal
implementation for such trait types would look like.

Cheers,

Sylvain


On Wed, Sep 23, 2015 at 12:39 PM, Thomas Robitaille <

Post by Thomas Robitaille
Hi everyone,
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait
* number of dimension (for arrays)
* shape (for arrays)
* domain (e.g. positive, negative, range of values)
* units (with support for astropy.units, pint, and quantities)
radius = NumericalTrait(domain='strictly-positive', ndim=0)
position = NumericalTrait(shape=(3,))
and all the validation will then be done automatically when the user
sets 'radius' or 'position'.
In addition, tuples and lists can get automatically converted to
arrays, and default values can be specified. You can read more about
https://github.com/astrofrog/numtraits
and it can be easily installed with
pip install numtraits
The package supports both Python 3.3+ and Legacy Python (2.7) :)
At this point, we would be very interested in feedback - the package
is still very young and we can still change the API if needed. Please
open issues with suggestions!
Cheers,
Tom and Francesco
_______________________________________________
NumPy-Discussion mailing list
https://mail.scipy.org/mailman/listinfo/numpy-discussion

[Thomas Robitaille]

Hi Sylvain,

Post by Sylvain Corlay
Hi Thomas,
This is great news!
FYI, the traitlets module has been undergoing significant refactoring
lately, improving the API to favor a broader usage in the community.
One reason for this is that several projects outside of the Jupyter
organization are considering adopting traitlets. You can find a summary
of the ongoing work and API changes
here: https://github.com/ipython/traitlets/issues/48
One of the items in this discussion is about what would be the best
place for a repository of trait types for standard data structures of
the scipy stack (numpy array, pandas series and dataframes, etc...) It
is unlikely that such trait types would be accepted in those libraries
at this moment, and the main traitlets package might not be the right
place for it either - hence the need for another repo. However, if we
don't work on a centralized project, we will probably see a number of
competing implementations in different libraries that are clients of
traitlets.
Hence the idea would be to propose a new project in the Jupyter
incubator with a reference implementation. What would be cool would be
to join forces and work on a specification or start a discussion of what
the ideal implementation for such trait types would look like.

I'm very open to collaborating on centralizing these kind of scipy-stack
traits. I'm not particularly attached to the idea of keeping our
numtraits implementation separate, and would be very happy to merge it
in to a larger effort or only re-use parts of it. Realistically I won't
be able to lead/write a proposal for the incubator in the next few
weeks, but if no one gets to it first, I can try and work on it later in
the year.

Cheers,
Tom

Post by Sylvain Corlay
Cheers,
Sylvain
On Wed, Sep 23, 2015 at 12:39 PM, Thomas Robitaille
Hi everyone,
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait
* number of dimension (for arrays)
* shape (for arrays)
* domain (e.g. positive, negative, range of values)
* units (with support for astropy.units, pint, and quantities)
radius = NumericalTrait(domain='strictly-positive', ndim=0)
position = NumericalTrait(shape=(3,))
and all the validation will then be done automatically when the user
sets 'radius' or 'position'.
In addition, tuples and lists can get automatically converted to
arrays, and default values can be specified. You can read more about
https://github.com/astrofrog/numtraits
and it can be easily installed with
pip install numtraits
The package supports both Python 3.3+ and Legacy Python (2.7) :)
At this point, we would be very interested in feedback - the package
is still very young and we can still change the API if needed. Please
open issues with suggestions!
Cheers,
Tom and Francesco
_______________________________________________
NumPy-Discussion mailing list
https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________
NumPy-Discussion mailing list
https://mail.scipy.org/mailman/listinfo/numpy-discussion