[Numpy-discussion] Inconsistent behavior for ufuncs in numpy v1.10.X

2016-01-25 Thread Solbrig,Jeremy
Hello, Much of what is below was copied from this stack overflow question. I am attempting to subclass numpy.ma.MaskedArray. I am currently using Python v2.7.10. The

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Sturla Molden
On 23/01/16 22:25, Sebastian Berg wrote: Do you agree with this, or would it be a major inconvenience? I think any user of as_strided should be considered a power user. This is an inherently dangerous function, that can easily segfault the process. Anyone who uses as_strided should be

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Sturla Molden
On 25/01/16 18:06, Sebastian Berg wrote: That said, I guess I could agree with you in the regard that there are so many *other* awful ways to use as_strided, that maybe it really is just so bad, that improving one thing doesn't actually help anyway ;). That is roughly my position on this,

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Sebastian Berg
On Mo, 2016-01-25 at 16:11 +0100, Sturla Molden wrote: > On 23/01/16 22:25, Sebastian Berg wrote: > > > Do you agree with this, or would it be a major inconvenience? > > I think any user of as_strided should be considered a power user. > This > is an inherently dangerous function, that can

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread Nathaniel Smith
On Mon, Jan 25, 2016 at 2:37 PM, G Young wrote: > Hello all, > > I currently have a branch on my fork (not PR) where I am experimenting with > running Appveyor CI via Virtualenv instead of Conda. I have build running > here. What do people think of using Virtualenv (as we

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread G Young
Hello all, I currently have a branch on my fork (not PR) where I am experimenting with running Appveyor CI via Virtualenv instead of Conda. I have build running here . What do people think of using Virtualenv (as we do on Travis)

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread G Young
With regards to testing numpy, both Conda and Pip + Virtualenv work quite well. I have used both to install master and run unit tests, and both pass with flying colors. This chart here illustrates my point nicely as

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread Michael Sarahan
Conda can generally install older versions of python in environments: conda create -n myenv python=3.4 You really don't need any particular initial version of python/conda in order to do this. You do, however, need to activate the new environment to use it: activate myenv (For windows, you do

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread Bryan Van de Ven
> On Jan 25, 2016, at 5:21 PM, G Young wrote: > > With regards to testing numpy, both Conda and Pip + Virtualenv work quite > well. I have used both to install master and run unit tests, and both pass > with flying colors. This chart here illustrates my point nicely as

Re: [Numpy-discussion] Appveyor Testing Changes

2016-01-25 Thread G Young
Ah, yes, that is true. That point had completely escaped my mind. In light of this, it seems that it's not worth the while then to completely switch over to pip + virtualenv. It's might be better actually to rewrite the current Appveyor tests to use environments so that the test suite can be

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Juan Nunez-Iglesias
I agree that it's not ideal that the return value of as_strided is writable. However, to be clear, this *would* break the API, which should not happen between minor releases when using semantic versioning. Even with a deprecation cycle, for libraries such as scikit-image that want to maintain

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Sebastian Berg
On Mon Jan 25 01:46:55 2016 GMT+0100, Juan Nunez-Iglesias wrote: > > Yeah, that is a real use case. I am not planning to remove the option, > > but it would be as a `readonly` keyword argument, which means you would > > need to make the code depend on the numpy version if you require a > >

Re: [Numpy-discussion] Make as_strided result writeonly

2016-01-25 Thread Nathaniel Smith
On Sun, Jan 24, 2016 at 4:46 PM, Juan Nunez-Iglesias wrote: >> Yeah, that is a real use case. I am not planning to remove the option, >> but it would be as a `readonly` keyword argument, which means you would >> need to make the code depend on the numpy version if you require