On Jun 24, 2017 7:29 AM, "Sylvain Corlay" wrote: Also, one quick question: is the LGPL license a deliberate choice or is it not important to you? Most projects in the Python scientific stack are BSD licensed. So the LGPL choice makes it unlikely that a higher-level project adopts it as a dependency. If you are the only copyright holder, you would still have the possibility to license it under a more permissive license such as BSD or MIT... Why would LGPL be a problem in a dependency? That doesn't stop you making your code BSD, and it's less restrictive license-wise than depending on MKL or the windows C runtime... -n

On Sat, 2017-06-24 at 15:47 -0400, josef.pktd@gmail.com wrote:

On Sat, Jun 24, 2017 at 3:16 PM, Nathaniel Smith wrote:

...

On Jun 24, 2017 7:29 AM, "Sylvain Corlay"

...

wrote:

Also, one quick question: is the LGPL license a deliberate choice or is it not important to you? Most projects in the Python scientific stack are BSD licensed. So the LGPL choice makes it unlikely that a higher-level project adopts it as a dependency. If you are the only copyright holder, you would still have the possibility to license it under a more permissive license such as BSD or MIT...

Why would LGPL be a problem in a dependency? That doesn't stop you making your code BSD, and it's less restrictive license-wise than depending on MKL or the windows C runtime...

Is scipy still including any LGPL code, I thought not. There might still be some optional dependencies that not many users are using by default. ? Julia packages are mostly MIT, AFAIK. (except for the GPL parts because of cholmod, which we (?) avoid)

Well, I don't think scipy has many dependencies (but I would not be surprised if those are LGPL). Not a specialist, but as a dependency it should be fine (that is the point of the L in LGPL after all as far as I understand, it is much less viral). If you package it with your own stuff, you have to make sure to point out that parts are LGPL of course (just like there is a reason you get the GPL printed out with some devices) and if you modify it provide these modifications, etc. Of course you cannot include it into the scipy codebase itself, but there is probably no aim of doing so here, so without a specific reason I would think that LGPL is a great license. - Sebastian

Josef  

...

-n

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On Sat, 2017-06-24 at 22:58 +0200, Carl Kleffner wrote:

Does this still apply: https://scipy.github.io/old-wiki/pages/License _Compatibility.html

Of course, but it talks about putting it into the code base of scipy not about being able to use the package in any way in a dependency (i.e. `import package`). - Sebastian

Carl

2017-06-24 22:07 GMT+02:00 Sebastian Berg

...

: On Sat, 2017-06-24 at 15:47 -0400, josef.pktd@gmail.com wrote:

...

On Sat, Jun 24, 2017 at 3:16 PM, Nathaniel Smith wrote:

...

On Jun 24, 2017 7:29 AM, "Sylvain Corlay"

...

...

...

wrote:

Also, one quick question: is the LGPL license a deliberate choice or is it not important to you? Most projects in the Python scientific stack are BSD licensed. So the LGPL choice makes it unlikely that a higher-level project adopts it as a dependency. If you are the only copyright holder, you would still have the possibility to license it under a more permissive license such as BSD or MIT...

Why would LGPL be a problem in a dependency? That doesn't stop you making your code BSD, and it's less restrictive license-wise

.com than

...

...

depending on MKL or the windows C runtime...

Is scipy still including any LGPL code, I thought not. There might still be some optional dependencies that not many users are using by default. ? Julia packages are mostly MIT, AFAIK. (except for the GPL parts because of cholmod, which we (?) avoid)

Well, I don't think scipy has many dependencies (but I would not be surprised if those are LGPL). Not a specialist, but as a dependency it should be fine (that is the point of the L in LGPL after all as far as I understand, it is much less viral). If you package it with your own stuff, you have to make sure to point out that parts are LGPL of course (just like there is a reason you get the GPL printed out with some devices) and if you modify it provide these modifications, etc.

Of course you cannot include it into the scipy codebase itself, but there is probably no aim of doing so here, so without a specific reason  I would think that LGPL is a great license.

- Sebastian

...

Josef  

...

-n

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On 20170624@16:29, Sylvain Corlay wrote:

Hi Michele,

This is really interesting. I am a co-author of the xtensor project and one thing that could be interesting is to wrap the various sparse matrix data structures in the form of xtensor expressions. A byproduct of doing so is that it would simplify creating bindings for multiple scientific computing languages (Python, Julia, R, and more coming). You can see the blog post http://quantstack.net/c++/2017/05/30/polyglot-scientific-computing-with- xtensor.html for reference... This article exemplifies manipulation of numerical arrays. Now I ask you: Given an interactive language $L of the one you cite above, can xtensor provide objects with custom type and operators for manipulation in *that* language, like in e.g. the pyrsb case: a=rsb_matrix((4,4))

Hi Sylvain, print(a+a) # + operator and 'print' interfacing ?

Also, one quick question: is the LGPL license a deliberate choice or is it not important to you? Most projects in the Python scientific stack are BSD licensed. So the LGPL choice makes it unlikely that a higher-level project adopts it as a dependency. If you are the only copyright holder, you would still have the possibility to license it under a more permissive license such as BSD or MIT... No important choice. No problems relicensing the PyRSB prototype to BSD or MIT.

Congratulations on the release! Thanks for the interest and welcome constructive feedback :-)

Sylvain

On Wed, Jun 21, 2017 at 11:51 AM, Michele Martone wrote:

...

Hi.

I'm the author of the high performance multithreaded sparse matrix library `librsb' (mostly C, LGPLv3): http://librsb.sourceforge.net/

I'm *not* a user of SciPy/NumPy/Python, but using Cython I have written a proof-of-concept interface to librsb, named `PyRSB': https://github.com/michelemartone/pyrsb

PyRSB is in a prototypal state; e.g. still lacks good error handling. Its interface is trivial, as it mimicks that of SciPy's 'csr_matrix'. Advantages over csr_matrix are in fast multithreaded multiplication of huge sparse matrices. Intended application area is iterative solution of linear systems; particularly fast if with symmetric matrices and many rhs.

With this email I am looking for prospective: - users/testers - developers (any interest to collaborate/adopt/include the project?)

Looking forward for your feedback, Michele

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On 20170624@16:29, Sylvain Corlay wrote:

Hi Michele,

This is really interesting. I am a co-author of the xtensor project and one thing that could be interesting is to wrap the various sparse matrix data structures in the form of xtensor expressions. A byproduct of doing so is that it would simplify creating bindings for multiple scientific computing languages (Python, Julia, R, and more coming). You can see the blog post http://quantstack.net/c++/2017/05/30/polyglot-scientific-computing-with- xtensor.html for reference... This article exemplifies manipulation of numerical arrays. Now I ask you: Given an interactive language $L of the one you cite above, can xtensor provide objects with custom type and operators for manipulation in *that* language, like in e.g. the pyrsb case: a=rsb_matrix((4,4))

Hi Sylvain, print(a+a) # + operator and 'print' interfacing ?

Also, one quick question: is the LGPL license a deliberate choice or is it not important to you? Most projects in the Python scientific stack are BSD licensed. So the LGPL choice makes it unlikely that a higher-level project adopts it as a dependency. If you are the only copyright holder, you would still have the possibility to license it under a more permissive license such as BSD or MIT... No important choice. No problems relicensing the PyRSB prototype to BSD or MIT.

Congratulations on the release! Thanks for the interest and welcome constructive feedback :-)

Sylvain

On Wed, Jun 21, 2017 at 11:51 AM, Michele Martone wrote:

...

Hi.

I'm the author of the high performance multithreaded sparse matrix library `librsb' (mostly C, LGPLv3): http://librsb.sourceforge.net/

I'm *not* a user of SciPy/NumPy/Python, but using Cython I have written a proof-of-concept interface to librsb, named `PyRSB': https://github.com/michelemartone/pyrsb

PyRSB is in a prototypal state; e.g. still lacks good error handling. Its interface is trivial, as it mimicks that of SciPy's 'csr_matrix'. Advantages over csr_matrix are in fast multithreaded multiplication of huge sparse matrices. Intended application area is iterative solution of linear systems; particularly fast if with symmetric matrices and many rhs.

With this email I am looking for prospective: - users/testers - developers (any interest to collaborate/adopt/include the project?)

Looking forward for your feedback, Michele

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