I think most of have the opposite desire: we're trying to move more functionality out of the core language and into packages.
-- John On Sunday, July 12, 2015 at 3:03:31 AM UTC+2, Burak Budanur wrote: > > I heard a lot about Julia language over the last year and last week > had a conversation with a colleague, who attended Juliacon and was > quite impressed. We talked about possibly moving some of our fluid > dynamics projects to Julia, so that for a new student who is joining > the project it would be much easier to start without going through > learning c++ and/or fortran. > > > I am a physicist and most of my day job is some form of scientific > computing. My current default working environment is python > (numpy, scipy, sympy, matplotlib) + fortran (f2py) when some part > of my code needs to speed up. Yesterday I decided to start a a > new, relatively easy project as a simple example for an upcoming > paper. So I thought this might be a good occasion to start > learning Julia language to code a simple dynamical systems toolbox > in it, which might be useful for other people as well. > > > Basic functionality I need from the language are these: > > > - Symbolic differentiation (for computation of Jacobians) > - Numerical integration of ODEs (a general purpose integrator, such as > lsoda from odepack, wrapped in scipy.integrate.odeint) > - Linear algebra functions > - Interpolation > - Plotting in 2D and 3D > > > After reading The Julia Express and parts of the documentation, I > thought that such a project is not a good investment, at least for > now. The reason is all the functionality I listed above are provided > by external packages, partially excluding linear algebra functions. > I'm aware that I can use specific packages for all the functionality > I mentioned above, but each such package is maintained by different > people, and they can change or become obsolete. I can also find some > Fortran/C code, and include in Julia, and have all these > functionality, but then what is the advantage of using Julia, as > opposed to, say, python? > > > In a more general sense, I am a little bit turned off by the > presence of an external package for almost every task I need to > do. I can understand this kind of structure in python as it is a > general purpose language. But since Julia is a language > specifically for scientific computation, I'd be happy to have > something like the basic functionality of MATLAB in the main > language. > > > I understand that Julia is under development and there is a lot to > change and to be added, but I am wondering what is the Julia's future > directions regarding these issues? I did some search, but could not > find an answer to this question, so I apologize if this was already > answered elsewhere. > I heard a lot about Julia language over the last year and last week > had a conversation with a colleague, who attended Juliacon and was > quite impressed. We talked about possibly moving some of our fluid > dynamics projects to Julia, so that for a new student who is joining > the project it would be much easier to start without going through > learning c++ and/or fortran. > > I am a physicist and most of my day job is some form of scientific > computing. My current default working environment is python > (numpy, scipy, sympy, matplotlib) + fortran (f2py) when some part > of my code needs to speed up. Yesterday I decided to start a a > new, relatively easy project as a simple example for an upcoming > paper. So I thought this might be a good occasion to start > learning Julia language to code a simple dynamical systems toolbox > in it, which might be useful for other people as well. > > Basic functionality I need from the language are these: > > - Symbolic differentiation (for computation of Jacobians) > - Numerical integration of ODEs (a general purpose integrator, such as > lsoda from odepack, wrapped in scipy.integrate.odeint) > - Linear algebra functions > - Interpolation > - Plotting in 2D and 3D > > After reading The Julia Express and parts of the documentation, I > thought that such a project is not a good investment, at least for > now. The reason is all the functionality I listed above are provided > by external packages, partially excluding linear algebra functions. > I'm aware that I can use specific packages for all the functionality > I mentioned above, but each such package is maintained by different > people, and they can change or become obsolete. I can also find some > Fortran/C code, and include in Julia, and have all these > functionality, but then what is the advantage of using Julia, as > opposed to, say, python? > > In a more general sense, I am a little bit turned off by the > presence of an external package for almost every task I need to > do. I can understand this kind of structure in python as it is a > general purpose language. But since Julia is a language > specifically for scientific computation, I'd be happy to have > something like the basic functionality of MATLAB in the main > language. > > I understand that Julia is under development and there is a lot to > change and to be added, but I am wondering what is the Julia's future > directions regarding these issues? I did some search, but could not > find an answer to this question, so I apologize if this was already > answered elsewhere. >
