Thanks Kevin, That solved the problem!
I used 'condo install mpmath’ in addition to ‘pip install mpmath’, just to make sure (shows I am way too rusty on Python stuff), and then reinstalled both SymPy and Julia. Thanks a lot, will certainly track Julia development! Regards, Rob > On May 16, 2016, at 08:19, Kevin Squire <[email protected]> wrote: > > Hi Rob, > > You'll need to install the `mpmath` package for python. > > If you use `pip`, you should just be able to run `pip install mpmath`. > > Otherwise, you'll have to find and install the package using your preferred > method. > > (I also ran into this. John, you should probably mention this in the README.) > > Cheers, > Kevin > > On Mon, May 16, 2016 at 8:14 AM, Rob J. Goedman <[email protected] > <mailto:[email protected]>> wrote: > Hi, > > As I use Mathematica quite a bit, I’m very interested in SJulia! > > I’m wondering if I need an additional Module or library to get around below > issue. This is on OS X and Julia 0.5- > > ERROR: InitError: PyError (:PyImport_ImportModule) <type > 'exceptions.ImportError'> > ImportError('No module named mpmath',) > > [inlined code] from /Users/rob/.julia/v0.5/PyCall/src/exception.jl:56 > in pyimport(::String) at /Users/rob/.julia/v0.5/PyCall/src/PyCall.jl:285 > [inlined code] from /Users/rob/.julia/v0.5/SJulia/src/SJulia.jl:3 > in import_sympy() at /Users/rob/.julia/v0.5/SJulia/src/sympy.jl:23 > in init_sympy() at /Users/rob/.julia/v0.5/SJulia/src/sympy.jl:677 > in __init__() at /Users/rob/.julia/v0.5/SJulia/src/SJulia.jl:64 > in _require_from_serialized(::Int64, ::Symbol, ::String, ::Bool) at > ./loading.jl:174 > in require(::Symbol) at ./loading.jl:365 > in eval(::Module, ::Any) at ./boot.jl:226 > during initialization of module Julia > > On Julia 4.0 SymPy won’t work on my system (it complains about precompiling): > > julia> using SymPy > INFO: Precompiling module SymPy... > ERROR: LoadError: LoadError: UndefVarError: _apply_recipe not defined > > But on Julia 5.0: > > > julia> using SymPy > > x = symbols("x") > x > > julia> a = [x 1; 1 x] > 2×2 Array{SymPy.Sym,2} > ⎡x 1⎤ > ⎢ ⎥ > ⎣1 x⎦ > > julia> det(a) > ⎛ 1⎞ > x⋅⎜x - ─⎟ > ⎝ x⎠ > > julia> versioninfo > versioninfo (generic function with 4 methods) > > julia> versioninfo() > Julia Version 0.5.0-dev+4110 > Commit 5d52f02 (2016-05-16 02:25 UTC) > Platform Info: > System: Darwin (x86_64-apple-darwin15.5.0) > CPU: Intel(R) Core(TM) i7-4980HQ CPU @ 2.80GHz > WORD_SIZE: 64 > BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell) > LAPACK: libopenblas64_ > LIBM: libopenlibm > LLVM: libLLVM-3.7.1 (ORCJIT, haswell) > >> On May 12, 2016, at 19:47, [email protected] >> <mailto:[email protected]> wrote: >> >> The symbolic mathematics language project that I announced last year has >> been greatly expanded. >> >> Here is the link: https://github.com/jlapeyre/SJulia.jl >> <https://github.com/jlapeyre/SJulia.jl> >> >> The best way to find what is new is to look at the tests >> https://github.com/jlapeyre/SJulia.jl/tree/master/sjtest >> <https://github.com/jlapeyre/SJulia.jl/tree/master/sjtest> > >
