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Worth noting that Julia's SymPy binding [1] is pretty pretty nice to work with too. If anyone's looking for big Julia project, I think a symbolic math package w

Worth noting that Julia's SymPy binding [1] is pretty pretty nice to work with too. If anyone's looking for big Julia project, I think a symbolic math package written fully in Julia would be a really exciting development. As far as I know, there isn't one yet. The better-known symbolic math packages for Julia still use bindings to C++ (SymEngine.jl [2]) or Python (SymPy.jl, Symata.jl [3]). [1] - https://github.com/JuliaPy/SymPy.jl https://github.com/JuliaPy/SymPy.jl [2] - https://github.com/symengine/SymEngine.jl https://github.com/symengine/SymEngine.jl [3] - https://github.com/jlapeyre/Symata.jl https://github.com/jlapeyre/Symata.jl

ChrisRackauckas 6y ago
ModelingToolkit.jl is a symbolic math package written fully in Julia (with a bunch of extra symbolic-numerics features) https://github.com/SciML/ModelingToolkit.jl https://github.com/SciML/ModelingToolkit.jl https://mtk.sciml.ai/dev/tutorials/symbolic_functions/ https://mtk.sciml.ai/dev/tutorials/symbolic_functions/ It's more like SymEngine in terms of completeness right now, though there's a good amount of simplification and equation solving built in. It's still growing, it's not at SymPy yet, but it's moving fast.
- snicker7 6y ago
  What is great about ModelingToolkit.jl is how its used in practical ways for other packages. E.g. NeuralPDE.jl. Compared to SymPy, I feel that it is less of a "how do I integrate this function" package and more about "how can I build this DSL" framework. https://github.com/SciML/NeuralPDE.jl https://github.com/SciML/NeuralPDE.jl