# On potentially expanding or pruning the standard library

**URL:** <https://discourse.julialang.org/t/on-potentially-expanding-or-pruning-the-standard-library/103532>\
**Category:** Internals & Design\
**Created:** [September 5, 2023, 6:17am UTC](https://discourse.julialang.org/t/on-potentially-expanding-or-pruning-the-standard-library/103532 "2023-09-05T06:17:46Z")\
**Posts on this page:** 1\
**Showing post:** 12

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**Author:** ![GregVernon](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/gregvernon/32/5611_2.png) [@GregVernon](https://discourse.julialang.org/u/GregVernon)\
**Post date:** [September 5, 2023, 4:31pm UTC](https://discourse.julialang.org/t/on-potentially-expanding-or-pruning-the-standard-library/103532/12 "2023-09-05T16:31:04Z")

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> [@Sukera](#):
>
> I’m willing to bet that more than 95% of usecases for python you have in mind are not at all possible with just it’s standard library - scientific computing in python more or less lives off of numpy, pytorch and the like. All of these are third party packages.

I 100% agree with this, its largely the reason behind this post and [my other post](https://discourse.julialang.org/t/proposal-ability-to-add-entire-organizations-ecosystems-with-a-single-command/103531) that talks about trying to simplify adding third party packages (by adding an entire org’s production packages).

With Python, there’s at least the idea ingrained in Pythonista’s that

> “if you want numerical computing, simply install NumPy. If you want scientific computing solutions, simply install SciPy.”

Whereas with Julia it’s more like:

> “if you want numerical computing, add `Polynomials.jl`, `Roots.jl`, `Interpolations.jl`, `Bessels.jl`, `SpecialFunctions.jl`, `Richardson.jl`, `QuadGK.jl`, `FFTW.jl`, `Combinatorics.jl`, `NFFT.jl`, `Cubature.jl`, `FastChebInterp.jl`, `HCubature.jl`, `FunctionZeros.jl`, `KahanSummation.jl`, `RealDot.jl`, `Calculus.jl`, `IterativeSolvers.jl`, `LinearMaps.jl`, `Arpack.jl`, `Preconditioners.jl`, `AlgebraicMultigrid.jl`, `BenchmarkTools.jl`, etc., etc.,”

And I just think that this has at least some deleterious impact for new users of Julia. If instead Julia users’ hive-mind had the thought of “Oh, with Julia if you want to do numerical computing add `JuliaMath` and `JuliaLinearAlgebra`” then we probably have a solution that doesn’t require expanding the standard library, though maybe we could prune `LinearAlgebra` to the care of the `JuliaLinearAlgebra` organization?.

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