Daniel Pinyol comments

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                                            Daniel Pinyol

Multilingual or Chinese version plan?

Spanish also please

fixed issues discovered bj JET.jl

fyi, latest 0.6.2 release can now analyse Metatheory.jl

preallocate actually has more (while not by number of bytes) allocations!

With julia 1.8, this sample case generates 1k allocations instead of 1 ```julia julia> using AutoPreallocation julia> function f() x = rand(100) nothing end f (generic function with 1 method)...

dead code detection

:+1: I currently detect some cases on my code with a sloppy multiline grep, but it would be cool if jet could make it

Unable to mock classes that make call to 'toString()'

hi, any news on this? any workaround? thanks

Fix failure setting optimize option (#480)

@MilesCranmer rebased. thanks

Pickling/unpickling a dtype resets isbuiltin flag

I can reproduce this issue with `copy.copy()` or `copy.deepcopy()

NumPy interop to do list - `to_numpy`

It would also be nice to be able to get np arrays with dtype `np.object` for ``` pl.DataFrame({"A": [[1,2]], "B":1}, {"A": pl.Array(pl.Int64, 2), "B": pl.Int32}).to_numpy() ``` instead of this exception...

SVector sometimes allocates

@fredrikekre thank you for the quick reply. Can you think of any workaround? Any kind of function barrier?

SVector sometimes allocates

@andyferris I still get allocations. Am I missing something? thanks ``` using StaticArrays function createMVector(len::Val{L}) where {L} return MVector{L, Int}((1 for i in 1:L)) end const s=[1] julia> @allocated createMVector(Val(length(s)))...