The Julia Language
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
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In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.
E
You can open a default notebook with the Pluto option
Pluto.run(notebook="test.jl")
Especially when using Pluto as a REST Server (with fonsp/Pluto.jl#1052 ) it would be good to have the possibility to start multiple notebooks from the command line.
Suggested syntax:
Pluto.run(notebook=["test.jl", "test2.jl"])
Currently, the opening of a notebook works by pass
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Jul 5, 2021 - Julia
Motivated by https://discourse.julialang.org/t/getting-started-mip-variables-and-datastructure/63766/6
It would be nice to have
model = Model()
@variable(model, x[i=1:3], name="x_$(i)")Currently there is
model = Model()
julia> @variable(model, x[i=1:3], base_name="x_$(i)")
3-element Vector{VariableRef}:
x_1[1]
x_2[2]
x_3[3]which isn't quite the sam
Details
(This is related to JuliaPlots/Plots.jl#1706)
For example scatter(skipmissing([1.0, 2.0, missing, 1.0])) fails with Cannot convert Base.SkipMissing{Vector{Union{Missing, Float64}}} to series data for plotting.
Generally skipmissing is not required but it seems odd to see this fail.
Also I stumbled on this while trying to make a histogram, e.g.
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May 15, 2021 - Jupyter Notebook
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Jul 11, 2021 - Julia
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Jul 1, 2021 - Julia
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Jul 10, 2021 - Julia
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Jul 9, 2021 - Julia
I found that function mod2pi is not implemented yet, but mod works. Is there any list of implemented functions? Minimal working example is:
using Zygote
# This is working
gradient(x -> mod(x, 2pi), 1.)
# This is not
gradient(x -> mod2pi(x), 1.)
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Jul 11, 2021 - TypeScript
I've noticed that calling delete! on an Axis3 does not completely remove it:
julia> fig = Figure()
julia> ax = Axis3(fig[1, 1])
Axis3()
julia> surface!(ax, rand(100, 100))
Surface{Tuple{IntervalSets.ClosedInterval{Float32}, IntervalSets.ClosedInterval{Float32}, Matrix{Float32}}}
julia> delete!(ax)

There's a post going around on Twitter for how to write a super fast DFA, e.g. for UTF8 validation: https://twitter.com/_rsc/status/1413843059972923394?s=19. We have a UTF8 validation function, so we should try this technique. Should be reasonably simple to do.