@tlienart Thanks! I’ve added an issue for your first suggestion and am going to improve on that. For your second suggestion, I think that’s not possible yet. The site shows too many false positives. So far, I did find some interesting problems in code and created PRs manually:
@Mason that’s not off topic. Are you sure that x === missing is the same as x === nothing? I’m not an expert, so it could definitely be true. Would you mind elaborating a bit more?
Both missing and nothing are defined as Missing() and Nothing() respectively, and ismissing and isnothing are both defined as
ismissing(::Any) = false
ismissing(::Missing) = true
and
isnothing(::Any) = false
isnothing(::Nothing) = true
respectively, so as far as I can tell, they’re exactly analogous.
I believe it’s usually recommended to use x === nothing and x === missing when possible because the compiler is able to optimize it in more circumstances. From what I understand, ismissing and isnothing are mostly useful for higher order functions, e.g.
any(ismissing, x)
I do expect that ismissing(x) is easier to read for new Julia users, and performance is not really the issue for most practical problems („premature optimization is the root of all evil“), but you might very well be right that its not an useful pattern to check for. I‘m gonna look into it a bit more. 
Maybe these are relevant:
That’s pretty dope and I’m happy that you analysed two of my repos 
How long does it take to produces the results? Is it out of reach to do this for all registered packages?
Haha, you’re welcome
Currently, it takes about 20 minutes (https://github.com/rikhuijzer/ShowLint/actions), so it’s not too bad. Good idea. I’ve put it in my task list (https://github.com/rikhuijzer/ShowLint/issues/11).
@joa-quim In response to https://discourse.julialang.org/t/ismissing-x-versus-x-missing/52171/3: That’s why I’m working ShowLint with the possibility to disable lint patterns in bulk. Instead of adding a lint configuration to each project/repository, I could just disable the check for this pattern and similar checks on all “high-performance” repositories. Basically, the idea is that all the configuration complexity is moved away from the user and is managed at one place. Also, the idea is that its easier for the Julia community to help busy package creators out. For example, some packages are created one or more years ago and the creator has moved on to other things. With something like ShowLint, the community can more easily assist these creators in keeping their packages working and up-to-date.
Oh and maybe only lint the src folder as something like a == a can be helpful in testing to check if the function for == is correctly implemented.
You’re quick. It took me until this morning to realize that https://github.com/rikhuijzer/ShowLint/issues/9
Comparison with Boolean constants are only redundant if you can prove that the value itself is a Bool. And b == trues(n) is not equivalent to bs(n).
Haha I didn’t look at the issues though 
I saw that you changed some a == a in the latest run. Have you tackled the false positives in JuMP.jl for example? There you have @constraint(m, x-1 == 1) and form it into @constraint(m, x-true)
@GunnarFarneback Yes, I’m still tweaking the rules and am note sure what to do with it. I do think that https://github.com/JuliaData/YAML.jl/pull/103 shows that there are situations where that check can be useful but, indeed, its a part of Julia since x == true will give missing if x is a missing.
@Wikunia I got some tips from Rijnard van Tonder (Comby’s creator) and expect to have that fixed later today
This is great. I’d love to see more linting in Julia. A few points:
a == a appears to also trigger on 2 * a == a * 2 and even x/a == a, which should not be intended.x -> f(x) triggers on x -> 2gx(x), suggesting 2gx, which is not corretThanks for both. Good catch on x/a == a. Should be fixed somewhere today.
Looks like a neat tool!
My few points:
findall(x -> x==false, [true, false]) should probably be findall(!, [true, false]) rather than broadcasting.cond == false with cond only seems safe if you are sure that cond::Bool. I don’t see examples where this is clearly violated, but I do have functions which expect either nothing or false. And findall(!, [true, false, nothing]) obviously won’t work.Thanks for your suggestions!
I’m afraid that I don’t understand what would be the difference between findall(!, A) and findall(.!A), and why the former would be preferred. Could you explain the difference?
So, this is now the second pattern which doesn’t handle missings well. 
Thanks for pointing that out
My thinking was that this would save allocating an array here. Although for findall in particular, it might not actually be faster?
julia> @btime findfirst(x->!x, r) setup=(r=rand(Bool, 10^6)); # same as findfirst(!, r)
2.283 ns (0 allocations: 0 bytes)
julia> @btime findfirst(.!r) setup=(r=rand(Bool, 10^6));
137.891 μs (4 allocations: 126.42 KiB)
julia> @btime count(x->!x, r) setup=(r=rand(Bool, 10^6));
80.810 μs (0 allocations: 0 bytes)
julia> @btime count(.!r) setup=(r=rand(Bool, 10^6));
142.010 μs (4 allocations: 126.42 KiB)
julia> @btime findall(x->!x, r) setup=(r=rand(Bool, 10^6));
671.744 μs (8 allocations: 3.92 MiB)
julia> @btime findall(.!r) setup=(r=rand(Bool, 10^6));
668.053 μs (6 allocations: 3.93 MiB)
Edit – that’s because the second-last line explicitly calls the last here, findall(testf::Function, A::AbstractArray) = findall(testf.(A)), so there can’t be a difference. Sorry about the noise!
This is a good idea and I hope it can gain some more traction / incorporation into IDEs. Traceur.jl has a similar design space and is perhaps worth looking into.
I think the author of comby did this against a large GitHub code-base and automatically submitted PRs
Also see: