This talk is inspired by the classic Wat talk by Gary Bernhardt, applied to Julia.

Huge thanks to Mason Protter, many of the inital specimens are his.

Why collect a huge array of scary footguns? Others have ranted before on all the things that are bad about Julia, profusely! Enthusiastically! I think there's good value in knowing precisely why you should hate your tools. I'm clearly in the "Julia will take over the world camp", and that effusiveness can work great for some projects, but it's good to understand the limitations of the tools we use. There's well known effective ways to come across in a reasoned manner when pitching Julia for a particular use case, but being able to specify *many* of these limitations and the pain points they inflict will generally show that you're willing to take criticism in a healthy manner.

As always, if you want to support me writing more of these Julia horror stories, please consider sponsoring me on GitHub.

`TODO`

and, or on empty collections

broadcasting shenanigans: (Credit to Mosè Giordano)

```
julia> all([] .== [42])
true
julia> all([] .≈ [42])
true
```

RNG seed set by

`@testset`

: (Credit to Michael Abbott)

```
julia> @testset begin
x = rand()
@testset for i in 1:10
y = rand()
@test x == y
end
end;
Test Summary: | Pass Total Time
test set | 10 10 0.0s
```

Operator precedene with ranges: (Credit to Oscar Smith)

```
julia> -5:5 .+ .5
-5.0:1.0:5.0
julia> (-5:5) .+ .5
-4.5:1.0:5.5
```

Another few examples from Bogumił Kamiński's Blog "Confused by Julia" (which I will include for the completeness of this list, but leave you to visit his blog for the explainers)

```
julia> :a => x -> x => :b
:a => var"#1#2"()
```

```
julia> 1 == 3 & 1 == 1
true
```

`var"N+1"`

and other sneaky shenanigans like stealing the pipe operator with an even uglier syntax

```
struct PseudoClass{T}
data::T
end(o::PseudoClass)(f, args...; kwargs...) = f(o.data, args...; kwargs...)
var"'ᶜ" = PseudoClass
my_thing'ᶜ(stuff)'ᶜ(more_stuff, an_argument)'ᶜ(final_stuff; a_keyword_argument)
```

Courtesy of Stefan Karpinski

```
julia> e = 9998.0
9998.0
julia> 2e
19996.0
julia> 2e+4
20000.0
julia> 2e+5 # This should be 20001.0, and yet...
200000.0
julia> 2e + 5 # note the spacing
200001.0
```

Shadowing: Courtesy of Kristoffer Carlsson

```
julia> git_tree-sha1 = "8eb7b4d4ca487caade9ba3e85932e28ce6d6e1f8";
julia> 1-2
"8eb7b4d4ca487caade9ba3e85932e28ce6d6e1f8"
```

And another example:

```
julia> function f(x)
my_cool-variable=3
if x > 5
return my_cool_variable
else
return 3 - 1
end
end
f (generic function with 1 method)
julia> f(2)
3
julia> 3-1
2
```

Symbols and numbers: Courtesy of

`Mosè Giordano`

:

```
julia> :a === "a"
false
julia> :2 === 2
true
```

Credit to `Jakob Nybo Nissen`

:

```
julia> :1234567890123456789 == 1234567890123456789
true
julia> :12345678901234567890 == 12345678901234567890
false
```

See also this issue.

As a corollary, a Pythonista stumper:

```
julia> arr1 = reshape(1.0:4.0, 2, 2)
2×2 reshape(::StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, 2, 2) with eltype Float64:
1.0 3.0
2.0 4.0
julia> arr2 = zeros(2, 2)
2×2 Matrix{Float64}:
0.0 0.0
0.0 0.0
julia> arr2 .= arr1[:, :2]
2×2 Matrix{Float64}:
3.0 3.0
4.0 4.0
```

because `:2`

is not the same as `1:2`

```
julia> arr2 .= arr1[:, 1:2]
2×2 Matrix{Float64}:
1.0 3.0
2.0 4.0
```

Callable ints by

`Alexander Plavin`

: link here

```
julia> (1)(2)
2
# but
julia> x = 1
1
julia> (x)(2)
ERROR: MethodError: objects of type Int64 are not callable
```

BUT! This can be avoided, as `Mason Protter`

invokes through the magic of type piracy:

```
julia> (x::Int)(y) = x * y
julia> x = 1
1
julia> (x)(2)
2
```

and the following super dirty:

```
julia> (s::Symbol)(x) = getproperty(x, s)
julia> :im(1 - im)
-1
```

Lowering is hard, credit to `Jonnie Diegelman`

:

```
julia> nums = zeros(Int, 10);
julia> for nums[rand(1:10)] in 1:20
end
julia> nums
10-element Vector{Int64}:
12
16
7
20
19
18
15
0
13
17
```

(Python suffers from something similar). Explanation: As `Jabon Nissen`

pointed out, "It's because for i in 1:20 lowers to for i = 1:20 in Julia. Here, it's nums[rand(1:10)] = 1:20" This is another one for the road

```
julia> nums = [1, 3, 5, 7, 9];
julia> gen = (n for n in nums if n in nums);
julia> collect(gen)
5-element Vector{Int64}:
1
3
5
7
9
julia> nums = [1, 3, 5, 7, 9];
julia> gen = (n for n in nums if n in nums);
julia> nums = [1, 2, 3, 4];
julia> collect(gen)
2-element Vector{Int64}:
1
3
```

Why does this happen: Jeff points out that the thing to iterate over is evaluated once; everything inside has to be evaluated for each iteration and so can change. However, a cleverly place `let`

binding can avoid some of these headaches:

```
julia> gen = let nums = 1:2:9
(n for n in nums if n in nums)
end;
julia> nums = 1:4;
julia> collect(gen)
5-element Vector{Int64}:
1
3
5
7
9
```

`isequal`

vs`egal`

vs`==`

vs`===`

```
julia> first(1,2)
1-element Vector{Int64}:
1
```

Rationale: Partly explained in the docstring for `first`

. Maybe a MATLAB-ism.

```
julia> # Credit to Dheepak Krishnamurthy
julia> 1[1][1][1] == 1
true
```

What is this syntax?

```
julia> function (YOLO)
YOLO + 1
end
```

Credit to `Miha Zgubič`

```
julia> append!([1, 2, 3], "4")
4-element Vector{Int64}:
1
2
3
52
```

Explanation: `convert`

is called implicitly to make `"4"`

into `Char`

, and since `Int('4') == 52`

, you get the result above.

You can get similar results with

```
push!([1, 2, 3], '4')
x = [1, 2, 3];
x[3] = '4';
x
copyto!([1,2,3], "456")
```

Credit to `Michael Abott`

for those.

Not that the general Julia idiom of `[x, y]`

will try to promote to a common element type of possible, but only if it equals one of the input types. This is a constraint that homogenous array representation demands, but can lead to some interesting cases like: (Credit to `MIlan Bouchet-Valat`

)

```
julia> [BigInt[1], [1.0]]
2-element Vector{Vector}:
BigInt[1]
[1.0]
julia> [[1], [1.0]]
2-element Vector{Vector{Float64}}:
[1.0]
[1.0]
```

Credit to `Vasily Pisarev`

.

```
julia> countlines("""
Mary had a little lamb,
Its fleece was white as snow,
And every where that Mary went
The lamb was sure to go
""")
ERROR: SystemError: opening file "Mary had a little lamb,\n Its fleece was white as snow,\nAnd every where that Mary went\n The lamb was sure to go\n": No such file or directory
```

```
julia> threetuple = (3, 3.0, 3f0)
(3, 3.0, 3.0f0)
julia> threetuple isa NTuple
false
julia> threetuple isa NTuple{3,Number}
true
```

Mark Kittisopikul

© Miguel Raz Guzmán Macedo. Last modified: August 09, 2022. Website built with Franklin.jl and the Julia programming language.