One interesting thing is that if julia can prove what types a function will be called with at compile time, it doesn't have to do dynamic dispatch, so it has no overhead. It's what the julia folks call type-stable code
This becomes an important part of optimizing Julia code. There is some tooling for this. Below, identity is a type stable function because we know that an Int64 argument results in a Int64 output. The macro code_warntype reveals the type analysis:
```
julia> @code_warntype identity(5)
MethodInstance for identity(::Int64)
from identity(x) @ Base operators.jl:513
Arguments
#self#::Core.Const(identity)
x::Int64
Body::Int64
1 ─ nothing
└── return x
```
This is type unstable and results in dynamic dispatch because we are not sure if the argument to identity will be an Int64 or a Float64.
```
julia> f(x) = identity(x ≥ 0 ? x : x + 0.0)
f (generic function with 1 method)
This becomes an important part of optimizing Julia code. There is some tooling for this. Below, identity is a type stable function because we know that an Int64 argument results in a Int64 output. The macro code_warntype reveals the type analysis:
julia> @code_warntype identity(5)
MethodInstance for identity(::Int64)
from identity(x) in Base at operators.jl:526
Arguments
#self#::Core.Const(identity)
x::Int64
Body::Int64
1 ─ return x
julia> f(x) = identity(x ≥ 0 ? x : x + 0.0)
f (generic function with 1 method)
julia> @code_warntype f(5)
MethodInstance for f(::Int64)
from f(x) in Main at REPL[6]:1
Arguments
#self#::Core.Const(f)
x::Int64
Locals
@_3::Union{Float64, Int64}
Body::Union{Float64, Int64}
1 ─ %1 = (x ≥ 0)::Bool
└── goto #3 if not %1
2 ─ (@_3 = x)
└── goto #4
3 ─ (@_3 = x + 0.0)
4 ┄ %6 = @_3::Union{Float64, Int64}
│ %7 = Main.identity(%6)::Union{Float64, Int64}
└── return %7