JuliaLang / julia / #37241
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implement `compilerbarrier` builtin (#46432)

This builtin is useful to control compiler behavior.
It could be considered as a more robust and generalized version of `inferencebarrier`.

I scratched the following docstring for `compilerbarrier`, that hopefully
explains its purpose.

    Base.compilerbarrier(setting::Symbol, val)

This function puts a barrier at a specified compilation phase.
It is supposed to only influence the compilation behavior according to `setting`,
and its runtime semantics is just to return the second argument `val` (except that
this function will perform additional checks on `setting` in a case when `setting`
isn't known precisely at compile-time.)

Currently either of the following `setting`s is allowed:
- Barriers on abstract interpretation:
* `:type`: the return type of this function call will be inferred as `Any` always
(the strongest barrier on abstract interpretation)
* `:const`: the return type of this function call will be inferred with widening
constant information on `val`
* `:conditional`: the return type of this function call will be inferred with widening
conditional information on `val` (see the example below)
- Any barriers on optimization aren't implemented yet

!!! note
    This function is supposed to be used _with `setting` known precisely at compile-time_.
    Note that in a case when the `setting` isn't known precisely at compile-time, the compiler
    currently will put the most strongest barrier(s) rather than emitting a compile-time warning.

\# Examples

```julia
julia> Base.return_types((Int,)) do a
       x = compilerbarrier(:type, a) # `x` won't be inferred as `x::Int`
       return x
   end |> only
Any

julia> Base.return_types() do
       x = compilerbarrier(:const, 42)
       if x == 42 # no constant information here, so inference also accounts for the else branch
           return x # but `x` is still inferred as `x::Int` at least here
       else
    ... (continued)

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