Popularity
243 Stars
Updated Last
1 Year Ago
Started In
March 2018

Traceur

Build Status Docs

Traceur is essentially a codified version of the Julia performance tips. You run your code, it tells you about any obvious performance traps.

julia> using Traceur

julia> naive_relu(x) = x < 0 ? 0 : x

julia> @trace naive_relu(1.0)
naive_relu(::Float64) at none:1
    returns Union{Float64, Int64}
1.0

julia> function naive_sum(xs)
         s = 0
         for x in xs
           s += x
         end
         return s
       end

julia> @trace naive_sum([1.])
Base.indexed_next(::Tuple{Int64,Bool}, ::Int64, ::Int64) at tuple.jl:54
    returns Tuple{Union{Bool, Int64},Int64}
naive_sum(::Array{Float64,1}) at none:2
    s is assigned as Int64 at line 2
    s is assigned as Float64 at line 4
    dynamic dispatch to s + x at line 4
    returns Union{Float64, Int64}
1.0

julia> y = 1

julia> f(x) = x+y

julia> @trace f(1)
f(::Int64) at none:1
    uses global variable Main.y
    dynamic dispatch to x + Main.y at line 1
    returns Any
2

Mechanics

The heavily lifting is done by analyse, which takes a Call (essentially a (f, args...) tuple for each function called in the code). Most of the analysis steps work by retrieving the code_typed of the function, inspecting it for issues and emitting any warnings.

Suggestions for (or better, implementations of!) further analysis passes are welcome.

Required Packages

Used By Packages

No packages found.