JET.jl

JET employs Julia's type inference system to detect potential bugs and type instabilities.

Warning

Please note that due to JET's tight integration with the Julia compiler, the results presented by JET can vary significantly depending on the version of Julia you are using. Additionally, the implementation of the Base module and standard libraries bundled with Julia can also affect the results.

Moreover, the Julia compiler's plugin system is still unstable and its interface changes frequently, so each version of JET is compatible with only limited versions of Julia. The Julia package manager will automatically select and install the latest version of JET that is compatible with your Julia version. However, if you are using the nightly version of Julia, please note that a compatible version of JET may not have been released yet, and JET installed via the Julia package manager may not function properly.

Quickstart

See more commands, options and explanations in the documentation.

Installation

JET is a standard Julia package. So you can just install it via Julia's built-in package manager and use it just like any other package:

julia> using Pkg; Pkg.add("JET")
[ some output elided ]

julia> using JET

Detect type instability with `@report_opt`

Type instabilities can be detected in function calls using the @report_opt macro, which works similar to the @code_warntype macro. Note that, because JET relies on Julia's type inference, if a chain of inference is broken due to dynamic dispatch, then all downstream function calls will be unknown to the compiler, and so JET cannot analyze them.

julia> @report_opt foldl(+, Any[]; init=0)═════ 2 possible errors found ═════
┌ kwcall(::@NamedTuple{init::Int64}, ::typeof(foldl), op::typeof(+), itr::Vector{Any}) @ Base ./reduce.jl:198
│┌ foldl(op::typeof(+), itr::Vector{Any}; kw::@Kwargs{init::Int64}) @ Base ./reduce.jl:198
││┌ kwcall(::@NamedTuple{init::Int64}, ::typeof(mapfoldl), f::typeof(identity), op::typeof(+), itr::Vector{Any}) @ Base ./reduce.jl:175
│││┌ mapfoldl(f::typeof(identity), op::typeof(+), itr::Vector{Any}; init::Int64) @ Base ./reduce.jl:175
││││┌ mapfoldl_impl(f::typeof(identity), op::typeof(+), nt::Int64, itr::Vector{Any}) @ Base ./reduce.jl:44
│││││┌ foldl_impl(op::Base.BottomRF{typeof(+)}, nt::Int64, itr::Vector{Any}) @ Base ./reduce.jl:48
││││││┌ _foldl_impl(op::Base.BottomRF{typeof(+)}, init::Int64, itr::Vector{Any}) @ Base ./reduce.jl:58
│││││││┌ (::Base.BottomRF{typeof(+)})(acc::Int64, x::Any) @ Base ./reduce.jl:86
││││││││ runtime dispatch detected: +(acc::Int64, x::Any)::Any
│││││││└────────────────────
││││││┌ _foldl_impl(op::Base.BottomRF{typeof(+)}, init::Int64, itr::Vector{Any}) @ Base ./reduce.jl:62
│││││││┌ (::Base.BottomRF{typeof(+)})(acc::Any, x::Any) @ Base ./reduce.jl:86
││││││││ runtime dispatch detected: +(acc::Any, x::Any)::Any
│││││││└────────────────────

Detect type errors with `@report_call`

This works best on type stable code, so use @report_opt liberally before using @report_call.

julia> @report_call foldl(+, Char[])═════ 2 possible errors found ═════
┌ foldl(op::typeof(+), itr::Vector{Char}) @ Base ./reduce.jl:198
│┌ foldl(op::typeof(+), itr::Vector{Char}; kw::@Kwargs{}) @ Base ./reduce.jl:198
││┌ mapfoldl(f::typeof(identity), op::typeof(+), itr::Vector{Char}) @ Base ./reduce.jl:175
│││┌ mapfoldl(f::typeof(identity), op::typeof(+), itr::Vector{Char}; init::Base._InitialValue) @ Base ./reduce.jl:175
││││┌ mapfoldl_impl(f::typeof(identity), op::typeof(+), nt::Base._InitialValue, itr::Vector{Char}) @ Base ./reduce.jl:44
│││││┌ foldl_impl(op::Base.BottomRF{typeof(+)}, nt::Base._InitialValue, itr::Vector{Char}) @ Base ./reduce.jl:48
││││││┌ _foldl_impl(op::Base.BottomRF{typeof(+)}, init::Base._InitialValue, itr::Vector{Char}) @ Base ./reduce.jl:62
│││││││┌ (::Base.BottomRF{typeof(+)})(acc::Char, x::Char) @ Base ./reduce.jl:86
││││││││ no matching method found `+(::Char, ::Char)`: (op::Base.BottomRF{typeof(+)}).rf::typeof(+)(acc::Char, x::Char)
│││││││└────────────────────
│││││┌ foldl_impl(op::Base.BottomRF{typeof(+)}, nt::Base._InitialValue, itr::Vector{Char}) @ Base ./reduce.jl:49
││││││┌ reduce_empty_iter(op::Base.BottomRF{typeof(+)}, itr::Vector{Char}) @ Base ./reduce.jl:380
│││││││┌ reduce_empty_iter(op::Base.BottomRF{typeof(+)}, itr::Vector{Char}, ::Base.HasEltype) @ Base ./reduce.jl:381
││││││││┌ reduce_empty(op::Base.BottomRF{typeof(+)}, ::Type{Char}) @ Base ./reduce.jl:357
│││││││││┌ reduce_empty(::typeof(+), ::Type{Char}) @ Base ./reduce.jl:343
││││││││││ no matching method found `zero(::Type{Char})`: zero(T::Type{Char})
│││││││││└────────────────────

Analyze packages with `report_package`

This looks for all method definitions and analyses function calls based on their signatures. Note that this is less accurate than @report_call, because the actual input types cannot be known for generic methods.

julia> using Pkg; Pkg.activate(; temp=true, io=devnull); Pkg.add("AbstractTrees"; io=devnull);
julia> Pkg.status()Status `/tmp/jl_qn6Fb2/Project.toml`
  [1520ce14] AbstractTrees v0.4.5
julia> report_package("AbstractTrees"; toplevel_logger=nothing)═════ 9 possible errors found ═════
┌ isroot(root::Any, x::Any) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/base.jl:102
│ no matching method found `parent(::Any, ::Any)`: AbstractTrees.parent(root::Any, x::Any)
└────────────────────
┌ AbstractTrees.StableNode{T}(x::T, ch::Any) where T @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/base.jl:260
│┌ collect(::Type{AbstractTrees.StableNode{_A}} where _A, itr::Any) @ Base ./array.jl:636
││┌ _collect(::Type{…}, itr::Any, isz::Union{…}) where _A @ Base ./array.jl:638
│││┌ _array_for(::Type{AbstractTrees.StableNode{…}} where _A, itr::Base.HasLength, isz::Any) @ Base ./array.jl:668
││││┌ _similar_shape(itr::Base.HasLength, ::Base.HasLength) @ Base ./array.jl:652
│││││ no matching method found `length(::Base.HasLength)`: length(itr::Base.HasLength)
││││└────────────────────
││││┌ _similar_shape(itr::Base.HasLength, ::Base.HasShape) @ Base ./array.jl:653
│││││┌ axes(A::Base.HasLength) @ Base ./abstractarray.jl:98
││││││ no matching method found `size(::Base.HasLength)`: size(A::Base.HasLength)
│││││└────────────────────
┌ AbstractTrees.IndexNode(tree::Any) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/indexing.jl:117
│ no matching method found `rootindex(::Any)`: rootindex(tree::Any)
└────────────────────
┌ parent(idx::AbstractTrees.IndexNode) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/indexing.jl:127
│ no matching method found `parentindex(::Any, ::Any)`: pidx = parentindex((idx::AbstractTrees.IndexNode).tree::Any, (idx::AbstractTrees.IndexNode).index::Any)
└────────────────────
┌ nextsibling(idx::AbstractTrees.IndexNode) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/indexing.jl:132
│ no matching method found `nextsiblingindex(::Any, ::Any)`: sidx = nextsiblingindex((idx::AbstractTrees.IndexNode).tree::Any, (idx::AbstractTrees.IndexNode).index::Any)
└────────────────────
┌ prevsibling(idx::AbstractTrees.IndexNode) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/indexing.jl:137
│ no matching method found `prevsiblingindex(::Any, ::Any)`: sidx = prevsiblingindex((idx::AbstractTrees.IndexNode).tree::Any, (idx::AbstractTrees.IndexNode).index::Any)
└────────────────────
┌ prevsibling(csr::AbstractTrees.IndexedCursor) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/cursors.jl:234
│ no matching method found `getindex(::Nothing, ::Int64)` (1/2 union split): (AbstractTrees.parent(csr::AbstractTrees.IndexedCursor)::Union{Nothing, AbstractTrees.IndexedCursor})[idx::Int64]
└────────────────────
┌ (::AbstractTrees.var"#17#18")(n::Any) @ AbstractTrees /home/runner/.julia/packages/AbstractTrees/Ftf8W/src/iteration.jl:323
│ no matching method found `parent(::Any, ::Any)`: AbstractTrees.parent(getfield(#self#::AbstractTrees.var"#17#18", :tree)::Any, n::Any)
└────────────────────

Limitations

JET explores the functions you call directly as well as their inferable callees. However, if the argument types for a call cannot be inferred, JET does not analyze the callee. Consequently, a report of No errors detected does not imply that your entire codebase is free of errors. To increase the confidence in JET's results use @report_opt to make sure your code is inferrible.

JET integrates with SnoopCompile, and you can sometimes use SnoopCompile to collect the data to perform more comprehensive analyses. SnoopCompile's limitation is that it only collects data for calls that have not been previously inferred, so you must perform this type of analysis in a fresh session.

See SnoopCompile's JET-integration documentation for further details.

Acknowledgement

This project started as my undergrad thesis project at Kyoto University, supervised by Prof. Takashi Sakuragawa. We were heavily inspired by ruby/typeprof, an experimental type understanding/checking tool for Ruby. The grad thesis about this project is published at https://github.com/aviatesk/grad-thesis, but currently, it's only available in Japanese.