Limitations
There are some kinds of changes that Revise (or often, Julia itself) cannot automatically incorporate into a running Julia session:
- changes to global bindings (but see below for struct definitions on Julia 1.12+)
- conflicts between variables and functions sharing the same name
- removal of
exports
These kinds of changes require that you restart your Julia session.
Struct revision (Julia 1.12+)
Starting with Julia 1.12, Revise can handle changes to struct definitions. When you modify a struct, Revise will automatically re-evaluate the struct definition and any methods or types that depend on it.
For example, this now works:
struct Inner
value::Int
end
struct Outer
inner::Inner
end
print_value(o::Outer) = println(o.inner.value)If you change it to:
struct Inner
value::Float64
name::String
endRevise will redefine Inner, and also re-evaluate Outer (which uses Inner as a field type) and print_value (which references Outer in its signature).
Binding revision is not yet supported
While struct revision is supported, more general "binding revision" is not yet implemented. Specifically, Revise does not track implicit dependencies between top-level bindings.
For example:
MyVecType{T} = Vector{T} # changing this to AbstractVector{T} won't update A
struct MyVec{T}
v::MyVecType{T}
endIf you change MyVecType{T} from Vector{T} to AbstractVector{T}, the struct A will not be automatically re-evaluated because Revise does not track the dependency edge from MyVecType to MyVec. The same applies to const bindings and other global bindings that are referenced in type definitions.
Supporting this would require tracking implicit binding edges across all top-level code, which involves significant interpreter enhancements and is deferred to future work. This limitation also underlies the issues with macros and generated functions described below.
As a workaround, you can manually call revise to force re-evaluation of all definitions in MyModule, which will pick up the new bindings.
Workaround for the struct revision issue before Julia 1.12
On Julia versions prior to 1.12, struct definitions cannot be revised. During early stages of development, it's quite common to want to change type definitions. You can work around Julia's/Revise's limitations by temporary renaming. We'll illustrate this below, using write to be explicit about when updates to the file happen. But in ordinary usage, these are changes you'd likely make with your editor.
julia> using Pkg, Revise
julia> Pkg.generate("MyPkg")
Generating project MyPkg:
MyPkg/Project.toml
MyPkg/src/MyPkg.jl
Dict{String, Base.UUID} with 1 entry:
"MyPkg" => UUID("69940cda-0c72-4a1a-ae0b-fd3109336fe8")
julia> cd("MyPkg")
julia> write("src/MyPkg.jl","""
module MyPkg
export FooStruct, processFoo
abstract type AbstractFooStruct end
struct FooStruct1 <: AbstractFooStruct
bar::Int
end
FooStruct = FooStruct1
function processFoo(foo::AbstractFooStruct)
@info foo.bar
end
end
""")
230
julia> Pkg.activate(".")
Activating project at `~/blah/MyPkg`
julia> using MyPkg
No Changes to `~/blah/MyPkg/Project.toml`
No Changes to `~/blah/MyPkg/Manifest.toml`
Precompiling MyPkg
1 dependency successfully precompiled in 2 seconds
julia> processFoo(FooStruct(1))
[ Info: 1
julia> write("src/MyPkg.jl","""
module MyPkg
export FooStruct, processFoo
abstract type AbstractFooStruct end
struct FooStruct2 <: AbstractFooStruct # change version number
bar::Float64 # change type of the field
end
FooStruct = FooStruct2 # update alias reference
function processFoo(foo::AbstractFooStruct)
@info foo.bar
end
end
""");
julia> FooStruct # make sure FooStruct refers to FooStruct2
MyPkg.FooStruct2
julia> processFoo(FooStruct(3.5))
[ Info: 3.5Here, note that we made two changes: we updated the "version number" of FooStruct when we changed something about its fields, and we also re-assigned FooStruct to alias the new version. We did not change the definition of any methods that have been typed AbstractFooStruct.
This works as long as the new type name doesn't conflict with an existing name; within a session you need to change the name each time you change the definition.
Once your development has converged on a solution, it's best to switch to the "permanent" name: in the example above, FooStruct is a non-constant global variable, and if used internally in a function there will be consequent performance penalties. Switching to the permanent name will force you to restart your session.
julia> isconst(MyPkg, :FooStruct)
true
julia> write("src/MyPkg.jl","""
module MyPkg
export FooStruct, processFoo
abstract type AbstractFooStruct end # this could be removed
struct FooStruct <: AbstractFooStruct # change to just FooStruct
bar::Float64
end
function processFoo(foo::AbstractFooStruct) # consider changing to FooStruct
@info foo.bar
end
end
""");
julia> run(Base.julia_cmd()) # start a new Julia session, alternatively exit() and restart julia
julia> using Pkg, Revise # NEW Julia Session
julia> Pkg.activate(".")
Activating project at `~/blah/MyPkg`
julia> using MyPkg
Precompiling MyPkg
1 dependency successfully precompiled in 2 seconds
julia> isconst(MyPkg, :FooStruct)
trueOther limitations
In addition, some situations may require special handling:
Macros and generated functions
If you change a macro definition or methods that get called by @generated functions outside their quote block, these changes will not be propagated to functions that have already evaluated the macro or generated function.
You may explicitly call revise(MyModule) to force reevaluating every definition in module MyModule. Note that when a macro changes, you have to revise all of the modules that use it.
Distributed computing (multiple workers) and anonymous functions
Revise supports changes to code in worker processes. The code must be loaded in the main process in which Revise is running.
Revise cannot handle changes in anonymous functions used in remotecalls. Consider the following module definition:
module ParReviseExample
using Distributed
greet(x) = println("Hello, ", x)
foo() = for p in workers()
remotecall_fetch(() -> greet("Bar"), p)
end
end # moduleChanging the remotecall to remotecall_fetch((x) -> greet("Bar"), p, 1) will fail, because the new anonymous function is not defined on all workers. The workaround is to write the code to use named functions, e.g.,
module ParReviseExample
using Distributed
greet(x) = println("Hello, ", x)
greetcaller() = greet("Bar")
foo() = for p in workers()
remotecall_fetch(greetcaller, p)
end
end # moduleand the corresponding edit to the code would be to modify it to greetcaller(x) = greet("Bar") and remotecall_fetch(greetcaller, p, 1).