Limitations

There are some kinds of changes that Revise (or often, Julia itself) cannot incorporate into a running Julia session:

• changes to type definitions
• conflicts between variables and functions sharing the same name

These kinds of changes require that you restart your Julia session.

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 # module

Changing 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 # module

and the corresponding edit to the code would be to modify it to greetcaller(x) = greet("Bar") and remotecall_fetch(greetcaller, p, 1).