I'm afraid it's not quite true, and I found simple way to show it. In the next code snippet I define function `f` and serialize it to a file:
julia> f(x) = x + 1 f (generic function with 1 method) julia> f(5) 6 julia> open("example.jld", "w") do io serialize(io, f) end Then I close Julia REPL and in a new session try to load and use this function: julia> f2 = open("example.jld") do io deserialize(io) end (anonymous function) julia> f2(5) ERROR: function f not defined on process 1 in error at error.jl:21 in anonymous at serialize.jl:398 So deserialized function still refers to the old definition, which is not available in this new session. Is there any better way to serialize a function and run it on an unrelated Julia process? On Monday, August 10, 2015 at 2:33:11 PM UTC+3, Jeff Waller wrote: > > > >> My question is: does Julia's serialization produce completely >> self-containing code that can be run on workers? In other words, is it >> possible to send serialized function over network to another host / Julia >> process and applied there without any additional information from the first >> process? >> >> I made some tests on a single machine, and when I defined function >> without `@everywhere`, worker failed with a message "function myfunc not >> defined on process 1". With `@everywhere`, my code worked, but will it work >> on multiple hosts with essentially independent Julia processes? >> > > According to Jey here > <https://groups.google.com/forum/#!searchin/julia-users/jey/julia-users/bolLGcSCrs0/fGGVLgNhI2YJ>, > > Base.serialize does what we want; it's contained in serialize.jl > <https://github.com/JuliaLang/julia/blob/master/base/serialize.jl> > >