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>
>
>
