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Hi,
Thanks for the awesome package. It really made some workflow yesterday quite smooth when I needed to iterate over the "presentation" of some dataframe but it'd have been quite painful to decouple that from the heavy computation for such a small one-off script.
Used it nicely with ThreadSafeDict.
But when things were accumulating too much in memory I was looking at LRUCache, but I've been getting:
julia>@memoizeLRU(maxsize=5) functionmycond(x)
println(x);
returncond(x)
end
ERROR: MethodError: objects of type LRU{Matrix{Float64}, Float64} are not callable
Stacktrace:
[1] #s44#53
@ C:\Users\elom\.julia\packages\Memoization\xgAKx\src\Memoization.jl:173 [inlined]
[2] var"#s44#53"(::Any, #unused#::Any)
@ Main .\none:0
[3] (::Core.GeneratedFunctionStub)(::Any, ::Vararg{Any})
@ Core .\boot.jl:580
[4] get_caches()
@ Memoization C:\Users\elom\.julia\packages\Memoization\xgAKx\src\Memoization.jl:58
[5] find_caches(func::typeof(_cond12))
@ Memoization C:\Users\elom\.julia\packages\Memoization\xgAKx\src\Memoization.jl:81
[6] empty_cache!(func::Function)
@ Memoization C:\Users\elom\.julia\packages\Memoization\xgAKx\src\Memoization.jl:80
[7] top-level scope
@ C:\Users\elom\.julia\packages\Memoization\xgAKx\src\Memoization.jl:180
Hi,
Thanks for the awesome package. It really made some workflow yesterday quite smooth when I needed to iterate over the "presentation" of some dataframe but it'd have been quite painful to decouple that from the heavy computation for such a small one-off script.
Used it nicely with ThreadSafeDict.
But when things were accumulating too much in memory I was looking at
LRUCache
, but I've been getting:I've skimmed #4 and when you said
That doesn't seem to be the case anymore. Maybe there was a recent regression?
in fact I get the same error when I try your
JLD2BackedDicts
example.Note: I am using v0.2 and Julia v1.7.2
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