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[BUG]: PyCall.jl doesn't convert pyobject to Julia array when run in Juno #591
Comments
I can't repro this (with [email protected]) using PyCall
const np = pyimport("numpy")
a = np.zeros(3) # => Vector{Float64} with 3 elements |
@aviatesk I believe this bug still exists and can be reproduced with the following
Package versions are as follows
|
Could you try you can also reproduce this, e.g. using Debugger.jl or other JuliaInterpreter-based debugger ? I guess it's an upstream issue. |
@aviatesk Thanks! It seems to be an upstream issue. I got it replicated in REPL using Debugger.jl. Going to post an issue to the upstream
|
cool, here is where you want to post it: https://github.com/JuliaDebug/JuliaInterpreter.jl/issues |
Details
Steps to reproduce
using PyCall
np = pyimport("numpy")
a= np.zeros(3)
a stays PyObject
2.In REPL:
a= np.zeros(3)
3-element Array{Float64,1}:
0.0
0.0
0.0
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