1.4.2-pre-58353fd273.log

Julia Version 1.4.2-pre.13
Commit 58353fd273 (2020-05-10 17:03 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
Environment:
  JULIA_DEPOT_PATH = ::/usr/local/share/julia
  JULIA_NUM_THREADS = 2

  Resolving package versions...
  Installed InterpretMe ─ v0.1.0
   Updating `~/.julia/environments/v1.4/Project.toml`
  [e2b23942] + InterpretMe v0.1.0
   Updating `~/.julia/environments/v1.4/Manifest.toml`
  [e2b23942] + InterpretMe v0.1.0
  [8f399da3] + Libdl 
  [37e2e46d] + LinearAlgebra 
  [9a3f8284] + Random 
  [9e88b42a] + Serialization 
  [2f01184e] + SparseArrays 
  [10745b16] + Statistics 
    Testing InterpretMe
Status `/tmp/jl_DTPUB7/Manifest.toml`
  [621f4979] AbstractFFTs v0.5.0
  [79e6a3ab] Adapt v1.0.1
  [7d9fca2a] Arpack v0.4.0
  [68821587] Arpack_jll v3.5.0+3
  [4fba245c] ArrayInterface v2.8.7
  [b99e7846] BinaryProvider v0.5.9
  [336ed68f] CSV v0.6.1
  [324d7699] CategoricalArrays v0.7.7
  [aaaa29a8] Clustering v0.14.0
  [944b1d66] CodecZlib v0.6.0
  [3da002f7] ColorTypes v0.10.3
  [5ae59095] Colors v0.12.0
  [bbf7d656] CommonSubexpressions v0.2.0
  [34da2185] Compat v3.9.1
  [e66e0078] CompilerSupportLibraries_jll v0.3.3+0
  [8f4d0f93] Conda v1.4.1
  [9a962f9c] DataAPI v1.3.0
  [a93c6f00] DataFrames v0.20.2
  [864edb3b] DataStructures v0.17.15
  [e2d170a0] DataValueInterfaces v1.0.0
  [7806a523] DecisionTree v0.10.1
  [163ba53b] DiffResults v1.0.2
  [b552c78f] DiffRules v1.0.1
  [b4f34e82] Distances v0.8.2
  [31c24e10] Distributions v0.22.6
  [ffbed154] DocStringExtensions v0.8.1
  [e30172f5] Documenter v0.24.11
  [fdbdab4c] ElasticArrays v1.2.0
  [2904ab23] ElasticPDMats v0.2.1
  [e2ba6199] ExprTools v0.1.1
  [8f5d6c58] EzXML v1.1.0
  [7a1cc6ca] FFTW v1.2.1
  [f5851436] FFTW_jll v3.3.9+5
  [442a2c76] FastGaussQuadrature v0.4.2
  [5789e2e9] FileIO v1.3.0
  [48062228] FilePathsBase v0.7.0
  [1a297f60] FillArrays v0.8.9
  [6a86dc24] FiniteDiff v2.3.1
  [53c48c17] FixedPointNumbers v0.8.0
  [f6369f11] ForwardDiff v0.10.10
  [cc18c42c] GaussianMixtures v0.3.1
  [891a1506] GaussianProcesses v0.11.2
  [7869d1d1] IRTools v0.3.2
  [1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
  [e2b23942] InterpretMe v0.1.0
  [41ab1584] InvertedIndices v1.0.0
  [c8e1da08] IterTools v1.3.0
  [82899510] IteratorInterfaceExtensions v1.0.0
  [033835bb] JLD2 v0.1.13
  [682c06a0] JSON v0.21.0
  [b964fa9f] LaTeXStrings v1.1.0
  [94ce4f54] Libiconv_jll v1.16.0+2
  [d3d80556] LineSearches v7.0.1
  [856f044c] MKL_jll v2019.0.117+2
  [1914dd2f] MacroTools v0.5.5
  [e1d29d7a] Missings v0.4.3
  [78c3b35d] Mocking v0.7.1
  [0db19996] NBInclude v2.2.0
  [d41bc354] NLSolversBase v7.6.1
  [872c559c] NNlib v0.6.6
  [77ba4419] NaNMath v0.3.3
  [b8a86587] NearestNeighbors v0.4.4
  [4536629a] OpenBLAS_jll v0.3.9+4
  [efe28fd5] OpenSpecFun_jll v0.5.3+3
  [429524aa] Optim v0.20.6
  [bac558e1] OrderedCollections v1.2.0
  [90014a1f] PDMats v0.9.12
  [d96e819e] Parameters v0.12.1
  [69de0a69] Parsers v1.0.3
  [2dfb63ee] PooledArrays v0.5.3
  [85a6dd25] PositiveFactorizations v0.2.3
  [92933f4c] ProgressMeter v1.2.0
  [438e738f] PyCall v1.91.4
  [d330b81b] PyPlot v2.9.0
  [1fd47b50] QuadGK v2.3.1
  [df47a6cb] RData v0.7.1
  [ce6b1742] RDatasets v0.6.7
  [3cdcf5f2] RecipesBase v0.8.0
  [189a3867] Reexport v0.2.0
  [ae029012] Requires v1.0.1
  [79098fc4] Rmath v0.6.1
  [f50d1b31] Rmath_jll v0.2.2+0
  [3646fa90] ScikitLearn v0.6.1
  [6e75b9c4] ScikitLearnBase v0.5.0
  [b85f4697] SoftGlobalScope v1.0.10
  [a2af1166] SortingAlgorithms v0.3.1
  [276daf66] SpecialFunctions v0.10.0
  [90137ffa] StaticArrays v0.12.3
  [2913bbd2] StatsBase v0.32.2
  [4c63d2b9] StatsFuns v0.9.4
  [3783bdb8] TableTraits v1.0.0
  [bd369af6] Tables v1.0.4
  [f269a46b] TimeZones v1.1.1
  [3bb67fe8] TranscodingStreams v0.9.5
  [3a884ed6] UnPack v1.0.0
  [81def892] VersionParsing v1.2.0
  [ea10d353] WeakRefStrings v0.6.2
  [02c8fc9c] XML2_jll v2.9.9+4
  [83775a58] Zlib_jll v1.2.11+9
  [e88e6eb3] Zygote v0.4.8
  [700de1a5] ZygoteRules v0.2.0
  [2a0f44e3] Base64 
  [ade2ca70] Dates 
  [8bb1440f] DelimitedFiles 
  [8ba89e20] Distributed 
  [9fa8497b] Future 
  [b77e0a4c] InteractiveUtils 
  [76f85450] LibGit2 
  [8f399da3] Libdl 
  [37e2e46d] LinearAlgebra 
  [56ddb016] Logging 
  [d6f4376e] Markdown 
  [a63ad114] Mmap 
  [44cfe95a] Pkg 
  [de0858da] Printf 
  [3fa0cd96] REPL 
  [9a3f8284] Random 
  [ea8e919c] SHA 
  [9e88b42a] Serialization 
  [1a1011a3] SharedArrays 
  [6462fe0b] Sockets 
  [2f01184e] SparseArrays 
  [10745b16] Statistics 
  [4607b0f0] SuiteSparse 
  [8dfed614] Test 
  [cf7118a7] UUIDs 
  [4ec0a83e] Unicode 
ERROR: LoadError: PyError (PyImport_ImportModule

The Python package sklearn could not be found by pyimport. Usually this means
that you did not install sklearn in the Python version being used by PyCall.

PyCall is currently configured to use the Python version at:

/usr/bin/python3

and you should use whatever mechanism you usually use (apt-get, pip, conda,
etcetera) to install the Python package containing the sklearn module.

One alternative is to re-configure PyCall to use a different Python
version on your system: set ENV["PYTHON"] to the path/name of the python
executable you want to use, run Pkg.build("PyCall"), and re-launch Julia.

Another alternative is to configure PyCall to use a Julia-specific Python
distribution via the Conda.jl package (which installs a private Anaconda
Python distribution), which has the advantage that packages can be installed
and kept up-to-date via Julia.  As explained in the PyCall documentation,
set ENV["PYTHON"]="", run Pkg.build("PyCall"), and re-launch Julia. Then,
To install the sklearn module, you can use `pyimport_conda("sklearn", PKG)`,
where PKG is the Anaconda package the contains the module sklearn,
or alternatively you can use the Conda package directly (via
`using Conda` followed by `Conda.add` etcetera).

) <class 'ModuleNotFoundError'>
ModuleNotFoundError("No module named 'sklearn'",)

Stacktrace:
 [1] pyimport(::String) at /home/pkgeval/.julia/packages/PyCall/zqDXB/src/PyCall.jl:536
 [2] pyimport_conda(::String, ::String, ::String) at /home/pkgeval/.julia/packages/PyCall/zqDXB/src/PyCall.jl:694
 [3] pyimport_conda at /home/pkgeval/.julia/packages/PyCall/zqDXB/src/PyCall.jl:693 [inlined]
 [4] import_sklearn() at /home/pkgeval/.julia/packages/ScikitLearn/uiLep/src/Skcore.jl:119
 [5] top-level scope at /home/pkgeval/.julia/packages/ScikitLearn/uiLep/src/Skcore.jl:163
 [6] include(::String) at ./client.jl:439
 [7] top-level scope at none:6
in expression starting at /home/pkgeval/.julia/packages/InterpretMe/zfL8T/test/runtests.jl:6
ERROR: Package InterpretMe errored during testing
Stacktrace:
 [1] pkgerror(::String, ::Vararg{String,N} where N) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/Types.jl:53
 [2] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/Operations.jl:1510
 [3] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:316
 [4] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:303
 [5] #test#68 at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:297 [inlined]
 [6] test at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:297 [inlined]
 [7] #test#67 at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:296 [inlined]
 [8] test at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:296 [inlined]
 [9] test(::String; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:295
 [10] test(::String) at /workspace/srcdir/usr/share/julia/stdlib/v1.4/Pkg/src/API.jl:295
 [11] top-level scope at none:16