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1.5.0-DEV-c9805191e3.log
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Julia Version 1.5.0-DEV.570
Commit c9805191e3 (2020-04-04 00:18 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, skylake)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
JULIA_NUM_THREADS = 2
Resolving package versions...
Installed PooledArrays ──────────────── v0.5.3
Installed WeakRefStrings ────────────── v0.6.2
Installed SortingAlgorithms ─────────── v0.3.1
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed Parsers ───────────────────── v1.0.1
Installed JSON ──────────────────────── v0.21.0
Installed DataStructures ────────────── v0.17.11
Installed AutoMLPipeline ────────────── v0.1.10
Installed Conda ─────────────────────── v1.4.1
Installed PyCall ────────────────────── v1.91.4
Installed Reexport ──────────────────── v0.2.0
Installed InvertedIndices ───────────── v1.0.0
Installed DataAPI ───────────────────── v1.1.0
Installed CategoricalArrays ─────────── v0.7.7
Installed StatsBase ─────────────────── v0.33.0
Installed DecisionTree ──────────────── v0.10.1
Installed OrderedCollections ────────── v1.1.0
Installed VersionParsing ────────────── v1.2.0
Installed DataValueInterfaces ───────── v1.0.0
Installed Tables ────────────────────── v1.0.3
Installed MacroTools ────────────────── v0.5.5
Installed MLBase ────────────────────── v0.8.0
Installed Compat ────────────────────── v3.8.0
Installed ScikitLearnBase ───────────── v0.5.0
Installed TableTraits ───────────────── v1.0.0
Installed IterTools ─────────────────── v1.3.0
Installed Missings ──────────────────── v0.4.3
Installed DataFrames ────────────────── v0.20.2
Installed FilePathsBase ─────────────── v0.7.0
Installed CSV ───────────────────────── v0.6.0
Updating `~/.julia/environments/v1.5/Project.toml`
08437348 + AutoMLPipeline v0.1.10
Updating `~/.julia/environments/v1.5/Manifest.toml`
08437348 + AutoMLPipeline v0.1.10
336ed68f + CSV v0.6.0
324d7699 + CategoricalArrays v0.7.7
34da2185 + Compat v3.8.0
8f4d0f93 + Conda v1.4.1
9a962f9c + DataAPI v1.1.0
a93c6f00 + DataFrames v0.20.2
864edb3b + DataStructures v0.17.11
e2d170a0 + DataValueInterfaces v1.0.0
7806a523 + DecisionTree v0.10.1
48062228 + FilePathsBase v0.7.0
41ab1584 + InvertedIndices v1.0.0
c8e1da08 + IterTools v1.3.0
82899510 + IteratorInterfaceExtensions v1.0.0
682c06a0 + JSON v0.21.0
f0e99cf1 + MLBase v0.8.0
1914dd2f + MacroTools v0.5.5
e1d29d7a + Missings v0.4.3
bac558e1 + OrderedCollections v1.1.0
69de0a69 + Parsers v1.0.1
2dfb63ee + PooledArrays v0.5.3
438e738f + PyCall v1.91.4
189a3867 + Reexport v0.2.0
6e75b9c4 + ScikitLearnBase v0.5.0
a2af1166 + SortingAlgorithms v0.3.1
2913bbd2 + StatsBase v0.33.0
3783bdb8 + TableTraits v1.0.0
bd369af6 + Tables v1.0.3
81def892 + VersionParsing v1.2.0
ea10d353 + WeakRefStrings v0.6.2
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
8dfed614 + Test
cf7118a7 + UUIDs
4ec0a83e + Unicode
Building Conda ─────────→ `~/.julia/packages/Conda/3rPhK/deps/build.log`
Building PyCall ────────→ `~/.julia/packages/PyCall/zqDXB/deps/build.log`
Building AutoMLPipeline → `~/.julia/packages/AutoMLPipeline/FnJnG/deps/build.log`
Testing AutoMLPipeline
Status `/tmp/jl_hNlDHM/Project.toml`
08437348 AutoMLPipeline v0.1.10
336ed68f CSV v0.6.0
8f4d0f93 Conda v1.4.1
a93c6f00 DataFrames v0.20.2
7806a523 DecisionTree v0.10.1
c8e1da08 IterTools v1.3.0
f0e99cf1 MLBase v0.8.0
438e738f PyCall v1.91.4
2913bbd2 StatsBase v0.33.0
ade2ca70 Dates
9a3f8284 Random
10745b16 Statistics
8dfed614 Test
Status `/tmp/jl_hNlDHM/Manifest.toml`
08437348 AutoMLPipeline v0.1.10
336ed68f CSV v0.6.0
324d7699 CategoricalArrays v0.7.7
34da2185 Compat v3.8.0
8f4d0f93 Conda v1.4.1
9a962f9c DataAPI v1.1.0
a93c6f00 DataFrames v0.20.2
864edb3b DataStructures v0.17.11
e2d170a0 DataValueInterfaces v1.0.0
7806a523 DecisionTree v0.10.1
48062228 FilePathsBase v0.7.0
41ab1584 InvertedIndices v1.0.0
c8e1da08 IterTools v1.3.0
82899510 IteratorInterfaceExtensions v1.0.0
682c06a0 JSON v0.21.0
f0e99cf1 MLBase v0.8.0
1914dd2f MacroTools v0.5.5
e1d29d7a Missings v0.4.3
bac558e1 OrderedCollections v1.1.0
69de0a69 Parsers v1.0.1
2dfb63ee PooledArrays v0.5.3
438e738f PyCall v1.91.4
189a3867 Reexport v0.2.0
6e75b9c4 ScikitLearnBase v0.5.0
a2af1166 SortingAlgorithms v0.3.1
2913bbd2 StatsBase v0.33.0
3783bdb8 TableTraits v1.0.0
bd369af6 Tables v1.0.3
81def892 VersionParsing v1.2.0
ea10d353 WeakRefStrings v0.6.2
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
8dfed614 Test
cf7118a7 UUIDs
4ec0a83e Unicode
[ Info: suppressing PyCall warnings
ERROR: LoadError: LoadError: InitError: PyError (PyImport_ImportModule
The Python package sklearn.decomposition could not be found by pyimport. Usually this means
that you did not install sklearn.decomposition 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.decomposition 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.decomposition module, you can use `pyimport_conda("sklearn.decomposition", PKG)`,
where PKG is the Anaconda package the contains the module sklearn.decomposition,
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] __init__() at /home/pkgeval/.julia/packages/AutoMLPipeline/FnJnG/src/skpreprocessor.jl:17
[5] _include_from_serialized(::String, ::Array{Any,1}) at ./loading.jl:697
[6] _require_from_serialized(::String) at ./loading.jl:748
[7] _require(::Base.PkgId) at ./loading.jl:1039
[8] require(::Base.PkgId) at ./loading.jl:927
[9] require(::Module, ::Symbol) at ./loading.jl:922
[10] include(::Function, ::Module, ::String) at ./Base.jl:380
[11] include at ./Base.jl:368 [inlined]
[12] include(::String) at /home/pkgeval/.julia/packages/AutoMLPipeline/FnJnG/test/runtests.jl:1
[13] top-level scope at /home/pkgeval/.julia/packages/AutoMLPipeline/FnJnG/test/runtests.jl:11
[14] include(::String) at ./client.jl:441
[15] top-level scope at none:6
during initialization of module SKPreprocessors
in expression starting at /home/pkgeval/.julia/packages/AutoMLPipeline/FnJnG/test/test_skpreprocessing.jl:5
in expression starting at /home/pkgeval/.julia/packages/AutoMLPipeline/FnJnG/test/runtests.jl:11
ERROR: Package AutoMLPipeline errored during testing
Stacktrace:
[1] pkgerror(::String, ::Vararg{String,N} where N) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/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 /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/Operations.jl:1523
[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 /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:316
[4] test(::Pkg.Types.Context, ::Array{Pkg.Types.PackageSpec,1}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:303
[5] #test#68 at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:297 [inlined]
[6] test at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:297 [inlined]
[7] #test#67 at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:296 [inlined]
[8] test at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:296 [inlined]
[9] test(::String; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:295
[10] test(::String) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.5/Pkg/src/API.jl:295
[11] top-level scope at none:16