Package evaluation of ScikitLearn on Julia 1.13.0-DEV.1244 (c841b5fe7d*) started at 2025-10-02T21:47:13.614 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 7.24s ################################################################################ # Installation # Installing ScikitLearn... Resolving package versions... Installed Conda ── v1.10.2 Installed PyCall ─ v1.96.4 Updating `~/.julia/environments/v1.13/Project.toml` [3646fa90] + ScikitLearn v0.7.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [34da2185] + Compat v4.18.1 [8f4d0f93] + Conda v1.10.2 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.0 ⌅ [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [ffbed154] + DocStringExtensions v0.9.5 [842dd82b] + InlineStrings v1.4.5 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [682c06a0] + JSON v0.21.4 [b964fa9f] + LaTeXStrings v1.4.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [e1d29d7a] + Missings v1.2.0 [bac558e1] + OrderedCollections v1.8.1 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 [2dfb63ee] + PooledArrays v1.4.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 [08abe8d2] + PrettyTables v3.0.11 [438e738f] + PyCall v1.96.4 [189a3867] + Reexport v1.2.2 [3646fa90] + ScikitLearn v0.7.0 [6e75b9c4] + ScikitLearnBase v0.5.0 [91c51154] + SentinelArrays v1.4.8 [a2af1166] + SortingAlgorithms v1.2.2 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 ⌅ [2913bbd2] + StatsBase v0.33.21 [892a3eda] + StringManipulation v0.4.1 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3a884ed6] + UnPack v1.0.2 [81def892] + VersionParsing v1.3.0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [b27032c2] + LibCURL v0.6.4 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [fa267f1f] + TOML v1.0.3 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.16.0+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.9.9 [4536629a] + OpenBLAS_jll v0.3.29+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.13.1+0 [8e850ede] + nghttp2_jll v1.67.1+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Building Conda ─→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/b19db3927f0db4151cb86d073689f2428e524576/build.log` Building PyCall → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/9816a3826b0ebf49ab4926e2b18842ad8b5c8f04/build.log` Installation completed after 51.06s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Warning: Could not use exact versions of packages in manifest, re-resolving └ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:76 Precompiling package dependencies... Precompilation completed after 269.62s ################################################################################ # Testing # Testing ScikitLearn Test Could not use exact versions of packages in manifest, re-resolving. Note: if you do not check your manifest file into source control, then you can probably ignore this message. However, if you do check your manifest file into source control, then you probably want to pass the `allow_reresolve = false` kwarg when calling the `Pkg.test` function. Updating `/tmp/jl_BVhb1C/Project.toml` [7806a523] + DecisionTree v0.12.4 [cc18c42c] + GaussianMixtures v0.3.13 [891a1506] + GaussianProcesses v0.12.5 [0db19996] + NBInclude v2.4.0 [d330b81b] + PyPlot v2.11.6 ⌅ [df47a6cb] + RData v0.8.3 [ce6b1742] + RDatasets v0.7.7 [3646fa90] + ScikitLearn v0.7.0 [8dfed614] ~ Test ⇒ v1.11.0 Updating `/tmp/jl_BVhb1C/Manifest.toml` [47edcb42] + ADTypes v1.18.0 [1520ce14] + AbstractTrees v0.4.5 [79e6a3ab] + Adapt v4.4.0 [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [4fba245c] + ArrayInterface v7.20.0 [336ed68f] + CSV v0.10.15 ⌅ [324d7699] + CategoricalArrays v0.10.8 [d360d2e6] + ChainRulesCore v1.26.0 [aaaa29a8] + Clustering v0.15.8 [944b1d66] + CodecZlib v0.7.8 [3da002f7] + ColorTypes v0.12.1 [5ae59095] + Colors v0.13.1 [bbf7d656] + CommonSubexpressions v0.3.1 [187b0558] + ConstructionBase v1.6.0 [7806a523] + DecisionTree v0.12.4 [8bb1440f] + DelimitedFiles v1.9.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.8 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.120 [fdbdab4c] + ElasticArrays v1.2.12 [2904ab23] + ElasticPDMats v0.2.3 [4e289a0a] + EnumX v1.0.5 [e2ba6199] + ExprTools v0.1.10 ⌅ [442a2c76] + FastGaussQuadrature v0.4.9 [5789e2e9] + FileIO v1.17.0 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.14.0 [6a86dc24] + FiniteDiff v2.28.1 [53c48c17] + FixedPointNumbers v0.8.5 ⌅ [f6369f11] + ForwardDiff v0.10.39 [cc18c42c] + GaussianMixtures v0.3.13 [891a1506] + GaussianProcesses v0.12.5 [076d061b] + HashArrayMappedTries v0.2.0 [3587e190] + InverseFunctions v0.1.17 ⌅ [92d709cd] ↓ IrrationalConstants v0.2.4 ⇒ v0.1.1 ⌅ [033835bb] + JLD2 v0.5.15 [692b3bcd] + JLLWrappers v1.7.1 [d3d80556] + LineSearches v7.4.0 [78c3b35d] + Mocking v0.8.1 [0db19996] + NBInclude v2.4.0 [d41bc354] + NLSolversBase v7.10.0 [77ba4419] + NaNMath v1.1.3 [b8a86587] + NearestNeighbors v0.4.22 [429524aa] + Optim v1.13.2 [90014a1f] + PDMats v0.11.35 [85a6dd25] + PositiveFactorizations v0.2.4 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.3.0 [d330b81b] + PyPlot v2.11.6 [1fd47b50] + QuadGK v2.11.2 ⌅ [df47a6cb] + RData v0.8.3 [ce6b1742] + RDatasets v0.7.7 [3cdcf5f2] + RecipesBase v1.3.4 [ae029012] + Requires v1.3.1 ⌅ [79098fc4] + Rmath v0.7.1 [3646fa90] + ScikitLearn v0.7.0 [7e506255] + ScopedValues v1.5.0 [6c6a2e73] + Scratch v1.3.0 [efcf1570] + Setfield v1.1.2 [b85f4697] + SoftGlobalScope v1.1.0 [276daf66] + SpecialFunctions v2.5.1 [90137ffa] + StaticArrays v1.9.15 [1e83bf80] + StaticArraysCore v1.4.3 ⌅ [4c63d2b9] + StatsFuns v0.9.18 [dc5dba14] + TZJData v1.5.0+2025b [f269a46b] + TimeZones v1.22.0 [3bb67fe8] + TranscodingStreams v0.11.3 [ea10d353] + WeakRefStrings v1.4.2 [76eceee3] + WorkerUtilities v1.6.1 ⌅ [68821587] + Arpack_jll v3.5.1+1 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 ⌅ [f50d1b31] + Rmath_jll v0.4.3+0 [76f85450] + LibGit2 v1.11.0 [56ddb016] + Logging v1.11.0 [44cfe95a] + Pkg v1.13.0 [4607b0f0] + SuiteSparse [a4e569a6] + Tar v1.10.0 [8dfed614] ~ Test ⇒ v1.11.0 [e37daf67] + LibGit2_jll v1.9.1+0 [05823500] + OpenLibm_jll v0.8.7+0 [efcefdf7] + PCRE2_jll v10.46.0+0 [3f19e933] + p7zip_jll v17.6.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Test Successfully re-resolved Status `/tmp/jl_BVhb1C/Project.toml` [34da2185] Compat v4.18.1 [8f4d0f93] Conda v1.10.2 [a93c6f00] DataFrames v1.8.0 [7806a523] DecisionTree v0.12.4 [cc18c42c] GaussianMixtures v0.3.13 [891a1506] GaussianProcesses v0.12.5 [c8e1da08] IterTools v1.10.0 [1914dd2f] MacroTools v0.5.16 [0db19996] NBInclude v2.4.0 [d96e819e] Parameters v0.12.3 [438e738f] PyCall v1.96.4 [d330b81b] PyPlot v2.11.6 ⌅ [df47a6cb] RData v0.8.3 [ce6b1742] RDatasets v0.7.7 [3646fa90] ScikitLearn v0.7.0 [6e75b9c4] ScikitLearnBase v0.5.0 [10745b16] Statistics v1.11.1 ⌅ [2913bbd2] StatsBase v0.33.21 [81def892] VersionParsing v1.3.0 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_BVhb1C/Manifest.toml` [47edcb42] ADTypes v1.18.0 [1520ce14] AbstractTrees v0.4.5 [79e6a3ab] Adapt v4.4.0 [66dad0bd] AliasTables v1.1.3 [7d9fca2a] Arpack v0.5.4 [4fba245c] ArrayInterface v7.20.0 [336ed68f] CSV v0.10.15 ⌅ [324d7699] CategoricalArrays v0.10.8 [d360d2e6] ChainRulesCore v1.26.0 [aaaa29a8] Clustering v0.15.8 [944b1d66] CodecZlib v0.7.8 [3da002f7] ColorTypes v0.12.1 [5ae59095] Colors v0.13.1 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [8f4d0f93] Conda v1.10.2 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.0 ⌅ [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [7806a523] DecisionTree v0.12.4 [8bb1440f] DelimitedFiles v1.9.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.8 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.5 [fdbdab4c] ElasticArrays v1.2.12 [2904ab23] ElasticPDMats v0.2.3 [4e289a0a] EnumX v1.0.5 [e2ba6199] ExprTools v0.1.10 ⌅ [442a2c76] FastGaussQuadrature v0.4.9 [5789e2e9] FileIO v1.17.0 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.14.0 [6a86dc24] FiniteDiff v2.28.1 [53c48c17] FixedPointNumbers v0.8.5 ⌅ [f6369f11] ForwardDiff v0.10.39 [cc18c42c] GaussianMixtures v0.3.13 [891a1506] GaussianProcesses v0.12.5 [076d061b] HashArrayMappedTries v0.2.0 [842dd82b] InlineStrings v1.4.5 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 ⌅ [92d709cd] IrrationalConstants v0.1.1 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] JLD2 v0.5.15 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v0.21.4 [b964fa9f] LaTeXStrings v1.4.0 [d3d80556] LineSearches v7.4.0 [2ab3a3ac] LogExpFunctions v0.3.29 [1914dd2f] MacroTools v0.5.16 [e1d29d7a] Missings v1.2.0 [78c3b35d] Mocking v0.8.1 [0db19996] NBInclude v2.4.0 [d41bc354] NLSolversBase v7.10.0 [77ba4419] NaNMath v1.1.3 [b8a86587] NearestNeighbors v0.4.22 [429524aa] Optim v1.13.2 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.35 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.0 [08abe8d2] PrettyTables v3.0.11 [92933f4c] ProgressMeter v1.11.0 [43287f4e] PtrArrays v1.3.0 [438e738f] PyCall v1.96.4 [d330b81b] PyPlot v2.11.6 [1fd47b50] QuadGK v2.11.2 ⌅ [df47a6cb] RData v0.8.3 [ce6b1742] RDatasets v0.7.7 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 ⌅ [79098fc4] Rmath v0.7.1 [3646fa90] ScikitLearn v0.7.0 [6e75b9c4] ScikitLearnBase v0.5.0 [7e506255] ScopedValues v1.5.0 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays v1.4.8 [efcf1570] Setfield v1.1.2 [b85f4697] SoftGlobalScope v1.1.0 [a2af1166] SortingAlgorithms v1.2.2 [276daf66] SpecialFunctions v2.5.1 [90137ffa] StaticArrays v1.9.15 [1e83bf80] StaticArraysCore v1.4.3 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.1 ⌅ [2913bbd2] StatsBase v0.33.21 ⌅ [4c63d2b9] StatsFuns v0.9.18 [892a3eda] StringManipulation v0.4.1 [dc5dba14] TZJData v1.5.0+2025b [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [f269a46b] TimeZones v1.22.0 [3bb67fe8] TranscodingStreams v0.11.3 [3a884ed6] UnPack v1.0.2 [81def892] VersionParsing v1.3.0 [ea10d353] WeakRefStrings v1.4.2 [76eceee3] WorkerUtilities v1.6.1 ⌅ [68821587] Arpack_jll v3.5.1+1 [efe28fd5] OpenSpecFun_jll v0.5.6+0 ⌅ [f50d1b31] Rmath_jll v0.4.3+0 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0 [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.11.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.16.0+0 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.9.9 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.4+0 [efcefdf7] PCRE2_jll v10.46.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.13.1+0 [8e850ede] nghttp2_jll v1.67.1+0 [3f19e933] p7zip_jll v17.6.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... [ Info: Running `conda install -q -y -c anaconda conda` in root environment Channels: - anaconda - conda-forge Platform: linux-64 Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... done ## Package Plan ## environment location: /home/pkgeval/.julia/conda/3/x86_64 added / updated specs: - conda The following packages will be downloaded: package | build ---------------------------|----------------- ca-certificates-2025.9.9 | h06a4308_0 133 KB anaconda conda-25.9.0 | py312h06a4308_0 1.3 MB anaconda ------------------------------------------------------------ Total: 1.4 MB The following packages will be UPDATED: ca-certificates conda-forge/noarch::ca-certificates-2~ --> anaconda/linux-64::ca-certificates-2025.9.9-h06a4308_0 conda conda-forge::conda-25.3.1-py312h7900f~ --> anaconda::conda-25.9.0-py312h06a4308_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Running `conda install -q -y -c conda-forge libstdcxx-ngnothing` in root environment Error while loading conda entry point: conda-libmamba-solver (cannot import name 'Spinner' from 'conda.common.io' (/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/common/io.py)) CondaValueError: You have chosen a non-default solver backend (libmamba) but it was not recognized. Choose one of: classic [ Info: scikit-learn isn't properly installed.Please make sure PyCall is using the default Conda or non-conda local python. base: Error During Test at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:16 Got exception outside of a @test LoadError: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y -c conda-forge libstdcxx-ngnothing`,["JULIA_NUM_PRECOMPILE_TASKS=1", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "CI=true", "OPENBLAS_NUM_THREADS=1", "JULIA_PKGEVAL=true", "HOME=/home/pkgeval", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "JULIA_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "JULIA_CPU_THREADS=1", "DISPLAY=:1", "PYTHONIOENCODING=UTF-8", "PKGEVAL=true", "JULIA_LOAD_PATH=@:/tmp/jl_BVhb1C", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "LANG=C.UTF-8", "R_HOME=*"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:611 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:526 [3] run @ ./process.jl:523 [inlined] [4] runconda(args::Cmd, env::String) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:182 [5] add(pkg::String, env::String; channel::String, satisfied_skip_solve::Bool, args::Cmd) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:343 ┌ [6] add │ @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] ╰──── repeated 2 times [8] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:208 [9] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/test_base.jl:272 [10] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [11] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [13] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:17 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [15] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:17 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [17] top-level scope @ none:6 [18] eval(m::Module, e::Any) @ Core ./boot.jl:489 [19] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [20] _start() @ Base ./client.jl:577 in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/test_base.jl:12 [ Info: Running `conda install -q -y -c anaconda conda` in root environment Error while loading conda entry point: conda-libmamba-solver (cannot import name 'Spinner' from 'conda.common.io' (/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/common/io.py)) CondaValueError: You have chosen a non-default solver backend (libmamba) but it was not recognized. Choose one of: classic [ Info: scikit-learn isn't properly installed.Please make sure PyCall is using the default Conda or non-conda local python. pipeline: Error During Test at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:21 Got exception outside of a @test LoadError: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y -c anaconda conda`,["JULIA_NUM_PRECOMPILE_TASKS=1", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "CI=true", "OPENBLAS_NUM_THREADS=1", "JULIA_PKGEVAL=true", "HOME=/home/pkgeval", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "JULIA_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "JULIA_CPU_THREADS=1", "DISPLAY=:1", "PYTHONIOENCODING=UTF-8", "PKGEVAL=true", "JULIA_LOAD_PATH=@:/tmp/jl_BVhb1C", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "LANG=C.UTF-8", "R_HOME=*"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:611 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:526 [3] run @ ./process.jl:523 [inlined] [4] runconda(args::Cmd, env::String) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:182 [5] add(pkg::String, env::String; channel::String, satisfied_skip_solve::Bool, args::Cmd) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:343 ┌ [6] add │ @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] ╰──── repeated 2 times [8] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:207 [9] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/test_pipeline.jl:272 [10] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [11] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [13] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:22 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [15] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:22 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [17] top-level scope @ none:6 [18] eval(m::Module, e::Any) @ Core ./boot.jl:489 [19] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [20] _start() @ Base ./client.jl:577 in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/test_pipeline.jl:17 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 ┌ Warning: The least populated class in y has only 2 members, which is too few. The minimum number of labels for any class cannot be less than n_folds=3. └ @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/cross_validation.jl:144 [ Info: Running `conda install -q -y -c anaconda conda` in root environment Error while loading conda entry point: conda-libmamba-solver (cannot import name 'Spinner' from 'conda.common.io' (/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/common/io.py)) CondaValueError: You have chosen a non-default solver backend (libmamba) but it was not recognized. Choose one of: classic [ Info: scikit-learn isn't properly installed.Please make sure PyCall is using the default Conda or non-conda local python. quickstart: Error During Test at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:34 Got exception outside of a @test LoadError: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y -c anaconda conda`,["JULIA_NUM_PRECOMPILE_TASKS=1", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "CI=true", "OPENBLAS_NUM_THREADS=1", "JULIA_PKGEVAL=true", "HOME=/home/pkgeval", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "JULIA_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "JULIA_CPU_THREADS=1", "DISPLAY=:1", "PYTHONIOENCODING=UTF-8", "PKGEVAL=true", "JULIA_LOAD_PATH=@:/tmp/jl_BVhb1C", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "LANG=C.UTF-8", "R_HOME=*"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:611 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:526 [3] run @ ./process.jl:523 [inlined] [4] runconda(args::Cmd, env::String) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:182 [5] add(pkg::String, env::String; channel::String, satisfied_skip_solve::Bool, args::Cmd) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:343 ┌ [6] add │ @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] ╰──── repeated 2 times [8] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:207 [9] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/test_quickstart.jl:272 [10] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [11] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [13] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:35 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [15] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:35 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [17] top-level scope @ none:6 [18] eval(m::Module, e::Any) @ Core ./boot.jl:489 [19] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [20] _start() @ Base ./client.jl:577 in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/test_quickstart.jl:13 [ Info: Running `conda install -q -y -c anaconda conda` in root environment Error while loading conda entry point: conda-libmamba-solver (cannot import name 'Spinner' from 'conda.common.io' (/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/common/io.py)) CondaValueError: You have chosen a non-default solver backend (libmamba) but it was not recognized. Choose one of: classic [ Info: scikit-learn isn't properly installed.Please make sure PyCall is using the default Conda or non-conda local python. DataFrames: Error During Test at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:37 Got exception outside of a @test LoadError: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y -c anaconda conda`,["JULIA_NUM_PRECOMPILE_TASKS=1", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "CI=true", "OPENBLAS_NUM_THREADS=1", "JULIA_PKGEVAL=true", "HOME=/home/pkgeval", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "JULIA_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "JULIA_CPU_THREADS=1", "DISPLAY=:1", "PYTHONIOENCODING=UTF-8", "PKGEVAL=true", "JULIA_LOAD_PATH=@:/tmp/jl_BVhb1C", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "LANG=C.UTF-8", "R_HOME=*"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:611 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:526 [3] run @ ./process.jl:523 [inlined] [4] runconda(args::Cmd, env::String) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:182 [5] add(pkg::String, env::String; channel::String, satisfied_skip_solve::Bool, args::Cmd) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:343 ┌ [6] add │ @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] ╰──── repeated 2 times [8] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:207 [9] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/test_dataframes.jl:272 [10] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [11] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [12] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [13] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:38 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [15] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:38 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [17] top-level scope @ none:6 [18] eval(m::Module, e::Any) @ Core ./boot.jl:489 [19] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [20] _start() @ Base ./client.jl:577 in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/test_dataframes.jl:3 Testing ../examples/Classifier_Comparison.ipynb [ Info: Installing matplotlib via the Conda matplotlib package... [ Info: Running `conda install -q -y matplotlib` in root environment Error while loading conda entry point: conda-libmamba-solver (cannot import name 'Spinner' from 'conda.common.io' (/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/common/io.py)) CondaValueError: You have chosen a non-default solver backend (libmamba) but it was not recognized. Choose one of: classic Notebook examples: Error During Test at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:63 Got exception outside of a @test LoadError: InitError: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y matplotlib`,["JULIA_NUM_PRECOMPILE_TASKS=1", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_PKG_PRECOMPILE_AUTO=0", "CI=true", "OPENBLAS_NUM_THREADS=1", "JULIA_PKGEVAL=true", "HOME=/home/pkgeval", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "JULIA_NUM_THREADS=1", "OPENBLAS_MAIN_FREE=1", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "JULIA_CPU_THREADS=1", "DISPLAY=:1", "PYTHONIOENCODING=UTF-8", "PKGEVAL=true", "JULIA_LOAD_PATH=@:/tmp/jl_BVhb1C", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "LANG=C.UTF-8", "R_HOME=*"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:611 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:526 [3] run @ ./process.jl:523 [inlined] [4] runconda(args::Cmd, env::String) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:182 [5] add(pkg::String, env::String; channel::String, satisfied_skip_solve::Bool, args::Cmd) @ Conda ~/.julia/packages/Conda/zReqD/src/Conda.jl:343 ┌ [6] add │ @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] ╰──── repeated 2 times [8] pyimport_conda(modulename::String, condapkg::String, channel::String) @ PyCall ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:721 [9] pyimport_conda @ ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:715 [inlined] [10] __init__() @ PyPlot ~/.julia/packages/PyPlot/G422O/src/init.jl:174 [11] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1413 [12] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1401 [13] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}; register::Bool) @ Base ./loading.jl:1289 [14] _include_from_serialized @ ./loading.jl:1246 [inlined] [15] _require_search_from_serialized(pkg::Base.PkgId, sourcepath::String, build_id::UInt128, stalecheck::Bool; reasons::Dict{String, Int64}, DEPOT_PATH::Vector{String}) @ Base ./loading.jl:2101 [16] _require_search_from_serialized @ ./loading.jl:1995 [inlined] [17] __require_prelocked(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2645 [18] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2511 [19] macro expansion @ ./loading.jl:2439 [inlined] [20] macro expansion @ ./lock.jl:376 [inlined] [21] __require(into::Module, mod::Symbol) @ Base ./loading.jl:2403 [22] require @ ./loading.jl:2379 [inlined] [23] eval_import_path @ ./module.jl:36 [inlined] [24] eval_import_path_all(at::Module, path::Expr, keyword::String) @ Base ./module.jl:60 [25] _eval_using(to::Module, path::Expr) @ Base ./module.jl:137 [26] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/examples/Classifier_Comparison.ipynb:In[1]:9 [27] eval(m::Module, e::Any) @ Core ./boot.jl:489 [28] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String) @ Base ./loading.jl:2918 [29] include_string @ ./loading.jl:2928 [inlined] [30] my_include_string(m::Module, s::String, path::String, prev::String, softscope::Bool) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:30 [31] #3 @ ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:93 [inlined] [32] task_local_storage(body::NBInclude.var"#3#4"{Bool, Module, String, String, String, String}, key::Symbol, val::Bool) @ Base ./task.jl:298 [33] nbinclude(m::Module, path::String; renumber::Bool, counters::UnitRange{Int64}, regex::Regex, anshook::typeof(identity), softscope::Bool) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:92 [34] nbinclude(m::Module, path::String) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:57 [35] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:56 [36] eval(m::Module, e::Any) @ Core ./boot.jl:489 [37] (::var"#run_examples#run_examples##0"{Vector{String}})() @ Main ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:54 [38] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [40] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:64 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [42] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:64 [inlined] [43] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [44] top-level scope @ none:6 [45] eval(m::Module, e::Any) @ Core ./boot.jl:489 [46] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [47] _start() @ Base ./client.jl:577 during initialization of module PyPlot in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/examples/Classifier_Comparison.ipynb:In[1]:9 caused by: PyError (PyImport_ImportModule The Python package matplotlib could not be imported by pyimport. Usually this means that you did not install matplotlib in the Python version being used by PyCall. PyCall is currently configured to use the Julia-specific Python distribution installed by the Conda.jl package. To install the matplotlib module, you can use `pyimport_conda("matplotlib", PKG)`, where PKG is the Anaconda package that contains the module matplotlib, or alternatively you can use the Conda package directly (via `using Conda` followed by `Conda.add` etcetera). Alternatively, if you want to use a different Python distribution on your system, such as a system-wide Python (as opposed to the Julia-specific Python), you can re-configure PyCall with that Python. As explained in the PyCall documentation, set ENV["PYTHON"] to the path/name of the python executable you want to use, run Pkg.build("PyCall"), and re-launch Julia. ) ModuleNotFoundError("No module named 'matplotlib'") Stacktrace: [1] pyimport(name::String) @ PyCall ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:558 [2] pyimport_conda(modulename::String, condapkg::String, channel::String) @ PyCall ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:716 [3] pyimport_conda @ ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:715 [inlined] [4] __init__() @ PyPlot ~/.julia/packages/PyPlot/G422O/src/init.jl:174 [5] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1413 [6] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1401 [7] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}; register::Bool) @ Base ./loading.jl:1289 [8] _include_from_serialized @ ./loading.jl:1246 [inlined] [9] _require_search_from_serialized(pkg::Base.PkgId, sourcepath::String, build_id::UInt128, stalecheck::Bool; reasons::Dict{String, Int64}, DEPOT_PATH::Vector{String}) @ Base ./loading.jl:2101 [10] _require_search_from_serialized @ ./loading.jl:1995 [inlined] [11] __require_prelocked(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2645 [12] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2511 [13] macro expansion @ ./loading.jl:2439 [inlined] [14] macro expansion @ ./lock.jl:376 [inlined] [15] __require(into::Module, mod::Symbol) @ Base ./loading.jl:2403 [16] require @ ./loading.jl:2379 [inlined] [17] eval_import_path @ ./module.jl:36 [inlined] [18] eval_import_path_all(at::Module, path::Expr, keyword::String) @ Base ./module.jl:60 [19] _eval_using(to::Module, path::Expr) @ Base ./module.jl:137 [20] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/examples/Classifier_Comparison.ipynb:In[1]:9 [21] eval(m::Module, e::Any) @ Core ./boot.jl:489 [22] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String) @ Base ./loading.jl:2918 [23] include_string @ ./loading.jl:2928 [inlined] [24] my_include_string(m::Module, s::String, path::String, prev::String, softscope::Bool) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:30 [25] #3 @ ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:93 [inlined] [26] task_local_storage(body::NBInclude.var"#3#4"{Bool, Module, String, String, String, String}, key::Symbol, val::Bool) @ Base ./task.jl:298 [27] nbinclude(m::Module, path::String; renumber::Bool, counters::UnitRange{Int64}, regex::Regex, anshook::typeof(identity), softscope::Bool) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:92 [28] nbinclude(m::Module, path::String) @ NBInclude ~/.julia/packages/NBInclude/pfsyO/src/NBInclude.jl:57 [29] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:56 [30] eval(m::Module, e::Any) @ Core ./boot.jl:489 [31] (::var"#run_examples#run_examples##0"{Vector{String}})() @ Main ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:54 [32] top-level scope @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:12 [33] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [34] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:64 [inlined] [35] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1952 [inlined] [36] macro expansion @ ~/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:64 [inlined] [37] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:310 [38] top-level scope @ none:6 [39] eval(m::Module, e::Any) @ Core ./boot.jl:489 [40] exec_options(opts::Base.JLOptions) @ Base ./client.jl:310 [41] _start() @ Base ./client.jl:577 Test Summary: | Pass Error Total Time ScikitLearnTests | 57 5 62 4m38.0s models | 9 9 31.2s base | 1 1 26.3s pipeline | 1 1 0.6s crossvalidation | 38 38 14.3s utils | 10 10 0.8s quickstart | 1 1 2m38.3s DataFrames | 1 1 7.2s Notebook examples | 1 1 39.3s RNG of the outermost testset: Xoshiro(0x9987712cf5ed325d, 0x59e35d8803093d43, 0x441b12090d986a15, 0x79ff477c8e976c21, 0x51b3d85a2926f176) ERROR: LoadError: Some tests did not pass: 57 passed, 0 failed, 5 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/ScikitLearn/sqLdT/test/runtests.jl:10 Testing failed after 299.34s ERROR: LoadError: Package ScikitLearn errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2673 [3] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2522 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:538 [5] kwcall(::@NamedTuple{julia_args::Cmd, io::IOContext{IO}}, ::typeof(Pkg.API.test), ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:515 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:168 [7] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:157 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [9] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [inlined] [10] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkg::String) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:155 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:219 [12] include(mod::Module, _path::String) @ Base ./Base.jl:309 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [14] _start() @ Base ./client.jl:577 in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 PkgEval failed after 658.58s: package tests unexpectedly errored