Package evaluation of BiochemNetABC on Julia 1.11.4 (a71dd056e0*) started at 2025-04-08T23:22:23.825 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.38s ################################################################################ # Installation # Installing BiochemNetABC... Resolving package versions... Installed Conda ── v1.10.2 Installed PyCall ─ v1.96.4 Updating `~/.julia/environments/v1.11/Project.toml` [eb87d800] + BiochemNetABC v0.1.0 Updating `~/.julia/environments/v1.11/Manifest.toml` [9d0fb3db] + ARFIMA v0.4.0 [1520ce14] + AbstractTrees v0.4.5 [66dad0bd] + AliasTables v1.1.3 [eb87d800] + BiochemNetABC v0.1.0 [d1d4a3ce] + BitFlags v0.1.9 [944b1d66] + CodecZlib v0.7.8 [35d6a980] + ColorSchemes v3.29.0 [3da002f7] + ColorTypes v0.12.1 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.0 [34da2185] + Compat v4.16.0 [f0e56b4a] + ConcurrentUtilities v2.5.0 [8f4d0f93] + Conda v1.10.2 [d38c429a] + Contour v0.6.3 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.7.0 [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [7806a523] + DecisionTree v0.12.4 [8bb1440f] + DelimitedFiles v1.9.1 [b4f34e82] + Distances v0.10.12 [aaf54ef3] + DistributedArrays v0.6.7 [31c24e10] + Distributions v0.25.118 [ffbed154] + 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OpenSSL v1.4.3 [bac558e1] + OrderedCollections v1.8.0 [90014a1f] + PDMats v0.11.33 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.1 [ccf2f8ad] + PlotThemes v3.3.0 [995b91a9] + PlotUtils v1.4.3 [91a5bcdd] + Plots v1.40.11 [2dfb63ee] + PooledArrays v1.4.3 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [08abe8d2] + PrettyTables v2.4.0 [27ebfcd6] + Primes v0.5.7 [43287f4e] + PtrArrays v1.3.0 [438e738f] + PyCall v1.96.4 [d330b81b] + PyPlot v2.11.6 [1fd47b50] + QuadGK v2.11.2 [3cdcf5f2] + RecipesBase v1.3.4 [01d81517] + RecipesPipeline v0.6.12 [189a3867] + Reexport v1.2.2 [05181044] + RelocatableFolders v1.0.1 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [3646fa90] + ScikitLearn v0.7.0 [6e75b9c4] + ScikitLearnBase v0.5.0 [6c6a2e73] + Scratch v1.2.1 [91c51154] + SentinelArrays v1.4.8 [992d4aef] + Showoff v1.0.3 [777ac1f9] + SimpleBufferStream v1.2.0 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.0 [860ef19b] + StableRNGs 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[b77e0a4c] + InteractiveUtils v1.11.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.11.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.2.0 [44cfe95a] + Pkg v1.11.0 [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 [1a1011a3] + SharedArrays v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.11.0 [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 v1.1.1+0 [deac9b47] + LibCURL_jll v8.6.0+0 [e37daf67] + LibGit2_jll v1.7.2+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.6+0 [14a3606d] + MozillaCACerts_jll v2023.12.12 [4536629a] + OpenBLAS_jll v0.3.27+1 [05823500] + OpenLibm_jll v0.8.5+0 [efcefdf7] + PCRE2_jll v10.42.0+1 [bea87d4a] + SuiteSparse_jll v7.7.0+0 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.59.0+0 [3f19e933] + p7zip_jll v17.4.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints 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 70.59s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 145.73s ################################################################################ # Testing # Testing BiochemNetABC Status `/tmp/jl_K47NL6/Project.toml` [9d0fb3db] ARFIMA v0.4.0 [eb87d800] BiochemNetABC v0.1.0 [31c24e10] Distributions v0.25.118 [069b7b12] FunctionWrappers v1.1.3 [91a5bcdd] Plots v1.40.11 [1fd47b50] QuadGK v2.11.2 [3646fa90] ScikitLearn v0.7.0 [276daf66] SpecialFunctions v2.5.0 [90137ffa] StaticArrays v1.9.13 ⌅ [2913bbd2] StatsBase v0.33.21 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.11.0 [56ddb016] Logging v1.11.0 [9a3f8284] Random v1.11.0 [1a1011a3] SharedArrays v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_K47NL6/Manifest.toml` [9d0fb3db] ARFIMA v0.4.0 [1520ce14] AbstractTrees v0.4.5 [66dad0bd] AliasTables v1.1.3 [eb87d800] BiochemNetABC v0.1.0 [d1d4a3ce] BitFlags v0.1.9 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.29.0 [3da002f7] ColorTypes v0.12.1 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.0 [34da2185] Compat v4.16.0 [f0e56b4a] ConcurrentUtilities v2.5.0 [8f4d0f93] Conda v1.10.2 [d38c429a] Contour v0.6.3 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.7.0 [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [7806a523] DecisionTree v0.12.4 [8bb1440f] DelimitedFiles v1.9.1 [b4f34e82] Distances v0.10.12 [aaf54ef3] DistributedArrays v0.6.7 [31c24e10] Distributions v0.25.118 [ffbed154] DocStringExtensions v0.9.4 [460bff9d] ExceptionUnwrapping v0.1.11 [c87230d0] FFMPEG v0.4.2 [1a297f60] FillArrays v1.13.0 [53c48c17] FixedPointNumbers v0.8.5 [1fa38f19] Format v1.3.7 [069b7b12] FunctionWrappers v1.1.3 [28b8d3ca] GR v0.73.13 [42e2da0e] Grisu v1.0.2 [cd3eb016] HTTP v1.10.15 [34004b35] HypergeometricFunctions v0.3.28 [842dd82b] InlineStrings v1.4.3 [18e54dd8] IntegerMathUtils v0.1.2 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [1019f520] JLFzf v0.1.10 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [b964fa9f] LaTeXStrings v1.4.0 [23fbe1c1] Latexify v0.16.7 [2ab3a3ac] LogExpFunctions v0.3.29 [e6f89c97] LoggingExtras v1.1.0 [1914dd2f] MacroTools v0.5.15 [739be429] MbedTLS v1.1.9 [442fdcdd] Measures v0.3.2 [e1d29d7a] Missings v1.2.0 [77ba4419] NaNMath v1.1.3 [b8a86587] NearestNeighbors v0.4.21 [4d8831e6] OpenSSL v1.4.3 [bac558e1] OrderedCollections v1.8.0 [90014a1f] PDMats v0.11.33 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.1 [ccf2f8ad] PlotThemes v3.3.0 [995b91a9] PlotUtils v1.4.3 [91a5bcdd] Plots v1.40.11 [2dfb63ee] PooledArrays v1.4.3 ⌅ [aea7be01] PrecompileTools v1.2.1 [21216c6a] Preferences v1.4.3 [08abe8d2] PrettyTables v2.4.0 [27ebfcd6] Primes v0.5.7 [43287f4e] PtrArrays v1.3.0 [438e738f] PyCall v1.96.4 [d330b81b] PyPlot v2.11.6 [1fd47b50] QuadGK v2.11.2 [3cdcf5f2] RecipesBase v1.3.4 [01d81517] RecipesPipeline v0.6.12 [189a3867] Reexport v1.2.2 [05181044] RelocatableFolders v1.0.1 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[f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.11.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.2.0 [44cfe95a] Pkg v1.11.0 [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 [1a1011a3] SharedArrays v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.11.0 [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 v1.1.1+0 [deac9b47] LibCURL_jll v8.6.0+0 [e37daf67] LibGit2_jll v1.7.2+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.6+0 [14a3606d] MozillaCACerts_jll v2023.12.12 [4536629a] OpenBLAS_jll v0.3.27+1 [05823500] OpenLibm_jll v0.8.5+0 [efcefdf7] PCRE2_jll v10.42.0+1 [bea87d4a] SuiteSparse_jll v7.7.0+0 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.59.0+0 [3f19e933] p7zip_jll v17.4.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints 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-2025.2.25 | h06a4308_0 136 KB anaconda certifi-2025.1.31 | py312h06a4308_0 164 KB anaconda conda-24.11.3 | py312h06a4308_0 1.2 MB anaconda ------------------------------------------------------------ Total: 1.4 MB The following packages will be UPDATED: ca-certificates conda-forge::ca-certificates-2025.1.3~ --> anaconda::ca-certificates-2025.2.25-h06a4308_0 The following packages will be SUPERSEDED by a higher-priority channel: certifi conda-forge/noarch::certifi-2025.1.31~ --> anaconda/linux-64::certifi-2025.1.31-py312h06a4308_0 conda conda-forge::conda-24.11.3-py312h7900~ --> anaconda::conda-24.11.3-py312h06a4308_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Running `conda install -q -y -c conda-forge 'libstdcxx-ng>=3.4,<13.0'` in root environment Channels: - conda-forge - anaconda 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: - libstdcxx-ng[version='>=3.4,<13.0'] The following packages will be downloaded: package | build ---------------------------|----------------- libstdcxx-ng-12.3.0 | hc0a3c3a_7 3.3 MB conda-forge ------------------------------------------------------------ Total: 3.3 MB The following packages will be SUPERSEDED by a higher-priority channel: certifi anaconda/linux-64::certifi-2025.1.31-~ --> conda-forge/noarch::certifi-2025.1.31-pyhd8ed1ab_0 The following packages will be DOWNGRADED: libstdcxx-ng 14.2.0-h4852527_2 --> 12.3.0-hc0a3c3a_7 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Installing sklearn via the Conda scikit-learn>=1.2,<1.3 package... [ Info: Running `conda config --add channels conda-forge --file /home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml --force` in root environment /home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/conda/base/context.py:201: FutureWarning: Adding 'defaults' to channel list implicitly is deprecated and will be removed in 25.3. To remove this warning, please choose a default channel explicitly with conda's regular configuration system, e.g. by adding 'defaults' to the list of channels: conda config --add channels defaults For more information see https://docs.conda.io/projects/conda/en/stable/user-guide/configuration/use-condarc.html deprecated.topic( [ Info: Running `conda install -q -y 'scikit-learn>=1.2,<1.3'` in root environment Channels: - conda-forge - defaults - anaconda Platform: linux-64 Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... warning libmamba Added empty dependency for problem type SOLVER_RULE_UPDATE failed LibMambaUnsatisfiableError: Encountered problems while solving: - package scikit-learn-1.2.0-py310h209a8ca_0 requires python >=3.10,<3.11.0a0, but none of the providers can be installed Could not solve for environment specs The following packages are incompatible ├─ pin-1 is installable and it requires │ └─ python 3.12.* , which can be installed; └─ scikit-learn >=1.2,<1.3 is not installable because there are no viable options ├─ scikit-learn [1.2.0|1.2.1|1.2.2] would require │ └─ python >=3.10,<3.11.0a0 , which conflicts with any installable versions previously reported; ├─ scikit-learn [1.2.0|1.2.1|1.2.2] would require │ └─ python >=3.11,<3.12.0a0 , which conflicts with any installable versions previously reported; ├─ scikit-learn [1.2.0|1.2.1|1.2.2] would require │ └─ python >=3.8,<3.9.0a0 , which conflicts with any installable versions previously reported; └─ scikit-learn [1.2.0|1.2.1|1.2.2] would require └─ python >=3.9,<3.10.0a0 , which conflicts with any installable versions previously reported. Pins seem to be involved in the conflict. Currently pinned specs: - python 3.12.* (labeled as 'pin-1') ERROR: LoadError: InitError: UndefVarError: `CONDA` not defined in `ScikitLearn.Skcore` Stacktrace: [1] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:225 [2] __init__() @ BiochemNetABC ~/.julia/packages/BiochemNetABC/Ip6oi/src/BiochemNetABC.jl:36 [3] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1378 [4] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1366 [5] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}, ignore_native::Nothing; register::Bool) @ Base ./loading.jl:1254 [6] _include_from_serialized (repeats 2 times) @ ./loading.jl:1210 [inlined] [7] _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:2057 [8] _require(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2527 [9] __require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2388 [10] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [11] invoke_in_world @ ./essentials.jl:1086 [inlined] [12] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2375 [13] macro expansion @ ./loading.jl:2314 [inlined] [14] macro expansion @ ./lock.jl:273 [inlined] [15] __require(into::Module, mod::Symbol) @ Base ./loading.jl:2271 [16] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [17] invoke_in_world @ ./essentials.jl:1086 [inlined] [18] require(into::Module, mod::Symbol) @ Base ./loading.jl:2260 [19] include(fname::String) @ Main ./sysimg.jl:38 [20] top-level scope @ none:6 during initialization of module BiochemNetABC in expression starting at /home/pkgeval/.julia/packages/BiochemNetABC/Ip6oi/test/runtests.jl:4 caused by: failed process: Process(setenv(`/home/pkgeval/.julia/conda/3/x86_64/bin/conda install -q -y 'scikit-learn>=1.2,<1.3'`,["PYTHONIOENCODING=UTF-8", "LANG=C.UTF-8", "PATH=/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/bin:/sbin", "OPENBLAS_MAIN_FREE=1", "CONDARC=/home/pkgeval/.julia/conda/3/x86_64/condarc-julia.yml", "CONDA_PREFIX=/home/pkgeval/.julia/conda/3/x86_64", "JULIA_CPU_THREADS=1", "JULIA_NUM_PRECOMPILE_TASKS=1", "DISPLAY=:1", "JULIA_LOAD_PATH=@:/tmp/jl_K47NL6", "PKGEVAL=true", "OPENBLAS_NUM_THREADS=1", "CI=true", "JULIA_PKG_PRECOMPILE_AUTO=0", "JULIA_PKGEVAL=true", "JULIA_DEPOT_PATH=/home/pkgeval/.julia:/usr/local/share/julia:", "JULIA_NUM_THREADS=1", "R_HOME=*", "HOME=/home/pkgeval"]), ProcessExited(1)) [1] Stacktrace: [1] pipeline_error @ ./process.jl:598 [inlined] [2] run(::Cmd; wait::Bool) @ Base ./process.jl:513 [3] run @ ./process.jl:510 [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 (repeats 2 times) @ ~/.julia/packages/Conda/zReqD/src/Conda.jl:326 [inlined] [7] pyimport_conda(modulename::String, condapkg::String, channel::String) @ PyCall ~/.julia/packages/PyCall/1gn3u/src/PyCall.jl:721 [8] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:219 [9] __init__() @ BiochemNetABC ~/.julia/packages/BiochemNetABC/Ip6oi/src/BiochemNetABC.jl:36 [10] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1378 [11] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1366 [12] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}, ignore_native::Nothing; register::Bool) @ Base ./loading.jl:1254 [13] _include_from_serialized (repeats 2 times) @ ./loading.jl:1210 [inlined] [14] _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:2057 [15] _require(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2527 [16] __require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2388 [17] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [18] invoke_in_world @ ./essentials.jl:1086 [inlined] [19] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2375 [20] macro expansion @ ./loading.jl:2314 [inlined] [21] macro expansion @ ./lock.jl:273 [inlined] [22] __require(into::Module, mod::Symbol) @ Base ./loading.jl:2271 [23] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [24] invoke_in_world @ ./essentials.jl:1086 [inlined] [25] require(into::Module, mod::Symbol) @ Base ./loading.jl:2260 [26] include(fname::String) @ Main ./sysimg.jl:38 [27] top-level scope @ none:6 caused by: PyError (PyImport_ImportModule The Python package sklearn could not be imported 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 Julia-specific Python distribution installed by the Conda.jl package. To install the sklearn module, you can use `pyimport_conda("sklearn", PKG)`, where PKG is the Anaconda package that contains the module sklearn, 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 'sklearn'") 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] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/sqLdT/src/Skcore.jl:219 [4] __init__() @ BiochemNetABC ~/.julia/packages/BiochemNetABC/Ip6oi/src/BiochemNetABC.jl:36 [5] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1378 [6] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1366 [7] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}, ignore_native::Nothing; register::Bool) @ Base ./loading.jl:1254 [8] _include_from_serialized (repeats 2 times) @ ./loading.jl:1210 [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:2057 [10] _require(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2527 [11] __require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2388 [12] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [13] invoke_in_world @ ./essentials.jl:1086 [inlined] [14] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:2375 [15] macro expansion @ ./loading.jl:2314 [inlined] [16] macro expansion @ ./lock.jl:273 [inlined] [17] __require(into::Module, mod::Symbol) @ Base ./loading.jl:2271 [18] #invoke_in_world#3 @ ./essentials.jl:1089 [inlined] [19] invoke_in_world @ ./essentials.jl:1086 [inlined] [20] require(into::Module, mod::Symbol) @ Base ./loading.jl:2260 [21] include(fname::String) @ Main ./sysimg.jl:38 [22] top-level scope @ none:6 Testing failed after 94.03s ERROR: LoadError: Package BiochemNetABC errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.11/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{Pkg.Types.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/v1.11/Pkg/src/Operations.jl:2124 [3] test @ /opt/julia/share/julia/stdlib/v1.11/Pkg/src/Operations.jl:2007 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{Pkg.Types.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/v1.11/Pkg/src/API.jl:481 [5] test(pkgs::Vector{Pkg.Types.PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.11/Pkg/src/API.jl:159 [6] test @ /opt/julia/share/julia/stdlib/v1.11/Pkg/src/API.jl:147 [inlined] [7] #test#74 @ /opt/julia/share/julia/stdlib/v1.11/Pkg/src/API.jl:146 [inlined] [8] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:219 in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 PkgEval failed after 349.58s: package tests unexpectedly errored