Package evaluation to test CherenkovDeconvolution on Julia 1.10.10 (c8be17dcfd*) started at 2026-02-02T22:24:53.405 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.10` Set-up completed after 5.3s ################################################################################ # Installation # Installing CherenkovDeconvolution... Resolving package versions... Installed Conda ── v1.10.3 Installed PyCall ─ v1.94.1 Updating `~/.julia/environments/v1.10/Project.toml` [7995dc16] + CherenkovDeconvolution v0.3.0 Updating `~/.julia/environments/v1.10/Manifest.toml` [47edcb42] + ADTypes v1.21.0 [79e6a3ab] + Adapt v4.4.0 [4fba245c] + ArrayInterface v7.22.0 [7995dc16] + CherenkovDeconvolution v0.3.0 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [8f4d0f93] + Conda v1.10.3 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.1 ⌅ [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.16 [6e83dbb3] + Discretizers v3.2.4 [ffbed154] + DocStringExtensions v0.9.5 [4e289a0a] + EnumX v1.0.6 [1a297f60] + FillArrays v1.16.0 [6a86dc24] + FiniteDiff v2.29.0 [f6369f11] + ForwardDiff v1.3.2 [842dd82b] + InlineStrings v1.4.5 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.4.0 [b964fa9f] + LaTeXStrings v1.4.0 ⌃ [d3d80556] + LineSearches v7.5.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.16 [e1d29d7a] + Missings v1.2.0 [d8a4904e] + MutableArithmetics v1.6.7 ⌅ [d41bc354] + NLSolversBase v7.10.0 [77ba4419] + NaNMath v1.1.3 ⌅ [429524aa] + Optim v1.13.3 [bac558e1] + OrderedCollections v1.8.1 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 ⌅ [f27b6e38] + Polynomials v3.1.8 [2dfb63ee] + PooledArrays v1.4.3 [85a6dd25] + PositiveFactorizations v0.2.4 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.5.1 [08abe8d2] + PrettyTables v3.1.2 ⌅ [438e738f] + PyCall v1.94.1 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 ⌅ [3646fa90] + ScikitLearn v0.6.6 [6e75b9c4] + ScikitLearnBase v0.5.0 [91c51154] + SentinelArrays v1.4.9 [efcf1570] + Setfield v1.1.2 [a2af1166] + SortingAlgorithms v1.2.2 [276daf66] + SpecialFunctions v2.6.1 [1e83bf80] + StaticArraysCore v1.4.4 [82ae8749] + StatsAPI v1.8.0 ⌅ [2913bbd2] + StatsBase v0.33.21 [892a3eda] + StringManipulation v0.4.2 [ec057cc2] + StructUtils v2.6.2 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3a884ed6] + UnPack v1.0.2 [81def892] + VersionParsing v1.3.0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [0dad84c5] + ArgTools v1.1.1 [56f22d72] + Artifacts [2a0f44e3] + Base64 [ade2ca70] + Dates [8ba89e20] + Distributed [f43a241f] + Downloads v1.6.0 [7b1f6079] + FileWatching [9fa8497b] + Future [b77e0a4c] + InteractiveUtils [b27032c2] + LibCURL v0.6.4 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [ca575930] + NetworkOptions v1.2.0 [de0858da] + Printf [3fa0cd96] + REPL [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.1010+0 [14a3606d] + MozillaCACerts_jll v2025.12.2 [4536629a] + OpenBLAS_jll v0.3.23+5 [05823500] + OpenLibm_jll v0.8.5+0 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 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/8f06b0cfa4c514c7b9546756dbae91fcfbc92dc9/build.log` Building PyCall → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/53b8b07b721b77144a0fbbbc2675222ebf40a02d/build.log` Installation completed after 71.86s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 5195.4 ms ✓ Polynomials 1168.9 ms ✓ Conda 8482.4 ms ✓ PyCall 70986.9 ms ✓ ScikitLearn 97536.9 ms ✓ CherenkovDeconvolution 5 dependencies successfully precompiled in 187 seconds. 96 already precompiled. 1 dependency had output during precompilation: ┌ CherenkovDeconvolution │ WARNING: method definition for decode_estimate at /home/pkgeval/.julia/packages/CherenkovDeconvolution/Mui86/src/Methods.jl:319 declares type variable I but does not use it. │ WARNING: method definition for decode_estimate at /home/pkgeval/.julia/packages/CherenkovDeconvolution/Mui86/src/Methods.jl:323 declares type variable I but does not use it. └ Precompilation completed after 197.54s ################################################################################ # Testing # Testing CherenkovDeconvolution Status `/tmp/jl_3O4iX6/Project.toml` [7995dc16] CherenkovDeconvolution v0.3.0 [a93c6f00] DataFrames v1.8.1 [6e83dbb3] Discretizers v3.2.4 [b4f34e82] Distances v0.10.12 [cc2ba9b6] MLDataUtils v0.5.4 [0db19996] NBInclude v2.4.0 ⌅ [429524aa] Optim v1.13.3 ⌅ [f27b6e38] Polynomials v3.1.8 ⌅ [438e738f] PyCall v1.94.1 ⌅ [3646fa90] ScikitLearn v0.6.6 [6e75b9c4] ScikitLearnBase v0.5.0 ⌅ [2913bbd2] StatsBase v0.33.21 [ddb6d928] YAML v0.4.16 [37e2e46d] LinearAlgebra [9a3f8284] Random [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_3O4iX6/Manifest.toml` [47edcb42] ADTypes v1.21.0 [79e6a3ab] Adapt v4.4.0 [4fba245c] ArrayInterface v7.22.0 [7995dc16] CherenkovDeconvolution v0.3.0 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [8f4d0f93] Conda v1.10.3 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.1 ⌅ [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [8bb1440f] DelimitedFiles v1.9.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.16 [6e83dbb3] Discretizers v3.2.4 [b4f34e82] Distances v0.10.12 [ffbed154] DocStringExtensions v0.9.5 [4e289a0a] EnumX v1.0.6 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.29.0 [f6369f11] ForwardDiff v1.3.2 [842dd82b] InlineStrings v1.4.5 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v1.4.0 [b964fa9f] LaTeXStrings v1.4.0 ⌅ [7f8f8fb0] LearnBase v0.3.0 ⌃ [d3d80556] LineSearches v7.5.1 [2ab3a3ac] LogExpFunctions v0.3.29 ⌃ [9920b226] MLDataPattern v0.5.4 [cc2ba9b6] MLDataUtils v0.5.4 [66a33bbf] MLLabelUtils v0.5.7 [1914dd2f] MacroTools v0.5.16 [dbb5928d] MappedArrays v0.4.3 [e1d29d7a] Missings v1.2.0 [d8a4904e] MutableArithmetics v1.6.7 [0db19996] NBInclude v2.4.0 ⌅ [d41bc354] NLSolversBase v7.10.0 [77ba4419] NaNMath v1.1.3 ⌅ [429524aa] Optim v1.13.3 [bac558e1] OrderedCollections v1.8.1 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 ⌅ [f27b6e38] Polynomials v3.1.8 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 ⌅ [aea7be01] PrecompileTools v1.2.1 [21216c6a] Preferences v1.5.1 [08abe8d2] PrettyTables v3.1.2 ⌅ [438e738f] PyCall v1.94.1 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 ⌅ [3646fa90] ScikitLearn v0.6.6 [6e75b9c4] ScikitLearnBase v0.5.0 [91c51154] SentinelArrays v1.4.9 [efcf1570] Setfield v1.1.2 [b85f4697] SoftGlobalScope v1.1.0 [a2af1166] SortingAlgorithms v1.2.2 [276daf66] SpecialFunctions v2.6.1 [1e83bf80] StaticArraysCore v1.4.4 [82ae8749] StatsAPI v1.8.0 ⌅ [2913bbd2] StatsBase v0.33.21 [69024149] StringEncodings v0.3.7 [892a3eda] StringManipulation v0.4.2 [ec057cc2] StructUtils v2.6.2 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3a884ed6] UnPack v1.0.2 [81def892] VersionParsing v1.3.0 [ddb6d928] YAML v0.4.16 [94ce4f54] Libiconv_jll v1.18.0+0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [0dad84c5] ArgTools v1.1.1 [56f22d72] Artifacts [2a0f44e3] Base64 [ade2ca70] Dates [8ba89e20] Distributed [f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching [9fa8497b] Future [b77e0a4c] InteractiveUtils [b27032c2] LibCURL v0.6.4 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [a63ad114] Mmap [ca575930] NetworkOptions v1.2.0 [de0858da] Printf [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [fa267f1f] TOML v1.0.3 [8dfed614] Test [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.4.0+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.1010+0 [14a3606d] MozillaCACerts_jll v2025.12.2 [4536629a] OpenBLAS_jll v0.3.23+5 [05823500] OpenLibm_jll v0.8.5+0 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.52.0+1 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 ---------------------------|----------------- conda-26.1.0 | py312h06a4308_0 1.3 MB anaconda ------------------------------------------------------------ Total: 1.3 MB The following packages will be UPDATED: conda conda-forge::conda-25.11.0-py312h7900~ --> anaconda::conda-26.1.0-py312h06a4308_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Running `conda install -q -y -c conda-forge 'libstdcxx-ng>=3.4,<13.0'` in root environment Channels: - 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: - libstdcxx-ng[version='>=3.4,<13.0'] The following packages will be downloaded: package | build ---------------------------|----------------- libgcc-15.2.0 | h767d61c_6 804 KB conda-forge libgcc-ng-15.2.0 | h69a702a_6 29 KB conda-forge libgomp-15.2.0 | h767d61c_6 438 KB conda-forge libstdcxx-15.2.0 | h8f9b012_6 3.7 MB conda-forge libstdcxx-ng-12.3.0 | hc0a3c3a_7 3.3 MB conda-forge ------------------------------------------------------------ Total: 8.3 MB The following packages will be DOWNGRADED: libstdcxx-ng 15.2.0-hdf11a46_15 --> 12.3.0-hc0a3c3a_7 The following packages will be REVISED: libgcc 15.2.0-he0feb66_15 --> 15.2.0-h767d61c_6 libgcc-ng 15.2.0-h69a702a_15 --> 15.2.0-h69a702a_6 libgomp 15.2.0-he0feb66_15 --> 15.2.0-h767d61c_6 libstdcxx 15.2.0-h934c35e_15 --> 15.2.0-h8f9b012_6 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done [ Info: Installing sklearn via the Conda scikit-learn package... [ Info: Running `conda install -q -y scikit-learn` in root environment Channels: - 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: - scikit-learn The following packages will be downloaded: package | build ---------------------------|----------------- joblib-1.5.3 | pyhd8ed1ab_0 221 KB conda-forge scikit-learn-1.8.0 |np2py312h3226591_1 9.3 MB conda-forge scipy-1.17.0 | py312h54fa4ab_1 16.1 MB conda-forge threadpoolctl-3.6.0 | pyhecae5ae_0 23 KB conda-forge ------------------------------------------------------------ Total: 25.6 MB The following NEW packages will be INSTALLED: joblib conda-forge/noarch::joblib-1.5.3-pyhd8ed1ab_0 scikit-learn conda-forge/linux-64::scikit-learn-1.8.0-np2py312h3226591_1 scipy conda-forge/linux-64::scipy-1.17.0-py312h54fa4ab_1 threadpoolctl conda-forge/noarch::threadpoolctl-3.6.0-pyhecae5ae_0 Preparing transaction: ...working... done Verifying transaction: ...working... done Executing transaction: ...working... done ERROR: LoadError: InitError: 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. ) ImportError("/opt/julia/bin/../lib/julia/libstdc++.so.6: version `CXXABI_1.3.15' not found (required by /home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/spatial/_distance_pybind.cpython-312-x86_64-linux-gnu.so)") File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/__init__.py", line 70, in from sklearn.base import clone # noqa: E402 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/base.py", line 19, in from sklearn.utils._metadata_requests import _MetadataRequester, _routing_enabled File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/__init__.py", line 9, in from sklearn.utils._chunking import gen_batches, gen_even_slices File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/_chunking.py", line 11, in from sklearn.utils._param_validation import Interval, validate_params File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/_param_validation.py", line 17, in from sklearn.utils.validation import _is_arraylike_not_scalar File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/validation.py", line 24, in from sklearn.utils._array_api import ( File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/_array_api.py", line 20, in from sklearn.utils.fixes import parse_version File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/sklearn/utils/fixes.py", line 16, in import scipy.stats File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/stats/__init__.py", line 628, in from ._stats_py import * File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/stats/_stats_py.py", line 40, in from scipy.spatial import distance_matrix File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/spatial/__init__.py", line 117, in from ._geometric_slerp import geometric_slerp File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/spatial/_geometric_slerp.py", line 7, in from scipy.spatial.distance import euclidean File "/home/pkgeval/.julia/conda/3/x86_64/lib/python3.12/site-packages/scipy/spatial/distance.py", line 117, in from . import _hausdorff, _distance_pybind, _distance_wrap Stacktrace: [1] pyimport(name::String) @ PyCall ~/.julia/packages/PyCall/ygXW2/src/PyCall.jl:558 [2] pyimport_conda(modulename::String, condapkg::String, channel::String) @ PyCall ~/.julia/packages/PyCall/ygXW2/src/PyCall.jl:722 [3] pyimport_conda @ ~/.julia/packages/PyCall/ygXW2/src/PyCall.jl:715 [inlined] [4] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/Wvn7B/src/Skcore.jl:215 [5] __init__() @ CherenkovDeconvolution.Binnings ~/.julia/packages/CherenkovDeconvolution/Mui86/src/Binnings.jl:43 [6] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1196 [7] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1184 [8] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}) @ Base ./loading.jl:1129 [9] _require_search_from_serialized(pkg::Base.PkgId, sourcepath::String, build_id::UInt128) @ Base ./loading.jl:1654 [10] _require(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2011 [11] __require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:1885 [12] #invoke_in_world#3 @ ./essentials.jl:926 [inlined] [13] invoke_in_world @ ./essentials.jl:923 [inlined] [14] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:1876 [15] macro expansion @ ./loading.jl:1863 [inlined] [16] macro expansion @ ./lock.jl:270 [inlined] [17] __require(into::Module, mod::Symbol) @ Base ./loading.jl:1826 [18] #invoke_in_world#3 @ ./essentials.jl:926 [inlined] [19] invoke_in_world @ ./essentials.jl:923 [inlined] [20] require(into::Module, mod::Symbol) @ Base ./loading.jl:1819 [21] include(fname::String) @ Base.MainInclude ./client.jl:487 [22] top-level scope @ none:6 during initialization of module Binnings in expression starting at /home/pkgeval/.julia/packages/CherenkovDeconvolution/Mui86/test/runtests.jl:1 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/ygXW2/src/PyCall.jl:558 [2] pyimport_conda(modulename::String, condapkg::String, channel::String) @ PyCall ~/.julia/packages/PyCall/ygXW2/src/PyCall.jl:716 [3] pyimport_conda @ ~/.julia/packages/PyCall/ygXW2/src/PyCall.jl:715 [inlined] [4] import_sklearn() @ ScikitLearn.Skcore ~/.julia/packages/ScikitLearn/Wvn7B/src/Skcore.jl:215 [5] __init__() @ CherenkovDeconvolution.Binnings ~/.julia/packages/CherenkovDeconvolution/Mui86/src/Binnings.jl:43 [6] run_module_init(mod::Module, i::Int64) @ Base ./loading.jl:1196 [7] register_restored_modules(sv::Core.SimpleVector, pkg::Base.PkgId, path::String) @ Base ./loading.jl:1184 [8] _include_from_serialized(pkg::Base.PkgId, path::String, ocachepath::Nothing, depmods::Vector{Any}) @ Base ./loading.jl:1129 [9] _require_search_from_serialized(pkg::Base.PkgId, sourcepath::String, build_id::UInt128) @ Base ./loading.jl:1654 [10] _require(pkg::Base.PkgId, env::String) @ Base ./loading.jl:2011 [11] __require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:1885 [12] #invoke_in_world#3 @ ./essentials.jl:926 [inlined] [13] invoke_in_world @ ./essentials.jl:923 [inlined] [14] _require_prelocked(uuidkey::Base.PkgId, env::String) @ Base ./loading.jl:1876 [15] macro expansion @ ./loading.jl:1863 [inlined] [16] macro expansion @ ./lock.jl:270 [inlined] [17] __require(into::Module, mod::Symbol) @ Base ./loading.jl:1826 [18] #invoke_in_world#3 @ ./essentials.jl:926 [inlined] [19] invoke_in_world @ ./essentials.jl:923 [inlined] [20] require(into::Module, mod::Symbol) @ Base ./loading.jl:1819 [21] include(fname::String) @ Base.MainInclude ./client.jl:487 [22] top-level scope @ none:6 Testing failed after 98.19s ERROR: LoadError: Package CherenkovDeconvolution errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.10/Pkg/src/Types.jl:70 [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/v1.10/Pkg/src/Operations.jl:2034 [3] test @ /opt/julia/share/julia/stdlib/v1.10/Pkg/src/Operations.jl:1915 [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::Base.PipeEndpoint}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.10/Pkg/src/API.jl:444 [5] test(pkgs::Vector{Pkg.Types.PackageSpec}; io::Base.PipeEndpoint, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.10/Pkg/src/API.jl:159 [6] test @ /opt/julia/share/julia/stdlib/v1.10/Pkg/src/API.jl:147 [inlined] [7] #test#74 @ /opt/julia/share/julia/stdlib/v1.10/Pkg/src/API.jl:146 [inlined] [8] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:223 in expression starting at /PkgEval.jl/scripts/evaluate.jl:214 PkgEval failed after 401.17s: package tests unexpectedly errored