Why Atom try to reinstall Matplotlib using Conda so frequently?

It often happens that Atom tries to reinstall matplotlib using Conda. However, this is already installed and I don’t understand why it gets stuck on this. Below I copy the exact code and message that I get.

Note: this message is a little bit random. If for example I need to restart my Atom session, then often this message comes by. What I do to fix this is to close Atom and open it again, and often times the message goes away.

Could anyone provide some advice on how to fix this issue ? It is not critical, but certainly affects the user experience using Julia and Atom.


import Pkg

    Status `~/Documents/Julia/Project.toml`
  [336ed68f] CSV v0.5.23
  [8f4d0f93] Conda v1.3.0
  [a93c6f00] DataFrames v0.20.0
  [f67ccb44] HDF5 v0.12.5
  [4138dd39] JLD v0.9.2
  [a93385a2] JuliaDB v0.13.0
  [10e44e05] MATLAB v0.7.3
  [b8a86587] NearestNeighbors v0.4.4
  [30363a11] NetCDF v0.8.2
  [f27b6e38] Polynomials v0.6.0
  [438e738f] PyCall v1.91.2
  [d330b81b] PyPlot v2.8.2
  [295af30f] Revise v2.5.0
  [f2b01f46] Roots v0.8.4
  [bd369af6] Tables v0.2.11
  [64499a7a] WriteVTK v1.4.0

using PyPlot

[ Info: Installing matplotlib via the Conda matplotlib package...
[ Info: Running `conda install -y matplotlib` in root environment
Collecting package metadata (current_repodata.json): done
Solving environment: done

# All requested packages already installed.

ERROR: LoadError: InitError: PyCall.PyError("PyImport_ImportModule\n\nThe Python package matplotlib could not be found by pyimport. Usually this means\nthat you did not install matplotlib in the Python version being used by PyCall.\n\nPyCall is currently configured to use the Julia-specific Python distribution\ninstalled by the Conda.jl package.  To install the matplotlib module, you can\nuse `pyimport_conda(\"matplotlib\", PKG)`, where PKG is the Anaconda\npackage the contains the module matplotlib, or alternatively you can use the\nConda package directly (via `using Conda` followed by `Conda.add` etcetera).\n\nAlternatively, if you want to use a different Python distribution on your\nsystem, such as a system-wide Python (as opposed to the Julia-specific Python),\nyou can re-configure PyCall with that Python.   As explained in the PyCall\ndocumentation, set ENV[\"PYTHON\"] to the path/name of the python executable\nyou want to use, run Pkg.build(\"PyCall\"), and re-launch Julia.\n\n", PyCall.PyObject(Ptr{PyCall.PyObject_struct} @0x000000013311ef40), PyCall.PyObject(Ptr{PyCall.PyObject_struct} @0x0000000133b554a8), PyCall.PyObject(Ptr{PyCall.PyObject_struct} @0x00000001333c2b08))
 [1] pyimport(::String) at /Users/josimar/.julia/packages/PyCall/ttONZ/src/PyCall.jl:544
 [2] pyimport_conda(::String, ::String, ::String) at /Users/josimar/.julia/packages/PyCall/ttONZ/src/PyCall.jl:708
 [3] pyimport_conda at /Users/josimar/.julia/packages/PyCall/ttONZ/src/PyCall.jl:701 [inlined]
 [4] __init__() at /Users/josimar/.julia/packages/PyPlot/4wzW1/src/init.jl:179
 [5] _include_from_serialized(::String, ::Array{Any,1}) at ./loading.jl:692
 [6] _require_search_from_serialized(::Base.PkgId, ::String) at ./loading.jl:776
 [7] _require(::Base.PkgId) at ./loading.jl:1001
 [8] require(::Base.PkgId) at ./loading.jl:922
 [9] require(::Module, ::Symbol) at ./loading.jl:917
during initialization of module PyPlot