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jupyterhub docker image with DIVAnd pre-installed

License: GNU General Public License v2.0

Dockerfile 39.81% Shell 38.90% Julia 21.29%

divand-jupyterhub's People

Contributors

alexander-barth avatar ctroupin avatar marie59 avatar

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Forkers

kha9-irfa9 marie59 anuprulez

divand-jupyterhub's Issues

Run docker image

I am trying to run the docker image after building it to use it in a jupytherhub locally. And when I launch the run command I get this message:
Customizing authentication via ServerApp.login_handler_class=<class 'jupyterhub.singleuser.mixins.make_singleuser_app.<locals>.JupyterHubLoginHandler'> is deprecated in Jupyter Server 2.0. Use ServerApp.identity_provider_class. Falling back on legacy authentication. JUPYTERHUB_API_TOKEN env is required to run jupyterhub-singleuser. Did you launch it manually?
Maybe it's coming from the jupyterhub/singleuser:3.1 image and we could use a different one ?

Problem with contourpy package

Hi @Alexander-Barth and @ctroupin,
It's me again, I got the tool running on a local galaxy and now I'm trying to run the entire notebook "90-full-analysis.ipynb" to be sure that everything is in order and to finalize the docker image (still some small modifications to be made after some testing).
At the step "2.1 Choice of bathymetry" when I try to run the figure just below I get the following error :

`PyError ($(Expr(:escape, :(ccall(#= /home/jovyan/.julia/packages/PyCall/twYvK/src/pyfncall.jl:43 =# @pysym(:PyObject_Call), PyPtr, (PyPtr, PyPtr, PyPtr), o, pyargsptr, kw))))) <class 'ImportError'>
ImportError("/opt/julia-1.8.3/bin/../lib/julia/libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /opt/conda/lib/python3.10/site-packages/contourpy/_contourpy.cpython-310-x86_64-linux-gnu.so)")
 File "/opt/conda/lib/python3.10/site-packages/matplotlib/pyplot.py", line 2527, in contour
   __ret = gca().contour(
 File "/opt/conda/lib/python3.10/site-packages/matplotlib/__init__.py", line 1442, in inner
   return func(ax, *map(sanitize_sequence, args), **kwargs)
 File "/opt/conda/lib/python3.10/site-packages/matplotlib/axes/_axes.py", line 6451, in contour
   contours = mcontour.QuadContourSet(self, *args, **kwargs)
 File "/opt/conda/lib/python3.10/site-packages/matplotlib/contour.py", line 769, in __init__
   kwargs = self._process_args(*args, **kwargs)
 File "/opt/conda/lib/python3.10/site-packages/matplotlib/contour.py", line 1395, in _process_args
   import contourpy
 File "/opt/conda/lib/python3.10/site-packages/contourpy/__init__.py", line 7, in <module>
   from contourpy._contourpy import (


Stacktrace:
 [1] pyerr_check
   @ ~/.julia/packages/PyCall/twYvK/src/exception.jl:75 [inlined]
 [2] pyerr_check
   @ ~/.julia/packages/PyCall/twYvK/src/exception.jl:79 [inlined]
 [3] _handle_error(msg::String)
   @ PyCall ~/.julia/packages/PyCall/twYvK/src/exception.jl:96
 [4] macro expansion
   @ ~/.julia/packages/PyCall/twYvK/src/exception.jl:110 [inlined]
 [5] #107
   @ ~/.julia/packages/PyCall/twYvK/src/pyfncall.jl:43 [inlined]
 [6] disable_sigint
   @ ./c.jl:473 [inlined]
 [7] __pycall!
   @ ~/.julia/packages/PyCall/twYvK/src/pyfncall.jl:42 [inlined]
 [8] _pycall!(ret::PyCall.PyObject, o::PyCall.PyObject, args::Tuple{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, Matrix{Float64}, Vector{Float64}}, nargs::Int64, kw::PyCall.PyObject)
   @ PyCall ~/.julia/packages/PyCall/twYvK/src/pyfncall.jl:29
 [9] _pycall!(ret::PyCall.PyObject, o::PyCall.PyObject, args::Tuple{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, Matrix{Float64}, Vector{Float64}}, kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:colors, :linewidths), Tuple{String, Float64}}})
   @ PyCall ~/.julia/packages/PyCall/twYvK/src/pyfncall.jl:11
[10] pycall(::PyCall.PyObject, ::Type{PyCall.PyAny}, ::StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:colors, :linewidths), Tuple{String, Float64}}})
   @ PyCall ~/.julia/packages/PyCall/twYvK/src/pyfncall.jl:83
[11] contour(::StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, ::Vararg{Any}; kws::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:colors, :linewidths), Tuple{String, Float64}}})
   @ PyPlot ~/.julia/packages/PyPlot/H01LC/src/PyPlot.jl:194
[12] top-level scope
   @ In[17]:5`

Did you already have that ? Any idea of where it could be coming from ?

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