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module load anaconda3/2021.11 source activate <you environment> #e.g source activate s123456-tf-cpu conda install <another-package-1> <another-package-2> #To see the packages in your Conda environment, run this command conda list conda deactivate exit For some packages you will need to add the conda-forge channel or even perform the installation using pip as the last step. |
Custom Conda Environment
The procedure above will only be useful if you only need the base Conda environment which includes just less than three hundred packages. If you need custom packages then you should create a new Conda environment and include jupyter in addition to the other packages that you need. The necessary modifications are shown below:
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ssh snumber@@gc-prd-hpclogin1.rcs.griffith.edu.au
module load anaconda3/2020.11
source /usr/local/bin/s3proxy.sh
conda create --name myenv jupyter <package-2> <package-3>
source activate myenv
#To see the packages in your Conda environment, run this command
conda list
conda deactivate
exit
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Using Widgets
conda create --name widg-env --channel conda-forge matplotlib jupyterlab ipywidgets ipympl
Usage
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ssh -N -f -L localhost:8889:localhost:8889 snumber@n059.rcs.griffith.edu.au |
Custom Conda Environment
The procedue procedure above will only be useful if you only need the base Conda environment which includes just less than three hundred packages. If you need custom packages then you should create a new Conda environment and include jupyter in addition to the other packages that you need. The necessary modifications are shown below:
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|---|
...
# from behind VPN if off-campus or on wireless ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au module load anaconda3/2020.11 |
...
source /usr/local/bin/s3proxy.sh conda create --name myenv jupyter <package-2> <package-3> source activate myenv |
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#To see the packages in your Conda environment, run this command |
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conda list conda deactivate exit |
# from behind VPN if off-campus or on wireless
ssh snumber@gc-prd-hpclogin1.rcs.griffith.edu.au module load anaconda3/2020.11
jupyter-notebook --no-browser --port=8889 --ip=127.0.0.1
The packages in the base environment will not be available in your custom environment unless you explicitly list them (e.g., numpy, matplotlib, scipy).
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