Difference between revisions of "UKCA Chemistry and Aerosol Tutorials: Python notebooks"
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alias jopen='ssh -N -f -L localhost:4801:localhost:4801 ukca' |
alias jopen='ssh -N -f -L localhost:4801:localhost:4801 ukca' |
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− | and then use the command <tt>jopen</tt> from within your terminal. |
+ | and then use the command <tt>jopen</tt> from within your terminal. |
+ | |||
+ | Once the connection has been established you'll be able to connect using the link above. |
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=== On the virtual machine === |
=== On the virtual machine === |
Revision as of 13:39, 11 January 2024
UKCA Chemistry and Aerosol Tutorials at UMvn13.0
During these Tutorials several Jupyter notebooks are provided using both cf-python and the Iris Python libraries. On pre-installed virtual machines these can be found in the
Tutorials/UMvn13.0/notebooks
Due to the SSH connection you will be making to these virtual machines, it is better to run jupyter remotely and then connect to it from the browser on your desktop machine.
You could also use equivalent python scripts held in the
Tutorials/UMvn13.0/scripts
directory using the pyterm command to open a terminal that is able to run the necessary Python libraries.
How to connect
- On your VM, change directory using the cd command into the directory that you want to run the scripts from, e.g.
- cd Tutorials/UMvn13.0/notebooks
- On your VM run the command jnotebook to start a jupyter notebook server, or jlab to start a jupyter lab server.
- On your personal desktop machine, open a connection to your AWS instance using one of the methods below.
- On your desktop machine, connect to the following web address using the Firefox web browser:
Technical notes
The above instructions make use of some alias and shortcuts to work. The full details of this are:
On your personal computer
Windows via MobaXTerm
On Windows you can use MobaXTerm to connect to the AWS instance to tunnel through to allow you to run Jupyter remotely.
You will need to open a local session, where you run the following command, e.g.
ssh -N -f -L localhost:4801:localhost:4801 -i /path/to/[KEY NAME] ubuntu@[EC2 VM IP ADDRESS]
Where /path/to/[KEY NAME] is the full path to the location of your private key file that you use to connect to the AWS instance. Once this connection has been established you will be able to connect using the link above.
SSH via a terminal (macOS or GNU/Linux)
You will be able to connect using the following SSH command:
ssh -N -f -L localhost:4801:localhost:4801 -i ~/.ssh/[KEY NAME] ubuntu@[EC2 VM IP ADDRESS]
You could also edit your ~/.ssh/config file to include the following
Host ukca Hostname [EC2 VM IP ADDRESS] User ubuntu IdentityFile ~/.ssh/[KEY NAME] HostKeyAlgorithms ssh-rsa
and then connect by
ssh -N -f -L localhost:4801:localhost:4801 ukca
You could also make an alias in your ~/.zshrc or ~/.bashrc, e.g.
alias jopen='ssh -N -f -L localhost:4801:localhost:4801 ukca'
and then use the command jopen from within your terminal.
Once the connection has been established you'll be able to connect using the link above.
On the virtual machine
The two alias are set in the ~/.bashrc file on the VM:
alias jlab="lxterminal -l -e 'export PATH=~/miniconda3/bin:$PATH && jupyter-lab --no-browser --port=4801'" alias jnotebook="lxterminal -l -e 'export PATH=~/miniconda3/bin:$PATH && jupyter notebook --no-browser --port=4801'"
and the
/home/vagrant/.jupyter/jupyter_notebook_config.py
file has the following setting
c.NotebookApp.token = 'UKCATraining'
This means that when you run the command jnotebook or jlab you then launch a new terminal pointing to the python installation in the /home/vagrant/miniconda3/bin directory.