Installation                                                                
============

Using the :code:`.zip`-file
***************************

Download the :code:`.zip`-file from Canvas or (:download:`here<wise_course_modelling_2024.zip>`) and move it to a preferred directory on your system.

Open a powershell/terminal on your computer. Move to the folder where you want to run all your projects.

::

    cd path/to/your/preferred/directory/


-------------------------------------------------------------------------------

Using git
*********

Open a powershell/terminal on your computer. Move to the folder where you want to run all your projects and install your *repository*:

::

    cd path/to/your/preferred/directory/


Now we need to clone the repository.

::

    git clone https://gitlab.com/cahmd/wise_course_modelling_2024.git
    


Now change the directory to the installation folder:


-------------------------------------------------------------------------------

Lets install the container, which is only possible when being in the powershell/terminal. Change the directory by 

::

    cd wise_course_modelling_2024/install


and after, run 

.. content-tabs::

    .. tab-container:: dinstall_tab1
        :title: Linux (Ubuntu, Suse, Debian)

        ::
            
            docker build -t wise/jupyter . 

    .. tab-container:: dinstall_tab2
        :title: Mac OS X

        ::

            docker build --platform linux/amd64 -t wise/jupyter .


    .. tab-container:: dinstall_tab3
        :title: Windows (via PS and MSL)

        ::
            
            docker build -t wise/jupyter . 


in order to build the docker container. Informations what this container includes are in the section "Details about the Docker container". This my take a while to install. After, change one directory back

::

    cd ../


and run the container by executing

.. content-tabs::

    .. tab-container:: drun_tab1
        :title: Linux (Ubuntu, Suse, Debian)

        ::
            
            docker run -p 8765:8765 -v $(pwd):/wisejupyter wise/jupyter


    .. tab-container:: drun_tab2
        :title: Mac OS X

        ::

            docker run -p 8765:8765 -v $(pwd):/wisejupyter wise/jupyter


    .. tab-container:: drun_tab3
        :title: Windows (via PS and MSL)

        ::
            
            docker run -p 8765:8765 -v ${pwd}:/wisejupyter wise/jupyter 

        Note the curly braces what are different from Linux and Mac!


Now you can switch to your browser and copy the address

::

  http://localhost:8765


The website you should see now looks like the one in the figure

.. image:: pictures/login.png
    :width: 400
    :align: center
    :alt: Login page 


You see the need for a password or a token. Go back to your terminal and copy the token shown there (marked by the yellow circle in the following picture)

.. image:: pictures/token.png
    :width: 400
    :align: center
    :alt: Extract the token 


Insert the copied token to the file and press enter. The screen you see now should look like this

.. image:: pictures/login_sucess.png
    :width: 400
    :align: center
    :alt: Success login page 

Alternatively, you can copy the entire :code:`http://` - adress, that looks similar to 

::

    http://127.0.0.1:8765/tree?token=be7b93d1a1911ebc4ae8a6b4f289ebce8329c44a91491878 

**Congratulations!!!**, you are now in the working environment! This is a jupyter instance running in a linux environment with various scientific software installed.

Optional: In the jupyter notebook, click :code:`View->Open jupyterlab`, which opens a slightly different view with more advanced features. More on the notebooks in the chapter "Notebooks".