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# In the first two sessions of our hands-on tutorial,
# we use jupyter notebooks to introduce higher-order network
# analytics with the python package pathpy. For each unit of
# the tutorial, we will provide you with a skeleton notebook,
# that contains descriptions, TODOs, as well as empty code
# cells, which we will fill together. Each session concludes
# with a self-paced and open-ended **Exploration** unit, in
# which you can apply the methods to real data. For each of the
# explorations, we provide a suggestion of what you can study in
# the data sets that we provide, but feel free to pose your own
# questions and to use own data.
# There are essentially three ways in which you can complete this
# hands-on tutorial:
# 1. Editing a stand-alone .py file in an editor of your choice
# 2. Editing jupyter .ipynb notebook files in the browser
# 3. Editing a stand-alone .py file in Visual Studio Code, using
# VSCode's jupyter plug-in
# While it is your choice how you want to work, for the sake of
# convenience we will use option 3. In the following we briefly
# demonstrate how it works. If you want to use option 3 as well,
# make sure to install VS Code and the associated plugins as
# described in the setup instructions available at
# Once you have set up Visual Studio Code, launch it either by clicking
# the icon or by executing `code` in a terminal.
# In the File menu, click 'File -> Open Folder' and navigate to your local
# copy of the repository material, which you have preferably cloned via git
# as described in the setup instructions.
# Let us now explore how to work with jupyter in VS Code. In a py file, we can
# simply add the comment tag #%% to the beginning of a line. This will mark
# the beginning of a jupyter cell and a Code Lens 'Run Cell' will appear above that
# line. Let's write the following python code below that Code Lens:
x = 'Hello World'
# Let us now add a second comment tag, which marks the start of another cell.
# Let's write the following code:
# We can now execute the code in a jupyter cell (delimited by the two #%% tags) by
# clicking the Code Lens. Try it with the first cell. When you first evaluate a cell
# you will be asked for the Notebook server in which the python kernel should be started.
# In the pop-up menu, you can just select "Start new Notebook". Visual Studio Code will
# start a new kernel, and once it is ready you will see 'Python 3 Kernel (idle)' in the
# status bar.
# Now our first line has been executed in our new kernel, and the kernel is waiting
# to execute our python code. Click the second cell, which prints the string.
# The output will appear in a new Results window. By default, each evaluation of a cell
# overwrites prior output, but we can change this behavior by ticking the "Append Results"
# tickbox. Try it by executing the second cell multiple times.
# If for some reason we don't want to use the jupyter kernel, we can simply execute the
# whole code file using our standard python interpreter. We can just hit F5 or click
# 'Debug -> Start Debugging'. Try it.
# This execution mode is great to debug your code by setting breakpoints. Just click to the
# left of line 48 in this file such that the red circle appear. Then hit F5.
# VS Code will highlight syntax errors (and, to a certain extent type errors) as
# you write your code. Try it by uncommenting 'x := 42' in the next line. Any problems will
# further appear in the problems window below the code editor.
# x:= 42
# VS Code will automatically show documentation extracted from the docstring of
# python classes and methods. Try it by typing print(...
# With STRG+SPACE you will see a list of variables, methods, symbols that are
# available at the current point in your code. Try it by uncommenting the next line,
# move the cursor after the dot and hit CTRL+SPACE.
# x.
# Finally, VS Code comes with integrated support for git repository. In fact, in the bottom left
# corner of the status bar, you should see a branch symbol "master" and next to it a small
# sync icon. Whenever you click this icon, you will automatically receive updates to all files in
# the repository. We will use this mechanism to distribute a live solution as we move forward with
# the tutorial. For this, you should work on the .py or .ipynb files in the "code" folder. We will
# work on the corresponding files in the "live_solution" folder. Whenver we sync our solution to
# the repository, you shall be able to directly sync it to your machine. If you keep the code file
# in the "live_solution" folder open (e.g. in a side panel) you will see the code update live to
# the version shown on the tutors screen. Let's try this with the file "1_2_pathpy.nb" in the
# "live_solutions" folder. I will edit the file and tell you to click the sync icon. You should see
# the file updating in VS Code.
# We are now ready to start the tutorial with unit 1.2. You can now navigate to the file
# code/ in the repository, which you will edit. You can keep the live_solution open as
# well if you want to have the tutor's version next to your version.