The generation of the model is controlled by the workflow management system
`Snakemake <https://snakemake.bitbucket.io/>`_.
In a nutshell, the ``Snakefile`` declares for each python script in the ``scripts`` directory a rule which describes which files the scripts consume and produce (their corresponding input and output files).
The ``snakemake`` tool then runs the scripts in the correct order according to the rules' input/output dependencies.
Moreover, it is able to track, what parts of the workflow have to be regenerated, when a data file or a script is modified/updated.
The **blocks** represent the individual rules which are required to create the file ``networks/elec_s_128.nc``. The **arrows** indicate the outputs from preceding rules which a particular rule takes as input data.
..note::
The dependency graph shown above was generated using
For the use of ``snakemake``, it makes sense to familiarize oneself quickly with its `basic tutorial <https://snakemake.readthedocs.io/en/stable/tutorial/basics.html>`_ and then read carefully through the section `Executing Snakemake <https://snakemake.readthedocs.io/en/stable/executable.html>`_, noting the arguments ``-j``, ``-n``, ``-r``, but also ``--dag``, ``-R`` and ``-t``.
It is easy to run PyPSA-Eur for multiple scenarios using the `wildcards feature <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_ of ``snakemake``. Wildcards allow to generalise a rule to produce all files that follow a `regular expression <https://en.wikipedia.org/wiki/Regular_expression>`_ pattern, which e.g. defines one particular scenario. One can think of a wildcard as a parameter that shows up in the input/output file names and thereby determines which rules to run, what data to retrieve and what files to produce. **Details are explained in**:ref:`wildcards`**and**:ref:`scenario`.
