.. SPDX-FileCopyrightText: PyPSA-Earth and PyPSA-Eur Authors .. .. SPDX-License-Identifier: CC-BY-4.0 .. _learning_materials: Learning materials =================================== PyPSA meets Earth builds on top of several open-source packages, which are here recalled together with recommended sources to learn them from scratch. .. _data_science_basics: YouTube Tutorials --------------------- We host **training** and **presentation** videos about PyPSA ecosystem tools made for users, developers and interested people. - `Training playlist `_ - `Presentation playlist `_ - `Youtube channel `_ PyPSA Introduction (essential) ------------------------------- - `Watch `_ how PyPSA-Eur is designed (1h) - `Watch `_ and put your hands on to make PyPSA-Eur work on your computer (1-3h) - While watching these PyPSA videos always have a look into the excellent `PyPSA-Eur documentation `_ - To see what data we can extract we work usually closely with the `basic PyPSA documentation `_ - Follow the `PyPSA-Earth hackathon `_. Check the videos from this `Youtube series `_ since it explains and applies partially the hackathon material. Data science basics (essential) -------------------------------- - Fabian Neumann just shared with the world the possibly best training material for `"Data Science for Energy System Modelling" `_. This is a free multi-week course preparing you for all you need for PyPSA-Earth. - Refresh your Python knowledge by watching `CSDojo's playlist `_. His content is excellent as introduction. You will learn in effective short videos the python basics such as variables If/else statements, functions, lists, for loops, while loops, dictionaries, classes and objects, boolean, list comprehensions, sets - put your hands on and write some test scripts as the video suggests. (~3h) - Familiarize yourself with numpy and panda dataframes. In the Python-based PyPSA tool, we do not work with Excel. Powerful panda dataframes are our friends. `Here `__ is an extensive 30h course that provides a great introduction if this is completely unfamiliar to you. - `Introduction to Unix-shell `_ - "Use of the shell is fundamental to a wide range of advanced computing tasks, including high-performance computing and automated workflow. These lessons will introduce you to this powerful tool." (optional 4h, to become a pro) Git and GitHub -------------- For code collaboration we use GitHub. Which is a common source control tool that is a very popular collaborative code development tool. Here some notes if you are not already familiar with it: - Git and GitHub is not the same. Usually, you work with git on your computer (offline) to push changes to GitHub (online). - `Here `__ a great intro which we recommend - Learning by doing. Maybe one of the best ways to learn is to puts your hands on open a GitHub repository and upload/change/reverse files from your local computer on some dummy scripts. - This `cheatsheet `_ might help using the Git commands Snakemake and advanced changes ------------------------------ Snakemake is our brain in PyPSA. It automates many tasks & keeps the code structure clean. Therefore, it is quite useful to learn if your task is to integrate features into PyPSA. We can recommend: - `snakemake basic and advanced tutorial here `__ (takes max 3-5h and makes a lot of fun). - Explore how PyPSA uses snakemake in the Snakefile and scripts - the GitHub search function is your best friend to find quickly what interests you. Code environment ---------------- We can recommend setting up VScode from Microsoft. Add some extension if you like as described in `this video `_. For instance GitHub, Gitlense, and maybe some others. *Note*: if you decide to use Visual Studio Code, check out the tutorial about how to use `Git `_ and `Github `_ in Visual Studio Code