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Toolbox overview

Before starting the course let's "unpack our toolbox" to ensure that we have the necessary digital working environment ready. This means we introduce the different software components used in E-TRAINEE Module 1 (and partly also in other Modules). Thereby, we cover installation and some basic methods of

  • Visual Studio Code (code editor)
  • Conda (package management system)
  • Jupyter Notebooks (interactive computing), with some Python fundamentals (programming language)
  • GeoPython - A quickstart to geographic data handling in Python: Vector data with GeoPandas, raster data with rasterio, and multidimensional raster data with xarray.

Background and objective

The objective of this introduction to the E-TRAINEE course is to provide you with the software knowledge and skills needed to start with the practical parts of E-TRAINEE Module 1. For working on these practical parts, there are often a couple of similar software tools and varieties that may be suitable for a specific task, e.g. (our choice in bold):

  • Program code can be run by executing either "normal" scripts (e.g. *.py files) or code cells within interactive Jupyter Notebooks (*.ipynb) with text explanations as well as graphics and other output in between.
  • Jupyter Notebook documents can be edited and run in various web-based or desktop applications, such as JupyterLab, JupyterHub, Jupyter Desktop, or Visual Studio Code, etc..
  • Data can be processed with a variety of graphical user interface software or command line tools or by scripting in a programming language such as R, Python, JavaScript, or Julia.
  • GeoPython: For handling geographic data in Python, we focus on the packages GeoPandas, rasterio and xarray. There are other packages available but some of them introduce unnecessary complexity, are no longer well-maintained, or are tailored to rather specific tasks.

Out of this variety, we selected a set of tools that makes up a tested and proven digital working environment. We hope that, by using a such a recommended, uniform environment for all course participants, you will (i) encounter less software-related problems, (ii) get more helpful, more specific instructions, (iii) learn an approach that enables you to set up and customize your working environment also for follow-up tasks (such as your MSc thesis, where you may need to install additional or different packages). A concise, step-by-step guide will show you how to make the components of this environment interact, so you don't need to search the endless resources of the web, and you have a condensed resource to look things up in case you forget something.

In addition to setting up such a working environment, you will learn some of the most useful methods of geodata handling and visualization in Python. This will be helpful when working on the practical parts of E-TRAINEE Module 1, where many of the more advanced workflows build upon these tools and methods.

Next: VSCode

Get started with the Visual Studio Code source-code editor here