First access and interface

You can access the ESA MAAP coding environment (Experiment) from the ESA PAL page. Once there, you can scroll down and click on "Coding (Experiment)".

Next, you can choose between four different environments:

Minimal: the simplest one, with the minimum number of pre-installed packages and libraries.
Datascience: it comes with Python, R and Julia, together with some scientific packages already installed on it.
MAAP: it comes with some specific pre-installed libraries for MAAP users. Python is the only language installed.
Rtools add-on: it comes with both Python and R, with the R tools already installed.

Interface

As you can see from the image below, the ESA MAAP coding environment is based on Jupyter. This means that most of the functionalities related to writing codes, interacting with the terminal or managing the file browser, are exactly the same. So, the main aspects will be covered in this guide, but in case you need a deeper understanding you can refer to the Jupyter documentation.

Once the workspace has loaded, you can see the Jupyter interface, characterized by the Launcher, the file browser and the sidebar.

Launcher

The Launcher is the central part of the screen, where the available kernels are displayed.

To display a new Launcher page, you can click on the blue icon “+” on the top left, or on the "+" icon near the Launcher tab.

From the Launcher, you can:

Create a new notebook file
Write commands by console
Open the terminal
Create new text and markdown files
Create new Python files (.py) or, depending on the chosen environment, create also R (.r) and Julia (.jl) files

Notebook files

To create and edit a new notebook file (.ipynb), you can click on one of the kernel icons under the “Notebook” section, depending on which programming language you want to use. The new notebook file will appear on the left side, initially named Untitled.ipynb. The new file will be saved under the current working directory.

Console

By clicking on one of the icons under the “Console” section, you can write commands in the language you selected. Commands can be written in multiple rows (by clicking Enter) and they can be sent by clicking Shift + Enter.

Terminal

The terminal is accessible by clicking on the “Terminal” icon, under the “Other” section, and it will be opened referring to the current working directory. You can assess your current directory by typing the pwd command.

The user’s Jupyter home directory (~) is mounted to /home/jovyan.

Files in here persist across sessions and exist across the workspaces. Other folders can be created in /home/jovyan (e.g. /home/jovyan/new_folder) to organize files in a persistent way. See the related documentation to learn more.

On the left part of the screen, you can find the Jupyter Sidebar, which includes:

File Browser
Running Terminals & Kernels
Git Repo Interface
Table of Contents
Extension Manager

Note: the Git repo interface is not available in the “Minimal Environment”.

Clone a Repository with GitHub

Here is an example repository you can use for this guide: https://github.com/MAAP-Project/dps-unit-test

Copy the Github clone link from https://github.com/MAAP-Project/dps-unit-test, going in “Code” and then clicking the icon as showed below:

Open the built-in Jupyter Github to the left of the file browser. Choose “Clone a Repository” and paste in the .git link you copied from the Github repository. You can also access this menu through the Git tab at the top of the Jupyter window.

Now you should see a new folder with the cloned Git repository. By clicking on the Github icon while browsing to the new folder, you can see additional information about the repo.

Upload Files and Folders

On the left side of the screen you can see the uploaded folders and/or files. Other folders can be created by clicking on the icon highlighted by the red arrow. To upload one or more files, click on the icon highlighted by the blue arrow.