example-vscode-remote-snap-sar-calibration

A development container is a running Docker container with a well-defined tool/runtime stack and its prerequisites. The VS Code Remote - Containers extension allows you to clone a repository or open any folder mounted into (or already inside) a dev container and take advantage of VS Code's full development feature set.

The well-defined tool/runtime stack in this VS Code Remote container is:

• ESA's SNAP EO Toolbox
• SNAP snappy Python bindings
• snapista, a SNAP Python thin layer on top of snappy for creating and running SNAP GPT processing graphs
• Python development support tools such as flake8, black, mypy, etc.
• a Python project that does the SAR calibration of Sentinel-1 GRD data

Installation

To get started, follow these steps:

1. Install and configure Docker for your operating system.

   Windows / macOS:

   1. Install Docker Desktop for Windows/Mac.

   2. If you are using Windows Subsystem for Linux (WSL) 2 on Windows, to enable the Windows WSL 2 back-end: Right-click on the Docker taskbar item and select Settings. Check Use the WSL 2 based engine and verify your distribution is enabled under Resources > WSL Integration.

   Linux:

   1. Follow the official install instructions for Docker CE/EE for your distribution. If you are using Docker Compose, follow the Docker Compose directions as well.

   2. Add your user to the docker group by using a terminal to run: sudo usermod -aG docker $USER

   3. Sign out and back in again so your changes take effect.

2. Follow the steps in https://github.com/snap-contrib/docker-volume-eo/blob/master/README.md to create a local docker volume with the Sentinel-1 GRD acquisition

3. Install Visual Studio Code

4. Install the Remote Development extension pack.

5. In Visual Studio Code, run Remote-Containers: Clone Repository in Container Volume... from the Command Palette (F1)

6. Add the URL to this git repository: https://github.com/snap-contrib/example-vscode-remote-snap-sar-calibration.git

7. Select "Master" and Create New Volume

8. Wait a few minutes for the build to complete

9. Activate conda env and install the 'sar-calibration' app:

conda activate env_snap
python setup.py install

11. Exploit the sar-calibration command line utility or evolve the python project