Exercise: STAC#
Timing
Time: 20 min
Goals
Getting familiar with Jupyter in the Puhti web interface
Learn to use STAC for searching for raster data
Prerequisites
CSC user account and project with access to Puhti.
Open JupyterLab in Puhti web interface#
Open Puhti web interface and log in
Change the default project and username
project_200xxxx
is example project name, replace with your own CSC project name.cscusername
is example username, replace with your username.
Open the Jupyter launch page: from front page or
Apps -> Jupyter
Use settings:
(Reservation:
geocomputing_thu
, only during course)Project:
project_200xxxx
Partition:
interactive
(small
during course)Number of CPU cores: 1
Memory (Gb): 8
Local disk: 0
Time: 0:15:00
Python: geoconda
Module version: default
Working directory:
/scratch/project_200xxxx
Launch
Wait a moment for Jupyter to start ->
Connect to Jupyter
Open
Preparations#
Open new Termianl window
Make a folder for the exercise materials and make it your working directory
Change the project name and username.
mkdir -p /scratch/project_200xxxx/students/cscusername
cd /scratch/project_200xxxx/students/cscusername
Copy the example scripts to Puhti.
git clone https://github.com/csc-training/geocomputing.git
STAC Notebook#
In file exporer open: `students/cscusername/geocomputing/python/STAC
Open
STAC_CSC_example.ipynb
notebookFollow the notebook, use
Shift+Enter
for running cells.
End the session#
Close the web tab
In Active sessions view:
Cancel
Key points
STAC is an easy option for finding and downloading raster data.
Jupyter is a nice tool for interactively working with Python.