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arlas_playground

Clone the project

The arlas_playground (repo) project contains scripts and resources you need to run the tutorials.

Clone it in your working directory:

git clone git@github.com:gisaia/arlas_playground.git
cd arlas_playground

Prerequisite

This repo illustrates a couple of usages of ARLAS. In order to play with it, you'll need:

  • git version (>=2.39.3)
  • python 3.10
  • curl (>=8.4.0)

Python virtual environment

If it's the first time you run the project, create a virtual env before running the documentation.

Run at project root:

python -m venv env_arlas_playground

Success

Now the env_arlas_playground env exists and is stored at project root.

To activate the environment in your terminal/powershell:

source env_arlas_playground/bin/activate

env_arlas_playground\Scripts\Activate.ps1

On Microsoft Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user.

You can do this by issuing the following PowerShell command: 

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

See venv documentation for more information.

Once the environment is activated, install the project dependency:

pip install -r requirements.txt

Tip

To add the project root to your PYTHONPATH, simply run in your terminal: 

export PYTHONPATH="$(pwd):$PYTHONPATH"

It can be added permanently to your shell configuration file (.bashrc, .bash_profile, or .zshrc)

ARLAS Instance

The tutorials require ARLAS up and running.

You can either use the ARLAS cloud service managed by Gisaïa or deploy the ARLAS software stack on your infrastructure/computer:

  • ARLAS Cloud: The simplest way to access an ARLAS instance is to create an ARLAS Cloud account. See ARLAS Cloud Guide.
  • Run ARLAS stack: To run a simple ARLAS stack and Elasticsearch on your machine, follow the Deploying ARLAS Guide.

Install and configure arlas_cli

Install arlas_cli with pip:

pip install arlas_cli

To ensure that it is installed and that you have the latest version, run:

arlas_cli --version

To configure arlas_cli to access your ARLAS Cloud account, see ARLAS CLI cloud configuration guide.

When installed, arlas_cli is configured for a local ARLAS stack deployment.

To make sure that the local configuration is set as default, run:

arlas_cli confs set local

For more details, check the full arlas_cli documentation.

Now you can play

For the different examples, you will see how to:

  • Get the spatio-temporal data
  • Transform the data
  • Index the data
  • Set up a collection
  • Set up a dashboard

You can now choose an example of ARLAS usage on spatio-temporal data: