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arlas_playground

Clone the project

The arlas_playground 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)
  • docker (>=27.0.3)
  • docker compose
  • python 3.10
  • curl (>=8.4.0)
  • csvkit (>=1.4.0)
  • jq (>=1.7.1)

Run ./check_requirements.sh to check these requirements.

Then, we'll also install:

  • arlas_cli
  • ARLAS Exploration Stack (Only to run ARLAS Locally)

Python virtual environment

Create the new 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

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

Activate environment

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.

Install python dependencies in the environment

Once the environment is activated, install the project dependency:

pip install -r requirements.txt

ARLAS Stack

The tutorials require an up and running ARLAS Stack.

ARLAS Cloud

The simplest way is to create an ARLAS Cloud account.

See ARLAS Cloud Guide

Install and run ARLAS Exploration Stack (Optional)

Warning

You don't need to install and launch ARLAS Exploration Stack if you are using ARLAS Cloud.

To run the simplest ARLAS stack and Elasticsearch on the local machine, follow the Deploying ARLAS Guide.

Install and configure arlas_cli

arlas_cli is installed with the project requirements

pip install arlas_cli

Check if it is installed and that you have the latest version:

arlas_cli --version

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

By default, arlas_cli is configured for a local ARLAS stack deployment.

Warning

If arlas_cli is configured for local ARLAS, the --config local option in all tutorials arlas_cli commands must be specified.

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: