Overview
info
This doc explains how the MageAI is used in the Cenabast proyect
See also:
MageAI is be used as a Middleman in charge of recolecting information from Cenabast APIs and ingesting them into the Spree aplication via its Rest API.
Implementation
MageAI is currently used for the product sincronization service
A data pipeline can be created for each pipeline we want to create.
Data pipeline creation Guidelines:
- The pipeline is scheduled to run every X hours
- The pipeline requests a token, request information from 1-N APIs, and merge that information
- The pipeline injects the information to the Spree Aplication via an API request
- Spree native API must be used. Prefering to decorate the less amount possible.
Deployment
MageAI service is present in the docker-compose.yml file. By default it will run when starting the services. On dvelopment environments, it can be accessed via http://localhost:6789/.
Important environment variables
-
CENABAST_API_BASE_URL
- Root URL to use
-
CENABAST_API_BASE_PATH
- Base path that points to the root of the API to use
-
CENABAST_API_USER
- API User to obtain a token from
-
CENABAST_API_PASSWORD
- Password of the API user