I recently thought of creating a SuDoKu game using JavaScript. Having played the classic game and enjoyed it in the past, I did not think of how complex the process of generating an instance of a game would be in the beginning. I quickly realized even after generating the random completed state successfully, creating a […]

We have the Ne4j graph database running and the Cypher query ready to get the recommendation for every drink. We will need an Apollo server running in front of it to enable graphQL. GatsbyJs will connect to that graphQL endpoint during the build time to query for the recommended/similar drinks while building each drink’s detail page.

A recommendation engine can give site visitors an opportunity to discover the most relevant content on the site depending on the page user is browsing. A content publisher or a store can benefit from extra views/exposure or upselling.

The objective of this exercise for me was to dump all the product data as CSV / JSON so I could index them into Algolia. The exercise consisted of multiple steps to get to the required form of data. I will run through all those steps and explain what is happening.

When working on a new feature requiring schema updates, you may end up creating multiple fragments of migrations. This YouTube video explains how you could consolidate or squash these migrations without having to lose your local data.

I have tried to put together a video tutorial series on YouTube. Please support by subscribing to my YouTube and leaving your feedback on the videos.