Exploring Redis Cache Logic: Managing Shopping Cart in Application Development

The State Changers meeting majorly focused on resolving the issue of product cart management. The problem identified was, instead of increasing the product quantity in the cart, each additional item was being added as a separate item. The team explored a solution involving updating the logic structure in the backend to effectively differentiate between adding an element to a list and updating something in existing place.

The discussion mentioned the use of Redis for maintaining cart data at a fast rate. The State Changers proposed that instead of adding items to the list, the shopping cart array is stored as JSON inside the cart. This was suggested to employ a get-value, set-value mechanism instead of adding to the end of the array. The method involves a shopping cart array which can be accessed, modified and updated back in Redis. The meeting also covered various scenarios arising while managing a product cart, including creating the object for the cart, pulling and modifying an existing cart, increasing the volume of items and more. The solutions proposed were based around data manipulation using array functions, conditional structures (if-then-else), and updating variables to incorporate changes in the cart. Used tools or methods involved "cache Redis", "has cache value", "data manipulation" and "set cache value". No specific tools such as "Xano", "WeWeb", "FlutterFlow", "Zapier", "Make", "Integromat", "Outseta", "Retool", "Bubble", "Adalo", "AppGyver", "AppSheet", "Comnoco", "Fastgen", "Firebase", "Google", "OAuth", "Stripe", "Twilio", "Airtable", "DraftBit", "Javascript", "Typescript", "React", "Vue.js", "JSX", "HTML", "CSS", "lambda", "serverless", "State Change", "ScriptTag", "OpenAI", "AI21" were mentioned in the transcript.

(Source: Office Hours 5/12 )

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