The problem mydb-cli solves

There is this specific problem faced where multiple developers working on the same database schema can cause conflicts, leading to errors or broken features. Mostly, in Flask apps using SQL based databases, applying migrations directly to production can introduce bugs or performance issues. Not just a production scenario, but also any conflict if occurs while amending a database, be it structure, its entries, and other stuff, that just completely deletes the entire database.
More often, in an e-commerce platform, developers might feel the need to modify the database schema for new features like product catalog updates or order processing changes. Applying these changes directly to the live database can cause data corruption and downtime during the deployment process, thereby resulting into a bad user experience with the application. Moreover, if at all developer tries changing the database details or schema on the live production server, that would be a very bad practice which increase processing times therefore, lowering down process efficiency ultimately.
So we came up with a solution where we thought why not just use database branches, that isolate changes, allowing developers to work independently on different features or migrations (or transactions). This would possibly prevent conflicts, henceforth ensuring a safe testing, resulting into making it more easier to apply validated changes to production without any risk enduring confidence among developers while making changes to database structures.

Challenges we ran into

One challenge I encountered was handling database and table names that were unexpectedly returned as bytearrays instead of strings, causing errors in schema queries. This issue, specific to how certain MySQL drivers handle binary data, led to invalid table names during SQL execution, preventing essential schema retrieval operations. Diagnosing and fixing the problem required explicitly decoding bytearrays to strings to ensure compatibility across database operations. Addressing this added complexity, as I had to carefully inspect and handle these data types to maintain smooth functionality and avoid runtime errors in my application.