After conducting an in-depth investigation, it became evident that directly retrieving keys from the deployed flagsmith instance and subsequently pushing them to the chain was not feasible.
Initially, I developed a small script to extract some project data, albeit not all. However, upon further analysis, I realized that iterating over this data and pushing it to the chain would pose significant readability issues for each user.
To address this challenge, I propose implementing a solution where data is loaded individually for each user before being pushed. Subsequently, the entire dataset can be loaded, and a systematic approach can be employed to extract the exact feature required for each user.
Moreover, it may be necessary to develop a dedicated client to facilitate this process. Instead of pushing the data into a key-value store, we can consider creating a project with a similar database schema. This project can then accommodate the entire dataset, which can be accessed and utilized through a custom client within the application. This approach ensures better organization and accessibility of the data while maintaining clarity and coherence for users.
After conducting an in-depth investigation, it became evident that directly retrieving keys from the deployed
flagsmithinstance and subsequently pushing them to the chain was not feasible.Initially, I developed a small script to extract some project data, albeit not all. However, upon further analysis, I realized that iterating over this data and pushing it to the chain would pose significant readability issues for each user.
To address this challenge, I propose implementing a solution where data is loaded individually for each user before being pushed. Subsequently, the entire dataset can be loaded, and a systematic approach can be employed to extract the exact feature required for each user.
Moreover, it may be necessary to develop a dedicated client to facilitate this process. Instead of pushing the data into a key-value store, we can consider creating a project with a similar database schema. This project can then accommodate the entire dataset, which can be accessed and utilized through a custom client within the application. This approach ensures better organization and accessibility of the data while maintaining clarity and coherence for users.
Example of the data