Currently, the script uses text files to store and manage data about followed and unfollowed users. However, as the amount of data grows and the need for more complex queries arises, using text files may become inefficient and error-prone. To improve data management, we should consider switching from text files to SQLite databases.
Proposed Solution
Replace the existing file-based storage system with an SQLite database.
Create a database schema with a table to store followed and unfollowed user information, including user ID, follow timestamp, and unfollow timestamp (if applicable).
Update the existing functions that interact with the data storage to use SQLite queries instead of file read/write operations. This includes functions like save_followed_user, load_followed_users, mark_unfollowed_user, and any other functions that access the storage.
Implement error handling and data integrity checks to ensure smooth operation and data consistency.
By implementing these changes, we can expect better performance, easier data querying, and more robust data management.
Issue Description
Currently, the script uses text files to store and manage data about followed and unfollowed users. However, as the amount of data grows and the need for more complex queries arises, using text files may become inefficient and error-prone. To improve data management, we should consider switching from text files to SQLite databases.
Proposed Solution
By implementing these changes, we can expect better performance, easier data querying, and more robust data management.