The algo's used have been optimized for scalability and human readability, the idea is that the data files need to be small, efficient and be well usable on a e.g. git based storage system.

dbcollection, can linked to a context of hero (can be a circle or another area worth remembering things for)
db, there can be more than 1 db per dbcollection
the secret is specified per dbcollection
each subdb inherits the secret from the dbcollection but needs to be configured as encrypted


> TODO: fix, we refactored

import incubaid.herolib.data.dbfs

mut dbcollection := get(context: 'test', secret: '123456')!

mut db := dbcollection.get_encrypted("db_a")!

db.set('a', 'bbbb')!
assert 'bbbb' == db.get('a')!

dbfs examples


import incubaid.herolib.data.dbfs

mut dbcollection := get(context: 'test', secret: '123456')!

mut db := dbcollection.get_encrypted("db_a")!


>> TODO: need to be updated, is now based on key and id

//get the value
fn (mut db DB) get(name_ string) !string {

//set the key/value will go to filesystem, is organzed per context and each db has a name
fn (mut db DB) set(name_ string, data_ string) !

//check if entry exists based on keyname
fn (mut db DB) exists(name_ string) bool
 
//delete an entry
fn (mut db DB) delete(name_ string) !

//get all keys of the db (e.g. per session)
fn (mut db DB) keys(prefix string) ![]string

// delete all data
fn (mut db DB) destroy() !