Nano filesystem storage
A minimalistic, secure, type-safe, zero-dependencies, persistent data store.
Note If you want safely use it in electron app look at electron-nano-store
Usage
import { defineStore } from "fs-nano-store";
/**
* Declare types for you storage
*/
type Store = {
name: string,
role: 'admin' | 'user'
}
const { get, set, changes } = await defineStore<Store>('/path/to/storage-file.json')
get('name') // undefined
set('name', 'Alex')
get('name') // Alex
// Store is Type-safe
// TS Error: Argument of type '"wrong-role"' is not assignable to parameter of type '"admin" | "user"'.
set('role', 'wrong-role')
// fs-nano-store automatically tracks any storage-file.json changes.
// Additionally, you can addListener on the `changed` event that emits
// if the store file has been modified somehow outside defined store methods.
changes.addListener('changed', () => {
})Note
Objects in store are immutable and will be deeply cloned on each
get/set.const obj = {} store.set('obj', obj) store.get('obj') === obj // false store.get('obj') === store.get('obj') // false store.get('obj').bar = 'baz' // will no have effect obj.bar = 'baz' // will not affected to stored data
Custom serializer
By default, all data is serialized in JSON using global JSON.
So if you want to store more complex data types like Date or Map, or want to have custom stringify/parse logic,
you need to use your own serializer that supports those data types. Example with superjson:
import { defineStore } from 'fs-nano-store'
import superjson from 'superjson';
type Store = {
date: Date,
}
const store = defineStore<Store>('store-file.json', {
serializer: superjson
})
store.set('date', new Date)
store.get('date') // Date objectMigrating from v0.2.x to v0.3.x
In https://github.com/cawa-93/fs-nano-store/commit/bd2dfb50c92eadae68f6a12e406acf6daacd05f7 Was changed how exactly data saving to filesystem. Old store files are incompatible. You may need manually convert old data to new format by command:
const newDataStr = JSON.stringify(
Object.entries(serializer.parse(oldDataStr))
.map(([k,v]) => [k,serializer.stringify(v)])
)