[Showcase] FletStorage: Lightweight, namespaced, and async storage with auto JSON serialization

[BogdanovychA]

Hi Flet community! 🚀

I'd like to share a utility I've been working on: FletStorage.

While building several Flet apps, I found myself repeatedly writing boilerplate code for SharedPreferences to handle JSON serialization and avoid key collisions. I decided to extract this logic into a separate, reusable package.

What is FletStorage?

It's a lightweight, asynchronous wrapper around Flet's built-in SharedPreferences that simplifies data persistence.

Key Features

• Automatic JSON Serialization: Store and retrieve dict, list, int, bool, and str directly without manual json.dumps() or json.loads()
• Namespaced Storage: Automatically prefixes keys with your app_name to prevent data collisions between apps on the same device/domain
• Fully Asynchronous: Designed for modern Flet apps with a non-blocking API
• Robust API: Includes methods like get_or_default(), contains_key(), and a parallelized clear() for better performance

Quick Example

import flet as ft
from flet_storage import FletStorage

async def main(page: ft.Page):
    storage = FletStorage("my_app")
    
    # Save complex objects directly
    await storage.set("user", {"name": "Ivan", "age": 25})
    
    # Retrieve data (auto-deserialized)
    user = await storage.get("user")
    
    # Get with default value if key doesn't exist
    theme = await storage.get_or_default("theme", "light")
    
    # Clear only this app's data
    await storage.clear()

ft.run(main)

Links

• 📦 PyPI: https://pypi.org/project/flet-storage/
• 💻 GitHub: https://github.com/BogdanovychA/flet-storage

I'd love to hear your feedback or suggestions! If you find it useful, feel free to give it a ⭐ on GitHub.

Happy coding with Flet! 🎉

[VoHeCode]

Hi, did you write this to store large amounts of data? Or is it more for smaller datasets that will be used within the program?

[BogdanovychA]

Great question!

FletStorage is designed for smaller datasets - typical client-side storage use cases like:

• User settings/preferences
• App config
• Auth tokens
• Small lists (todos, favorites)
• UI state

The goal is to eliminate JSON serialization boilerplate for common app data, not replace databases. 🎯

[VoHeCode]

Nice.
Did you test that under all possible Platforms? I ask, because i had have massive problems to get this kind of stuff running crossplattform (that mean all except Apple - which i don't own). I ended up with the standard python configparser and the OS - configpath and/or datapath. Which - by the way- drives me nuts on android. Because the user of the phone do not have access to den programm-data-path. So in some apps i decide to store all the app data in public folders like documents and/or downloads. This is a intrestic one. Regards, Volker. (excuse my stumbling english)

[BogdanovychA]

Thanks for the question - your English is great! 👍

My testing status:

✅ Tested and working:

• Android (2 production apps)
• Web (same apps)
• Linux (compiled binary)
• Windows (dev environment, not compiled)

❌ Not tested:

• iOS/macOS (no Apple hardware)

Cross-platform confidence:

FletStorage is just a wrapper, so it inherits Flet's cross-platform compatibility. If Flet works on a platform, FletStorage should too.

[Qye-Leisure]

Hello, I've created a node editor similar to n8n to store workflow execution data (the output of each node's execution). The data format is almost always JSON, or simply a list of dictionaries. Is this suitable for this purpose? This data is not permanently stored; it's just temporary data, retaining only the most recent execution data. In special cases, data for a specified number of days will be retained, such as for 7 days.

[BogdanovychA]

Yes, FletStorage can handle this use case, but with some considerations:

✅ Good fit for:

• JSON data and lists of dictionaries (perfect - that's exactly what it's designed for)
• Temporary workflow execution results
• Recent execution history

⚠️ Considerations:

1. Storage limits: Since it's built on SharedPreferences/localStorage, you're limited by platform storage:

   • Web: ~5-10MB
   • Desktop/Mobile: More generous, but still meant for smaller datasets

2. Data retention: You'll need to implement your own cleanup logic to:

   • Keep only recent executions
   • Delete data older than X days
   • Prevent storage from growing indefinitely

[Qye-Leisure]

Okay, thank you very much

[Twilight0]

That's amazing, thanks for sharing. I am probably going to use it on my planned Android app because I have to apply many options.

[BogdanovychA]

🤖 Update: AI Agent Skill Available!

I've created an AI agent skill for flet-storage that's now available on Skills.sh!

Install:

npx skills add bogdanovycha/flet-storage

This gives AI assistants (Claude, ChatGPT, etc.) deep context about the package, including:

• Complete API reference
• Usage patterns and best practices
• Common pitfalls and solutions
• Cross-platform considerations

Now you can get even better AI assistance when working with flet-storage! 🎯

🔗 https://skills.sh/bogdanovycha/flet-storage/flet-storage