jozzdart/prf

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Define. Get. Set. Done.

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No boilerplate. No repeated strings. No setup. Define your variables once, then get() and set() them anywhere with zero friction. prf makes local persistence faster, simpler, and easier to scale, with 20+ built-in types and a clean, type-safe API. Designed to fully replace raw use of SharedPreferences.

Table of Contents

• Introduction
• Why Use prf?
• SharedPreferences vs prf
• Setup & Basic Usage (Step-by-Step)
• Available Methods and Supported Types
• Accessing prf Without async
• Migrating from SharedPreferences to prf
• Recommended Companion Packages
• Why prf Wins in Real Apps
• Adding Custom prfs (Advanced)
• More jozz Packages

Define → Get → Set → Done

Just define your variable once — no strings, no boilerplate:

final username = Prf<String>('username');

Then get it:

final value = await username.get();

Or set it:

await username.set('Joey');

That’s it. You're done. Works out of the box with all of these:

• bool int double String num Duration DateTime BigInt Uri Uint8List (binary)
• Also lists List<String> List<int> List<***> of all supported types!
• JSON & enums

All supported types use efficient binary encoding under the hood for optimal performance and minimal storage footprint — no setup required. Just use Prf<T> with any listed type, and everything works seamlessly.

Why Use prf

Working with SharedPreferences often leads to:

• Repeated string keys
• Manual casting and null handling
• Verbose async boilerplate
• Scattered, hard-to-maintain logic

prf solves all of that with a one-line variable definition that’s type-safe, cached, and instantly usable throughout your app. No key management, no setup, no boilerplate, no .getString(...) everywhere.

What Sets prf Apart?

• ✅ Single definition — just one line to define, then reuse anywhere
• ✅ Type-safe — no casting, no runtime surprises
• ✅ Automatic caching — with Prf<T> for fast access
• ✅ Easy isolate safety — with .isolated
• ✅ Lazy initialization — no need to call SharedPreferences.getInstance() or anything.
• ✅ Supports more than just primitives — 20+ types, Enums & JSON
• ✅ Built for testing — easily reset, override, or mock storage
• ✅ Cleaner codebase — no more scattered prefs.get...() or typo-prone string keys

SharedPreferences vs prf

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Feature	SharedPreferences (raw)	prf
Define Once, Reuse Anywhere	❌ Manual strings everywhere	✅ One-line variable definition
Type Safety	❌ Requires manual casting	✅ Fully typed, no casting needed
Supports Advanced Types	❌ No - only 5 types.	✅ Built-in support for 20+ types and supports enums & JSON
Readability	❌ Repetitive and verbose	✅ Clear, concise, expressive
Centralized Keys	❌ You manage key strings	✅ Keys are defined as variables
Lazy Initialization	❌ Must await getInstance() manually	✅ Internally managed
Supports Primitives	✅ Yes	✅ Yes
Isolate & Caching	⚠️ Partial — must manually choose between caching or no-caching APIs	✅ Just .isolate for full isolate-safety ✅ Prf<T> for faster cached access (not isolate-safe)

Code Comparison

Using SharedPreferences:

final prefs = await SharedPreferences.getInstance();
await prefs.setString('username', 'Joey');
final username = prefs.getString('username') ?? '';

Using prf with cached access (Prf<T>):

final username = Prf<String>('username');
await username.set('Joey');
final name = await username.get();

Using prf with isolate-safe access (PrfIso<T>):

final username = Prf<String>('username').isolated;
await username.set('Joey');
final name = await username.get();

If you're tired of:

• Duplicated string keys
• Manual casting and null handling
• Scattered async boilerplate

Then prf is your drop-in solution for fast, safe, scalable, and elegant local persistence.

🚀 Setup & Basic Usage (Step-by-Step)

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Step 1: Add prf to your pubspec.yaml

dependencies:
  prf: ^latest

Then run:

flutter pub get

---

Step 2: Define Your Variable

You only need one line to create a saved variable.
For example, to save how many coins a player has:

final playerCoins = Prf<int>('player_coins');

This means:

• You're saving an int (number)
• The key is 'player_coins'

---

Step 3: Save a Value

To give the player 100 coins:

await playerCoins.set(100);

---

Step 4: Read the Value

To read how many coins the player has:

final coins = await playerCoins.get();

print('Coins: $coins'); // 100

That’s it! 🎉 You don’t need to manage string keys or setup anything. Just define once, then use anywhere in your app.

---

Step 5 (Optional): Use .prf<T>() Shortcut

Instead of defining the key explicitly, you can use the .prf<T>() extension on a string:

final playerCoins = 'player_coins'.prf<int>();

From there it behave the same as defining using Prf<T>

await playerCoins.set(100);
final coins = await playerCoins.get();

print('Coins: $coins');

This works exactly the same — just a stylistic preference if you like chaining on string keys.

📖 Available Methods and Supported Types

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✅ All Prf<T> types support these methods out of the box

• get() → returns the current value (cached or from disk)
• set(value) → saves the value and updates the cache (if applicable)
• remove() → deletes the value from storage (and cache if applicable)
• isNull() → returns true if the value is null
• getOrFallback(fallback) → returns the value or a fallback if null
• existsOnPrefs() → checks if the key exists in storage
• getOrDefault() → returns the value, or throws if no value exists and no default is defined (safe alternative to assuming non-null values)

📦 Supported Types:

final someData = Prf<T>('key');

All of these work automatically (practically every type):

• bool, int, double, num, String, Duration, DateTime, Uri, BigInt, Uint8List (binary)
• List<bool>, List<int>, List<String>, List<double>, List<num>, List<DateTime>, List<Duration>, List<Uint8List>, List<Uri>, List<BigInt>

All supported types use efficient binary encoding under the hood for optimal performance and minimal storage footprint — no setup required. Just use Prf<T> and everything works seamlessly.

🔧 Specialized Types - Enums & JSON

For enums and custom models, use the built-in factory helpers:

• Prf.enumerated<T>() → enum value
• Prf.enumeratedList<T>() → list of enum values
• Prf.json<T>() → custom model object
• Prf.jsonList<T>() → list of custom model objects

• Prf.cast<T, TCast>() → custom behavior

---

🛰 Need Isolate Safety?

Every Prf object supports the .isolated getter — no matter the type (enums, bytes, JSON, lists, etc).
It returns a PrfIso that works safely across isolates (no caching, always reads from disk).

These are practically the same:

final safeUser = Prf<String>('username').isolated; // Same
final safeUser = PrfIso<String>('username');       // Same

---

🎯 Example: Persisting an Enum

Define your enum:

enum AppTheme { light, dark, system }

Store it using Prf.enumerated (cached) or PrfIso.enumerated (isolate-safe):

final appTheme = Prf.enumerated<AppTheme>(
  'app_theme',
  values: AppTheme.values,
);

Usage:

final currentTheme = await appTheme.get(); // AppTheme.light / dark / system
await appTheme.set(AppTheme.dark);

---

📚 Persisting a List of Enums

Define your enum:

enum Permission { read, write, delete }

Store a list using Prf.enumeratedList (cached) or PrfIso.enumeratedList (isolate-safe):

final permissions = Prf.enumeratedList<Permission>(
  'user_permissions',
  values: Permission.values,
);

Usage:

final current = await permissions.get(); // [Permission.read, Permission.write]
await permissions.set([Permission.read, Permission.delete]);

---

🧠 Custom Types? No Problem

Want to persist something more complex?
Use Prf.json<T>() or PrfIso.json<T>() with any model that supports toJson and fromJson:

final userData = Prf.json<User>(
  'user',
  fromJson: (json) => User.fromJson(json),
  toJson: (user) => user.toJson(),
);

---

🧠 Complex Lists? Just Use jsonList

For model lists, use Prf.jsonList<T>() or PrfIso.jsonList<T>():

final favoriteBooks = Prf.jsonList<Book>(
  'favorite_books',
  fromJson: (json) => Book.fromJson(json),
  toJson: (book) => book.toJson(),
);

Usage:

await favoriteBooks.set([book1, book2]);
final list = await favoriteBooks.get(); // List<Book>

---

🧩 Custom Casting Adapter with .cast()

Need to persist a custom object that can be converted to a supported type (like String, int and all 20+ types)? Use the .cast() factory to define on-the-fly adapters with custom encode/decode logic — no full adapter class needed!

final langPref = Prf.cast<Locale, String>(
  'saved_language',
  encode: (locale) => locale.languageCode,
  decode: (string) => string == null ? null : Locale(string),
);

• T → your custom type (e.g., Locale)
• TCast → any built-in supported type (e.g., String, int, List<String>, etc)
• encode → how to convert T to TCast
• decode → how to restore T from TCast

Great for storing objects that don’t need full toJson() support — just convert to a native type and you're done!

⚡ Accessing prf Without Async

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If you want instant, non-async access to a stored value, you can pre-load it into memory. Use Prf.value<T>() to create a prf object that automatically initializes and caches the value.

Example:

final userScore = await Prf.value<int>('user_score');

// Later, anywhere — no async needed:
print(userScore.cachedValue); // e.g., 42

• Prf.value<T>() reads the stored value once and caches it.
• You can access .cachedValue instantly after initialization.
• If no value was stored yet, .cachedValue will be the defaultValue or null.

✅ Best for fast access inside UI widgets, settings screens, and forms.
⚠️ Not suitable for use across isolates — use .isolated or PrfIso<T> for isolate safety.

Quick Summary

• await Prf.value<T>() → loads and caches the value.
• .cachedValue → direct, instant access afterward.
• No async needed for future reads!

💡 Altervative - .prf() from String Keys

final username = 'username'.prf<String>();
await username.set('Joey');
final name = await username.get();

Isolate-safe version:

final username = 'username'.prf<String>().isolated;
await username.set('Joey');
final name = await username.get();

🔁 Migrating from SharedPreferences to prf

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Whether you're using the modern SharedPreferencesAsync or the legacy SharedPreferences, migrating to prf is simple and gives you cleaner, type-safe, and scalable persistence — without losing any existing data.

In fact, you can use prf with your current keys and values out of the box, preserving all previously stored data. But while backwards compatibility is supported, we recommend reviewing all built-in types and usage that prf provide — which may offer a cleaner, more powerful way to structure your logic going forward, without relying on legacy patterns or custom code.

---

✅ If you're already using SharedPreferencesAsync

You can switch to prf with zero configuration — just use the same keys.

Before (SharedPreferencesAsync):

final prefs = SharedPreferencesAsync();
await prefs.setBool('dark_mode', true);
final isDark = await prefs.getBool('dark_mode');

After (prf):

final darkMode = Prf<bool>('dark_mode');
await darkMode.set(true);
final isDark = await darkMode.get();

• ✅ As long as you're using the same keys and types, your data will still be there. No migration needed.
• 🧼 Or — if you don't care about previously stored values, you can start fresh and use prf types right away. They’re ready to go with clean APIs and built-in caching for all dart types, enums, JSONs, and more.

---

✅ If you're using the legacy SharedPreferences class

You can still switch to prf using the same keys:

Before (SharedPreferences):

final prefs = await SharedPreferences.getInstance();
await prefs.setString('username', 'Joey');
final name = prefs.getString('username');

After (prf):

final username = Prf<String>('username');
await username.set('Joey');
final name = await username.get();

• ⚠️ prf uses SharedPreferencesAsync, which is isolate-safe, more robust — and does not share data with the legacy SharedPreferences API. The legacy API is already planned for deprecation, so migrating away from it is strongly recommended.
• ✅ If you're still in development, you can safely switch to prf now — saved values from before will not be accessible, but that's usually fine while iterating.

The migration bellow automatically migrates old values into the new backend if needed. Safe to call multiple times — it only runs once.

---

⚠️ If your app is already in production using SharedPreferences

If your app previously used SharedPreferences (the legacy API), and you're now using prf (which defaults to SharedPreferencesAsync):

• You must run a one-time migration to move your data into the new backend (especially on Android, where the storage backend switches to DataStore).

Run this before any reads or writes, ideally at app startup:

await PrfService.migrateFromLegacyPrefsIfNeeded();

This ensures your old values are migrated into the new system. It is safe to call multiple times — migration will only occur once.

Summary

Case	Do you need to migrate?	Do your keys stay the same?
Using SharedPreferencesAsync	❌ No migration needed	✅ Yes
Using SharedPreferences (dev only)	❌ No migration needed	✅ Yes
Using SharedPreferences (production)	✅ Yes — run migration once	✅ Yes
Starting fresh	❌ No migration, no legacy	🔄 You can pick new keys

With prf, you get:

• 🚀 Type-safe, reusable variables
• 🧠 Cleaner architecture
• 🔄 Built-in in-memory caching
• 🔐 Isolate-safe behavior with SharedPreferencesAsync
• 📦 Out-of-the-box support for 20+ types, enums, full JSON models and more

🌟 Recommended Companion Packages

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In addition to typed variables, prf connects seamlessly with additional persistence power tools — packages built specifically to extend the capabilities of prf into advanced real-world use cases.
These tools offer plug-and-play solutions that carry over the same caching, async-safety, and persistence guarantees you expect from prf.

Packages:
limit package → https://pub.dev/packages/limit
track package → https://pub.dev/packages/track

• ⏲ limit — manage cooldowns and rate limits across sessions and isolates. Includes:

  • Cooldown (fixed-time delays, e.g. daily rewards, retry timers)
  • RateLimiter (token bucket rate limiting, e.g. 1000 actions per 15 minutes)

• 🔥 track — track progress, activity, and usage over time. Includes:

  • StreakTracker (aligned streak tracking, e.g. daily habits)
  • HistoryTracker (rolling lists of recent items with optional deduplication)
  • PeriodicCounter (auto-reset counters per period, e.g. daily tasks)
  • RolloverCounter (sliding-window counters, e.g. attempts per hour)
  • ActivityCounter (detailed time-based activity stats)
  • BestRecord (coming soon: track best performances or highscores)

🔍 Why prf Wins in Real Apps

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Working with SharedPreferences directly can quickly become verbose, error-prone, and difficult to scale. Whether you’re building a simple prototype or a production-ready app, clean persistence matters.

❌ The Problem with Raw SharedPreferences

Even in basic use cases, you're forced to:

• Reuse raw string keys (risk of typos and duplication)
• Manually cast and fallback every read
• Handle async boilerplate (getInstance) everywhere
• Encode/decode complex types manually
• Spread key logic across multiple files

Let’s see how this unfolds in practice.

Example: Saving and Reading Multiple Values

Goal: Save and retrieve a username, isFirstLaunch, and a signupDate.

SharedPreferences (verbose and repetitive)

final prefs = await SharedPreferences.getInstance();

// Save values
await prefs.setString('username', 'Joey');
await prefs.setBool('is_first_launch', false);
await prefs.setString(
  'signup_date',
  DateTime.now().toIso8601String(),
);

// Read values
final username = prefs.getString('username') ?? '';
final isFirstLaunch = prefs.getBool('is_first_launch') ?? true;
final signupDateStr = prefs.getString('signup_date');
final signupDate = signupDateStr != null
  ? DateTime.tryParse(signupDateStr)
  : null;

🔻 Issues:

• Repeated string keys — no compile-time safety
• Manual fallback handling and parsing
• No caching — every .get hits disk
• Boilerplate increases exponentially with more values

Example: Same Logic with prf

final username = Prf<String>('username');
final isFirstLaunch = Prf<bool>('is_first_launch', defaultValue: true);
final signupDate = Prf<DateTime>('signup_date');

// Save
await username.set('Joey');
await isFirstLaunch.set(false);
await signupDate.set(DateTime.now());

// Read
final name = await username.get();         // 'Joey'
final first = await isFirstLaunch.get();   // false
final date = await signupDate.get();       // DateTime instance

💡 Defined once, used anywhere — fully typed, cached, and clean.

It Gets Worse with Models

Storing a User model in raw SharedPreferences requires:

1. Manual jsonEncode / jsonDecode
2. Validation on read
3. String-based key tracking

SharedPreferences with Model:

// Get SharedPreferences
final prefs = await SharedPreferences.getInstance();
// Encode to JSON
final json = jsonEncode(user.toJson());
// Set value
await prefs.setString('user_data', json);

// Read
final raw = prefs.getString('user_data');
User? user;
if (raw != null) {
  try {
    // Decode JSON
    final decoded = jsonDecode(raw);
    // Convert to User
    user = User.fromJson(decoded);
  } catch (_) {
    // fallback or error
  }
}

✅ Same Logic with prf

// Define once
final userData = Prf.json<User>(
  'user_data',
  fromJson: User.fromJson,
  toJson: (u) => u.toJson(),
);

// Save
await userData.set(user);

// Read
final savedUser = await userData.get(); // User?

Fully typed. Automatically parsed. Fallback-safe. Reusable across your app.

Built for Real Apps

prf was built to eliminate the day-to-day pain of using SharedPreferences in production codebases:

• ✅ Define once — reuse anywhere
• ✅ Clean API — get(), set(), remove(), isNull() for all types
• ✅ Supports 20+ types, enum, JSON
• ✅ Automatic caching — fast access after first read
• ✅ Test-friendly — easily reset, mock, or inspect values

How to Add Custom prf Types

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For most use cases, you can use built-in types or factories like Prf.enumerated<T>(), Prf.json<T>(), and now Prf.cast<T, TCast>() to persist almost anything. This section is for advanced users who want full control — but with less boilerplate thanks to the new .cast() API.

🧪 1. Define Your Custom Class

class Color {
  final int r, g, b;
  const Color(this.r, this.g, this.b);

  Map<String, dynamic> toJson() => {'r': r, 'g': g, 'b': b};
  factory Color.fromJson(Map<String, dynamic> json) =>
      Color(json['r'] ?? 0, json['g'] ?? 0, json['b'] ?? 0);
}

⚡ 2. Use .cast() to Store It

You can store Color as a String by encoding it as JSON:

final favoriteColor = Prf.cast<Color, String>(
  'favorite_color',
  encode: (color) => jsonEncode(color.toJson()),
  decode: (string) => string == null
      ? null
      : Color.fromJson(jsonDecode(string)),
);

🧩 Access and Use It

await favoriteColor.set(Color(255, 0, 0));
final color = await favoriteColor.get();

print(color?.r); // 255

🚦 Want Isolate-Safe?

Just add .isolated:

final safeColor = favoriteColor.isolated;

Summary

• Use Prf.cast<T, TCast>() to quickly persist custom objects.
• No need to write full adapter classes.
• Encode to any supported type (String, int, List, etc.).
• Add .isolated for isolate-safe usage.

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---

📦 More jozz Packages

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I’m Jozz — and my packages share a simple philosophy: developer experience first. I try to avoid boilerplate wherever possible, and most of these packages were born out of real needs in my own projects. Each one comes with clear documentation, minimal setup, and APIs that are easy to pick up without surprises.

They’re built to be lightweight, reliable, and ready for production, always with simplicity in mind. There are more packages in the works, following the same approach. If you find them useful and feel like supporting, you’re welcome to do so (:

☕ Buy me a coffee

• shrink – Compress Anything in One Line
• track – Persistent Streaks, Counters & Records
• prf – SharedPreferences, Without the Pain
• time_plus – Smarter DateTime & Duration Extensions
• exui – Supercharge Your Flutter UI
• limit – Cooldowns & Rate Limits, Simplified
• jozz_events – Strongly-Typed Events for Clean Architecture

🔽 shrink – Compress Anything in One Line

Because every byte counts. shrink makes data compression effortless with a one-line API and fully lossless results. It auto-detects the best method, often cutting size by 5× to 40× (and up to 1,000×+ for structured data). Perfect for Firestore, local storage, or bandwidth-sensitive apps. Backed by clear docs and real-world benchmarks.

📊 track – Persistent Streaks, Counters & Records

Define once, track forever. track gives you plug-and-play tools for streaks, counters, activity logs, and records — all persisted safely across sessions and isolates. From daily streaks to rolling counters to best-ever records, it handles resets, history, and storage automatically. Clean APIs, zero boilerplate, and deeply detailed documentation.

🐝 hivez – Hive, but Safer & Smarter

hivez is a production-ready layer on top of Hive CE that keeps its raw speed but makes it safer and easier to use. It auto-initializes boxes, enforces type safety, and gives you a single unified API for Box, LazyBox, and IsolatedBox. Concurrency issues are handled with built-in locks, and you also get extras like backup/restore, search, and crash recovery. Backed by clear, detailed documentation, hivez is designed for real-world apps where you want Hive’s performance without the boilerplate or pitfalls.

⏱ time_plus – Smarter DateTime & Duration Extensions

Stop wrestling with DateTime and Duration. time_plus adds the missing tools you wish Dart had built in: add and subtract time units, start/end of day/week/month, compare by precision, yesterday/tomorrow, fractional durations, and more. Built with 128+ extensions, 700+ tests, and zero dependencies, it’s faster, more precise, and more reliable than the classic time package — while keeping APIs clear and intuitive. Ideal for scheduling, analytics, or any app where every microsecond counts.

🎨 exui – Supercharge Your Flutter UI

Everything your widgets wish they had. exui is a zero-dependency extension library for Flutter with 200+ chainable utilities for padding, margin, centering, gaps, visibility, constraints, gestures, buttons, text styling, and more — all while keeping your widget tree fully native.

No wrappers. No boilerplate. Just concise, expressive methods that feel built into Flutter itself. Backed by hundreds of unit tests and exceptional documentation, exui makes UI code cleaner, faster, and easier to maintain.

⏲ limit – Cooldowns & Rate Limits, Simplified

One line. No boilerplate. No setup. limit gives you persistent cooldowns and token-bucket rate limiting across sessions, isolates, and restarts. Perfect for daily rewards, retry delays, API quotas, or chat limits. Define once, automate forever — the system handles the timing, persistence, and safety behind the scenes. Clear docs and practical examples included.

📢 jozz_events – Strongly-Typed Events for Clean Architecture

A domain-first, framework-agnostic event bus built for scalable apps. jozz_events enables decoupled, strongly-typed communication between features and layers — without the spaghetti. It’s lightweight, dependency-free, lifecycle-aware, and integrates naturally with Clean Architecture. Ideal for Flutter or pure Dart projects where modularity, testability, and clarity matter most.

🔗 License MIT © Jozz

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