Signal(42)
Computed(λ)
Effect()
reactive()

Signals for Python
Reactive State Management
Inspired by SolidJS & Angular

Bring the power of SolidJS and Angular Signals to Python with automatic dependency tracking.
Think Excel spreadsheets for your Python code—the reactive model you know and love.
⭐ Star on GitHub 📚 Read the Docs ⚡ Try it Live
pip install reaktiv

Signals You Already Know

Just like Excel formulas automatically recalculate when cells change, or how SolidJS/Angular Signals work— reaktiv brings the same reactive primitives to Python.

reaktiv_demo.py 
from reaktiv import Signal, Computed, Effect

# Reactive data sources (like Excel cells)
count = Signal(0)
multiplier = Signal(2)

# Reactive computations (like Excel formulas)
double = Computed(lambda: count() * multiplier())
squared = Computed(lambda: count() ** 2)
summary = Computed(lambda: f"Count: {count()}, Double: {double()}, Squared: {squared()}")

# Reactive side effects (automatically run when data changes)
logger = Effect(lambda: print(f"📊 {summary()}"))

# Just change your data - everything reacts automatically!
count.set(3)        # 📊 Count: 3, Double: 6, Squared: 9
multiplier.set(5)   # 📊 Count: 3, Double: 15, Squared: 9
count.set(4)        # 📊 Count: 4, Double: 20, Squared: 16

Excel Meets Frontend Reactivity

When you change A1 in Excel, all formulas using A1 automatically recalculate. SolidJS and Angular Signals work the same way. reaktiv brings both concepts to Python.

🎯 Familiar Patterns

  • • Signal(value) — reactive data sources (like Excel cells)
  • • Computed(fn) — derived state (like Excel formulas)
  • • Effect(fn) — side effects that auto-run
  • • Automatic dependency tracking
  • • Fine-grained updates

💡 Use Cases

  • • Configuration management
  • • Data processing pipelines
  • • Real-time monitoring
  • • Jupyter notebook computations
  • • FastAPI / Django backends

Why reaktiv?

The battle-tested reactive model from SolidJS and Angular, reimagined for Python developers.

Signals for Python

Inspired by Angular and SolidJS, Signal, Computed, and Effect enable fine-grained reactivity.

Automatic Dependency Tracking

reaktiv tracks relationships between variables and updates state precisely and efficiently.

No Boilerplate

Just use plain Python — no decorators, no class magic. It works seamlessly with functions and data.

Designed for Everyone

Whether you're building backends, notebooks, or desktop tools — reaktiv fits right in.

What Developers Say

👨‍💻
"This feels like magic. Finally, reactive programming in plain Python! I've been waiting for something like this for years."
— Early user feedback

Join the growing community of Python developers using reaktiv. Share your experience →

Ready to Get Started?

Install reaktiv and start building reactive Python applications today.

pip install reaktiv
📖 Quick Start Guide 🛠️ View Examples 📝 Read the Article

Try Signals in Python!

Experience the SolidJS/Angular reactive model in Python. Run real reaktiv code directly in your browser.

🚀 Basic Example
🔢 Counter App
📝 Todo List
📊 Data Pipeline

Python Code

💡 Try this: Modify the values, add new signals, or create your own computed values!
ℹ️ Note: Each run starts with a fresh Python session for clean execution.

Output

Click "Run Code" to see the output...

Reactive Primitives

  • • Signal — reactive data sources (like SolidJS/Angular)
  • • Computed — derived reactive state that auto-updates
  • • Effect — side effects that run when dependencies change
  • • Everything updates automatically with fine-grained reactivity!

🚀 Instant Feedback

Run code immediately in your browser. No setup, no downloads, no installations required.

🔄 Real Reactivity

See actual reactive updates in action. Watch how changes propagate automatically through your data.

⚡ Learn by Doing

Experiment with different examples. Modify code, break things, learn how reactivity works.

packages = ["reaktiv"]