Documentation: https://dougmercer.github.io/signified

Source Code: https://github.com/dougmercer/signified

A Python library for reactive programming (with kind-of working type narrowing).

pip install signified

signified is a reactive programming library that implements two primary data structures: Signal and Computed.

Both of these objects implement the Observer and Observable design patterns. This means that they can notify other Observers if they change, and they can subscribe to be notified if another Observable changes.

This allows us to create a network of computation, where one value being modified can trigger other objects to update.

This allows us to write more declarative code, like,

x = Signal(3)
x_squared = x ** 2  # currently equal to 9
x.value = 10  # Will immediately notify x_squared, whose value will become 100.

Here, x_squared became a reactive expression (more specifically, a Computed object) whose value is always equal to x ** 2. Neat!

signified's Signal object effectively gives us a container which stores a value, and Computed gives us a container to store the current value of a function. In the above example, we generated the Computed object on-the-fly using overloaded Python operators like **, but we could have just as easily done,

from signified import computed

@computed
def power(x, n):
    return x**n

x_squared = power(x, 2)  # equivalent to the above

Together, these data structures allow us to implement a wide variety of capabilities. In particular, I wrote this library to make my to-be-released animation library easier to maintain and more fun to work with.

Other reactive Python libraries don't really attempt to implement type hints (e.g., param).

signified is type hinted and supports type narrowing even for nested reactive values.

from signified import Signal

a = Signal(1.0)
b = Signal(Signal(Signal(2)))
reveal_type(a + b)  # Computed[float | int]

Unfortunately, for the time being, our type hints only work with pyright.

Checkout https://dougmercer.github.io/signified to find out more.

signified has some support for numpy and IPython built in.

Specify while installing like this, or just have numpy/ipython installed!

pip install signified[numpy] # just numpy
pip install signified[ipython] # just ipython
pip install signified[all] # both