Library Comparison¶

This page compares signified with two other Python reactive libraries: reaktiv and param. All three implement reactive programming, but they differ in API design, feature scope, and performance.

Features At a Glance¶

	signified	reaktiv	param
Read a value	`x.value`	`x()`	`x.rx.value`
Write a value	`x.value = v`	`x.set(v)`	`x.rx.value = v`
Derived value (inline)	`y = x * 2`	—	`y = x.rx() * 2`
Derived value (decorator)	`@computed`	`@Computed`	`@param.depends`
React to changes	`Effect(fn)`	`Effect(fn)`	`x.rx.watch(fn)` / `obj.param.watch(fn, ...)`
Operator overloading	Yes	No	Yes (via `obj.rx()`)
Async support	No	Yes	Yes
Multithreading support	No	Yes	No

API Comparison¶

Here is the same computation expressed in each library:

signifiedreaktivparam

from signified import Signal, Effect

price = Signal(10.0)
quantity = Signal(3)
total = price * quantity      # Computed automatically via operator overload

print(total.value)            # 30.0

printer = Effect(lambda: print(f"Total: {total.value}"))

price.value = 15.0            # prints "Total: 45.0"

from reaktiv import Signal, Computed, Effect

price = Signal(10.0)
quantity = Signal(3)
total = Computed(lambda: price() * quantity())   # Explicit lambda

print(total())                # 30.0

printer = Effect(lambda: print(f"Total: {total()}"))

price.set(15.0)               # prints "Total: 45.0"

from param import rx

price = rx(10.0)
quantity = rx(3)
total = price * quantity      # Computed automatically via operator overload

print(total.rx.value)         # 30.0

total.rx.watch(lambda v: print(f"Total: {v}"))

price.rx.value = 15.0         # prints "Total: 45.0"

Key usability differences¶

signified overloads Python operators so reactive expressions can typically read like normal code (price * quantity returns a reactive Computed object). The .rx namespace handles some additional operations Python cannot easily overload, such as equality/identity testing.

reaktiv requires explicit Computed(lambda: ...) wrappers but, like signified, automatically tracks dependencies — every signal read inside the lambda is tracked.

param supports two reactive styles. The rx interface (shown above) allows standalone reactive values with operator overloading, similar to signified. The Parameterized class-based style provides rich metadata: type checking, bounds, documentation, and introspection. It integrates deeply with the HoloViz ecosystem (Panel, HoloViews).

Performance¶

Benchmarks were run with signified-bench at commit 36e10c9edab4202dd30b5c2950b8cb6f29215eda using pytest-benchmark. The versions compared here were signified==0.4.0, reaktiv==0.21.3, and param==2.3.3, run on a MacBook M1 Max. These numbers are meant to give a broad sense of performance rather than serve as a fully rigorous benchmark suite. Results show median wall-clock time per scenario (lower is better).

signified 0.4.0 vs reaktiv vs param¶

With 0.4.0, signified and reaktiv are closely matched in terms of single threaded performance. The amount of overhead either library would introduce is small compared to whatever work would typically be done within non-toy computed functions.

param is significantly slower.

Scenario	signified 0.4.0	reaktiv	param
`signal_read_write`	8 ms	7 ms	204 ms
`multi_input_computed`	26 ms	36 ms	421 ms
`shared_dependency_branches`	26ms	28 ms	613 ms
`shared_clock_reads`	47 ms	49 ms	1240 ms
`deep_chain_updates`	120 ms	134 ms	1576 ms
`fanout_updates`	206 ms	236 ms	3593 ms
`diamond_updates`	224 ms	257 ms	3933 ms
`effect_fanout_updates`	494 ms	1501 ms	3156 ms

signified 0.4.0 is a substantial performance release. Across all scenarios it runs roughly 2.5–3× faster than 0.3.2.

Choosing a library¶

Choose signified if you want Pythonic syntax, operator overloading, and competitive performance. However, signified does not support async and is not threadsafe.

Choose reaktiv if you prefer an explicit, Angular-inspired API where every dependency is a function call, or if you need built-in async resource loading.

Choose param if you are building UI components in the HoloViz ecosystem (Panel, HoloViews).

Other libraries that are not comparable to `signified`¶

ReactiveX (rxpy) works with processing asynchronous streams of data with operators. It is an inherently different computation model at its core, even if it looks similar at first glance.