This release is a pre-release and may not be stable for production use.
signals
primitives for transparent reactive programming in python
install
pip install signals
usage
from signals import Signal, effect
a = Signal(0)
b = Signal(2)
def c():
return a() + b()
print(c()) # 2
a.set(1)
print(c()) # 3
b.set(3)
print(c()) # 4
# Log the values of a, b, c whenever one changes
@effect
def log_abc():
print(a(), b(), c())
a.set(2) # prints (2, 3, 5)
cell magic
we also provide a ipython cell magic %%effect, which offers a convenient way
re-execute cells that use signals.
In[1]:
%load_ext signals
from signals import Signal
a = Signal(0)
b = Signal(2)
In[2]:
%%effect
a() + b() # re-evaluates the cell whenever a or b changes
In[3]:
a.set(1)
what
signals is an implementation of transparent reactive programming (TRP) for
Python.
TRP is a declarative programming paradigm for expressing relationships between values that vary over time. These time-varying values are known as signals. Whenever a signal changes, the system automatically updates all dependents.
Spreadsheets are the classic example of TRP: cells linked by formulas update automatically when values change. The system discovers dependencies by observing data access, dynamically constructing a dependency graph.
The key features of TRP include:
- declarative: the programmer specifies relationships between values
- transparent: the system (not the programmer) automatically tracks dependencies
- efficient: the system performs only the necessary computations to ensure relationships hold over time
why
TL;DR - TRP is a natural fit for interactive computing but has so far lacked the right interface in popular tools to go mainstream. You can read more of my unfinished thoughts on this topic.
development
this project uses uv for development.
uv run ruff check # lints code
uv run ruff format # formats code
uv run pytest # run tests
2 maintainers
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