reactive.isolate
reactive.isolate()
Create a non-reactive scope within a reactive scope.
Ordinarily, the simple act of reading a reactive value causes a relationship to be established between the caller and the reactive value, where a change to the reactive value will cause the caller to re-execute. (The same applies for the act of getting a reactive calculation's value.) with isolate() lets you read a reactive value or calculation without establishing this relationship.
with isolate() can also be useful for calling reactive calculations at the console, which can be useful for debugging. To do so, wrap the calls to the reactive calculation with with isolate().
Returns
| Type | Description |
|---|---|
| Generator[None, None, None] | A context manager that executes the given expression in a scope where reactive values can be read, but do not cause the reactive scope of the caller to be re-evaluated when they change. |
See Also
Examples
#| standalone: true
#| components: [editor, viewer]
#| layout: vertical
#| viewerHeight: 400
## file: app.py
import matplotlib.pyplot as plt
import numpy as np
from shiny import App, Inputs, Outputs, Session, reactive, render, ui
app_ui = ui.page_fluid(
ui.input_slider("n", "Number of observations", min=0, max=1000, value=500),
ui.input_action_button("go", "Go!", class_="btn-success"),
ui.output_plot("plot"),
)
def server(input: Inputs, output: Outputs, session: Session):
@render.plot(alt="A histogram")
def plot():
# Take a reactive dependency on the action button...
input.go()
# ...but don't take a reactive dependency on the slider
with reactive.isolate():
np.random.seed(19680801)
x = 100 + 15 * np.random.randn(input.n())
fig, ax = plt.subplots()
ax.hist(x, bins=30, density=True)
return fig
app = App(app_ui, server)