The interact
function (ipywidgets.interact
) automatically creates user interface (UI) controls for exploring code and data interactively. It is the easiest way to get started using IPython's widgets.
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# Start with some imports!
from __future__ import print_function
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
At the most basic level, interact
auto-generates UI controls for function arguments, and then calls the function with those arguments when you manipulate the controls interactively. To use interact
, you need to define a function that you want to explore. Here is a function that prints its only argument x
.
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# Very basic function
def f(x):
return x
When you pass this function as the first argument to interact
along with an integer keyword argument (x=10
), a slider is generated and bound to the function parameter. Note that the semicolon here just prevents an out cell from showing up.
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# Generate a slider to interact with
interact(f, x=10,);
When you move the slider, the function is called, which prints the current value of x
.
If you pass True
or False
, interact
will generate a check-box:
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# Booleans generate check-boxes
interact(f, x=True);
If you pass a string, interact
will generate a text area.
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# Strings generate text areas
interact(f, x='Hi there!');
interact
can also be used as a decorator. This allows you to define a function and interact with it in a single shot. As this example shows, interact
also works with functions that have multiple arguments.
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# Using a decorator!
@interact(x=True, y=1.0)
def g(x, y):
return (x, y)
There are times when you may want to explore a function using interact
, but fix one or more of its arguments to specific values. This can be accomplished by wrapping values with the fixed
function.
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# Again, a simple function
def h(p, q):
return (p, q)
When we call interact
, we pass fixed(20)
for q to hold it fixed at a value of 20
.
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interact(h, p=5, q=fixed(20));
Notice that a slider is only produced for p
as the value of q
is fixed.
When you pass an integer-valued keyword argument of 10
(x=10
) to interact
, it generates an integer-valued slider control with a range of $[-10,+3\times10]$. In this case, 10
is an abbreviation for an actual slider widget:
IntSlider(min=-10,max=30,step=1,value=10)
In fact, we can get the same result if we pass this IntSlider
as the keyword argument for x
:
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# Can call the IntSlider to get more specific
interact(f, x=widgets.IntSlider(min=-10,max=30,step=1,value=10));
This examples clarifies how interact
process its keyword arguments:
Widget
instance with a value
attribute, that widget is used. Any widget with a value
attribute can be used, even custom ones.The following table gives an overview of different widget abbreviations:
Keyword argument | Widget |
`True` or `False` | Checkbox |
`'Hi there'` | Text |
`value` or `(min,max)` or `(min,max,step)` if integers are passed | IntSlider |
`value` or `(min,max)` or `(min,max,step)` if floats are passed | FloatSlider |
`('orange','apple')` or `{'one':1,'two':2}` | Dropdown |
You have seen how the check-box and text-area widgets work above. Here, more details about the different abbreviations for sliders and drop-downs are given.
If a 2-tuple of integers is passed (min,max)
, an integer-valued slider is produced with those minimum and maximum values (inclusively). In this case, the default step size of 1
is used.
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# Min,Max slider with Tuples
interact(f, x=(0,4));
If a 3-tuple of integers is passed (min,max,step)
, the step size can also be set.
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# (min, max, step)
interact(f, x=(0,8,2));
A float-valued slider is produced if the elements of the tuples are floats. Here the minimum is 0.0
, the maximum is 10.0
and step size is 0.1
(the default).
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interact(f, x=(0.0,10.0));
The step size can be changed by passing a third element in the tuple.
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interact(f, x=(0.0,10.0,0.01));
For both integer and float-valued sliders, you can pick the initial value of the widget by passing a default keyword argument to the underlying Python function. Here we set the initial value of a float slider to 5.5
.
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@interact(x=(0.0,20.0,0.5))
def h(x=5.5):
return x
Dropdown menus are constructed by passing a tuple of strings. In this case, the strings are both used as the names in the drop-down menu UI and passed to the underlying Python function.
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interact(f, x=('apples','oranges'));
If you want a drop-down menu that passes non-string values to the Python function, you can pass a dictionary. The keys in the dictionary are used for the names in the drop-down menu UI and the values are the arguments that are passed to the underlying Python function.
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interact(f, x={'one': 10, 'two': 20});
If you are using Python 3, you can also specify widget abbreviations using function annotations.
Define a function with a checkbox widget abbreviation for the argument x
.
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def f(x:True): # python 3 only
return x
Then, because the widget abbreviation has already been defined, you can call interact
with a single argument.
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interact(f);
If you are running Python 2, function annotations can be defined using the @annotate
function.
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from IPython.utils.py3compat import annotate
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@annotate(x=True)
def f(x):
return x
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interact(f);
In addition to interact
, IPython provides another function, interactive
, that is useful when you want to reuse the widgets that are produced or access the data that is bound to the UI controls.
Here is a function that returns the sum of its two arguments.
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def f(a, b):
return a+b
Unlike interact
, interactive
returns a Widget
instance rather than immediately displaying the widget.
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w = interactive(f, a=10, b=20)
The widget is a Box
, which is a container for other widgets.
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type(w)
Out[67]:
The children of the Box
are two integer-valued sliders produced by the widget abbreviations above.
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w.children
Out[68]:
To actually display the widgets, you can use IPython's display
function.
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from IPython.display import display
display(w)
At this point, the UI controls work just like they would if interact
had been used. You can manipulate them interactively and the function will be called. However, the widget instance returned by interactive
also give you access to the current keyword arguments and return value of the underlying Python function.
Here are the current keyword arguments. If you rerun this cell after manipulating the sliders, the values will have changed.
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w.kwargs
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Here is the current return value of the function.
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w.result
Out[71]: