# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
"""Interact with functions using widgets."""
from collections.abc import Iterable, Mapping
from inspect import signature, Parameter
from inspect import getcallargs
from inspect import getfullargspec as check_argspec
import sys
from IPython import get_ipython
from . import (Widget, ValueWidget, Text,
FloatSlider, IntSlider, Checkbox, Dropdown,
VBox, Button, DOMWidget, Output)
from IPython.display import display, clear_output
from traitlets import HasTraits, Any, Unicode, observe
from numbers import Real, Integral
from warnings import warn
empty = Parameter.empty
[docs]def show_inline_matplotlib_plots():
"""Show matplotlib plots immediately if using the inline backend.
With ipywidgets 6.0, matplotlib plots don't work well with interact when
using the inline backend that comes with ipykernel. Basically, the inline
backend only shows the plot after the entire cell executes, which does not
play well with drawing plots inside of an interact function. See
https://github.com/jupyter-widgets/ipywidgets/issues/1181/ and
https://github.com/ipython/ipython/issues/10376 for more details. This
function displays any matplotlib plots if the backend is the inline backend.
"""
if 'matplotlib' not in sys.modules:
# matplotlib hasn't been imported, nothing to do.
return
try:
import matplotlib as mpl
from ipykernel.pylab.backend_inline import flush_figures
except ImportError:
return
if (mpl.get_backend() == 'module://ipykernel.pylab.backend_inline' or
mpl.get_backend() == 'module://matplotlib_inline.backend_inline'):
flush_figures()
[docs]def interactive_output(f, controls):
"""Connect widget controls to a function.
This function does not generate a user interface for the widgets (unlike `interact`).
This enables customisation of the widget user interface layout.
The user interface layout must be defined and displayed manually.
"""
out = Output()
def observer(change):
kwargs = {k:v.value for k,v in controls.items()}
show_inline_matplotlib_plots()
with out:
clear_output(wait=True)
f(**kwargs)
show_inline_matplotlib_plots()
for k,w in controls.items():
w.observe(observer, 'value')
show_inline_matplotlib_plots()
observer(None)
return out
def _matches(o, pattern):
"""Match a pattern of types in a sequence."""
if not len(o) == len(pattern):
return False
comps = zip(o,pattern)
return all(isinstance(obj,kind) for obj,kind in comps)
def _get_min_max_value(min, max, value=None, step=None):
"""Return min, max, value given input values with possible None."""
# Either min and max need to be given, or value needs to be given
if value is None:
if min is None or max is None:
raise ValueError('unable to infer range, value from: ({}, {}, {})'.format(min, max, value))
diff = max - min
value = min + (diff / 2)
# Ensure that value has the same type as diff
if not isinstance(value, type(diff)):
value = min + (diff // 2)
else: # value is not None
if not isinstance(value, Real):
raise TypeError('expected a real number, got: %r' % value)
# Infer min/max from value
if value == 0:
# This gives (0, 1) of the correct type
vrange = (value, value + 1)
elif value > 0:
vrange = (-value, 3*value)
else:
vrange = (3*value, -value)
if min is None:
min = vrange[0]
if max is None:
max = vrange[1]
if step is not None:
# ensure value is on a step
tick = int((value - min) / step)
value = min + tick * step
if not min <= value <= max:
raise ValueError('value must be between min and max (min={}, value={}, max={})'.format(min, value, max))
return min, max, value
def _yield_abbreviations_for_parameter(param, kwargs):
"""Get an abbreviation for a function parameter."""
name = param.name
kind = param.kind
default = param.default
not_found = (name, empty, empty)
if kind in (Parameter.POSITIONAL_OR_KEYWORD, Parameter.KEYWORD_ONLY):
if name in kwargs:
value = kwargs.pop(name)
elif default is not empty:
value = default
else:
yield not_found
yield (name, value, default)
elif kind == Parameter.VAR_KEYWORD:
# In this case name=kwargs and we yield the items in kwargs with their keys.
for k, v in kwargs.copy().items():
kwargs.pop(k)
yield k, v, empty
[docs]class interactive(VBox):
"""
A VBox container containing a group of interactive widgets tied to a
function.
Parameters
----------
__interact_f : function
The function to which the interactive widgets are tied. The `**kwargs`
should match the function signature.
__options : dict
A dict of options. Currently, the only supported keys are
``"manual"`` (defaults to ``False``), ``"manual_name"`` (defaults
to ``"Run Interact"``) and ``"auto_display"`` (defaults to ``False``).
**kwargs : various, optional
An interactive widget is created for each keyword argument that is a
valid widget abbreviation.
Note that the first two parameters intentionally start with a double
underscore to avoid being mixed up with keyword arguments passed by
``**kwargs``.
"""
[docs] def __init__(self, __interact_f, __options={}, **kwargs):
VBox.__init__(self, _dom_classes=['widget-interact'])
self.result = None
self.args = []
self.kwargs = {}
self.f = f = __interact_f
self.clear_output = kwargs.pop('clear_output', True)
self.manual = __options.get("manual", False)
self.manual_name = __options.get("manual_name", "Run Interact")
self.auto_display = __options.get("auto_display", False)
new_kwargs = self.find_abbreviations(kwargs)
# Before we proceed, let's make sure that the user has passed a set of args+kwargs
# that will lead to a valid call of the function. This protects against unspecified
# and doubly-specified arguments.
try:
check_argspec(f)
except TypeError:
# if we can't inspect, we can't validate
pass
else:
getcallargs(f, **{n:v for n,v,_ in new_kwargs})
# Now build the widgets from the abbreviations.
self.kwargs_widgets = self.widgets_from_abbreviations(new_kwargs)
# This has to be done as an assignment, not using self.children.append,
# so that traitlets notices the update. We skip any objects (such as fixed) that
# are not DOMWidgets.
c = [w for w in self.kwargs_widgets if isinstance(w, DOMWidget)]
# If we are only to run the function on demand, add a button to request this.
if self.manual:
self.manual_button = Button(description=self.manual_name)
c.append(self.manual_button)
self.out = Output()
c.append(self.out)
self.children = c
# Wire up the widgets
# If we are doing manual running, the callback is only triggered by the button
# Otherwise, it is triggered for every trait change received
# On-demand running also suppresses running the function with the initial parameters
if self.manual:
self.manual_button.on_click(self.update)
# Also register input handlers on text areas, so the user can hit return to
# invoke execution.
for w in self.kwargs_widgets:
if isinstance(w, Text):
w.continuous_update = False
w.observe(self.update, names='value')
else:
for widget in self.kwargs_widgets:
widget.observe(self.update, names='value')
self.update()
# Callback function
[docs] def update(self, *args):
"""
Call the interact function and update the output widget with
the result of the function call.
Parameters
----------
*args : ignored
Required for this method to be used as traitlets callback.
"""
self.kwargs = {}
if self.manual:
self.manual_button.disabled = True
try:
show_inline_matplotlib_plots()
with self.out:
if self.clear_output:
clear_output(wait=True)
for widget in self.kwargs_widgets:
value = widget.get_interact_value()
self.kwargs[widget._kwarg] = value
self.result = self.f(**self.kwargs)
show_inline_matplotlib_plots()
if self.auto_display and self.result is not None:
display(self.result)
except Exception as e:
ip = get_ipython()
if ip is None:
self.log.warning("Exception in interact callback: %s", e, exc_info=True)
else:
ip.showtraceback()
finally:
if self.manual:
self.manual_button.disabled = False
# Find abbreviations
def signature(self):
return signature(self.f)
[docs] def find_abbreviations(self, kwargs):
"""Find the abbreviations for the given function and kwargs.
Return (name, abbrev, default) tuples.
"""
new_kwargs = []
try:
sig = self.signature()
except (ValueError, TypeError):
# can't inspect, no info from function; only use kwargs
return [ (key, value, value) for key, value in kwargs.items() ]
for param in sig.parameters.values():
for name, value, default in _yield_abbreviations_for_parameter(param, kwargs):
if value is empty:
raise ValueError('cannot find widget or abbreviation for argument: {!r}'.format(name))
new_kwargs.append((name, value, default))
return new_kwargs
# Abbreviations to widgets
# Return a factory for interactive functions
@classmethod
def factory(cls):
options = dict(manual=False, auto_display=True, manual_name="Run Interact")
return _InteractFactory(cls, options)
class _InteractFactory:
"""
Factory for instances of :class:`interactive`.
This class is needed to support options like::
>>> @interact.options(manual=True)
... def greeting(text="World"):
... print("Hello {}".format(text))
Parameters
----------
cls : class
The subclass of :class:`interactive` to construct.
options : dict
A dict of options used to construct the interactive
function. By default, this is returned by
``cls.default_options()``.
kwargs : dict
A dict of **kwargs to use for widgets.
"""
def __init__(self, cls, options, kwargs={}):
self.cls = cls
self.opts = options
self.kwargs = kwargs
def widget(self, f):
"""
Return an interactive function widget for the given function.
The widget is only constructed, not displayed nor attached to
the function.
Returns
-------
An instance of ``self.cls`` (typically :class:`interactive`).
Parameters
----------
f : function
The function to which the interactive widgets are tied.
"""
return self.cls(f, self.opts, **self.kwargs)
def __call__(self, __interact_f=None, **kwargs):
"""
Make the given function interactive by adding and displaying
the corresponding :class:`interactive` widget.
Expects the first argument to be a function. Parameters to this
function are widget abbreviations passed in as keyword arguments
(``**kwargs``). Can be used as a decorator (see examples).
Returns
-------
f : __interact_f with interactive widget attached to it.
Parameters
----------
__interact_f : function
The function to which the interactive widgets are tied. The `**kwargs`
should match the function signature. Passed to :func:`interactive()`
**kwargs : various, optional
An interactive widget is created for each keyword argument that is a
valid widget abbreviation. Passed to :func:`interactive()`
Examples
--------
Render an interactive text field that shows the greeting with the passed in
text::
# 1. Using interact as a function
def greeting(text="World"):
print("Hello {}".format(text))
interact(greeting, text="Jupyter Widgets")
# 2. Using interact as a decorator
@interact
def greeting(text="World"):
print("Hello {}".format(text))
# 3. Using interact as a decorator with named parameters
@interact(text="Jupyter Widgets")
def greeting(text="World"):
print("Hello {}".format(text))
Render an interactive slider widget and prints square of number::
# 1. Using interact as a function
def square(num=1):
print("{} squared is {}".format(num, num*num))
interact(square, num=5)
# 2. Using interact as a decorator
@interact
def square(num=2):
print("{} squared is {}".format(num, num*num))
# 3. Using interact as a decorator with named parameters
@interact(num=5)
def square(num=2):
print("{} squared is {}".format(num, num*num))
"""
# If kwargs are given, replace self by a new
# _InteractFactory with the updated kwargs
if kwargs:
kw = dict(self.kwargs)
kw.update(kwargs)
self = type(self)(self.cls, self.opts, kw)
f = __interact_f
if f is None:
# This branch handles the case 3
# @interact(a=30, b=40)
# def f(*args, **kwargs):
# ...
#
# Simply return the new factory
return self
# positional arg support in: https://gist.github.com/8851331
# Handle the cases 1 and 2
# 1. interact(f, **kwargs)
# 2. @interact
# def f(*args, **kwargs):
# ...
w = self.widget(f)
try:
f.widget = w
except AttributeError:
# some things (instancemethods) can't have attributes attached,
# so wrap in a lambda
f = lambda *args, **kwargs: __interact_f(*args, **kwargs)
f.widget = w
show_inline_matplotlib_plots()
display(w)
return f
def options(self, **kwds):
"""
Change options for interactive functions.
Returns
-------
A new :class:`_InteractFactory` which will apply the
options when called.
"""
opts = dict(self.opts)
for k in kwds:
try:
# Ensure that the key exists because we want to change
# existing options, not add new ones.
_ = opts[k]
except KeyError:
raise ValueError("invalid option {!r}".format(k))
opts[k] = kwds[k]
return type(self)(self.cls, opts, self.kwargs)
interact = interactive.factory()
interact_manual = interact.options(manual=True, manual_name="Run Interact")
[docs]class fixed(HasTraits):
"""A pseudo-widget whose value is fixed and never synced to the client."""
value = Any(help="Any Python object")
description = Unicode('', help="Any Python object")
[docs] def __init__(self, value, **kwargs):
super().__init__(value=value, **kwargs)
[docs] def get_interact_value(self):
"""Return the value for this widget which should be passed to
interactive functions. Custom widgets can change this method
to process the raw value ``self.value``.
"""
return self.value
Try Jupyter Widgets