class SimpleWatchExample(param.Parameterized):
a = param.Parameter(default=0)
b = param.Parameter(default=0)
c = param.Parameter(default=0)
d = param.Integer(default=0)
e = param.Event()
f = param.Event()
def method(self, event):
self.b = self.a * 2
class Transform(param.Parameterized):
"""Gets data and applies transform"""
_type = "base"
widgets = param.Dict(default={})
updated = param.Event()
redrawn = param.Event(
doc="event gets triggered when widgets are changed and the controller needs to redraw them"
)
_hash = param.Integer(doc="Hash of current transform state")
_cache = param.ClassSelector(default=Cache(), class_=Cache)
def __init__(self, **params):
super().__init__(**params)
# perhaps htey should all be private to prevent namespace collision with filter options
@property
def source_hash(self):
return self.source.hash
@property
def hash_key(self):
"""hashable key describing the transform"""
excluded = ["updated", "source", "widgets"]
return tuple(
(item, make_tuple(val))
for item, val in self.param.get_param_values()
if not (item.startswith("_") or item in excluded)
)
@property
def hash(self):
tup = (*self.hash_key, self.source_hash)
return hash(tup)
def update_hash(self):
if self.hash == self._hash:
return False
else:
self._hash = self.hash
return True
def update(self):
if self.update_hash():
self._update_options() # todo this shouldnt be here
self.updated = True
class Button(_ClickButton):
clicks = param.Integer(default=0)
value = param.Event()
_rename = {'clicks': None, 'name': 'label', 'value': None}
_widget_type = _BkButton
def _server_click(self, doc, ref, event):
processing = bool(self._events)
self._events.update({"clicks": self.clicks + 1})
self.param.trigger('value')
if not processing:
if doc.session_context:
doc.add_timeout_callback(partial(self._change_coroutine, doc),
self._debounce)
else:
self._change_event(doc)
def _process_property_change(self, msg):
msg = super()._process_property_change(msg)
if 'clicks' in msg:
msg['clicks'] = self.clicks + 1
return msg
def on_click(self, callback):
self.param.watch(callback, 'clicks', onlychanged=False)
class WebAppTransform(param.Parameterized): #todo subclass from Transform?
updated = param.Event()
def __init__(self, **params):
super().__init__(**params)
self.widgets = self.generate_widgets()
@property
def panel(self):
return pn.Column(*self.widgets.values())
# widget = self.widget.clone()
# self.widget.link(widget, value='value', bidirectional=True)
# return widget
def generate_widgets(self, **kwargs):
"""returns a dict with keys parameter names and values default mapped widgets"""
names = [
p for p in self.param
if self.param[p].precedence is None or self.param[p].precedence > 1
]
widgets = pn.Param(self.param,
show_name=False,
show_labels=True,
widgets=kwargs)
return {k: v for k, v in zip(names[1:], widgets)}
class Source(param.Parameterized):
"""Base class for sources"""
_type = "base"
updated = param.Event()
def get(self):
raise NotImplementedError()
class Button(_ClickButton):
clicks = param.Integer(default=0)
value = param.Event()
_rename = {'clicks': None, 'name': 'label', 'value': None}
_target_transforms = {'event:button_click': None, 'value': None}
_widget_type = _BkButton
@property
def _linkable_params(self):
return super()._linkable_params + ['value']
def jslink(self,
target,
code=None,
args=None,
bidirectional=False,
**links):
links = {
'event:' + self._event if p == 'value' else p: v
for p, v in links.items()
}
super().jslink(target, code, args, bidirectional, **links)
jslink.__doc__ = Widget.jslink.__doc__
def _server_click(self, doc, ref, event):
processing = bool(self._events)
self._events.update({"clicks": self.clicks + 1})
self.param.trigger('value')
if not processing:
if doc.session_context:
doc.add_timeout_callback(partial(self._change_coroutine, doc),
self._debounce)
else:
self._change_event(doc)
def _process_property_change(self, msg):
msg = super()._process_property_change(msg)
if 'clicks' in msg:
msg['clicks'] = self.clicks + 1
return msg
def on_click(self, callback):
self.param.watch(callback, 'clicks', onlychanged=False)
class TestButton(param.Parameterized):
action = param.Action(lambda x: x._print_something())
event = param.Event()
updating = param.Boolean()
view = param.Parameter(precedence=-1)
def __init__(self, **params):
super().__init__(**params)
self.view = self._create_view()
@param.depends("event", watch=True)
def _print_something(self):
if self.updating:
return
self.updating = True
print(f"event: {self.event}, action: {self.action}")
time.sleep(1)
self.updating = False
@param.depends("updating", watch=True)
def toggle_loading(self):
self._action_button.loading = self.updating
self._event_button.loading = self.updating
def _create_view(self):
widgets = pn.Param(
self,
parameters=["action", "event", "updating"],
widgets={
"action": {
"button_type": "primary"
},
"event": {
"button_type": "success"
},
"updating": {
"disabled": True
},
},
)
self._action_button = widgets[1]
self._event_button = widgets[2]
self._updating_checkbox = widgets[3]
return widgets
class TestButton(param.Parameterized):
action = param.Action(lambda x: x._print_something())
event = param.Event()
updating = param.Boolean()
@param.depends("event", watch=True)
def _print_something(self):
if self.updating:
return
self.updating = True
print(f"event: {self.event}, action: {self.action}")
time.sleep(1)
self.updating = False
class OptsBase(param.Parameterized):
_type = None
updated = param.Event()
def __init__(self, **params):
super().__init__(**params)
self._excluded_from_opts = ["name"
] # todo remove this and opts property
self.widgets = self.generate_widgets()
@property
def panel(self):
return pn.Column(*self.widgets.values())
@property
def opts(self):
opts = {
name: self.param[name]
for name in self.param if name not in self._excluded_from_opts
}
return opts
def generate_widgets(self, **kwargs):
"""returns a dict with keys parameter names and values default mapped widgets"""
# todo base class?
names = [
p for p in self.param
if self.param[p].precedence is None or self.param[p].precedence > 1
]
widgets = pn.Param(self.param,
show_name=False,
show_labels=True,
widgets=kwargs)
return {k: v for k, v in zip(names[1:], widgets)}
class WebAppFilter(Filter):
"""
"""
source = param.ClassSelector(Source)
# maybe instead of making filters co-dependent the second filter should have a DerivedSource
# but we'll deal with this later
filters = param.List()
updated = param.Event()
def __init__(self, **params):
super().__init__(**params)
if self.source:
self.source.param.watch(self.update, 'updated')
for filt in self.filters:
filt.param.watch(self.update, 'updated')
def get_data(self):
"""Equivalent to view's get_data method"""
query = {
filt.field: filt.query
for filt in self.filters if filt.query is not None and (
filt.table is None or filt.table == self.table)
}
data = self.source.get(self.table, **query)
return data
@param.depends('value', watch=True)
def update(self, *events):
"""gets called when the source event triggers"""
self.updated = True
class SpeechToText(Widget):
"""
The SpeechToText widget controls the speech recognition service of
the browser.
It wraps the HTML5 SpeechRecognition API. See
https://developer.mozilla.org/en-US/docs/Web/API/SpeechRecognition
This functionality is **experimental** and only supported by
Chrome and a few other browsers. Checkout
https://caniuse.com/speech-recognition for a up to date list of
browsers supporting the SpeechRecognition Api. Or alternatively
https://developer.mozilla.org/en-US/docs/Web/API/SpeechRecognition#Browser_compatibility
On some browsers, like Chrome, using Speech Recognition on a web
page involves a server-based recognition engine. Your audio is
sent to a web service for recognition processing, so it won't work
offline. Whether this is secure and confidential enough for your
use case is up to you to evaluate.
"""
abort = param.Event(doc="""
Stops the speech recognition service from listening to
incoming audio, and doesn't attempt to return a
RecognitionResult.""")
start = param.Event(doc="""
Starts the speech recognition service listening to incoming
audio with intent to recognize grammars associated with the
current SpeechRecognition.""")
stop = param.Event(doc="""
Stops the speech recognition service from listening to
incoming audio, and attempts to return a RecognitionResult
using the audio captured so far.""")
lang = param.ObjectSelector(default="",
objects=[""] + LANGUAGE_CODES,
allow_None=True,
label="Language",
doc="""
The language of the current SpeechRecognition in BCP 47
format. For example 'en-US'. If not specified, this defaults
to the HTML lang attribute value, or the user agent's language
setting if that isn't set either. """)
continuous = param.Boolean(default=False,
doc="""
Controls whether continuous results are returned for each
recognition, or only a single result. Defaults to False""")
interim_results = param.Boolean(default=False,
doc="""
Controls whether interim results should be returned (True) or
not (False.) Interim results are results that are not yet
final (e.g. the RecognitionResult.is_final property is
False).""")
max_alternatives = param.Integer(default=1,
bounds=(1, 5),
doc="""
Sets the maximum number of RecognitionAlternatives provided
per result. A number between 1 and 5. The default value is
1.""")
service_uri = param.String(doc="""
Specifies the location of the speech recognition service used
by the current SpeechRecognition to handle the actual
recognition. The default is the user agent's default speech
service.""")
grammars = param.ClassSelector(class_=GrammarList,
doc="""
A GrammarList object that represents the grammars that will be
understood by the current SpeechRecognition service""")
button_hide = param.Boolean(default=False,
label="Hide the Button",
doc="""
If True no button is shown. If False a toggle Start/ Stop button is shown."""
)
button_type = param.ObjectSelector(default="light",
objects=BUTTON_TYPES,
doc="""
The button styling.""")
button_not_started = param.String(label="Button Text when not started",
doc="""
The text to show on the button when the SpeechRecognition
service is NOT started. If '' a *muted microphone* icon is
shown.""")
button_started = param.String(label="Button Text when started",
doc="""
The text to show on the button when the SpeechRecognition
service is started. If '' a *muted microphone* icon is
shown.""")
started = param.Boolean(constant=True,
doc="""
Returns True if the Speech Recognition Service is started and
False otherwise.""")
audio_started = param.Boolean(constant=True,
doc="""
Returns True if the Audio is started and False otherwise.""")
sound_started = param.Boolean(constant=True,
doc="""
Returns True if the Sound is started and False otherwise.""")
speech_started = param.Boolean(constant=True,
doc="""
Returns True if the the User has started speaking and False otherwise."""
)
results = param.List(constant=True,
doc="""
The `results` as a list of Dictionaries.""")
value = param.String(constant=True,
label="Last Result",
doc="""
The transcipt of the highest confidence RecognitionAlternative
of the last RecognitionResult. Please note we strip the
transcript for leading spaces.""")
_grammars = param.List(constant=True,
doc="""
List used to transfer the serialized grammars from server to
browser.""")
_widget_type = _BkSpeechToText
_rename = {
"value": None,
"grammars": None,
"_grammars": "grammars",
}
def __init__(self, **params):
super().__init__(**params)
if self.grammars:
self._update_grammars()
def __repr__(self, depth=None):
# Custom repr needed to avoid infinite recursion because this Parameterized class has
# multiple actions
return f"SpeechToText(name='{self.name}')"
@param.depends("grammars", watch=True)
def _update_grammars(self):
with param.edit_constant(self):
if self.grammars:
self._grammars = self.grammars.serialize() # pylint: disable=no-member
else:
self._grammars = []
@param.depends("results", watch=True)
def _update_results(self):
# pylint: disable=unsubscriptable-object
with param.edit_constant(self):
if self.results and "alternatives" in self.results[-1]:
self.value = (self.results[-1]["alternatives"][0]["transcript"]
).lstrip()
else:
self.value = ""
@property
def results_deserialized(self):
"""
Returns the results as a List of RecognitionResults
"""
return RecognitionResult.create_from_list(self.results)
@property
def results_as_html(self) -> str:
"""
Returns the `results` formatted as html
Convenience method for ease of use
"""
if not self.results:
return "No results"
html = "<div class='pn-speech-recognition-result'>"
total = len(self.results) - 1
for index, result in enumerate(reversed(self.results_deserialized)):
if len(self.results) > 1:
html += f"<h3>Result {total-index}</h3>"
html += f"<span>Is Final: {result.is_final}</span><br/>"
for index2, alternative in enumerate(result.alternatives):
if len(result.alternatives) > 1:
html += f"<h4>Alternative {index2}</h4>"
html += f"""
<span>Confidence: {alternative.confidence:.2f}</span>
</br>
<p>
<strong>{alternative.transcript}</strong>
</p>
"""
html += "</div>"
return html
class GridEditor(param.Parameterized):
"""
Interactive boundary editor for previewing and generating pygridgen grids.
Core features:
* Add, drag and delete nodes interactively with the PointsDraw tool
* Toggle their polarity (beta) value with the Tap Tool
* Insert nodes into selected edges after selecting them with the Tap Tool.
* Set a focus function and update the grid
* Pythonic access to the geopandas boundary DataFrame.
* Serializable state to capture editor state between sessions
* Customizable background tile sources or background tile elements.
For more information please visit https://github.com/pygridgen/hologridgen
"""
# Algorithmic parameters hidden from the GUI
max_nodes = param.Integer(default=1000, precedence=-1,
doc = "Maximum number of nodes in a boundary")
ul_idx=param.Integer(default=0, precedence=-1,
doc='Upper left index: parameter of grid generation')
polarity_value = param.Dict(default={'+':1, '0':0, '-':-1}, precedence=-1, doc="""
Beta values to associate with the three node polarities (positive
'+', neutral '0' and negative '-'). Setting '+':4/3 for instance
enables grid generation with only three positive nodes.""")
# Parameters not in the GUI for Pythonic data access
focus = param.ClassSelector(default=None, class_=pgg.Focus,
allow_None=True, precedence=-1, doc="""
Parameter that can be set to a pygridgen Focus object (or None).
When set, mesh generation will apply the specified Focus
function.""")
grid = param.ClassSelector(default=None, class_=pgg.grid.Gridgen,
allow_None=True, precedence=-1, doc="""
Parameter that exposes the pygridgen Gridgen object that will be
set after mesh generation """)
ready = param.Boolean(default=False, precedence=-1, doc="""
Boolean predicate indicating readiness for mesh generation: mesh generation
can be executed when the sum of the polarity in the boundary is 4.""")
# User settings hidden from the GUI, settable in the constructor (precedence= -1)
width = param.Integer(default=600, precedence=-1, bounds=(200, 1000),
doc="Width of the HoloViews object corresponding to the editor view area")
height = param.Integer(default=600, precedence=-1, bounds=(200, 1000),
doc="Height of the HoloViews object corresponding to the editor view area")
custom_background = param.Parameter(default=None, precedence=-1, doc="""
Custom HoloViews element to use as the background when the
background parameter is set to 'Custom'.""")
background = param.ObjectSelector('None', objects=TILE_SOURCES.keys(), doc="""
Selector of available default tile sources which can also be set
to 'None' for no background or 'Custom' in which case the
HoloViews/GeoViews element set in the custom_background parameter
(if any) is used as the background.""")
# Customizable HoloViews styles (hidden from the GUI, settable in the constructor)
node_style = param.Dict(dict(cmap={'+': 'red', '-': 'blue', '0':'black'}),
precedence=-1, doc="""
Style options for nodes. Note that the size is overidden by the
node_size param controllable in the GUI and the polarity colors
can be changed by setting the cmap dictionary.""")
mesh_style = param.Dict(dict(line_width=2, line_alpha=1, line_color='blue'),
precedence=-1, doc="Style options for displayed mesh.")
edge_style = param.Dict(dict(line_width=2, line_alpha=1, line_color='green',
nonselection_color='green', nonselection_alpha=0.5),
precedence=-1, doc="""
Style options for displayed boundary edges. The nonselection_*
options set how deselected edges appear when the Tap tool is used
to insert new nodes into edges""")
start_indicator_style = param.Dict(
dict(marker='triangle', angle=30, fill_alpha=0, size=30, color='black'),
precedence=-1, doc="""
Style of the start marker indicating the first boundary
point. Default is a triangle that can be rotated by setting the
'angle' keyword.""")
# GUI controllable parameters
node_size = param.Integer(default=10, bounds=(1,200),
doc="Size of nodes used to mark the boundary.")
edge_width = param.Integer(default=2, bounds=(1,50), doc="Width of the boundary edges")
xres = param.Integer(default=50, bounds=(2, None), doc="""
X resolution of the generated grid""")
yres = param.Integer(default=50, bounds=(2, None), doc="""
Y resolution of the generated grid""")
generate_mesh = param.Event(doc='Event that runs mesh generation')
hide_mesh = param.Event(doc='Event that clears displayed mesh')
insert_points = param.Event(
doc='Event that inserts a new node into an edge selected with the Tap tool')
_columns = ['color', 'polarity', 'x', 'y']
def __init__(self, data=None, **params):
data_params = {} if data is None else {k:v for k,v in data.items()
if k not in self._columns}
params = dict(data_params, **params)
data = {k:[] for k in self._columns} if (data is None) else data
super().__init__(**params)
def install_handle(plot, element):
"Handle needed to make the draw_tool available in the JS callback"
plot.handles['draw_tool'] = plot.state.tools[-1]
node_style = dict(self.node_style,
tools=['tap'],
color=hv.dim('polarity'),
fill_alpha=hv.dim('polarity').categorize({'0':0, '+':1, '-':1 }),
show_legend=False, hooks=[install_handle])
# PointDraw Stream that enables the PointDraw Bokeh tool
self._node_stream = hv.streams.PointDraw(data=data,
num_objects=self.max_nodes,
empty_value = '+')
# Nodes is a DynamicMap returning hv.Points along the boundary
self.nodes = hv.DynamicMap(self.points,
streams=[self._node_stream,
self.param.insert_points,
self.param.node_size]).opts(**node_style)
# DynamicMap drawing the boundary as a hv.Path element
self.boundary_dmap = hv.DynamicMap(self._boundary,
streams=[self._node_stream,
hv.streams.Selection1D()])
# DynamicMap placing the start indicator
self.start_marker = hv.DynamicMap(self._start_marker,
streams=[self._node_stream]
).opts(**self.start_indicator_style)
# Initial, empty mesh
self.qmesh = hv.QuadMesh((np.zeros((2,2)), np.zeros((2,2)), np.zeros((2,2))))
self._selected_edge_index = None
@classmethod
def from_geopandas(cls, df):
"""
Classmethod that allows a GridEditor to be initialized from a
boundary geopandas DataFrame (such as the one available from the
.boundary property).
"""
if len(df) == 0:
return GridEditor()
allowed = [el for el in cls._columns if el != 'geometry']
color_vals = {v:k for k,v in cls.polarity_value.items()}
data = {k:list(v) for k,v in df.to_dict(orient='list').items() if k in allowed}
data['color'] = [color_vals[p] for p in data['polarity']]
data['polarity'] = data['color']
return GridEditor(data)
@property
def boundary(self):
"Property returning the boundary GeoDataFrame"
exclude = ['color', 'fill_alpha']
data = self._node_stream.data
polarity = [self.polarity_value[c] for c in data['color']]
df_data = {c:[el for el in v] for c,v in data.items() if c not in exclude}
df_data['polarity'] = polarity
df = pd.DataFrame(df_data)
return geopandas.GeoDataFrame(df, geometry=geopandas.points_from_xy(df.x, df.y))
@property
def data(self, exclude=['name', 'fill_alpha', 'grid']):
"""
Propery exposing serializable state of the editor that can be
passed into the GridEditor constructor to restore that state
"""
data = {k:[el for el in v] for k,v in self._node_stream.data.items()}
param_data = {p:getattr(self, p) for p in self.param}
data.update(param_data)
return {k:v for k,v in data.items() if k not in exclude}
def _ready(self):
"Predicate method indicating current readiness for mesh generation"
data = self._node_stream.data
if len(data['x']) > 3:
summed = sum(self.polarity_value[el] for el in data['color'])
return (summed == 4)
else:
return False
@pn.depends('ready', watch=True)
def _check_readiness(self):
"Callback used to disable generate mesh button till ready"
for widget in self.widgets:
if isinstance(widget, pn.widgets.button.Button) and (widget.name == 'Generate mesh'):
button = widget
break
button.disabled = not self.ready
@pn.depends('_node_stream.data')
def _geojson(self):
"Callback to generate GeoJSON file when download button is clicked"
boundary = self.boundary
bio = BytesIO()
if len(boundary) != 0:
boundary.to_file(bio, driver='GeoJSON')
bio.seek(0)
return bio
# DynamicMap callbacks
def points(self, data, insert_points, node_size):
"DynamicMap callback returns Points representing boundary nodes"
new_data = {'x': data['x'], 'y': data['y'],
'polarity' : np.array(data['color'], dtype='U1')}
if insert_points and len(self._selected_edge_index)==1:
point_index = self._selected_edge_index[0] + 1
sx, ex = new_data['x'][point_index-1], new_data['x'][point_index]
sy, ey = new_data['y'][point_index-1], new_data['y'][point_index]
new_data['x'] = np.insert(new_data['x'], point_index, (sx+ex) / 2.)
new_data['y'] = np.insert(new_data['y'], point_index, (sy+ey) / 2.)
new_data['polarity'] = np.insert(new_data['polarity'], point_index, '+')
return hv.Points(new_data, vdims=['polarity']).opts(size=node_size)
def _generate_mesh(self, generate_mesh=False, hide_mesh=False):
"Callback returning generated QuadMesh element"
if not self.ready:
return self.qmesh.opts(fill_alpha=0, line_alpha=0)
elif hide_mesh or (not generate_mesh):
return self.qmesh.opts(fill_alpha=0, line_alpha=0)
if self.ready:
gdf = self.boundary
kwargs = dict(shape=(self.xres, self.yres), ul_idx=self.ul_idx)
if self.focus is not None:
kwargs['focus'] = self.focus
self.grid = pgg.Gridgen(gdf.geometry.x, gdf.geometry.y, gdf.polarity, **kwargs)
xdim, ydim = self.grid.x.shape
zs = np.ones((xdim-1, ydim-1))
self.qmesh = hv.QuadMesh((np.array(self.grid.x), np.array(self.grid.y), zs))
return self.qmesh.opts(**self.mesh_style, fill_alpha=0)
def _boundary(self, data, index):
"Callback drawing Path element defining boundary"
self._selected_edge_index = index
xs, ys = data['x'], data['y']
lines = []
for i in range(len(xs)-1):
s, e = i, (i+1)
lines.append([(xs[s], ys[s]), (xs[e], ys[e])])
self.ready = self._ready()
return hv.Path(lines).opts(**self.edge_style)
def _start_marker(self, data):
"Callback to draw the start marker"
if len(data['x']) == 0:
return hv.Points(None)
return hv.Points((data['x'][0], data['y'][0]))
def _background(self, background):
"""
Callback that allows the background to be switched between tile
sources, a custom background element or None for no
background
"""
elements = []
if background != 'None':
elements = [TILE_SOURCES[background].opts(global_extent=True, alpha=1)]
elif background == 'None':
if self.custom_background:
elements = [self.custom_background]
else:
elements = [TILE_SOURCES[list(TILE_SOURCES.keys())[0]].opts(alpha=0)]
return hv.Overlay(elements)
def view(self):
"Main entry point for using the GridEditor after construction"
self.polarity_link = PolaritySwap(self.nodes)
param_stream = hv.streams.Params(self,
['generate_mesh', 'hide_mesh'],
transient=True)
elements = [hv.DynamicMap(self._background, streams=[self.param.background]),
self.boundary_dmap.apply.opts(line_width=self.param.edge_width),
self.start_marker,
self.nodes,
hv.DynamicMap(self._generate_mesh,
streams=[param_stream])]
hvobj = hv.Overlay(elements).collate()
self.widgets = pn.Param(self.param,
widgets={'edge_select_mode': pn.widgets.Toggle})
obj = pn.Row(pn.Column(self.widgets,
pn.widgets.FileDownload(callback=self._geojson,
filename='boundary.geojson')),
hvobj.opts(width=self.width, height=self.height))
self.param.trigger('ready')
return obj
class TextToSpeech(Utterance, Widget):
"""
The `TextToSpeech` widget wraps the HTML5 SpeechSynthesis API
See https://developer.mozilla.org/en-US/docs/Web/API/SpeechSynthesis
Reference: https://panel.holoviz.org/reference/widgets/TextToSpeech.html
:Example:
>>> TextToSpeech(name="Speech Synthesis", value="Data apps are nice")
"""
auto_speak = param.Boolean(default=True,
doc="""
Whether or not to automatically speak when the value changes.""")
cancel = param.Event(doc="""
Removes all utterances from the utterance queue.""")
pause = param.Event(doc="""
Puts the TextToSpeak object into a paused state.""")
resume = param.Event(doc="""
Puts the TextToSpeak object into a non-paused state: resumes
it if it was already paused.""")
paused = param.Boolean(readonly=True,
doc="""
A Boolean that returns true if the TextToSpeak object is in a
paused state.""")
pending = param.Boolean(readonly=True,
doc="""
A Boolean that returns true if the utterance queue contains
as-yet-unspoken utterances.""")
speak = param.Event(doc="""
Speak. I.e. send a new Utterance to the browser""")
speaking = param.Boolean(readonly=True,
doc="""
A Boolean that returns true if an utterance is currently in
the process of being spoken — even if TextToSpeak is in a
paused state.""")
voices = param.List(readonly=True,
doc="""
Returns a list of Voice objects representing all the available
voices on the current device.""")
_voices = param.List()
_widget_type = _BkTextToSpeech
_rename = {
"auto_speak": None,
"lang": None,
"pitch": None,
"rate": None,
"speak": None,
"value": None,
"voice": None,
"voices": None,
"volume": None,
"_voices": "voices",
}
def _process_param_change(self, msg):
speak = msg.get('speak') or ('value' in msg and self.auto_speak)
msg = super()._process_param_change(msg)
if speak:
msg['speak'] = self.to_dict()
return msg
@param.depends("_voices", watch=True)
def _update_voices(self):
voices = []
for _voice in self._voices: # pylint: disable=not-an-iterable
voice = Voice(**_voice)
voices.append(voice)
self.voices = voices
self.set_voices(self.voices)
def __repr__(self, depth=None):
# We need to do this because otherwise a error is raised when used in notebook
# due to infinite recursion
return f"TextToSpeech(name={self.name})"
def __str__(self):
return f"TextToSpeech(name={self.name})"
class DataFrameSource(Source):
tables = param.Dict({}, doc="Dictionary of tables in this Source")
updated = param.Event()
dropna = param.Boolean(
True,
doc=
'Remove rows of all NaN when adding / selecting / removing dataframes'
)
# def __init__(self, **params):
# pass
# super().__init__(**params)
# if self.df.columns.nlevels == 1:
# self.tables = [self.name]
# self.multiindex = False
# elif self.df.columns.nlevels == 2:
# self.multiindex = True
# self.tables = [] # todo populate tables for multiindex
# else:
# raise ValueError("Currently column multiindex beyond two levels is not supported")
def remove_df(self, table, name, level):
raise NotImplementedError('Removing datafarmes not implemented')
self.updated = True
def add_df(self, df, table, names=None):
"""
#Todo method for adding a table to multindex source
Parameters
----------
df
Returns
-------
"""
# todo check if df already present, update?
target_df = self.tables[table]
df = df.copy()
if target_df.columns.nlevels != df.columns.nlevels:
if isinstance(names, str):
names = [names]
if len(names) != target_df.columns.nlevels - df.columns.nlevels:
raise ValueError(
f"Insufficient names provided to match target dataframe multindex level {df.columns.nlevels}"
)
if df.columns.nlevels == 1:
cols = ((column, ) for column in df.columns)
else:
cols = df.columns
tuples = tuple((*names, *tup) for tup in cols)
new_index = pd.MultiIndex.from_tuples(
tuples, names=target_df.columns.names)
df.columns = new_index
new_df = pd.concat([target_df, df], axis=1)
if self.dropna:
new_df = new_df.dropna(how='all')
self.tables[table] = new_df
#todo check for row indices
self.updated = True
def get(self, table, **query):
df = self.tables[table]
# This means querying a field with the same name as higher-levels columns is not possible
while df.columns.nlevels > 1:
selected_col = query.pop(df.columns.names[0], False)
if selected_col:
df = df[selected_col]
if self.dropna:
df = df.dropna(
how='all'
) # These subsets will have padded NaN rows. Remove?
else:
break
dask = query.pop('__dask', False)
df = self._filter_dataframe(df, **query)
return df
@cached_schema
def get_schema(self, table=None):
schemas = {}
for name in self.tables:
if table is not None and name != table:
continue
df = self.get(name)
schemas[name] = get_dataframe_schema(df)['items']['properties']
return schemas if table is None else schemas[table]
def get_unique(self, table=None, field=None, **query):
"""Get unique values for specified tables and fields"""
print('deprecation candidate')
unique_values = {}
for name in self.tables:
if table is not None and name != table:
continue
df = self.get(name, **query)
if field is not None:
unique_values[name] = df[field].unique()
else:
unique_values[name] = {
field_name: df[field_name].unique()
for field_name in df.columns
}
return unique_values if table is None else unique_values[table]
class Button(_ClickButton):
"""
The `Button` widget allows triggering events when the button is
clicked.
The Button provides a `value` parameter, which will toggle from
`False` to `True` while the click event is being processed
It also provides an additional `clicks` parameter, that can be
watched to subscribe to click events.
Reference: https://panel.holoviz.org/reference/widgets/Button.html#widgets-gallery-button
:Example:
>>> pn.widgets.Button(name='Click me', button_type='primary')
"""
clicks = param.Integer(default=0,
doc="""
Number of clicks (can be listened to)""")
value = param.Event(doc="""
Toggles from False to True while the event is being processed.""")
_rename = {'clicks': None, 'name': 'label', 'value': None}
_target_transforms = {'event:button_click': None, 'value': None}
_widget_type = _BkButton
@property
def _linkable_params(self):
return super()._linkable_params + ['value']
def jslink(self,
target,
code=None,
args=None,
bidirectional=False,
**links):
links = {
'event:' + self._event if p == 'value' else p: v
for p, v in links.items()
}
super().jslink(target, code, args, bidirectional, **links)
jslink.__doc__ = Widget.jslink.__doc__
def _process_event(self, event):
self.param.trigger('value')
self.clicks += 1
def on_click(self, callback):
"""
Register a callback to be executed when the `Button` is clicked.
The callback is given an `Event` argument declaring the number of clicks
Arguments
---------
callback: (callable)
The function to run on click events. Must accept a positional `Event` argument
"""
self.param.watch(callback, 'clicks', onlychanged=False)
