def __init__(self, backend, dimensions, plots):
"""
The primary constructor for Dashboard Widgets.
:param backend: A dc_dashboard.Backend.Backend object which provides the backing data for
the dashboard
:param dimensions: A list of dc_dashboard.Dimension.Dimension objects describing cross filter
dimensions and groups used in the Dashboard
:param plots: A list of dc_dashboard.Plot.Plot/Layer objects describing the plots you
wish to use
"""
self._backend = backend
self._widget = DashboardWidget()
self._widget.on_trait_change(lambda tmp: self.update_fitlers(),
"filters")
self._dimensions = {dim.name: dim for dim in dimensions}
self._widget.dim_code = json.dumps(
{dim.name: dim.get_json_object()
for dim in dimensions})
self._widget.layout = json.dumps(
[plot.get_json_object() for plot in plots])
self._filters = {}
backend.register_dashboard(self)
def __init__(self, backend, dimensions, plots):
"""
The primary constructor for Dashboard Widgets.
:param backend: A dc_dashboard.Backend.Backend object which provides the backing data for
the dashboard
:param dimensions: A list of dc_dashboard.Dimension.Dimension objects describing cross filter
dimensions and groups used in the Dashboard
:param plots: A list of dc_dashboard.Plot.Plot/Layer objects describing the plots you
wish to use
"""
self._backend = backend
self._widget = DashboardWidget()
self._widget.on_trait_change(lambda tmp:self.update_fitlers(), "filters")
self._dimensions = {dim.name: dim for dim in dimensions}
self._widget.dim_code = json.dumps({dim.name: dim.get_json_object() for dim in dimensions})
self._widget.layout = json.dumps([plot.get_json_object() for plot in plots])
self._filters = {}
backend.register_dashboard(self)
class Dashboard(object):
def __init__(self, backend, dimensions, plots):
"""
The primary constructor for Dashboard Widgets.
:param backend: A dc_dashboard.Backend.Backend object which provides the backing data for
the dashboard
:param dimensions: A list of dc_dashboard.Dimension.Dimension objects describing cross filter
dimensions and groups used in the Dashboard
:param plots: A list of dc_dashboard.Plot.Plot/Layer objects describing the plots you
wish to use
"""
self._backend = backend
self._widget = DashboardWidget()
self._widget.on_trait_change(lambda tmp: self.update_fitlers(),
"filters")
self._dimensions = {dim.name: dim for dim in dimensions}
self._widget.dim_code = json.dumps(
{dim.name: dim.get_json_object()
for dim in dimensions})
self._widget.layout = json.dumps(
[plot.get_json_object() for plot in plots])
self._filters = {}
backend.register_dashboard(self)
def update_fitlers(self):
new_filters = self.get_filters()
if not new_filters == self._filters:
self._backend.filter_changed()
def set_data(self, data):
"""
Passes data from Python -> JavaScript
:param data: a pd.core.frame.Dataframe or JSon string representing the data to be passed
to java script
:raise ("Unknown data type"): if an illegal type of data is passed
"""
t = type(data)
if t == pd.core.frame.DataFrame:
self._widget.data = data.to_json(orient="records")
else:
self._widget.data = data
def get_filters(self):
"""
Parses the dimensional filters returned by JavaScript into column level filters usable by a backend.
:return: A list of tuples (column_name, filters) describing filters which have been applied by the client.
The filters object is a list of individual filters which should be ORed together.
Multiple tuples for the same column may coexist and should be ORed together.
Individual filters are one of two forms, a single value which is an equivalence filter or
a list of the form [min max] which describes a range filter.
"""
filter_json = json.loads(self._widget.filters)
filter_map = {
name.encode("utf8"): filters
for name, filters in filter_json.iteritems() if len(filters) > 0
}
filters = []
for dim, dim_filts in filter_map.iteritems():
filters = filters + self._dimensions[dim].proc_filters(
dim_filts).items()
return filters
def show(self):
""" Method to cause rendering of the widget. """
buttons = self._backend.get_toolbar()
if buttons is not None:
toolbar = widgets.ContainerWidget()
toolbar.children = buttons
display(toolbar)
toolbar.remove_class('vbox')
toolbar.add_class('hbox')
display(self._widget)
class Dashboard(object):
def __init__(self, backend, dimensions, plots):
"""
The primary constructor for Dashboard Widgets.
:param backend: A dc_dashboard.Backend.Backend object which provides the backing data for
the dashboard
:param dimensions: A list of dc_dashboard.Dimension.Dimension objects describing cross filter
dimensions and groups used in the Dashboard
:param plots: A list of dc_dashboard.Plot.Plot/Layer objects describing the plots you
wish to use
"""
self._backend = backend
self._widget = DashboardWidget()
self._widget.on_trait_change(lambda tmp:self.update_fitlers(), "filters")
self._dimensions = {dim.name: dim for dim in dimensions}
self._widget.dim_code = json.dumps({dim.name: dim.get_json_object() for dim in dimensions})
self._widget.layout = json.dumps([plot.get_json_object() for plot in plots])
self._filters = {}
backend.register_dashboard(self)
def update_fitlers(self):
new_filters = self.get_filters()
if not new_filters == self._filters:
self._backend.filter_changed()
def set_data(self, data):
"""
Passes data from Python -> JavaScript
:param data: a pd.core.frame.Dataframe or JSon string representing the data to be passed
to java script
:raise ("Unknown data type"): if an illegal type of data is passed
"""
t = type(data)
if t == pd.core.frame.DataFrame:
self._widget.data = data.to_json(orient="records")
else:
self._widget.data = data
def get_filters(self):
"""
Parses the dimensional filters returned by JavaScript into column level filters usable by a backend.
:return: A list of tuples (column_name, filters) describing filters which have been applied by the client.
The filters object is a list of individual filters which should be ORed together.
Multiple tuples for the same column may coexist and should be ORed together.
Individual filters are one of two forms, a single value which is an equivalence filter or
a list of the form [min max] which describes a range filter.
"""
filter_json = json.loads(self._widget.filters)
filter_map = {name.encode("utf8"): filters for name, filters in filter_json.iteritems() if len(filters) > 0}
filters = []
for dim, dim_filts in filter_map.iteritems():
filters = filters + self._dimensions[dim].proc_filters(dim_filts).items()
return filters
def show(self):
""" Method to cause rendering of the widget. """
buttons = self._backend.get_toolbar()
if buttons is not None:
toolbar = widgets.ContainerWidget()
toolbar.children = buttons
display(toolbar)
toolbar.remove_class('vbox')
toolbar.add_class('hbox')
display(self._widget)
