Modeling chart properties

bokeh_chart_props.py

from bokeh.properties import HasProps, List, String, Either, Instance, Bool
from bokeh.models.widgets import Select, Widget, Toggle
import pandas as pd
from blaze.interactive import InteractiveSymbol, Data
from odo import odo
from bokeh.io import vform
from bokeh.plotting import output_file, show
from bokeh.plotting import figure, Figure


class Constraint(HasProps):
    name = String

IS_NOT_CONSTANT = Constraint(name='IS_NOT_CONSTANT')
IS_LOGICAL = Constraint(name='IS_LOGICAL')


# Models
class Column(HasProps):
    """A column option used to model input to Charts."""
    name = String
    alt_names = List(String)
    valid_types = List(Instance(Constraint))
    widget = Instance(Widget, default=Select())

    selection = String
    type = String


class BoolOption(HasProps):
    name = String
    widget = Instance(Widget, default=Toggle())

    def __nonzero__(self):
        if self.widget:
            return True
        else:
            return False


class DataResource(HasProps):
    """Model for a blaze data source."""
    source = String
    #tables = List
    #columns = List
    #symbol = Any

    def __init__(self, **properties):
        source = properties.get('source')
        if isinstance(source, str):
            #properties['symbol'] = Data(source)
            pass
        elif isinstance(source, pd.DataFrame):
            #properties['symbol'] = Data(source)
            properties['source'] = 'DataFrame'
        super(DataResource, self).__init__(**properties)

    @property
    def df(self):
        return odo(self.symbol, pd.DataFrame)


class Chart(Widget):
    """A generic plot for table-like data."""
    data = Instance(DataResource)
    options = List(Either(Instance(Column), Bool))

    fig = Instance(Figure)

    def __init__(self, **properties):
        properties['data'] = DataResource(source=properties.get('data'))
        super(Chart, self).__init__(**properties)

        for option in self.options:
            option.widget.on_change('value', self, 'plot')

    def plot(self):
        raise NotImplementedError


# My Unique Chart
class MyChart(Chart):

    x = Column(name='x', valid_types=[IS_NOT_CONSTANT])
    y = Column(name='x', valid_types=[IS_NOT_CONSTANT])
    flip = BoolOption(name='flip')
    options = [x, y, flip]

    def plot(self):
        if self.flip:
            self.fig = figure(plot_width=400, plot_height=400)
            self.fig.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)
            return self.fig
        else:
            self.fig = figure(plot_width=400, plot_height=400)
            self.fig.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="green", alpha=0.5)
            return self.fig


def interact(chart):
    output_file("test.html")
    widgets = []
    for option in chart.options:
        widgets.append(option.widget)
    widgets.append(chart.plot())
    show(vform(*widgets))


if __name__ == '__main__':

    df = pd.DataFrame(dict(x=[1,2,3], y=[2,3,4]))

    c = MyChart()
    print c.properties_with_values()
    print MyChart.options

    # DataResource takes anything blaze takes
    dr = DataResource(source=df)
    print dr.properties_with_values()

    dr = DataResource(source='sqlite:///C:\Users\Nick\Downloads\lahman2013.sqlite')
    print dr.properties_with_values()

    # create special chart
    c = MyChart(data='sqlite:///C:\Users\Nick\Downloads\lahman2013.sqlite')
    print c.properties_with_values()
    
    # end goal is interactive chart with simple command
    interact(c)

Latest update produces the output I'd want to see, just isn't interactive yet (not on server).

This produces the output below, when called by interact(chart)

class MyChart(Chart):

    x = Column(name='x', valid_types=[IS_NOT_CONSTANT])
    y = Column(name='x', valid_types=[IS_NOT_CONSTANT])
    flip = BoolOption(name='flip')
    options = [x, y, flip]

    def plot(self):
        self.fig = figure(plot_width=400, plot_height=400)
        self.fig.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)
        return self.fig