I recently built a dashboard that includes bokeh widgets. Every time I run it I need to go to anaconda prompt and type
bokeh serve --show myapp.py
Is there a more friendly way to do this without open up a cmd window? I'm currently on Windows 7 and soon to be updated to Windows 10.
Thanks!
This is explained here in Bokeh documentation: Running a Bokeh Server
And here is one example for Bokeh v1.1.0:
from tornado.ioloop import IOLoop
from bokeh.server.server import Server
from bokeh.application import Application
from bokeh.application.handlers.function import FunctionHandler
from bokeh.plotting import figure, ColumnDataSource
import random
def make_document(doc):
source = ColumnDataSource({'x': [], 'y': [], 'color': []})
def update():
new = {'x': [random.random()], 'y': [random.random()], 'color': [random.choice(['red', 'blue', 'green'])]}
source.stream(new)
doc.add_periodic_callback(update, 1000)
fig = figure(title = 'Streaming Circle Plot!', x_range = [0, 1], y_range = [0, 1])
fig.circle(source = source, x = 'x', y = 'y', color = 'color', size = 10)
doc.title = "Now with live updating!"
doc.add_root(fig)
apps = {'/': Application(FunctionHandler(make_document))}
io_loop = IOLoop.current()
server = Server(applications = {'/': Application(FunctionHandler(make_document))}, io_loop = io_loop, port = 5001)
server.start()
server.show('/')
io_loop.start()
And here is the requested code converted from Bokey movies example (Bokeh v1.1.0):
from tornado.ioloop import IOLoop
from bokeh.server.server import Server
from bokeh.application import Application
from bokeh.application.handlers.function import FunctionHandler
from os.path import dirname, join
import numpy as np
import pandas.io.sql as psql
import sqlite3 as sql
from bokeh.plotting import figure
from bokeh.layouts import layout, column
from bokeh.models import ColumnDataSource, Div
from bokeh.models.widgets import Slider, Select, TextInput
from bokeh.io import curdoc
from bokeh.sampledata.movies_data import movie_path
def make_document(doc):
conn = sql.connect(movie_path)
query = open(join(dirname(__file__), 'query.sql')).read()
movies = psql.read_sql(query, conn)
movies["color"] = np.where(movies["Oscars"] > 0, "orange", "grey")
movies["alpha"] = np.where(movies["Oscars"] > 0, 0.9, 0.25)
movies.fillna(0, inplace = True) # just replace missing values with zero
movies["revenue"] = movies.BoxOffice.apply(lambda x: '{:,d}'.format(int(x)))
with open(join(dirname(__file__), "razzies-clean.csv")) as f:
razzies = f.read().splitlines()
movies.loc[movies.imdbID.isin(razzies), "color"] = "purple"
movies.loc[movies.imdbID.isin(razzies), "alpha"] = 0.9
axis_map = {
"Tomato Meter": "Meter",
"Numeric Rating": "numericRating",
"Number of Reviews": "Reviews",
"Box Office (dollars)": "BoxOffice",
"Length (minutes)": "Runtime",
"Year": "Year",
}
desc = Div(text = open(join(dirname(__file__), "description.html")).read(), width = 800)
# Create Input controls
reviews = Slider(title = "Minimum number of reviews", value = 80, start = 10, end = 300, step = 10)
min_year = Slider(title = "Year released", start = 1940, end = 2014, value = 1970, step = 1)
max_year = Slider(title = "End Year released", start = 1940, end = 2014, value = 2014, step = 1)
oscars = Slider(title = "Minimum number of Oscar wins", start = 0, end = 4, value = 0, step = 1)
boxoffice = Slider(title = "Dollars at Box Office (millions)", start = 0, end = 800, value = 0, step = 1)
genre = Select(title = "Genre", value = "All",
options = open(join(dirname(__file__), 'genres.txt')).read().split())
director = TextInput(title = "Director name contains")
cast = TextInput(title = "Cast names contains")
x_axis = Select(title = "X Axis", options = sorted(axis_map.keys()), value = "Tomato Meter")
y_axis = Select(title = "Y Axis", options = sorted(axis_map.keys()), value = "Number of Reviews")
# Create Column Data Source that will be used by the plot
source = ColumnDataSource(data = dict(x = [], y = [], color = [], title = [], year = [], revenue = [], alpha = []))
TOOLTIPS = [
("Title", "@title"),
("Year", "@year"),
("$", "@revenue")
]
p = figure(plot_height = 600, plot_width = 700, title = "", toolbar_location = None, tooltips = TOOLTIPS)
p.circle(x = "x", y = "y", source = source, size = 7, color = "color", line_color = None, fill_alpha = "alpha")
def select_movies():
genre_val = genre.value
director_val = director.value.strip()
cast_val = cast.value.strip()
selected = movies[
(movies.Reviews >= reviews.value) &
(movies.BoxOffice >= (boxoffice.value * 1e6)) &
(movies.Year >= min_year.value) &
(movies.Year <= max_year.value) &
(movies.Oscars >= oscars.value)
]
if (genre_val != "All"):
selected = selected[selected.Genre.str.contains(genre_val) == True]
if (director_val != ""):
selected = selected[selected.Director.str.contains(director_val) == True]
if (cast_val != ""):
selected = selected[selected.Cast.str.contains(cast_val) == True]
return selected
def update():
df = select_movies()
x_name = axis_map[x_axis.value]
y_name = axis_map[y_axis.value]
p.xaxis.axis_label = x_axis.value
p.yaxis.axis_label = y_axis.value
p.title.text = "%d movies selected" % len(df)
source.data = dict(
x = df[x_name],
y = df[y_name],
color = df["color"],
title = df["Title"],
year = df["Year"],
revenue = df["revenue"],
alpha = df["alpha"],
)
controls = [reviews, boxoffice, genre, min_year, max_year, oscars, director, cast, x_axis, y_axis]
for control in controls:
control.on_change('value', lambda attr, old, new: update())
inputs = column(*controls)
l = layout([
[desc],
[inputs, p],
])
update() # initial load of the data
doc.add_root(l)
doc.title = "Movies"
io_loop = IOLoop.current()
server = Server(applications = {'/': Application(FunctionHandler(make_document))}, io_loop = io_loop, port = 5001)
server.start()
server.show('/')
io_loop.start()