是否有通过 bokeh serve --show 启动 bokeh 服务器的替代方法？
Is there an alternative for initiate bokeh server through bokeh serve --show?
我最近构建了一个包含散景小部件的仪表板。每次我 运行 我都需要去 anaconda 提示符并输入
散景服务 --show myapp.py
有没有更友好的方法可以在不打开 cmd 的情况下执行此操作 window？我目前在 Windows 7，很快就会更新到 Windows 10。
谢谢！
这在 Bokeh 文档中有解释：Running a Bokeh Server
这是 Bokeh v1.1.0 的一个示例：
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()
这是从 Bokey 电影示例 (Bokeh v1.1.0) 转换而来的请求代码：
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()
我最近构建了一个包含散景小部件的仪表板。每次我 运行 我都需要去 anaconda 提示符并输入
散景服务 --show myapp.py
有没有更友好的方法可以在不打开 cmd 的情况下执行此操作 window？我目前在 Windows 7，很快就会更新到 Windows 10。
谢谢！
这在 Bokeh 文档中有解释：Running a Bokeh Server
这是 Bokeh v1.1.0 的一个示例：
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()
这是从 Bokey 电影示例 (Bokeh v1.1.0) 转换而来的请求代码：
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()