Web applications 是否有通过bokeh服务——show启动bokeh服务器的替代方案？

我最近构建了一个包含bokeh小部件的仪表板。每次运行它时，我都需要转到anaconda提示符并键入

bokeh发球-显示myapp.py

有没有一种更友好的方法可以在不打开cmd窗口的情况下执行此操作？我目前使用的是Windows 7，很快就会更新到Windows 10

---

谢谢

Bokeh文档中对此进行了解释：

下面是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()

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()

---

Bokeh文档对此进行了解释：

下面是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()

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()

---

下面是从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 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()

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()

---

下面是从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 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()

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()

---

你好，托尼，谢谢你的回复。我正试着读你的密码和博克的医生。但是我对编码真的很陌生，你能提供更多关于每个函数扮演什么角色的见解吗？另外，我的项目是基于bokeh的一个例子。我想知道在你的例子中提到的那些函数中哪些是这个项目所必需的。非常感谢。见第二个答案你好，托尼，谢谢你的回复。我正试着读你的密码和博克的医生。但是我对编码真的很陌生，你能提供更多关于每个函数扮演什么角色的见解吗？另外，我的项目是基于bokeh的一个例子。我想知道在你的例子中提到的那些函数中哪些是这个项目所必需的。非常感谢。请参阅第二个答案感谢您的努力！虽然在我运行浏览器后，浏览器上显示了“500:内部服务器错误”。知道这里有什么问题吗？代码适用于Bokeh v1.1.0和Tornado v4.5.3。如果您使用不同版本，请考虑升级BOKEH或降级龙卷风。谢谢您的努力！虽然在我运行浏览器后，浏览器上显示了“500:内部服务器错误”。知道这里有什么问题吗？代码适用于Bokeh v1.1.0和Tornado v4.5.3。如果你使用不同的版本，请考虑升级BOKEH或降级龙卷风。