python使用Bokeh库实现实时数据的可视化

from bokeh.io import curdoc
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource
import random
from datetime import datetime
from functools import partial
from tornado import gen
from tornado.ioloop import PeriodicCallback

# 准备数据源
source = ColumnDataSource(data=dict(x=[], y=[]))

# 创建图表
plot = figure(plot_height=300, plot_width=800, title="实时数据可视化",
              x_axis_type="datetime", y_range=[0, 100])

# 添加折线图
line = plot.line(x='x', y='y', source=source, line_width=2)

# 更新数据
@gen.coroutine
def update():
    new_data = dict(
        x=[datetime.now()],
        y=[random.randint(0, 100)]
    )
    source.stream(new_data)

# 定时更新数据
callback = PeriodicCallback(partial(update), 1000)
callback.start()

# 显示图表
curdoc().add_root(plot)

from bokeh.models import HoverTool

# 添加交互工具
hover = HoverTool(tooltips=[("数值", "@y")])
plot.add_tools(hover, "pan", "wheel_zoom", "reset", "save")

from bokeh.layouts import gridplot

# 创建多个图表
plot1 = figure()
plot2 = figure()

# 设置联动
plot1.x_range = plot2.x_range
plot1.y_range = plot2.y_range

# 自定义样式
plot.title.text_color = "navy"
plot.title.text_font_size = "16px"
plot.xaxis.axis_label = "时间"
plot.yaxis.axis_label = "数值"
plot.xaxis.axis_label_text_color = "orange"

from bokeh.server.server import Server
from tornado.ioloop import IOLoop

# 定义应用程序
def modify_doc(doc):
    # 在此添加图表和交互组件
    pass

# 启动Bokeh服务器
apps = {'/': modify_doc}
server = Server(apps, io_loop=IOLoop(), port=5000)
server.start()

from sqlalchemy import create_engine
import pandas as pd

# 连接数据库
engine = create_engine('sqlite:///data.db')

# 查询数据
df = pd.read_sql_query("SELECT * FROM table_name", engine)

# 创建数据源
source = ColumnDataSource(data=df)

from bokeh.client import push_session
from bokeh.plotting import figure

# 连接Bokeh服务器
session = push_session(curdoc())

# 实时更新数据
def update_data():
    # 在此处更新数据
    pass

# 创建图表
plot = figure()
plot.circle('x', 'y', source=source)

# 将图表添加到文档中
curdoc().add_root(plot)

# 定时更新数据
curdoc().add_periodic_callback(update_data, 1000)

# 打开会话
session.show()

# 阻止脚本退出
session.loop_until_closed()

from bokeh.layouts import layout
from bokeh.models import Slider

# 创建滑动条
slider = Slider(start=0, end=100, value=50, step=1, title="阈值")

# 定义回调函数
def update_plot(attr, old, new):
    # 在此处更新图表
    pass

# 监听滑动条变化
slider.on_change('value', update_plot)

# 创建布局
l = layout([[slider]])

# 添加到文档中
curdoc().add_root(l)