Question

挣扎着使用Bokeh和Flask来绘制来自流媒体的数据。

数据源更新已安排，不受Bokeh管理（我看到它每秒都会完成）。

如何强制刷新图表（可能不是所有页面，因为最终版本中有多个图表）？

这是故障代码的精简版和可运行版。任何想法都是受欢迎的。

# -*- coding: utf-8 -*-

import numpy as np
import pandas as pd

from bokeh.embed import components
from bokeh.plotting import figure
from bokeh.resources import INLINE
from bokeh.models.sources import ColumnDataSource

from flask import Flask, render_template_string
from flask_apscheduler import APScheduler
from apscheduler.triggers.interval import IntervalTrigger

html_template = """
<!DOCTYPE html>
<html lang="en">
    <head>
        <meta charset="utf-8">
        {{ js_resources | safe }}
        {{ css_resources | safe }}
    </head>
    <body>
        <div>
            {{ plot_div.graph_1 | safe }}
        </div>

        {{ plot_script | safe }}
    </body>
</html>
"""
resources = INLINE
js_resources = resources.render_js()
css_resources = resources.render_css()

app = Flask(__name__)

@app.route("/")
def main_graph():

    script, div = components({'graph_1': graph_1.figure,})

    return  render_template_string(html_template,
        js_resources=js_resources,
        css_resources=css_resources,
        plot_script=script,
        plot_div=div)

# -------------------------------------------------------------------------------------------------------------------


class Generic3Lines:

    def __init__(self, scheduler):

        self.data_source = ColumnDataSource()

        self.figure = figure()
        self.figure.axis.visible = True

        self.update_data()

        line1 = self.figure.line(y="value_1", line_color="red",   x="date_time", source=self.data_source)
        line2 = self.figure.line(y="value_2", line_color="blue",  x="date_time", source=self.data_source)
        line3 = self.figure.line(y="value_3", line_color="green", x="date_time", source=self.data_source)

        scheduler.add_job(id="scheduled_update", func=self.update_data, trigger=IntervalTrigger(seconds=1))

    def update_data(self):

        df = pd.DataFrame(dict(
            date_time = range(180),
            "value_1" = np.random.random(size=180)*5+5,
            "value_2" = np.random.random(size=180)*5+10,
            "value_3" = np.random.random(size=180)*5+15,
        ))

        print(df.head(1))

        self.data_source = dict(date_time=df["date_time"],
                                 value_1=df["value_1"],
                                 value_2=df["value_2"],
                                 value_3=df["value_3"],
                                 )

scheduler = APScheduler()
scheduler.start()

graph_1 = Generic3Lines(scheduler=scheduler)

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5050)

使用Flask的流数据刷新Bokeh 0.12.6图表

0 个答案: