在this tutorial之后,我试图使用Holoviews而非Bokeh(here作为CSV文件可用的示例数据)来可视化数据集,并使用Flask来提供结果。我决定使用Flask而不是Bokeh Server,因为我正在使用前者构建更大的工作流。
我的代码如下:
from flask import Flask, render_template, request
import numpy as np
import pandas as pd
from datetime import datetime
from bokeh.embed import components
from bokeh.io import curdoc
import holoviews as hv
hv.extension("bokeh")
app = Flask(__name__)
renderer = hv.renderer('bokeh')
infile = "./uploads/test.csv"
def loadRegionData(regionProperty, **kwargs):
df = pd.read_csv(infile, parse_dates=['Datetime'])
df1 = df[regionProperty]
df = pd.concat([df['Datetime'],df1], axis=1)
return hv.Curve(df)
colNames = ((pd.read_csv(infile, nrows=1)).drop(['Datetime'], axis=1)).columns.values
dmap = hv.DynamicMap(loadRegionData, kdims='RegionProperty').redim.values(RegionProperty=colNames)
hvplot = renderer.get_plot(dmap)
plot = hvplot.state
plot.name = 'plot'
curdoc().add_root(plot)
@app.route("/")
def index():
# Embed plot into HTML via Flask Render
script, div = components(plot)
return render_template("index.html", script=script, div=div)
if __name__ == '__main__':
app.run(port=5000, debug=True)
我遇到了以下(不相关的问题)
index()
函数中的正确变量返回/引用到我的index.html
中:
<html>
<head>
<link
href="http://cdn.pydata.org/bokeh/release/bokeh-1.0.2.min.css"
rel="stylesheet" type="text/css">
<link
href="http://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.2.min.css"
rel="stylesheet" type="text/css">
<script src="http://cdn.pydata.org/bokeh/release/bokeh-1.0.2.min.js"></script>
<script src="http://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.2.min.js"></script>
</head>
<body>
<h1>Holoview test</h1>
{{ script|safe }}
{{ div|safe }}
</body>
</html>
如何让Flask同时显示下拉选择器?