Getting the build an app example to work from the command-line

Panel
1

I would like to get the build an app example to work from the command-line. I dont typically use Jupyter. How would I modify this code so that I can type python example_1.py:

import panel as pn
import hvplot.pandas
import pandas as pd
import numpy as np

pn.extension(design='material')

csv_file = ("https://raw.githubusercontent.com/holoviz/panel/main/examples/assets/occupancy.csv")
data = pd.read_csv(csv_file, parse_dates=["date"], index_col="date")

data.tail()
print(data.tail())

def transform_data(variable, window, sigma):
    ''' Calculates the rolling average and the outliers '''
    avg = data[variable].rolling(window=window).mean()
    residual = data[variable] - avg
    std = residual.rolling(window=window).std()
    outliers = np.abs(residual) > std * sigma
    return avg, avg[outliers]

def create_plot(variable="Temperature", window=30, sigma=10):
    ''' Plots the rolling average and the outliers '''
    avg, highlight = transform_data(variable, window, sigma)
    return avg.hvplot(height=300, width=400, legend=False) * highlight.hvplot.scatter(
        color="orange", padding=0.1, legend=False
    )

create_plot(variable='Temperature', window=20, sigma=10)


variable_widget = pn.widgets.Select(name="variable", value="Temperature", options=list(data.columns))
window_widget = pn.widgets.IntSlider(name="window", value=30, start=1, end=60)
sigma_widget = pn.widgets.IntSlider(name="sigma", value=10, start=0, end=20)

bound_plot = pn.bind(create_plot, variable=variable_widget, window=window_widget, sigma=sigma_widget)

first_app = pn.Column(variable_widget, window_widget, sigma_widget, bound_plot)

first_app
2

You can run Panel app through command line. Here is the doc that should help.

3

Thank you. A key part of that doc is that you must append .servable() to the panel instance.

working code:

import panel as pn
import hvplot.pandas
import pandas as pd
import numpy as np

pn.extension(design='material')

csv_file = ("https://raw.githubusercontent.com/holoviz/panel/main/examples/assets/occupancy.csv")
data = pd.read_csv(csv_file, parse_dates=["date"], index_col="date")

data.tail()
print(data.tail())

def transform_data(variable, window, sigma):
    ''' Calculates the rolling average and the outliers '''
    avg = data[variable].rolling(window=window).mean()
    residual = data[variable] - avg
    std = residual.rolling(window=window).std()
    outliers = np.abs(residual) > std * sigma
    return avg, avg[outliers]

def create_plot(variable="Temperature", window=30, sigma=10):
    ''' Plots the rolling average and the outliers '''
    avg, highlight = transform_data(variable, window, sigma)
    return avg.hvplot(height=300, width=400, legend=False) * highlight.hvplot.scatter(
        color="orange", padding=0.1, legend=False
    )

create_plot(variable='Temperature', window=20, sigma=10)


variable_widget = pn.widgets.Select(name="variable", value="Temperature", options=list(data.columns))
window_widget = pn.widgets.IntSlider(name="window", value=30, start=1, end=60)
sigma_widget = pn.widgets.IntSlider(name="sigma", value=10, start=0, end=20)

bound_plot = pn.bind(create_plot, variable=variable_widget, window=window_widget, sigma=sigma_widget)

first_app = pn.Column(variable_widget, window_widget, sigma_widget, bound_plot)

first_app.servable()
4

Sure. I’m glad you got it working. Now, you can set this post as “resolved” by picking the right reply.

1 Like
5

Indeed you need to mark at least one Panel object with .servable() for panel serve to pick it up and render it in the served app. In a notebook context, .servable() isn’t required as Panel objects support the rich display functionality offered by IPython. In a notebook again, marking an object with .servable() has no effect, it’s a no-op; it’s only useful if you ultimately serve directly the notebook with panel serve.