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Creating an editor-type app

In this tutorial we will create an editor-only application, that can be used to visualize world population and life expectancy data in a few different ways:

  1. bar chart of the Netherlands
  2. animated scatter plot per continent
  3. world map surface plot

The end result can be downloaded here.

tip

For more examples of 'editor' type applications, please visit the sample apps

A template 'editor' type app can be generated using the CLI. We will use this template app as a starting point for the tutorial. Run the following command (replace editor-tutorial with the folder name of your choice):

viktor-cli create-app --app-type editor editor-tutorial

Folder structure

The app has the following folder structure:

editor-tutorial
├── app.py
├── CHANGELOG.md
├── README.md
├── requirements.txt
├── tests
│ └── __init__.py
└── viktor.config.toml

Note that the app type ('editor') has been defined in viktor.config.toml:

Dependencies

Navigate to the newly created folder and open requirements.txt and add plotly as additional requirement. We will use this package to create the (interactive) visualizations.

# viktor==X.X.X
plotly

Installation

Now run the install command from within the folder to install the app and its dependencies, clear any previous saved local database, and run start to start to app:

viktor-cli install
viktor-cli clear
viktor-cli start

Login to the app in your browser to verify that the app is installed and running as expected. You will be redirected to the app's editor, which is currently a blank page.

note

If you see the "Workspaces" menu upon logging in, click the "Open" button on the "Development" workspace. After opening, you will be redirected to the app's editor.

Defining the editor (input / output)

Open app.py and replace it with the following code:

from viktor import ViktorControllerfrom viktor.parametrization import ViktorParametrization, OptionFieldfrom viktor.views import PlotlyView, PlotlyResultimport plotly.express as pxclass Parametrization(ViktorParametrization):    _options = ["The Netherlands", "Continents", "Global"]    graph = OptionField("Life expectancy:", options=_options, default="Continents", variant="radio", flex=100)class Controller(ViktorController):    label = 'My Entity Type'    parametrization = Parametrization(width=20)    @PlotlyView("Life Expectancy", duration_guess=3)    def plotly_view(self, params, **kwargs):        dataframe = px.data.gapminder()        if params.graph == 'The Netherlands':            data = dataframe.query("country == 'Netherlands' ")            fig = px.bar(data, x='year', y='pop', color='lifeExp')        elif params.graph == 'Continents':            fig = px.scatter(dataframe, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",                             size="pop", color="continent", hover_name="country", facet_col="continent",                             log_x=True, size_max=75, range_x=[100, 100000], range_y=[25, 90])        elif params.graph == 'Global':            fig = px.choropleth(dataframe, locations='iso_alpha', color='lifeExp', hover_name='country',                                animation_frame='year', color_continuous_scale=px.colors.sequential.Plasma,                                projection='natural earth')        else:            raise NotImplementedError        return PlotlyResult(fig.to_json())

In your browser, refresh the page to reload the editor. On the left side, you will now see radio buttons with the defined options. Go ahead and select another option and see how it influences the results on the right-hand side.