Parameters and Forms
Apps can be parameterised, allowing them to dynamically generate reports through web forms or the API.
Stakeholders commonly need to provide some configuration to your apps to enable self-service report generation. Datapane allows you to add parameters, which are presented to end users as web forms. This means that other people who have accounts on your instance can generate reports without worrying about code, notebooks, or setting up a Python environment.
Running & Parameters
Input parameters can be defined in your
datapane.yaml configuration file, where you can enter a schema and configure the inputs. In your Python code, the parameters which you define in this file are accessible in the
Params dictionary. You can get an item from the dictionary with
Following the previous example, the dataset we are pulling includes a few other useful parameters which people may want to graph. Let's add the ability for the end-user to choose from
gdp_per_capita . Additionally, let's allow them to choose a subset of continents for the graph.
Based on this, we are going to add two parameters:
continents to the
parameters section of our
datapane.yaml. To configure what the end-user's form looks like, we can choose the type of widget. For the above, we're choosing a
enum (which provides a dropdown select menu where the user must select one option), and a
list (which allows the user to choose or more choices from a predefined list). We can also set the default parameters for each input and a description.
Full details of parameter configuration and available fields are provided in the API reference.
name: covid_script script: simple_script.py # this could also be ipynb if it was a notebook parameters: - name: field_to_plot description: Field to plot type: enum choices: - new_cases_smoothed_per_million - new_deaths_smoothed_per_million - median_age - gdp_per_capita - name: continents description: Field to plot type: list choices: - Africa - Asia - Europe - Oceania - North America - South America default: - Asia - North America
You can then use the
Params object as you would when running on your Datapane instance, and we can customise our data and graph based on those inputs.
We'll place the folloding in a file named
import pandas as pd import altair as alt import datapane as dp dataset = pd.read_csv("https://covid.ourworldindata.org/data/owid-covid-data.csv") # Get input parameters continents = dp.Params.get("continents", ["Asia", "North America"]) field_to_plot = dp.Params.get("field_to_plot", "new_cases_smoothed_per_million") df = ( dataset[dataset.continent.isin(continents)] .groupby(["continent", "date"])[field_to_plot] .mean() .tail(1000) .reset_index() ) plot = ( alt.Chart(df) .mark_area(opacity=0.4, stroke="black") .encode( x="date:T", y=alt.Y(field_to_plot, stack=None), color=alt.Color("continent:N", scale=alt.Scale(scheme="set1")), tooltip="continent:N", ) .interactive() .properties(width="container") ) report = dp.Report(dp.Plot(plot), dp.Table(df)) report.upload(name="covid_report")
When we run
app deploy, Datapane will deploy a new version of our app, and use our parameters definition to generate the following form:
Stakeholders can enter parameters and generate custom reports themselves, based on these fields.