Use Dash to Build to Web Apps on Google Calendar Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Google Calendars, the pandas module, and the Dash framework, you can build Google Calendar-connected web applications for Google Calendar data. This article shows how to connect to Google Calendar with the CData Connector and use pandas and Dash to build a simple web app for visualizing Google Calendar data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Google Calendar data in Python. When you issue complex SQL queries from Google Calendar, the driver pushes supported SQL operations, like filters and aggregations, directly to Google Calendar and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Google Calendar Data

Connecting to Google Calendar data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

You can connect to Google APIs on behalf of individual users or on behalf of a domain. Google uses the OAuth authentication standard. See the "Getting Started" section of the help documentation for a guide.

After installing the CData Google Calendar Connector, follow the procedure below to install the other required modules and start accessing Google Calendar through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Google Calendar Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.googlecalendar as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Google Calendar Connector to create a connection for working with Google Calendar data.

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Google Calendar

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT Summary, StartDateTime FROM VacationCalendar WHERE SearchTerms = 'beach trip'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-googlecalendaredataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Google Calendar data and configure the app layout.

trace = go.Bar(x=df.Summary, y=df.StartDateTime, name='Summary')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Google Calendar VacationCalendar Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Google Calendar data.

python googlecalendar-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Google Calendars to start building Python apps with connectivity to Google Calendar data. Reach out to our Support Team if you have any questions.

Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.googlecalendar as mod
import plotly.graph_objs as go

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Summary, StartDateTime FROM VacationCalendar WHERE SearchTerms = 'beach trip'", cnxn)
app_name = 'dash-googlecalendardataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Summary, y=df.StartDateTime, name='Summary')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Google Calendar VacationCalendar Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)