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Use Dash to Build to Web Apps on YouTube Data

The CData Python Connector for YouTube enables you to create Python applications that use pandas and Dash to build YouTube-connected web apps.

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

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

Connecting to YouTube Data

Connecting to YouTube 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.

YouTube uses the OAuth authentication standard. To access Google APIs on behalf on individual users, you can use the embedded CData credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

After installing the CData YouTube Connector, follow the procedure below to install the other required modules and start accessing YouTube 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 YouTube 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.youtube as mod
import plotly.graph_objs as go

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

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

Execute SQL to YouTube

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 Title, ViewCount FROM Videos WHERE MyRating = 'like'", 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-youtubeedataplot'

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 YouTube data and configure the app layout.

trace = go.Bar(x=df.Title, y=df.ViewCount, name='Title')

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='YouTube Videos 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 YouTube data.

python youtube-dash.py

Free Trial & More Information

Download a free, 30-day trial of the YouTube Python Connector to start building Python apps with connectivity to YouTube 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.youtube as mod
import plotly.graph_objs as go

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

df = pd.read_sql("SELECT Title, ViewCount FROM Videos WHERE MyRating = 'like'", cnxn)
app_name = 'dash-youtubedataplot'

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.Title, y=df.ViewCount, name='Title')

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='YouTube Videos Data', barmode='stack')
		})
], className="container")

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