Use Dash to Build to Web Apps on Vercel Data

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

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

Connecting to Vercel Data

Connecting to Vercel 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.

Using API Key Authentication

Vercel uses Bearer token authentication. You can use either a personal access token or an OAuth access token as the API key.

To obtain a personal access token:

1. Log into your Vercel account at https://vercel.com/
2. Navigate to Account Settings > Tokens.
3. Click Create Token, enter a name and expiration, and click Create.
4. Copy the generated token (it will only be shown once).

After obtaining your token, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Vercel personal access token or OAuth access token.

Example Connection String

Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;

Working with Teams

Many Vercel resources are scoped to a team. To scope all requests to a specific team, set the TeamId connection property to your team's ID. You can find your team ID by querying the Teams table or from the Vercel dashboard. Alternatively, you can specify TeamId in your SQL queries using the WHERE clause where supported.

Connecting to Vercel

Once the authentication is configured, you can connect to Vercel and query data from any of the available tables such as Projects, Deployments, Teams, and Domains.

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

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

cnxn = mod.connect("Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;")

Execute SQL to Vercel

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 , FROM User WHERE = ''", 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-apiedataplot'

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 Vercel data and configure the app layout.

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

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='Vercel User 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 Vercel data.

python api-dash.py

👁 Vercel data in a Dash web app (Salesforce is shown).

Free Trial & More Information

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

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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.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;")

df = pd.read_sql("SELECT , FROM User WHERE = ''", cnxn)
app_name = 'dash-apidataplot'

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

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='Vercel User Data', barmode='stack')
		})
], className="container")

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