How to Build an ETL App for Vercel Data in Python with CData

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 and the petl framework, you can build Vercel-connected applications and pipelines for extracting, transforming, and loading Vercel data. This article shows how to connect to Vercel with the CData Python Connector and use petl and pandas to extract, transform, and load 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 petl
pip install pandas

Build an ETL App for Vercel Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL 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 petl as etl
import pandas as pd
import cdata.api as mod

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;")

Create a SQL Statement to Query Vercel

Use SQL to create a statement for querying Vercel. In this article, we read data from the User entity.

sql = "SELECT , FROM User WHERE = ''"

Extract, Transform, and Load the Vercel Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Vercel data. In this example, we extract Vercel data, sort the data by the column, and load the data into a CSV file.

Loading Vercel Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

etl.tocsv(table2,'user_data.csv')

With the CData API Driver for Python, you can work with Vercel data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

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

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Full Source Code

import petl as etl
import pandas as pd
import cdata.api as mod

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

sql = "SELECT , FROM User WHERE = ''"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

etl.tocsv(table2,'user_data.csv')