How to Build an ETL App for Perigon 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 Perigon-connected applications and pipelines for extracting, transforming, and loading Perigon data. This article shows how to connect to Perigon with the CData Python Connector and use petl and pandas to extract, transform, and load Perigon data.

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

Connecting to Perigon Data

Connecting to Perigon 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

To use the Perigon API, you need to obtain an API key from your Perigon account. Navigate to the Perigon dashboard and generate an API key from your account settings.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Perigon API key.

Example connection string:

Profile=C:\profiles\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"

Available Tables

The Perigon profile provides access to the following tables:

• Articles - News articles retrieved from the Perigon news intelligence API
• Headlines - Story clusters grouping related headline articles
• Sources - News sources tracked by the Perigon news intelligence API
• Journalists - Journalist profiles tracked by the Perigon news intelligence API

After installing the CData Perigon Connector, follow the procedure below to install the other required modules and start accessing Perigon 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 Perigon 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 Perigon Connector to create a connection for working with Perigon data.

cnxn = mod.connect("Profile=C:\profiles\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"")

Create a SQL Statement to Query Perigon

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

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

Extract, Transform, and Load the Perigon Data

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

Loading Perigon Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with Perigon 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 Perigon data. Reach out to our Support Team if you have any questions.

Full Source Code

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

cnxn = mod.connect("Profile=C:\profiles\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"")

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

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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