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

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

Connecting to Planio Data

Connecting to Planio 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.

Start by setting the Profile connection property to the location of the Planio Profile on disk (e.g. C:\profiles\Planio.apip). Next, set the ProfileSettings connection property to the connection string for Planio (see below).

Planio API Profile Settings

Enable the REST API in Planio Administration Settings, then go to My Account > API Access Key and click Show to reveal your API key. Your subdomain is the prefix of your Planio account URL.

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

cnxn = mod.connect("Profile=C:\profiles\Planio.apip;ProfileSettings='APIKey=your_api_key;Subdomain=your_subdomain';")

Create a SQL Statement to Query Planio

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

sql = "SELECT Id, Name FROM Companies WHERE Country = 'United States'"

Extract, Transform, and Load the Planio Data

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

Loading Planio Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

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

With the CData API Driver for Python, you can work with Planio 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 Planio 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\Planio.apip;ProfileSettings='APIKey=your_api_key;Subdomain=your_subdomain';")

sql = "SELECT Id, Name FROM Companies WHERE Country = 'United States'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

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