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

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

Connecting to Aha! Data

Connecting to Aha! 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 Aha! Profile on disk (e.g. C:\profiles\aha.apip). Next, set the ProfileSettings connection property to the connection string for Aha! (see below).

Aha! API Profile Settings

The Aha! API uses OAuth-based authentication.

You will first need to register an OAuth app with Aha!. This can be done from your Aha! account under 'Settings' > 'Personal' > 'Developer' > 'OAuth Applications'. Additionally, set the Domain, found in the domain name of your Aha account. For example if your Aha account is acmeinc.aha.io, then the Domain should be 'acmeinc'.

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

• AuthScheme: Set this to OAuth.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
• OAuthClientId: Set this to the client_id that is specified in you app settings.
• OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
• CallbackURL: Set this to the Redirect URI you specified in your app settings.
• Domain: Set this in the ProfileSettings to your Aha domain.

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

cnxn = mod.connect("Profile=C:\profiles\aha.apip;ProfileSettings='Domain=acmeinc';Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

Create a SQL Statement to Query Aha!

Use SQL to create a statement for querying Aha!. In this article, we read data from the Ideas entity.

sql = "SELECT Id, Name FROM Ideas WHERE AssignedToUserId = 'my_user_id'"

Extract, Transform, and Load the Aha! Data

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

Loading Aha! Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Aha! 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 Aha! 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\aha.apip;ProfileSettings='Domain=acmeinc';Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

sql = "SELECT Id, Name FROM Ideas WHERE AssignedToUserId = 'my_user_id'"

table1 = etl.fromdb(cnxn,sql)

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

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