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

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

Connecting to ApprovalMax Data

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

ApprovalMax API Profile Settings

To authenticate to ApprovalMax and connect to your own data or to allow other users to connect to their data, the ApprovalMax Public API requires the OAuth 2.0 authorization code flow.

First, you will need to register an OAuth application with ApprovalMax. Sign in to the ApprovalMax Developer Portal (https://developer.approvalmax.com/applications) and create a new application. Your OAuth application will be assigned a Client ID and a Client Secret, and you must register at least one Redirect URI (Callback URL).

A Premium ApprovalMax subscription (or active trial) is required to use the Public API.

After setting the following connection properties, 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 shown in your application settings on the ApprovalMax Developer Portal.
• OAuthClientSecret: Set this to the Client Secret that is shown in your application settings on the ApprovalMax Developer Portal.
• CallbackURL: Set this to the Redirect URI that is registered in your application settings.
• Scope: (Optional) Override the default OAuth scopes. The default value openid offline_access https://www.approvalmax.com/scopes/public_api/read grants read-only access to all tables in this profile and enables refresh tokens. Use the principle of least privilege when narrowing this scope.

The OAuth Authorization URL is https://identity.approvalmax.com/connect/authorize and the Token URL is https://identity.approvalmax.com/connect/token. Both authorization_code and refresh_token grant types are supported.

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

cnxn = mod.connect("Profile=C:\profiles\ApprovalMax.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=your_callback_url;")

Create a SQL Statement to Query ApprovalMax

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

sql = "SELECT UserId, Email FROM UserProfiles WHERE CompanyId = '00000000-0000-0000-0000-000000000000'"

Extract, Transform, and Load the ApprovalMax Data

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

Loading ApprovalMax Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with ApprovalMax 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 ApprovalMax 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\ApprovalMax.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=your_callback_url;")

sql = "SELECT UserId, Email FROM UserProfiles WHERE CompanyId = '00000000-0000-0000-0000-000000000000'"

table1 = etl.fromdb(cnxn,sql)

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

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