How to Visualize ApprovalMax Data in Python with pandas

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, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build ApprovalMax-connected Python applications and scripts for visualizing ApprovalMax data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to ApprovalMax data, execute queries, and visualize the results.

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.

Follow the procedure below to install the required modules and start accessing ApprovalMax through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize ApprovalMax Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with ApprovalMax data.

engine = create_engine("api:///?Profile=C:\profiles\ApprovalMax.apip&AuthScheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackURL=your_callback_url")

Execute SQL to ApprovalMax

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT UserId, Email FROM UserProfiles WHERE CompanyId = '00000000-0000-0000-0000-000000000000'", engine)

Visualize ApprovalMax Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the ApprovalMax data. The show method displays the chart in a new window.

df.plot(kind="bar", x="UserId", y="Email")
plt.show()

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 pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\profiles\ApprovalMax.apip&AuthScheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackURL=your_callback_url")
df = pandas.read_sql("SELECT UserId, Email FROM UserProfiles WHERE CompanyId = '00000000-0000-0000-0000-000000000000'", engine)

df.plot(kind="bar", x="UserId", y="Email")
plt.show()