How to Visualize Discourse 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 Discourse-connected Python applications and scripts for visualizing Discourse data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Discourse data, execute queries, and visualize the results.

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

Connecting to Discourse Data

Connecting to Discourse 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.

The Discourse API uses API Key authentication.

Using API Key Authentication

Discourse requires API Key and Username for authentication. API Keys are generated in the Discourse Admin panel under the API section. You can create user-specific API keys or all-users API keys. Once you have obtained the API Key, set it along with the Domain and Username in the ProfileSettings connection property.

Example Connection string

Profile=C:\profiles\Discourse.apip;ProfileSettings='Domain=forum.example.com;APIKey=your_api_key;Username=your_username;'AuthScheme=APIKey;

Follow the procedure below to install the required modules and start accessing Discourse 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 Discourse Data in Python

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

engine = create_engine("api:///?Profile=C:\profiles\Discourse.apip&ProfileSettings='Domain=forum.example.com&APIKey=your_api_key&Username=your_username&'AuthScheme=APIKey")

Execute SQL to Discourse

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

df = pandas.read_sql("SELECT , FROM Backups WHERE = ''", engine)

Visualize Discourse Data

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

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

👁 Discourse data in a Python plot (Salesforce is shown).

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 Discourse data. Reach out to our Support Team if you have any questions.

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Full Source Code

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

engine = create_engine("api:///?Profile=C:\profiles\Discourse.apip&ProfileSettings='Domain=forum.example.com&APIKey=your_api_key&Username=your_username&'AuthScheme=APIKey")
df = pandas.read_sql("SELECT , FROM Backups WHERE = ''", engine)

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