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Python Connector Libraries for Basecamp Data Connectivity. Integrate Basecamp with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use pandas to Visualize Basecamp Data in Python

The CData Python Connector for Basecamp enables you use pandas and other modules to analyze and visualize live Basecamp data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Basecamp, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Basecamp-connected Python applications and scripts for visualizing Basecamp data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Basecamp data, execute queries, and visualize the results.

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

Connecting to Basecamp Data

Connecting to Basecamp 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.

Basecamp uses basic or OAuth 2.0 authentication. To use basic authentication you will need the user and password that you use for logging in to Basecamp. To authenticate to Basecamp via OAuth 2.0, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with Basecamp.

See the Getting Started section in the help documentation for a connection guide.

Additionally, you will need to specify the AccountId connection property. This can be copied from the URL after you log in.

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

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

engine = create_engine("basecamp:///?User=test@northwind.db&Password=test123")

Execute SQL to Basecamp

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

df = pandas.read_sql("SELECT Name, DocumentsCount FROM Projects WHERE Drafts = 'True'", engine)

Visualize Basecamp Data

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

df.plot(kind="bar", x="Name", y="DocumentsCount")

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Basecamp to start building Python apps and scripts with connectivity to Basecamp 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("basecamp:///?User=test@northwind.db&Password=test123")
df = pandas.read_sql("SELECT Name, DocumentsCount FROM Projects WHERE Drafts = 'True'", engine)

df.plot(kind="bar", x="Name", y="DocumentsCount")