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

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

Connecting to Claude Compliance Data

Connecting to Claude Compliance 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 driver connects to Claude Compliance using a Compliance Access Key, the only supported authentication method. Set the following connection property:

• APIKey: The Compliance Access Key you created.

Creating a Compliance Access Key

1. Enable the Compliance API for your organization.
2. Sign in to claude.ai as a primary owner or organization owner and open Organization settings > API > Keys.
3. Select Create Key and assign only the scopes your integration needs:
   • read:compliance_activities for Activities and the typed activity views.
   • read:compliance_org_data for organizations, roles, groups, and settings.
   • read:compliance_user_data for users, chats, files, projects, and downloads.
   • delete:compliance_user_data for the explicit Delete stored procedures.
4. Create the key and copy it when it appears. The key starts with sk-ant-api01- and is shown only once.

Optionally, set OrganizationUUID to limit organization-scoped views (such as OrganizationUsers and ComplianceRoles) to a single linked organization. If it is left empty, those views default to the first available organization and do not include data from all linked organizations.

After installing the CData Claude Compliance Connector, follow the procedure below to install the other required modules and start accessing Claude Compliance 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 Claude Compliance 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.claudecompliance as mod

You can now connect with a connection string. Use the connect function for the CData Claude Compliance Connector to create a connection for working with Claude Compliance data.

cnxn = mod.connect("APIKey=your_compliance_access_key;")

Create a SQL Statement to Query Claude Compliance

Use SQL to create a statement for querying Claude Compliance. In this article, we read data from the Projects entity.

sql = "SELECT Id, Name FROM Projects WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'"

Extract, Transform, and Load the Claude Compliance Data

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

Loading Claude Compliance Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for Claude Compliance, you can work with Claude Compliance 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 Python Connector for Claude Compliance to start building Python apps and scripts with connectivity to Claude Compliance 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.claudecompliance as mod

cnxn = mod.connect("APIKey=your_compliance_access_key;")

sql = "SELECT Id, Name FROM Projects WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'"

table1 = etl.fromdb(cnxn,sql)

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

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