Active Directory Python Connector

Read, Write, and Update Active Directory with Python

Easily connect Python-based Data Access, Visualization, ORM, ETL, AI/ML, and Custom Apps with Active Directory!


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Python Connector Libraries for Active Directory Data Connectivity. Integrate Active Directory with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Active Directory data with Python and any Python-based applications.

Features

  • Compatible with LDAP v2 and LDAP v3
  • Customize table schema, splitting ObjectClass attributes into individual rows and Description attributes into their own columns
  • Connect to live Active Directory data, for real-time data access
  • Full support for data aggregation and complex JOINs in SQL queries
  • Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
  • Seamless integration with leading BI, reporting, and ETL tools and with custom applications

Specifications

  • Python Database API (DB-API) Modules for Active Directory with bi-directional access.
  • Write SQL, get Active Directory data. Access Active Directory through standard Python Database Connectivity.
  • Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
  • Simple command-line based data exploration of Active Directory Users, Groups, Roles, Contacts, and more!
  • Full Unicode support for data, parameter, & metadata.


CData Python Connectors in Action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

WATCH THE PYTHON CONNECTOR VIDEO OVERVIEW

Python Connectivity with Active Directory

Full-featured and consistent SQL access to any supported data source through Python


  • Universal Python Active Directory Connectivity

    Easily connect to Active Directory data from common Python-based frameworks, including:


    • Data Analysis/Visualization: Jupyter Notebook, pandas, Matplotlib
    • ORM: SQLAlchemy, SQLObject, Storm
    • Web Applications: Dash, Django
    • ETL: Apache Airflow, Luigi, Bonobo, Bubbles, petl
  • Popular Tooling Integration

    The Active Directory Connector integrates seamlessly with popular data science and developer tooling like Anaconda, Visual Studio Python IDE, PyCharm, and more. Real Python,

  • Replication and Caching

    Our replication and caching commands make it easy to copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, etc. The replication commands include many features that allow for intelligent incremental updates to cached data.

  • String, Date, Numeric SQL Functions

    The Active Directory Connector includes a library of 50 plus functions that can manipulate column values into the desired result. Popular examples include Regex, JSON, and XML processing functions.

  • Collaborative Query Processing

    Our Python Connector enhances the capabilities of Active Directory with additional client-side processing, when needed, to enable analytic summaries of data such as SUM, AVG, MAX, MIN, etc.

  • Easily Customizable and Configurable

    The data model exposed by our Active Directory Connector can easily be customized to add or remove tables/columns, change data types, etc. without requiring a new build. These customizations are supported at runtime using human-readable schema files that are easy to edit.

  • Enterprise-class Secure Connectivity

    Includes standard Enterprise-class security features such as TLS/ SSL data encryption for all client-server communications.

Connecting to Active Directory with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Active Directory from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Active Directory
  • Query Active Directory to retrieve or update data
  • Connect your Active Directory data with Python data tools.


Connecting to Active Directory in Python

To connect to your data from Python, import the extension and create a connection:

import cdata.active directory as mod
conn = mod.connect("User=user@domain.com; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Users")
 
rs = cur.fetchall()
 
for row in rs:
print(row)

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

Visualize Active Directory Data with pandas

The data-centric interfaces of the Active Directory Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

engine = create_engine("active directory///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM Users", engine)

df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

Active Directory Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the Active Directory Connector as easily as interacting with a database table.