Python for Data Science

Data scientists and engineers are choosing Python for data science due to its easy-to-read nature and powerful analytics packages. It is now a popular programming language used for ensuring data quality, working with multiple data sources, and generating visualizations.

While the open source distribution of Python may be satisfactory for an individual, it doesn’t always meet the support, security, or platform requirements of large organizations.

This is why organizations choose ActivePython for their data science and big data projects, as well as for running numerical routines.

Pre-bundled with the most important packages Data Scientists need, ActivePython is pre-compiled so you and your team don’t have to waste time creating their own open source distribution. You can focus on what’s important–spending more time building algorithms and predictive machine learning models against your big data sources, and less time on environment configuration.

Big Data Connectors and Analytics Packages, Security and Support

ActivePython is 100% compatible with the open source Python programming language, but also provides the security and commercial support that organizations require.

ActivePython include open source libraries for data science, machine learning, scientific computing and working with big data. You can use ActivePython to manipulate data structures, run statistical models, regressions and time series tasks, as well as deliver visualizations to your business users and executives sooner–no matter where your data lives. Most data engineers are familiar with MATLAB, but ActivePython can offer a better alternative to MATLAB in many cases.

Some Popular Python Packages Pre-compiled in ActivePython

Python for Data Science, Big Data, Machine Learning and Scientific Computing

  • pandas (data analytics, dataframe analysis, and data manipulation)
  • NumPy (multi-dimensional arrays, array objects and high-performance numerical computations)
  • SciPy (algorithms to use with numpy)
  • HDF5 (store & manipulate data)
  • Matplotlib (data visualization, bar charts, scatterplots and histograms)
  • Bokeh (plotting library)
  • Jupyter (research collaboration)
  • PyTables (managing HDF5 datasets)
  • HDFS (C/C++ wrapper for Hadoop)
  • pymongo (MongoDB driver)
  • SQLAlchemy (Python SQL Toolkit)
  • redis (Redis access libraries)
  • Pillow (image processing library)
  • pyMySQL (MySQL connector)
  • scikit-learn (machine learning and model selection)
  • TensorFlow (deep learning with neural networks)*
  • scikit-learn (machine learning algorithms)
  • keras (high-level neural networks API)
  • seaborn (data visualization library)
  • NLTK (NLP, or natural language processing)

Python for Security:

  • cryptography (recipes and primitives)
  • pyOpenSSL (python interface to OpenSSL)
  • passlib (password hashing)
  • requests-oauthlib (Oauth support)
  • ecdsa (cryptographic signature)
  • PyCryptodome (PyCrypto replacement)
  • service_identity (prevents pyOpenSSL man-in-the-middle attacks)


Every organization is focused on security, but not every individual. Downloading a pre-compiled binary package quickly in order to get the job done is extremely common, but it can leave companies vulnerable if it contains compromised code.

By using ActivePython there is no more guessing if your Python distribution has incorporated the latest OpenSSL patch or if an unvetted package has been downloaded from an unverified repository.

We make the latest release of Python libraries available for every build, and provide timely security updates for critical issues.

Having served Fortune 1000 companies for 20 years, we understand the security requirements of organizations like yours, and can provide the peace of mind you need.

Learn more about Python Security here.


Our Python experts answer your questions by email or phone, so you and your team don’t have to rely on the open source community and public forums for help.

Versions and Platforms:

Our ActivePython builds and packages are consistent across all popular operating systems whether they are on-premise or in the cloud. We offer support for the following versions and platforms:

  • Support for Python 2.7.18, 3.5+
  • Support for Windows, Linux, and macOS

Learn more about all supported versions here.

Greater Security, Reduced Risk

There are significant advantages to using the ActivePython distribution in your organization. ActiveState Enterprise Tier provides guaranteed technical support, legal indemnification and quality assurance. With our Enterprise Tier, you’ll enjoy the advantages of open source while minimizing the risks.

By using ActivePython, you and your team can:

  • Ensure security of your models built in Python
  • Meet open source license requirements of your organization
  • Get support through private channels to keep your intellectual property safe
  • Avoid vendor lock-in. ActivePython is a commercial distribution of Python that is 100% compatible with the open source releases
  • Share your use of ActivePython with all your development teams

With deep roots in open source, and as a founding member of the Python Foundation, ActiveState actively contributes to the Python community. We offer the functionality, security and support that your enterprise needs while being compatible with the open source distribution of Python.

Download ActivePython Community Edition to get started or contact us to learn more about using ActivePython in your organization.

You can also start by trying our mini ML runtime for Linux or Windows that includes most of the popular Machine Learning libraries and Data Science packages, pre-compiled and ready to use in projects ranging from recommendation engines to dashboards.

*TensorFlow is available on ActivePython 2.7 for Linux and ActivePython 3.5 for Windows and MacOS; the Intel MKL is available on ActivePython 2.7 and 3.5 for Windows and Linux.

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