Accelerate computational packages: NumPy, scikit-learn, and more.

Optimize performance with integrated libraries and parallelism techniques.

Overcome challenges with slow performance across applications.

Who Needs This Product?

High-Performance Computing (HPC) Developers

Accelerate compute-intensive Python computational packages like NumPy, SciPy, and scikit-learn.

Data Scientists and Analysts

Easily implement and scale performance-packed, production-ready algorithms for data analysis.

Domain Experts

Access immediate optimized performance. Non-programmers can just download, install, and go.

Commercial Support with Intel® Parallel Studio XE

Intel® Distribution of Python* is included in our flagship product, Intel® Parallel Studio XE. This powerful, robust suite of software development tools has everything you need to write Python native extensions: C and Fortran compilers, numerical libraries, and profilers. Help boost application performance by taking advantage of the ever-increasing processor core counts and vector register widths available in processors based on technology from Intel and other compatible processors. The 30-day trial includes online customer support.

Free Trial


Community Forum

Get the help you need from the developer community and our tech experts through the public tool forum.


Priority Customer Support

New software purchases include a year of free software updates and confidential priority customer support through our Online Service Center. Get direct access to our technical experts when you need it. It is available when you purchase Intel Distribution for Python with Intel Parallel Studio XE or Intel® VTune™ Amplifer.

Online Service Center

Key Specifications

  • Target OS: Linux*, Windows* 7 and later, macOS*
  • Versions: Python* 2.7 and 3.5
  • Package Management: Conda and Continuum Anaconda Cloud
  • Compatible With: Microsoft Visual Studio*, PyCharm*
  • Python Packages: NumPy, SciPY, scikit-learn, pandas, matplotlib, Numba, Intel® Threading Building Blocks, pyDAAL, Jupyter, mpi4py, pip, and others.

Release Notes