What's Included
The following Python* packages are useful tools for day-to-day scientific and engineering work. You can get all of it by installing standalone distribution. Alternatively, you can install these packages individually into existing Python installation by the following command:
conda install <package-name> -c https://software.repos.intel.com/python/conda/
Additionally, two convenience metapackages intelpython3_core and intelpython3_full are offered to install a core subset of the following packages or all the following packages respectively:
Install core packages into existing Python installation:
conda install intelpython3_core -c https://software.repos.intel.com/python/conda/
Install all packages into existing Python installation:
conda install intelpython3_full -c https://software.repos.intel.com/python/conda/
Package and Environment Managers
Get essential tools for installing, updating, and deleting Python packages and environments.
Data Processing and Modeling Packages
Use these packages in numeric and data science workflows for data collection, ingestion, preprocessing, normalization, transformation, aggregation, and analysis.
Machine Learning Packages
Foundational packages that allow a machine to automatically learn from data without programming it explicitly.
Python Interpreter and Compilers
Use these tools for a versatile interactive experience and to achieve scaled performance.
Advanced Programming Packages
Essential packages that enable fine-grained controls for data management, devices management, concurrency, and parallelism.
Development Packages and Runtimes
Use these runtime packages for enabling performance across Intel-optimized Python packages.
Priority Support
Available through the Intel® oneAPI Base Toolkit.
Package and Environment Managers
Python* package and environment managers are essential tools for productivity. These allow for installation, updating, and removal of no longer needed packages from the Python environment. They also manage multiple Python environments customized by a user for multiple purposes or needs.
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Package |
Description |
References |
How to Get It |
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conda* |
A popular package manager that comes with the Python installation. You do not need to install it separately. |
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conda install conda -c https://software.repos.intel.com/python/conda/ conda install conda -c conda-forge conda install conda -c main Download Intel® Distribution for Python* Download Intel® AI Analytics Toolkit
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pip |
A classic Python package manager that comes with the Python installation. You do not need to install it separately. |
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conda install pip -c https://software.repos.intel.com/python/conda/ conda install pip -c conda-forge conda install pip -c main Download Intel® Distribution for Python* |
Data Processing and Modeling
Data processing is an essential part of numerical and data science workflows, and is based on numerical and statistical algorithms. It includes data collection, ingestion, preprocessing, normalization, transformation, aggregation, and analysis. Data analysis serves a basis for modeling of phenomena.
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Package |
Description |
References |
How to Get It |
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numpy |
A foundational math library for core operations on N-dimensional arrays, optimized for Intel CPUs through Intel® oneAPI Math Kernel Library (oneMKL). Optimizations include linear algebra, fast Fourier transform (FFT), universal functions, and random number generators (RNG). |
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conda install numpy -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple numpy Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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scipy |
A scientific library for numerical integration, interpolation, optimization, linear algebra, and statistics. The Intel-optimized version is based on oneMKL. |
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conda install scipy -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple scipy Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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numexpr |
A lazy evaluation of numerical expressions for NumPy that optimizes memory use and makes use of all available CPU cores. The Intel-optimized version is based on oneMKL. |
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conda install numexpr -c https://software.repos.intel.com/python/conda/ -c conda-forge Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mkl_service |
Python interfaces to oneMKL service functions for controlling MKL behavior. It is not typically necessary to install this package with Intel optimized NumPy, SciPy, or NumExpr because they come with this package. However, it may be needed with other Python packages that rely on oneMKL if fine-grain control is necessary. |
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conda install mkl-service -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple mkl-service Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mkl_fft |
Python interfaces to oneMKL FFT functions. It is not typically necessary to install this package with Intel-optimized NumPy or SciPy because they come with this package. However, it may be needed to directly access MKL FFT interfaces rather than through NumPy or SciPy. |
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conda install mkl_fft -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple mkl-fft Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mkl_umath |
Python interfaces to oneMKL vector math library (VML) functions. It is not typically necessary to install this package with Intel-optimized NumPy or NumExpr because they come with this package. However, it may be needed to directly access MKL VML interfaces rather than through NumPy or NumExpr. |
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conda install mkl_umath -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple mkl-umath Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mkl_random |
Python interfaces to oneMKL RNG functions. It is not typically necessary to install this package with Intel-optimized NumPy because it comes with this package. However, it may be needed to directly access MKL RNG interfaces rather than through NumPy. |
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conda install mkl_random -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple mkl-random Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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dpnp |
The Data Parallel Extensions for NumPy library implements a subset of NumPy that can be offloaded to Intel GPUs. Learn more about Data Parallel Extensions for Python. |
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conda install dpnp -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple dpnp Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
Foundational Machine Learning
Deep learning and machine learning are special models that allow a machine to automatically learn from data without programming it explicitly.
While Intel® Distribution for Python includes a few foundational machine learning packages, AI Tools provides a more comprehensive set of tools for deep learning and machine learning.
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Package |
Description |
Reference |
How to Get It |
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scikit-learn |
A comprehensive set of machine learning algorithms for classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. |
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conda install scikit-learn -c https://software.repos.intel.com/python/conda/ pip install scikit-learn Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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scikit-learn-intelex |
Intel® Extension for Scikit-learn* provides scikit-learn like interfaces for Intel® oneAPI Data Analytics Library (oneDAL). It is not typically necessary to install Intel Extension for Scikit-learn as it comes with Intel optimized scikit-learn. You can install the extension with standard scikit-learn to enable Intel optimizations and additional capabilities. |
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conda install scikit-learn-intelex -c https://software.repos.intel.com/python/conda/ pip install scikit-learn-intelex Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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xgboost |
XGBoost is a regularizing gradient boosting framework. |
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conda install xgboost -c https://software.repos.intel.com/python/conda/ pip install xgboost Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
Python Interpreter and Compilers
The Python interpreter is the core of a versatile interactive experience with the language. It is expressive, intuitive, and fast enough for interactive usage. It is robust and secure for enterprise installations.
Python compilers are an important addition to the Python interpreter for scaling up Python applications. While initial prototyping work is mostly interactive, in a production setting the Python interpreter may become too slow to process large volumes of data.
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Package |
Description |
Reference |
How to Get It |
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python |
A Python interpreter for best interactive experiences. Intel provides a robust and a secure build suitable for production enterprise environments. |
conda install python=[version] -c https://software.repos.intel.com/python/conda/ -c conda-forge Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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numba |
A just-in-time (JIT) compiler for a subset of Python and NumPy. It can generate highly efficient native code leveraging the latest Intel instructions such as Intel® Advanced Vector Extensions 2 (Intel® AVX2) and Intel® Advanced Vector Extensions 512 (Intel® AVX-512). It is also capable of generating multithreaded code through OpenMP* or oneAPI Threading Building Blocks (oneTBB) that uses all available CPU cores. |
conda install numba -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install numba Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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numba-dpex |
Data Parallel Extension for Numba allow compilation of Numba codes to any data parallel device with minimum code changes.
For more information read Data Parallel Extensions for Python. |
conda install numba-dpex -c https://software.repos.intel.com/python/conda/ Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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cython |
An optimizing static compiler for Python, which is useful in writing C extensions for Python. Unlike Numba, which supports a subset of Python, Cython is a superset of the Python language.
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conda install cython -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install Cython Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
Advanced Programming Packages
These are essential packages that enable fine-grained controls for data management, device management, concurrency, and parallelism.
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Package |
Description |
Reference |
How to Get It |
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tbb4py |
A library of composable multithreading based on oneTBB. It enables composability of two or more multithreaded modules by using the oneTBB library as a common work scheduler. oneTBB is a flexible performance library that supports scalable parallel programming using C++ code and is compliant with the ISO C++ standard. |
conda install tbb4py -c https://software.repos.intel.com/python/conda/ pip install -i https://pypi.anaconda.org/intel/simple tbb4py pip install tbb4py Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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smp |
A library that controls thread affinity and static partitioning. Useful in static multiprocessing (SMP) programs where each process uses multithreaded library. Lack of affinity or partitioning controls provided by SMP leads to quadratic oversubscription of CPU cores by significantly degrading performance. |
conda install smp -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install smp Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mpi4py |
A Python binding for MPI. Comes with Intel® MPI Library acceleration. |
conda install mpi4py -c https://software.repos.intel.com/python/conda/ -c conda-forge python -m pip install mpi4py Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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dpctl |
A Data Parallel Control library that helps to manage CPU and GPU devices through Python. It also implements the Python Array API standard. Learn more about Data Parallel Extensions for Python. |
conda install dpctl -c https://software.repos.intel.com/python/conda/ -c conda-forge pip install -i https://pypi.anaconda.org/intel/simple dpctl Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
Development Packages and Runtimes
Runtime packages are foundational for enabling Python performance. However, if you're a developer of a Python project that relies on built-in Intel libraries, you will also need the related development and runtime packages to ship your project.
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Package |
Description |
Reference |
How to Get It |
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mkl |
A Python package that provides all you need to ship oneMKL with your project. |
conda install mkl -c https://software.repos.intel.com/python/conda/ pip install mkl pip install -i https://pypi.anaconda.org/intel/simple mkl Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |
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mkl-devel |
A development package for oneMKL. |
conda install mkl-devel -c https://software.repos.intel.com/python/conda/ pip install mkl-devel |
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mkl-include |
A development package for oneMKL consisting of include files only. |
conda install mkl-include -c https://software.repos.intel.com/python/conda/ pip install mkl-include pip install -i https://pypi.anaconda.org/intel/simple mkl-dpcpp |
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mkl-static |
A development package for oneMKL consisting of static files only. |
conda install mkl-static -c https://software.repos.intel.com/python/conda/ pip install mkl-static |
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mkl-dpcpp |
A Python package that provides all you need to ship oneMKL with your project. Learn more about Data Parallel Extensions for Python. |
conda install mkl-dpcpp -c https://software.repos.intel.com/python/conda/ pip install mkl-dpcpp conda install intelpython3_full -c https://software.repos.intel.com/python/conda/ Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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mkl-devel-dpcpp |
A development package that provides all you need for oneMKL development for SYCL devices. Learn more about Data Parallel Extensions for Python. |
conda install mkl-devel-dpcpp -c https://software.repos.intel.com/python/conda/ pip install mkl-devel-dpcpp |
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dal |
A Python package that provides all you need to ship oneDAL with your project. |
conda install dal -c https://software.repos.intel.com/python/conda/ pip install dal conda install intelpython3_full -c https://software.repos.intel.com/python/conda/ Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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dal-devel |
A development package that provides all you need for development with oneDAL. |
conda install -c https://software.repos.intel.com/python/conda/ dal-devel pip install dal-devel |
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dal-include |
A development package that provides oneDAL include files only. |
conda install -c https://software.repos.intel.com/python/conda/ dal-include pip install dal-include |
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dal-static |
A development package that provides oneDAL include files only. |
conda install -c https://software.repos.intel.com/python/conda/ dal-static pip install dal-static |
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ipp |
Python package that provides all you need to ship Intel® Integrated Performance Primitives (Intel® IPP) with your project. |
conda install ipp -c https://software.repos.intel.com/python/conda/ pip install ipp conda install intelpython3_full -c https://software.repos.intel.com/python/conda/ |
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ipp-devel |
A development package that provides all you need for development with Intel IPP. |
conda install ipp-devel -c https://software.repos.intel.com/python/conda/ pip install ipp-devel |
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ipp-include |
A development package that provides Intel IPP header files only. |
conda install ipp-include -c https://software.repos.intel.com/python/conda/ pip install ipp-include |
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ipp-static |
A development package that provides Intel IPP header files only. |
conda install ipp-static -c https://software.repos.intel.com/python/conda/ pip install ipp-static |
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tbb |
A Python package that provides all you need to ship oneTBB with your project. |
conda install tbb -c https://software.repos.intel.com/python/conda/ pip install tbb pip install -i https://pypi.anaconda.org/intel/simple tbb Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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tbb-devel |
A development package that provides all you need for development with oneTBB. |
conda install tbb-devel -c https://software.repos.intel.com/python/conda/ pip install tbb-devel |
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impi_rt |
Python package that provides all you need to ship Intel® MPI with your project. |
conda install -c https://software.repos.intel.com/python/conda/ impi_rt pip install impi-rt conda install intelpython3_full -c https://software.repos.intel.com/python/conda/ Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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impi-devel |
A development package that provides all you need for development with Intel® MPI. |
conda install -c https://software.repos.intel.com/python/conda/ impi-devel pip install impi-devel |
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intel-openmp |
A Python package that provides all you need to ship OpenMP* with your project. |
conda install intel-openmp -c https://software.repos.intel.com/python/conda/ pip install -i https://pypi.anaconda.org/intel/simple intel-openmp pip install intel-openmp Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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intel-opencl-rt |
A Python package that provides all you need to ship OpenCL™ Runtimes with your project. |
conda install intel-opencl-rt -c https://software.repos.intel.com/python/conda/ pip install -i https://pypi.anaconda.org/intel/simple intel-opencl-rt pip install intel-opencl-rt Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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icc_rt |
A Python package that provides all you need to ship your project that has native code compiled with Intel® C and Intel® C++ compilers. |
conda install icc_rt -c https://software.repos.intel.com/python/conda/ pip install icc-rt conda install intelpython3_full -c https://software.repos.intel.com/python/conda/ Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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fortran-rt |
A Python package that provides all you need to ship your project that has native code compiled with Intel® Fortran Compiler. |
conda install intel-fortran-rt -c https://software.repos.intel.com/python/conda/ pip install -i https://pypi.anaconda.org/intel/simple intel-fortran-rt pip install intel-fortran-rt Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud
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dpcpp-cpp-rt |
A Python package that provides all you need to ship your project and that has native code compiled with Intel® oneAPI DPC++ Compiler. Learn more about Data Parallel Extensions for Python.
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Intel oneAPI DPC++/C++ Compiler Developer Guide and Reference |
conda install dpcpp-cpp-rt -c https://software.repos.intel.com/python/conda/ pip install -i https://pypi.anaconda.org/intel/simple dpcpp-cpp-rt pip install dpcpp-cpp-rt Download Intel Distribution for Python Download AI Tools Access Intel Developer Cloud |