mkl-include
Intel® oneAPI Math Kernel Library
Decision gist · record as of 2026-08-14
Yes, if you are building or deploying MKL-dependent compiled extensions on Linux x86_64 or Windows x64 and are willing to manually configure MKLROOT. No, if you expect a pure-Python package or automatic environment setup. The proprietary license and platform limitations mean it is not a general-purpose math library—it is a system integration tool for Intel MKL users.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- MKLROOT environment variable must be configured manually post-installation; platform limited to Linux x86_64 or Windows x64; requires onemkl-license package.
- Medium install friction due to platform-specific wheels (Linux x86_64 and Windows x64 only) and a runtime dependency on onemkl-license.
- The package is actively maintained with a recent release.
License · maintenance · safety
(unclear) — Licensed under Intel Simplified Software License (proprietary), classified as unclear treatment. Users should review Intel's license terms before deploying in commercial or restricted environments.
last release 2026-07-01 (44 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 172,491 downloads/mo, #10,334 on PyPI
Alternatives
Verify before relying
pip install mkl-include
# After installation, set MKLROOT environment variable manually
# (not set automatically by PyPI installation)
import ctypes
# Link against MKL C interface via ctypes or compiler flags- Whether onemkl-license is freely available or requires separate licensing from Intel
- Specific Python version compatibility (requires_python is unspecified)
- Whether MKLROOT setup documentation covers all common deployment scenarios
What it is and what it does
mkl-include is Intel's Python package providing C and DPC++ language bindings to the oneAPI Math Kernel Library, a collection of highly optimized mathematical routines for linear algebra, Fourier transforms, and related computations. It targets developers building performance-critical numerical applications on Intel hardware. The package ships platform-specific wheels for Linux x86_64 and Windows x64, and depends on onemkl-license at runtime. It is not a standalone library—it provides headers and interfaces to call Intel MKL from C or C++ code, typically used by other libraries or compiled extensions rather than directly from Python.
The package is actively maintained and has been in production use since 2017. A key gotcha is that the MKLROOT environment variable is not set automatically during PyPI installation and must be configured manually according to Intel's developer documentation. This makes it less of a drop-in dependency and more of a system integration step, particularly relevant for containerized or CI/CD deployments.
Use it for
- Building compiled Python extensions (e.g., NumPy, SciPy) that link against Intel MKL for faster linear algebra
- Developing C/C++ applications that call MKL routines and need the header files and interface definitions
- Optimizing numerical workloads on Intel CPUs by providing access to threaded BLAS, LAPACK, and FFT kernels
- Setting up development environments where MKL-accelerated libraries are built from source
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or deploying MKL-dependent compiled extensions on Linux x86_64 or Windows x64 and are willing to manually configure MKLROOT.
No, if you expect a pure-Python package or automatic environment setup. The proprietary license and platform limitations mean it is not a general-purpose math library—it is a system integration tool for Intel MKL users.
Install
mkl-include on PyPI
Before you install
Medium install friction due to platform-specific wheels (Linux x86_64 and Windows x64 only) and a runtime dependency on onemkl-license. The package is actively maintained with a recent release.
MKLROOT environment variable must be configured manually post-installation; platform limited to Linux x86_64 or Windows x64; requires onemkl-license package.
License in practice
Licensed under Intel Simplified Software License (proprietary), classified as unclear treatment. Users should review Intel's license terms before deploying in commercial or restricted environments.
Quickstart
pip install mkl-include
# After installation, set MKLROOT environment variable manually
# (not set automatically by PyPI installation)
import ctypes
# Link against MKL C interface via ctypes or compiler flagsVerify before relying
- Whether onemkl-license is freely available or requires separate licensing from Intel
- Specific Python version compatibility (requires_python is unspecified)
- Whether MKLROOT setup documentation covers all common deployment scenarios
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packageonemkl-license |
| Maintenance | Actively maintained 44 days since the last release |
| First released | |
| Downloads | 172,491 / month, #10,334 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Other AudienceIntended Audience :: Science/ResearchIntended Audience :: System AdministratorsLicense :: Other/Proprietary LicenseOperating System :: POSIX :: LinuxTopic :: Software Development :: Libraries |
Evidence: mkl_include-2026.1.0-py2.py3-none-manylinux_2_28_x86_64.whl; mkl_include-2026.1.0-py2.py3-none-win_amd64.whl
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See also mkl · mkl-static · onemkl-license · onemkl-sycl-dft · onemkl-sycl-rng · onemkl-sycl-lapack · onemkl-sycl-blas · onemkl-sycl-sparse · dpcpp-cpp-rt · threadpoolctl