{"library":"onemkl-license","title":"Intel oneAPI Math Kernel Library License","description":"Intel oneAPI Math Kernel Library (oneMKL) is a collection of optimized math routines for scientific, engineering, and financial applications, including BLAS, LAPACK, sparse solvers, FFTs, and vector math. The `onemkl-license` PyPI package provides the licensing information for Intel oneMKL. It is not a direct Python-callable library for mathematical computations but rather a component that signifies the presence and licensing of the underlying oneMKL binaries, which are typically utilized by other Python packages (e.g., NumPy, SciPy) or through specific Python bindings like `mkl-service`, `mkl-fft`, and `mkl-random`. The current version is 2025.3.1, with releases tied to the oneAPI toolkit cadence.","language":"python","status":"active","last_verified":"Mon May 18","install":{"commands":["pip install onemkl-license"],"cli":null},"imports":["import onemkl_license\n# onemkl_license does not expose callable functions for math operations.\n# It's primarily a marker for the MKL installation and license.","import mkl\n# This import is typically for the 'mkl-service' package."],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import os\nimport platform\n\ntry:\n    # mkl-service is a common way to interact with MKL runtime settings\n    import mkl\n    print(f\"MKL version: {mkl.get_version()}\")\n    print(f\"MKL threading layer: {mkl.get_threading_layer()}\")\n\n    # Example: Setting the number of MKL threads\n    # mkl.set_num_threads(4)\n    # print(f\"MKL threads set to: {mkl.get_max_threads()}\")\n\nexcept ImportError:\n    print(\"mkl-service not installed or MKL not detected.\")\n    print(\"To use MKL functionalities in Python, consider installing 'mkl-service' \")\n    print(\"or a Python distribution that ships with MKL-optimized libraries (e.g., Anaconda).\")\n    print(\"The 'onemkl-license' package itself does not expose Python functions for computation.\")\n\n# Check for MKLROOT environment variable, often used in direct MKL installations\nmkl_root = os.environ.get('MKLROOT', 'Not set')\nprint(f\"MKLROOT environment variable: {mkl_root}\")\n\n# On Linux, check for MKL libraries in LD_LIBRARY_PATH\nif platform.system() == 'Linux':\n    ld_path = os.environ.get('LD_LIBRARY_PATH', 'Not set')\n    print(f\"LD_LIBRARY_PATH: {ld_path}\")\n    if mkl_root != 'Not set' and mkl_root not in ld_path:\n        print(\"Warning: MKLROOT is set but not in LD_LIBRARY_PATH. This might cause linking issues.\")\n","lang":"python","description":"This quickstart demonstrates how to check for the presence and configure the underlying Intel oneMKL through the `mkl-service` Python package, which is a common way to interact with oneMKL runtime settings. It also checks for relevant environment variables. The `onemkl-license` package itself does not provide functions for direct mathematical computation.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-18","installed_version":"2026.0.0","pypi_latest":"2026.0.0","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":1.5,"avg_import_s":null,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"onemkl-license","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"onemkl-license","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":1.4,"import_time_s":null,"mem_mb":null,"disk_size":"18M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"onemkl-license","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"onemkl-license","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":1.5,"import_time_s":null,"mem_mb":null,"disk_size":"20M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"onemkl-license","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"onemkl-license","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":1.4,"import_time_s":null,"mem_mb":null,"disk_size":"12M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"onemkl-license","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"onemkl-license","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":1.4,"import_time_s":null,"mem_mb":null,"disk_size":"12M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"onemkl-license","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"onemkl-license","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":1.7,"import_time_s":null,"mem_mb":null,"disk_size":"18M"}]}}