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3.5.0 (2024-04-29)

3.4.0 (2024-03-20)

  • Added support for Python interpreters statically linked against libc or linked against alternative implementations of libc like musl (on Alpine Linux for instance). #171

  • Added support for Pyodide #169

3.3.0 (2024-02-14)

  • Extended FlexiBLAS support to be able to switch backend at runtime. #163

  • Added support for FlexiBLAS #156

  • Fixed a bug where an unsupported library would be detected because it shares a common prefix with one of the supported libraries. Now the symbols are also checked to identify the supported libraries. #151

3.2.0 (2023-07-13)

  • Dropped support for Python 3.6 and 3.7.

  • Added support for custom library controllers. Custom controllers must inherit from the threadpoolctl.LibController class and be registered to threadpoolctl using the threadpoolctl.register function. #138

  • A warning is raised on macOS when threadpoolctl finds both Intel OpenMP and LLVM OpenMP runtimes loaded simultaneously by the same Python program. See details and workarounds at https://github.com/joblib/threadpoolctl/blob/master/multiple_openmp.md. #142

3.1.0 (2022-01-31)

  • Fixed a detection issue of the BLAS libraires packaged by conda-forge on Windows. #112

  • threadpool_limits and ThreadpoolController.limit now accept the string "sequential_blas_under_openmp" for the limits parameter. It should only be used for the specific case when one wants to have sequential BLAS calls within an OpenMP parallel region. It takes into account the unexpected behavior of OpenBLAS with the OpenMP threading layer. #114

3.0.0 (2021-10-01)

  • New object threadpooctl.ThreadpoolController which holds controllers for all the supported native libraries. The states of these libraries is accessible through the info method (equivalent to threadpoolctl.threadpool_info()) and their number of threads can be limited with the limit method which can be used as a context manager (equivalent to threadpoolctl.threadpool_limits()). This is especially useful to avoid searching through all loaded shared libraries each time. #95

  • Added support for OpenBLAS built for 64bit integers in Fortran. #101

  • Added the possibility to use threadpoolctl.threadpool_limits and threadpooctl.ThreadpoolController as decorators through their wrap method. #102

  • Fixed an attribute error when using old versions of OpenBLAS or BLIS that are missing version query functions. #88 #91

  • Fixed an attribute error when python is run with -OO. #87

2.2.0 (2021-07-09)

  • threadpoolctl.threadpool_info() now reports the architecture of the CPU cores detected by OpenBLAS (via openblas_get_corename) and BLIS (via bli_arch_query_id and bli_arch_string).

  • Fixed a bug when the version of MKL was not found. The "version" field is now set to None in that case. #82

2.1.0 (2020-05-29)

  • New commandline interface:

    python -m threadpoolctl -i numpy

    will try to import the numpy package and then return the output of threadpoolctl.threadpool_info() on STDOUT formatted using the JSON syntax. This makes it easier to quickly introspect a Python environment.

2.0.0 (2019-12-05)

  • Expose MKL, BLIS and OpenBLAS threading layer in information displayed by threadpool_info. This information is referenced in the threading_layer field. #48 #60

  • When threadpoolctl finds libomp (LLVM OpenMP) and libiomp (Intel OpenMP) both loaded, a warning is raised to recall that using threadpoolctl with this mix of OpenMP libraries may cause crashes or deadlocks. #49

1.1.0 (2019-09-12)

  • Detect libraries referenced by symlinks (e.g. BLAS libraries from conda-forge). #34

  • Add support for BLIS. #23

  • Breaking change: method get_original_num_threads on the threadpool_limits context manager to cheaply access the initial state of the runtime:

    • drop the user_api parameter;
    • instead return a dict {user_api: num_threads};
    • fixed a bug when the limit parameter of threadpool_limits was set to None.

    #32

1.0.0 (2019-06-03)

Initial release.