The `tbb` library provides Intel® oneAPI Threading Building Blocks (oneTBB), a C++ template library for parallel programming. The Python package primarily distributes the oneTBB C++ runtime libraries and headers, enabling other Python packages (e.g., NumPy, SciPy) to leverage TBB for parallelization. It is currently at version 2022.3.1 and sees regular updates, typically a few times per year, to introduce new features and address issues.
pip install tbbVerified import paths — ran on the pinned version, not inferred.
Demonstrates how to import the `tbb` package to retrieve information about the installed Intel oneTBB C++ library, such as its version and file system paths. This is useful for verifying installation or for C++/Python interoperability projects.
Understand that `tbb` is a backend dependency provider. For Python parallelization, consider libraries like `joblib`, `numba`, or native `multiprocessing`.
Update C++ build scripts or environment configurations to use `C_INCLUDE_PATH` and `CPLUS_INCLUDE_PATH` instead of `CPATH` when building against TBB 2022.2.0 or newer.
Ensure your development environment has a compatible C++ compiler (e.g., GCC, Clang, MSVC) and a build system (e.g., CMake, Make) configured to locate and link against the TBB libraries.
When writing or updating C++ code that uses TBB, prefer `oneapi::tbb::` for types and functions. For older code, verify that the TBB version you are linking against provides the necessary `tbb::` aliases.
For C++ code, migrate usage from `tbb::task_scheduler_init` to `tbb::task_arena` to leverage improved control and modern best practices for task scheduling.
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