tbb
Intel® oneAPI Threading Building Blocks (oneTBB)
Decision gist · record as of 2026-08-14
Yes, if you need task-based parallelism in Python and are comfortable with the Intel Simplified Software License terms. The library is actively maintained, has no known vulnerabilities, and is widely used (top 5000 PyPI packages). Install friction is moderate due to platform-specific wheels (x86_64 only). Verify Python version compatibility and license compatibility with your project before adopting.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires x86_64 architecture (manylinux_2_28 or Windows); Python version requirements unspecified in metadata.
- Medium install friction due to platform-specific wheels (manylinux and Windows x86_64 only); active maintenance with recent releases and a well-maintained upstream repository.
License · maintenance · safety
(unclear) — Licensed under Intel Simplified Software License (not SPDX-standardized); license treatment is unclear, so review the LICENSE.txt terms before adopting in proprietary or copyleft projects.
last release 2026-07-01 (44 days) · last repo commit 2026-08-14 · 6,712 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,293,341 downloads/mo, #2,671 on PyPI
Alternatives
Verify before relying
pip install tbb
import tbb
# oneTBB provides C++ parallelism primitives accessible through Python bindings- Exact Python version compatibility (requires_python is unspecified in metadata)
- Scope and stability of the Python API surface relative to the C++ library
- Whether tcmlib runtime dependency is a separate package or bundled
What it is and what it does
oneTBB is a task-based parallelism library that lets you write portable, scalable parallel code without managing threads directly. Instead of spawning and coordinating threads, you express logical parallelism through templates and task patterns; the library schedules work across available cores. The Python package wraps the C++ oneTBB library, making its parallelism primitives available to Python applications.
It is designed for developers who need to parallelize compute-intensive workloads—data processing, scientific computing, machine learning—without becoming threading experts. oneTBB emphasizes composability (mixing it with other threading packages) and future-proof scalability. The library is part of the oneAPI ecosystem and maintained by the UXL Foundation.
Use it for
- Parallelize data-parallel algorithms (e.g., map-reduce-style operations) across multiple cores in Python applications.
- Accelerate scientific and numerical computing by distributing independent tasks to available processors.
- Build scalable machine learning pipelines that exploit multi-core hardware without explicit thread management.
- Integrate task-based parallelism into existing Python applications that call C++ libraries.
- Write portable parallel code that scales automatically with the number of available cores.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need task-based parallelism in Python and are comfortable with the Intel Simplified Software License terms.
The library is actively maintained, has no known vulnerabilities, and is widely used (top 5000 PyPI packages). Install friction is moderate due to platform-specific wheels (x86_64 only). Verify Python version compatibility and license compatibility with your project before adopting.
Install
tbb on PyPI
Before you install
Medium install friction due to platform-specific wheels (manylinux and Windows x86_64 only); active maintenance with recent releases and a well-maintained upstream repository.
Requires x86_64 architecture (manylinux_2_28 or Windows); Python version requirements unspecified in metadata.
License in practice
Licensed under Intel Simplified Software License (not SPDX-standardized); license treatment is unclear, so review the LICENSE.txt terms before adopting in proprietary or copyleft projects.
Quickstart
pip install tbb
import tbb
# oneTBB provides C++ parallelism primitives accessible through Python bindingsVerify before relying
- Exact Python version compatibility (requires_python is unspecified in metadata)
- Scope and stability of the Python API surface relative to the C++ library
- Whether tcmlib runtime dependency is a separate package or bundled
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packagetcmlib |
| Maintenance | Actively maintained 44 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,293,341 / month, #2,671 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: tbb-2023.1.0-py2.py3-none-manylinux_2_28_x86_64.whl; tbb-2023.1.0-py3-none-win_amd64.whl
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See also tbb-devel · tcmlib · oneccl · intel-openmp · oneccl-devel · mkl · onemkl-license · mkl-static · onemkl-sycl-blas · mkl-include