Numba: A High Performance Python Compiler
Numba is an open-source JIT compiler that translates a subset of Python and NumPy code into fast machine code using the LLVM compiler infrastructure. It is designed to provide high performance for numerical and scientific computing, enabling Python developers to achieve speeds comparable to C, C++, and Fortran without having to leave the Python ecosystem.
0
0 / day
0
0 / day
0 page per visit
0%
-
Domain Rating
-
Domain Authority
-
Citation Level
2012
English, etc
Website Key Features
Just-In-Time Compilation
Compiles Python functions to machine code at runtime, significantly speeding up numerical and scientific computations.
NumPy Support
Seamlessly integrates with NumPy, allowing for efficient operations on large arrays and matrices.
GPU Acceleration
Supports CUDA for GPU programming, enabling massive parallelization of computations.
Parallelization
Offers easy-to-use parallel loops and automatic parallelization features for multi-core CPUs.
Extensibility
Allows developers to extend Numba with custom types and functions, enhancing its capabilities.
Dynamic Typing
Maintains Python's dynamic typing while providing the performance benefits of static typing.
Interoperability
Works well with other Python libraries and tools, facilitating integration into existing workflows.
Community Support
Backed by a strong community of developers and users, providing a wealth of resources and support.
Additional information
License
Numba is released under the BSD 2-Clause 'Simplified' License.
Development
Actively developed and maintained by a community of contributors, with regular updates and new features.
Documentation
Comprehensive documentation is available, including tutorials, examples, and API references.
Community and Support
Numba has an active community forum, mailing lists, and IRC channels for support and discussions.
Performance
Numba can achieve performance comparable to that of compiled languages like C and Fortran for numerical computations.
Use Cases
Ideal for scientific computing, data analysis, machine learning, and any application requiring high-performance numerical computations.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for numba.pydata.org