On behalf of the numba team I am pleased to announce a new version of Numba, 0.7. The release includes open sourced ufunc, open sourced array expression and slicing compilation, experimental python 3 support (many thanks to Hernan Grecco's continuous efforts to reach full compatibility), support for some typed containers, support for CFFI and improved ctypes support, and a variety of other features. Download: https://pypi.python.org/pypi/numba/0.7.0 Documentation: http://numba.pydata.org/numba-doc/0.7/ Github: https://github.com/numba/numba Numba will be part of the next anaconda CE release 1.4, to be released soon. Numba ====== Numba is an just-in-time specializing compiler for Python and NumPy code to LLVM for annotated functions (through decorators). It's goal is to seamlessly integrate with the Python scientific software stack and provide optimized native code and integration with native foreign languages. Dependencies: ============ * llvmpy 0.10.0 * meta (optional) * cython * numpy * LLVM 3.2 (3.1 might work but is not officially supported) Release notes: ============ * Open sourced single-threaded ufunc vectorizer * Open sourced NumPy array expression compilation * Open sourced fast NumPy array slicing * Experimental Python 3 support * Support for typed containers * typed lists and tuples * Support for iteration over objects * Support object comparisons * Preliminary CFFI support * Jit calls to CFFI functions (passed into autojit functions) * TODO: Recognize ffi_lib.my_func attributes * Improved support for ctypes * Allow declaring extension attribute types as through class attributes * Support for type casting in Python * Get the same semantics with or without numba compilation * Support for recursion * For jit methods and extension classes * Allow jit functions as C callbacks * Friendlier error reporting * Internal improvements * A variety of bug fixes Many thanks to everyone who contributed to this release! Hernan Grecco Ilan Schnell Jon Riehl Mark Florisson Martin Spacek Siu Kwan Lam Travis E. Oliphant Enjoy!