Version 0.45.1
This patch release addresses some regressions reported in the 0.45.0 release and adds support for NumPy 1.17:
* accept scalar/0d-arrays
* Fix. Parfors reduction vars not deleted.
* Use process level locks for fork() only.
* Try to fix.
* Fix np1.17 isnan, isinf, isfinite ufuncs
* Fix np.interp for np1.17 nan handling
* Fix nump1.17 random function non-aliasing
Version 0.45.0
In this release, Numba gained an experimental numba.typed.List container as a future replacement of the reflected list. In addition, functions decorated with parallel=True can now be cached to reduce compilation overhead associated with the auto-parallelization.
Enhancements from user contributed PRs (with thanks!):
James Bourbeau added the Numba version to reportable error messages, added the signature parameter to inspect_types, improved the docstring of normalize_signatur, and fixed by adding reference counting to register_dispatcher
Guilherme Leobas implemented the dominator tree and dominance frontier algorithms
Nick White fixed the issue with round in the CUDA target.
Joshua Adelman added support for determining if a value is in a range (i.e. x in range(...)), and added windowing functions (np.bartlett, np.hamming, np.blackman, np.hanning, np.kaiser) from NumPy.
Lucio Fernandez-Arjona added support for np.select
Rob Ennis added support for np.flatnonzero
Keith Kraus extended the __cuda_array_interface__ with an optional mask attribute.
Gregory R. Lee replaced deprecated use of inspect.getargspec
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