numba
https://github.com/numba/numba
Python
NumPy aware dynamic Python compiler using LLVM
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- Issues
- Standard container like C+ STL
- Wrong list result with parallel=True despite no resizing and no cross-thread access of the list
- CUDA - Inline literal in (...) statements
- CUDA: Error handling variables not added to the `@llvm.used` list
- Support for Advanced Numpy dtypes
- Introduce `context.call_overload` and raise dynamic exception in `guard_match_core_dims`
- Unable to convert generator returning 1D arrays into a 2D array using fromiter/vstack
- give primitive types a faster key&value compare, copy, and zero methods in TypedDict
- [Feature Request] `key_equal`, `copy_key`, `zero_key` in dict is slower than direct assignment if key type is primitive
- Type inference leads to libNVVM bugs on 0.59.1
- Docs
- Python not yet supported