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| -rw-r--r-- | doc/neps/roadmap.rst | 113 |
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diff --git a/doc/neps/roadmap.rst b/doc/neps/roadmap.rst index 8a2cc6e5c..b7e407244 100644 --- a/doc/neps/roadmap.rst +++ b/doc/neps/roadmap.rst @@ -1,5 +1,114 @@ ============= -NumPy roadmap +NumPy Roadmap ============= -Current version of roadmap goes here. +This is a live snapshot of tasks and features we will be investing resources +in. It may be used to encourage and inspire developers and to search for +funding. + +Interoperability protocols & duck typing +======================================== + +`__array_function__` +-------------------- +See `NEP 18`_ and a sample implementation_ + +Array Duck-Typing +----------------- +`NEP 22`_ `np.asduckarray()` + + +Mixins like `NDArrayOperatorsMixin`: + +- for mutable arrays +- for reduction methods implemented as ufuncs + +Better dtypes +------------- + +- Easier custom dtypes + - Simplify and/or wrap the current C-API + - More consistent support for dtype metadata + - Support for writing a dtype in Python +- New string dtype(s): + - Fixed width encoded strings (utf8, latin1, ...) + - Variable length strings (could share implementation with dtype=object, but are explicitly type-checked) + - One of these should probably be the default for text data. The current behavior on Python 3 is neither efficient nor user friendly. +- `np.int` should not be platform dependent +- better coercion for string + number + +Random number generation policy & rewrite +----------------------------------------- + +`NEP 19`_ and a `reference implementation`_ + +Indexing +-------- + +vindex/oindex `NEP 21`_ + +Infrastructure +-------------- + +NumPy is much more than just the code base itself, we also maintain +docs, CI, benchmarks, etc. + +- Rewrite numpy.org +- Benchmarking: improve the extent of the existing suite, and run & render + the results as part of the docs or website. + + - Hardware: find a machine that can reliably run serial benchmarks + - ASV produces graphs, could we set up a site? Currently at + https://pv.github.io/numpy-bench/, should that become a community resource? + +Functionality outside core +-------------------------- + +Some things inside NumPy do not actually match the `Scope of NumPy`. + +- A backend system for `numpy.fft` (so that e.g. `fft-mkl` doesn't need to monkeypatch numpy) + +- Rewrite masked arrays to not be a ndarray subclass -- maybe in a separate project? +- MaskedArray as a duck-array type, and/or +- dtypes that support missing values + +- Write a strategy on how to deal with overlap between numpy and scipy for `linalg` and `fft` (and implement it). + +- Deprecate `np.matrix` + +Continuous Integration +---------------------- + +We depend on CI to discover problems as we continue to develop NumPy before the +code reaches downstream users. + +- CI for more exotic platforms (e.g. ARM is now available from + http://www.shippable.com/, but it is not free). +- Multi-package testing +- Add an official channel for numpy dev builds for CI usage by other projects so + they may confirm new builds do not break their package. + +Typing +------ + +Python type annotation syntax should support ndarrays and dtypes. + +- Type annotations for NumPy: github.com/numpy/numpy-stubs +- Support for typing shape and dtype in multi-dimensional arrays in Python more generally + +NumPy scalars +------------- + +Numpy has both scalars and zero-dimensional arrays. + +- The current implementation adds a large maintenance burden -- can we remove + scalars and/or simplify it internally? +- Zero dimensional arrays get converted into scalars by most NumPy functions. + Can this be fixed? + +.. _`NEP 19`: https://www.numpy.org/neps/nep-0019-rng-policy.html +.. _`NEP 22`: http://www.numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html +.. _`NEP 18`: https://www.numpy.org/neps/nep-0018-array-function-protocol.html +.. _implementation: https://gist.github.com/shoyer/1f0a308a06cd96df20879a1ddb8f0006 +.. _`reference implementation`: https://github.com/bashtage/randomgen +.. _`NEP 21`: https://www.numpy.org/neps/nep-0021-advanced-indexing.html |