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NumPy Enhancement Proposals - Home NumPy Enhancement Proposals - Home
  • Index
  • The Scope of NumPy
  • Current roadmap
  • Wish list
  • Wishlist
  • GitHub
  • Index
  • The Scope of NumPy
  • Current roadmap
  • Wish list
  • Wishlist
  • GitHub

Section Navigation

  • The Scope of NumPy
  • Current roadmap
  • Wish list
  • Meta-NEPs (NEPs about NEPs or active Processes)
    • NEP 0 — Purpose and process
    • NEP 23 — Backwards compatibility and deprecation policy
    • NEP 36 — Fair play
    • NEP 45 — C style guide
    • NEP 46 — NumPy sponsorship guidelines
    • NEP 48 — Spending NumPy project funds
    • NEP X — Template and instructions
  • Provisional NEPs (provisionally accepted; interface may change)
  • Accepted NEPs (implementation in progress)
    • NEP 41 — First step towards a new datatype system
    • NEP 42 — New and extensible DTypes
    • NEP 44 — Restructuring the NumPy documentation
    • NEP 51 — Changing the representation of NumPy scalars
  • Open NEPs (under consideration)
    • NEP 43 — Enhancing the extensibility of UFuncs
    • NEP 53 — Evolving the NumPy C-API for NumPy 2.0
    • NEP 54 — SIMD infrastructure evolution: adopting Google Highway when moving to C++?
  • Finished NEPs
    • NEP 1 — A simple file format for NumPy arrays
    • NEP 5 — Generalized universal functions
    • NEP 7 — A proposal for implementing some date/time types in NumPy
    • NEP 10 — Optimizing iterator/UFunc performance
    • NEP 13 — A mechanism for overriding Ufuncs
    • NEP 14 — Plan for dropping Python 2.7 support
    • NEP 15 — Merging multiarray and umath
    • NEP 18 — A dispatch mechanism for NumPy's high level array functions
    • NEP 19 — Random number generator policy
    • NEP 20 — Expansion of generalized universal function signatures
    • NEP 22 — Duck typing for NumPy arrays – high level overview
    • NEP 27 — Zero rank arrays
    • NEP 28 — numpy.org website redesign
    • NEP 29 — Recommend Python and NumPy version support as a community policy standard
    • NEP 32 — Remove the financial functions from NumPy
    • NEP 34 — Disallow inferring ``dtype=object`` from sequences
    • NEP 35 — Array creation dispatching with __array_function__
    • NEP 38 — Using SIMD optimization instructions for performance
    • NEP 40 — Legacy datatype implementation in NumPy
    • NEP 49 — Data allocation strategies
    • NEP 50 — Promotion rules for Python scalars
    • NEP 52 — Python API cleanup for NumPy 2.0
    • NEP 55 — Add a UTF-8 variable-width string DType to NumPy
    • NEP 56 — Array API standard support in NumPy's main namespace
  • Deferred and Superseded NEPs
    • NEP 2 — A proposal to build numpy without warning with a big set of warning flags
    • NEP 3 — Cleaning the math configuration of numpy.core
    • NEP 4 — A (third) proposal for implementing some date/time types in NumPy
    • NEP 6 — Replacing Trac with a different bug tracker
    • NEP 8 — A proposal for adding groupby functionality to NumPy
    • NEP 9 — Structured array extensions
    • NEP 11 — Deferred UFunc evaluation
    • NEP 12 — Missing data functionality in NumPy
    • NEP 21 — Simplified and explicit advanced indexing
    • NEP 24 — Missing data functionality - alternative 1 to NEP 12
    • NEP 25 — NA support via special dtypes
    • NEP 26 — Summary of missing data NEPs and discussion
    • NEP 30 — Duck typing for NumPy arrays - implementation
    • NEP 31 — Context-local and global overrides of the NumPy API
    • NEP 37 — A dispatch protocol for NumPy-like modules
    • NEP 47 — Adopting the array API standard
  • Rejected and Withdrawn NEPs
    • NEP 16 — An abstract base class for identifying "duck arrays"
    • NEP 17 — Split out masked arrays
  • Roadmap & NumPy enhancement proposals
  • Rejected and Withdrawn NEPs

Rejected and Withdrawn NEPs#

  • NEP 16 — An abstract base class for identifying "duck arrays"
  • NEP 17 — Split out masked arrays

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