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Siu Kwan Lam edited this page Jan 22, 2019 · 2 revisions

Attendees: Ehsan, Stuart, Stan, Siu

0. Feature Discussion

  • Default arguments in @overload_method?
    • @overload_method does not accept default arguments, but @overload can.
    • Check Literal value in @overload_method
  • Any other features blocking refactoring of older Numba implementations?
    • @overload with explicit allowed type signatures
    • add new interface/abstract? types (i.e. ArrayLike) to help with writing these type signatures
      • don't use Python's class inheritance
    • Decide on new repo layout
    • Error handling of new errors
    • Note: keeping ASV benchmark updated
    • Note: refactoring numpy impl to use np.asarray(a:ArrayLike)
    • Note: split exception hierarchy to tell if it's user vs internal error.

1. New issues

  • #3675 - Will class definition be supported in the future of nopython mode?
  • #3674 - String Features
  • #3673 - Comparing tuples of strings error
    • has PR to fix this.
  • #3671 - parfors typing error for ne builtin
    • might be related to #3673
  • #3670 - Raspberry pi 3B+ pip install error
  • #3669 - Numba 0.42 crashes for large number of function calls containing conditional return
    • fix in IRBuilder to stop appending .endif when large.

Already Closed

  • #3667 - getitem on 0d arrays broken/unsupported

2. Open PRs

  • #3678 - [WIP] Support for str.split and str.join
    • will be blocked on default args to @overload_method
  • #3677 - Ensure all referenced compiled functions are linked properly
    • ready for review
  • #3676 - Fixes constant string lowering inside tuples
    • ready for review
  • #3672 - Avoid leaking memory when iterating over uniform tuple
    • i'm reviewing

Already Merged

  • #3668 - Add Azure Pipelines build badge

Old Active

View https://github.com/numba/numba/projects/10 instead

  • #3661 - Access C Struct as Numpy Structured Array

    • Awaiting re-review
  • #3660 - Added Ignore message to test numba.tests.test_lists.TestLists.test_mul_error…

    • Awaiting author
  • #3657 - np.max, np.min, np.nanmax, np.nanmin - support for complex dtypes

    • Ready for review
  • #3655 - WIP: support numpy.average

    • WIP
  • #3648 - Fail on @overload signature mismatch.

  • #3646 - Log internal errors encountered in typeinfer

    • Ready for review
  • #3645 - Enforce and fix that AbstractTemplate.generic must be returning a Sig…

    • Awaiting re-review
  • #3640 - [WIP] PassThruContainer

    • Author has new questions
  • #3638 - Fix frame injection in the dispatcher tracing path.

    • WIP
  • #3633 - Support for np.extract

    • Awaiting re-review
  • #3630 - np.where with broadcasting

    • Awaiting re-review
  • #3627 - Support for np.trapz

    • Awaiting review

Old

  • #3604 - [WIP] Support for np.interp

  • #3592 - WIP: Add dead branch prune before type inference.

    • bug in parfors related to dead code elimination?
  • #3561 - Fixing the boolean copy from data

    • In progress
  • #3556 - [WIP] Support for np.trim_zeros

    • in progress
  • #3519 - WIP: fix-3457 support of numpy repeat.

  • #3468 - Add support for np.clip and ndarray.clip.

    • depends on fix on @overload_method for kwargs
  • 3450 - [WIP] generated_jit for CUDA kernels

  • 3134 - [WIP] Cfunc x86 abi

    • Needs re-review
  • 3046 - Pairwise sum implementation.

  • #2999 - Support LowLevelCallable

  • #2942 - Fix linkage nature (declspec(dllexport)) of some test functions

  • #2894: [WIP] Implement jitclass default constructor arguments.

  • #2817: [WIP] Emit LLVM optimization remarks

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4. Next Release: Version 0.43, RC=Feb 26?, Final=March 5?

  • Initial dictionary support
  • ???
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