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inpydata/numexpr (press backspace or delete to remove)

Is it possible, to use **kwargs on compiled expressions? Currently I get always error like result = compiled_expr.run(a=a, b=b, c=c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ValueError: number ...
  • mhechthz
  • 3
  • Opened 
    4 days ago
  • #516

I am trying to investigate a regression in pandas test suite involving numexpr evaluation, where we have some tests that seem to have started failing with the recent release of numpy 2.3.0. I have been ...
  • jorisvandenbossche
  • 2
  • Opened 
    on Jun 12
  • #515

Hello, In this module of Awkward Array: https://github.com/scikit-hep/awkward/blob/main/src/awkward/_connect/numexpr.py we implement bindings of awkward arrays to numexpr so that numexpr can evaluate ...
  • ikrommyd
  • 7
  • Opened 
    on Jun 10
  • #514

https://numexpr.readthedocs.io/en/latest/release_notes.html
  • ngoldbaum
  • Opened 
    on Jun 9
  • #513

Python 3.14 optimized handling recounts which is likely causing test failures of numexpr: https://docs.python.org/3.14/whatsnew/3.14.html#whatsnew314-refcount While testing with Python 3.14.0b2 in Fedora ...
  • befeleme
  • 5
  • Opened 
    on May 29
  • #511

Trying to build for PyPy3.10: $ pip install numexpr==2.10.2 [...] running build_ext building numexpr.interpreter extension creating build/temp.macosx-11.0-arm64-pypy310/numexpr ...
Stale
  • Cerebus
  • 5
  • Opened 
    on May 22
  • #510

I want to use numpy s math function and I try: evaluate( log2(x) , { log2 : numpy.log2}), it gives errors.
Stale
  • westNeighbor
  • 2
  • Opened 
    on Apr 22
  • #509

This tracking issue aims to collect all the issues and PRs related for the current free-threaded CPython 3.13 (a.k.a. no-GIL ) builds. For context, this new experimental CPython version enables multithreaded ...
  • andfoy
  • 18
  • Opened 
    on Feb 13
  • #503

As promised, you can now [1] do a runtime check for PyArray_RUNTIME_VERSION = NPY_2_3_API_VERSION. If this is the case, NPY_MAXARGS is irrelevant (integer number of operands supported). NumPy always raised ...
Stale
  • seberg
  • 4
  • Opened 
    on Jan 7
  • #502

I changed the NumPy buffering setup a bit to simplify the code and make it faster in general. This probably has little or no effect on numexpr (the core loop size may be smaller occasionally, but you ...
  • seberg
  • 5
  • Opened 
    on Dec 20, 2024
  • #500
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