numexpr
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Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
I saw that several bugs related to Python 3.13 have already been addressed, so I was wondering if numexpr already supports 3.13, and if so, if and when binary wheels...
There are a couple of issues in the way `numexpr.cpu.info` is used in `print_versions()`: 1) all the subclasses of `CPUInfoBase` have a class attribute `info`, whereas `CPUInfoBase` does not; this...
```python >>> ne.evaluate('a', local_dict={'a': 1}) array(1, dtype=int32) >>> ne.evaluate('a', global_dict={'a': 1}) KeyError: 'a' ``` The problem is a regression introduced in https://github.com/pydata/numexpr/commit/21ff376a0853aff6aea63343c6010d6434917319 because global_dict is not passed to re_evaluate (which...
I want to use numpy's math function and I try: evaluate("log2(x)", {"log2": numpy.log2}), it gives errors.
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...
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 expressions between awkward arrays. In the latest numexpr release...
https://numexpr.readthedocs.io/en/latest/release_notes.html
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 g++ -pthread -arch arm64 -DNDEBUG -O2 -fPIC -DNPY_TARGET_VERSION=NPY_1_23_API_VERSION -I/private/var/folders/vj/vkfg28_d3m36zls5s7mf5whh0000gn/T/pip-build-env-io43xb_n/overlay/lib/pypy3.10/site-packages/numpy/_core/include -I/Users/tmiller/.pyenv/versions/pypy3.10-7.3.17/envs/pypy-task-analysis/include -I/Users/tmiller/.pyenv/versions/pypy3.10-7.3.17/include/pypy3.10 -c...
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...