./math/py-numexpr, Numerical expression evaluator for NumPy

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Branch: CURRENT, Version: 2.10.1, Package name: py312-numexpr-2.10.1, Maintainer: pkgsrc-users

Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.


Required to run:
[devel/py-setuptools] [math/py-numpy] [lang/python37]

Required to build:
[pkgtools/cwrappers]

Master sites:

Filesize: 99.199 KB

Version history: (Expand)

CVS history: (Expand)


   2024-11-11 08:29:31 by Thomas Klausner | Files touched by this commit (862) 
Log message:
py-*: remove unused tool dependency

py-setuptools includes the py-wheel functionality nowadays
   2024-10-14 08:46:10 by Thomas Klausner | Files touched by this commit (325) 
Log message:
*: clean-up after python38 removal
   2024-02-12 15:34:18 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numexpr: updated to 2.9.0

Changes from 2.8.8 to 2.9.0
---------------------------
* Support for PyPy. The full test suite
  should pass now, at least for the 3.10 version.
* Fixed more sanitizer issues.
* Modernized the test suite to avoid some warnings.
   2023-12-17 17:05:31 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numexpr: updated to 2.8.8

Changes from 2.8.7 to 2.8.8
---------------------------

* Fix re_evaluate not taking global_dict as argument. Thanks to Teng Liu
  (@27rabbitlt).

* Fix parsing of simple complex numbers.  Now, `ne.evaluate('1.5j')` works.
  Thanks to Teng Liu (@27rabbitlt).

* Fixes for upcoming NumPy 2.0:

  * Replace npy_cdouble with C++ complex. Thanks to Teng Liu (@27rabbitlt).
  * Add NE_MAXARGS for future numpy change NPY_MAXARGS. Now it is set to 64
    to match NumPy 2.0 value. Thanks to Teng Liu (@27rabbitlt).
   2023-09-30 12:35:06 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numexpr: updated to 2.8.7

Changes from 2.8.6 to 2.8.7
---------------------------

* More permissive rules in sanitizing regular expression: allow to access digits
  after the . with scientific notation.  Thanks to Thomas Vincent.

* Don't reject double underscores that are not at the start or end of a variable
  name (pandas uses those), or scientific-notation numbers with digits after the
  decimal point.  Thanks to Rebecca Palmer.

* Do not use `numpy.alltrue` in the test suite, as it has been deprecated
  (replaced by `numpy.all`).  Thanks to Rebecca Chen.

* Wheels for Python 3.12.  Wheels for 3.7 and 3.8 are not generated anymore.
   2023-09-17 11:04:12 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numexpr: updated to 2.8.6

Changes from 2.8.5 to 2.8.6
---------------------------

* The sanitization can be turned off by default by setting an environment variable,

    `set NUMEXPR_SANITIZE=0`

* Improved behavior of the blacklist to avoid triggering on private variables
  and scientific notation numbers.
   2023-08-07 07:24:27 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numexpr: updated to 2.8.5

Changes from 2.8.4 to 2.8.5
---------------------------

* A `validate` function has been added. This function checks the inputs, returning
  `None` on success or raising an exception on invalid inputs. This function was
  added as numerous projects seem to be using NumExpr for parsing user inputs.
  `re_evaluate` may be called directly following `validate`.
* As an addendum to the use of NumExpr for parsing user inputs, is that NumExpr
  calls `eval` on the inputs. A regular expression is now applied to help sanitize
  the input expression string, forbidding '__', ':', and ';'. Attribute access
  is also banned except for '.r' for real and '.i'  for imag.
* Thanks to timbrist for a fix to behavior of NumExpr with integers to negative
  powers. NumExpr was pre-checking integer powers for negative values, which
  was both inefficient and causing parsing errors in some situations. Now NumExpr
  will simply return 0 as a result for such cases. While NumExpr generally tries
  to follow NumPy behavior, performance is also critical.
* Thanks to peadar for some fixes to how NumExpr launches threads for embedded
  applications.
* Thanks to de11n for making parsing of the `site.cfg` for MKL consistent among
  all shared platforms.
   2023-08-02 01:20:57 by Thomas Klausner | Files touched by this commit (158) 
Log message:
*: remove more references to Python 3.7