Path to this page:
./
math/py-numexpr,
Numerical expression evaluator for NumPy
Branch: CURRENT,
Version: 2.10.1,
Package name: py312-numexpr-2.10.1,
Maintainer: pkgsrc-usersNumexpr 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)
- (2024-10-14) Updated to version: py312-numexpr-2.10.1
- (2024-07-31) Updated to version: py311-numexpr-2.10.1
- (2024-02-12) Updated to version: py311-numexpr-2.9.0
- (2023-12-17) Updated to version: py311-numexpr-2.8.8
- (2023-09-30) Updated to version: py311-numexpr-2.8.7
- (2023-09-17) Updated to version: py311-numexpr-2.8.6
CVS history: (Expand)
2024-02-12 15:34:18 by Adam Ciarcinski | Files touched by this commit (2) | |
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) | |
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) | |
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) | |
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) | |
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
|
2023-07-01 10:37:47 by Thomas Klausner | Files touched by this commit (105) | |
Log message:
*: restrict py-numpy users to 3.9+ in preparation for update
|
2022-11-03 11:46:15 by Adam Ciarcinski | Files touched by this commit (2) | |
Log message:
py-numexpr: updated to 2.8.4
Changes from 2.8.3 to 2.8.4
---------------------------
* Support for Python 3.11 has been added.
* Thanks to Tobias Hangleiter for an improved accuracy complex `expm1` function.
While it is 25 % slower, it is significantly more accurate for the real component
over a range of values and matches NumPy outputs much more closely.
* Thanks to Kirill Kouzoubov for a range of fixes to constants parsing that was
resulting in duplicated constants of the same value.
* Thanks to Mark Harfouche for noticing that we no longer need `numpy` version
checks. `packaging` is no longer a requirement as a result.
|