| Commit message (Collapse) | Author | Age | Files | Lines |
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`load_module` is deprecated since python 3.4 and will be removed in python 3.12.
Use `exec_module` instead. Provide a convenience function in `distutils.misc_utils`
instead of `npy_load_module` from `compat.py3k`.
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This is just a technical prototype to measure and discuss the impact and
implication of moving to C++ for kernel code generation.
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The only reasons I can think for this to fail are an incomplete
installation or an environment hostile to fork(), both of which should
probably be fixed before trying to compile NumPy.
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The old function only handled the default `/cygdrive` prefix. This
can be customized to different values: `/` and `/mnt` are both common.
`/proc/cygdrive` does the same thing, regardless of user customization.
`cygpath` handles all of these. There's also a C function if you'd
prefer to avoid the `fork()` call, which tends to be slow on Cygwin.
Edit: Fix the cyg2win32 function to have correct types.
It returned bytes earlier; this should return a string.
Edit: Fix docsrting to follow numpydoc.
BLD,DOC: Expand documentation for cyg2win32
Fix a misleading statement, and expand on the things `cygpath`
handles that can otherwise be tricky to get right.
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* Accelerate in "NumPy 1.21+".
I thought the NumPy 1.20.0 release note decommissioned "the Accelerate library as a candidate" but it doesn't mention BLAS.
https://github.com/numpy/numpy/pull/15759/files#diff-6fde01624b4d27874d419c0f8aeae3743c4f5e7e1c9f2b039eb453a714d0cbb1R396 seems to affect both but
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`:numpy:`
Thanks, Matti!
Can you illuminate what the colons do in pip install? The doc webpage and CLI help says:
> Accepts either ":all:" to disable all binary packages, ":none:" to empty the set (notice the colons), or one or more package names with commas between them **(no colons).**
Co-authored-by: Matti Picus <matti.picus@gmail.com>
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* Give the OS-specific site-packages directories for NumPy's OpenBLAS.
* Include the `pip install numpy --only-binary numpy` variation, but not `:numpy:` since pip install doesn't document that. `pip install --only-binary numpy numpy` also works but that's confusing to parse.
* Drop the sentence on the Accelerate bug on macOS < 11.3 since this isn't the place for it.
* Also drop the search-order part about Accelerate? This applies to Numpy 1.19 as well as 1.21+.
* Clarify the part about finding external BLAS/LAPACK libs.
Some doc should explain what people need to know about installation. If they need portable, reproducible results, they should probably use the same BLAS/LAPACK libs compiled with the same compiler everywhere.
It's unfortunate to install NumPy + SciPy linked to Accelerate, along with more pips, only to discover that NumPy won't load on their Mac and have to start over. Or will SciPy reject the older LAPACK API and have problems using different BLAS/LAPACK libs?
Installing pips in Docker takes over an hour (vs. 15 minutes) if linking NumPy and SciPy to an external BLAS/LAPACK (and another pip conditionally compiles from source if NumPy did).
Worse to have to debug CI failures because their CI on Linux computes different output than Accelerate.
Should this also explain how to tell which release of OpenBLAS is included in a NumPy installation? (What got us into installing NumPy from source was needing an OpenBLAS bug fix release.)
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... per recent numpy-discussion@python.org discussion.
My aim was to explain the rules clearly including background that developers might need to learn.
I made some guesses to fill in details. For sure let me know whatever's wrong or unclear here.
Should the website installation page https://numpy.org/install/ link to this doc so developers can learn how to install NumPy for their situation?
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Threading is guaranteed to be supported in Python 3.7+
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* replace superfluous single-character regex character
classes with their literal string equivalents; this
avoids the overhead associated with a character class
when there's only a single character enclosed (so there's
no benefit to the class overhead)
* for more information see:
Chapter 6 of:
Friedl, Jeffrey. Mastering Regular Expressions. 3rd ed.,
O’Reilly Media, 2009.
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The new tags look like '1.21.0.dev0+98.gaa0453721f', where '98' is the
number of commits since the 1.21.0 branch was started and 'aa0453721f'.
The chosen form may be specified in the 'setup.cfg' file. This PR adds
two new files 'numpy/_version.py' and 'numpy/version.py'. The latter
is kept because it is part of the public API and is actually used by
some downstream projects, but it is no longer dynamically created.
See https://github.com/python-versioneer/python-versioneer/ for more
information.
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Part of changes for #17620 to prevent importing numpy during builds to support cross compilation.
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numpy.distutils generates a function `__config__.show`. This change
makes the docstring of that function complete (with the required
imports) and runnable. This prevents numpy.distutils from adding
doctests that will fail -- if picked-up by the test runner.
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numpy/distutils/misc_util.py (gh-#17051)
see #17012 item 13
Co-authored-by: Jakob <jakobjakobson13@posteo.de>
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* MAINT: use list-based APIs to call subprocesses
* TST, MAINT: add a test for mingw32ccompiler.build_import, clean up lib2def
Co-authored-by: Matti Picus <matti.picus@gmail.com>
Co-authored-by: Eric Wieser <wieser.eric@gmail.com>
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Thanks to Sergey Kojoian for the original patch to create
the docstring.
Closes gh-9258.
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This replaces basestring with str except in
- tools/npy_tempita/
- numpy/compat/py3k.py
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MAINT: cleanup use of sys.exc_info
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This code originates from python 2.6, before there was an `as` clause in `except`.
This removes all callers of `numpy.distutils.compat.get_exception`.
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Inheriting from object was necessary for Python 2 compatibility to use
new-style classes. In Python 3, this is unnecessary as there are no
old-style classes.
Dropping the object is more idiomatic Python.
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As numpy is Python 3 only, these import statements are now unnecessary
and don't alter runtime behavior.
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Allow overriding npy-pkg-config directory using the NPY_PKG_CONFIG_PATH
environment variable, making it easier to use numpy in cross-compilation
setups.
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This is generating a SyntaxWarning.
It looks like it has been like this from
2006 (8869df5b1cba1ffeda6d772eee1a7507fe18bdef) when this first came
into the code base.
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This makes it easier to visually jump between functions.
A couple places have changed to not emit leading whitespace where they previously did. Since this is C code and not fortran, that doesn't matter.
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Not super important, but saves some lines. Only the low-hanging ones here.
Found while tracking down an unrelated ResourceWarning
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* BUG: Use subprocess.check_output to avoid leaking file handles
This emitted a ResourceWarning as previously written, as the streams never got closed.
This change also detects errors in `svnversion` and `hg`, rather than ignoring the error code and hoping stdout contains a revision anyway.
* BUG: Fix distutils.get_version on python 3
Previously, this would throw `TypeError: cannot use a string pattern on a bytes-like object`, which would then be silenced and never seen.
The previous commit stopped silencing this error, so now everything is visibly broken rather than silently broken
Changing the strings to raw strings fixes the problem
* BUG: Don't use `close_fds`, which fails on windows
This argument was introduced along with subprocess in f5afa7836d56640f25ff3fbd2c59b8dcf016e26f to replace `popen4`, and probably wasn't necessary in the first place.
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(#12448)
* Review F401,F841,F842 flake8 errors (unused variables, imports)
* Review comments
* More tests in test_installed_npymath_ini
* Review comments
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MAINT: delay import of distutils.msvccompiler to avoid warning on non-Windows.
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