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To better help in troubleshooting build issues. Job limit might also
help with the memory limit issues we've been seeing.
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* Patch Mathematica
Mathematica installer moves all files and directories from installation directory to a backup one. The problem is that it also moves .spack to this backup location. Once it's done it does not move .spack back where it was.
My patch creates a copy of .spack to /tmp then moves it back right before exiting the install call.
* Make lint happy
* Use Spack native copy()
As suggested in peer-review let's:
- Copy .spack to stage directory so I don't have to use random
- Use Spack native copy() to do these operations
* Use join_path to create paths
As per peer-review suggestion:
- Use join_path to create paths
- Use copy_tree since we're copying a directory that could have sub-directories
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Release notes: https://github.com/DrTimothyAldenDavis/SuiteSparse/releases/tag/v5.7.2
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* Update package.py to include py-notebook 6.0.3 and sha
* Update package.py
* [py-notebook] updated py-tornado version requirements
* [py-notebook] reworked and reordered for readability
* [py-notebook] updated version requirement for py-jupyter-client
* [py-notebook] updated version requirements for py-jupyter-core
Co-authored-by: ehdeec <ehdeec@rit.edu>
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Applying to boost @1.56.0:1.72.0 as that's the version
range, where this patch can be cleanly applied. I was not
able to test this myself, but got positive feedback.
See: https://github.com/boostorg/build/issues/440
See: https://github.com/macports/macports-ports/pull/6726
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* new package: BART
This PR adds the BART (Berkeley Advanced Reconstruction Toolset)
package.
Despite the presence of CMake files, this package builds with a
Makefile. It looks like the project is moving away from cmake. The patch
for MKL has been committed upstream so should only be necessary for this
version of BART. The Makefile patch is meant for working with Spack and
would not be useful upstream. The bart scripts are still setup to use
bart with the subcommands being individual binaries. This patches those
to use the single binary with built-in subcommands and assumes that
spack is providing the TOOLBOX environment variable and setting PATH.
* Update var/spack/repos/builtin/packages/bart/package.py
Yes, '==' make more sense for a single string.
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
* The python dependencies are run time only.
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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* New patch release SLEPc 3.13.1
* Update var/spack/repos/builtin/packages/slepc/package.py
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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The performance improvements done in #14693 where leaving the DB in an inconsistent state when specs were removed from it. This PR updates the DB internal state whenever the DB is written to a file.
Note that we still cannot properly enumerate installed dependents, so there is a TODO in this code. Fixing that will require the dependents dictionaries in specs to be re-keyed (either by hash, or not keyed at all -- a list would do). See #11983 for details.
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* new package: py-youtube-dl + fixes for dependencies
This PR adds the py-youtube-dl program. In addition, there are a couple
of dependency packages that needed to be updated.
* ffmpeg
This is needed by py-youtube-dl. However, the spack ffmpeg recipe does
not include a lot of options, specifically, a dependency on openssl for
working with the https protocol.
- Added updated version.
- Added variants for the different licensing options.
- Added "meta" variants for X and drawtext. These turn on/off several
options.
- Set variants and dependencies for many options. The defaults are based
on the configuration settings in ffmpeg.
- Set dependencies that were missing or that will likely get pulled in
from the system.
* libxml2
The ffmpeg+libxml2 variant initially failed to build. The issue is that
libxml2 sets the headers property to
include_dir = self.spec.prefix.include.libxml2
The ffmpeg configure looks for prefix.include and fills in the rest.
This could probably be patched in ffmpeg but the headers property in the
libxml2 recipe is not consistent with the environment module or the
pkgconfig file, both of which set the headers path to prefix.include.
This PR sets the libxml2 headers property to
include_dir = self.spec.prefix.include
A spot check of a few libxml2 dependents did not rreveal any problems
with this change.
* Comment out libxml2 dependency in ffmpeg
The header property issue of the spack libxml2 package will need to be
resolved in another PR before libxml2 can be enabled in ffmpeg.
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* Add more tau variants
* Add more tau variants
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* new package: openmm
* dependency adjustments
* 1. modify dependencies
2. openmm dynamically compiles cuda kernels during runtime,
attempt to set up an environment that will work.
* Update var/spack/repos/builtin/packages/openmm/package.py
Co-Authored-By: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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* [py-jupyter-core] added version 4.6.3
* [py-jupyter-core] updated python version requirement
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* votca-tools: add mkl support
* Update package.py
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* votca-*: add v1.6_rc2
* votca-*: develop -> master
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If hdf was built with +libtirpc, we need to add -ltirpc to our link
flags.
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This adds a boolean 'libtirpc' variant to the hdf package.
Default is false, which will reproduce previous behavior (which
was to rely either on system xdr headers/library, or have hdf use
it's builtin xdr lib/headers (which are only for 32 bit))
If true, a dependency is added on 'libtirpc', and the LIBS and
CPPFLAGS are updated in the configure command to find the libtirpc
library and xdr.h header.
This is needed as RHEL8 (and presumably other distros have or will be)
removed xdr.h from glib-headers package,which was breaking the previous
behavior of using system xdr headers.
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* new package: py-torchsummary
* add numpy
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* opencv: assorted fixes
1. depends on blas when +lapack
2. set cuda nvcc flags for cuda_arch
3. let cuda/contrib builds work
4. depends on hdf5 when cuda/contrib
5. depends on ant when +java
6. allow protobuf version to be different
7. let opencv recompile it's protoc files.
* ant is a build-time dependency
* register +cuda~contrib as impossible.
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* New package: tensorboardX
* prune back to just what's in setup.py for now
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* Add new version of py-hypothesis
* Update package.py
* Update package.py
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The old api is found in version 0.3.0 which uses a different release
name, so the url function was updated to properly find the older
releases. Also, this removes the boost constraint on the 0.3.0 version
which does not need it.
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Signed-off-by: Tim Lane <tilne@amazon.com>
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* py-clint: new package at 0.5.1
* py-clint: update py-setuptools dep type
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* meson: Add 0.54.0
This change also improves the rpath patch we are using. Instead of never
removing the rpath, we now only keep it if running within Spack to
guarantee consistent behavior of Meson.
* meson: Make ninja a hard dependency
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* Update doxygen package
* Add new version releases 1.8.16 and 1.8.17
* Add mscgen as an optional dependency.
* Update doxygen package.py
Fix typo in mscgen dependency specification
* Remove whitespace for flake8
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* primer3: move to github, add 2.5.0, fix 2.3.7
- The Primer3 project moved to GitHub.
- update the URL
- compare the tarballs 2.3.7 from Sourceforge and github, no
significant differences (e.g. the Sourceforge tarball contained a
couple of "tmp" files).
- update the signature for the 2.3.7 tarball.
- @2.3.7 doesn't build with gcc@8.4.0, there's a dubious pointer/int
comparison that causes an error. It was fixed upstream in newer
versions, apply simple patch to this version so that it continues to
be build-able with newer compilers. See:
- https://github.com/primer3-org/primer3/issues/2
- https://github.com/primer3-org/primer3/issues/3
- Add info for @2.5.0, which builds cleanly.
* Flake8 cleanup
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* [gtk-doc] created template
* [gtk-doc] using custom url to standardize on dotted version
* [gtk-doc] added description and homepage
* [gtk-doc] added dependencies and added pdf variant
* [gtk-doc] commented out pdf variant
* [gtk-doc] cleaned up leftover fixmes
* [gtk-doc] flake8
* [gtk-doc] readded url
* [gtk-doc] python packages are build and run dependencies
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fixes #5029
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* py-torch: Fix v1.4.0 by adding v1.4.1
version/tag hack so that 1.4.0 is still workable.
see pytorch/pytorch#35149
* delete/disable fbgemm support in 1.4.0
* moved conflict
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* Skip collection of compiler link paths if compiler does not define a verbose flag
* modules config bug: allow user to configure a compiler without an explicit entry for loaded modules
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Newer versions of glib require Meson, so this PR adds support for that
using a hybrid approach. glib@5.28: will be built using Meson, older
versions still make use of Autotools.
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* Add libvdwxc as variant
* py-gpaw: add missing line for libvdwxc conditions
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- Updates Kripke URL to its Github repository.
- Adds previous Kripke versions.
- Adds 'caliper' variant.
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Change the build to work again, and be more in line with the other
tensorflow packages. Add version 2.1.
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