* updates and fixes for libpressio
* differentiate between standalone and build tests
* add e4s tags
Co-authored-by: Robert Underwood <runderwood@anl.gov>
* include py-darshan
* include requested changes
* fix required versions
* fix style
* fix style
* Update package.py
* Update var/spack/repos/builtin/packages/py-darshan/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Boost 1.64.0 has build errors when building the python and MPI modules. This was previously just a comment in the package.py which allowed broken specs to concretize. The comments are now expressed in conflicts to prevent this.
Currently, external `PythonPackage`s cause install failures because the logic in `PythonPackage` assumes that it can ask for `spec["python"]`. Because we chop off externals' dependencies, an external Python extension may not have a `python` dependency.
This PR resolves the issue by guaranteeing that a `python` node is present in one of two ways:
1. If there is already a `python` node in the DAG, we wire the external up to it.
2. If there is no existing `python` node, we wire up a synthetic external `python` node, and we assume that it has the same prefix as the external.
The assumption in (2) isn't always valid, but it's better than leaving the user with a non-working `PythonPackage`.
The logic here is specific to `python`, but other types of extensions could take advantage of it. Packages need only define `update_external_dependencies(self)`, and this method will be called on externals after concretization. This likely needs to be fleshed out in the future so that any added nodes are included in concretization, but for now we only bolt on dependencies post-concretization.
Co-authored-by: Todd Gamblin <tgamblin@llnl.gov>
* [mfem] updates related to building with cuda
* [hypre] tweak to support building with external ROCm/HIP
* [mfem] more tweaks related to building with +rocm
* [mfem] temporary (?) workaround for issue #33684
* [mfem] fix style
* [mfem] fix +shared+miniapps install
* Add checksum for py-protobuf 4.21.7, protobuf 21.7
* Update var/spack/repos/builtin/packages/protobuf/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update package.py
* Update var/spack/repos/builtin/packages/protobuf/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update var/spack/repos/builtin/packages/protobuf/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update package.py
* Update package.py
* Delete protoc2.5.0_aarch64.patch
* Update package.py
* Restore but deprecate py-protobuf 3.0.0a/b; deprecate py-tensorflow 0.x
* Fix audit
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Spack currently creates a temporary sbang that is moved "atomically" in place,
but this temporary causes races when multiple processes start installing sbang.
Let's just stick to an idempotent approach. Notice that we only re-install sbang
if Spack updates it (since we do file compare), and sbang was only touched
18 times in the past 6 years, whereas we hit the sbang tempfile issue
frequently with parallel install on a fresh spack instance in CI.
Also fixes a bug where permissions weren't updated if config changed but
the latest version of the sbang file was already installed.
The `intel` compiler at versions > 20 is provided by the `intel-oneapi-compilers-classic`
package (a thin wrapper around the `intel-oneapi-compilers` package), and the `oneapi`
compiler is provided by the `intel-oneapi-compilers` package.
Prior to this work, neither of these compilers could be bootstrapped by Spack as part of
an install with `install_missing_compilers: True`.
Changes made to make these two packages bootstrappable:
1. The `intel-oneapi-compilers-classic` package includes a bin directory and symlinks
to the compiler executables, not just logical pointers in Spack.
2. Spack can look for bootstrapped compilers in directories other than `$prefix/bin`,
defined on a per-package basis
3. `intel-oneapi-compilers` specifies a non-default search directory for the
compiler executables.
4. The `spack.compilers` module now can make more advanced associations between
packages and compilers, not just simple name translations
5. Spack support for lmod hierarchies accounts for differences between package
names and the associated compiler names for `intel-oneapi-compilers/oneapi`,
`intel-oneapi-compilers-classic/intel@20:`, `llvm+clang/clang`, and
`llvm-amdgpu/rocmcc`.
- [x] full end-to-end testing
- [x] add unit tests
* Add zstd support for elfutils
Not defining `+zstd` implies `--without-zstd` flag to configure.
This avoids automatic library detection and thus make the build only
depends on Spack installed dependencies.
* Use autotools helper "with_or_without"
* Revert use of with_or_without
Using `with_or_without()` with `variant` keyword does not seem to work.
"spack install foo" no longer adds package "foo" to the environment
(i.e. to the list of root specs) by default: you must specify "--add".
Likewise "spack uninstall foo" no longer removes package "foo" from
the environment: you must specify --remove. Generally this means
that install/uninstall commands will no longer modify the users list
of root specs (which many users found problematic: they had to
deactivate an environment if they wanted to uninstall a spec without
changing their spack.yaml description).
In more detail: if you have environments e1 and e2, and specs [P, Q, R]
such that P depends on R, Q depends on R, [P, R] are in e1, and [Q, R]
are in e2:
* `spack uninstall --dependents --remove r` in e1: removes R from e1
(but does not uninstall it) and uninstalls (and removes) P
* `spack uninstall -f --dependents r` in e1: will uninstall P, Q, and
R (i.e. e2 will have dependent specs uninstalled as a side effect)
* `spack uninstall -f --dependents --remove r` in e1: this uninstalls
P, Q, and R, and removes [P, R] from e1
* `spack uninstall -f --remove r` in e1: uninstalls R (so it is
"missing" in both environments) and removes R from e1 (note that e1
would still install R as a dependency of P, but it would no longer
be listed as a root spec)
* `spack uninstall --dependents r` in e1: will fail because e2 needs R
Individual unit tests were created for each of these scenarios.
Somehow a network error when cloning the repo for ci gets
categorized by gitlab as a script failure. To make sure we retry
jobs that failed for that reason or a similar one, include
"script_failure" as one of the reasons for retrying service jobs
(which include "no specs to rebuild" jobs, update buildcache
index jobs, and temp storage cleanup jobs.
Add a `project` block to the toml config along with development and CI
dependencies and a minimal `build-system` block, doing basically
nothing, so that spack can be bootstrapped to a full development
environment with:
```shell
$ hatch -e dev shell
```
or for a minimal environment without hatch:
```shell
$ python3 -m venv venv
$ source venv/bin/activate
$ python3 -m pip install --upgrade pip
$ python3 -m pip install -e '.[dev]'
```
This means we can re-use the requirements list throughout the workflow
yaml files and otherwise maintain this list in *one place* rather than
several disparate ones. We may be stuck with a couple more temporarily
to continue supporting python2.7, but aside from that it's less places
to get out of sync and a couple new bootstrap options.
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
This change uses the aws cli, if available, to retrieve spec files
from the mirror to a local temp directory, then parallelizes the
reading of those files from disk using multiprocessing.ThreadPool.
If the aws cli is not available, then a ThreadPool is used to fetch
and read the spec files from the mirror.
Using aws cli results in ~16 times speed up to recreate the binary
mirror index, while just parallelizing the fetching and reading
results in ~3 speed up.
