This commit fixes a subtle bug that may occur when
a package is a "possible_provider" of a virtual but
no "provides_virtual" can be deduced. In that case
the cardinality constraint on "provides_virtual"
may arbitrarily assign a package the role of provider
even if the constraints for it to be one are not fulfilled.
The fix reworks the logic around three concepts:
- "possible_provider": a package may provide a virtual if some constraints are met
- "provides_virtual": a package meet the constraints to provide a virtual
- "provider": a package selected to provide a virtual
Spack packages can now fetch versions from CVS repositories. Note
this fetch mechanism is unsafe unless using :extssh:. Most public
CVS repositories use an insecure protocol implemented as part of CVS.
Here we are adding an install_times.json into the spack install metadata folder.
We record a total, global time, along with the times for each phase. The type
of phase or install start / end is included (e.g., build or fail)
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
Add a new "spack audit" command. This command can check for issues
with configuration or with packages and is intended to help a
user debug a failed Spack build.
In some cases the reported issues are always errors but are too
costly to check for (e.g. packages that specify missing variants on
dependencies). In other cases the issues may be legitimate but
uncommon usage of Spack and we want to be sure the user intended the
behavior (e.g. duplicate compiler definitions).
Audits are grouped by theme, and for now the two themes are packages
and configuration. For example you can run all available audits
on packages with "spack audit packages". It is intended that in
the future users will be able to define their own audits.
The package audits are good candidates for running in package_sanity
(i.e. they could catch bugs in user-submitted packages before they
are merged) but that is left for a later PR.
This should get us most of the way there to support using monitor during a spack container build, for both Singularity and Docker. Some quick notes:
### Docker
Docker works by way of BUILDKIT and being able to specify --secret. What this means is that you can prefix a line with a mount of type secret as follows:
```bash
# Install the software, remove unnecessary deps
RUN --mount=type=secret,id=su --mount=type=secret,id=st cd /opt/spack-environment && spack env activate . && export SPACKMON_USER=$(cat /run/secrets/su) && export SPACKMON_TOKEN=$(cat /run/secrets/st) && spack install --monitor --fail-fast && spack gc -y
```
Where the id for one or more secrets corresponds to the file mounted at `/run/secrets/<name>`. So, for example, to build this container with su (spackmon user) and sv (spackmon token) defined I would export them on my host and do:
```bash
$ DOCKER_BUILDKIT=1 docker build --network="host" --secret id=st,env=SPACKMON_TOKEN --secret id=su,env=SPACKMON_USER -t spack/container .
```
And when we add `env` to the secret definition that tells the build to look for the secret with id "st" in the environment variable `SPACKMON_TOKEN` for example.
If the user is building locally with a local spack monitor, we also need to set the `--network` to be the host, otherwise you can't connect to it (a la isolation of course.)
## Singularity
Singularity doesn't have as nice an ability to clearly specify secrets, so (hoping this eventually gets implemented) what I'm doing now is providing the user instructions to write the credentials to a file, add it to the container to source, and remove when done.
## Tags
Note that the tags PR https://github.com/spack/spack/pull/23712 will need to be merged before `--monitor-tags` will actually work because I'm checking for the attribute (that doesn't exist yet):
```bash
"tags": getattr(args, "monitor_tags", None)
```
So when that PR is merged to update the argument group, it will work here, and I can either update the PR here to not check if the attribute is there (it will be) or open another one in the case this PR is already merged.
Finally, I added a bunch of documetation for how to use monitor with containerize. I say "mostly working" because I can't do a full test run with this new version until the container base is built with the updated spack (the request to the monitor server for an env install was missing so I had to add it here).
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
When running executables from build dependencies, we want to avoid that
`LD_PRELOAD` and `DYLD_INSERT_LIBRARIES` any of their shared libs build
by spack with system libraries.
this will first support uploads for spack monitor, and eventually could be
used for other kinds of spack uploads
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
* extending example for buildcaches
I was attempting to create a local build cache from a directory, and I found the
docs for both buildcaches and mirrors, but did not connect the docs that the
url variable could be the local filesystem variable. I am extending the docs for
buildcaches with an example of creating and interacting with one on the filesystem
because I suspect other users will run into this need and possibly not find what
they are looking for.
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
* adding as follows to spack mirror list
Co-authored-by: Tamara Dahlgren <35777542+tldahlgren@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: Tamara Dahlgren <35777542+tldahlgren@users.noreply.github.com>
It is currently kind of confusing to the reader to distinguish spack buildcache install
and spack install, and it is not clear how to use a build cache once a mirror is added.
Hopefully this little big of description can help (and I hope I got it right!)
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
Use the 'version_yearlike' attribute instead of 'version' to
check if the SPACK_COMPILER_EXTRA_RPATHS should be set to include
the built-in 'libfabrics'.
When using the bare 'version', the comparison is wrong when
building with 'intel-parallel-studio', which has the version
format '<edition>.YYYY.Nupdate', due to the leading '<edition>'.
Extracting specs for the result of a solve has been factored
as a method into the asp.Result class. The method account for
virtual specs being passed as initial requests.
Minimizing compiler mismatches in the DAG and preferring newer
versions of packages are now higher priority than trying to use as
many default values as possible in multi-valued variants.
Since the module roots were removed from the config file,
`--print-shell-vars` cannot find the module roots anymore. Fix it by
using the new `root_path` function. Moreover, the roots for lmod and
modules seems to have been flipped by accident.
The VALID_VERSION regex didn't check that the version string was
completely valid, only that a prefix of it was. This version ensures
the entire string represents a valid version.
This makes a few related changes.
1. Make the SEGMENT_REGEX identify *which* arm it matches by what groups
are populated, including whether it's a string or int component or a
separator all at once.
2. Use the updated regex to parse the input once with a findall rather
than twice, once with findall and once with split, since the version
components and separators can be distinguished by their group status.
3. Rather than "convert to int, on exception stay string," if the int
group is set then convert to int, if not then construct an instance
of the VersionStrComponent class
4. VersionStrComponent now implements all of the special string
comparison logic as part of its __lt__ and __eq__ methods to deal
with infinity versions and also overloads comparison with integers.
5. Version now uses direct tuple comparison since it has no per-element
special logic outside the VersionStrComponent class.
Co-authored-by: Massimiliano Culpo <massimiliano.culpo@gmail.com>
Passing absolute paths from pipeline generate job to downstream rebuild jobs
causes problems when the CI_PROJECT_DIR is not the same for the generate and
rebuild jobs. This has happened, for example, when gitlab checks out the
project into a runner-specific directory and different runners are chosen
for the generate and rebuild jobs.
* ensure that the stage root exists for `spack stage -p <PATH>`
* add test to verify `spack stage -p <PATH>` works!
* move out shared tmp staging path setup to a fixture to fix the test
* Simplified the spack.util.gpg implementation
All the classes defined in this Python module,
which were previously used to construct singleton
instances, have been removed in favor of four
global variables. These variables are initialized
lazily, like before.
The API of the module has been unchanged for the
most part. A few tests have been modified to use
the new global names.
For me the buildcache force overwrite option does not work. It tries to
delete a file, but errors with a key error, apparently because the
leading / has to be removed.
* util.tty.log: read up to 100 lines if ready
Rework to read up to 100 lines from the captured stdin as long as data
is ready to be read immediately. Adds a helper function to poll with
`select` for ready data. This showed a roughly 5-10x perf improvement
for high-rate writes through the logger with relatively short lines.
* util.tty.log: Defer flushes to end of ready reads
Rather than flush per line, flush per set of reads. Since this is a
non-blocking loop, the total perceived wait is short.
* util.tty.log: only scan each line once, usually
Rather than always find all control characters then substitute them all,
use `subn` to count the number of control characters replaced. Only if
control characters exist find out what they are. This could be made
truly single pass with sub with a function, but it's a more intrusive
change and this got 99%ish of the performance improvement (roughly
another 2x in some cases).
* util.tty.log: remove check for `readable`
Python < 3 does not support a readable check on streams, should not be
necessary here since we control the only use and it's explicitly a
stream to be read.
This PR allows users to `--export`, `--export-secret`, or both to export GPG keys
from Spack. The docs are updated that include a warning that this usually does not
need to be done.
This addresses an issue brought up in slack, and also represented in #14721.
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
Currently, module configurations are inconsistent because modulefiles are generated with the configs for the active environment, but are shared among all environments (and spack outside any environment).
This PR fixes that by allowing Spack environments (or other spack config scopes) to define additional sets of modules to generate. Each set of modules can enable either lmod or tcl modules, and contains all of the previously available module configuration. The user defines the name of each module set -- the set configured in Spack by default is named "default", and is the one returned by module manipulation commands in the absence of user intervention.
As part of this change, the module roots configuration moved from the config section to inside each module configuration.
Additionally, it adds a feature that the modulefiles for an environment can be configured to be relative to an environment view rather than the underlying prefix. This will not be enabled by default, as it should only be enabled within an environment and for non-default views constructed with separate projections per-spec.
### Overview
The goal of this PR is to make gitlab pipeline builds (especially build failures) more reproducible outside of the pipeline environment. The two key changes here which aim to improve reproducibility are:
1. Produce a `spack.lock` during pipeline generation which is passed to child jobs via artifacts. This concretized environment is used both by generated child jobs as well as uploaded as an artifact to be used when reproducing the build locally.
2. In the `spack ci rebuild` command, if a spec needs to be rebuilt from source, do this by generating and running an `install.sh` shell script which is then also uploaded as a job artifact to be run during local reproduction.
To make it easier to take advantage of improved build reproducibility, this PR also adds a new subcommand, `spack ci reproduce-build`, which, given a url to job artifacts:
- fetches and unzips the job artifacts to a local directory
- looks for the generated pipeline yaml and parses it to find details about the job to reproduce
- attempts to provide a copy of the same version of spack used in the ci build
- if the ci build used a docker image, the command prints a `docker run` command you can run to get an interactive shell for reproducing the build
#### Some highlights
One consequence of this change will be much smaller pipeline yaml files. By encoding the concrete environment in a `spack.lock` and passing to child jobs via artifacts, we will no longer need to encode the concrete root of each spec and write it into the job variables, greatly reducing the size of the generated pipeline yaml.
Additionally `spack ci rebuild` output (stdout/stderr) is no longer internally redirected to a log file, so job output will appear directly in the gitlab job trace. With debug logging turned on, this often results in log files getting truncated because they exceed the maximum amount of log output gitlab allows. If this is a problem, you still have the option to `tee` command output to a file in the within the artifacts directory, as now each generated job exposes a `user_data` directory as an artifact, which you can fill with whatever you want in your custom job scripts.
There are some changes to be aware of in how pipelines should be set up after this PR:
#### Pipeline generation
Because the pipeline generation job now writes a `spack.lock` artifact to be consumed by generated downstream jobs, `spack ci generate` takes a new option `--artifacts-root`, inside which it creates a `concrete_env` directory to place the lockfile. This artifacts root directory is also where the `user_data` directory will live, in case you want to generate any custom artifacts. If you do not provide `--artifacts-root`, the default is for it to create a `jobs_scratch_dir` within your `CI_PROJECT_DIR` (a gitlab predefined environment variable) or whatever is your current working directory if that variable isn't set. Here's the diff of the PR testing `.gitlab-ci.yml` taking advantage of the new option:
```
$ git diff develop..pipelines-reproducible-builds share/spack/gitlab/cloud_pipelines/.gitlab-ci.yml
diff --git a/share/spack/gitlab/cloud_pipelines/.gitlab-ci.yml b/share/spack/gitlab/cloud_pipelines/.gitlab-ci.yml
index 579d7b56f3..0247803a30 100644
--- a/share/spack/gitlab/cloud_pipelines/.gitlab-ci.yml
+++ b/share/spack/gitlab/cloud_pipelines/.gitlab-ci.yml
@@ -28,10 +28,11 @@ default:
- cd share/spack/gitlab/cloud_pipelines/stacks/${SPACK_CI_STACK_NAME}
- spack env activate --without-view .
- spack ci generate --check-index-only
+ --artifacts-root "${CI_PROJECT_DIR}/jobs_scratch_dir"
--output-file "${CI_PROJECT_DIR}/jobs_scratch_dir/cloud-ci-pipeline.yml"
artifacts:
paths:
- - "${CI_PROJECT_DIR}/jobs_scratch_dir/cloud-ci-pipeline.yml"
+ - "${CI_PROJECT_DIR}/jobs_scratch_dir"
tags: ["spack", "public", "medium", "x86_64"]
interruptible: true
```
Notice how we replaced the specific pointer to the generated pipeline file with its containing folder, the same folder we passed as `--artifacts-root`. This way anything in that directory (the generated pipeline yaml, as well as the concrete environment directory containing the `spack.lock`) will be uploaded as an artifact and available to the downstream jobs.
#### Rebuild jobs
Rebuild jobs now must activate the concrete environment created by `spack ci generate` and provided via artifacts. When the pipeline is generated, a directory called `concrete_environment` is created within the artifacts root directory, and this is where the `spack.lock` file is written to be passed to the generated rebuild jobs. The artifacts root directory can be specified using the `--artifacts-root` option to `spack ci generate`, otherwise, it is assumed to be `$CI_PROJECT_DIR`. The directory containing the concrete environment files (`spack.yaml` and `spack.lock`) is then passed to generated child jobs via the `SPACK_CONCRETE_ENV_DIR` variable in the generated pipeline yaml file.
When you don't provide custom `script` sections in your `mappings` within the `gitlab-ci` section of your `spack.yaml`, the default behavior of rebuild jobs is now to change into `SPACK_CONCRETE_ENV_DIR` and activate that environment. If you do provide custom rebuild scripts in your `spack.yaml`, be aware those scripts should do the same thing: assume `SPACK_CONCRETE_ENV_DIR` contains the concretized environment to activate. No other changes to existing custom rebuild scripts should be required as a result of this PR.
As mentioned above, one key change made in this PR is the generation of the `install.sh` script by the rebuild jobs, as that same script is both run by the CI rebuild job as well as exported as an artifact to aid in subsequent attempts to reproduce the build outside of CI. The generated `install.sh` script contains only a single `spack install` command with arguments computed by `spack ci rebuild`. If the install fails, the job trace in gitlab will contain instructions on how to reproduce the build locally:
```
To reproduce this build locally, run:
spack ci reproduce-build https://gitlab.next.spack.io/api/v4/projects/7/jobs/240607/artifacts [--working-dir <dir>]
If this project does not have public pipelines, you will need to first:
export GITLAB_PRIVATE_TOKEN=<generated_token>
... then follow the printed instructions.
```
When run locally, the `spack ci reproduce-build` command shown above will download and process the job artifacts from gitlab, then print out instructions you can copy-paste to run a local reproducer of the CI job.
This PR includes a few other changes to the way pipelines work, see the documentation on pipelines for more details.
This PR erelies on
~- [ ] #23194 to be able to refer to uninstalled specs by DAG hash~
EDIT: that is going to take longer to come to fruition, so for now, we will continue to install specs represented by a concrete `spec.yaml` file on disk.
- [x] #22657 to support install a single spec already present in the active, concrete environment
- [x] add `in_buildcache` field to DB records to indicate what parts of an index,
which includes roots and dependencies, are in the buildcache.
- [x] add `mark()` method to DB for setting values on single nodes of the DAG.
I would like to be able to export (and save and then load programatically)
spack blame metadata, so this commit adds a spack blame --json argument,
along with developer docs for it
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
This work will come in two phases. The first here is to allow saving of a local result
with spack monitor, and the second will add a spack monitor command so the user can
do spack monitor upload.
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
Co-authored-by: vsoch <vsoch@users.noreply.github.com>
Currently if one package does `depends_on('pkg default_library=shared')`
and another does `depends_on('pkg default_library=both')`, you'd get a
concretization error.
With this PR one package can do `depends_on('pkg default_library=shared')`
and another depends_on('default_library=static'), and it would concretize to
`pkg default_library=shared,static`
Co-authored-by: Massimiliano Culpo <massimiliano.culpo@gmail.com>
Bash has a builtin `fc` that will override the compiler if you use "fc",
so it's better to use the full spack-supplied compiler path.
Additionally, the filter regex in the docs was wrong: it replaced the
entire assignment operation with the RHS.
* Modification to R environment
This PR modifies how the R environmnet is presented, and fixes
installing the standalone Rmath library.
- The Rmath build and install methods are combined into one
- Set parallel=False when installing Rmath
- remove the run environment that set up variables for libraries and
headers that are not really needed, and pollute the environment.
* Add setup_run_environment back
- Add back the setup_run_environment with LD_LIBRARY_PATH and
PKG_CONFIG_PATH.
- Adjust documentation to reflect the current code.
Spack uses curl to fetch URL resources. For locally-stored resources
it uses curl's file protocol; when using this protocol, curl expects
that the URL encoding conforms to RFC 3986 (which reserves characters
like '?' and '=' for special use).
We were not performing this encoding, and found a resource where
curl was interpreting this in an unfavorable way (succeeding, but
producing an empty file). This commit properly encodes URLs when
using curl's file protocol.
This error did not likely come up before because in most contexts
Spack was either fetching via http or it was using URLs without
offending characters (for example, the sha-based URLs in mirrors
never contain these characters).
Spack doesn't require users to manually index their repos; it reindexes the indexes automatically when things change. To determine when to do this, it has to `stat()` all package files in each repository to make sure that indexes up to date with packages. We currently index virtual providers, patches by sha256, and tags on packages.
When this was originally implemented, we ran the checker all the time, at startup, but that was slow (see #7587). But we didn't go far enough -- it still consults the checker and does all the stat operations just to see if a package exists (`Repo.exists()`). That might've been a wash in 2018, but as the number of packages has grown, it's gotten slower -- checking 5k packages is expensive and users see this for small operations. It's a win now to make `Repo.exists()` check files directly.
**Fix:**
This PR does a number of things to speed up `spack load`, `spack info`, and other commands:
- [x] Make `Repo.exists()` check files directly again with `os.path.exists()` (this is the big one)
- [x] Refactor `Spec.satisfies()` so that a checking for virtual packages only happens if needed
(avoids some calls to exists())
- [x] Avoid calling `Repo.exists(spec)` in `Repo.get()`. `Repo.get()` will ultimately try to load
a `package.py` file anyway; we can let the failure to load it indicate that the package doesn't
exist, and avoid another call to exists().
- [x] Fix up some comments in spec parsing
- [x] Call `UnknownPackageError` more consistently in `repo.py`
- [x] `analyze` isn't commonly used; move it to long help
(`spack -H` vs `spack -h`). Give it its own section.
- [x] make it clear from `spack -h` that `spack module` can generate
module files
- [x] shorten help for `spack style`
Currently, module configurations are inconsistent because modulefiles are generated with the configs for the active environment, but are shared among all environments (and spack outside any environment).
This PR fixes that by allowing Spack environments (or other spack config scopes) to define additional sets of modules to generate. Each set of modules can enable either lmod or tcl modules, and contains all of the previously available module configuration. The user defines the name of each module set -- the set configured in Spack by default is named "default", and is the one returned by module manipulation commands in the absence of user intervention.
As part of this change, the module roots configuration moved from the `config` section to inside each module configuration.
Additionally, it adds a feature that the modulefiles for an environment can be configured to be relative to an environment view rather than the underlying prefix. This will not be enabled by default, as it should only be enabled within an environment and for non-default views constructed with separate projections per-spec.
TODO:
- [x] code changes to support multiple module sets
- [x] code changes to support modules relative to a view
- [x] Tests for multiple module configurations
- [x] Tests for modules relative to a view
- [x] Backwards compatibility for module roots from config section
- [x] Backwards compatibility for default module set without the name specified
- [x] Tests for backwards compatibility
The implementation for __str__ has been simplified to traverse the spec directly,
and doesn't call anymore the flat_dependencies method. Dead code has been
removed.
For configure (e.g. for hdf5) to pass, this option needs to be pulled out when invoked in ccld mode.
I thought it had fixed the issue but I still saw it after that. After some digging, my guess is that I was able
to get hdf5 to build with ifort instead of ifx. Lot of overlapping changes occurring at the time, as it were.
There are still outstanding issues building hdf5 with ifx, and Intel is looking into what appears to be a
compiler bug, but this manifests during build and is likely a separate issue.
I have verified that the making the edit in 'ccld' mode removes the -loopopt=0 and enables hdf5 to pass
configure. It should be fine to make the edit in 'ld' mode as well, but I have not tested that and didn't
include an -or- condition for it.
Currently, environment views blink out of existence during the view regeneration, and are slowly built back up to their new and improved state. This is not good if other processes attempt to access the view -- they can see it in an inconsistent state.
This PR fixes makes environment view updates atomic. This requires a level of indirection (via symlink, similar to nix or guix) from the view root to the underlying implementation on the filesystem.
Now, an environment view at `/path/to/foo` is a symlink to `/path/to/._foo/<hash>`, where `<hash>` is a hash of the contents of the view. We construct the view in its content-keyed hash directory, create a new symlink to this directory, and atomically replace the symlink with one to the new view.
This PR has a couple of other benefits:
* It future-proofs environment views so that we can implement rollback.
* It ensures that we don't leave users in an inconsistent state if building a new view fails for some reason.
For background:
* there is no atomic operation in posix that allows for a non-empty directory to be replaced.
* There is an atomic `renameat2` in the linux kernel starting in version 3.15, but many filesystems don't support the system call, including NFS3 and NFS4, which makes it a poor implementation choice for an HPC tool, so we use the symlink approach that others tools like nix and guix have used successfully.
fixes#22351
The ASP-based solver now accounts for the presence
in the DAG of deprecated versions and tries to minimize
their number at highest priority.
Variants explicitly set in an abstract root spec are considered
as defaults for the package they refer to, and they override
what is in packages.yaml and in package.py. This is relevant
only for multi-valued variants, where a constraint may extend
an already default value.
The code for guessing cpu archtype based on craype modules names got confused,
at least on LLNL RZ prototype systems. In particular a (L) or (D) at the end of a craype-x86-xxx or other
cpu architecture module was geting the logic confused.
With this patch, any white space + remaining characters in the moduel name are removed.
Signed-off-by: Howard Pritchard <howardp@lanl.gov>
There have been a lot of questions and some confusion recently surrounding Spack installation test capabilities so this PR is intended to clean up and refine the documentation for "Checking an installation".
It aims to better distinguish between checks that are performed during an installation (i.e., build-time tests) and those that can be done days and weeks after the software has been installed (i.e., install (or smoke) tests).
When we first merged the ASP-based solver, unit-tests
were run in a Docker container with root permissions
and that was preventing a few tests to succeed.
Since some time though, clingo is tested as a regular
user within Github Actions VMs, so we should start to
run checks again.
In an active concretize environment, support installing one or more
cli specs only if they are already present in the environment. The
`--no-add` option is the default for root specs, but optional for
dependency specs. I.e. if you `spack install <depspec>` in an
environment, the dependency-only spec `depspec` will be added as a
root of the environment before being installed. In addition,
`spack install --no-add <spec>` fails if it does not find an
unambiguous match for `spec`.
Like compilers targets now try to minimize
mismatches, instead of maximizing matches.
Deduction of mismatches is reworked to be
the opposite of a match, since computing
that is faster.
The ASP-based solver can natively manage cases where more than one root spec is given, and is able to concretize all the roots together (ensuring one spec per package at most).
Modifications:
- [x] When concretising together an environment the ASP-based solver calls directly its `solve` method rather than constructing a temporary fake root package.
The loading protocol mandates that the the module we are going
to import needs to be already in sys.modules before its code is
executed, so to prevent unbounded recursions and multiple loading.
Loading a module from file exits early if the module is already
in sys.modules
When installing OneAPI packages as root (e.g. in a container), the
installer places cache files in /var/intel/installercache that
interfere with future Spack installs. This ensures that when
running an installation as a root user that this is removed.
The function we coded in Spack to load Python modules with arbitrary
names from a file seem to have issues with local imports. For
loading hooks though it is unnecessary to use such functions, since
we don't care to bind a custom name to a module nor we have to load
it from an unknown location.
This PR thus modifies spack.hook in the following ways:
- Use __import__ instead of spack.util.imp.load_source (this
addresses #20005)
- Sync module docstring with all the hooks we have
- Avoid using memoization in a module function
- Marked with a leading underscore all the names that are supposed
to stay local
This is as much a question as it is a minor fine-tuning of the docs. I've been known to add things to an environment by editing the `spack.yaml` file directly. When I read the previous version of this sentence, I was afraid that `spack add` was actually doing *two* things, modifying the `spack.yaml` and updating something else that defined the roots of the Environment. A bit of experimentation suggests that editing the `spack.yaml` file is sufficient to change the roots.
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
fixes#22786
Trying to get optimization flags for a specific target from
a compiler may trigger warnings. In the context of constructing
facts for the ASP-based solver we don't want to show these
warnings to the user, so here we simply ignore them.
This isn't a significant issue, but I noticed that the docstring incorrectly references "tty.fail" and I wanted to quickly fix it to reflect the correct command, tty.die. I also wanted to fix the docstrings to not be large clumps, to what @tgamblin suggested after I wrote this - having one line at the top that is a quick summary, and more verbose after that.
This provides initial support for [spack monitor](https://github.com/spack/spack-monitor), a web application that stores information and analysis about Spack installations. Spack can now contact a monitor server and upload analysis -- even after a build is already done.
Specifically, this adds:
- [x] monitor options for `spack install`
- [x] `spack analyze` command
- [x] hook architecture for analyzers
- [x] separate build logs (in addition to the existing combined log)
- [x] docs for spack analyze
- [x] reworked developer docs, with hook docs
- [x] analyzers for:
- [x] config args
- [x] environment variables
- [x] installed files
- [x] libabigail
There is a lot more information in the docs contained in this PR, so consult those for full details on this feature.
Additional tests will be added in a future PR.
In debug mode, processes taking an exclusive lock write out their node name to
the lock file. We were using `getfqdn()` for this, but it seems to produce
inconsistent results when used from within some github actions containers.
We get this error because getfqdn() seems to return a short name in one place
and a fully qualified name in another:
```
File "/home/runner/work/spack/spack/lib/spack/spack/test/llnl/util/lock.py", line 1211, in p1
assert lock.host == self.host
AssertionError: assert 'fv-az290-764....cloudapp.net' == 'fv-az290-764'
- fv-az290-764.internal.cloudapp.net
+ fv-az290-764
!!!!!!!!!!!!!!!!!!!! Interrupted: stopping after 1 failures !!!!!!!!!!!!!!!!!!!!
== 1 failed, 2547 passed, 7 skipped, 22 xfailed, 2 xpassed in 1238.67 seconds ==
```
This seems to stem from https://bugs.python.org/issue5004.
We don't really need to get a fully qualified hostname for debugging, so use
`gethostname()` because its results are more consistent. This seems to fix the
issue.
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
* Clarify stub compiler definition in compilers.yaml
* Update explanation of why stub compiler definition is needed
* Add note about required module definition when using Spack-installed
intel-parallel-studio as intel-compiler
* Add suggestion about updating package config preferences based on
choice of variants when installing intel-parallel-studio to avoid
reinstallation
We remove system paths from search variables like PATH and
from -L options because they may contain many packages and
could interfere with Spack-built packages. External packages
may be installed to prefixes that are not actually system paths
but are still "merged" in the sense that many other packages are
installed there. To avoid conflicts, this PR places all external
packages at the end of search paths.
We set LC_ALL=C to encourage a build process to generate ASCII
output (so our logger daemon can decode it). Most packages
respect this but it appears that intel-oneapi-compilers does
not in some cases (see #22813). This reads the output of the build
process as UTF-8, which still works if the build process respects
LC_ALL=C but also works if the process generates UTF-8 output.
For Python >= 3.7 all files are opened with UTF-8 encoding by
default. Python 2 does not support the encoding argument on
'open', so to support Python 2 the files would have to be
opened in byte mode and explicitly decoded (as a side note,
this would be the only way to handle other encodings without
being informed of them in advance).
* bugfix: fix representation of null in spack_yaml output
Nulls were previously printed differently by `spack config blame config`
and `spack config get config`. Fix this in the `spack_yaml` dumpers.
* bugfix: `spack config blame` should print all lines of config
`spack config blame` was not printing all lines of configuration because
there were no annotations for empty lines in the YAML dump output. Fix
this by removing empty lines.
- Use debugoptimized as default build type, just like RelWithDebInfo for cmake
- Do not strip by default, and add a default_library variant which conveniently support both shared and static
By default, clingo doesn't show any optimization criteria (maximized or
minimized sums) if the set they aggregate is empty. Per the clingo
mailing list, we can get around that by adding, e.g.:
```
#minimize{ 0@2 : #true }.
```
for the 2nd criterion. This forces clingo to print out the criterion but
does not affect the optimization.
This PR adds directives as above for all of our optimization criteria, as
well as facts with descriptions of each criterion,like this:
```
opt_criterion(2, "number of non-default variants")
```
We use facts in `concretize.lp` rather than hard-coding these in `asp.py`
so that the names can be maintained in the same place as the other
optimization criteria.
The now-displayed weights and the names are used to display optimization
output like this:
```console
(spackle):solver> spack solve --show opt zlib
==> Best of 0 answers.
==> Optimization Criteria:
Priority Criterion Value
1 version weight 0
2 number of non-default variants (roots) 0
3 multi-valued variants + preferred providers for roots 0
4 number of non-default variants (non-roots) 0
5 number of non-default providers (non-roots) 0
6 count of non-root multi-valued variants 0
7 compiler matches + number of nodes 1
8 version badness 0
9 non-preferred compilers 0
10 target matches 0
11 non-preferred targets 0
zlib@1.2.11%apple-clang@12.0.0+optimize+pic+shared arch=darwin-catalina-skylake
```
Note that this is all hidden behind a `--show opt` option to `spack
solve`. Optimization weights are no longer shown by default, but you can
at least inspect them and more easily understand what is going on.
- [x] always show optimization criteria in `clingo` output
- [x] add `opt_criterion()` facts for all optimizationc criteria
- [x] make display of opt criteria optional in `spack solve`
- [x] rework how optimization criteria are displayed, and add a `--show opt`
optiong to `spack solve`
CachedCMakePackage is a CMakePackage subclass for using CMake initial
cache. This feature of CMake allows packages to increase reproducibility,
especially between spack builds and manual builds. It also allows
packages to sidestep certain parsing bugs in extremely long cmake
commands, and to avoid system limits on the length of the command line.
Co-authored by: Chris White <white238@llnl.gov>
In the face of two consecutive spaces in the command line, the compiler wrapper would skip all remaining arguments, causing problems building py-scipy with Intel compiler. This PR solves the problem.
* Fixed compiler wrapper in the face of extra spaces between arguments
Co-authored-by: Elizabeth Fischer <elizabeth.fischer@alaska.edu>
Original commit message:
This feature of CMake allows packages to increase reproducibility, especially between
Spack- and manual builds. It also allows packages to sidestep certain parsing bugs in
extremely long ``cmake`` commands, and to avoid system limits on the length of the
command line.
Adding:
Co-authored by: Chris White <white238@llnl.gov>
This reverts commit c4f0a3cf6c.
CachedCMakePackage is a specialized class for packages built using CMake initial cache.
This feature of CMake allows packages to increase reproducibility, especially between
Spack- and manual builds. It also allows packages to sidestep certain parsing bugs in
extremely long ``cmake`` commands, and to avoid system limits on the length of the
command line.
Autoconf before 2.70 will erroneously pass ifx's -loopopt argument to the
linker, requiring all packages to use autoconf 2.70 or newer to use ifx.
This is a hotfix enabling ifx to be used in Spack. Instead of bothering
to upgrade autoconf for every package, we'll just strip out the
problematic flag if we're in `ld` mode.
- [x] Add a conditional to the `cc` wrapper to skip `-loopopt` in `ld`
mode. This can probably be generalized in the future to strip more
things (e.g., via an environment variable we can constrol from
Spack) but it's good enough for now.
- [x] Add a test ensuring that `-loopopt` arguments are stripped in link
mode, but not in compile mode.
Since `lazy_lexicographic_ordering` handles `None` comparison for us, we
don't need to adjust the spec comparators to return empty strings or
other type-specific empty types. We can just leverage the None-awareness
of `lazy_lexicographic_ordering`.
- [x] remove "or ''" from `_cmp_iter` in `Spec`
- [x] remove setting of `self.namespace` to `''` in `MockPackage`
We have been using the `@llnl.util.lang.key_ordering` decorator for specs
and most of their components. This leverages the fact that in Python,
tuple comparison is lexicographic. It allows you to implement a
`_cmp_key` method on your class, and have `__eq__`, `__lt__`, etc.
implemented automatically using that key. For example, you might use
tuple keys to implement comparison, e.g.:
```python
class Widget:
# author implements this
def _cmp_key(self):
return (
self.a,
self.b,
(self.c, self.d),
self.e
)
# operators are generated by @key_ordering
def __eq__(self, other):
return self._cmp_key() == other._cmp_key()
def __lt__(self):
return self._cmp_key() < other._cmp_key()
# etc.
```
The issue there for simple comparators is that we have to bulid the
tuples *and* we have to generate all the values in them up front. When
implementing comparisons for large data structures, this can be costly.
This PR replaces `@key_ordering` with a new decorator,
`@lazy_lexicographic_ordering`. Lazy lexicographic comparison maps the
tuple comparison shown above to generator functions. Instead of comparing
based on pre-constructed tuple keys, users of this decorator can compare
using elements from a generator. So, you'd write:
```python
@lazy_lexicographic_ordering
class Widget:
def _cmp_iter(self):
yield a
yield b
def cd_fun():
yield c
yield d
yield cd_fun
yield e
# operators are added by decorator (but are a bit more complex)
There are no tuples that have to be pre-constructed, and the generator
does not have to complete. Instead of tuples, we simply make functions
that lazily yield what would've been in the tuple. If a yielded value is
a `callable`, the comparison functions will call it and recursively
compar it. The comparator just walks the data structure like you'd expect
it to.
The ``@lazy_lexicographic_ordering`` decorator handles the details of
implementing comparison operators, and the ``Widget`` implementor only
has to worry about writing ``_cmp_iter``, and making sure the elements in
it are also comparable.
Using this PR shaves another 1.5 sec off the runtime of `spack buildcache
list`, and it also speeds up Spec comparison by about 30%. The runtime
improvement comes mostly from *not* calling `hash()` `_cmp_iter()`.
* Make -j flag less exceptional
The -j flag in spack behaves differently from make, ctest, ninja, etc,
because it caps the number of jobs to an arbitrary number 16.
Spack will behave like other tools if `spack install` uses a reasonable
default, and `spack install -j <num>` *overrides* that default.
This will be particularly useful for Spack usage outside of a traditional
HPC context and for HPC centers that encourage users to compile on
login nodes with many cores instead of on compute nodes, which has
become increasingly common as individual nodes have more cores.
This maintains the existing default value of min(num_cpus, 16). However,
as it is right now, Spack does a poor job at determining the number of
cpus on linux, since it doesn't take cgroups into account. This is
particularly problematic when using distributed builds with slurm. This PR
also introduces `spack.util.cpus.cpus_available()` to consolidate
knowledge on determining the number of available cores, and improves
core detection for linux. This should also improve core detection for Docker/
Kubernetes, which also use cgroups.
This commit extends the API of the __call__ method of the
SpackCommand class to permit passing global arguments
like those interposed between the main "spack" command
and the subsequent subcommand.
The functionality is used to fix an issue where running
```spack -e . location -b some_package```
ends up printing the name of the environment instead of
the build directory of the package, because the location arg
parser also stores this value as `arg.env`.
fixes#22294
A combination of the swapping order for global variables and
the fact that most of them are lazily evaluated resulted in
custom install tree not being taken into account if clingo
had to be bootstrapped.
This commit fixes that particular issue, but a broader refactor
may be needed to ensure that similar situations won't affect us
in the future.
Remote buildcache indices need to be stored in a place that does not
require writing to the Spack prefix. Move them from the install_tree to
the misc_cache.
fixes#22565
This change enforces the uniqueness of the version_weight
atom per node(Package) in the DAG. It does so by applying
FTSE and adding an extra layer of indirection with the
possible_version_weight/2 atom.
Before this change it may have happened that for the same
node two different version_weight/2 were in the answer set,
each of which referred to a different spec with the same
version, and their weights would sum up.
This lead to unexpected result like preferring to build a
new version of an external if the external version was
older.
* Make stage use concrete specs from environment
Same as in https://github.com/spack/spack/pull/21642, the idea is that
we want to easily stage a package that fails to build in a complex
environment. Instead of making the user create a spec by hand (basically
transforming all the rules in the environment manifest into a spec,
defying the purpose of the environment...), use the provided spec as a
filter for the already concretized specs. This also speeds up things,
cause we don't have to reconcretize.
* clingo: modify recipe for bootstrapping
Modifications:
- clingo builds with shared Python only if ^python+shared
- avoid building the clingo app for bootstrapping
- don't link to libpython when bootstrapping
* Remove option that breaks on linux
* Give more hints for the current Python
* Disable CLINGO_BUILD_PY_SHARED for bootstrapping
* bootstrapping: try to detect the current python from std library
This is much faster than calling external executables
* Fix compatibility with Python 2.6
* Give hints on which compiler and OS to use when bootstrapping
This change hints which compiler to use for bootstrapping clingo
(either GCC or Apple Clang on MacOS). On Cray platforms it also
hints to build for the frontend system, where software is meant
to be installed.
* Use spec_for_current_python to constrain module requirement
* ASP-based solver: avoid adding values to variants when they're set
fixes#22533fixes#21911
Added a rule that prevents any value to slip in a variant when the
variant is set explicitly. This is relevant for multi-valued variants,
in particular for those that have disjoint sets of values.
* Ensure disjoint sets have a clear semantics for external packages
fixes#22547
SingleFileScope was not able to repopulate its cache before this
change. This was affecting the configuration seen by environments
using clingo bootstrapped from sources, since the bootstrapping
operation involved a few cache invalidation for config files.
This change accounts for platform specific configuration scopes,
like ~/.spack/linux, during bootstrapping. These scopes were
previously not accounted for and that was causing issues e.g.
when searching for compilers.
* Replace URL computation in base IntelOneApiPackage class with
defining URLs in component packages (this is expected to be
simpler for now)
* Add component_dir property that all oneAPI component packages must
define. This property names a directory that should exist after
installation completes (useful for making sure the install was
successful) and also defines the search location for the
component's environment update script.
* Add needed dependencies for components (e.g. intel-oneapi-dnn
requires intel-oneapi-tbb). The compilers provided by
intel-oneapi-compilers need some components under certain
circumstances (e.g. when enabling SYCL support) but these were
omitted since the libraries should only be linked when a
dependent package requests that feature
* Remove individual setup_run_environment implementations and use
IntelOneApiPackage superclass method which sources vars.sh
(located in a subdirectory of component_dir)
* Add documentation for IntelOneApiPackge build system
Co-authored-by: Vasily Danilin <vasily.danilin@yandex.ru>
* unit tests: mark slow tests as "maybeslow"
This commit also removes the "network" marker and
marks every "network" test as "maybeslow". Tests
marked as db are maintained, but they're not slow
anymore.
* GA: require style tests to pass before running unit-tests
* GA: make MacOS unit tests fail fast
* GA: move all unit tests into the same workflow, run style tests as a prerequisite
All the unit tests have been moved into the same workflow so that a single
run of the dorny/paths-filter action can be used to ask for coverage based
on the files that have been changed in a PR. The basic idea is that for PRs
that introduce only changes to packages coverage is not necessary, this
resulting in a faster execution of the tests.
Also, for package only PRs slow unit tests are skipped.
Finally, MacOS and linux unit tests are now conditional on style tests passing
meaning that e.g. we won't waste a MacOS worker if we know that the PR has
flake8 issues.
* Addressed review comments
* Skipping slow tests on MacOS for package only recipes
* QA: make tests on changes correct before merging
In most cases, we want condition_holds(ID) to imply any imposed
constraints associated with the ID. However, the dependency relationship
in Spack is special because it's "extra" conditional -- a dependency
*condition* may hold, but we have decided that externals will not have
dependencies, so we need a way to avoid having imposed constraints appear
for nodes that don't exist.
This introduces a new rule that says that constraints are imposed
*unless* we define `do_not_impose(ID)`. This allows rules like
dependencies, which rely on more than just spec conditions, to cancel
imposed constraints.
We add one special case for this: dependencies of externals.
We only consider test dependencies some of the time. Some packages are
*only* test dependencies. Spack's algorithm was previously generating
dependency conditions that could hold, *even* if there was no potential
dependency type.
- [x] change asp.py so that this can't happen -- we now only generate
dependency types for possible dependencies.
This builds on #20638 by unifying all the places in the concretizer where
things are conditional on specs. Previously, we duplicated a common spec
conditional pattern for dependencies, virtual providers, conflicts, and
externals. That was introduced in #20423 and refined in #20507, and
roughly looked as follows.
Given some directives in a package like:
```python
depends_on("foo@1.0+bar", when="@2.0+variant")
provides("mpi@2:", when="@1.9:")
```
We handled the `@2.0+variant` and `@1.9:` parts by generating generated
`dependency_condition()`, `required_dependency_condition()`, and
`imposed_dependency_condition()` facts to trigger rules like this:
```prolog
dependency_conditions_hold(ID, Parent, Dependency) :-
attr(Name, Arg1) : required_dependency_condition(ID, Name, Arg1);
attr(Name, Arg1, Arg2) : required_dependency_condition(ID, Name, Arg1, Arg2);
attr(Name, Arg1, Arg2, Arg3) : required_dependency_condition(ID, Name, Arg1, Arg2, Arg3);
dependency_condition(ID, Parent, Dependency);
node(Parent).
```
And we handled `foo@1.0+bar` and `mpi@2:` parts ("imposed constraints")
like this:
```prolog
attr(Name, Arg1, Arg2) :-
dependency_conditions_hold(ID, Package, Dependency),
imposed_dependency_condition(ID, Name, Arg1, Arg2).
attr(Name, Arg1, Arg2, Arg3) :-
dependency_conditions_hold(ID, Package, Dependency),
imposed_dependency_condition(ID, Name, Arg1, Arg2, Arg3).
```
These rules were repeated with different input predicates for
requirements (e.g., `required_dependency_condition`) and imposed
constraints (e.g., `imposed_dependency_condition`) throughout
`concretize.lp`. In #20638 it got to be a bit confusing, because we used
the same `dependency_condition_holds` predicate to impose constraints on
conditional dependencies and virtual providers. So, even though the
pattern was repeated, some of the conditional rules were conjoined in a
weird way.
Instead of repeating this pattern everywhere, we now have *one* set of
consolidated rules for conditions:
```prolog
condition_holds(ID) :-
condition(ID);
attr(Name, A1) : condition_requirement(ID, Name, A1);
attr(Name, A1, A2) : condition_requirement(ID, Name, A1, A2);
attr(Name, A1, A2, A3) : condition_requirement(ID, Name, A1, A2, A3).
attr(Name, A1) :- condition_holds(ID), imposed_constraint(ID, Name, A1).
attr(Name, A1, A2) :- condition_holds(ID), imposed_constraint(ID, Name, A1, A2).
attr(Name, A1, A2, A3) :- condition_holds(ID), imposed_constraint(ID, Name, A1, A2, A3).
```
this allows us to use `condition(ID)` and `condition_holds(ID)` to
encapsulate the conditional logic on specs in all the scenarios where we
need it. Instead of defining predicates for the requirements and imposed
constraints, we generate the condition inputs with generic facts, and
define predicates to associate the condition ID with a particular
scenario. So, now, the generated facts for a condition look like this:
```prolog
condition(121).
condition_requirement(121,"node","cairo").
condition_requirement(121,"variant_value","cairo","fc","True").
imposed_constraint(121,"version_satisfies","fontconfig","2.10.91:").
dependency_condition(121,"cairo","fontconfig").
dependency_type(121,"build").
dependency_type(121,"link").
```
The requirements and imposed constraints are generic, and we associate
them with their meaning via the id. Here, `dependency_condition(121,
"cairo", "fontconfig")` tells us that condition 121 has to do with the
dependency of `cairo` on `fontconfig`, and the conditional dependency
rules just become:
```prolog
dependency_holds(Package, Dependency, Type) :-
dependency_condition(ID, Package, Dependency),
dependency_type(ID, Type),
condition_holds(ID).
```
Dependencies, virtuals, conflicts, and externals all now use similar
patterns, and the logic for generating condition facts is common to all
of them on the python side, as well. The more specific routines like
`package_dependencies_rules` just call `self.condition(...)` to get an id
and generate requirements and imposed constraints, then they generate
their extra facts with the returned id, like this:
```python
def package_dependencies_rules(self, pkg, tests):
"""Translate 'depends_on' directives into ASP logic."""
for _, conditions in sorted(pkg.dependencies.items()):
for cond, dep in sorted(conditions.items()):
condition_id = self.condition(cond, dep.spec, pkg.name) # create a condition and get its id
self.gen.fact(fn.dependency_condition( # associate specifics about the dependency w/the id
condition_id, pkg.name, dep.spec.name
))
# etc.
```
- [x] unify generation and logic for conditions
- [x] use unified logic for dependencies
- [x] use unified logic for virtuals
- [x] use unified logic for conflicts
- [x] use unified logic for externals
LocalWords: concretizer mpi attr Arg concretize lp cairo fc fontconfig
LocalWords: virtuals def pkg cond dep fn refactor github py
* Rewrite relative dev_spec paths internally to absolute paths in case of relocation of the environment file
* Test relative paths for dev_path in environments
* Add a --keep-relative flag to spack env create
This ensures that relative paths of develop paths are not expanded to
absolute paths when initializing the environment in a different location
from the spack.yaml init file.
Currently, regardless of a spec being concrete or not, we validate its variants in `spec_clauses` (part of `SpackSolverSetup`).
This PR skips the check if the spec is concrete.
The reason we want to do this is so that the solver setup class (really, `spec_clauses`) can be used for cases when we just want the logic statements / facts (is that what they are called?) and we don't need to re-validate an already concrete spec. We can't change existing concrete specs, and we have to be able to handle them *even if they violate constraints in the current spack*. This happens in practice if we are doing the validation for a spec produced by a different spack install.
Signed-off-by: vsoch <vsoch@users.noreply.github.com>
This pull request will add the ability for a user to add a configuration argument on the fly, on the command line, e.g.,:
```bash
$ spack -c config:install_tree:root:/path/to/config.yaml -c packages:all:compiler:[gcc] list --help
```
The above command doesn't do anything (I'm just getting help for list) but you can imagine having another root of packages, and updating it on the fly for a command (something I'd like to do in the near future!)
I've moved the logic for config_add that used to be in spack/cmd/config.py into spack/config.py proper, and now both the main.py (where spack commands live) and spack/cmd/config.py use these functions. I only needed spack config add, so I didn't move the others. We can move the others if there are also needed in multiple places.
Was getting the following error:
```
$ spack test list
==> Error: issubclass() arg 1 must be a class
```
This PR adds a check in `has_test_method` (in case it is re-used elsewhere such as #22097) and ensures a class is passed to the method from `spack test list`.
This is a workaround for an issue with how "spack install" is invoked from within "spack ci rebuild". The fact that we don't get an exception or even the actual returncode when using the object returned by spack.util.executable.which('spack') to install the target spec means we get no indication of failures about the install command itself. Instead we rely on the subsequent buildcache creation failure to fail the job.
Unlike the other commands of the `R CMD` interface, the `INSTALL` command
will read `Renviron` files. This can potentially break builds of r-
packages, depending on what is set in the `Renviron` file. This PR adds
the `--vanilla` flag to ensure that neither `Rprofile` nor `Renviron` files
are read during Spack builds of r- packages.
This adds a `--path` option to `spack python` that shows the `python`
interpreter that Spack is using.
e.g.:
```console
$ spack python --path
/Users/gamblin2/src/spack/var/spack/environments/default/.spack-env/view/bin/python
```
This is useful for debugging, and we can ask users to run it to
understand what python Spack is picking up via preferences in `bin/spack`
and via the `SPACK_PYTHON` environment variable introduced in #21222.
`spack test list` will show you which *installed* packages can be tested
but it won't show you which packages have tests.
- [x] add `spack test list --all` to show which packages have test methods
- [x] update `has_test_method()` to handle package instances *and*
package classes.
* Improve R package creation
This PR adds the `list_url` attribute to CRAN R packages when using
`spack create`. It also adds the `git` attribute to R Bioconductor
packages upon creation.
* Switch over to using cran/bioc attributes
The cran/bioc entries are set to have the '=' line up with homepage
entry, but homepage does not need to exist in the package file. If it
does not, that could affect the alignment.
* Do not have to split bioc
* Edit R package documentation
Explain Bioconductor packages and add `cran` and `bioc` attributes.
* Update lib/spack/docs/build_systems/rpackage.rst
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Update lib/spack/docs/build_systems/rpackage.rst
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* Simplify the cran attribute
The version can be faked so that the cran attribute is simply equal to
the CRAN package name.
* Edit the docs to reflect new `cran` attribute format
* Use the first element of self.versions() for url
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
This allows users to use relative paths for mirrors and repos and other things that may be part of a Spack environment. There are two ways to do it.
1. Relative to the file
```yaml
spack:
repos:
- local_dir/my_repository
```
Which will refer to a repository like this in the directory where `spack.yaml` lives:
```
env/
spack.yaml <-- the config file above
local_dir/
my_repository/ <-- this repository
repo.yaml
packages/
```
2. Relative to the environment
```yaml
spack:
repos:
- $env/local_dir/my_repository
```
Both of these would refer to the same directory, but they differ for included files. For example, if you had this layout:
```
env/
spack.yaml
repository/
includes/
repos.yaml
repository/
```
And this `spack.yaml`:
```yaml
spack:
include: includes/repos.yaml
```
Then, these two `repos.yaml` files are functionally different:
```yaml
repos:
- $env/repository # refers to env/repository/ above
repos:
- repository # refers to env/includes/repository/ above
```
The $env variable will not be evaluated if there is no active environment. This generally means that it should not be used outside of an environment's spack.yaml file. However, if other aspects of your workflow guarantee that there is always an active environment, it may be used in other config scopes.
* Allow the bootstrapping of clingo from sources
Allow python builds with system python as external
for MacOS
* Ensure consistent configuration when bootstrapping clingo
This commit uses context managers to ensure we can
bootstrap clingo using a consistent configuration
regardless of the use case being managed.
* Github actions: test clingo with bootstrapping from sources
* Add command to inspect and clean the bootstrap store
Prevent users to set the install tree root to the bootstrap store
* clingo: documented how to bootstrap from sources
Co-authored-by: Gregory Becker <becker33@llnl.gov>
If a user creates a wrapper for the ifx binary called ifx_orig,
this causes the ifx --version command to produce:
$ ifx --version
ifx_orig (IFORT) 2021.1 Beta 20201113
Copyright (C) 1985-2020 Intel Corporation. All rights reserved.
The regex for ifx currently expects the output to begin with
"ifx (IFORT)..." so the wrapper would not be detected as ifx. This
PR removes the need for the static "ifx" string which allows wrappers
to be detected as ifx.
In general, the Intel compiler regexes do not include the invoked
executable name (i.e., ifort, icc, icx, etc.), so this is not
expected to cause any issues.
* make `spack fetch` work with environments
* previously: `spack fetch` required the explicit statement of
the specs to be fetched, even when in an environment
* now: if there is no spec(s) provided to `spack fetch` we check
if an environment is active and if yes we fetch all
uninstalled specs.
When using an external package with the old concretizer, all
dependencies of that external package were severed. This was not
performed bidirectionally though, so for an external package W with
a dependency on Z, if some other package Y depended on Z, Z could
still pull properties (e.g. compiler) from W since it was not
severed as a parent dependency.
This performs the severing bidirectionally, and adds tests to
confirm expected behavior when using config from DAG-adjacent
packages during concretization.
This allows for quickly configuring a spack install/env to use upstream packages by default. This is particularly important when upstreaming from a set of officially supported spack installs on a production cluster. By configuring such that package preferences match the upstream, you ensure maximal reuse of existing package installations.
Fixes for gitlab pipelines
* Remove accidentally retained testing branch name
* Generate pipeline w/out debug mode
* Make jobs interruptible for auto-cancel pending
* Work around concretization conflicts
* Support clingo when used with cffi
Clingo recently merged in a new Python module option based on cffi.
Compatibility with this module requires a few changes to spack - it does not automatically convert strings/ints/etc to Symbol and clingo.Symbol.string throws on failure.
manually convert str/int to clingo.Symbol types
catch stringify exceptions
add job for clingo-cffi to Spack CI
switch to potassco-vendored wheel for clingo-cffi CI
on_unsat argument when cffi
* Spec.splice feature
Construct a new spec with a dependency swapped out. Currently can only swap dependencies of the same name, and can only apply to concrete specs.
This feature is not yet attached to any install functionality, but will eventually allow us to "rewire" a package to depend on a different set of dependencies.
Docstring is reformatted for git below
Splices dependency "other" into this ("target") Spec, and return the result as a concrete Spec.
If transitive, then other and its dependencies will be extrapolated to a list of Specs and spliced in accordingly.
For example, let there exist a dependency graph as follows:
T
| \
Z<-H
In this example, Spec T depends on H and Z, and H also depends on Z.
Suppose, however, that we wish to use a differently-built H, known as H'. This function will splice in the new H' in one of two ways:
1. transitively, where H' depends on the Z' it was built with, and the new T* also directly depends on this new Z', or
2. intransitively, where the new T* and H' both depend on the original Z.
Since the Spec returned by this splicing function is no longer deployed the same way it was built, any such changes are tracked by setting the build_spec to point to the corresponding dependency from the original Spec.
Co-authored-by: Nathan Hanford <hanford1@llnl.gov>
If you install packages using spack install in an environment with
complex spec constraints, and the install fails, you may want to
test out the build using spack build-env; one issue (particularly
if you use concretize: together) is that it may be hard to pass
the appropriate spec that matches what the environment is
attempting to install.
This updates the build-env command to default to pulling a matching
spec from the environment rather than concretizing what the user
provides on the command line independently.
This makes a similar change to spack cd.
If the user-provided spec matches multiple specs in the environment,
then these commands will now report an error and display all
matching specs (to help the user specify).
Co-authored-by: Gregory Becker <becker33@llnl.gov>
