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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 |
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| .codecov.yml | ||
| .coveragerc | ||
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| .readthedocs.yml | ||
| CHANGELOG.md | ||
| COPYRIGHT | ||
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| README.md | ||
Spack
Spack is a multi-platform package manager that builds and installs multiple versions and configurations of software. It works on Linux, macOS, and many supercomputers. Spack is non-destructive: installing a new version of a package does not break existing installations, so many configurations of the same package can coexist.
Spack offers a simple "spec" syntax that allows users to specify versions and configuration options. Package files are written in pure Python, and specs allow package authors to write a single script for many different builds of the same package. With Spack, you can build your software all the ways you want to.
See the Feature Overview for examples and highlights.
To install spack and your first package, make sure you have Python. Then:
$ git clone https://github.com/spack/spack.git
$ cd spack/bin
$ ./spack install zlib
Documentation
Full documentation is available, or
run spack help or spack help --all.
Tutorial
We maintain a hands-on tutorial. It covers basic to advanced usage, packaging, developer features, and large HPC deployments. You can do all of the exercises on your own laptop using a Docker container.
Feel free to use these materials to teach users at your organization about Spack.
Community
Spack is an open source project. Questions, discussion, and contributions are welcome. Contributions can be anything from new packages to bugfixes, documentation, or even new core features.
Resources:
- Slack workspace: spackpm.slack.com. To get an invitation, click here.
- Mailing list: groups.google.com/d/forum/spack
- Twitter: @spackpm. Be sure to
@mentionus!
Contributing
Contributing to Spack is relatively easy. Just send us a
pull request.
When you send your request, make develop the destination branch on the
Spack repository.
Your PR must pass Spack's unit tests and documentation tests, and must be PEP 8 compliant. We enforce these guidelines with our CI process. To run these tests locally, and for helpful tips on git, see our Contribution Guide.
Spack's develop branch has the latest contributions. Pull requests
should target develop, and users who want the latest package versions,
features, etc. can use develop.
Releases
For multi-user site deployments or other use cases that need very stable software installations, we recommend using Spack's stable releases.
Each Spack release series also has a corresponding branch, e.g.
releases/v0.14 has 0.14.x versions of Spack, and releases/v0.13 has
0.13.x versions. We backport important bug fixes to these branches but
we do not advance the package versions or make other changes that would
change the way Spack concretizes dependencies within a release branch.
So, you can base your Spack deployment on a release branch and git pull
to get fixes, without the package churn that comes with develop.
The latest release is always available with the releases/latest tag.
See the docs on releases for more details.
Code of Conduct
Please note that Spack has a Code of Conduct. By participating in the Spack community, you agree to abide by its rules.
Authors
Many thanks go to Spack's contributors.
Spack was created by Todd Gamblin, tgamblin@llnl.gov.
Citing Spack
If you are referencing Spack in a publication, please cite the following paper:
- Todd Gamblin, Matthew P. LeGendre, Michael R. Collette, Gregory L. Lee, Adam Moody, Bronis R. de Supinski, and W. Scott Futral. The Spack Package Manager: Bringing Order to HPC Software Chaos. In Supercomputing 2015 (SC’15), Austin, Texas, November 15-20 2015. LLNL-CONF-669890.
License
Spack is distributed under the terms of both the MIT license and the Apache License (Version 2.0). Users may choose either license, at their option.
All new contributions must be made under both the MIT and Apache-2.0 licenses.
See LICENSE-MIT, LICENSE-APACHE, COPYRIGHT, and NOTICE for details.
SPDX-License-Identifier: (Apache-2.0 OR MIT)
LLNL-CODE-811652