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()`.
* New package py-argh
* Fixed deps
* Changed setuptools type
* Update var/spack/repos/builtin/packages/py-argh/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
* 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.
* Fixed a bug in the DiHydrogen package where the variant legacy was
changed to distconv and wasn't fully propagated. Cleaned up the
openmp variants on the blas library packages in DiHydrogen and
Elemental. Extended support for Aluminum v1.0 in LBANN, Hydrogen, and
DiHydrogen. Fixed a when clause in the LBANN dependencies.
* Removed the upper range limit for the Aluminum library dependence
* Update var/spack/repos/builtin/packages/dihydrogen/package.py
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
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.
