Expand answer
We'll install MG(1)
, a standard editor.
Make sure you're setup as per the instructions linked on the README, then install the editor via
$ spack install mg
One can then run mg
with
$ spack load mg
$ mg foo.txt
Expand answer
If you are on the BlueBrain5, you shouldn't need to.
As described here, one can use the system packages available with appropriate configuration options. If those instructions don't help, please use the #spack channel on Slack.
Expand answer
Make sure the spack
repo is checked out in a subdirectory of $HOME
.
The spack
repository is quite large, and when it is checked out under a
/gpfs/bbp.cscs.ch/project/*
directory, performance can be 10x slower
than on the SSD provided storage of $HOME
.
Expand answer
No. Possibilities are being explored to provide a binary cache configuration for our desktops.
Expand answer
The spack module tcl refresh
command respects a exclude list that can be
found via:
$ spack config blame modules
This exclude list is overruled by a corresponding include list. If your software is not listed in the latter, no modules will be generated for it.
Use
$ spack config add "modules:default:tcl:include:[my_package]"
$ spack module tcl refresh my_package
To produce an up-to-date module for my_package
(adjust as needed).
Expand answer
When determining what to build (to concretize a spec in "Spack lingo"), sometimes Spack will not be able to satisfy the requirements of all software needing to be built. It may then display a somewhat cryptic error message:
❯ spack spec -I py-morphology-repair-workflow\^py-pandas@1.3:
Input spec
--------------------------------
- py-morphology-repair-workflow
- ^py-pandas@1.3:
Concretized
--------------------------------
==> Error: py-morphology-repair-workflow ^py-pandas@1.3: is unsatisfiable, errors are:
no version satisfies the given constraints
To see full clingo unsat cores, re-run with `spack --show-cores=full`
For full, subset-minimal unsat cores, re-run with `spack --show-cores=minimized
Warning: This may take (up to) hours for some specs
By running the recommendation, one may produce more cryptic output:
❯ spack --show-cores=full spec -I py-morphology-repair-workflow\^py-pandas@1.3:
Input spec
--------------------------------
- py-morphology-repair-workflow
- ^py-pandas@1.3:
Concretized
--------------------------------
==> Error: py-morphology-repair-workflow ^py-pandas@1.3: is unsatisfiable, conflicts are:
condition(5258)
condition(5275)
condition(5281)
dependency_condition(5258,"py-morph-validator","py-pandas")
dependency_condition(5275,"py-morphology-repair-workflow","py-morph-validator")
dependency_condition(5281,"py-morphology-repair-workflow","py-pandas")
dependency_type(5258,"build")
dependency_type(5275,"run")
dependency_type(5281,"run")
imposed_constraint(5258,"version_satisfies","py-pandas","0.25:1.2.99")
no version satisfies the given constraints
root("py-morphology-repair-workflow")
version_satisfies("py-pandas","1.3:")
For full, subset-minimal unsat cores, re-run with `spack --show-cores=minimized
Warning: This may take (up to) hours for some specs
By analyzing the output, it can be seen that
py-morphology-repair-workflow
depends on py-morph-validator
,
which in turn depends on py-pandas
between versions 0.25
and
1.2.99
(using the numerical references together with the package names
/ versions).
This in turn conflicts with the user requirement of a py-pandas
newer
than 1.3
.
Removing said user requirement will make the software install.
In other instances, loosening dependency requirements in packages may be
the appropriate solution.