Spack tries to automatically configure packages with information from
dependencies such that all you need to do is to list the dependencies
(i.e., with the depends_on directive) and the build system (for example
by deriving from CmakePackage).
However, there are many special cases. Often you need to retrieve details about dependencies to set package-specific configuration options, or to define package-specific environment variables used by the package's build system. This tutorial covers how to retrieve build information from dependencies, and how you can automatically provide important information to dependents in your package.
Note
We do not recommend doing this section of the tutorial in a production Spack instance.
The tutorial uses custom package definitions with missing sections that will be filled in during the tutorial. These package definitions are stored in a separate package repository, which can be enabled with:
$ spack repo add --scope=site var/spack/repos/tutorialThis section of the tutorial may also require a newer version of gcc. If you have not already installed gcc @7.2.0 and added it to your configuration, you can do so with:
$ spack install [email protected] %[email protected]
$ spack compiler add --scope=site `spack location -i [email protected] %[email protected]`If you are using the tutorial docker image, all dependency packages will have been installed. Otherwise, to install these packages you can use the following commands:
$ spack install openblas
$ spack install netlib-lapack
$ spack install mpichNow, you are ready to set your preferred EDITOR and continue with
the rest of the tutorial.
Note
Several of these packages depend on an MPI implementation. You can use OpenMPI if you install it from scratch, but this is slow (>10 min.). A binary cache of MPICH may be provided, in which case you can force the package to use it and install quickly. All tutorial examples with packages that depend on MPICH include the spec syntax for building with it.
Spack sets up several environment variables like PATH by default to aid in
building a package, but many packages make use of environment variables which
convey specific information about their dependencies (e.g., MPICC).
This section covers how to update your Spack packages so that package-specific
environment variables are defined at build-time.
Dependencies can set environment variables that are required when their
dependents build. For example, when a package depends on a python extension
like py-numpy, Spack's python package will add it to PYTHONPATH
so it is available at build time; this is required because the default setup
that spack does is not sufficient for python to import modules.
To provide environment setup for a dependent, a package can implement the
:py:func:`setup_dependent_build_environment
<spack.package.PackageBase.setup_dependent_build_environment>`
and or :py:func:`setup_dependent_run_environment
<spack.package.PackageBase.setup_dependent_run_environment>` functions.
These functions take as a parameter a :py:class:`EnvironmentModifications
<spack.util.environment.EnvironmentModifications>` object, which includes
convenience methods to update the environment. For example, an MPI
implementation can set MPICC for build-time use for packages that
depend on it:
def setup_dependent_build_environment(self, env, dependent_spec):
env.set('MPICC', join_path(self.prefix.bin, 'mpicc'))In this case packages that depend on mpi will have MPICC defined in
their environment when they build. This section is focused on modifying the
build-time environment represented by env, but it's worth noting that
modifications to the run-time environment, made through the
:py:func:`setup_dependent_run_environment
<spack.package.PackageBase.setup_dependent_run_environment>` function's
env parameter, are included in Spack's automatically-generated
module files.
We can practice by editing the mpich package to set the MPICC
environment variable in the build-time environment of dependent packages.
root@advanced-packaging-tutorial:/# spack edit mpichOnce you're finished, the method should look like this:
def setup_dependent_environment(self, spack_env, run_env, dependent_spec):
spack_env.set('MPICC', join_path(self.prefix.bin, 'mpicc'))
spack_env.set('MPICXX', join_path(self.prefix.bin, 'mpic++'))
spack_env.set('MPIF77', join_path(self.prefix.bin, 'mpif77'))
spack_env.set('MPIF90', join_path(self.prefix.bin, 'mpif90'))
spack_env.set('MPICH_CC', spack_cc)
spack_env.set('MPICH_CXX', spack_cxx)
spack_env.set('MPICH_F77', spack_f77)
spack_env.set('MPICH_F90', spack_fc)
spack_env.set('MPICH_FC', spack_fc)At this point we can, for instance, install netlib-scalapack with
mpich:
root@advanced-packaging-tutorial:/# spack install netlib-scalapack ^mpich
...
==> Created stage in /usr/local/var/spack/stage/netlib-scalapack-2.0.2-km7tsbgoyyywonyejkjoojskhc5knz3z
==> No patches needed for netlib-scalapack
==> Building netlib-scalapack [CMakePackage]
==> Executing phase: 'cmake'
==> Executing phase: 'build'
==> Executing phase: 'install'
==> Successfully installed netlib-scalapack
Fetch: 0.01s. Build: 3m 59.86s. Total: 3m 59.87s.
[+] /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/netlib-scalapack-2.0.2-km7tsbgoyyywonyejkjoojskhc5knz3zand double check the environment logs to verify that every variable was set to the correct value.
Packages can modify their own build-time environment by implementing the
:py:func:`setup_build_environment
<spack.package.PackageBase.setup_build_environment` function and run-time
environment by implementing the
:py:func:`setup_run_environment
<spack.package.PackageBase.setup_run_environment` function.
For qt this looks like:
def setup_build_environment(self, env):
env.set('MAKEFLAGS', '-j{0}'.format(make_jobs))
if self.spec.satisfies('@5.11:'):
# QDoc uses LLVM as of 5.11; remove the LLVM_INSTALL_DIR to
# disable
try:
llvm_path = self.spec['llvm'].prefix
except KeyError:
# Prevent possibly incompatible system LLVM from being found
llvm_path = "/spack-disable-llvm"
env.set('LLVM_INSTALL_DIR', llvm_path)
def setup_run_environment(self, env):
env.set('QTDIR', self.prefix)
env.set('QTINC', self.prefix.inc)
env.set('QTLIB', self.prefix.lib)
env.prepend_path('QT_PLUGIN_PATH', self.prefix.plugins)When qt builds, MAKEFLAGS will be defined in the environment and,
for versions from 5.11 on, LLVM_INSTALL_DIR will also be defined.
To contrast with qt's :py:func:`setup_dependent_build_environment
<spack.package.PackageBase.setup_dependent_build_environment>`
function:
def setup_dependent_build_environment(self, env, dependent_spec):
env.set('QTDIR', self.prefix)
env.set('QTINC', self.prefix.inc)
env.set('QTLIB', self.prefix.lib)
env.prepend_path('QT_PLUGIN_PATH', self.prefix.plugins)It is not necessary to implement a setup_dependent_run_environment
method for qt so one is not provided.
Let's see how it works by completing the elpa package:
root@advanced-packaging-tutorial:/# spack edit elpaIn the end your method should look like:
def setup_environment(self, spack_env, run_env):
spec = self.spec
spack_env.set('CC', spec['mpi'].mpicc)
spack_env.set('FC', spec['mpi'].mpifc)
spack_env.set('CXX', spec['mpi'].mpicxx)
spack_env.set('SCALAPACK_LDFLAGS', spec['scalapack'].libs.joined())
spack_env.append_flags('LDFLAGS', spec['lapack'].libs.search_flags)
spack_env.append_flags('LIBS', spec['lapack'].libs.link_flags)At this point it's possible to proceed with the installation of elpa ^mpich
Although Spack attempts to help packages locate their dependency libraries
automatically (e.g. by setting PKG_CONFIG_PATH and CMAKE_PREFIX_PATH),
a package may have unique configuration options that are required to locate
libraries. When a package needs information about dependency libraries, the
general approach in Spack is to query the dependencies for the locations of
their libraries and set configuration options accordingly. By default most
Spack packages know how to automatically locate their libraries. This section
covers how to retrieve library information from dependencies and how to locate
libraries when the default logic doesn't work.
If you need to access the libraries of a dependency, you can do so
via the libs property of the spec, for example in the arpack-ng
package:
def install(self, spec, prefix):
lapack_libs = spec['lapack'].libs.joined(';')
blas_libs = spec['blas'].libs.joined(';')
cmake(*[
'-DLAPACK_LIBRARIES={0}'.format(lapack_libs),
'-DBLAS_LIBRARIES={0}'.format(blas_libs)
], '.')Note that arpack-ng is querying virtual dependencies, which Spack
automatically resolves to the installed implementation (e.g. openblas
for blas).
We've started work on a package for armadillo. You should open it,
read through the comment that starts with # TUTORIAL: and complete
the cmake_args section:
root@advanced-packaging-tutorial:/# spack edit armadilloIf you followed the instructions in the package, when you are finished your
cmake_args method should look like:
def cmake_args(self):
spec = self.spec
return [
# ARPACK support
'-DARPACK_LIBRARY={0}'.format(spec['arpack-ng'].libs.joined(";")),
# BLAS support
'-DBLAS_LIBRARY={0}'.format(spec['blas'].libs.joined(";")),
# LAPACK support
'-DLAPACK_LIBRARY={0}'.format(spec['lapack'].libs.joined(";")),
# SuperLU support
'-DSuperLU_INCLUDE_DIR={0}'.format(spec['superlu'].prefix.include),
'-DSuperLU_LIBRARY={0}'.format(spec['superlu'].libs.joined(";")),
# HDF5 support
'-DDETECT_HDF5={0}'.format('ON' if '+hdf5' in spec else 'OFF')
]As you can see, getting the list of libraries that your dependencies provide
is as easy as accessing the their libs attribute. Furthermore, the interface
remains the same whether you are querying regular or virtual dependencies.
At this point you can complete the installation of armadillo using openblas
as a LAPACK provider (armadillo ^openblas ^mpich):
root@advanced-packaging-tutorial:/# spack install armadillo ^openblas ^mpich
==> pkg-config is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/pkg-config-0.29.2-ae2hwm7q57byfbxtymts55xppqwk7ecj
...
==> superlu is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/superlu-5.2.1-q2mbtw2wo4kpzis2e2n227ip2fquxrno
==> Installing armadillo
==> Using cached archive: /usr/local/var/spack/cache/armadillo/armadillo-8.100.1.tar.xz
==> Staging archive: /usr/local/var/spack/stage/armadillo-8.100.1-n2eojtazxbku6g4l5izucwwgnpwz77r4/armadillo-8.100.1.tar.xz
==> Created stage in /usr/local/var/spack/stage/armadillo-8.100.1-n2eojtazxbku6g4l5izucwwgnpwz77r4
==> Applied patch undef_linux.patch
==> Building armadillo [CMakePackage]
==> Executing phase: 'cmake'
==> Executing phase: 'build'
==> Executing phase: 'install'
==> Successfully installed armadillo
Fetch: 0.01s. Build: 3.96s. Total: 3.98s.
[+] /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/armadillo-8.100.1-n2eojtazxbku6g4l5izucwwgnpwz77r4Hopefully the installation went fine and the code we added expanded to the right list
of semicolon separated libraries (you are encouraged to open armadillo's
build logs to double check).
Spack provides a default implementation for libs which often works
out of the box. A user can write a package definition without having to
implement a libs property and dependents can retrieve its libraries
as shown in the above section. However, the default implementation assumes that
libraries follow the naming scheme lib<package name>.so (or e.g.
lib<package name>.a for static libraries). Packages which don't
follow this naming scheme must implement this function themselves, e.g.
opencv:
@property
def libs(self):
shared = "+shared" in self.spec
return find_libraries(
"libopencv_*", root=self.prefix, shared=shared, recursive=True
)This issue is common for packages which implement an interface (i.e.
virtual package providers in Spack). If we try to build another version of
armadillo tied to netlib-lapack (armadillo ^netlib-lapack ^mpich)
we'll notice that this time the installation won't complete:
root@advanced-packaging-tutorial:/# spack install armadillo ^netlib-lapack ^mpich
==> pkg-config is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/pkg-config-0.29.2-ae2hwm7q57byfbxtymts55xppqwk7ecj
...
==> openmpi is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/openmpi-3.0.0-yo5qkfvumpmgmvlbalqcadu46j5bd52f
==> Installing arpack-ng
==> Using cached archive: /usr/local/var/spack/cache/arpack-ng/arpack-ng-3.5.0.tar.gz
==> Already staged arpack-ng-3.5.0-bloz7cqirpdxj33pg7uj32zs5likz2un in /usr/local/var/spack/stage/arpack-ng-3.5.0-bloz7cqirpdxj33pg7uj32zs5likz2un
==> No patches needed for arpack-ng
==> Building arpack-ng [Package]
==> Executing phase: 'install'
==> Error: RuntimeError: Unable to recursively locate netlib-lapack libraries in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/netlib-lapack-3.6.1-jjfe23wgt7nkjnp2adeklhseg3ftpx6z
RuntimeError: RuntimeError: Unable to recursively locate netlib-lapack libraries in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/netlib-lapack-3.6.1-jjfe23wgt7nkjnp2adeklhseg3ftpx6z
/usr/local/var/spack/repos/builtin/packages/arpack-ng/package.py:105, in install:
5 options.append('-DCMAKE_INSTALL_NAME_DIR:PATH=%s/lib' % prefix)
6
7 # Make sure we use Spack's blas/lapack:
>> 8 lapack_libs = spec['lapack'].libs.joined(';')
9 blas_libs = spec['blas'].libs.joined(';')
10
11 options.extend([
See build log for details:
/usr/local/var/spack/stage/arpack-ng-3.5.0-bloz7cqirpdxj33pg7uj32zs5likz2un/arpack-ng-3.5.0/spack-build-out.txtUnlike openblas which provides a library named libopenblas.so,
netlib-lapack provides liblapack.so, so it needs to implement
customized library search logic. Let's edit it:
root@advanced-packaging-tutorial:/# spack edit netlib-lapackand follow the instructions in the # TUTORIAL: comment as before.
What we need to implement is:
@property
def lapack_libs(self):
shared = True if '+shared' in self.spec else False
return find_libraries(
'liblapack', root=self.prefix, shared=shared, recursive=True
)i.e., a property that returns the correct list of libraries for the LAPACK interface.
We use the name lapack_libs rather than libs because
netlib-lapack can also provide blas, and when it does it is provided
as a separate library file. Using this name ensures that when
dependents ask for lapack libraries, netlib-lapack will retrieve only
the libraries associated with the lapack interface. Now we can finally
install armadillo ^netlib-lapack ^mpich:
root@advanced-packaging-tutorial:/# spack install armadillo ^netlib-lapack ^mpich
...
==> Building armadillo [CMakePackage]
==> Executing phase: 'cmake'
==> Executing phase: 'build'
==> Executing phase: 'install'
==> Successfully installed armadillo
Fetch: 0.01s. Build: 3.75s. Total: 3.76s.
[+] /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/armadillo-8.100.1-sxmpu5an4dshnhickh6ykchyfda7jpynSince each implementation of a virtual package is responsible for locating the
libraries associated with the interfaces it provides, dependents do not need
to include special-case logic for different implementations and for example
need only ask for spec['blas'].libs.
Build tools usually also provide a set of executables that can be used when another package is being installed. Spack gives you the opportunity to monkey-patch dependent modules and attach attributes to them. This helps make the packager experience as similar as possible to what would have been the manual installation of the same package.
An example here is the automake package, which overrides
:py:func:`setup_dependent_package <spack.package.PackageBase.setup_dependent_package>`:
def setup_dependent_package(self, module, dependent_spec):
# Automake is very likely to be a build dependency,
# so we add the tools it provides to the dependent module
executables = ['aclocal', 'automake']
for name in executables:
setattr(module, name, self._make_executable(name))so that every other package that depends on it can use directly aclocal
and automake with the usual function call syntax of :py:class:`Executable <spack.util.executable.Executable>`:
aclocal('--force')An advanced feature of the Spec's build-interface protocol is the support for extra parameters after the subscript key. In fact, any of the keys used in the query can be followed by a comma-separated list of extra parameters which can be inspected by the package receiving the request to fine-tune a response.
Let's look at an example and try to install netcdf ^mpich:
root@advanced-packaging-tutorial:/# spack install netcdf ^mpich
==> libsigsegv is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/libsigsegv-2.11-fypapcprssrj3nstp6njprskeyynsgaz
==> m4 is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/m4-1.4.18-r5envx3kqctwwflhd4qax4ahqtt6x43a
...
==> Error: AttributeError: 'list' object has no attribute 'search_flags'
AttributeError: AttributeError: 'list' object has no attribute 'search_flags'
/usr/local/var/spack/repos/builtin/packages/netcdf/package.py:207, in configure_args:
50 # used instead.
51 hdf5_hl = self.spec['hdf5:hl']
52 CPPFLAGS.append(hdf5_hl.headers.cpp_flags)
>> 53 LDFLAGS.append(hdf5_hl.libs.search_flags)
54
55 if '+parallel-netcdf' in self.spec:
56 config_args.append('--enable-pnetcdf')
See build log for details:
/usr/local/var/spack/stage/netcdf-4.4.1.1-gk2xxhbqijnrdwicawawcll4t3c7dvoj/netcdf-4.4.1.1/spack-build-out.txtWe can see from the error that netcdf needs to know how to link the high-level interface
of hdf5, and thus passes the extra parameter hl after the request to retrieve it.
Clearly the implementation in the hdf5 package is not complete, and we need to fix it:
root@advanced-packaging-tutorial:/# spack edit hdf5If you followed the instructions correctly, the code added to the
lib property should be similar to:
query_parameters = self.spec.last_query.extra_parameters
key = tuple(sorted(query_parameters))
libraries = query2libraries[key]
shared = '+shared' in self.spec
return find_libraries(
libraries, root=self.prefix, shared=shared, recurse=True
)where we highlighted the line retrieving the extra parameters. Now we can successfully
complete the installation of netcdf ^mpich:
root@advanced-packaging-tutorial:/# spack install netcdf ^mpich
==> libsigsegv is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/libsigsegv-2.11-fypapcprssrj3nstp6njprskeyynsgaz
==> m4 is already installed in /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/m4-1.4.18-r5envx3kqctwwflhd4qax4ahqtt6x43a
...
==> Installing netcdf
==> Using cached archive: /usr/local/var/spack/cache/netcdf/netcdf-4.4.1.1.tar.gz
==> Already staged netcdf-4.4.1.1-gk2xxhbqijnrdwicawawcll4t3c7dvoj in /usr/local/var/spack/stage/netcdf-4.4.1.1-gk2xxhbqijnrdwicawawcll4t3c7dvoj
==> Already patched netcdf
==> Building netcdf [AutotoolsPackage]
==> Executing phase: 'autoreconf'
==> Executing phase: 'configure'
==> Executing phase: 'build'
==> Executing phase: 'install'
==> Successfully installed netcdf
Fetch: 0.01s. Build: 24.61s. Total: 24.62s.
[+] /usr/local/opt/spack/linux-ubuntu16.04-x86_64/gcc-5.4.0/netcdf-4.4.1.1-gk2xxhbqijnrdwicawawcll4t3c7dvoj