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Advanced Topics in Packaging

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.

Setup for the Tutorial

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/tutorial

This 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 mpich

Now, 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.

Modifying a Package's Build Environment

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.

Set environment variables in dependent packages 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_environment <spack.package.PackageBase.setup_dependent_environment>` function. This function takes 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 packages that depend on it:

def setup_dependent_environment(self, spack_env, run_env, dependent_spec):
    spack_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 spack_env, but it's worth noting that modifications to run_env 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 mpich

Once 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-km7tsbgoyyywonyejkjoojskhc5knz3z

and double check the environment logs to verify that every variable was set to the correct value.

Set environment variables in your own package

Packages can modify their own build-time environment by implementing the :py:func:`setup_environment <spack.package.PackageBase.setup_environment>` function. For qt this looks like:

def setup_environment(self, spack_env, run_env):
    spack_env.set('MAKEFLAGS', '-j{0}'.format(make_jobs))
    run_env.set('QTDIR', self.prefix)

When qt builds, MAKEFLAGS will be defined in the environment.

To contrast with qt's :py:func:`setup_dependent_environment <spack.package.PackageBase.setup_dependent_environment>` function:

def setup_dependent_environment(self, spack_env, run_env, dependent_spec):
    spack_env.set('QTDIR', self.prefix)

Let's see how it works by completing the elpa package:

root@advanced-packaging-tutorial:/# spack edit elpa

In 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

Retrieving Library Information

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.

Accessing dependency libraries

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 armadillo

If 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-n2eojtazxbku6g4l5izucwwgnpwz77r4

Hopefully 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).

Providing libraries to dependents

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.txt

Unlike 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-lapack

and 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-sxmpu5an4dshnhickh6ykchyfda7jpyn

Since 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.

Other Packaging Topics

Attach attributes to other packages

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')

Extra query parameters

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.txt

We 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 hdf5

If 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