.. Copyright 2013-2019 Lawrence Livermore National Security, LLC and other Spack Project Developers. See the top-level COPYRIGHT file for details. SPDX-License-Identifier: (Apache-2.0 OR MIT) .. _advanced-packaging-tutorial: ============================ 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 :code:`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: .. code-block:: console $ 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: .. code-block:: console $ spack install gcc@7.2.0 %gcc@5.4.0 $ spack compiler add --scope=site `spack location -i gcc@7.2.0 %gcc@5.4.0` 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: .. code-block:: console $ 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 .. _adv_pkg_tutorial_start: --------------------------------------- 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 ` function. This function takes as a parameter a :py:class:`EnvironmentModifications ` object which includes convenience methods to update the environment. For example, an MPI implementation can set ``MPICC`` for packages that depend on it: .. code-block:: python 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. .. code-block:: console root@advanced-packaging-tutorial:/# spack edit mpich Once you're finished, the method should look like this: .. code-block:: python 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``: .. code-block:: console 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 ` function. For ``qt`` this looks like: .. code-block:: python 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 ` function: .. code-block:: python 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: .. code-block:: console root@advanced-packaging-tutorial:/# spack edit elpa In the end your method should look like: .. code-block:: python 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: .. code-block:: python 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: .. code-block:: console 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: .. code-block:: python 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``): .. code-block:: console 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.so`` (or e.g. ``lib.a`` for static libraries). Packages which don't follow this naming scheme must implement this function themselves, e.g. ``opencv``: .. code-block:: python @property def libs(self): shared = "+shared" in self.spec return find_libraries( "libopencv_*", root=self.prefix, shared=shared, recurse=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: .. code-block:: console 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 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: .. code-block:: console root@advanced-packaging-tutorial:/# spack edit netlib-lapack and follow the instructions in the ``# TUTORIAL:`` comment as before. What we need to implement is: .. code-block:: python @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``: .. code-block:: console 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 :code:`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 `: .. code-block:: python 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 `: .. code-block:: python 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``: .. code-block:: console 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 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: .. code-block:: console root@advanced-packaging-tutorial:/# spack edit hdf5 If you followed the instructions correctly, the code added to the ``lib`` property should be similar to: .. code-block:: python :emphasize-lines: 1 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``: .. code-block:: console 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