BuildSystem

BuildSystem is used by PETSc for configuration testing. Written solely in Python, it consists of a number of objects running in a coordinated fashion. Below we describe the main objects involved, and the organization of both the files and in-memory objects during the configure run. However, first we discuss the configure and build process at a higher level.

What is a build?

The build stage compiles source to object files, stores them somehow (usually in archives), and links shared libraries and executables. These are mechanical operations that reduce to applying a construction rule to sets of files. The Make tool is great at this job. However, other parts of Make are not as useful, and we should distinguish the two.

Make uses a single predicate, “older than”, to decide whether to apply a rule. This is a disaster. A useful upgrade to make would expand the list of available predicates, including things like “md5sum has changed” and “flags have changed”. There have been attempts to use Make to determine whether a file has changed, for example by using stamp files. However, it cannot be done without severe contortions which make it much harder to see what Make is doing and maintain the system. Right now, we can combine make with the ccache utility to minimize recompiling and relinking.

Why is configure necessary?

The configure program is designed to assemble all information and preconditions necessary for the build stage. This is a far more complicated task, heavily dependent on the local hardware and software environment. It is also the source of nearly every build problem. The most crucial aspect of a configure system is not performance, scalability, or even functionality, but debuggability. Configuration failure is at least as common as success, due to broken tools, operating system upgrades, hardware incompatibilities, user error, and a host of other reasons. Problem diagnosis is the single biggest bottleneck for development and maintenance time. Unfortunately, current systems are built to optimize the successful case rather than the unsuccessful. In PETSc, we have developed the BuildSystem package to remedy the shortcomings of configuration systems such as Autoconf, CMake, and SCons.

Why use PETSc BuildSystem?

PETSc’s fully functional configure model BuildSystem has also been used as the configuration tool for other open sources packages. As more than a few configuration tools currently exist, it is instructive to consider why PETSc would choose to create another from scratch. Below we list features and design considerations which lead us to prefer BuildSystem to the alternatives.

Namespacing

BuildSystem wraps collections of related tests in Python modules, which also hold the test results. Thus results are accessed using normal Python namespacing. As rudimentary as this sounds, no namespacing beyond the use of variable name prefixes is present in SCons, CMake, or Autoconf. Instead, a flat namespace is used, mirroring the situation in C. This tendency appears again when composing command lines for external tools, such as the compiler and linker. In the traditional configure tools, options are aggregated in a single bucket variable, such as INCLUDE or LIBS, whereas in BuildSystem one can trace the provenance of a flag before it is added to the command line. CMake also makes the unfortunate decision to force all link options to resolve to full paths, which causes havoc with compiler-private libraries.

Explicit control flow

The BuildSystem configure modules mentioned above, containing one Configure object per module, are organized explicitly into a directed acyclic graph (DAG). The user indicates dependence, an edge in the dependence graph, with a single call, requires('path.to.other.test', self), which not only structures the DAG, but returns the Configure object. The caller can then use this object to access the results of the tests run by the dependency, achieving test and result encapsulation simply.

Multi-language tests

BuildSystem maintains an explicit language stack, so that the current language can be manipulated by the test environment. A compile or link can be run using any language, complete with the proper compilers, flags, libraries, etc., with a single call. This automation is crucial for cross-language tests, which are thinly supported in current tools. In fact, the design of these tools inhibits this kind of check. The check_function_exists() call in Autoconf and CMake looks only for the presence of a particular symbol in a library, and fails in C++ and on Microsoft Windows, whereas the equivalent BuildSystem test can also take a declaration. The try_compile() test in Autoconf and CMake requires the entire list of libraries be present in the LIBS variable, providing no good way to obtain libraries from other tests in a modular fashion. As another example, if the user has a dependent library that requires libstdc++, but they are working with a C project, no straightforward method exists to add this dependency.

Subpackages

The most complicated, yet perhaps most useful, part of BuildSystem is support for dependent packages. It provides an object scaffolding for including a 3rd party package (more than 100 are now available) so that PETSc downloads, builds, and tests the package for inclusion. The native configure and build system for the package is used, and special support exists for GNU and CMake packages. No similar system exists in the other tools, which rely on static declarations, such as pkg-config or FindPackage.cmake files, that are not tested and often become obsolete. They also require that any dependent packages use the same configuration and build system.

Batch environments

Most systems, such as Autoconf and CMake, do not actually run tests in a batch environment, but rather require a direct specification, in CMake a “platform file”. This requires a human expert to write and maintain the platform file. Alternatively, BuildSystem submits a dynamically generated set of tests to the batch system, enabling automatic cross-configuration and cross-compilation.

Caching

Caching often seems like an attractive option since configuration can be quite time-consuming, and both Autoconf and CMake enable caching by default. However, no system has the ability to reliably invalidate the cache when the environment for the configuration changes. For example, a compiler or library dependency may be upgraded on the system. Moreover, dependencies between cached variables are not tracked, so that even if some variables are correctly updated after an upgrade, others which depend on them may not be. Moreover, CMake mixes together information which is discovered automatically with that explicitly provided by the user, which is often not tested.

Concision

The cognitive load is usually larger for larger code bases, and our observation is that the addition of logic to Autoconf and CMake is often quite cumbersome and verbose as they do not employ a modern, higher level language. Although BuildSystem itself is not widely used, it has the advantage of being written in a widely-understood, high-level language.

High level organization

A minimal BuildSystem setup consists of a config directory off the package root, which contains all the Python necessary to run (in addition to the BuildSystem source). At minimum, the config directory contains configure.py, which is executed to run the configure process, and a module for the package itself. For example, PETSc contains config/PETSc/petsc.py. It is also common to include a top level configure file to execute the configure, as this looks like Autotools,

#!/usr/bin/env python
import os
execfile(os.path.join(os.path.dirname(__file__), 'config', 'configure.py'))

The configure.py script constructs a tree of configure modules and executes the configure process over it. A minimal version of this would be

package = 'PETSc'

def configure(configure_options):
  # Command line arguments take precedence (but don't destroy argv[0])
  sys.argv = sys.argv[:1] + configure_options + sys.argv[1:]
  framework = config.framework.Framework(['--configModules='+package+'.Configure', '--optionsModule='+package+'.compilerOptions']+sys.argv[1:], loadArgDB = 0)
  framework.setup()
  framework.configure(out = sys.stdout)
  framework.storeSubstitutions(framework.argDB)
  framework.printSummary()
  framework.argDB.save(force = True)
  framework.logClear()
  framework.closeLog()

if __name__ == '__main__':
  configure([])

The PETSc configure.py is quite a bit longer than this, as it performs specialized command line processing, error handling, and integrating logging with the rest of PETSc.

The config/package/Configure.py module determines how the tree of Configure objects is built and how the configure information is output. The configure() method of the module will be run by the Framework object created at the top level. A minimal configure() method would look like

def configure(self):
  self.framework.header          = self.arch.arch+'/include/'+self.project+'conf.h'
  self.framework.makeMacroHeader = self.arch.arch+'/conf/'+self.project+'variables'
  self.framework.makeRuleHeader  = self.arch.arch+'/conf/'+self.project+'rules'

  self.Dump()
  self.logClear()
  return

The Dump method runs over the tree of configure modules, and outputs the data necessary for building, usually employing the addMakeMacro(), addMakeRule() and addDefine() methods. These methods funnel output to the include and make files defined by the framework object, and set at the beginning of this configure() method. There is also some simple information that is often used, which we define in the initializer,

def __init__(self, framework):
  config.base.Configure.__init__(self, framework)
  self.Project      = 'PETSc'
  self.project      = self.Project.lower()
  self.PROJECT      = self.Project.upper()
  self.headerPrefix = self.PROJECT
  self.substPrefix  = self.PROJECT
  self.framework.Project = self.Project
  return

More sophisticated configure assemblies, like PETSc, output some other custom information, such as information about the machine, configure process, and a script to recreate the configure run.

The Package configure module has two other main functions. First, top level options can be defined in the setupHelp() method,

def setupHelp(self, help):
  import nargs
  help.addArgument(self.Project, '-prefix=<path>', nargs.Arg(None, '', 'Specify location to install '+self.Project+' (eg. /usr/local)'))
  help.addArgument(self.Project, '-load-path=<path>', nargs.Arg(None, os.path.join(os.getcwd(), 'modules'), 'Specify location of auxiliary modules'))
  help.addArgument(self.Project, '-with-shared-libraries', nargs.ArgBool(None, 0, 'Make libraries shared'))
  help.addArgument(self.Project, '-with-dynamic-loading', nargs.ArgBool(None, 0, 'Make libraries dynamic'))
  return

This uses the BuildSystem help facility that is used to define options for all configure modules. The first argument groups these options into a section named for the package. The second task is to build the tree of modules for the configure run, using the setupDependencies() method. A simple way to do this is by explicitly declaring dependencies,

def setupDependencies(self, framework):
    config.base.Configure.setupDependencies(self, framework)
    self.setCompilers  = framework.require('config.setCompilers',                self)
    self.arch          = framework.require(self.Project+'.utilities.arch',       self.setCompilers)
    self.projectdir    = framework.require(self.Project+'.utilities.projectdir', self.arch)
    self.compilers     = framework.require('config.compilers',                   self)
    self.types         = framework.require('config.types',                       self)
    self.headers       = framework.require('config.headers',                     self)
    self.functions     = framework.require('config.functions',                   self)
    self.libraries     = framework.require('config.libraries',                   self)

    self.compilers.headerPrefix  = self.headerPrefix
    self.types.headerPrefix      = self.headerPrefix
    self.headers.headerPrefix    = self.headerPrefix
    self.functions.headerPrefix  = self.headerPrefix
    self.libraries.headerPrefix  = self.headerPrefix

The projectdir and arch modules define the project root directory and a build name so that multiple independent builds can be managed. The Framework.require() method creates an edge in the dependency graph for configure modules, and returns the module object so that it can be queried after the configure information is determined. Setting the header prefix routes all the defines made inside those modules to our package configure header. We can also automatically create configure modules based upon what we see on the filesystem,

for utility in os.listdir(os.path.join('config', self.Project, 'utilities')):
  (utilityName, ext) = os.path.splitext(utility)
  if not utilityName.startswith('.') and not utilityName.startswith('#') and ext == '.py' and not utilityName == '__init__':
    utilityObj                    = self.framework.require(self.Project+'.utilities.'+utilityName, self)
    utilityObj.headerPrefix       = self.headerPrefix
    utilityObj.archProvider       = self.arch
    utilityObj.languageProvider   = self.languages
    utilityObj.precisionProvider  = self.scalartypes
    utilityObj.installDirProvider = self.installdir
    utilityObj.externalPackagesDirProvider = self.externalpackagesdir
    setattr(self, utilityName.lower(), utilityObj)

The provider modules customize the information given to the module based upon settings for our package. For example, PETSc can be compiled with a scalar type that is single, double, or quad precision, and thus has a precisionProvider. If a package does not have this capability, the provider setting can be omitted.

Main objects

Framework

The config.framework.Framework object serves as the central control for a configure run. It maintains a graph of all the configure modules involved, which is also used to track dependencies between them. It initiates the run, compiles the results, and handles the final output. It maintains the help list for all options available in the run. The setup() method performs generic Script setup and then is called recursively on all the child modules. The cleanup() method performs the final output and logging actions,

• Substitute files

• Output configure header

• Log filesystem actions

Children may be added to the Framework using addChild() or getChild(), but the far more frequent method is to use require(). Here a module is requested, as in getChild(), but it is also required to run before another module, usually the one executing the require(). This provides a simple local interface to establish dependencies between the child modules, and provides a partial order on the children to the Framework.

A backwards compatibility mode is provided for which the user specifies a configure header and set of files to experience substitution, mirroring the common usage of Autoconf. Slight improvements have been made in that all defines are now guarded, various prefixes are allowed for defines and substitutions, and C specific constructs such as function prototypes and typedefs are removed to a separate header. However, this is not the intended future usage. The use of configure modules by other modules in the same run provides a model for the suggested interaction of a new build system with the Framework. If a module requires another, it merely executes a require(). For instance, the PETSc configure module for HYPRE requires information about MPI, and thus contains

self.mpi = self.framework.require("config.packages.MPI", self)

Notice that passing self for the last arguments means that the MPI module will run before the HYPRE module. Furthermore, we save the resulting object as self.mpi so that we may interrogate it later. HYPRE can initially test whether MPI was indeed found using self.mpi.found. When HYPRE requires the list of MPI libraries in order to link a test object, the module can use self.mpi.lib.

Base

The config.base.Configure is the base class for all configure objects. It handles several types of interaction. First, it has hooks that allow the Framework to initialize it correctly. The Framework will first instantiate the object and call setupDependencies(). All require() calls should be made in that method. The Framework will then call configure(). If it succeeds, the object will be marked as configured. Second, all configure tests should be run using executeTest() which formats the output and adds metadata for the log.

Third, all tests that involve preprocessing, compiling, linking, and running operator through base. Two forms of this check are provided for each operation. The first is an “output” form which is intended to provide the status and complete output of the command. The second, or “check” form will return a success or failure indication based upon the status and output. The routines are

outputPreprocess(), checkPreprocess(), preprocess()
outputCompile(),    checkCompile()
outputLink(),       checkLink()
outputRun(),        checkRun()

The language used for these operation is managed with a stack, similar to Autoconf, using pushLanguage() and popLanguage(). We also provide special forms used to check for valid compiler and linker flags, optionally adding them to the defaults.

checkCompilerFlag(), addCompilerFlag()
checkLinkerFlag(),   addLinkerFlag()

You can also use getExecutable() to search for executables.

After configure tests have been run, various kinds of output can be generated.A #define statement can be added to the configure header using addDefine(), and addTypedef() and addPrototype() also put information in this header file. Using addMakeMacro() and addMakeRule() will add make macros and rules to the output makefiles specified in the framework. In addition we provide addSubstitution() and addArgumentSubstitution() to mimic the behavior of Autoconf if necessary. The object may define a headerPrefix member, which will be appended, followed by an underscore, to every define which is output from it. Similarly, a substPrefix can be defined which applies to every substitution from the object. Typedefs and function prototypes are placed in a separate header in order to accommodate languages such as Fortran whose preprocessor can sometimes fail at these statements.