# # Copyright (C) 2016-2018 Codethink Limited # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library. If not, see . # # Authors: # Tristan Van Berkom # Jürg Billeter # Tristan Maat import os import itertools from operator import itemgetter from collections import OrderedDict from pyroaring import BitMap # pylint: disable=no-name-in-module from ._exceptions import PipelineError from ._message import Message, MessageType from ._profile import Topics, PROFILER from . import Scope, Consistency from ._project import ProjectRefStorage # PipelineSelection() # # Defines the kind of pipeline selection to make when the pipeline # is provided a list of targets, for whichever purpose. # # These values correspond to the CLI `--deps` arguments for convenience. # class PipelineSelection(): # Select only the target elements in the associated targets NONE = 'none' # As NONE, but redirect elements that are capable of it REDIRECT = 'redirect' # Select elements which must be built for the associated targets to be built PLAN = 'plan' # All dependencies of all targets, including the targets ALL = 'all' # All direct build dependencies and their recursive runtime dependencies, # excluding the targets BUILD = 'build' # All direct runtime dependencies and their recursive runtime dependencies, # including the targets RUN = 'run' # Pipeline() # # Args: # project (Project): The Project object # context (Context): The Context object # artifacts (Context): The ArtifactCache object # class Pipeline(): def __init__(self, context, project, artifacts): self._context = context # The Context self._project = project # The toplevel project # # Private members # self._artifacts = artifacts # load() # # Loads elements from target names. # # This function is called with a list of lists, such that multiple # target groups may be specified. Element names specified in `targets` # are allowed to be redundant. # # Args: # target_groups (list of lists): Groups of toplevel targets to load # fetch_subprojects (bool): Whether we should fetch subprojects as a part of the # loading process, if they are not yet locally cached # rewritable (bool): Whether the loaded files should be rewritable # this is a bit more expensive due to deep copies # # Returns: # (tuple of lists): A tuple of grouped Element objects corresponding to target_groups # def load(self, target_groups, *, fetch_subprojects=True, rewritable=False): # First concatenate all the lists for the loader's sake targets = list(itertools.chain(*target_groups)) with PROFILER.profile(Topics.LOAD_PIPELINE, "_".join(t.replace(os.sep, "-") for t in targets)): elements = self._project.load_elements(targets, rewritable=rewritable, fetch_subprojects=fetch_subprojects) # Now create element groups to match the input target groups elt_iter = iter(elements) element_groups = [ [next(elt_iter) for i in range(len(group))] for group in target_groups ] return tuple(element_groups) # resolve_elements() # # Resolve element state and cache keys. # # Args: # targets (list of Element): The list of toplevel element targets # def resolve_elements(self, targets): with self._context.timed_activity("Resolving cached state", silent_nested=True): for element in self.dependencies(targets, Scope.ALL): # Preflight element._preflight() # Determine initial element state. element._update_state() # dependencies() # # Generator function to iterate over elements and optionally # also iterate over sources. # # Args: # targets (list of Element): The target Elements to loop over # scope (Scope): The scope to iterate over # recurse (bool): Whether to recurse into dependencies # def dependencies(self, targets, scope, *, recurse=True): # Keep track of 'visited' in this scope, so that all targets # share the same context. visited = (BitMap(), BitMap()) for target in targets: for element in target.dependencies(scope, recurse=recurse, visited=visited): yield element # plan() # # Generator function to iterate over only the elements # which are required to build the pipeline target, omitting # cached elements. The elements are yielded in a depth sorted # ordering for optimal build plans # # Args: # elements (list of Element): List of target elements to plan # # Returns: # (list of Element): A depth sorted list of the build plan # def plan(self, elements): # Keep locally cached elements in the plan if remote artifact cache is used # to allow pulling artifact with strict cache key, if available. plan_cached = not self._context.get_strict() and self._artifacts.has_fetch_remotes() return _Planner().plan(elements, plan_cached) # get_selection() # # Gets a full list of elements based on a toplevel # list of element targets # # Args: # targets (list of Element): The target Elements # mode (PipelineSelection): The PipelineSelection mode # # Various commands define a --deps option to specify what elements to # use in the result, this function reports a list that is appropriate for # the selected option. # def get_selection(self, targets, mode, *, silent=True): elements = None if mode == PipelineSelection.NONE: elements = targets elif mode == PipelineSelection.REDIRECT: # Redirect and log if permitted elements = [] for t in targets: new_elm = t._get_source_element() if new_elm != t and not silent: self._message(MessageType.INFO, "Element '{}' redirected to '{}'" .format(t.name, new_elm.name)) if new_elm not in elements: elements.append(new_elm) elif mode == PipelineSelection.PLAN: elements = self.plan(targets) else: if mode == PipelineSelection.ALL: scope = Scope.ALL elif mode == PipelineSelection.BUILD: scope = Scope.BUILD elif mode == PipelineSelection.RUN: scope = Scope.RUN elements = list(self.dependencies(targets, scope)) return elements # except_elements(): # # Return what we are left with after the intersection between # excepted and target elements and their unique dependencies is # gone. # # Args: # targets (list of Element): List of toplevel targetted elements # elements (list of Element): The list to remove elements from # except_targets (list of Element): List of toplevel except targets # # Returns: # (list of Element): The elements list with the intersected # exceptions removed # def except_elements(self, targets, elements, except_targets): if not except_targets: return elements targeted = list(self.dependencies(targets, Scope.ALL)) visited = [] def find_intersection(element): if element in visited: return visited.append(element) # Intersection elements are those that are also in # 'targeted', as long as we don't recurse into them. if element in targeted: yield element else: for dep in element.dependencies(Scope.ALL, recurse=False): yield from find_intersection(dep) # Build a list of 'intersection' elements, i.e. the set of # elements that lie on the border closest to excepted elements # between excepted and target elements. intersection = list(itertools.chain.from_iterable( find_intersection(element) for element in except_targets )) # Now use this set of elements to traverse the targeted # elements, except 'intersection' elements and their unique # dependencies. queue = [] visited = [] queue.extend(targets) while queue: element = queue.pop() if element in visited or element in intersection: continue visited.append(element) queue.extend(element.dependencies(Scope.ALL, recurse=False)) # That looks like a lot, but overall we only traverse (part # of) the graph twice. This could be reduced to once if we # kept track of parent elements, but is probably not # significant. # Ensure that we return elements in the same order they were # in before. return [element for element in elements if element in visited] # targets_include() # # Checks whether the given targets are, or depend on some elements # # Args: # targets (list of Element): A list of targets # elements (list of Element): List of elements to check # # Returns: # (bool): True if all of `elements` are the `targets`, or are # somehow depended on by `targets`. # def targets_include(self, targets, elements): target_element_set = set(self.dependencies(targets, Scope.ALL)) element_set = set(elements) return element_set.issubset(target_element_set) # subtract_elements() # # Subtract a subset of elements # # Args: # elements (list of Element): The element list # subtract (list of Element): List of elements to subtract from elements # # Returns: # (list): The original elements list, with elements in subtract removed # def subtract_elements(self, elements, subtract): subtract_set = set(subtract) return [ e for e in elements if e not in subtract_set ] # track_cross_junction_filter() # # Filters out elements which are across junction boundaries, # otherwise asserts that there are no such elements. # # This is currently assumed to be only relevant for element # lists targetted at tracking. # # Args: # project (Project): Project used for cross_junction filtering. # All elements are expected to belong to that project. # elements (list of Element): The list of elements to filter # cross_junction_requested (bool): Whether the user requested # cross junction tracking # # Returns: # (list of Element): The filtered or asserted result # def track_cross_junction_filter(self, project, elements, cross_junction_requested): # Filter out cross junctioned elements if not cross_junction_requested: elements = self._filter_cross_junctions(project, elements) self._assert_junction_tracking(elements) return elements # assert_consistent() # # Asserts that the given list of elements are in a consistent state, that # is to say that all sources are consistent and can at least be fetched. # # Consequently it also means that cache keys can be resolved. # def assert_consistent(self, elements): inconsistent = [] inconsistent_workspaced = [] with self._context.timed_activity("Checking sources"): for element in elements: if element._get_consistency() == Consistency.INCONSISTENT: if element._get_workspace(): inconsistent_workspaced.append(element) else: inconsistent.append(element) if inconsistent: detail = "Exact versions are missing for the following elements:\n\n" for element in inconsistent: detail += " Element: {} is inconsistent\n".format(element._get_full_name()) for source in element.sources(): if source._get_consistency() == Consistency.INCONSISTENT: detail += " {} is missing ref\n".format(source) detail += '\n' detail += "Try tracking these elements first with `bst source track`\n" raise PipelineError("Inconsistent pipeline", detail=detail, reason="inconsistent-pipeline") if inconsistent_workspaced: detail = "Some workspaces do not exist but are not closed\n" + \ "Try closing them with `bst workspace close`\n\n" for element in inconsistent_workspaced: detail += " " + element._get_full_name() + "\n" raise PipelineError("Inconsistent pipeline", detail=detail, reason="inconsistent-pipeline-workspaced") # assert_sources_cached() # # Asserts that sources for the given list of elements are cached. # # Args: # elements (list): The list of elements # def assert_sources_cached(self, elements): uncached = [] with self._context.timed_activity("Checking sources"): for element in elements: if element._get_consistency() < Consistency.CACHED and \ not element._source_cached(): uncached.append(element) if uncached: detail = "Sources are not cached for the following elements:\n\n" for element in uncached: detail += " Following sources for element: {} are not cached:\n".format(element._get_full_name()) for source in element.sources(): if source._get_consistency() < Consistency.CACHED: detail += " {}\n".format(source) detail += '\n' detail += "Try fetching these elements first with `bst source fetch`,\n" + \ "or run this command with `--fetch` option\n" raise PipelineError("Uncached sources", detail=detail, reason="uncached-sources") ############################################################# # Private Methods # ############################################################# # _filter_cross_junction() # # Filters out cross junction elements from the elements # # Args: # project (Project): The project on which elements are allowed # elements (list of Element): The list of elements to be tracked # # Returns: # (list): A filtered list of `elements` which does # not contain any cross junction elements. # def _filter_cross_junctions(self, project, elements): return [ element for element in elements if element._get_project() is project ] # _assert_junction_tracking() # # Raises an error if tracking is attempted on junctioned elements and # a project.refs file is not enabled for the toplevel project. # # Args: # elements (list of Element): The list of elements to be tracked # def _assert_junction_tracking(self, elements): # We can track anything if the toplevel project uses project.refs # if self._project.ref_storage == ProjectRefStorage.PROJECT_REFS: return # Ideally, we would want to report every cross junction element but not # their dependencies, unless those cross junction elements dependencies # were also explicitly requested on the command line. # # But this is too hard, lets shoot for a simple error. for element in elements: element_project = element._get_project() if element_project is not self._project: detail = "Requested to track sources across junction boundaries\n" + \ "in a project which does not use project.refs ref-storage." raise PipelineError("Untrackable sources", detail=detail, reason="untrackable-sources") # _message() # # Local message propagator # def _message(self, message_type, message, **kwargs): args = dict(kwargs) self._context.message( Message(None, message_type, message, **args)) # _Planner() # # An internal object used for constructing build plan # from a given resolved toplevel element, while considering what # parts need to be built depending on build only dependencies # being cached, and depth sorting for more efficient processing. # class _Planner(): def __init__(self): self.depth_map = OrderedDict() self.visiting_elements = set() # Here we want to traverse the same element more than once when # it is reachable from multiple places, with the interest of finding # the deepest occurance of every element def plan_element(self, element, depth): if element in self.visiting_elements: # circular dependency, already being processed return prev_depth = self.depth_map.get(element) if prev_depth is not None and prev_depth >= depth: # element and dependencies already processed at equal or greater depth return self.visiting_elements.add(element) for dep in element.dependencies(Scope.RUN, recurse=False): self.plan_element(dep, depth) # Dont try to plan builds of elements that are cached already if not element._cached_success(): for dep in element.dependencies(Scope.BUILD, recurse=False): self.plan_element(dep, depth + 1) self.depth_map[element] = depth self.visiting_elements.remove(element) def plan(self, roots, plan_cached): for root in roots: self.plan_element(root, 0) depth_sorted = sorted(self.depth_map.items(), key=itemgetter(1), reverse=True) return [item[0] for item in depth_sorted if plan_cached or not item[0]._cached_success()]