Source code for taskflow.engines.action_engine.scopes

# -*- coding: utf-8 -*-

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from taskflow.engines.action_engine import compiler as co
from taskflow.engines.action_engine import traversal as tr
from taskflow import logging

LOG = logging.getLogger(__name__)

[docs]class ScopeWalker(object): """Walks through the scopes of a atom using a engines compilation. NOTE(harlowja): for internal usage only. This will walk the visible scopes that are accessible for the given atom, which can be used by some external entity in some meaningful way, for example to find dependent values... """ def __init__(self, compilation, atom, names_only=False): self._node = compilation.hierarchy.find(atom) if self._node is None: raise ValueError("Unable to find atom '%s' in compilation" " hierarchy" % atom) self._level_cache = {} self._atom = atom self._execution_graph = compilation.execution_graph self._names_only = names_only self._predecessors = None
[docs] def __iter__(self): """Iterates over the visible scopes. How this works is the following: We first grab all the predecessors of the given atom (lets call it ``Y``) by using the :py:class:`~.compiler.Compilation` execution graph (and doing a reverse breadth-first expansion to gather its predecessors), this is useful since we know they *always* will exist (and execute) before this atom but it does not tell us the corresponding scope *level* (flow, nested flow...) that each predecessor was created in, so we need to find this information. For that information we consult the location of the atom ``Y`` in the :py:class:`~.compiler.Compilation` hierarchy/tree. We lookup in a reverse order the parent ``X`` of ``Y`` and traverse backwards from the index in the parent where ``Y`` exists to all siblings (and children of those siblings) in ``X`` that we encounter in this backwards search (if a sibling is a flow itself, its atom(s) will be recursively expanded and included). This collection will then be assumed to be at the same scope. This is what is called a *potential* single scope, to make an *actual* scope we remove the items from the *potential* scope that are **not** predecessors of ``Y`` to form the *actual* scope which we then yield back. Then for additional scopes we continue up the tree, by finding the parent of ``X`` (lets call it ``Z``) and perform the same operation, going through the children in a reverse manner from the index in parent ``Z`` where ``X`` was located. This forms another *potential* scope which we provide back as an *actual* scope after reducing the potential set to only include predecessors previously gathered. We then repeat this process until we no longer have any parent nodes (aka we have reached the top of the tree) or we run out of predecessors. """ graph = self._execution_graph if self._predecessors is None: predecessors = set( node for node in graph.bfs_predecessors_iter(self._atom) if graph.nodes[node]['kind'] in co.ATOMS) self._predecessors = predecessors.copy() else: predecessors = self._predecessors.copy() last = self._node for lvl, parent in enumerate(self._node.path_iter(include_self=False)): if not predecessors: break last_idx = parent.index(last.item) try: visible, removals = self._level_cache[lvl] predecessors = predecessors - removals except KeyError: visible = [] removals = set() atom_it = tr.depth_first_reverse_iterate( parent, start_from_idx=last_idx) for atom in atom_it: if atom in predecessors: predecessors.remove(atom) removals.add(atom) visible.append(atom) if not predecessors: break self._level_cache[lvl] = (visible, removals) if LOG.isEnabledFor(logging.TRACE): visible_names = [ for a in visible] LOG.trace("Scope visible to '%s' (limited by parent '%s'" " index < %s) is: %s", self._atom,, last_idx, visible_names) if self._names_only: yield [ for a in visible] else: yield visible last = parent