# taskflow.engines.action_engine.scopes

# Source code for taskflow.engines.action_engine.scopes

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

    #    Copyright (C) 2014 Yahoo! Inc. All Rights Reserved.
    #
    #    Licensed under the Apache License, Version 2.0 (the "License"); you may
    #    not use this file except in compliance with the License. You may obtain
    #    a copy of the License at
    #
    #         http://www.apache.org/licenses/LICENSE-2.0
    #
    #    Unless required by applicable law or agreed to in writing, software
    #    distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
    #    WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
    #    License for the specific language governing permissions and limitations
    #    under the License.

    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__)

    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

        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 = [a.name for a in visible]
                        LOG.trace("Scope visible to '%s' (limited by parent '%s'"
                                  " index < %s) is: %s", self._atom,
                                  parent.item.name, last_idx, visible_names)
                if self._names_only:
                    yield [a.name for a in visible]
                else:
                    yield visible
                last = parent

this page last updated: 2025-02-27 12:56:39

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