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# -*- coding: utf-8 -*-
# Copyright (C) 2015 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.
import collections
import enum
from taskflow.engines.action_engine import compiler as co
class Direction(enum.Enum):
"""Traversal direction enum."""
#: Go through successors.
FORWARD = 1
#: Go through predecessors.
BACKWARD = 2
def _extract_connectors(execution_graph, starting_node, direction,
through_flows=True, through_retries=True,
through_tasks=True):
if direction == Direction.FORWARD:
connected_iter = execution_graph.successors
else:
connected_iter = execution_graph.predecessors
connected_to_functors = {}
if through_flows:
connected_to_functors[co.FLOW] = connected_iter
connected_to_functors[co.FLOW_END] = connected_iter
if through_retries:
connected_to_functors[co.RETRY] = connected_iter
if through_tasks:
connected_to_functors[co.TASK] = connected_iter
return connected_iter(starting_node), connected_to_functors
def breadth_first_iterate(execution_graph, starting_node, direction,
through_flows=True, through_retries=True,
through_tasks=True):
"""Iterates connected nodes in execution graph (from starting node).
Does so in a breadth first manner.
Jumps over nodes with ``noop`` attribute (does not yield them back).
"""
initial_nodes_iter, connected_to_functors = _extract_connectors(
execution_graph, starting_node, direction,
through_flows=through_flows, through_retries=through_retries,
through_tasks=through_tasks)
q = collections.deque(initial_nodes_iter)
while q:
node = q.popleft()
node_attrs = execution_graph.nodes[node]
if not node_attrs.get('noop'):
yield node
try:
node_kind = node_attrs['kind']
connected_to_functor = connected_to_functors[node_kind]
except KeyError:
pass
else:
q.extend(connected_to_functor(node))
def depth_first_iterate(execution_graph, starting_node, direction,
through_flows=True, through_retries=True,
through_tasks=True):
"""Iterates connected nodes in execution graph (from starting node).
Does so in a depth first manner.
Jumps over nodes with ``noop`` attribute (does not yield them back).
"""
initial_nodes_iter, connected_to_functors = _extract_connectors(
execution_graph, starting_node, direction,
through_flows=through_flows, through_retries=through_retries,
through_tasks=through_tasks)
stack = list(initial_nodes_iter)
while stack:
node = stack.pop()
node_attrs = execution_graph.nodes[node]
if not node_attrs.get('noop'):
yield node
try:
node_kind = node_attrs['kind']
connected_to_functor = connected_to_functors[node_kind]
except KeyError:
pass
else:
stack.extend(connected_to_functor(node))
def depth_first_reverse_iterate(node, start_from_idx=-1):
"""Iterates connected (in reverse) **tree** nodes (from starting node).
Jumps through nodes with ``noop`` attribute (does not yield them back).
"""
# Always go left to right, since right to left is the pattern order
# and we want to go backwards and not forwards through that ordering...
if start_from_idx == -1:
# All of them...
children_iter = node.reverse_iter()
else:
children_iter = reversed(node[0:start_from_idx])
for child in children_iter:
if child.metadata.get('noop'):
# Jump through these...
for grand_child in child.dfs_iter(right_to_left=False):
if grand_child.metadata['kind'] in co.ATOMS:
yield grand_child.item
else:
yield child.item
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