Files
deb-python-taskflow/taskflow/engines/action_engine/analyzer.py
Joshua Harlow 7b5dad30ed Rename the graph analyzer to analyzer
Adjust the graph analyzer to be a more generic compilation
analyzer which analyzes compilation objects (which are now
changed to be an object and not a named tuple) and provides
utility functions ontop of that object. This helps it become
possible to provide other useful analysis functions that are
not directly tied to the execution graph component but can
be provided ontop of other compilation components.

Change-Id: I2ab08db4f566d5f329d7e79b1c50ed65aad9e4b3
2014-06-03 01:22:47 +00:00

153 lines
5.3 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (C) 2013 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 networkx.algorithms import traversal
import six
from taskflow import retry as retry_atom
from taskflow import states as st
class Analyzer(object):
"""Analyzes a compilation output to get the next atoms for execution or
reversion by utilizing the compilations underlying structures (graphs,
nodes and edge relations...) and using this information along with the
atom state/states stored in storage to provide useful analysis functions
to the rest of the runtime system.
"""
def __init__(self, compilation, storage):
self._storage = storage
self._graph = compilation.execution_graph
def get_next_nodes(self, node=None):
if node is None:
execute = self.browse_nodes_for_execute()
revert = self.browse_nodes_for_revert()
return execute + revert
state = self.get_state(node)
intention = self._storage.get_atom_intention(node.name)
if state == st.SUCCESS:
if intention == st.REVERT:
return [node]
elif intention == st.EXECUTE:
return self.browse_nodes_for_execute(node)
else:
return []
elif state == st.REVERTED:
return self.browse_nodes_for_revert(node)
elif state == st.FAILURE:
return self.browse_nodes_for_revert()
else:
return []
def browse_nodes_for_execute(self, node=None):
"""Browse next nodes to execute for given node if specified and
for whole graph otherwise.
"""
if node:
nodes = self._graph.successors(node)
else:
nodes = self._graph.nodes_iter()
available_nodes = []
for node in nodes:
if self._is_ready_for_execute(node):
available_nodes.append(node)
return available_nodes
def browse_nodes_for_revert(self, node=None):
"""Browse next nodes to revert for given node if specified and
for whole graph otherwise.
"""
if node:
nodes = self._graph.predecessors(node)
else:
nodes = self._graph.nodes_iter()
available_nodes = []
for node in nodes:
if self._is_ready_for_revert(node):
available_nodes.append(node)
return available_nodes
def _is_ready_for_execute(self, task):
"""Checks if task is ready to be executed."""
state = self.get_state(task)
intention = self._storage.get_atom_intention(task.name)
transition = st.check_task_transition(state, st.RUNNING)
if not transition or intention != st.EXECUTE:
return False
task_names = []
for prev_task in self._graph.predecessors(task):
task_names.append(prev_task.name)
task_states = self._storage.get_atoms_states(task_names)
return all(state == st.SUCCESS and intention == st.EXECUTE
for state, intention in six.itervalues(task_states))
def _is_ready_for_revert(self, task):
"""Checks if task is ready to be reverted."""
state = self.get_state(task)
intention = self._storage.get_atom_intention(task.name)
transition = st.check_task_transition(state, st.REVERTING)
if not transition or intention not in (st.REVERT, st.RETRY):
return False
task_names = []
for prev_task in self._graph.successors(task):
task_names.append(prev_task.name)
task_states = self._storage.get_atoms_states(task_names)
return all(state in (st.PENDING, st.REVERTED)
for state, intention in six.itervalues(task_states))
def iterate_subgraph(self, retry):
"""Iterates a subgraph connected to current retry controller, including
nested retry controllers and its nodes.
"""
for _src, dst in traversal.dfs_edges(self._graph, retry):
yield dst
def iterate_retries(self, state=None):
"""Iterates retry controllers of a graph with given state or all
retries if state is None.
"""
for node in self._graph.nodes_iter():
if isinstance(node, retry_atom.Retry):
if not state or self.get_state(node) == state:
yield node
def iterate_all_nodes(self):
for node in self._graph.nodes_iter():
yield node
def find_atom_retry(self, atom):
return self._graph.node[atom].get('retry')
def is_success(self):
for node in self._graph.nodes_iter():
if self.get_state(node) != st.SUCCESS:
return False
return True
def get_state(self, node):
return self._storage.get_atom_state(node.name)