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# -*- 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.
import abc
import itertools
import weakref
from networkx.algorithms import traversal
import six
from taskflow import states as st
@six.add_metaclass(abc.ABCMeta)
class Decider(object):
"""Base class for deciders.
Provides interface to be implemented by sub-classes
Decider checks whether next atom in flow should be executed or not
"""
@abc.abstractmethod
def check(self, runtime):
"""Returns bool of whether this decider should allow running."""
@abc.abstractmethod
def affect(self, runtime):
"""If the :py:func:`~.check` returns false, affects associated atoms.
"""
def check_and_affect(self, runtime):
"""Handles :py:func:`~.check` + :py:func:`~.affect` in right order."""
proceed = self.check(runtime)
if not proceed:
self.affect(runtime)
return proceed
class IgnoreDecider(Decider):
"""Checks any provided edge-deciders and determines if ok to run."""
def __init__(self, atom, edge_deciders):
self._atom = atom
self._edge_deciders = edge_deciders
def check(self, runtime):
"""Returns bool of whether this decider should allow running."""
results = {}
for name in six.iterkeys(self._edge_deciders):
results[name] = runtime.storage.get(name)
for local_decider in six.itervalues(self._edge_deciders):
if not local_decider(history=results):
return False
return True
def affect(self, runtime):
"""If the :py:func:`~.check` returns false, affects associated atoms.
This will alter the associated atom + successor atoms by setting there
state to ``IGNORE`` so that they are ignored in future runtime
activities.
"""
successors_iter = runtime.analyzer.iterate_subgraph(self._atom)
runtime.reset_nodes(itertools.chain([self._atom], successors_iter),
state=st.IGNORE, intention=st.IGNORE)
class NoOpDecider(Decider):
"""No-op decider that says it is always ok to run & has no effect(s)."""
def check(self, runtime):
"""Always good to go."""
return True
def affect(self, runtime):
"""Does nothing."""
class Analyzer(object):
"""Analyzes a compilation and aids in execution processes.
Its primary purpose is 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 other useful functionality to
the rest of the runtime system.
"""
def __init__(self, runtime):
self._runtime = weakref.proxy(runtime)
self._storage = runtime.storage
self._execution_graph = runtime.compilation.execution_graph
def get_next_nodes(self, node=None):
"""Get next nodes to run (originating from node or all nodes)."""
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, NoOpDecider()),
]
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.
This returns a collection of nodes that *may* be ready to be
executed, if given a specific node it will only examine the successors
of that node, otherwise it will examine the whole graph.
"""
if node is not None:
nodes = self._execution_graph.successors(node)
else:
nodes = self._execution_graph.nodes_iter()
ready_nodes = []
for node in nodes:
is_ready, late_decider = self._get_maybe_ready_for_execute(node)
if is_ready:
ready_nodes.append((node, late_decider))
return ready_nodes
def browse_nodes_for_revert(self, node=None):
"""Browse next nodes to revert.
This returns a collection of nodes that *may* be ready to be be
reverted, if given a specific node it will only examine the
predecessors of that node, otherwise it will examine the whole
graph.
"""
if node is not None:
nodes = self._execution_graph.predecessors(node)
else:
nodes = self._execution_graph.nodes_iter()
ready_nodes = []
for node in nodes:
is_ready, late_decider = self._get_maybe_ready_for_revert(node)
if is_ready:
ready_nodes.append((node, late_decider))
return ready_nodes
def _get_maybe_ready(self, atom, transition_to, allowed_intentions,
connected_fetcher, connected_checker,
decider_fetcher):
state = self.get_state(atom)
ok_to_transition = self._runtime.check_atom_transition(atom, state,
transition_to)
if not ok_to_transition:
return (False, None)
intention = self._storage.get_atom_intention(atom.name)
if intention not in allowed_intentions:
return (False, None)
connected_states = self._storage.get_atoms_states(
connected_atom.name for connected_atom in connected_fetcher(atom))
ok_to_run = connected_checker(six.itervalues(connected_states))
if not ok_to_run:
return (False, None)
else:
return (True, decider_fetcher(atom))
def _get_maybe_ready_for_execute(self, atom):
"""Returns if an atom is *likely* ready to be executed."""
def decider_fetcher(atom):
edge_deciders = self._runtime.fetch_edge_deciders(atom)
if edge_deciders:
return IgnoreDecider(atom, edge_deciders)
else:
return NoOpDecider()
connected_checker = lambda connected_iter: \
all(state == st.SUCCESS and intention == st.EXECUTE
for state, intention in connected_iter)
connected_fetcher = self._execution_graph.predecessors_iter
return self._get_maybe_ready(atom, st.RUNNING, [st.EXECUTE],
connected_fetcher, connected_checker,
decider_fetcher)
def _get_maybe_ready_for_revert(self, atom):
"""Returns if an atom is *likely* ready to be reverted."""
connected_checker = lambda connected_iter: \
all(state in (st.PENDING, st.REVERTED)
for state, _intention in connected_iter)
decider_fetcher = lambda atom: NoOpDecider()
connected_fetcher = self._execution_graph.successors_iter
return self._get_maybe_ready(atom, st.REVERTING, [st.REVERT, st.RETRY],
connected_fetcher, connected_checker,
decider_fetcher)
def iterate_subgraph(self, atom):
"""Iterates a subgraph connected to given atom."""
for _src, dst in traversal.dfs_edges(self._execution_graph, atom):
yield dst
def iterate_retries(self, state=None):
"""Iterates retry atoms that match the provided state.
If no state is provided it will yield back all retry atoms.
"""
for atom in self._runtime.fetch_atoms_by_kind('retry'):
if not state or self.get_state(atom) == state:
yield atom
def iterate_all_nodes(self):
"""Yields back all nodes in the execution graph."""
for node in self._execution_graph.nodes_iter():
yield node
def find_atom_retry(self, atom):
"""Returns the retry atom associated to the given atom (or none)."""
return self._execution_graph.node[atom].get('retry')
def is_success(self):
"""Checks if all nodes in the execution graph are in 'happy' state."""
for atom in self.iterate_all_nodes():
atom_state = self.get_state(atom)
if atom_state == st.IGNORE:
continue
if atom_state != st.SUCCESS:
return False
return True
def get_state(self, atom):
"""Gets the state of a given atom (from the backend storage unit)."""
return self._storage.get_atom_state(atom.name)
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