Files
deb-python-taskflow/taskflow/atom.py
Joshua Harlow 14431bc076 Add and use a new simple helper logging module
Add a new logging BLATHER level to easily allow its
usage for messages that are below the normal DEBUG level
such as compilation information and scope lookup info
which can be very verbose in logs if always enabled.

Change-Id: I828211403bd02bfd6777b10cdcfe58fb0637a52c
2014-12-08 22:09:13 -08:00

200 lines
8.5 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (C) 2013 Rackspace Hosting Inc. All Rights Reserved.
# 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 six
from taskflow import exceptions
from taskflow.utils import misc
from taskflow.utils import reflection
def _save_as_to_mapping(save_as):
"""Convert save_as to mapping name => index.
Result should follow storage convention for mappings.
"""
# TODO(harlowja): we should probably document this behavior & convention
# outside of code so that it's more easily understandable, since what an
# atom returns is pretty crucial for other later operations.
if save_as is None:
return {}
if isinstance(save_as, six.string_types):
# NOTE(harlowja): this means that your atom will only return one item
# instead of a dictionary-like object or a indexable object (like a
# list or tuple).
return {save_as: None}
elif isinstance(save_as, (tuple, list)):
# NOTE(harlowja): this means that your atom will return a indexable
# object, like a list or tuple and the results can be mapped by index
# to that tuple/list that is returned for others to use.
return dict((key, num) for num, key in enumerate(save_as))
elif isinstance(save_as, set):
# NOTE(harlowja): in the case where a set is given we will not be
# able to determine the numeric ordering in a reliable way (since it is
# a unordered set) so the only way for us to easily map the result of
# the atom will be via the key itself.
return dict((key, key) for key in save_as)
raise TypeError('Atom provides parameter '
'should be str, set or tuple/list, not %r' % save_as)
def _build_rebind_dict(args, rebind_args):
"""Build a argument remapping/rebinding dictionary.
This dictionary allows an atom to declare that it will take a needed
requirement bound to a given name with another name instead (mapping the
new name onto the required name).
"""
if rebind_args is None:
return {}
elif isinstance(rebind_args, (list, tuple)):
rebind = dict(zip(args, rebind_args))
if len(args) < len(rebind_args):
rebind.update((a, a) for a in rebind_args[len(args):])
return rebind
elif isinstance(rebind_args, dict):
return rebind_args
else:
raise TypeError('Invalid rebind value: %s' % rebind_args)
def _build_arg_mapping(atom_name, reqs, rebind_args, function, do_infer,
ignore_list=None):
"""Builds an input argument mapping for a given function.
Given a function, its requirements and a rebind mapping this helper
function will build the correct argument mapping for the given function as
well as verify that the final argument mapping does not have missing or
extra arguments (where applicable).
"""
atom_args = reflection.get_callable_args(function, required_only=True)
if ignore_list:
for arg in ignore_list:
if arg in atom_args:
atom_args.remove(arg)
result = {}
if reqs:
result.update((a, a) for a in reqs)
if do_infer:
result.update((a, a) for a in atom_args)
result.update(_build_rebind_dict(atom_args, rebind_args))
if not reflection.accepts_kwargs(function):
all_args = reflection.get_callable_args(function, required_only=False)
extra_args = set(result) - set(all_args)
if extra_args:
extra_args_str = ', '.join(sorted(extra_args))
raise ValueError('Extra arguments given to atom %s: %s'
% (atom_name, extra_args_str))
# NOTE(imelnikov): don't use set to preserve order in error message
missing_args = [arg for arg in atom_args if arg not in result]
if missing_args:
raise ValueError('Missing arguments for atom %s: %s'
% (atom_name, ' ,'.join(missing_args)))
return result
class Atom(object):
"""An abstract flow atom that causes a flow to progress (in some manner).
An atom is a named object that operates with input flow data to perform
some action that furthers the overall flows progress. It usually also
produces some of its own named output as a result of this process.
:ivar version: An *immutable* version that associates version information
with this atom. It can be useful in resuming older versions
of atoms. Standard major, minor versioning concepts
should apply.
:ivar save_as: An *immutable* output ``resource`` name dictionary this atom
produces that other atoms may depend on this atom providing.
The format is output index (or key when a dictionary
is returned from the execute method) to stored argument
name.
:ivar rebind: An *immutable* input ``resource`` mapping dictionary that
can be used to alter the inputs given to this atom. It is
typically used for mapping a prior atoms output into
the names that this atom expects (in a way this is like
remapping a namespace of another atom into the namespace
of this atom).
:param name: Meaningful name for this atom, should be something that is
distinguishable and understandable for notification,
debugging, storing and any other similar purposes.
:param provides: A set, string or list of items that
this will be providing (or could provide) to others, used
to correlate and associate the thing/s this atom
produces, if it produces anything at all.
:param inject: An *immutable* input_name => value dictionary which
specifies any initial inputs that should be automatically
injected into the atoms scope before the atom execution
commences (this allows for providing atom *local* values that
do not need to be provided by other atoms/dependents).
:ivar inject: See parameter ``inject``.
"""
def __init__(self, name=None, provides=None, inject=None):
self._name = name
self.save_as = _save_as_to_mapping(provides)
self.version = (1, 0)
self.inject = inject
def _build_arg_mapping(self, executor, requires=None, rebind=None,
auto_extract=True, ignore_list=None):
self.rebind = _build_arg_mapping(self.name, requires, rebind,
executor, auto_extract, ignore_list)
out_of_order = self.provides.intersection(self.requires)
if out_of_order:
raise exceptions.DependencyFailure(
"Atom %(item)s provides %(oo)s that are required "
"by this atom"
% dict(item=self.name, oo=sorted(out_of_order)))
@property
def name(self):
"""A non-unique name for this atom (human readable)."""
return self._name
def __str__(self):
return "%s==%s" % (self.name, misc.get_version_string(self))
def __repr__(self):
return '<%s %s>' % (reflection.get_class_name(self), self)
@property
def provides(self):
"""Any outputs this atom produces.
NOTE(harlowja): there can be no intersection between what this atom
requires and what it produces (since this would be an impossible
dependency to satisfy).
"""
return set(self.save_as)
@property
def requires(self):
"""Any inputs this atom requires to function (if applicable).
NOTE(harlowja): there can be no intersection between what this atom
requires and what it produces (since this would be an impossible
dependency to satisfy).
"""
requires = set(self.rebind.values())
if self.inject:
requires = requires - set(six.iterkeys(self.inject))
return requires