# Copyright 2013-2015 ARM Limited
#
# 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.
#
# pylint: disable=E1101
import os
import logging
import inspect
from copy import copy
from collections import OrderedDict
from wlauto.core.bootstrap import settings
from wlauto.exceptions import ValidationError, ConfigError
from wlauto.utils.misc import isiterable, ensure_directory_exists as _d, get_article
from wlauto.utils.types import identifier, integer, boolean
[docs]class AttributeCollection(object):
"""
Accumulator for extension attribute objects (such as Parameters or Artifacts). This will
replace any class member list accumulating such attributes through the magic of
metaprogramming\ [*]_.
.. [*] which is totally safe and not going backfire in any way...
"""
@property
def values(self):
return self._attrs.values()
def __init__(self, attrcls, owner):
self._attrcls = attrcls
self._attrs = OrderedDict()
self.owner = owner
[docs] def add(self, p):
p = self._to_attrcls(p)
if p.name in self._attrs:
if p.override:
newp = copy(self._attrs[p.name])
for a, v in p.__dict__.iteritems():
if v is not None:
setattr(newp, a, v)
if not hasattr(newp, "_overridden"):
newp._overridden = self.owner # pylint: disable=protected-access
self._attrs[p.name] = newp
else:
# Duplicate attribute condition is check elsewhere.
pass
else:
self._attrs[p.name] = p
append = add
def __str__(self):
return 'AC({})'.format(map(str, self._attrs.values()))
__repr__ = __str__
def _to_attrcls(self, p):
if isinstance(p, basestring):
p = self._attrcls(p)
elif isinstance(p, tuple) or isinstance(p, list):
p = self._attrcls(*p)
elif isinstance(p, dict):
p = self._attrcls(**p)
elif not isinstance(p, self._attrcls):
raise ValueError('Invalid parameter value: {}'.format(p))
if (p.name in self._attrs and not p.override and
p.name != 'modules'): # TODO: HACK due to "diamond dependecy" in workloads...
raise ValueError('Attribute {} has already been defined.'.format(p.name))
return p
def __iadd__(self, other):
other = [self._to_attrcls(p) for p in other]
names = []
for p in other:
if p.name in names:
raise ValueError("Duplicate '{}' {}".format(p.name, p.__class__.__name__.split('.')[-1]))
names.append(p.name)
self.add(p)
return self
def __iter__(self):
return iter(self.values)
def __contains__(self, p):
return p in self._attrs
def __getitem__(self, i):
return self._attrs[i]
def __len__(self):
return len(self._attrs)
[docs]class AliasCollection(AttributeCollection):
def __init__(self):
super(AliasCollection, self).__init__(Alias, None)
def _to_attrcls(self, p):
if isinstance(p, tuple) or isinstance(p, list):
# must be in the form (name, {param: value, ...})
p = self._attrcls(p[1], **p[1])
elif not isinstance(p, self._attrcls):
raise ValueError('Invalid parameter value: {}'.format(p))
if p.name in self._attrs:
raise ValueError('Attribute {} has already been defined.'.format(p.name))
return p
[docs]class ListCollection(list):
def __init__(self, attrcls, owner): # pylint: disable=unused-argument
super(ListCollection, self).__init__()
self.owner = owner
[docs]class Param(object):
"""
This is a generic parameter for an extension. Extensions instantiate this to declare which parameters
are supported.
"""
# Mapping for kind conversion; see docs for convert_types below
kind_map = {
int: integer,
bool: boolean,
}
def __init__(self, name, kind=None, mandatory=None, default=None, override=False,
allowed_values=None, description=None, constraint=None, global_alias=None, convert_types=True):
"""
Create a new Parameter object.
:param name: The name of the parameter. This will become an instance member of the
extension object to which the parameter is applied, so it must be a valid
python identifier. This is the only mandatory parameter.
:param kind: The type of parameter this is. This must be a callable that takes an arbitrary
object and converts it to the expected type, or raised ``ValueError`` if such
conversion is not possible. Most Python standard types -- ``str``, ``int``, ``bool``, etc. --
can be used here. This defaults to ``str`` if not specified.
:param mandatory: If set to ``True``, then a non-``None`` value for this parameter *must* be
provided on extension object construction, otherwise ``ConfigError`` will be
raised.
:param default: The default value for this parameter. If no value is specified on extension
construction, this value will be used instead. (Note: if this is specified and
is not ``None``, then ``mandatory`` parameter will be ignored).
:param override: A ``bool`` that specifies whether a parameter of the same name further up the
hierarchy should be overridden. If this is ``False`` (the default), an exception
will be raised by the ``AttributeCollection`` instead.
:param allowed_values: This should be the complete list of allowed values for this parameter.
Note: ``None`` value will always be allowed, even if it is not in this list.
If you want to disallow ``None``, set ``mandatory`` to ``True``.
:param constraint: If specified, this must be a callable that takes the parameter value
as an argument and return a boolean indicating whether the constraint
has been satisfied. Alternatively, can be a two-tuple with said callable as
the first element and a string describing the constraint as the second.
:param global_alias: This is an alternative alias for this parameter, unlike the name, this
alias will not be namespaced under the owning extension's name (hence the
global part). This is introduced primarily for backward compatibility -- so
that old extension settings names still work. This should not be used for
new parameters.
:param convert_types: If ``True`` (the default), will automatically convert ``kind`` values from
native Python types to WA equivalents. This allows more ituitive interprestation
of parameter values, e.g. the string ``"false"`` being interpreted as ``False``
when specifed as the value for a boolean Parameter.
"""
self.name = identifier(name)
if kind is not None and not callable(kind):
raise ValueError('Kind must be callable.')
if convert_types and kind in self.kind_map:
kind = self.kind_map[kind]
self.kind = kind
self.mandatory = mandatory
self.default = default
self.override = override
self.allowed_values = allowed_values
self.description = description
if self.kind is None and not self.override:
self.kind = str
if constraint is not None and not callable(constraint) and not isinstance(constraint, tuple):
raise ValueError('Constraint must be callable or a (callable, str) tuple.')
self.constraint = constraint
self.global_alias = global_alias
[docs] def set_value(self, obj, value=None):
if value is None:
if self.default is not None:
value = self.default
elif self.mandatory:
msg = 'No values specified for mandatory parameter {} in {}'
raise ConfigError(msg.format(self.name, obj.name))
else:
try:
value = self.kind(value)
except (ValueError, TypeError):
typename = self.get_type_name()
msg = 'Bad value "{}" for {}; must be {} {}'
article = get_article(typename)
raise ConfigError(msg.format(value, self.name, article, typename))
current_value = getattr(obj, self.name, None)
if current_value is None:
setattr(obj, self.name, value)
elif not isiterable(current_value):
setattr(obj, self.name, value)
else:
new_value = current_value + [value]
setattr(obj, self.name, new_value)
if value is not None:
if self.allowed_values:
self._validate_allowed_values(obj, value)
if self.constraint:
self._validate_constraint(obj, value)
[docs] def get_type_name(self):
typename = str(self.kind)
if '\'' in typename:
typename = typename.split('\'')[1]
elif typename.startswith('<function'):
typename = typename.split()[1]
return typename
def _validate_allowed_values(self, obj, value):
if 'list' in str(self.kind):
for v in value:
if v not in self.allowed_values:
msg = 'Invalid value {} for {} in {}; must be in {}'
raise ConfigError(msg.format(v, self.name, obj.name, self.allowed_values))
else:
if value not in self.allowed_values:
msg = 'Invalid value {} for {} in {}; must be in {}'
raise ConfigError(msg.format(value, self.name, obj.name, self.allowed_values))
def _validate_constraint(self, obj, value):
msg_vals = {'value': value, 'param': self.name, 'extension': obj.name}
if isinstance(self.constraint, tuple) and len(self.constraint) == 2:
constraint, msg = self.constraint # pylint: disable=unpacking-non-sequence
elif callable(self.constraint):
constraint = self.constraint
msg = '"{value}" failed constraint validation for {param} in {extension}.'
else:
raise ValueError('Invalid constraint for {}: must be callable or a 2-tuple'.format(self.name))
if not constraint(value):
raise ConfigError(value, msg.format(**msg_vals))
def __repr__(self):
d = copy(self.__dict__)
del d['description']
return 'Param({})'.format(d)
__str__ = __repr__
Parameter = Param
[docs]class Artifact(object):
"""
This is an artifact generated during execution/post-processing of a workload.
Unlike metrics, this represents an actual artifact, such as a file, generated.
This may be "result", such as trace, or it could be "meta data" such as logs.
These are distinguished using the ``kind`` attribute, which also helps WA decide
how it should be handled. Currently supported kinds are:
:log: A log file. Not part of "results" as such but contains information about the
run/workload execution that be useful for diagnostics/meta analysis.
:meta: A file containing metadata. This is not part of "results", but contains
information that may be necessary to reproduce the results (contrast with
``log`` artifacts which are *not* necessary).
:data: This file contains new data, not available otherwise and should be considered
part of the "results" generated by WA. Most traces would fall into this category.
:export: Exported version of results or some other artifact. This signifies that
this artifact does not contain any new data that is not available
elsewhere and that it may be safely discarded without losing information.
:raw: Signifies that this is a raw dump/log that is normally processed to extract
useful information and is then discarded. In a sense, it is the opposite of
``export``, but in general may also be discarded.
.. note:: whether a file is marked as ``log``/``data`` or ``raw`` depends on
how important it is to preserve this file, e.g. when archiving, vs
how much space it takes up. Unlike ``export`` artifacts which are
(almost) always ignored by other exporters as that would never result
in data loss, ``raw`` files *may* be processed by exporters if they
decided that the risk of losing potentially (though unlikely) useful
data is greater than the time/space cost of handling the artifact (e.g.
a database uploader may choose to ignore ``raw`` artifacts, where as a
network filer archiver may choose to archive them).
.. note: The kind parameter is intended to represent the logical function of a particular
artifact, not its intended means of processing -- this is left entirely up to the
result processors.
"""
RUN = 'run'
ITERATION = 'iteration'
valid_kinds = ['log', 'meta', 'data', 'export', 'raw']
def __init__(self, name, path, kind, level=RUN, mandatory=False, description=None):
""""
:param name: Name that uniquely identifies this artifact.
:param path: The *relative* path of the artifact. Depending on the ``level``
must be either relative to the run or iteration output directory.
Note: this path *must* be delimited using ``/`` irrespective of the
operating system.
:param kind: The type of the artifact this is (e.g. log file, result, etc.) this
will be used a hit to result processors. This must be one of ``'log'``,
``'meta'``, ``'data'``, ``'export'``, ``'raw'``.
:param level: The level at which the artifact will be generated. Must be either
``'iteration'`` or ``'run'``.
:param mandatory: Boolean value indicating whether this artifact must be present
at the end of result processing for its level.
:param description: A free-form description of what this artifact is.
"""
if kind not in self.valid_kinds:
raise ValueError('Invalid Artifact kind: {}; must be in {}'.format(kind, self.valid_kinds))
self.name = name
self.path = path.replace('/', os.sep) if path is not None else path
self.kind = kind
self.level = level
self.mandatory = mandatory
self.description = description
[docs] def exists(self, context):
"""Returns ``True`` if artifact exists within the specified context, and
``False`` otherwise."""
fullpath = os.path.join(context.output_directory, self.path)
return os.path.exists(fullpath)
[docs] def to_dict(self):
return copy(self.__dict__)
[docs]class Alias(object):
"""
This represents a configuration alias for an extension, mapping an alternative name to
a set of parameter values, effectively providing an alternative set of default values.
"""
def __init__(self, name, **kwargs):
self.name = name
self.params = kwargs
self.extension_name = None # gets set by the MetaClass
[docs] def validate(self, ext):
ext_params = set(p.name for p in ext.parameters)
for param in self.params:
if param not in ext_params:
# Raising config error because aliases might have come through
# the config.
msg = 'Parameter {} (defined in alias {}) is invalid for {}'
raise ConfigError(msg.format(param, self.name, ext.name))
[docs]class Extension(object):
"""
Base class for all WA extensions. An extension is basically a plug-in.
It extends the functionality of WA in some way. Extensions are discovered
and loaded dynamically by the extension loader upon invocation of WA scripts.
Adding an extension is a matter of placing a class that implements an appropriate
interface somewhere it would be discovered by the loader. That "somewhere" is
typically one of the extension subdirectories under ``~/.workload_automation/``.
"""
__metaclass__ = ExtensionMeta
kind = None
name = None
parameters = [
Parameter('modules', kind=list,
description="""
Lists the modules to be loaded by this extension. A module is a plug-in that
further extends functionality of an extension.
"""),
]
artifacts = []
aliases = []
core_modules = []
[docs] @classmethod
def get_default_config(cls):
return {p.name: p.default for p in cls.parameters}
@property
def dependencies_directory(self):
return _d(os.path.join(settings.dependencies_directory, self.name))
@property
def _classname(self):
return self.__class__.__name__
def __init__(self, **kwargs):
self.__check_from_loader()
self.logger = logging.getLogger(self._classname)
self._modules = []
self.capabilities = getattr(self.__class__, 'capabilities', [])
for param in self.parameters:
param.set_value(self, kwargs.get(param.name))
for key in kwargs:
if key not in self.parameters:
message = 'Unexpected parameter "{}" for {}'
raise ConfigError(message.format(key, self.name))
[docs] def get_config(self):
"""
Returns current configuration (i.e. parameter values) of this extension.
"""
config = {}
for param in self.parameters:
config[param.name] = getattr(self, param.name, None)
return config
[docs] def validate(self):
"""
Perform basic validation to ensure that this extension is capable of running.
This is intended as an early check to ensure the extension has not been mis-configured,
rather than a comprehensive check (that may, e.g., require access to the execution
context).
This method may also be used to enforce (i.e. set as well as check) inter-parameter
constraints for the extension (e.g. if valid values for parameter A depend on the value
of parameter B -- something that is not possible to enfroce using ``Parameter``\ 's
``constraint`` attribute.
"""
if self.name is None:
raise ValidationError('Name not set for {}'.format(self._classname))
for param in self.parameters:
if param.mandatory and getattr(self, param.name, None) is None:
msg = 'No value specified for mandatory parameter {} in {}.'
raise ConfigError(msg.format(param.name, self.name))
[docs] def initialize(self, context):
pass
[docs] def finalize(self, context):
pass
[docs] def check_artifacts(self, context, level):
"""
Make sure that all mandatory artifacts have been generated.
"""
for artifact in self.artifacts:
if artifact.level != level or not artifact.mandatory:
continue
fullpath = os.path.join(context.output_directory, artifact.path)
if not os.path.exists(fullpath):
message = 'Mandatory "{}" has not been generated for {}.'
raise ValidationError(message.format(artifact.path, self.name))
def __getattr__(self, name):
if name == '_modules':
raise ValueError('_modules accessed too early!')
for module in self._modules:
if hasattr(module, name):
return getattr(module, name)
raise AttributeError(name)
[docs] def load_modules(self, loader):
"""
Load the modules specified by the "modules" Parameter using the provided loader. A loader
can be any object that has an atribute called "get_module" that implements the following
signature::
get_module(name, owner, **kwargs)
and returns an instance of :class:`wlauto.core.extension.Module`. If the module with the
specified name is not found, the loader must raise an appropriate exception.
"""
modules = list(reversed(self.core_modules)) + list(reversed(self.modules or []))
if not modules:
return
for module_spec in modules:
if not module_spec:
continue
module = self._load_module(loader, module_spec)
self._install_module(module)
[docs] def has(self, capability):
"""Check if this extension has the specified capability. The alternative method ``can`` is
identical to this. Which to use is up to the caller depending on what makes semantic sense
in the context of the capability, e.g. ``can('hard_reset')`` vs ``has('active_cooling')``."""
return capability in self.capabilities
can = has
def _load_module(self, loader, module_spec):
if isinstance(module_spec, basestring):
name = module_spec
params = {}
elif isinstance(module_spec, dict):
if len(module_spec) != 1:
message = 'Invalid module spec: {}; dict must have exctly one key -- the module name.'
raise ValueError(message.format(module_spec))
name, params = module_spec.items()[0]
else:
message = 'Invalid module spec: {}; must be a string or a one-key dict.'
raise ValueError(message.format(module_spec))
if not isinstance(params, dict):
message = 'Invalid module spec: {}; dict value must also be a dict.'
raise ValueError(message.format(module_spec))
module = loader.get_module(name, owner=self, **params)
module.initialize(None)
return module
def _install_module(self, module):
for capability in module.capabilities:
if capability not in self.capabilities:
self.capabilities.append(capability)
self._modules.append(module)
def __check_from_loader(self):
"""
There are a few things that need to happen in order to get a valide extension instance.
Not all of them are currently done through standard Python initialisation mechanisms
(specifically, the loading of modules and alias resolution). In order to avoid potential
problems with not fully loaded extensions, make sure that an extension is *only* instantiated
by the loader.
"""
stack = inspect.stack()
stack.pop(0) # current frame
frame = stack.pop(0)
# skip throuth the init call chain
while stack and frame[3] == '__init__':
frame = stack.pop(0)
if frame[3] != '_instantiate':
message = 'Attempting to instantiate {} directly (must be done through an ExtensionLoader)'
raise RuntimeError(message.format(self.__class__.__name__))
[docs]class Module(Extension):
"""
This is a "plugin" for an extension this is intended to capture functionality that may be optional
for an extension, and so may or may not be present in a particular setup; or, conversely, functionality
that may be reusable between multiple devices, even if they are not with the same inheritance hierarchy.
In other words, a Module is roughly equivalent to a kernel module and its primary purpose is to
implement WA "drivers" for various peripherals that may or may not be present in a particular setup.
.. note:: A mudule is itself an Extension and can therefore have its own modules.
"""
capabilities = []
@property
def root_owner(self):
owner = self.owner
while isinstance(owner, Module) and owner is not self:
owner = owner.owner
return owner
def __init__(self, owner, **kwargs):
super(Module, self).__init__(**kwargs)
self.owner = owner
while isinstance(owner, Module):
if owner.name == self.name:
raise ValueError('Circular module import for {}'.format(self.name))
[docs] def initialize(self, context):
pass