import warnings
from typing import Any, Optional, Union, Mapping
from .hashing import UniversalHashable
from .registration import Registered
from .variable import VariableContainer
from .variable import VariableContainerNamespace
from .variable import ReadOnlyVariableContainerNamespace
from .variable import VariableContainerMissingNamespace
from . import node
from . import missing_data
from . import events
class TaskInputError(ValueError):
pass
class Task(Registered, UniversalHashable, register=False):
"""Node in a task Graph with named inputs and outputs.
The universal hash of the task is equal to the universal
hash of the output. The universal hash of the output is
equal to the hash of the inputs and the task nonce.
A task is done when its output exists.
This is an abstract class. Instantiating a `Task` should be
done with `ewokscore.inittask.instantiate_task`.
"""
_INPUT_NAMES = set()
_OPTIONAL_INPUT_NAMES = set()
_OUTPUT_NAMES = set()
_N_REQUIRED_POSITIONAL_INPUTS = 0
def __init__(
self,
inputs: Optional[Mapping] = None,
varinfo: Optional[dict] = None,
node_id: Optional[node.NodeIdType] = None,
node_attrs: Optional[dict] = None,
execinfo: Optional[dict] = None,
):
"""The named arguments are inputs and Variable configuration"""
if inputs is None:
inputs = dict()
elif not isinstance(inputs, Mapping):
raise TypeError(inputs, type(inputs))
# Check required inputs
missing_required = set(self._INPUT_NAMES) - set(inputs.keys())
if missing_required:
raise TaskInputError(f"Missing inputs for {type(self)}: {missing_required}")
# Check required positional inputs
nrequiredargs = self._N_REQUIRED_POSITIONAL_INPUTS
for i in range(nrequiredargs):
if i not in inputs and str(i) not in inputs:
raise TaskInputError(
f"Missing inputs for {type(self)}: positional argument #{i}"
)
# Init missing optional inputs
missing_optional = set(self._OPTIONAL_INPUT_NAMES) - set(inputs.keys())
for varname in missing_optional:
inputs[varname] = self.MISSING_DATA
# Required outputs for the task to be "done"
ovars = {varname: self.MISSING_DATA for varname in self._OUTPUT_NAMES}
# Node/task info
node_id = node.get_node_id(node_id, node_attrs)
self.__node_id = node_id
self.__node_label = node.get_node_label(node_id, node_attrs)
task_id = self.class_registry_name()
task_id = node.get_task_identifier(node_attrs, task_id)
self.__task_id = task_id
if node_id and task_id:
self.__execinfo = execinfo
else:
self.__execinfo = None
# Misc
self.__exception = None
self.__succeeded = None
self._cancelled = False
# The output hash will update dynamically if any of the input
# variables change
varinfo = node.get_varinfo(node_attrs, varinfo)
self.__inputs = VariableContainer(value=inputs, varinfo=varinfo)
self.__outputs = VariableContainer(
value=ovars,
pre_uhash=self.__inputs,
instance_nonce=self.class_nonce(),
varinfo=varinfo,
)
self.__inputs_namespace = ReadOnlyVariableContainerNamespace(self.__inputs)
self.__outputs_namespace = VariableContainerNamespace(self.__outputs)
self.__missing_inputs_namespace = VariableContainerMissingNamespace(
self.__inputs
)
self.__missing_outputs_namespace = VariableContainerMissingNamespace(
self.__outputs
)
# The task class has the same hash as its output
super().__init__(pre_uhash=self.__outputs)
def __init_subclass__(
subclass,
input_names=tuple(),
optional_input_names=tuple(),
output_names=tuple(),
n_required_positional_inputs=0,
**kwargs,
):
super().__init_subclass__(**kwargs)
input_names = set(input_names)
optional_input_names = set(optional_input_names)
output_names = set(output_names)
reserved = subclass._reserved_variable_names()
forbidden = input_names & reserved
forbidden |= optional_input_names & reserved
forbidden |= output_names & reserved
if forbidden:
raise RuntimeError(
"The following names cannot be used a variable names: "
+ str(list(forbidden))
)
# Ensures that each subclass has their own sets:
subclass._INPUT_NAMES = subclass._INPUT_NAMES | set(input_names)
subclass._OPTIONAL_INPUT_NAMES = subclass._OPTIONAL_INPUT_NAMES | set(
optional_input_names
)
subclass._OUTPUT_NAMES = subclass._OUTPUT_NAMES | set(output_names)
subclass._N_REQUIRED_POSITIONAL_INPUTS = n_required_positional_inputs
@staticmethod
def _reserved_variable_names():
return VariableContainerNamespace._reserved_variable_names()
@classmethod
def instantiate(cls, registry_name: str, **kw):
r"""Factory method for instantiating a derived class.
:param str registry_name: for example "tasklib.tasks.MyTask" or "MyTask"
:param \**kw: `Task` constructor arguments
:returns Task:
"""
return cls.get_subclass(registry_name)(**kw)
@classmethod
def required_input_names(cls):
return cls._INPUT_NAMES
@classmethod
def optional_input_names(cls):
return cls._OPTIONAL_INPUT_NAMES
@classmethod
def input_names(cls):
return cls._INPUT_NAMES | cls._OPTIONAL_INPUT_NAMES
@classmethod
def output_names(cls):
return cls._OUTPUT_NAMES
@classmethod
def class_nonce_data(cls):
return super().class_nonce_data() + (
sorted(cls.input_names()),
sorted(cls.output_names()),
cls._N_REQUIRED_POSITIONAL_INPUTS,
)
@property
def input_variables(self):
if self.__inputs is None:
raise RuntimeError("references have been removed")
return self.__inputs
@property
def inputs(self):
return self.__inputs_namespace
@property
def missing_inputs(self):
return self.__missing_inputs_namespace
def get_input_value(self, key, default: Any = missing_data.MISSING_DATA):
if self.missing_inputs[key]:
return default
return self.inputs[key]
@property
def input_uhashes(self):
return self.get_input_uhashes()
def get_input_uhashes(self):
return self.__inputs.get_variable_uhashes()
@property
def input_values(self):
"""DEPRECATED"""
warnings.warn(
"the property 'input_values' is deprecated in favor of the function 'get_input_values'",
DeprecationWarning,
)
return self.get_input_values()
def get_input_values(self):
return self.__inputs.get_variable_values()
@property
def named_input_values(self):
"""DEPRECATED"""
warnings.warn(
"the property 'named_input_values' is deprecated in favor of the function 'get_named_input_values'",
DeprecationWarning,
)
return self.get_named_input_values()
def get_named_input_values(self):
return self.__inputs.get_named_variable_values()
@property
def positional_input_values(self):
"""DEPRECATED"""
warnings.warn(
"the property 'positional_input_values' is deprecated in favor of the function 'get_positional_input_values'",
DeprecationWarning,
)
return self.__inputs.get_positional_input_values()
def get_positional_input_values(self):
return self.__inputs.get_positional_variable_values()
@property
def npositional_inputs(self):
return self.__inputs.n_positional_variables
@property
def output_variables(self):
return self.__outputs
@property
def missing_outputs(self):
return self.__missing_outputs_namespace
@property
def outputs(self):
return self.__outputs_namespace
def get_output_value(self, key, default: Any = missing_data.MISSING_DATA):
if self.missing_outputs[key]:
return default
return self.outputs[key]
@property
def output_uhashes(self):
"""DEPRECATED"""
warnings.warn(
"the property 'output_uhashes' is deprecated in favor of the function 'get_output_uhashes'",
DeprecationWarning,
)
return self.get_output_uhashes()
def get_output_uhashes(self):
return self.__outputs.get_variable_uhashes()
@property
def output_values(self):
"""DEPRECATED"""
warnings.warn(
"the property 'output_values' is deprecated in favor of the function 'get_output_values'",
DeprecationWarning,
)
return self.get_output_values()
def get_output_values(self):
return self.__outputs.get_variable_values()
@property
def output_transfer_data(self):
"""DEPRECATED"""
warnings.warn(
"the property 'output_transfer_data' is deprecated in favor of the function 'get_output_transfer_data'",
DeprecationWarning,
)
return self.get_output_transfer_data()
def get_output_transfer_data(self):
"""The values are either `DataUri` or `Variable`"""
return self.__outputs.get_variable_transfer_data()
@property
def output_metadata(self) -> Union[dict, None]:
return self.__outputs.metadata
def _update_output_metadata(self):
metadata = self.output_metadata
if metadata is None:
return
if self.__node_label:
metadata.setdefault("title", self.__node_label)
@property
def done(self):
"""Completed (with or without exception)"""
return self.failed or self.succeeded
@property
def succeeded(self):
"""Completed without exception and with output values"""
if self._OUTPUT_NAMES:
return self.__outputs.has_value
else:
return self.__succeeded
@property
def failed(self):
"""Completed with exception"""
return self.__exception is not None
@property
def exception(self):
return self.__exception
def _get_repr_data(self):
data = super()._get_repr_data()
if self.__node_label:
data["label"] = repr(str(self.__node_label))
else:
data["label"] = None
@property
def label(self):
if self.__node_label:
return self.__node_label
else:
return str(self)
@property
def node_id(self):
return self.__node_id
@property
def job_id(self) -> Optional[str]:
if self.__execinfo:
return self.__execinfo.get("job_id")
@property
def workflow_id(self) -> Optional[str]:
if self.__execinfo:
return self.__execinfo.get("workflow_id")
def _iter_missing_input_values(self):
for iname in self._INPUT_NAMES:
var = self.__inputs.get(iname)
if var is None or not var.has_value:
yield iname
@property
def is_ready_to_execute(self):
try:
next(iter(self._iter_missing_input_values()))
except StopIteration:
return True
return False
@property
def cancelled(self) -> bool:
"""Return True if the task has been cancelled by the user"""
return self._cancelled
@cancelled.setter
def cancelled(self, cancelled: bool) -> None:
self._cancelled = cancelled
def assert_ready_to_execute(self):
lst = list(self._iter_missing_input_values())
if lst:
raise TaskInputError(
"The following inputs could not be loaded: " + str(lst)
)
def reset_state(self):
self._cancelled = False
self.__exception = None
self.__succeeded = None
self.__outputs.reset()
def execute(
self,
force_rerun: Optional[bool] = False,
raise_on_error: Optional[bool] = True,
cleanup_references: Optional[bool] = False,
):
with events.node_context(
self.__execinfo, node_id=self.__node_id, task_id=self.__task_id
) as execinfo:
self.__execinfo = execinfo
self.reset_state()
self._send_start_event()
try:
if force_rerun:
# Rerun a task which is already done
self.__outputs.force_non_existing()
if self.done:
return
self.assert_ready_to_execute()
self.run()
self._update_output_metadata()
self.__outputs.dump()
except Exception as e:
self.__exception = e
if raise_on_error:
raise RuntimeError(f"Task '{self.label}' failed") from e
else:
self.__succeeded = True
finally:
if cleanup_references:
self.cleanup_references()
self._send_send_event()
def _send_event(self, **kwargs):
"""Send an ewoks event"""
if self.__execinfo:
events.send_task_event(execinfo=self.__execinfo, **kwargs)
def _send_start_event(self):
input_uris = [
{"name": name, "value": str(uri) if uri else None}
for name, uri in self.__inputs.get_variable_uris().items()
]
output_uris = [
{"name": name, "value": str(uri) if uri else None}
for name, uri in self.__outputs.get_variable_uris().items()
]
task_uri = self.__outputs.data_uri
if task_uri:
task_uri = str(task_uri)
self._send_event(
event="start",
input_uris=input_uris,
output_uris=output_uris,
task_uri=task_uri,
)
def _send_send_event(self):
self._send_event(event="end", exception=self.exception)
def cleanup_references(self):
"""Removes all references to the inputs.
Side effect: fixes the uhash of the task and outputs
"""
self.__inputs = None
self.__inputs_namespace = None
self.__missing_inputs_namespace = None
self.__outputs.cleanup_references()
super().cleanup_references()
def run(self):
"""To be implemented by the derived classes"""
raise NotImplementedError
def cancel(self):
"""
Function called when a task is cancelled.
To be implemented by the derived classes
"""
raise NotImplementedError