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import copy
import datetime
import json
from typing import Any, Optional
from moto.core.common_models import BackendDict
from moto.stepfunctions.models import StateMachine, StepFunctionBackend
from moto.stepfunctions.parser.api import (
Definition,
EncryptionConfiguration,
ExecutionStatus,
GetExecutionHistoryOutput,
InvalidDefinition,
InvalidExecutionInput,
InvalidToken,
LoggingConfiguration,
MissingRequiredParameter,
Name,
ResourceNotFound,
SendTaskFailureOutput,
SendTaskHeartbeatOutput,
SendTaskSuccessOutput,
SensitiveCause,
SensitiveData,
SensitiveError,
TaskDoesNotExist,
TaskTimedOut,
TaskToken,
TraceHeader,
TracingConfiguration,
)
from moto.stepfunctions.parser.asl.component.state.exec.state_map.iteration.itemprocessor.map_run_record import (
MapRunRecord,
)
from moto.stepfunctions.parser.asl.eval.callback.callback import (
CallbackConsumerTimeout,
CallbackNotifyConsumerError,
CallbackOutcomeFailure,
CallbackOutcomeSuccess,
)
from moto.stepfunctions.parser.asl.parse.asl_parser import (
AmazonStateLanguageParser,
ASLParserException,
)
from moto.stepfunctions.parser.backend.execution import Execution
class StepFunctionsParserBackend(StepFunctionBackend):
def _get_executions(self, execution_status: Optional[ExecutionStatus] = None):
executions = []
for sm in self.state_machines:
for execution in sm.executions:
if execution_status is None or execution_status == execution.status:
executions.append(execution)
return executions
def _revision_by_name(self, name: str) -> Optional[StateMachine]:
for state_machine in self.state_machines:
if state_machine.name == name:
return state_machine
return None
@staticmethod
def _validate_definition(definition: str):
# Validate
# TODO: pass through static analyser.
try:
AmazonStateLanguageParser.parse(definition)
except ASLParserException as asl_parser_exception:
raise InvalidDefinition(message=repr(asl_parser_exception))
except Exception as exception:
exception_name = exception.__class__.__name__
exception_args = list(exception.args)
raise InvalidDefinition(
message=f"Error={exception_name} Args={exception_args} in definition '{definition}'."
)
def create_state_machine(
self,
name: str,
definition: str,
roleArn: str,
tags: Optional[list[dict[str, str]]] = None,
publish: Optional[bool] = None,
loggingConfiguration: Optional[LoggingConfiguration] = None,
tracingConfiguration: Optional[TracingConfiguration] = None,
encryptionConfiguration: Optional[EncryptionConfiguration] = None,
version_description: Optional[str] = None,
) -> StateMachine:
StepFunctionsParserBackend._validate_definition(definition=definition)
return super().create_state_machine(
name=name,
definition=definition,
roleArn=roleArn,
tags=tags,
publish=publish,
loggingConfiguration=loggingConfiguration,
tracingConfiguration=tracingConfiguration,
encryptionConfiguration=encryptionConfiguration,
version_description=version_description,
)
def send_task_heartbeat(self, task_token: TaskToken) -> SendTaskHeartbeatOutput:
running_executions = self._get_executions(ExecutionStatus.RUNNING)
for execution in running_executions:
try:
if execution.exec_worker.env.callback_pool_manager.heartbeat(
callback_id=task_token
):
return
except CallbackNotifyConsumerError as consumer_error:
if isinstance(consumer_error, CallbackConsumerTimeout):
raise TaskTimedOut()
else:
raise TaskDoesNotExist()
raise InvalidToken()
def send_task_success(
self, task_token: TaskToken, outcome: str
) -> SendTaskSuccessOutput:
outcome = CallbackOutcomeSuccess(callback_id=task_token, output=outcome)
running_executions = self._get_executions(ExecutionStatus.RUNNING)
for execution in running_executions:
try:
if execution.exec_worker.env.callback_pool_manager.notify(
callback_id=task_token, outcome=outcome
):
return
except CallbackNotifyConsumerError as consumer_error:
if isinstance(consumer_error, CallbackConsumerTimeout):
raise TaskTimedOut()
else:
raise TaskDoesNotExist()
raise InvalidToken()
def send_task_failure(
self,
task_token: TaskToken,
error: SensitiveError = None,
cause: SensitiveCause = None,
) -> SendTaskFailureOutput:
outcome = CallbackOutcomeFailure(
callback_id=task_token, error=error, cause=cause
)
for execution in self._get_executions():
try:
if execution.exec_worker.env.callback_pool_manager.notify(
callback_id=task_token, outcome=outcome
):
return SendTaskFailureOutput()
except CallbackNotifyConsumerError as consumer_error:
if isinstance(consumer_error, CallbackConsumerTimeout):
raise TaskTimedOut()
else:
raise TaskDoesNotExist()
raise InvalidToken()
def start_execution(
self,
state_machine_arn: str,
name: Name = None,
execution_input: SensitiveData = None,
trace_header: TraceHeader = None,
) -> Execution:
state_machine = self.describe_state_machine(state_machine_arn)
existing_execution = state_machine._handle_name_input_idempotency(
name, execution_input
)
if existing_execution is not None:
# If we found a match for the name and input, return the existing execution.
return existing_execution
# Update event change parameters about the state machine and should not affect those about this execution.
state_machine_clone = copy.deepcopy(state_machine)
if execution_input is None:
input_data = "{}"
else:
input_data = execution_input
try:
# Make sure input is valid json
json.loads(execution_input)
except Exception as ex:
raise InvalidExecutionInput(
str(ex)
) # TODO: report parsing error like AWS.
exec_name = name # TODO: validate name format
execution_arn = "arn:{}:states:{}:{}:execution:{}:{}"
execution_arn = execution_arn.format(
self.partition,
self.region_name,
self.account_id,
state_machine.name,
name,
)
execution = Execution(
name=exec_name,
sm_type=state_machine_clone.sm_type,
role_arn=state_machine_clone.roleArn,
exec_arn=execution_arn,
account_id=self.account_id,
region_name=self.region_name,
state_machine=state_machine_clone,
start_date=datetime.datetime.now(tz=datetime.timezone.utc),
cloud_watch_logging_session=None,
input_data=input_data,
trace_header=trace_header,
activity_store={},
)
state_machine.executions.append(execution)
execution.start()
return execution
def update_state_machine(
self,
arn: str,
definition: Definition = None,
role_arn: str = None,
logging_configuration: LoggingConfiguration = None,
tracing_configuration: TracingConfiguration = None,
encryption_configuration: EncryptionConfiguration = None,
publish: Optional[bool] = None,
version_description: str = None,
) -> StateMachine:
if not any(
[
definition,
role_arn,
logging_configuration,
tracing_configuration,
encryption_configuration,
]
):
raise MissingRequiredParameter(
"Either the definition, the role ARN, the LoggingConfiguration, the EncryptionConfiguration or the TracingConfiguration must be specified"
)
if definition is not None:
self._validate_definition(definition=definition)
return super().update_state_machine(
arn,
definition,
role_arn,
logging_configuration=logging_configuration,
tracing_configuration=tracing_configuration,
encryption_configuration=encryption_configuration,
publish=publish,
version_description=version_description,
)
def describe_map_run(self, map_run_arn: str) -> dict[str, Any]:
for execution in self._get_executions():
map_run_record: Optional[MapRunRecord] = (
execution.exec_worker.env.map_run_record_pool_manager.get(map_run_arn)
)
if map_run_record is not None:
return map_run_record.describe()
raise ResourceNotFound()
def list_map_runs(self, execution_arn: str) -> dict[str, Any]:
"""
Pagination is not yet implemented
"""
execution = self.describe_execution(execution_arn=execution_arn)
map_run_records: list[MapRunRecord] = (
execution.exec_worker.env.map_run_record_pool_manager.get_all()
)
return {
"mapRuns": [
map_run_record.list_item() for map_run_record in map_run_records
]
}
def update_map_run(
self,
map_run_arn: str,
max_concurrency: int,
tolerated_failure_count: str,
tolerated_failure_percentage: str,
) -> None:
# TODO: investigate behaviour of empty requests.
for execution in self._get_executions():
map_run_record = execution.exec_worker.env.map_run_record_pool_manager.get(
map_run_arn
)
if map_run_record is not None:
map_run_record.update(
max_concurrency=max_concurrency,
tolerated_failure_count=tolerated_failure_count,
tolerated_failure_percentage=tolerated_failure_percentage,
)
return
raise ResourceNotFound()
def get_execution_history(self, execution_arn: str) -> GetExecutionHistoryOutput:
execution = self.describe_execution(execution_arn=execution_arn)
return execution.to_history_output()
stepfunctions_parser_backends = BackendDict(StepFunctionsParserBackend, "stepfunctions")
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