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206 changes: 150 additions & 56 deletions src/aws_durable_execution_sdk_python/concurrency.py
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import threading
import time
from abc import ABC, abstractmethod
from collections import Counter
from concurrent.futures import Future, ThreadPoolExecutor
from dataclasses import dataclass
from enum import Enum
Expand Down Expand Up @@ -98,16 +99,69 @@ class BatchResult(Generic[R], BatchResultProtocol[R]): # noqa: PYI059
completion_reason: CompletionReason

@classmethod
def from_dict(cls, data: dict) -> BatchResult[R]:
def from_dict(
cls, data: dict, completion_config: CompletionConfig | None = None
) -> BatchResult[R]:
batch_items: list[BatchItem[R]] = [
BatchItem.from_dict(item) for item in data["all"]
]
# TODO: is this valid? assuming completion reason is ALL_COMPLETED?
completion_reason = CompletionReason(
data.get("completionReason", "ALL_COMPLETED")
)

completion_reason_value = data.get("completionReason")
if completion_reason_value is None:
# Infer completion reason from batch item statuses and completion config
# This aligns with the TypeScript implementation that uses completion config
# to accurately reconstruct the completion reason during replay
result = cls.from_items(batch_items, completion_config)
logger.warning(
"Missing completionReason in BatchResult deserialization, "
"inferred '%s' from batch item statuses. "
"This may indicate incomplete serialization data.",
result.completion_reason.value,
)
return result

completion_reason = CompletionReason(completion_reason_value)
return cls(batch_items, completion_reason)

@classmethod
def from_items(
cls,
items: list[BatchItem[R]],
completion_config: CompletionConfig | None = None,
):
"""
Infer completion reason based on batch item statuses and completion config.

This follows the same logic as the TypeScript implementation:
- If all items completed: ALL_COMPLETED
- If minSuccessful threshold met and not all completed: MIN_SUCCESSFUL_REACHED
- Otherwise: FAILURE_TOLERANCE_EXCEEDED
"""

statuses = (item.status for item in items)
counts = Counter(statuses)
succeeded_count = counts.get(BatchItemStatus.SUCCEEDED, 0)
failed_count = counts.get(BatchItemStatus.FAILED, 0)
started_count = counts.get(BatchItemStatus.STARTED, 0)

completed_count = succeeded_count + failed_count
total_count = started_count + completed_count

# If all items completed (no started items), it's ALL_COMPLETED
if completed_count == total_count:
completion_reason = CompletionReason.ALL_COMPLETED
elif ( # If we have completion config and minSuccessful threshold is met
completion_config
and (min_successful := completion_config.min_successful) is not None
and succeeded_count >= min_successful
):
completion_reason = CompletionReason.MIN_SUCCESSFUL_REACHED
else:
# Otherwise, assume failure tolerance was exceeded
completion_reason = CompletionReason.FAILURE_TOLERANCE_EXCEEDED

return cls(items, completion_reason)

def to_dict(self) -> dict:
return {
"all": [item.to_dict() for item in self.all],
Expand Down Expand Up @@ -163,19 +217,15 @@ def get_errors(self) -> list[ErrorObject]:

@property
def success_count(self) -> int:
return len(
[item for item in self.all if item.status is BatchItemStatus.SUCCEEDED]
)
return sum(1 for item in self.all if item.status is BatchItemStatus.SUCCEEDED)

@property
def failure_count(self) -> int:
return len([item for item in self.all if item.status is BatchItemStatus.FAILED])
return sum(1 for item in self.all if item.status is BatchItemStatus.FAILED)

@property
def started_count(self) -> int:
return len(
[item for item in self.all if item.status is BatchItemStatus.STARTED]
)
return sum(1 for item in self.all if item.status is BatchItemStatus.STARTED)

@property
def total_count(self) -> int:
Expand Down Expand Up @@ -336,25 +386,63 @@ def fail_task(self) -> None:
with self._lock:
self.failure_count += 1

def should_complete(self) -> bool:
"""Check if execution should complete."""
def should_continue(self) -> bool:
"""
Check if we should continue starting new tasks (based on failure tolerance).
Matches TypeScript shouldContinue() logic.
"""
with self._lock:
# Success condition
if self.success_count >= self.min_successful:
return True
# If no completion config, only continue if no failures
if (
self.tolerated_failure_count is None
and self.tolerated_failure_percentage is None
):
return self.failure_count == 0

# Failure conditions
if self._is_failure_condition_reached(
tolerated_count=self.tolerated_failure_count,
tolerated_percentage=self.tolerated_failure_percentage,
failure_count=self.failure_count,
# Check failure count tolerance
if (
self.tolerated_failure_count is not None
and self.failure_count > self.tolerated_failure_count
):
return True
return False

# Impossible to succeed condition
# TODO: should this keep running? TS doesn't currently handle this either.
remaining_tasks = self.total_tasks - self.success_count - self.failure_count
return self.success_count + remaining_tasks < self.min_successful
# Check failure percentage tolerance
if self.tolerated_failure_percentage is not None and self.total_tasks > 0:
failure_percentage = (self.failure_count / self.total_tasks) * 100
if failure_percentage > self.tolerated_failure_percentage:
return False

return True

def is_complete(self) -> bool:
"""
Check if execution should complete (based on completion criteria).
Matches TypeScript isComplete() logic.
"""
with self._lock:
completed_count = self.success_count + self.failure_count

# All tasks completed
if completed_count == self.total_tasks:
# Complete if no failure tolerance OR no failures OR min successful reached
return (
(
self.tolerated_failure_count is None
and self.tolerated_failure_percentage is None
)
or self.failure_count == 0
or self.success_count >= self.min_successful
)

# when we breach min successful, we've completed
return self.success_count >= self.min_successful

def should_complete(self) -> bool:
"""
Check if execution should complete.
Combines TypeScript shouldContinue() and isComplete() logic.
"""
return self.is_complete() or not self.should_continue()

def is_all_completed(self) -> bool:
"""True if all tasks completed successfully."""
Expand Down Expand Up @@ -640,40 +728,46 @@ def _on_task_complete(
self._completion_event.set()

def _create_result(self) -> BatchResult[ResultType]:
"""Build the final BatchResult."""
batch_items: list[BatchItem[ResultType]] = []
completed_branches: list[ExecutableWithState] = []
failed_branches: list[ExecutableWithState] = []
"""
Build the final BatchResult.

When this function executes, we've terminated the upper/parent context for whatever reason.
It follows that our items can be only in 3 states, Completed, Failed and Started (in all of the possible forms).
We tag each branch based on its observed value at the time of completion of the parent / upper context, and pass the
results to BatchResult.

Any inference wrt completion reason is left up to BatchResult, keeping the logic inference isolated.
"""
batch_items: list[BatchItem[ResultType]] = []
for executable in self.executables_with_state:
if executable.status is BranchStatus.COMPLETED:
completed_branches.append(executable)
batch_items.append(
BatchItem(
executable.index, BatchItemStatus.SUCCEEDED, executable.result
match executable.status:
case BranchStatus.COMPLETED:
batch_items.append(
BatchItem(
executable.index,
BatchItemStatus.SUCCEEDED,
executable.result,
)
)
)
elif executable.status is BranchStatus.FAILED:
failed_branches.append(executable)
batch_items.append(
BatchItem(
executable.index,
BatchItemStatus.FAILED,
error=ErrorObject.from_exception(executable.error),
case BranchStatus.FAILED:
batch_items.append(
BatchItem(
executable.index,
BatchItemStatus.FAILED,
error=ErrorObject.from_exception(executable.error),
)
)
case (
BranchStatus.PENDING
| BranchStatus.RUNNING
| BranchStatus.SUSPENDED
| BranchStatus.SUSPENDED_WITH_TIMEOUT
):
batch_items.append(
BatchItem(executable.index, BatchItemStatus.STARTED)
)
)

completion_reason: CompletionReason = (
CompletionReason.ALL_COMPLETED
if self.counters.is_all_completed()
else (
CompletionReason.MIN_SUCCESSFUL_REACHED
if self.counters.is_min_successful_reached()
else CompletionReason.FAILURE_TOLERANCE_EXCEEDED
)
)

return BatchResult(batch_items, completion_reason)
return BatchResult.from_items(batch_items, self.completion_config)

def _execute_item_in_child_context(
self,
Expand Down
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