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hkuds--lightrag/lightrag/kg/shared_storage.py
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2026-07-13 12:08:54 +08:00

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import os
import sys
import asyncio
import multiprocessing as mp
import uuid
from multiprocessing.synchronize import Lock as ProcessLock
from multiprocessing import Manager
import time
import logging
from contextvars import ContextVar
from typing import Any, Dict, List, Mapping, Optional, Union, TypeVar, Generic
from lightrag.constants import (
DEFAULT_GLOBAL_SLOT_HEARTBEAT_TTL,
DEFAULT_GLOBAL_SLOT_SUSPECT_GRACE,
DEFAULT_GLOBAL_SLOT_WAITER_STALE_TTL,
DEFAULT_QUEUE_STATS_STALE_TTL,
)
from lightrag.exceptions import PipelineNotInitializedError
DEBUG_LOCKS = False
# Define a direct print function for critical logs that must be visible in all processes
def direct_log(message, enable_output: bool = True, level: str = "DEBUG"):
"""
Log a message directly to stderr to ensure visibility in all processes,
including the Gunicorn master process.
Args:
message: The message to log
level: Log level for message (control the visibility of the message by comparing with the current logger level)
enable_output: Enable or disable log message (Force to turn off the message,)
"""
if not enable_output:
return
# Get the current logger level from the lightrag logger
try:
from lightrag.utils import logger
current_level = logger.getEffectiveLevel()
except ImportError:
# Fallback if lightrag.utils is not available
current_level = 20 # INFO
# Convert string level to numeric level for comparison
level_mapping = {
"DEBUG": 10, # DEBUG
"INFO": 20, # INFO
"WARNING": 30, # WARNING
"ERROR": 40, # ERROR
"CRITICAL": 50, # CRITICAL
}
message_level = level_mapping.get(level.upper(), logging.DEBUG)
if message_level >= current_level:
print(f"{level}: {message}", file=sys.stderr, flush=True)
T = TypeVar("T")
LockType = Union[ProcessLock, asyncio.Lock]
_is_multiprocess = None
_workers = None
_manager = None
# Global singleton data for multi-process keyed locks
_lock_registry: Optional[Dict[str, mp.synchronize.Lock]] = None
_lock_registry_count: Optional[Dict[str, int]] = None
_lock_cleanup_data: Optional[Dict[str, time.time]] = None
_registry_guard = None
# Timeout for keyed locks in seconds (Default 300)
CLEANUP_KEYED_LOCKS_AFTER_SECONDS = 300
# Cleanup pending list threshold for triggering cleanup (Default 500)
CLEANUP_THRESHOLD = 500
# Minimum interval between cleanup operations in seconds (Default 30)
MIN_CLEANUP_INTERVAL_SECONDS = 30
# Track the earliest cleanup time for efficient cleanup triggering (multiprocess locks only)
_earliest_mp_cleanup_time: Optional[float] = None
# Track the last cleanup time to enforce minimum interval (multiprocess locks only)
_last_mp_cleanup_time: Optional[float] = None
_initialized = None
# Default workspace for backward compatibility
_default_workspace: Optional[str] = None
# shared data for storage across processes
_shared_dicts: Optional[Dict[str, Any]] = None
_init_flags: Optional[Dict[str, bool]] = None # namespace -> initialized
_update_flags: Optional[Dict[str, bool]] = None # namespace -> updated
# locks for mutex access
_internal_lock: Optional[LockType] = None
_data_init_lock: Optional[LockType] = None
# Manager for all keyed locks
_storage_keyed_lock: Optional["KeyedUnifiedLock"] = None
# async locks for coroutine synchronization in multiprocess mode
_async_locks: Optional[Dict[str, asyncio.Lock]] = None
_debug_n_locks_acquired: int = 0
# --- Cross-worker global concurrency gate + queue stats aggregation ---
#
# Read-only configuration set once by the FIRST initialize_share_data() call
# (the gunicorn master, before fork — workers inherit it as a module global).
# Later no-arg calls (e.g. LightRAG.__post_init__) hit the `_initialized`
# guard and never overwrite it.
_global_concurrency_limits: Optional[Dict[str, int]] = None
# Separator between the queue name and the per-pid suffix in queue-stats
# namespace keys. \x1f (ASCII unit separator) cannot appear in queue names.
# (Concurrency gate state needs no separator: one key per group.)
KEY_SEP = "\x1f"
_CONCURRENCY_LEASE_NAMESPACE = "concurrency_leases"
_QUEUE_STATS_NAMESPACE = "queue_stats"
# Heartbeat / staleness parameters (module-level so tests can monkeypatch).
_heartbeat_ttl: float = DEFAULT_GLOBAL_SLOT_HEARTBEAT_TTL
_suspect_grace: float = DEFAULT_GLOBAL_SLOT_SUSPECT_GRACE
_queue_stats_stale_ttl: float = DEFAULT_QUEUE_STATS_STALE_TTL
_waiter_stale_ttl: float = DEFAULT_GLOBAL_SLOT_WAITER_STALE_TTL
# Per-process cached namespace references (avoid the internal lock on every
# publish). Reset by initialize_share_data()/finalize_share_data().
_lease_ns_cache: Optional[Dict[str, Any]] = None
_queue_stats_ns_cache: Optional[Dict[str, Any]] = None
# Rate limiting for acquire-failure warnings (fail-closed path).
_ACQUIRE_FAILURE_LOG_INTERVAL = 30.0
_last_acquire_failure_log: float = 0.0
def get_final_namespace(namespace: str, workspace: str | None = None):
global _default_workspace
if workspace is None:
workspace = _default_workspace
if workspace is None:
direct_log(
f"Error: Invoke namespace operation without workspace, pid={os.getpid()}",
level="ERROR",
)
raise ValueError("Invoke namespace operation without workspace")
final_namespace = f"{workspace}:{namespace}" if workspace else f"{namespace}"
return final_namespace
def inc_debug_n_locks_acquired():
global _debug_n_locks_acquired
if DEBUG_LOCKS:
_debug_n_locks_acquired += 1
print(f"DEBUG: Keyed Lock acquired, total: {_debug_n_locks_acquired:>5}")
def dec_debug_n_locks_acquired():
global _debug_n_locks_acquired
if DEBUG_LOCKS:
if _debug_n_locks_acquired > 0:
_debug_n_locks_acquired -= 1
print(f"DEBUG: Keyed Lock released, total: {_debug_n_locks_acquired:>5}")
else:
raise RuntimeError("Attempting to release lock when no locks are acquired")
def get_debug_n_locks_acquired():
global _debug_n_locks_acquired
return _debug_n_locks_acquired
class UnifiedLock(Generic[T]):
"""Provide a unified lock interface type for asyncio.Lock and multiprocessing.Lock"""
def __init__(
self,
lock: Union[ProcessLock, asyncio.Lock],
is_async: bool,
name: str = "unnamed",
enable_logging: bool = True,
async_lock: Optional[asyncio.Lock] = None,
):
self._lock = lock
self._is_async = is_async
self._pid = os.getpid() # for debug only
self._name = name # for debug only
self._enable_logging = enable_logging # for debug only
self._async_lock = async_lock # auxiliary lock for coroutine synchronization
async def _acquire_mp_lock_in_executor(self) -> None:
"""Acquire the multiprocess lock without blocking the event loop.
Cancellation safety: if this coroutine is cancelled while the
executor thread is still blocked inside ``acquire()``, the thread
cannot be interrupted and WILL take the lock eventually — with no
owner left to release it, every process would deadlock. The shield +
done-callback below returns such an orphaned acquisition immediately.
"""
loop = asyncio.get_running_loop()
acquire_future = loop.run_in_executor(None, self._lock.acquire)
try:
await asyncio.shield(acquire_future)
except asyncio.CancelledError:
def _release_orphaned_acquire(f) -> None:
if f.cancelled() or f.exception() is not None:
return
try:
self._lock.release()
except Exception:
pass
acquire_future.add_done_callback(_release_orphaned_acquire)
raise
async def __aenter__(self) -> "UnifiedLock[T]":
async_gate_acquired = False
try:
# If in multiprocess mode and async lock exists, acquire it first
if not self._is_async and self._async_lock is not None:
await self._async_lock.acquire()
async_gate_acquired = True
direct_log(
f"== Lock == Process {self._pid}: Acquired async lock '{self._name}",
level="DEBUG",
enable_output=self._enable_logging,
)
# Acquire the main lock
# Note: self._lock should never be None here as the check has been moved
# to get_internal_lock() and get_data_init_lock() functions
if self._is_async:
await self._lock.acquire()
else:
# A Manager lock proxy blocks the calling thread until every
# other PROCESS ahead of us releases — unbounded. Offload to
# the default executor so this process's event loop keeps
# serving while we wait (the async gate above already
# serializes this process's coroutines, so at most one
# executor thread per lock key is ever parked here).
await self._acquire_mp_lock_in_executor()
direct_log(
f"== Lock == Process {self._pid}: Acquired lock {self._name} (async={self._is_async})",
level="INFO",
enable_output=self._enable_logging,
)
return self
except asyncio.CancelledError:
# Cancellation can arrive while awaiting the executor-offloaded
# mp acquire (any orphaned acquisition is returned inside
# _acquire_mp_lock_in_executor). Roll back the per-process gate
# we already hold so this process's other coroutines never
# deadlock on it.
if async_gate_acquired:
self._async_lock.release()
direct_log(
f"== Lock == Process {self._pid}: Lock acquisition cancelled '{self._name}'",
level="WARNING",
enable_output=self._enable_logging,
)
raise
except Exception as e:
# If main lock acquisition fails, release the async lock if it was acquired
if async_gate_acquired:
self._async_lock.release()
direct_log(
f"== Lock == Process {self._pid}: Failed to acquire lock '{self._name}': {e}",
level="ERROR",
enable_output=True,
)
raise
async def __aexit__(self, exc_type, exc_val, exc_tb):
main_lock_released = False
async_lock_released = False
try:
# Release main lock first
if self._lock is not None:
if self._is_async:
self._lock.release()
else:
self._lock.release()
direct_log(
f"== Lock == Process {self._pid}: Released lock {self._name} (async={self._is_async})",
level="INFO",
enable_output=self._enable_logging,
)
main_lock_released = True
# Then release async lock if in multiprocess mode
if not self._is_async and self._async_lock is not None:
self._async_lock.release()
direct_log(
f"== Lock == Process {self._pid}: Released async lock {self._name}",
level="DEBUG",
enable_output=self._enable_logging,
)
async_lock_released = True
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to release lock '{self._name}': {e}",
level="ERROR",
enable_output=True,
)
# If main lock release failed but async lock hasn't been attempted yet, try to release it
if (
not main_lock_released
and not async_lock_released
and not self._is_async
and self._async_lock is not None
):
try:
direct_log(
f"== Lock == Process {self._pid}: Attempting to release async lock after main lock failure",
level="DEBUG",
enable_output=self._enable_logging,
)
self._async_lock.release()
direct_log(
f"== Lock == Process {self._pid}: Successfully released async lock after main lock failure",
level="INFO",
enable_output=self._enable_logging,
)
except Exception as inner_e:
direct_log(
f"== Lock == Process {self._pid}: Failed to release async lock after main lock failure: {inner_e}",
level="ERROR",
enable_output=True,
)
raise
def __enter__(self) -> "UnifiedLock[T]":
"""For backward compatibility"""
try:
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
# Acquire the main lock
# Note: self._lock should never be None here as the check has been moved
# to get_internal_lock() and get_data_init_lock() functions
direct_log(
f"== Lock == Process {self._pid}: Acquiring lock {self._name} (sync)",
level="DEBUG",
enable_output=self._enable_logging,
)
self._lock.acquire()
direct_log(
f"== Lock == Process {self._pid}: Acquired lock {self._name} (sync)",
level="INFO",
enable_output=self._enable_logging,
)
return self
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to acquire lock '{self._name}' (sync): {e}",
level="ERROR",
enable_output=True,
)
raise
def __exit__(self, exc_type, exc_val, exc_tb):
"""For backward compatibility"""
try:
if self._is_async:
raise RuntimeError("Use 'async with' for shared_storage lock")
direct_log(
f"== Lock == Process {self._pid}: Releasing lock '{self._name}' (sync)",
level="DEBUG",
enable_output=self._enable_logging,
)
self._lock.release()
direct_log(
f"== Lock == Process {self._pid}: Released lock {self._name} (sync)",
level="INFO",
enable_output=self._enable_logging,
)
except Exception as e:
direct_log(
f"== Lock == Process {self._pid}: Failed to release lock '{self._name}' (sync): {e}",
level="ERROR",
enable_output=True,
)
raise
def locked(self) -> bool:
if self._is_async:
return self._lock.locked()
else:
return self._lock.locked()
def _get_combined_key(factory_name: str, key: str) -> str:
"""Return the combined key for the factory and key."""
return f"{factory_name}:{key}"
def _perform_lock_cleanup(
lock_type: str,
cleanup_data: Dict[str, float],
lock_registry: Optional[Dict[str, Any]],
lock_count: Optional[Dict[str, int]],
earliest_cleanup_time: Optional[float],
last_cleanup_time: Optional[float],
current_time: float,
threshold_check: bool = True,
) -> tuple[int, Optional[float], Optional[float]]:
"""
Generic lock cleanup function to unify cleanup logic for both multiprocess and async locks.
Args:
lock_type: Lock type identifier ("mp" or "async")
cleanup_data: Cleanup data dictionary
lock_registry: Lock registry dictionary (can be None for async locks)
lock_count: Lock count dictionary (can be None for async locks)
earliest_cleanup_time: Earliest cleanup time
last_cleanup_time: Last cleanup time
current_time: Current time
threshold_check: Whether to check threshold condition (default True, set to False in cleanup_expired_locks)
Returns:
tuple: (cleaned_count, new_earliest_time, new_last_cleanup_time)
"""
if len(cleanup_data) == 0:
return 0, earliest_cleanup_time, last_cleanup_time
# If threshold check is needed and threshold not reached, return directly
if threshold_check and len(cleanup_data) < CLEANUP_THRESHOLD:
return 0, earliest_cleanup_time, last_cleanup_time
# Time rollback detection
if last_cleanup_time is not None and current_time < last_cleanup_time:
direct_log(
f"== {lock_type} Lock == Time rollback detected, resetting cleanup time",
level="WARNING",
enable_output=False,
)
last_cleanup_time = None
# Check cleanup conditions
has_expired_locks = (
earliest_cleanup_time is not None
and current_time - earliest_cleanup_time > CLEANUP_KEYED_LOCKS_AFTER_SECONDS
)
interval_satisfied = (
last_cleanup_time is None
or current_time - last_cleanup_time > MIN_CLEANUP_INTERVAL_SECONDS
)
if not (has_expired_locks and interval_satisfied):
return 0, earliest_cleanup_time, last_cleanup_time
try:
cleaned_count = 0
new_earliest_time = None
# Calculate total count before cleanup
total_cleanup_len = len(cleanup_data)
# Perform cleanup operation
for cleanup_key, cleanup_time in list(cleanup_data.items()):
if current_time - cleanup_time > CLEANUP_KEYED_LOCKS_AFTER_SECONDS:
# Remove from cleanup data
cleanup_data.pop(cleanup_key, None)
# Remove from lock registry if exists
if lock_registry is not None:
lock_registry.pop(cleanup_key, None)
if lock_count is not None:
lock_count.pop(cleanup_key, None)
cleaned_count += 1
else:
# Track the earliest time among remaining locks
if new_earliest_time is None or cleanup_time < new_earliest_time:
new_earliest_time = cleanup_time
# Update state only after successful cleanup
if cleaned_count > 0:
new_last_cleanup_time = current_time
# Log cleanup results
next_cleanup_in = max(
(new_earliest_time + CLEANUP_KEYED_LOCKS_AFTER_SECONDS - current_time)
if new_earliest_time
else float("inf"),
MIN_CLEANUP_INTERVAL_SECONDS,
)
if lock_type == "async":
direct_log(
f"== {lock_type} Lock == Cleaned up {cleaned_count}/{total_cleanup_len} expired {lock_type} locks, "
f"next cleanup in {next_cleanup_in:.1f}s",
enable_output=False,
level="INFO",
)
else:
direct_log(
f"== {lock_type} Lock == Cleaned up {cleaned_count}/{total_cleanup_len} expired locks, "
f"next cleanup in {next_cleanup_in:.1f}s",
enable_output=False,
level="INFO",
)
return cleaned_count, new_earliest_time, new_last_cleanup_time
else:
return 0, earliest_cleanup_time, last_cleanup_time
except Exception as e:
direct_log(
f"== {lock_type} Lock == Cleanup failed: {e}",
level="ERROR",
enable_output=True,
)
return 0, earliest_cleanup_time, last_cleanup_time
def _get_or_create_shared_raw_mp_lock(
factory_name: str, key: str
) -> Optional[mp.synchronize.Lock]:
"""Return the *singleton* manager.Lock() proxy for keyed lock, creating if needed."""
if not _is_multiprocess:
return None
with _registry_guard:
combined_key = _get_combined_key(factory_name, key)
raw = _lock_registry.get(combined_key)
count = _lock_registry_count.get(combined_key)
if raw is None:
raw = _manager.Lock()
_lock_registry[combined_key] = raw
count = 0
else:
if count is None:
raise RuntimeError(
f"Shared-Data lock registry for {factory_name} is corrupted for key {key}"
)
if (
count == 0 and combined_key in _lock_cleanup_data
): # Reusing an key waiting for cleanup, remove it from cleanup list
_lock_cleanup_data.pop(combined_key)
count += 1
_lock_registry_count[combined_key] = count
return raw
def _release_shared_raw_mp_lock(factory_name: str, key: str):
"""Release the *singleton* manager.Lock() proxy for *key*."""
if not _is_multiprocess:
return
global _earliest_mp_cleanup_time, _last_mp_cleanup_time
with _registry_guard:
combined_key = _get_combined_key(factory_name, key)
raw = _lock_registry.get(combined_key)
count = _lock_registry_count.get(combined_key)
if raw is None and count is None:
return
elif raw is None or count is None:
raise RuntimeError(
f"Shared-Data lock registry for {factory_name} is corrupted for key {key}"
)
count -= 1
if count < 0:
raise RuntimeError(
f"Attempting to release lock for {key} more times than it was acquired"
)
_lock_registry_count[combined_key] = count
current_time = time.time()
if count == 0:
_lock_cleanup_data[combined_key] = current_time
# Update earliest multiprocess cleanup time (only when earlier)
if (
_earliest_mp_cleanup_time is None
or current_time < _earliest_mp_cleanup_time
):
_earliest_mp_cleanup_time = current_time
# Use generic cleanup function
cleaned_count, new_earliest_time, new_last_cleanup_time = _perform_lock_cleanup(
lock_type="mp",
cleanup_data=_lock_cleanup_data,
lock_registry=_lock_registry,
lock_count=_lock_registry_count,
earliest_cleanup_time=_earliest_mp_cleanup_time,
last_cleanup_time=_last_mp_cleanup_time,
current_time=current_time,
threshold_check=True,
)
# Update global state if cleanup was performed
if cleaned_count > 0:
_earliest_mp_cleanup_time = new_earliest_time
_last_mp_cleanup_time = new_last_cleanup_time
class KeyedUnifiedLock:
"""
Manager for unified keyed locks, supporting both single and multi-process
• Keeps only a table of async keyed locks locally
• Fetches the multi-process keyed lock on every acquire
• Builds a fresh `UnifiedLock` each time, so `enable_logging`
(or future options) can vary per call.
• Supports dynamic namespaces specified at lock usage time
"""
def __init__(self, *, default_enable_logging: bool = True) -> None:
self._default_enable_logging = default_enable_logging
self._async_lock: Dict[str, asyncio.Lock] = {} # local keyed locks
self._async_lock_count: Dict[
str, int
] = {} # local keyed locks referenced count
self._async_lock_cleanup_data: Dict[
str, time.time
] = {} # local keyed locks timeout
self._mp_locks: Dict[
str, mp.synchronize.Lock
] = {} # multi-process lock proxies
self._earliest_async_cleanup_time: Optional[float] = (
None # track earliest async cleanup time
)
self._last_async_cleanup_time: Optional[float] = (
None # track last async cleanup time for minimum interval
)
def __call__(
self, namespace: str, keys: list[str], *, enable_logging: Optional[bool] = None
):
"""
Ergonomic helper so you can write:
async with storage_keyed_lock("namespace", ["key1", "key2"]):
...
"""
if enable_logging is None:
enable_logging = self._default_enable_logging
return _KeyedLockContext(
self,
namespace=namespace,
keys=keys,
enable_logging=enable_logging,
)
def _get_or_create_async_lock(self, combined_key: str) -> asyncio.Lock:
async_lock = self._async_lock.get(combined_key)
count = self._async_lock_count.get(combined_key, 0)
if async_lock is None:
async_lock = asyncio.Lock()
self._async_lock[combined_key] = async_lock
elif count == 0 and combined_key in self._async_lock_cleanup_data:
self._async_lock_cleanup_data.pop(combined_key)
count += 1
self._async_lock_count[combined_key] = count
return async_lock
def _release_async_lock(self, combined_key: str):
count = self._async_lock_count.get(combined_key, 0)
count -= 1
current_time = time.time()
if count == 0:
self._async_lock_cleanup_data[combined_key] = current_time
# Update earliest async cleanup time (only when earlier)
if (
self._earliest_async_cleanup_time is None
or current_time < self._earliest_async_cleanup_time
):
self._earliest_async_cleanup_time = current_time
self._async_lock_count[combined_key] = count
# Use generic cleanup function
cleaned_count, new_earliest_time, new_last_cleanup_time = _perform_lock_cleanup(
lock_type="async",
cleanup_data=self._async_lock_cleanup_data,
lock_registry=self._async_lock,
lock_count=self._async_lock_count,
earliest_cleanup_time=self._earliest_async_cleanup_time,
last_cleanup_time=self._last_async_cleanup_time,
current_time=current_time,
threshold_check=True,
)
# Update instance state if cleanup was performed
if cleaned_count > 0:
self._earliest_async_cleanup_time = new_earliest_time
self._last_async_cleanup_time = new_last_cleanup_time
def _get_lock_for_key(
self, namespace: str, key: str, enable_logging: bool = False
) -> UnifiedLock:
# 1. Create combined key for this namespace:key combination
combined_key = _get_combined_key(namespace, key)
# 2. get (or create) the perprocess async gate for this combined key
# Is synchronous, so no need to acquire a lock
async_lock = self._get_or_create_async_lock(combined_key)
# 3. fetch the shared raw lock
raw_lock = _get_or_create_shared_raw_mp_lock(namespace, key)
is_multiprocess = raw_lock is not None
if not is_multiprocess:
raw_lock = async_lock
# 4. build a *fresh* UnifiedLock with the chosen logging flag
if is_multiprocess:
return UnifiedLock(
lock=raw_lock,
is_async=False, # manager.Lock is synchronous
name=combined_key,
enable_logging=enable_logging,
async_lock=async_lock, # prevents eventloop blocking
)
else:
return UnifiedLock(
lock=raw_lock,
is_async=True,
name=combined_key,
enable_logging=enable_logging,
async_lock=None, # No need for async lock in single process mode
)
def _release_lock_for_key(self, namespace: str, key: str):
combined_key = _get_combined_key(namespace, key)
self._release_async_lock(combined_key)
_release_shared_raw_mp_lock(namespace, key)
def cleanup_expired_locks(self) -> Dict[str, Any]:
"""
Cleanup expired locks for both async and multiprocess locks following the same
conditions as _release_shared_raw_mp_lock and _release_async_lock functions.
Only performs cleanup when both has_expired_locks and interval_satisfied conditions are met
to avoid too frequent cleanup operations.
Since async and multiprocess locks work together, this method cleans up
both types of expired locks and returns comprehensive statistics.
Returns:
Dict containing cleanup statistics and current status:
{
"process_id": 12345,
"cleanup_performed": {
"mp_cleaned": 5,
"async_cleaned": 3
},
"current_status": {
"total_mp_locks": 10,
"pending_mp_cleanup": 2,
"total_async_locks": 8,
"pending_async_cleanup": 1
}
}
"""
global _lock_registry, _lock_registry_count, _lock_cleanup_data
global _registry_guard, _earliest_mp_cleanup_time, _last_mp_cleanup_time
cleanup_stats = {"mp_cleaned": 0, "async_cleaned": 0}
current_time = time.time()
# 1. Cleanup multiprocess locks using generic function
if (
_is_multiprocess
and _lock_registry is not None
and _registry_guard is not None
):
try:
with _registry_guard:
if _lock_cleanup_data is not None:
# Use generic cleanup function without threshold check
cleaned_count, new_earliest_time, new_last_cleanup_time = (
_perform_lock_cleanup(
lock_type="mp",
cleanup_data=_lock_cleanup_data,
lock_registry=_lock_registry,
lock_count=_lock_registry_count,
earliest_cleanup_time=_earliest_mp_cleanup_time,
last_cleanup_time=_last_mp_cleanup_time,
current_time=current_time,
threshold_check=False, # Force cleanup in cleanup_expired_locks
)
)
# Update global state if cleanup was performed
if cleaned_count > 0:
_earliest_mp_cleanup_time = new_earliest_time
_last_mp_cleanup_time = new_last_cleanup_time
cleanup_stats["mp_cleaned"] = cleaned_count
except Exception as e:
direct_log(
f"Error during multiprocess lock cleanup: {e}",
level="ERROR",
enable_output=True,
)
# 2. Cleanup async locks using generic function
try:
# Use generic cleanup function without threshold check
cleaned_count, new_earliest_time, new_last_cleanup_time = (
_perform_lock_cleanup(
lock_type="async",
cleanup_data=self._async_lock_cleanup_data,
lock_registry=self._async_lock,
lock_count=self._async_lock_count,
earliest_cleanup_time=self._earliest_async_cleanup_time,
last_cleanup_time=self._last_async_cleanup_time,
current_time=current_time,
threshold_check=False, # Force cleanup in cleanup_expired_locks
)
)
# Update instance state if cleanup was performed
if cleaned_count > 0:
self._earliest_async_cleanup_time = new_earliest_time
self._last_async_cleanup_time = new_last_cleanup_time
cleanup_stats["async_cleaned"] = cleaned_count
except Exception as e:
direct_log(
f"Error during async lock cleanup: {e}",
level="ERROR",
enable_output=True,
)
# 3. Get current status after cleanup
current_status = self.get_lock_status()
return {
"process_id": os.getpid(),
"cleanup_performed": cleanup_stats,
"current_status": current_status,
}
def get_lock_status(self) -> Dict[str, int]:
"""
Get current status of both async and multiprocess locks.
Returns comprehensive lock counts for both types of locks since
they work together in the keyed lock system.
Returns:
Dict containing lock counts:
{
"total_mp_locks": 10,
"pending_mp_cleanup": 2,
"total_async_locks": 8,
"pending_async_cleanup": 1
}
"""
global _lock_registry_count, _lock_cleanup_data, _registry_guard
status = {
"total_mp_locks": 0,
"pending_mp_cleanup": 0,
"total_async_locks": 0,
"pending_async_cleanup": 0,
}
try:
# Count multiprocess locks
if _is_multiprocess and _lock_registry_count is not None:
if _registry_guard is not None:
with _registry_guard:
status["total_mp_locks"] = len(_lock_registry_count)
if _lock_cleanup_data is not None:
status["pending_mp_cleanup"] = len(_lock_cleanup_data)
# Count async locks
status["total_async_locks"] = len(self._async_lock_count)
status["pending_async_cleanup"] = len(self._async_lock_cleanup_data)
except Exception as e:
direct_log(
f"Error getting keyed lock status: {e}",
level="ERROR",
enable_output=True,
)
return status
class _KeyedLockContext:
def __init__(
self,
parent: KeyedUnifiedLock,
namespace: str,
keys: list[str],
enable_logging: bool,
) -> None:
self._parent = parent
self._namespace = namespace
# The sorting is critical to ensure proper lock and release order
# to avoid deadlocks
self._keys = sorted(keys)
self._enable_logging = (
enable_logging
if enable_logging is not None
else parent._default_enable_logging
)
self._ul: Optional[List[Dict[str, Any]]] = None # set in __aenter__
# ----- enter -----
async def __aenter__(self):
if self._ul is not None:
raise RuntimeError("KeyedUnifiedLock already acquired in current context")
self._ul = []
try:
# Acquire locks for all keys in the namespace
for key in self._keys:
lock = None
entry = None
try:
# 1. Get lock object (reference count is incremented here)
lock = self._parent._get_lock_for_key(
self._namespace, key, enable_logging=self._enable_logging
)
# 2. Immediately create and add entry to list (critical for rollback to work)
entry = {
"key": key,
"lock": lock,
"entered": False,
"debug_inc": False,
"ref_incremented": True, # Mark that reference count has been incremented
}
self._ul.append(
entry
) # Add immediately after _get_lock_for_key for rollback to work
# 3. Try to acquire the lock
# Use try-finally to ensure state is updated atomically
lock_acquired = False
try:
await lock.__aenter__()
lock_acquired = True # Lock successfully acquired
finally:
if lock_acquired:
entry["entered"] = True
inc_debug_n_locks_acquired()
entry["debug_inc"] = True
except asyncio.CancelledError:
# Lock acquisition was cancelled
# The finally block above ensures entry["entered"] is correct
direct_log(
f"Lock acquisition cancelled for key {key}",
level="WARNING",
enable_output=self._enable_logging,
)
raise
except Exception as e:
# Other exceptions, log and re-raise
direct_log(
f"Lock acquisition failed for key {key}: {e}",
level="ERROR",
enable_output=True,
)
raise
return self
except BaseException:
# Critical: if any exception occurs (including CancelledError) during lock acquisition,
# we must rollback all already acquired locks to prevent lock leaks
# Use shield to ensure rollback completes
await asyncio.shield(self._rollback_acquired_locks())
raise
async def _rollback_acquired_locks(self):
"""Rollback all acquired locks in case of exception during __aenter__"""
if not self._ul:
return
async def rollback_single_entry(entry):
"""Rollback a single lock acquisition"""
key = entry["key"]
lock = entry["lock"]
debug_inc = entry["debug_inc"]
entered = entry["entered"]
ref_incremented = entry.get(
"ref_incremented", True
) # Default to True for safety
errors = []
# 1. If lock was acquired, release it
if entered:
try:
await lock.__aexit__(None, None, None)
except Exception as e:
errors.append(("lock_exit", e))
direct_log(
f"Lock rollback error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
# 2. Release reference count (if it was incremented)
if ref_incremented:
try:
self._parent._release_lock_for_key(self._namespace, key)
except Exception as e:
errors.append(("ref_release", e))
direct_log(
f"Lock rollback reference release error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
# 3. Decrement debug counter
if debug_inc:
try:
dec_debug_n_locks_acquired()
except Exception as e:
errors.append(("debug_dec", e))
direct_log(
f"Lock rollback counter decrementing error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
return errors
# Release already acquired locks in reverse order
for entry in reversed(self._ul):
# Use shield to protect each lock's rollback
try:
await asyncio.shield(rollback_single_entry(entry))
except Exception as e:
# Log but continue rolling back other locks
direct_log(
f"Lock rollback unexpected error for {entry['key']}: {e}",
level="ERROR",
enable_output=True,
)
self._ul = None
# ----- exit -----
async def __aexit__(self, exc_type, exc, tb):
if self._ul is None:
return
async def release_all_locks():
"""Release all locks with comprehensive error handling, protected from cancellation"""
async def release_single_entry(entry, exc_type, exc, tb):
"""Release a single lock with full protection"""
key = entry["key"]
lock = entry["lock"]
debug_inc = entry["debug_inc"]
entered = entry["entered"]
errors = []
# 1. Release the lock
if entered:
try:
await lock.__aexit__(exc_type, exc, tb)
except Exception as e:
errors.append(("lock_exit", e))
direct_log(
f"Lock release error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
# 2. Release reference count
try:
self._parent._release_lock_for_key(self._namespace, key)
except Exception as e:
errors.append(("ref_release", e))
direct_log(
f"Lock release reference error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
# 3. Decrement debug counter
if debug_inc:
try:
dec_debug_n_locks_acquired()
except Exception as e:
errors.append(("debug_dec", e))
direct_log(
f"Lock release counter decrementing error for key {key}: {e}",
level="ERROR",
enable_output=True,
)
return errors
all_errors = []
# Release locks in reverse order
# This entire loop is protected by the outer shield
for entry in reversed(self._ul):
try:
errors = await release_single_entry(entry, exc_type, exc, tb)
for error_type, error in errors:
all_errors.append((entry["key"], error_type, error))
except Exception as e:
all_errors.append((entry["key"], "unexpected", e))
direct_log(
f"Lock release unexpected error for {entry['key']}: {e}",
level="ERROR",
enable_output=True,
)
return all_errors
# CRITICAL: Protect the entire release process with shield
# This ensures that even if cancellation occurs, all locks are released
try:
all_errors = await asyncio.shield(release_all_locks())
except Exception as e:
direct_log(
f"Critical error during __aexit__ cleanup: {e}",
level="ERROR",
enable_output=True,
)
all_errors = []
finally:
# Always clear the lock list, even if shield was cancelled
self._ul = None
# If there were release errors and no other exception, raise the first release error
if all_errors and exc_type is None:
raise all_errors[0][2] # (key, error_type, error)
def get_internal_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified storage lock for data consistency"""
if _internal_lock is None:
raise RuntimeError(
"Shared data not initialized. Call initialize_share_data() before using locks!"
)
async_lock = _async_locks.get("internal_lock") if _is_multiprocess else None
return UnifiedLock(
lock=_internal_lock,
is_async=not _is_multiprocess,
name="internal_lock",
enable_logging=enable_logging,
async_lock=async_lock,
)
# Workspace based storage_lock is implemented by get_storage_keyed_lock instead.
# Workspace based pipeline_status_lock is implemented by get_storage_keyed_lock instead.
# No need to implement graph_db_lock:
# data integrity is ensured by entity level keyed-lock and allowing only one process to hold pipeline at a time.
def get_storage_keyed_lock(
keys: str | list[str], namespace: str = "default", enable_logging: bool = False
) -> _KeyedLockContext:
"""Return unified storage keyed lock for ensuring atomic operations across different namespaces"""
global _storage_keyed_lock
if _storage_keyed_lock is None:
raise RuntimeError("Shared-Data is not initialized")
if isinstance(keys, str):
keys = [keys]
return _storage_keyed_lock(namespace, keys, enable_logging=enable_logging)
def get_data_init_lock(enable_logging: bool = False) -> UnifiedLock:
"""return unified data initialization lock for ensuring atomic data initialization"""
if _data_init_lock is None:
raise RuntimeError(
"Shared data not initialized. Call initialize_share_data() before using locks!"
)
async_lock = _async_locks.get("data_init_lock") if _is_multiprocess else None
return UnifiedLock(
lock=_data_init_lock,
is_async=not _is_multiprocess,
name="data_init_lock",
enable_logging=enable_logging,
async_lock=async_lock,
)
def cleanup_keyed_lock() -> Dict[str, Any]:
"""
Force cleanup of expired keyed locks and return comprehensive status information.
This function actively cleans up expired locks for both async and multiprocess locks,
then returns detailed statistics about the cleanup operation and current lock status.
Returns:
Same as cleanup_expired_locks in KeyedUnifiedLock
"""
global _storage_keyed_lock
# Check if shared storage is initialized
if not _initialized or _storage_keyed_lock is None:
return {
"process_id": os.getpid(),
"cleanup_performed": {"mp_cleaned": 0, "async_cleaned": 0},
"current_status": {
"total_mp_locks": 0,
"pending_mp_cleanup": 0,
"total_async_locks": 0,
"pending_async_cleanup": 0,
},
}
return _storage_keyed_lock.cleanup_expired_locks()
def get_keyed_lock_status() -> Dict[str, Any]:
"""
Get current status of keyed locks without performing cleanup.
This function provides a read-only view of the current lock counts
for both multiprocess and async locks, including pending cleanup counts.
Returns:
Same as get_lock_status in KeyedUnifiedLock
"""
global _storage_keyed_lock
# Check if shared storage is initialized
if not _initialized or _storage_keyed_lock is None:
return {
"process_id": os.getpid(),
"total_mp_locks": 0,
"pending_mp_cleanup": 0,
"total_async_locks": 0,
"pending_async_cleanup": 0,
}
status = _storage_keyed_lock.get_lock_status()
status["process_id"] = os.getpid()
return status
def initialize_share_data(
workers: int = 1,
global_concurrency_limits: Optional[Mapping[str, int]] = None,
):
"""
Initialize shared storage data for single or multi-process mode.
When used with Gunicorn's preload feature, this function is called once in the
master process before forking worker processes, allowing all workers to share
the same initialized data.
In single-process mode, this function is called in FASTAPI lifespan function.
The function determines whether to use cross-process shared variables for data storage
based on the number of workers. If workers=1, it uses thread locks and local dictionaries.
If workers>1, it uses process locks and shared dictionaries managed by multiprocessing.Manager.
Args:
workers (int): Number of worker processes. If 1, single-process mode is used.
If > 1, multi-process mode with shared memory is used.
global_concurrency_limits: Optional mapping of concurrency group name
(e.g. "llm:extract", "embedding", "rerank") to the
cross-worker global max concurrency for that group.
Read-only after initialization; later calls (which hit
the already-initialized guard) never overwrite it.
"""
global \
_manager, \
_workers, \
_is_multiprocess, \
_lock_registry, \
_lock_registry_count, \
_lock_cleanup_data, \
_registry_guard, \
_internal_lock, \
_data_init_lock, \
_shared_dicts, \
_init_flags, \
_initialized, \
_update_flags, \
_async_locks, \
_storage_keyed_lock, \
_earliest_mp_cleanup_time, \
_last_mp_cleanup_time, \
_global_concurrency_limits, \
_lease_ns_cache, \
_queue_stats_ns_cache
# Check if already initialized
if _initialized:
direct_log(
f"Process {os.getpid()} Shared-Data already initialized (multiprocess={_is_multiprocess})"
)
return
_workers = workers
_global_concurrency_limits = (
{
str(group): int(limit)
for group, limit in global_concurrency_limits.items()
if limit is not None and int(limit) > 0
}
if global_concurrency_limits
else {}
)
_lease_ns_cache = None
_queue_stats_ns_cache = None
if _global_concurrency_limits:
direct_log(
f"Process {os.getpid()} Global concurrency limits: {_global_concurrency_limits}",
level="INFO",
)
if workers > 1:
_is_multiprocess = True
_manager = Manager()
_lock_registry = _manager.dict()
_lock_registry_count = _manager.dict()
_lock_cleanup_data = _manager.dict()
_registry_guard = _manager.RLock()
_internal_lock = _manager.Lock()
_data_init_lock = _manager.Lock()
_shared_dicts = _manager.dict()
_init_flags = _manager.dict()
_update_flags = _manager.dict()
_storage_keyed_lock = KeyedUnifiedLock()
# Initialize async locks for multiprocess mode
_async_locks = {
"internal_lock": asyncio.Lock(),
"graph_db_lock": asyncio.Lock(),
"data_init_lock": asyncio.Lock(),
}
direct_log(
f"Process {os.getpid()} Shared-Data created for Multiple Process (workers={workers})"
)
else:
_is_multiprocess = False
_internal_lock = asyncio.Lock()
_data_init_lock = asyncio.Lock()
_shared_dicts = {}
_init_flags = {}
_update_flags = {}
_async_locks = None # No need for async locks in single process mode
_storage_keyed_lock = KeyedUnifiedLock()
direct_log(f"Process {os.getpid()} Shared-Data created for Single Process")
# Initialize multiprocess cleanup times
_earliest_mp_cleanup_time = None
_last_mp_cleanup_time = None
# Mark as initialized
_initialized = True
async def initialize_pipeline_status(workspace: str | None = None):
"""
Initialize pipeline_status share data with default values.
This function could be called before during FASTAPI lifespan for each worker.
Args:
workspace: Optional workspace identifier for pipeline_status of specific workspace.
If None or empty string, uses the default workspace set by
set_default_workspace().
"""
pipeline_namespace = await get_namespace_data(
"pipeline_status", first_init=True, workspace=workspace
)
async with get_internal_lock():
# Check if already initialized by checking for required fields
if "busy" in pipeline_namespace:
return
# Create a shared list object for history_messages
history_messages = _manager.list() if _is_multiprocess else []
pipeline_namespace.update(
{
"autoscanned": False, # Auto-scan started
"busy": False, # Control concurrent processes
# Destructive subset of ``busy``: clear / delete jobs that
# DROP storages or remove input files. Concurrent enqueue
# would race against the drop and silently lose the
# accepted document, so reservation and the enqueue
# last-line guard reject when this is True. ``busy`` on
# its own (the processing loop) remains compatible with
# concurrent enqueue via request_pending.
"destructive_busy": False,
"scanning": False, # /documents/scan task running (whole lifecycle)
# Exclusive subset of ``scanning``: only True during the
# scan's *classification* phase, when run_scanning_process
# is reading doc_status to classify files (PROCESSED →
# archive, FAILED-without-full_docs → retry-as-new, etc.)
# and possibly deleting stale stubs. After classification
# the scan transitions to its processing phase (which
# behaves like any other busy processing run) and clears
# this flag, allowing concurrent uploads to land in
# doc_status while the scan-driven processing finishes.
"scanning_exclusive": False,
# Counter of upload/insert endpoints that have passed the
# idle preflight but whose background enqueue has not yet
# run. Closes the preflight-to-background race: scan
# refuses to start while this is > 0 so the bg task is
# guaranteed to see scanning=False at enqueue time.
"pending_enqueues": 0,
"job_name": "-", # Current job name (indexing files/indexing texts)
"job_start": None, # Job start time
"docs": 0, # Total number of documents to be indexed
"batchs": 0, # Number of batches for processing documents
"cur_batch": 0, # Current processing batch
"request_pending": False, # Flag for pending request for processing
"latest_message": "", # Latest message from pipeline processing
"history_messages": history_messages, # 使用共享列表对象
}
)
final_namespace = get_final_namespace("pipeline_status", workspace)
direct_log(
f"Process {os.getpid()} Pipeline namespace '{final_namespace}' initialized"
)
async def get_update_flag(namespace: str, workspace: str | None = None):
"""
Create a namespace's update flag for a workers.
Returen the update flag to caller for referencing or reset.
"""
global _update_flags
if _update_flags is None:
raise ValueError("Try to create namespace before Shared-Data is initialized")
final_namespace = get_final_namespace(namespace, workspace)
async with get_internal_lock():
if final_namespace not in _update_flags:
if _is_multiprocess and _manager is not None:
_update_flags[final_namespace] = _manager.list()
else:
_update_flags[final_namespace] = []
direct_log(
f"Process {os.getpid()} initialized updated flags for namespace: [{final_namespace}]"
)
if _is_multiprocess and _manager is not None:
new_update_flag = _manager.Value("b", False)
else:
# Create a simple mutable object to store boolean value for compatibility with mutiprocess
class MutableBoolean:
def __init__(self, initial_value=False):
self.value = initial_value
new_update_flag = MutableBoolean(False)
_update_flags[final_namespace].append(new_update_flag)
return new_update_flag
async def set_all_update_flags(namespace: str, workspace: str | None = None):
"""Set all update flag of namespace indicating all workers need to reload data from files"""
global _update_flags
if _update_flags is None:
raise ValueError("Try to create namespace before Shared-Data is initialized")
final_namespace = get_final_namespace(namespace, workspace)
async with get_internal_lock():
if final_namespace not in _update_flags:
raise ValueError(f"Namespace {final_namespace} not found in update flags")
# Update flags for both modes
for i in range(len(_update_flags[final_namespace])):
_update_flags[final_namespace][i].value = True
async def clear_all_update_flags(namespace: str, workspace: str | None = None):
"""Clear all update flag of namespace indicating all workers need to reload data from files"""
global _update_flags
if _update_flags is None:
raise ValueError("Try to create namespace before Shared-Data is initialized")
final_namespace = get_final_namespace(namespace, workspace)
async with get_internal_lock():
if final_namespace not in _update_flags:
raise ValueError(f"Namespace {final_namespace} not found in update flags")
# Update flags for both modes
for i in range(len(_update_flags[final_namespace])):
_update_flags[final_namespace][i].value = False
async def get_all_update_flags_status(workspace: str | None = None) -> Dict[str, list]:
"""
Get update flags status for all namespaces.
Returns:
Dict[str, list]: A dictionary mapping namespace names to lists of update flag statuses
"""
if _update_flags is None:
return {}
if workspace is None:
workspace = get_default_workspace()
result = {}
async with get_internal_lock():
for namespace, flags in _update_flags.items():
# Check if namespace has a workspace prefix (contains ':')
if ":" in namespace:
# Namespace has workspace prefix like "space1:pipeline_status"
# Only include if workspace matches the prefix
# Use rsplit to split from the right since workspace can contain colons
namespace_split = namespace.rsplit(":", 1)
if not workspace or namespace_split[0] != workspace:
continue
else:
# Namespace has no workspace prefix like "pipeline_status"
# Only include if we're querying the default (empty) workspace
if workspace:
continue
worker_statuses = []
for flag in flags:
if _is_multiprocess:
worker_statuses.append(flag.value)
else:
worker_statuses.append(flag)
result[namespace] = worker_statuses
return result
async def try_initialize_namespace(
namespace: str, workspace: str | None = None
) -> bool:
"""
Returns True if the current worker(process) gets initialization permission for loading data later.
The worker does not get the permission is prohibited to load data from files.
"""
global _init_flags, _manager
if _init_flags is None:
raise ValueError("Try to create nanmespace before Shared-Data is initialized")
final_namespace = get_final_namespace(namespace, workspace)
async with get_internal_lock():
if final_namespace not in _init_flags:
_init_flags[final_namespace] = True
direct_log(
f"Process {os.getpid()} ready to initialize storage namespace: [{final_namespace}]"
)
return True
direct_log(
f"Process {os.getpid()} storage namespace already initialized: [{final_namespace}]"
)
return False
async def get_namespace_data(
namespace: str, first_init: bool = False, workspace: str | None = None
) -> Dict[str, Any]:
"""get the shared data reference for specific namespace
Args:
namespace: The namespace to retrieve
first_init: If True, allows pipeline_status namespace to create namespace if it doesn't exist.
Prevent getting pipeline_status namespace without initialize_pipeline_status().
This parameter is used internally by initialize_pipeline_status().
workspace: Workspace identifier (may be empty string for global namespace)
"""
if _shared_dicts is None:
direct_log(
f"Error: Try to getnanmespace before it is initialized, pid={os.getpid()}",
level="ERROR",
)
raise ValueError("Shared dictionaries not initialized")
final_namespace = get_final_namespace(namespace, workspace)
async with get_internal_lock():
if final_namespace not in _shared_dicts:
# Special handling for pipeline_status namespace
if (
final_namespace.endswith(":pipeline_status")
or final_namespace == "pipeline_status"
) and not first_init:
# Check if pipeline_status should have been initialized but wasn't
# This helps users to call initialize_pipeline_status() before get_namespace_data()
raise PipelineNotInitializedError(final_namespace)
# For other namespaces or when allow_create=True, create them dynamically
if _is_multiprocess and _manager is not None:
_shared_dicts[final_namespace] = _manager.dict()
else:
_shared_dicts[final_namespace] = {}
return _shared_dicts[final_namespace]
class NamespaceLock:
"""
Reusable namespace lock wrapper that creates a fresh context on each use.
This class solves the lock re-entrance and concurrent coroutine issues by using
contextvars.ContextVar to provide per-coroutine storage. Each coroutine gets its
own independent lock context, preventing state interference between concurrent
coroutines using the same NamespaceLock instance.
Example:
lock = NamespaceLock("my_namespace", "workspace1")
# Can be used multiple times safely
async with lock:
await do_something()
# Can even be used concurrently without deadlock
await asyncio.gather(
coroutine_1(lock), # Each gets its own context
coroutine_2(lock) # No state interference
)
"""
def __init__(
self, namespace: str, workspace: str | None = None, enable_logging: bool = False
):
self._namespace = namespace
self._workspace = workspace
self._enable_logging = enable_logging
# Use ContextVar to provide per-coroutine storage for lock context
# This ensures each coroutine has its own independent context
self._ctx_var: ContextVar[Optional[_KeyedLockContext]] = ContextVar(
"lock_ctx", default=None
)
async def __aenter__(self):
"""Create a fresh context each time we enter"""
# Check if this coroutine already has an active lock context
if self._ctx_var.get() is not None:
raise RuntimeError(
"NamespaceLock already acquired in current coroutine context"
)
final_namespace = get_final_namespace(self._namespace, self._workspace)
ctx = get_storage_keyed_lock(
["default_key"],
namespace=final_namespace,
enable_logging=self._enable_logging,
)
# Acquire the lock first, then store context only after successful acquisition
# This prevents the ContextVar from being set if acquisition fails (e.g., due to cancellation),
# which would permanently brick the lock
result = await ctx.__aenter__()
self._ctx_var.set(ctx)
return result
async def __aexit__(self, exc_type, exc_val, exc_tb):
"""Exit the current context and clean up"""
# Retrieve this coroutine's context
ctx = self._ctx_var.get()
if ctx is None:
raise RuntimeError("NamespaceLock exited without being entered")
result = await ctx.__aexit__(exc_type, exc_val, exc_tb)
# Clear this coroutine's context
self._ctx_var.set(None)
return result
def get_namespace_lock(
namespace: str, workspace: str | None = None, enable_logging: bool = False
) -> NamespaceLock:
"""Get a reusable namespace lock wrapper.
This function returns a NamespaceLock instance that can be used multiple times
safely, even in concurrent scenarios. Each use creates a fresh lock context
internally, preventing lock re-entrance errors.
Args:
namespace: The namespace to get the lock for.
workspace: Workspace identifier (may be empty string for global namespace)
enable_logging: Whether to enable lock operation logging
Returns:
NamespaceLock: A reusable lock wrapper that can be used with 'async with'
Example:
lock = get_namespace_lock("pipeline_status", workspace="space1")
# Can be used multiple times
async with lock:
await do_something()
async with lock:
await do_something_else()
"""
return NamespaceLock(namespace, workspace, enable_logging)
def finalize_share_data():
"""
Release shared resources and clean up.
This function should be called when the application is shutting down
to properly release shared resources and avoid memory leaks.
In multi-process mode, it shuts down the Manager and releases all shared objects.
In single-process mode, it simply resets the global variables.
"""
global \
_manager, \
_is_multiprocess, \
_internal_lock, \
_data_init_lock, \
_shared_dicts, \
_init_flags, \
_initialized, \
_update_flags, \
_async_locks, \
_default_workspace, \
_global_concurrency_limits, \
_lease_ns_cache, \
_queue_stats_ns_cache
# Check if already initialized
if not _initialized:
direct_log(
f"Process {os.getpid()} storage data not initialized, nothing to finalize"
)
return
direct_log(
f"Process {os.getpid()} finalizing storage data (multiprocess={_is_multiprocess})"
)
# In multi-process mode, shut down the Manager
if _is_multiprocess and _manager is not None:
try:
# Clear shared resources before shutting down Manager
if _shared_dicts is not None:
# Clear pipeline status history messages first if exists
try:
pipeline_status = _shared_dicts.get("pipeline_status", {})
if "history_messages" in pipeline_status:
pipeline_status["history_messages"].clear()
except Exception:
pass # Ignore any errors during history messages cleanup
_shared_dicts.clear()
if _init_flags is not None:
_init_flags.clear()
if _update_flags is not None:
# Clear each namespace's update flags list and Value objects
try:
for namespace in _update_flags:
flags_list = _update_flags[namespace]
if isinstance(flags_list, list):
# Clear Value objects in the list
for flag in flags_list:
if hasattr(
flag, "value"
): # Check if it's a Value object
flag.value = False
flags_list.clear()
except Exception:
pass # Ignore any errors during update flags cleanup
_update_flags.clear()
# Shut down the Manager - this will automatically clean up all shared resources
_manager.shutdown()
direct_log(f"Process {os.getpid()} Manager shutdown complete")
except Exception as e:
direct_log(
f"Process {os.getpid()} Error shutting down Manager: {e}", level="ERROR"
)
# Reset global variables
_manager = None
_initialized = None
_is_multiprocess = None
_shared_dicts = None
_init_flags = None
_internal_lock = None
_data_init_lock = None
_update_flags = None
_async_locks = None
_default_workspace = None
_global_concurrency_limits = None
_lease_ns_cache = None
_queue_stats_ns_cache = None
direct_log(f"Process {os.getpid()} storage data finalization complete")
def set_default_workspace(workspace: str | None = None):
"""
Set default workspace for namespace operations for backward compatibility.
This allows get_namespace_data(),get_namespace_lock() or initialize_pipeline_status() to
automatically use the correct workspace when called without workspace parameters,
maintaining compatibility with legacy code that doesn't pass workspace explicitly.
Args:
workspace: Workspace identifier (may be empty string for global namespace)
"""
global _default_workspace
if workspace is None:
workspace = ""
_default_workspace = workspace
direct_log(
f"Default workspace set to: '{_default_workspace}' (empty means global)",
level="DEBUG",
)
def get_default_workspace() -> str:
"""
Get default workspace for backward compatibility.
Returns:
The default workspace string. Empty string means global namespace. None means not set.
"""
global _default_workspace
return _default_workspace
def get_pipeline_status_lock(
enable_logging: bool = False, workspace: str = None
) -> NamespaceLock:
"""Return unified storage lock for pipeline status data consistency.
This function is for compatibility with legacy code only.
"""
global _default_workspace
actual_workspace = workspace if workspace else _default_workspace
return get_namespace_lock(
"pipeline_status", workspace=actual_workspace, enable_logging=enable_logging
)
# ---------------------------------------------------------------------------
# Cross-worker global concurrency gate (lease + heartbeat semantics)
# ---------------------------------------------------------------------------
#
# Each group's whole gate state lives under a SINGLE key of the
# workspace-less "concurrency_leases" namespace::
#
# ns[group] = {
# "leases": {lease_id: {"pid": int, "updated_at": float,
# ("suspect_since": float)}},
# "waiters": {str(pid): {"pid": int, "wait_start": float,
# "last_poll": float}},
# }
#
# Whole-value replacement only — in multiprocess mode the namespace is a
# Manager dict, so in-place mutation of a retrieved value would NOT persist
# across processes. The single-key layout is deliberate: every proxy access
# is one IPC round trip to the manager process, so an acquire attempt under
# the group's keyed lock costs exactly one read (plus at most one write)
# instead of scanning per-lease keys. Reaping, capacity counting and waiter
# ranking all run on the local copy.
#
# Self-healing: holders refresh ``updated_at`` from their 5s health-check
# heartbeat. A lease is reclaimed when its owner PID is dead (immediately)
# or when its heartbeat expired AND the suspect grace elapsed (protects
# live-but-momentarily-stalled owners from false reclamation). Long-running
# tasks are never reclaimed as long as their owner keeps renewing.
#
# Best-effort cap, not a strict provider-side invariant: the lease table is
# the admission source of truth, so the cap is exact while holders keep
# renewing. A slot is reclaimed only when its owner PID is gone or its
# heartbeat has expired beyond the suspect grace. That prevents permanent
# capacity leaks after kill -9 / OOM and similar external termination, but
# the provider may still be finishing the abandoned HTTP request until its
# own timeout/connection close. During that window, a newly admitted caller
# can overlap with the abandoned provider-side call. Long event-loop stalls
# have the same shape after heartbeat TTL + suspect grace, though normal long
# calls are protected by regular renewal. A reclaimed lease is never
# resurrected (renew_global_slots refuses to re-insert a popped lease), which
# keeps the internal gate self-healing.
def is_share_data_initialized() -> bool:
"""Return True once initialize_share_data() has run in this process."""
return bool(_initialized)
def is_global_concurrency_limited(group: Optional[str]) -> bool:
"""Synchronous, cacheable check: does ``group`` have a global limit?
Reads only the module-level read-only configuration — no IPC. Returns
False when shared data is not initialized, no limits were configured,
or the group has no positive limit.
"""
if not group or not _global_concurrency_limits:
return False
limit = _global_concurrency_limits.get(group)
return limit is not None and limit > 0
def get_global_concurrency_limit(group: Optional[str]) -> Optional[int]:
"""Return the configured global limit for ``group`` (None if unlimited)."""
if not group or not _global_concurrency_limits:
return None
return _global_concurrency_limits.get(group)
def _pid_alive(pid: int) -> bool:
"""Best-effort liveness probe; errs on the side of 'alive'."""
if pid == os.getpid():
return True
try:
os.kill(pid, 0)
except ProcessLookupError:
return False
except OSError:
# PermissionError and friends: the process exists (or we cannot
# tell) — treat as alive so we never reclaim a live owner's lease.
return True
return True
async def _get_lease_namespace() -> Dict[str, Any]:
global _lease_ns_cache
if _lease_ns_cache is None:
_lease_ns_cache = await get_namespace_data(
_CONCURRENCY_LEASE_NAMESPACE, workspace=""
)
return _lease_ns_cache
async def _get_queue_stats_namespace() -> Dict[str, Any]:
global _queue_stats_ns_cache
if _queue_stats_ns_cache is None:
_queue_stats_ns_cache = await get_namespace_data(
_QUEUE_STATS_NAMESPACE, workspace=""
)
return _queue_stats_ns_cache
def _empty_gate_state() -> Dict[str, Any]:
return {"leases": {}, "waiters": {}}
def _load_gate_state(ns: Dict[str, Any], group: str) -> Dict[str, Any]:
"""Return a local, independently mutable copy of a group's gate state.
Exactly one proxy read. The nested dicts are copied so that mutating the
result never aliases the stored value (a plain dict in single-process
mode) — callers mutate the copy and write it back whole.
"""
raw = ns.get(group)
if raw is None:
return _empty_gate_state()
state = dict(raw)
state["leases"] = {
lease_id: dict(lease)
for lease_id, lease in dict(state.get("leases") or {}).items()
}
state["waiters"] = {
pid_key: dict(waiter)
for pid_key, waiter in dict(state.get("waiters") or {}).items()
}
return state
def _reap_gate_state(state: Dict[str, Any], now: float) -> tuple[int, bool]:
"""Reclaim dead/expired leases on a local state copy (no IPC).
Returns ``(live_lease_count, changed)``. Suspect handling: a lease whose
heartbeat expired while its PID is still alive is first marked with
``suspect_since`` and reclaimed only after ``_suspect_grace`` elapses
without a renewal; a renewal (fresh ``updated_at``) clears the suspect
mark. Dead PIDs are reclaimed immediately. Suspect leases still count
toward capacity so the global limit is never exceeded.
Waiter records are reaped in the same pass: a process whose lease was
just reclaimed (timed out / died), whose PID is dead, or whose record
has not been refreshed within ``_waiter_stale_ttl`` must not keep
occupying the longest-waiter seat — a ghost favored waiter would push
every live waiter onto the deferred backoff and waste freed slots.
"""
leases: Dict[str, Any] = state["leases"]
waiters: Dict[str, Any] = state["waiters"]
live = 0
changed = False
reclaimed_pids = set()
# Liveness is constant within this synchronous pass (no await, fixed
# ``now``), so memoize the probe: a PID holding many leases of this group
# is checked once instead of once per lease. NEVER cache across calls —
# PID reuse and staleness could reclaim a live owner's lease.
alive_cache: Dict[int, bool] = {}
def _alive(pid: int) -> bool:
cached = alive_cache.get(pid)
if cached is None:
cached = _pid_alive(pid)
alive_cache[pid] = cached
return cached
for lease_id in list(leases.keys()):
lease = leases[lease_id]
pid = lease.get("pid")
updated_at = lease.get("updated_at", 0.0)
if pid is None or not _alive(pid):
leases.pop(lease_id)
changed = True
if pid is not None:
reclaimed_pids.add(pid)
continue
if now - updated_at > _heartbeat_ttl:
suspect_since = lease.get("suspect_since")
if suspect_since is None:
lease["suspect_since"] = now
changed = True
live += 1
elif now - suspect_since > _suspect_grace:
leases.pop(lease_id)
reclaimed_pids.add(pid)
changed = True
else:
live += 1
else:
if "suspect_since" in lease:
lease.pop("suspect_since", None)
changed = True
live += 1
for pid_key in list(waiters.keys()):
waiter = waiters[pid_key]
pid = waiter.get("pid")
last_poll = waiter.get("last_poll", 0.0)
if (
pid is None
or pid in reclaimed_pids
or not _alive(pid)
or now - last_poll > _waiter_stale_ttl
):
waiters.pop(pid_key)
changed = True
return live, changed
def _log_acquire_failure(group: str, error: Exception) -> None:
global _last_acquire_failure_log
now = time.time()
if now - _last_acquire_failure_log >= _ACQUIRE_FAILURE_LOG_INTERVAL:
_last_acquire_failure_log = now
direct_log(
f"Process {os.getpid()} failed to acquire global slot for group "
f"'{group}' (fail-closed, task stays queued): {error}",
level="WARNING",
)
def _is_longest_live_waiter(state: Dict[str, Any], pid: int, now: float) -> bool:
"""Is ``pid`` the longest-waiting live poller in this gate state?
Operates on a local state copy after the reap pass has dropped
dead/stale waiter records — every remaining record belongs to a live,
actively polling process.
"""
my_start = None
others_min = None
for waiter in state["waiters"].values():
wait_start = waiter.get("wait_start", now)
if waiter.get("pid") == pid:
my_start = wait_start
elif others_min is None or wait_start < others_min:
others_min = wait_start
if my_start is None:
return False
return others_min is None or my_start <= others_min
async def _acquire_global_slot(
group: str, track_wait: bool
) -> tuple[Optional[str], bool]:
"""Shared implementation for the two acquire entry points.
Returns ``(lease_id, is_priority_waiter)``. When ``track_wait`` is set,
a failed attempt registers/refreshes this process's waiter record
(``wait_start`` set once per waiting episode, ``last_poll`` refreshed on
every attempt) and reports whether this process is the longest-waiting
live poller; a successful attempt always clears the record.
IPC budget under the keyed lock: one state read, plus one write only
when something changed (reap effects, waiter registration, or a new
lease) — a plain failed attempt on an unchanged gate writes nothing.
"""
limit = get_global_concurrency_limit(group)
if limit is None or limit <= 0:
return None, False
try:
ns = await _get_lease_namespace()
async with get_storage_keyed_lock(
group, namespace=_CONCURRENCY_LEASE_NAMESPACE, enable_logging=False
):
now = time.time()
state = _load_gate_state(ns, group)
in_use, changed = _reap_gate_state(state, now)
pid = os.getpid()
pid_key = str(pid)
if in_use >= limit:
if not track_wait:
if changed:
ns[group] = state
return None, False
waiter = state["waiters"].get(pid_key) or {
"pid": pid,
"wait_start": now,
}
waiter["last_poll"] = now
state["waiters"][pid_key] = waiter
ns[group] = state
return None, _is_longest_live_waiter(state, pid, now)
lease_id = uuid.uuid4().hex
state["leases"][lease_id] = {"pid": pid, "updated_at": now}
# Got a slot: this process is no longer waiting. Resetting here
# (rather than keeping seniority) is what de-prioritizes a
# backlog-heavy process after each win, yielding approximate
# round-robin across processes under sustained contention.
state["waiters"].pop(pid_key, None)
ns[group] = state
return lease_id, True
except Exception as e:
_log_acquire_failure(group, e)
return None, False
async def try_acquire_global_slot(group: str) -> Optional[str]:
"""Try to claim one global concurrency slot for ``group`` (non-blocking).
Returns a lease id on success, or None when the group is at capacity.
Any shared-storage error is fail-closed: returns None (with a
rate-limited warning) so the caller keeps the task queued and retries —
capacity is never exceeded due to infrastructure errors.
This plain variant never registers waiter records — use
:func:`try_acquire_global_slot_tracked` from polling loops that want
longest-waiter fairness.
"""
lease_id, _ = await _acquire_global_slot(group, track_wait=False)
return lease_id
async def try_acquire_global_slot_tracked(group: str) -> tuple[Optional[str], bool]:
"""Acquire variant for polling loops: ``(lease_id, is_priority_waiter)``.
On failure the caller's waiter record is registered/refreshed and the
second element reports whether this process is currently the
longest-waiting live poller of the group. Pollers should keep the
fastest poll interval when favored and back off (bounded) otherwise —
a soft FIFO across worker processes with no hard gate: any poller that
finds a free slot still takes it, so a sleeping favored waiter can
never leave capacity idle indefinitely. Fail-closed errors report
``(None, False)``.
"""
return await _acquire_global_slot(group, track_wait=True)
async def clear_slot_waiter(group: str) -> None:
"""Drop this process's waiter record for ``group`` (idempotent).
Called when a wrapper shuts down so a no-longer-polling process never
lingers in the longest-waiter seat; the stale TTL and the reap pass
cover crashes where this cleanup never runs.
"""
if not _initialized:
return
ns = await _get_lease_namespace()
async with get_storage_keyed_lock(
group, namespace=_CONCURRENCY_LEASE_NAMESPACE, enable_logging=False
):
state = _load_gate_state(ns, group)
if state["waiters"].pop(str(os.getpid()), None) is not None:
ns[group] = state
async def global_slot_waiters(group: str) -> List[Dict[str, Any]]:
"""Snapshot of processes actively polling for a slot of ``group``.
Returns ``[{"pid": ..., "waited": seconds}, ...]`` sorted by descending
wait time; stale records (not refreshed within the waiter TTL) are
skipped. Read-only and lock-free — intended for observability.
"""
if not _initialized:
return []
ns = await _get_lease_namespace()
now = time.time()
state = _load_gate_state(ns, group)
waiters = []
for waiter in state["waiters"].values():
if now - waiter.get("last_poll", 0.0) > _waiter_stale_ttl:
continue
waiters.append(
{
"pid": waiter.get("pid"),
"waited": max(0.0, now - waiter.get("wait_start", now)),
}
)
return sorted(waiters, key=lambda w: -w["waited"])
async def release_global_slot(group: str, lease_id: str) -> None:
"""Release a previously acquired global slot (idempotent).
Raises on shared-storage errors — callers that must never propagate
(e.g. worker ``finally`` blocks) wrap this and queue the lease for a
later retry; the heartbeat TTL guarantees eventual reclamation anyway.
"""
ns = await _get_lease_namespace()
async with get_storage_keyed_lock(
group, namespace=_CONCURRENCY_LEASE_NAMESPACE, enable_logging=False
):
state = _load_gate_state(ns, group)
if state["leases"].pop(lease_id, None) is not None:
ns[group] = state
async def renew_global_slots(group: str, lease_ids) -> None:
"""Refresh the heartbeat of this process's held leases for ``group``.
A renewal rewrites the lease whole (clearing any ``suspect_since``
mark). Leases that have already been reclaimed are NOT resurrected —
re-inserting could exceed the configured limit; the suspect grace
exists precisely to make false reclamation unlikely.
"""
lease_ids = list(lease_ids)
if not lease_ids:
return
ns = await _get_lease_namespace()
async with get_storage_keyed_lock(
group, namespace=_CONCURRENCY_LEASE_NAMESPACE, enable_logging=False
):
now = time.time()
state = _load_gate_state(ns, group)
changed = False
for lease_id in lease_ids:
if lease_id in state["leases"]:
state["leases"][lease_id] = {"pid": os.getpid(), "updated_at": now}
changed = True
if changed:
ns[group] = state
async def reconcile_global_slots(group: str) -> int:
"""Run the lease reaper for ``group``; return surviving lease count."""
ns = await _get_lease_namespace()
async with get_storage_keyed_lock(
group, namespace=_CONCURRENCY_LEASE_NAMESPACE, enable_logging=False
):
state = _load_gate_state(ns, group)
live, changed = _reap_gate_state(state, time.time())
if changed:
ns[group] = state
return live
async def global_concurrency_in_use(group: str) -> int:
"""Approximate count of currently held global slots for ``group``.
Lock-free single read — intended for observability.
"""
ns = await _get_lease_namespace()
return len(_load_gate_state(ns, group)["leases"])
# ---------------------------------------------------------------------------
# Cross-worker queue stats (best-effort, debounced snapshots)
# ---------------------------------------------------------------------------
#
# Each worker process publishes per-queue snapshots under
# ``f"{queue_name}{KEY_SEP}{pid}"`` in the workspace-less "queue_stats"
# namespace (whole-value replacement). The local closure counters remain
# the source of truth; the shared area only needs to be "fresh enough"
# (event-triggered publishes debounced by the caller + 5s heartbeat flush).
# Flat counter fields summed across workers during aggregation. These are
# the existing get_queue_stats() fields (schema compatibility for /health
# and the webui) plus the new global_slot_waits / physical_queued counters.
QUEUE_STATS_SUM_FIELDS = (
"queued",
"running",
"in_flight",
"worker_count",
"submitted_total",
"completed_total",
"failed_total",
"cancelled_total",
"rejected_total",
"global_slot_waits",
"physical_queued",
)
async def publish_queue_stats(queue_name: str, snapshot: Dict[str, Any]) -> None:
"""Publish this process's snapshot for ``queue_name`` (whole replacement).
The snapshot must carry ``pid`` and ``updated_at`` (wall-clock time) so
aggregation can reap stale entries. Best-effort by contract: callers
must tolerate exceptions.
"""
if not _initialized:
return
ns = await _get_queue_stats_namespace()
ns[f"{queue_name}{KEY_SEP}{os.getpid()}"] = dict(snapshot)
async def unpublish_queue_stats(queue_name: str) -> None:
"""Remove this process's snapshot for ``queue_name`` (idempotent)."""
if not _initialized:
return
ns = await _get_queue_stats_namespace()
ns.pop(f"{queue_name}{KEY_SEP}{os.getpid()}", None)
async def aggregate_queue_stats(queue_name: str) -> Dict[str, Any]:
"""Aggregate all workers' published snapshots for ``queue_name``.
Sums the flat counter fields across live snapshots and returns them
together with ``reporting_workers`` and the raw ``per_worker`` map.
Entries owned by dead PIDs or older than the stale TTL are reaped —
re-checked under the internal lock against the previously observed
``updated_at`` so a snapshot republished concurrently is never deleted.
"""
ns = await _get_queue_stats_namespace()
now = time.time()
prefix = f"{queue_name}{KEY_SEP}"
per_worker: Dict[str, Dict[str, Any]] = {}
stale: List[tuple] = []
for key in [k for k in ns.keys() if k.startswith(prefix)]:
raw = ns.get(key)
if raw is None:
continue
snap = dict(raw)
pid = snap.get("pid")
updated_at = snap.get("updated_at", 0.0)
if (pid is not None and not _pid_alive(pid)) or (
now - updated_at > _queue_stats_stale_ttl
):
stale.append((key, updated_at))
continue
per_worker[str(pid)] = snap
if stale:
async with get_internal_lock():
for key, seen_updated_at in stale:
current = ns.get(key)
if current is None:
continue
if dict(current).get("updated_at", 0.0) != seen_updated_at:
continue # republished since we looked — keep it
ns.pop(key, None)
aggregated: Dict[str, Any] = {
field: sum(int(snap.get(field, 0) or 0) for snap in per_worker.values())
for field in QUEUE_STATS_SUM_FIELDS
}
aggregated["reporting_workers"] = len(per_worker)
aggregated["per_worker"] = per_worker
return aggregated