import logging import sys import traceback import uuid import warnings from collections import namedtuple from datetime import datetime, timezone, timedelta from functools import total_ordering from typing import TYPE_CHECKING, Dict, List, Any, Callable, Optional, Tuple, Type, Union from redis import WatchError from .timeouts import BaseDeathPenalty, UnixSignalDeathPenalty if TYPE_CHECKING: from redis import Redis from redis.client import Pipeline from .job import Retry from .utils import as_text from .connections import resolve_connection from .defaults import DEFAULT_RESULT_TTL from .exceptions import DequeueTimeout, NoSuchJobError from .job import Job, JobStatus from .types import FunctionReferenceType, JobDependencyType from .serializers import resolve_serializer from .utils import backend_class, get_version, import_attribute, make_colorizer, parse_timeout, utcnow, compact green = make_colorizer('darkgreen') yellow = make_colorizer('darkyellow') blue = make_colorizer('darkblue') logger = logging.getLogger("rq.queue") class EnqueueData( namedtuple( 'EnqueueData', [ "func", "args", "kwargs", "timeout", "result_ttl", "ttl", "failure_ttl", "description", "job_id", "at_front", "meta", "retry", "on_success", "on_failure", ], ) ): """Helper type to use when calling enqueue_many NOTE: Does not support `depends_on` yet. """ __slots__ = () @total_ordering class Queue: job_class: Type['Job'] = Job death_penalty_class: Type[BaseDeathPenalty] = UnixSignalDeathPenalty DEFAULT_TIMEOUT: int = 180 # Default timeout seconds. redis_queue_namespace_prefix: str = 'rq:queue:' redis_queues_keys: str = 'rq:queues' @classmethod def all( cls, connection: Optional['Redis'] = None, job_class: Optional[Type['Job']] = None, serializer=None, death_penalty_class: Optional[Type[BaseDeathPenalty]] = None ) -> List['Queue']: """Returns an iterable of all Queues. Args: connection (Optional[Redis], optional): The Redis Connection. Defaults to None. job_class (Optional[Job], optional): The Job class to use. Defaults to None. serializer (optional): The serializer to use. Defaults to None. death_penalty_class (Optional[Job], optional): The Death Penalty class to use. Defaults to None. Returns: queues (List[Queue]): A list of all queues. """ connection = resolve_connection(connection) def to_queue(queue_key): return cls.from_queue_key( as_text(queue_key), connection=connection, job_class=job_class, serializer=serializer, death_penalty_class=death_penalty_class ) all_registerd_queues = connection.smembers(cls.redis_queues_keys) all_queues = [to_queue(rq_key) for rq_key in all_registerd_queues if rq_key] return all_queues @classmethod def from_queue_key( cls, queue_key: str, connection: Optional['Redis'] = None, job_class: Optional[Type['Job']] = None, serializer: Any = None, death_penalty_class: Optional[Type[BaseDeathPenalty]] = None, ) -> 'Queue': """Returns a Queue instance, based on the naming conventions for naming the internal Redis keys. Can be used to reverse-lookup Queues by their Redis keys. Args: queue_key (str): The queue key connection (Optional[Redis], optional): Redis connection. Defaults to None. job_class (Optional[Job], optional): Job class. Defaults to None. serializer (Any, optional): Serializer. Defaults to None. death_penalty_class (Optional[BaseDeathPenalty], optional): Death penalty class. Defaults to None. Raises: ValueError: If the queue_key doesn't start with the defined prefix Returns: queue (Queue): The Queue object """ prefix = cls.redis_queue_namespace_prefix if not queue_key.startswith(prefix): raise ValueError('Not a valid RQ queue key: {0}'.format(queue_key)) name = queue_key[len(prefix):] return cls(name, connection=connection, job_class=job_class, serializer=serializer, death_penalty_class=death_penalty_class) def __init__( self, name: str = 'default', default_timeout: Optional[int] = None, connection: Optional['Redis'] = None, is_async: bool = True, job_class: Union[str, Type['Job'], None] = None, serializer: Any = None, death_penalty_class: Type[BaseDeathPenalty] = UnixSignalDeathPenalty, **kwargs, ): """Initializes a Queue object. Args: name (str, optional): The queue name. Defaults to 'default'. default_timeout (Optional[int], optional): Queue's default timeout. Defaults to None. connection (Optional[Redis], optional): Redis connection. Defaults to None. is_async (bool, optional): Whether jobs should run "async" (using the worker). If `is_async` is false, jobs will run on the same process from where it was called. Defaults to True. job_class (Union[str, 'Job', optional): Job class or a string referencing the Job class path. Defaults to None. serializer (Any, optional): Serializer. Defaults to None. death_penalty_class (Type[BaseDeathPenalty, optional): Job class or a string referencing the Job class path. Defaults to UnixSignalDeathPenalty. """ self.connection = resolve_connection(connection) prefix = self.redis_queue_namespace_prefix self.name = name self._key = '{0}{1}'.format(prefix, name) self._default_timeout = parse_timeout(default_timeout) or self.DEFAULT_TIMEOUT self._is_async = is_async self.log = logger if 'async' in kwargs: self._is_async = kwargs['async'] warnings.warn('The `async` keyword is deprecated. Use `is_async` instead', DeprecationWarning) # override class attribute job_class if one was passed if job_class is not None: if isinstance(job_class, str): job_class = import_attribute(job_class) self.job_class = job_class self.death_penalty_class = death_penalty_class self.serializer = resolve_serializer(serializer) self.redis_server_version: Optional[Tuple[int, int, int]] = None def __len__(self): return self.count def __bool__(self): return True def __iter__(self): yield self def get_redis_server_version(self) -> Tuple[int, int, int]: """Return Redis server version of connection Returns: redis_version (Tuple): A tuple with the parsed Redis version (eg: (5,0,0)) """ if not self.redis_server_version: self.redis_server_version = get_version(self.connection) return self.redis_server_version @property def key(self): """Returns the Redis key for this Queue.""" return self._key @property def registry_cleaning_key(self): """Redis key used to indicate this queue has been cleaned.""" return 'rq:clean_registries:%s' % self.name @property def scheduler_pid(self) -> int: from rq.scheduler import RQScheduler pid = self.connection.get(RQScheduler.get_locking_key(self.name)) return int(pid.decode()) if pid is not None else None def acquire_cleaning_lock(self) -> bool: """Returns a boolean indicating whether a lock to clean this queue is acquired. A lock expires in 899 seconds (15 minutes - 1 second) Returns: lock_acquired (bool) """ lock_acquired = self.connection.set(self.registry_cleaning_key, 1, nx=1, ex=899) if not lock_acquired: return False return lock_acquired def empty(self): """Removes all messages on the queue. This is currently being done using a Lua script, which iterates all queue messages and deletes the jobs and it's dependents. It registers the Lua script and calls it. Even though is currently being returned, this is not strictly necessary. Returns: script (...): The Lua Script is called. """ script = """ local prefix = "{0}" local q = KEYS[1] local count = 0 while true do local job_id = redis.call("lpop", q) if job_id == false then break end -- Delete the relevant keys redis.call("del", prefix..job_id) redis.call("del", prefix..job_id..":dependents") count = count + 1 end return count """.format( self.job_class.redis_job_namespace_prefix ).encode( "utf-8" ) script = self.connection.register_script(script) return script(keys=[self.key]) def delete(self, delete_jobs: bool = True): """Deletes the queue. Args: delete_jobs (bool): If true, removes all the associated messages on the queue first. """ if delete_jobs: self.empty() with self.connection.pipeline() as pipeline: pipeline.srem(self.redis_queues_keys, self._key) pipeline.delete(self._key) pipeline.execute() def is_empty(self) -> bool: """Returns whether the current queue is empty. Returns: is_empty (bool): Whether the queue is empty """ return self.count == 0 @property def is_async(self): """Returns whether the current queue is async.""" return bool(self._is_async) def fetch_job(self, job_id: str) -> Optional['Job']: """Fetch a single job by Job ID. If the job key is not found, will run the `remove` method, to exclude the key. If the job has the same name as as the current job origin, returns the Job Args: job_id (str): The Job ID Returns: job (Optional[Job]): The job if found """ try: job = self.job_class.fetch(job_id, connection=self.connection, serializer=self.serializer) except NoSuchJobError: self.remove(job_id) else: if job.origin == self.name: return job def get_job_position(self, job_or_id: Union['Job', str]) -> Optional[int]: """Returns the position of a job within the queue Using Redis before 6.0.6 and redis-py before 3.5.4 has a complexity of worse than O(N) and should not be used for very long job queues. Redis and redis-py version afterwards should support the LPOS command handling job positions within Redis c implementation. Args: job_or_id (Union[Job, str]): The Job instance or Job ID Returns: _type_: _description_ """ job_id = job_or_id.id if isinstance(job_or_id, self.job_class) else job_or_id if self.get_redis_server_version() >= (6, 0, 6): try: return self.connection.lpos(self.key, job_id) except AttributeError: # not yet implemented by redis-py pass if job_id in self.job_ids: return self.job_ids.index(job_id) return None def get_job_ids(self, offset: int = 0, length: int = -1) -> List[str]: """Returns a slice of job IDs in the queue. Args: offset (int, optional): The offset. Defaults to 0. length (int, optional): The slice length. Defaults to -1 (last element). Returns: _type_: _description_ """ start = offset if length >= 0: end = offset + (length - 1) else: end = length job_ids = [as_text(job_id) for job_id in self.connection.lrange(self.key, start, end)] self.log.debug('Getting jobs for queue %s: %d found.', green(self.name), len(job_ids)) return job_ids def get_jobs(self, offset: int = 0, length: int = -1) -> List['Job']: """Returns a slice of jobs in the queue. Args: offset (int, optional): The offset. Defaults to 0. length (int, optional): The slice length. Defaults to -1. Returns: _type_: _description_ """ job_ids = self.get_job_ids(offset, length) return compact([self.fetch_job(job_id) for job_id in job_ids]) @property def job_ids(self) -> List[str]: """Returns a list of all job IDS in the queue.""" return self.get_job_ids() @property def jobs(self) -> List['Job']: """Returns a list of all (valid) jobs in the queue.""" return self.get_jobs() @property def count(self) -> int: """Returns a count of all messages in the queue.""" return self.connection.llen(self.key) @property def failed_job_registry(self): """Returns this queue's FailedJobRegistry.""" from rq.registry import FailedJobRegistry return FailedJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) @property def started_job_registry(self): """Returns this queue's StartedJobRegistry.""" from rq.registry import StartedJobRegistry return StartedJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) @property def finished_job_registry(self): """Returns this queue's FinishedJobRegistry.""" from rq.registry import FinishedJobRegistry # TODO: Why was job_class only ommited here before? Was it intentional? return FinishedJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) @property def deferred_job_registry(self): """Returns this queue's DeferredJobRegistry.""" from rq.registry import DeferredJobRegistry return DeferredJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) @property def scheduled_job_registry(self): """Returns this queue's ScheduledJobRegistry.""" from rq.registry import ScheduledJobRegistry return ScheduledJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) @property def canceled_job_registry(self): """Returns this queue's CanceledJobRegistry.""" from rq.registry import CanceledJobRegistry return CanceledJobRegistry(queue=self, job_class=self.job_class, serializer=self.serializer) def remove(self, job_or_id: Union['Job', str], pipeline: Optional['Pipeline'] = None): """Removes Job from queue, accepts either a Job instance or ID. Args: job_or_id (Union[Job, str]): The Job instance or Job ID string. pipeline (Optional[Pipeline], optional): The Redis Pipeline. Defaults to None. Returns: _type_: _description_ """ job_id = job_or_id.id if isinstance(job_or_id, self.job_class) else job_or_id if pipeline is not None: return pipeline.lrem(self.key, 1, job_id) return self.connection.lrem(self.key, 1, job_id) def compact(self): """Removes all "dead" jobs from the queue by cycling through it, while guaranteeing FIFO semantics. """ COMPACT_QUEUE = '{0}_compact:{1}'.format(self.redis_queue_namespace_prefix, uuid.uuid4()) # noqa self.connection.rename(self.key, COMPACT_QUEUE) while True: job_id = as_text(self.connection.lpop(COMPACT_QUEUE)) if job_id is None: break if self.job_class.exists(job_id, self.connection): self.connection.rpush(self.key, job_id) def push_job_id(self, job_id: str, pipeline: Optional['Pipeline'] = None, at_front: bool = False): """Pushes a job ID on the corresponding Redis queue. 'at_front' allows you to push the job onto the front instead of the back of the queue Args: job_id (str): The Job ID pipeline (Optional[Pipeline], optional): The Redis Pipeline to use. Defaults to None. at_front (bool, optional): Whether to push the job to front of the queue. Defaults to False. """ connection = pipeline if pipeline is not None else self.connection if at_front: result = connection.lpush(self.key, job_id) else: result = connection.rpush(self.key, job_id) self.log.debug('Pushed job %s into %s, %s job(s) are in queue.', blue(job_id), green(self.name), result) def create_job( self, func: 'FunctionReferenceType', args: Union[Tuple, List, None] = None, kwargs: Optional[Dict] = None, timeout: Optional[int] = None, result_ttl: Optional[int] = None, ttl: Optional[int] = None, failure_ttl: Optional[int] = None, description: Optional[str] = None, depends_on: Optional['JobDependencyType'] = None, job_id: Optional[str] = None, meta: Optional[Dict] = None, status: JobStatus = JobStatus.QUEUED, retry: Optional['Retry'] = None, *, on_success: Optional[Callable] = None, on_failure: Optional[Callable] = None, ) -> Job: """Creates a job based on parameters given Args: func (FunctionReferenceType): The function referce: a callable or the path. args (Union[Tuple, List, None], optional): The `*args` to pass to the function. Defaults to None. kwargs (Optional[Dict], optional): The `**kwargs` to pass to the function. Defaults to None. timeout (Optional[int], optional): Function timeout. Defaults to None. result_ttl (Optional[int], optional): Result time to live. Defaults to None. ttl (Optional[int], optional): Time to live. Defaults to None. failure_ttl (Optional[int], optional): Failure time to live. Defaults to None. description (Optional[str], optional): The description. Defaults to None. depends_on (Optional[JobDependencyType], optional): The job dependencies. Defaults to None. job_id (Optional[str], optional): Job ID. Defaults to None. meta (Optional[Dict], optional): Job metadata. Defaults to None. status (JobStatus, optional): Job status. Defaults to JobStatus.QUEUED. retry (Optional[Retry], optional): The Retry Object. Defaults to None. on_success (Optional[Callable], optional): On success callable. Defaults to None. on_failure (Optional[Callable], optional): On failure callable. Defaults to None. Raises: ValueError: If the timeout is 0 ValueError: If the job TTL is 0 or negative Returns: Job: The created job """ timeout = parse_timeout(timeout) if timeout is None: timeout = self._default_timeout elif timeout == 0: raise ValueError('0 timeout is not allowed. Use -1 for infinite timeout') result_ttl = parse_timeout(result_ttl) failure_ttl = parse_timeout(failure_ttl) ttl = parse_timeout(ttl) if ttl is not None and ttl <= 0: raise ValueError('Job ttl must be greater than 0') job = self.job_class.create( func, args=args, kwargs=kwargs, connection=self.connection, result_ttl=result_ttl, ttl=ttl, failure_ttl=failure_ttl, status=status, description=description, depends_on=depends_on, timeout=timeout, id=job_id, origin=self.name, meta=meta, serializer=self.serializer, on_success=on_success, on_failure=on_failure, ) if retry: job.retries_left = retry.max job.retry_intervals = retry.intervals return job def setup_dependencies(self, job: 'Job', pipeline: Optional['Pipeline'] = None) -> 'Job': """If a _dependent_ job depends on any unfinished job, register all the _dependent_ job's dependencies instead of enqueueing it. `Job#fetch_dependencies` sets WATCH on all dependencies. If WatchError is raised in the when the pipeline is executed, that means something else has modified either the set of dependencies or the status of one of them. In this case, we simply retry. Args: job (Job): The job pipeline (Optional[Pipeline], optional): The Redis Pipeline. Defaults to None. Returns: job (Job): The Job """ if len(job._dependency_ids) > 0: orig_status = job.get_status(refresh=False) pipe = pipeline if pipeline is not None else self.connection.pipeline() while True: try: # Also calling watch even if caller # passed in a pipeline since Queue#create_job # is called from within this method. pipe.watch(job.dependencies_key) dependencies = job.fetch_dependencies(watch=True, pipeline=pipe) pipe.multi() for dependency in dependencies: if dependency.get_status(refresh=False) != JobStatus.FINISHED: # NOTE: If the following code changes local variables, those values probably have # to be set back to their original values in the handling of WatchError below! job.set_status(JobStatus.DEFERRED, pipeline=pipe) job.register_dependency(pipeline=pipe) job.save(pipeline=pipe) job.cleanup(ttl=job.ttl, pipeline=pipe) if pipeline is None: pipe.execute() return job break except WatchError: if pipeline is None: # The call to job.set_status(JobStatus.DEFERRED, pipeline=pipe) above has changed the # internal "_status". We have to reset it to its original value (probably QUEUED), so # if during the next run no unfinished dependencies exist anymore, the job gets # enqueued correctly by enqueue_call(). job._status = orig_status continue else: # if pipeline comes from caller, re-raise to them raise elif pipeline is not None: pipeline.multi() # Ensure pipeline in multi mode before returning to caller return job def enqueue_call( self, func: 'FunctionReferenceType', args: Union[Tuple, List, None] = None, kwargs: Optional[Dict] = None, timeout: Optional[int] = None, result_ttl: Optional[int] = None, ttl: Optional[int] = None, failure_ttl: Optional[int] = None, description: Optional[str] = None, depends_on: Optional['JobDependencyType'] = None, job_id: Optional[str] = None, at_front: bool = False, meta: Optional[Dict] = None, retry: Optional['Retry'] = None, on_success: Optional[Callable[..., Any]] = None, on_failure: Optional[Callable[..., Any]] = None, pipeline: Optional['Pipeline'] = None, ) -> Job: """Creates a job to represent the delayed function call and enqueues it. It is much like `.enqueue()`, except that it takes the function's args and kwargs as explicit arguments. Any kwargs passed to this function contain options for RQ itself. Args: func (FunctionReferenceType): The reference to the function args (Union[Tuple, List, None], optional): THe `*args` to pass to the function. Defaults to None. kwargs (Optional[Dict], optional): THe `**kwargs` to pass to the function. Defaults to None. timeout (Optional[int], optional): Function timeout. Defaults to None. result_ttl (Optional[int], optional): Result time to live. Defaults to None. ttl (Optional[int], optional): Time to live. Defaults to None. failure_ttl (Optional[int], optional): Failure time to live. Defaults to None. description (Optional[str], optional): The job description. Defaults to None. depends_on (Optional[JobDependencyType], optional): The job dependencies. Defaults to None. job_id (Optional[str], optional): The job ID. Defaults to None. at_front (bool, optional): Whether to enqueue the job at the front. Defaults to False. meta (Optional[Dict], optional): Metadata to attach to the job. Defaults to None. retry (Optional[Retry], optional): Retry object. Defaults to None. on_success (Optional[Callable[..., Any]], optional): Callable for on success. Defaults to None. on_failure (Optional[Callable[..., Any]], optional): Callable for on failure. Defaults to None. pipeline (Optional[Pipeline], optional): The Redis Pipeline. Defaults to None. Returns: Job: The enqueued Job """ job = self.create_job( func, args=args, kwargs=kwargs, result_ttl=result_ttl, ttl=ttl, failure_ttl=failure_ttl, description=description, depends_on=depends_on, job_id=job_id, meta=meta, status=JobStatus.QUEUED, timeout=timeout, retry=retry, on_success=on_success, on_failure=on_failure, ) return self.enqueue_job(job, pipeline=pipeline, at_front=at_front) @staticmethod def prepare_data( func: 'FunctionReferenceType', args: Union[Tuple, List, None] = None, kwargs: Optional[Dict] = None, timeout: Optional[int] = None, result_ttl: Optional[int] = None, ttl: Optional[int] = None, failure_ttl: Optional[int] = None, description: Optional[str] = None, job_id: Optional[str] = None, at_front: bool = False, meta: Optional[Dict] = None, retry: Optional['Retry'] = None, on_success: Optional[Callable] = None, on_failure: Optional[Callable] = None, ) -> EnqueueData: """Need this till support dropped for python_version < 3.7, where defaults can be specified for named tuples And can keep this logic within EnqueueData Args: func (FunctionReferenceType): The reference to the function args (Union[Tuple, List, None], optional): THe `*args` to pass to the function. Defaults to None. kwargs (Optional[Dict], optional): THe `**kwargs` to pass to the function. Defaults to None. timeout (Optional[int], optional): Function timeout. Defaults to None. result_ttl (Optional[int], optional): Result time to live. Defaults to None. ttl (Optional[int], optional): Time to live. Defaults to None. failure_ttl (Optional[int], optional): Failure time to live. Defaults to None. description (Optional[str], optional): The job description. Defaults to None. job_id (Optional[str], optional): The job ID. Defaults to None. at_front (bool, optional): Whether to enqueue the job at the front. Defaults to False. meta (Optional[Dict], optional): Metadata to attach to the job. Defaults to None. retry (Optional[Retry], optional): Retry object. Defaults to None. on_success (Optional[Callable[..., Any]], optional): Callable for on success. Defaults to None. on_failure (Optional[Callable[..., Any]], optional): Callable for on failure. Defaults to None. Returns: EnqueueData: The EnqueueData """ return EnqueueData( func, args, kwargs, timeout, result_ttl, ttl, failure_ttl, description, job_id, at_front, meta, retry, on_success, on_failure, ) def enqueue_many(self, job_datas: List['EnqueueData'], pipeline: Optional['Pipeline'] = None) -> List[Job]: """Creates multiple jobs (created via `Queue.prepare_data` calls) to represent the delayed function calls and enqueues them. Args: job_datas (List['EnqueueData']): A List of job data pipeline (Optional[Pipeline], optional): The Redis Pipeline. Defaults to None. Returns: List[Job]: A list of enqueued jobs """ pipe = pipeline if pipeline is not None else self.connection.pipeline() jobs = [ self._enqueue_job( self.create_job( job_data.func, args=job_data.args, kwargs=job_data.kwargs, result_ttl=job_data.result_ttl, ttl=job_data.ttl, failure_ttl=job_data.failure_ttl, description=job_data.description, depends_on=None, job_id=job_data.job_id, meta=job_data.meta, status=JobStatus.QUEUED, timeout=job_data.timeout, retry=job_data.retry, on_success=job_data.on_success, on_failure=job_data.on_failure, ), pipeline=pipe, at_front=job_data.at_front, ) for job_data in job_datas ] if pipeline is None: pipe.execute() return jobs def run_job(self, job: 'Job') -> Job: """Run the job Args: job (Job): The job to run Returns: Job: _description_ """ job.perform() result_ttl = job.get_result_ttl(default_ttl=DEFAULT_RESULT_TTL) with self.connection.pipeline() as pipeline: job._handle_success(result_ttl=result_ttl, pipeline=pipeline) job.cleanup(result_ttl, pipeline=pipeline) pipeline.execute() return job @classmethod def parse_args(cls, f: 'FunctionReferenceType', *args, **kwargs): """ Parses arguments passed to `queue.enqueue()` and `queue.enqueue_at()` The function argument `f` may be any of the following: * A reference to a function * A reference to an object's instance method * A string, representing the location of a function (must be meaningful to the import context of the workers) Args: f (FunctionReferenceType): The function reference args (*args): function args kwargs (*kwargs): function kargs """ if not isinstance(f, str) and f.__module__ == '__main__': raise ValueError('Functions from the __main__ module cannot be processed ' 'by workers') # Detect explicit invocations, i.e. of the form: # q.enqueue(foo, args=(1, 2), kwargs={'a': 1}, job_timeout=30) timeout = kwargs.pop('job_timeout', None) description = kwargs.pop('description', None) result_ttl = kwargs.pop('result_ttl', None) ttl = kwargs.pop('ttl', None) failure_ttl = kwargs.pop('failure_ttl', None) depends_on = kwargs.pop('depends_on', None) job_id = kwargs.pop('job_id', None) at_front = kwargs.pop('at_front', False) meta = kwargs.pop('meta', None) retry = kwargs.pop('retry', None) on_success = kwargs.pop('on_success', None) on_failure = kwargs.pop('on_failure', None) pipeline = kwargs.pop('pipeline', None) if 'args' in kwargs or 'kwargs' in kwargs: assert args == (), 'Extra positional arguments cannot be used when using explicit args and kwargs' # noqa args = kwargs.pop('args', None) kwargs = kwargs.pop('kwargs', None) return ( f, timeout, description, result_ttl, ttl, failure_ttl, depends_on, job_id, at_front, meta, retry, on_success, on_failure, pipeline, args, kwargs, ) def enqueue(self, f: 'FunctionReferenceType', *args, **kwargs) -> 'Job': """Creates a job to represent the delayed function call and enqueues it. Receives the same parameters accepted by the `enqueue_call` method. Args: f (FunctionReferenceType): The function reference args (*args): function args kwargs (*kwargs): function kargs Returns: job (Job): The created Job """ ( f, timeout, description, result_ttl, ttl, failure_ttl, depends_on, job_id, at_front, meta, retry, on_success, on_failure, pipeline, args, kwargs, ) = Queue.parse_args(f, *args, **kwargs) return self.enqueue_call( func=f, args=args, kwargs=kwargs, timeout=timeout, result_ttl=result_ttl, ttl=ttl, failure_ttl=failure_ttl, description=description, depends_on=depends_on, job_id=job_id, at_front=at_front, meta=meta, retry=retry, on_success=on_success, on_failure=on_failure, pipeline=pipeline, ) def enqueue_at(self, datetime: datetime, f, *args, **kwargs): """Schedules a job to be enqueued at specified time Args: datetime (datetime): _description_ f (_type_): _description_ Returns: _type_: _description_ """ ( f, timeout, description, result_ttl, ttl, failure_ttl, depends_on, job_id, at_front, meta, retry, on_success, on_failure, pipeline, args, kwargs, ) = Queue.parse_args(f, *args, **kwargs) job = self.create_job( f, status=JobStatus.SCHEDULED, args=args, kwargs=kwargs, timeout=timeout, result_ttl=result_ttl, ttl=ttl, failure_ttl=failure_ttl, description=description, depends_on=depends_on, job_id=job_id, meta=meta, retry=retry, on_success=on_success, on_failure=on_failure, ) if at_front: job.enqueue_at_front = True return self.schedule_job(job, datetime, pipeline=pipeline) def schedule_job(self, job: 'Job', datetime: datetime, pipeline: Optional['Pipeline'] = None): """Puts job on ScheduledJobRegistry Args: job (Job): _description_ datetime (datetime): _description_ pipeline (Optional[Pipeline], optional): _description_. Defaults to None. Returns: _type_: _description_ """ from .registry import ScheduledJobRegistry registry = ScheduledJobRegistry(queue=self) pipe = pipeline if pipeline is not None else self.connection.pipeline() # Add Queue key set pipe.sadd(self.redis_queues_keys, self.key) job.save(pipeline=pipe) registry.schedule(job, datetime, pipeline=pipe) if pipeline is None: pipe.execute() return job def enqueue_in(self, time_delta: timedelta, func: 'FunctionReferenceType', *args, **kwargs) -> 'Job': """Schedules a job to be executed in a given `timedelta` object Args: time_delta (timedelta): The timedelta object func (FunctionReferenceType): The function reference Returns: job (Job): The enqueued Job """ return self.enqueue_at(datetime.now(timezone.utc) + time_delta, func, *args, **kwargs) def enqueue_job(self, job: 'Job', pipeline: Optional['Pipeline'] = None, at_front: bool = False) -> Job: """Enqueues a job for delayed execution checking dependencies. Args: job (Job): The job to enqueue pipeline (Optional[Pipeline], optional): The Redis pipeline to use. Defaults to None. at_front (bool, optional): Whether should enqueue at the front of the queue. Defaults to False. Returns: Job: The enqued job """ job.origin = self.name job = self.setup_dependencies(job, pipeline=pipeline) # If we do not depend on an unfinished job, enqueue the job. if job.get_status(refresh=False) != JobStatus.DEFERRED: return self._enqueue_job(job, pipeline=pipeline, at_front=at_front) return job def _enqueue_job(self, job: 'Job', pipeline: Optional['Pipeline'] = None, at_front: bool = False) -> Job: """Enqueues a job for delayed execution without checking dependencies. If Queue is instantiated with is_async=False, job is executed immediately. Args: job (Job): The job to enqueue pipeline (Optional[Pipeline], optional): The Redis pipeline to use. Defaults to None. at_front (bool, optional): Whether should enqueue at the front of the queue. Defaults to False. Returns: Job: The enqued job """ pipe = pipeline if pipeline is not None else self.connection.pipeline() # Add Queue key set pipe.sadd(self.redis_queues_keys, self.key) job.redis_server_version = self.get_redis_server_version() job.set_status(JobStatus.QUEUED, pipeline=pipe) job.origin = self.name job.enqueued_at = utcnow() if job.timeout is None: job.timeout = self._default_timeout job.save(pipeline=pipe) job.cleanup(ttl=job.ttl, pipeline=pipe) if self._is_async: self.push_job_id(job.id, pipeline=pipe, at_front=at_front) if pipeline is None: pipe.execute() if not self._is_async: job = self.run_sync(job) return job def run_sync(self, job: 'Job') -> 'Job': """Run a job synchronously, meaning on the same process the method was called. Args: job (Job): The job to run Returns: Job: The job instance """ with self.connection.pipeline() as pipeline: job.prepare_for_execution('sync', pipeline) try: job = self.run_job(job) except: # noqa with self.connection.pipeline() as pipeline: job.set_status(JobStatus.FAILED, pipeline=pipeline) exc_string = ''.join(traceback.format_exception(*sys.exc_info())) job._handle_failure(exc_string, pipeline) pipeline.execute() if job.failure_callback: job.failure_callback(job, self.connection, *sys.exc_info()) # type: ignore else: if job.success_callback: job.success_callback(job, self.connection, job.return_value()) # type: ignore return job def enqueue_dependents( self, job: 'Job', pipeline: Optional['Pipeline'] = None, exclude_job_id: Optional[str] = None ): """Enqueues all jobs in the given job's dependents set and clears it. When called without a pipeline, this method uses WATCH/MULTI/EXEC. If you pass a pipeline, only MULTI is called. The rest is up to the caller. Args: job (Job): The Job to enqueue the dependents pipeline (Optional[Pipeline], optional): The Redis Pipeline. Defaults to None. exclude_job_id (Optional[str], optional): Whether to exclude the job id. Defaults to None. """ from .registry import DeferredJobRegistry pipe = pipeline if pipeline is not None else self.connection.pipeline() dependents_key = job.dependents_key while True: try: # if a pipeline is passed, the caller is responsible for calling WATCH # to ensure all jobs are enqueued if pipeline is None: pipe.watch(dependents_key) dependent_job_ids = {as_text(_id) for _id in pipe.smembers(dependents_key)} # There's no dependents if not dependent_job_ids: break jobs_to_enqueue = [ dependent_job for dependent_job in self.job_class.fetch_many( dependent_job_ids, connection=self.connection, serializer=self.serializer ) if dependent_job and dependent_job.dependencies_are_met( parent_job=job, pipeline=pipe, exclude_job_id=exclude_job_id, ) ] pipe.multi() if not jobs_to_enqueue: break for dependent in jobs_to_enqueue: enqueue_at_front = dependent.enqueue_at_front or False registry = DeferredJobRegistry( dependent.origin, self.connection, job_class=self.job_class, serializer=self.serializer ) registry.remove(dependent, pipeline=pipe) if dependent.origin == self.name: self._enqueue_job(dependent, pipeline=pipe, at_front=enqueue_at_front) else: queue = self.__class__(name=dependent.origin, connection=self.connection) queue._enqueue_job(dependent, pipeline=pipe, at_front=enqueue_at_front) # Only delete dependents_key if all dependents have been enqueued if len(jobs_to_enqueue) == len(dependent_job_ids): pipe.delete(dependents_key) else: enqueued_job_ids = [job.id for job in jobs_to_enqueue] pipe.srem(dependents_key, *enqueued_job_ids) if pipeline is None: pipe.execute() break except WatchError: if pipeline is None: continue else: # if the pipeline comes from the caller, we re-raise the # exception as it it the responsibility of the caller to # handle it raise def pop_job_id(self) -> Optional[str]: """Pops a given job ID from this Redis queue. Returns: job_id (str): The job id """ return as_text(self.connection.lpop(self.key)) @classmethod def lpop(cls, queue_keys: List[str], timeout: Optional[int], connection: Optional['Redis'] = None): """Helper method. Intermediate method to abstract away from some Redis API details, where LPOP accepts only a single key, whereas BLPOP accepts multiple. So if we want the non-blocking LPOP, we need to iterate over all queues, do individual LPOPs, and return the result. Until Redis receives a specific method for this, we'll have to wrap it this way. The timeout parameter is interpreted as follows: None - non-blocking (return immediately) > 0 - maximum number of seconds to block Args: queue_keys (_type_): _description_ timeout (Optional[int]): _description_ connection (Optional[Redis], optional): _description_. Defaults to None. Raises: ValueError: If timeout of 0 was passed DequeueTimeout: BLPOP Timeout Returns: _type_: _description_ """ connection = resolve_connection(connection) if timeout is not None: # blocking variant if timeout == 0: raise ValueError('RQ does not support indefinite timeouts. Please pick a timeout value > 0') colored_queues = ''.join(map(str, [green(str(queue)) for queue in queue_keys])) logger.debug(f"Starting BLPOP operation for queues {colored_queues} with timeout of {timeout}") result = connection.blpop(queue_keys, timeout) if result is None: logger.debug(f"BLPOP Timeout, no jobs found on queues {colored_queues}") raise DequeueTimeout(timeout, queue_keys) queue_key, job_id = result return queue_key, job_id else: # non-blocking variant for queue_key in queue_keys: blob = connection.lpop(queue_key) if blob is not None: return queue_key, blob return None @classmethod def dequeue_any( cls, queues: List['Queue'], timeout: Optional[int], connection: Optional['Redis'] = None, job_class: Optional['Job'] = None, serializer: Any = None, death_penalty_class: Optional[Type[BaseDeathPenalty]] = None, ) -> Tuple['Job', 'Queue']: """Class method returning the job_class instance at the front of the given set of Queues, where the order of the queues is important. When all of the Queues are empty, depending on the `timeout` argument, either blocks execution of this function for the duration of the timeout or until new messages arrive on any of the queues, or returns None. See the documentation of cls.lpop for the interpretation of timeout. Args: queues (List[Queue]): List of queue objects timeout (Optional[int]): Timeout for the LPOP connection (Optional[Redis], optional): Redis Connection. Defaults to None. job_class (Optional[Type[Job]], optional): The job class. Defaults to None. serializer (Any, optional): Serializer to use. Defaults to None. death_penalty_class (Optional[Type[BaseDeathPenalty]], optional): The death penalty class. Defaults to None. Raises: e: Any exception Returns: job, queue (Tuple[Job, Queue]): A tuple of Job, Queue """ job_class: Job = backend_class(cls, 'job_class', override=job_class) while True: queue_keys = [q.key for q in queues] result = cls.lpop(queue_keys, timeout, connection=connection) if result is None: return None queue_key, job_id = map(as_text, result) queue = cls.from_queue_key(queue_key, connection=connection, job_class=job_class, serializer=serializer, death_penalty_class=death_penalty_class) try: job = job_class.fetch(job_id, connection=connection, serializer=serializer) except NoSuchJobError: # Silently pass on jobs that don't exist (anymore), # and continue in the look continue except Exception as e: # Attach queue information on the exception for improved error # reporting e.job_id = job_id e.queue = queue raise e return job, queue return None, None # Total ordering definition (the rest of the required Python methods are # auto-generated by the @total_ordering decorator) def __eq__(self, other): # noqa if not isinstance(other, Queue): raise TypeError('Cannot compare queues to other objects') return self.name == other.name def __lt__(self, other): if not isinstance(other, Queue): raise TypeError('Cannot compare queues to other objects') return self.name < other.name def __hash__(self): # pragma: no cover return hash(self.name) def __repr__(self): # noqa # pragma: no cover return '{0}({1!r})'.format(self.__class__.__name__, self.name) def __str__(self): return '<{0} {1}>'.format(self.__class__.__name__, self.name)