# # Copyright (C) 2016 Codethink Limited # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library. If not, see . # # Authors: # Tristan Van Berkom # Jürg Billeter # System imports import os from collections import deque from enum import Enum import traceback # Local imports from ..jobs import ElementJob, JobStatus from ..resources import ResourceType # BuildStream toplevel imports from ..._exceptions import BstError, set_last_task_error from ..._message import Message, MessageType # Queue status for a given element # # class QueueStatus(Enum): # The element is waiting for dependencies. WAIT = 1 # The element can skip this queue. SKIP = 2 # The element is ready for processing in this queue. READY = 3 # Queue() # # Args: # scheduler (Scheduler): The Scheduler # class Queue(): # These should be overridden on class data of of concrete Queue implementations action_name = None complete_name = None resources = [] # Resources this queues' jobs want def __init__(self, scheduler): # # Public members # self.failed_elements = [] # List of failed elements, for the frontend self.processed_elements = [] # List of processed elements, for the frontend self.skipped_elements = [] # List of skipped elements, for the frontend # # Private members # self._scheduler = scheduler self._resources = scheduler.resources # Shared resource pool self._wait_queue = deque() # Ready / Waiting elements self._done_queue = deque() # Processed / Skipped elements self._max_retries = 0 # Assert the subclass has setup class data assert self.action_name is not None assert self.complete_name is not None if ResourceType.UPLOAD in self.resources or ResourceType.DOWNLOAD in self.resources: self._max_retries = scheduler.context.sched_network_retries ##################################################### # Abstract Methods for Queue implementations # ##################################################### # process() # # Abstract method for processing an element # # Args: # element (Element): An element to process # # Returns: # (any): An optional something to be returned # for every element successfully processed # # def process(self, element): pass # status() # # Abstract method for reporting the status of an element. # # Args: # element (Element): An element to process # # Returns: # (QueueStatus): The element status # def status(self, element): return QueueStatus.READY # done() # # Abstract method for handling a successful job completion. # # Args: # job (Job): The job which completed processing # element (Element): The element which completed processing # result (any): The return value of the process() implementation # status (JobStatus): The return status of the Job # def done(self, job, element, result, status): pass ##################################################### # Scheduler / Pipeline facing APIs # ##################################################### # enqueue() # # Enqueues some elements # # Args: # elts (list): A list of Elements # def enqueue(self, elts): if not elts: return # Place skipped elements on the done queue right away. # # The remaining ready and waiting elements must remain in the # same queue, and ready status must be determined at the moment # which the scheduler is asking for the next job. # skip = [elt for elt in elts if self.status(elt) == QueueStatus.SKIP] wait = [elt for elt in elts if elt not in skip] self.skipped_elements.extend(skip) # Public record of skipped elements self._done_queue.extend(skip) # Elements to be processed self._wait_queue.extend(wait) # Elements eligible to be dequeued # dequeue() # # A generator which dequeues the elements which # are ready to exit the queue. # # Yields: # (Element): Elements being dequeued # def dequeue(self): while self._done_queue: yield self._done_queue.popleft() # dequeue_ready() # # Reports whether any elements can be promoted to other queues # # Returns: # (bool): Whether there are elements ready # def dequeue_ready(self): return any(self._done_queue) # harvest_jobs() # # Process elements in the queue, moving elements which were enqueued # into the dequeue pool, and creating as many jobs for which resources # can be reserved. # # Returns: # ([Job]): A list of jobs which can be run now # def harvest_jobs(self): unready = [] ready = [] while self._wait_queue: if not self._resources.reserve(self.resources, peek=True): break element = self._wait_queue.popleft() status = self.status(element) if status == QueueStatus.WAIT: unready.append(element) elif status == QueueStatus.SKIP: self._done_queue.append(element) self.skipped_elements.append(element) else: reserved = self._resources.reserve(self.resources) assert reserved ready.append(element) self._wait_queue.extendleft(unready) return [ ElementJob(self._scheduler, self.action_name, self._element_log_path(element), element=element, queue=self, action_cb=self.process, complete_cb=self._job_done, max_retries=self._max_retries) for element in ready ] ##################################################### # Private Methods # ##################################################### # _update_workspaces() # # Updates and possibly saves the workspaces in the # main data model in the main process after a job completes. # # Args: # element (Element): The element which completed # job (Job): The job which completed # def _update_workspaces(self, element, job): workspace_dict = None if job.child_data: workspace_dict = job.child_data.get('workspace', None) # Handle any workspace modifications now # if workspace_dict: context = element._get_context() workspaces = context.get_workspaces() if workspaces.update_workspace(element._get_full_name(), workspace_dict): try: workspaces.save_config() except BstError as e: self._message(element, MessageType.ERROR, "Error saving workspaces", detail=str(e)) except Exception as e: # pylint: disable=broad-except self._message(element, MessageType.BUG, "Unhandled exception while saving workspaces", detail=traceback.format_exc()) # _job_done() # # A callback reported by the Job() when a job completes # # This will call the Queue implementation specific Queue.done() # implementation and trigger the scheduler to reschedule. # # See the Job object for an explanation of the call signature # def _job_done(self, job, element, status, result): # Now release the resources we reserved # self._resources.release(self.resources) # Update values that need to be synchronized in the main task # before calling any queue implementation self._update_workspaces(element, job) # Give the result of the job to the Queue implementor, # and determine if it should be considered as processed # or skipped. try: self.done(job, element, result, status) except BstError as e: # Report error and mark as failed # self._message(element, MessageType.ERROR, "Post processing error", detail=str(e)) self.failed_elements.append(element) # Treat this as a task error as it's related to a task # even though it did not occur in the task context # # This just allows us stronger testing capability # set_last_task_error(e.domain, e.reason) except Exception as e: # pylint: disable=broad-except # Report unhandled exceptions and mark as failed # self._message(element, MessageType.BUG, "Unhandled exception in post processing", detail=traceback.format_exc()) self.failed_elements.append(element) else: # All elements get placed on the done queue for later processing. self._done_queue.append(element) # These lists are for bookkeeping purposes for the UI and logging. if status == JobStatus.SKIPPED or job.get_terminated(): self.skipped_elements.append(element) elif status == JobStatus.OK: self.processed_elements.append(element) else: self.failed_elements.append(element) # Convenience wrapper for Queue implementations to send # a message for the element they are processing def _message(self, element, message_type, brief, **kwargs): context = element._get_context() message = Message(element._get_unique_id(), message_type, brief, **kwargs) context.message(message) def _element_log_path(self, element): project = element._get_project() key = element._get_display_key()[1] action = self.action_name.lower() logfile = "{key}-{action}".format(key=key, action=action) return os.path.join(project.name, element.normal_name, logfile)