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117 lines
3 KiB
Python
117 lines
3 KiB
Python
from common.exceptions import TaskListError
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import logging
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log = logging.getLogger(__name__)
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class TaskList(object):
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def __init__(self):
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self.tasks = set()
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self.tasks_completed = []
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def add(self, *args):
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self.tasks.update(args)
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def remove(self, task):
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self.tasks.discard(self.get(task))
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def replace(self, task, replacement):
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self.remove(task)
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self.add(replacement)
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def get(self, ref):
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return next(task for task in self.tasks if type(task) is ref)
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def run(self, bootstrap_info):
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task_list = self.create_list(self.tasks)
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log.debug('Tasklist:\n\t{list}'.format(list='\n\t'.join(repr(task) for task in task_list)))
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for task in task_list:
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if hasattr(task, 'description'):
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log.info(task.description)
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else:
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log.info('Running {task}'.format(task=task))
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task.run(bootstrap_info)
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self.tasks_completed.append(task)
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def create_list(self, tasks):
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from common.phases import order
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graph = {}
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for task in tasks:
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graph[task] = []
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graph[task].extend([self.get(succ) for succ in task.before])
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graph[task].extend([succ for succ in tasks if type(task) in succ.after])
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succeeding_phases = order[order.index(task.phase)+1:]
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graph[task].extend([succ for succ in tasks if succ.phase in succeeding_phases])
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components = self.strongly_connected_components(graph)
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cycles_found = 0
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for component in components:
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if len(component) > 1:
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cycles_found += 1
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log.debug('Cycle: {list}\n'.format(list=', '.join(repr(task) for task in component)))
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if cycles_found > 0:
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msg = ('{0} cycles were found in the tasklist, '
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'consult the logfile for more information.'.format(cycles_found))
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raise TaskListError(msg)
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sorted_tasks = self.topological_sort(graph)
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return sorted_tasks
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def strongly_connected_components(self, graph):
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# Source: http://www.logarithmic.net/pfh-files/blog/01208083168/sort.py
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# Find the strongly connected components in a graph using Tarjan's algorithm.
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# graph should be a dictionary mapping node names to lists of successor nodes.
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result = []
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stack = []
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low = {}
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def visit(node):
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if node in low:
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return
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num = len(low)
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low[node] = num
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stack_pos = len(stack)
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stack.append(node)
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for successor in graph[node]:
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visit(successor)
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low[node] = min(low[node], low[successor])
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if num == low[node]:
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component = tuple(stack[stack_pos:])
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del stack[stack_pos:]
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result.append(component)
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for item in component:
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low[item] = len(graph)
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for node in graph:
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visit(node)
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return result
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def topological_sort(self, graph):
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# Source: http://www.logarithmic.net/pfh-files/blog/01208083168/sort.py
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count = {}
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for node in graph:
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count[node] = 0
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for node in graph:
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for successor in graph[node]:
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count[successor] += 1
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ready = [node for node in graph if count[node] == 0]
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result = []
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while ready:
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node = ready.pop(-1)
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result.append(node)
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for successor in graph[node]:
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count[successor] -= 1
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if count[successor] == 0:
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ready.append(successor)
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return result
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