mirror of
https://github.com/ansible/awx.git
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4ced911c00
* New InstanceGroup model and associative relationship with Instances * Associative instances between Organizations, Inventory, and Job Templates and InstanceGroups * Migrations for adding fields and tables for Instance Groups * Adding activity stream reference for instance groups * Task Manager Refactoring: ** Simplifying task manager relationships and move away from the interstitial hash tables ** Simplify dependency determination logic ** Reduce task manager runtime complexity by removing the partial references and moving the logic into the task manager directly or relying on Job model logic for determinism
125 lines
3.8 KiB
Python
125 lines
3.8 KiB
Python
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from awx.main.models import (
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Job,
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AdHocCommand,
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InventoryUpdate,
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ProjectUpdate,
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WorkflowJob,
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)
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class SimpleDAG(object):
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''' A simple implementation of a directed acyclic graph '''
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def __init__(self):
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self.nodes = []
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self.edges = []
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def __contains__(self, obj):
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for node in self.nodes:
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if node['node_object'] == obj:
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return True
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return False
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def __len__(self):
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return len(self.nodes)
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def __iter__(self):
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return self.nodes.__iter__()
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def generate_graphviz_plot(self):
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def short_string_obj(obj):
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if type(obj) == Job:
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type_str = "Job"
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if type(obj) == AdHocCommand:
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type_str = "AdHocCommand"
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elif type(obj) == InventoryUpdate:
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type_str = "Inventory"
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elif type(obj) == ProjectUpdate:
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type_str = "Project"
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elif type(obj) == WorkflowJob:
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type_str = "Workflow"
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else:
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type_str = "Unknown"
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type_str += "%s" % str(obj.id)
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return type_str
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doc = """
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digraph g {
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rankdir = LR
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"""
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for n in self.nodes:
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doc += "%s [color = %s]\n" % (
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short_string_obj(n['node_object']),
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"red" if n['node_object'].status == 'running' else "black",
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)
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for from_node, to_node, label in self.edges:
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doc += "%s -> %s [ label=\"%s\" ];\n" % (
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short_string_obj(self.nodes[from_node]['node_object']),
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short_string_obj(self.nodes[to_node]['node_object']),
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label,
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)
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doc += "}\n"
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gv_file = open('/tmp/graph.gv', 'w')
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gv_file.write(doc)
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gv_file.close()
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def add_node(self, obj, metadata=None):
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if self.find_ord(obj) is None:
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self.nodes.append(dict(node_object=obj, metadata=metadata))
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def add_edge(self, from_obj, to_obj, label=None):
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from_obj_ord = self.find_ord(from_obj)
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to_obj_ord = self.find_ord(to_obj)
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if from_obj_ord is None or to_obj_ord is None:
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raise LookupError("Object not found")
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self.edges.append((from_obj_ord, to_obj_ord, label))
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def add_edges(self, edgelist):
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for edge_pair in edgelist:
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self.add_edge(edge_pair[0], edge_pair[1], edge_pair[2])
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def find_ord(self, obj):
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for idx in range(len(self.nodes)):
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if obj == self.nodes[idx]['node_object']:
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return idx
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return None
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def get_dependencies(self, obj, label=None):
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antecedents = []
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this_ord = self.find_ord(obj)
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for node, dep, lbl in self.edges:
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if label:
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if node == this_ord and lbl == label:
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antecedents.append(self.nodes[dep])
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else:
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if node == this_ord:
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antecedents.append(self.nodes[dep])
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return antecedents
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def get_dependents(self, obj, label=None):
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decendents = []
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this_ord = self.find_ord(obj)
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for node, dep, lbl in self.edges:
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if label:
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if dep == this_ord and lbl == label:
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decendents.append(self.nodes[node])
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else:
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if dep == this_ord:
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decendents.append(self.nodes[node])
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return decendents
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def get_leaf_nodes(self):
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leafs = []
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for n in self.nodes:
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if len(self.get_dependencies(n['node_object'])) < 1:
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leafs.append(n)
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return leafs
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def get_root_nodes(self):
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roots = []
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for n in self.nodes:
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if len(self.get_dependents(n['node_object'])) < 1:
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roots.append(n)
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return roots
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