class CtsLab: '''This class defines the Lab Environment for the Cluster Test System. It defines those things which are expected to change from test environment to test environment for the same cluster manager. It is where you define the set of nodes that are in your test lab what kind of reset mechanism you use, etc. This class is derived from a UserDict because we hold many different parameters of different kinds, and this provides provide a uniform and extensible interface useful for any kind of communication between the user/administrator/tester and CTS. At this point in time, it is the intent of this class to model static configuration and/or environmental data about the environment which doesn't change as the tests proceed. Well-known names (keys) are an important concept in this class. The HasMinimalKeys member function knows the minimal set of well-known names for the class. The following names are standard (well-known) at this time: nodes An array of the nodes in the cluster reset A ResetMechanism object logger An array of objects that log strings... CMclass The type of ClusterManager we are running (This is a class object, not a class instance) RandSeed Random seed. It is a triple of bytes. (optional) The CTS code ignores names it doesn't know about/need. The individual tests have access to this information, and it is perfectly acceptable to provide hints, tweaks, fine-tuning directions or other information to the tests through this mechanism. ''' def __init__(self, args=None): self.Env = EnvFactory().getInstance(args) self.Scenario = None self.logger = LogFactory() self.rsh = RemoteFactory().getInstance() def dump(self): self.Env.dump() def has_key(self, key): return self.Env.has_key(key) def __getitem__(self, key): return self.Env[key] def __setitem__(self, key, value): self.Env[key] = value def HasMinimalKeys(self): 'Return TRUE if our object has the minimal set of keys/values in it' result = 1 for key in self.MinimalKeys: if not self.has_key(key): result = None return result def run(self, Scenario, Iterations): if not Scenario: self.logger.log("No scenario was defined") return 1 self.logger.log("Cluster nodes: ") for node in self.Env["nodes"]: self.logger.log(" * %s" % (node)) if not Scenario.SetUp(): return 1 try : Scenario.run(Iterations) except : self.logger.log("Exception by %s" % sys.exc_info()[0]) self.logger.traceback(traceback) Scenario.summarize() Scenario.TearDown() return 1 #ClusterManager.oprofileSave(Iterations) Scenario.TearDown() Scenario.summarize() if Scenario.Stats["failure"] > 0: return Scenario.Stats["failure"] elif Scenario.Stats["success"] != Iterations: self.logger.log("No failure count but success != requested iterations") return 1 return 0 def IsValidNode(self, node): 'Return TRUE if the given node is valid' return self.Nodes.has_key(node) def __CheckNode(self, node): "Raise a ValueError if the given node isn't valid" if not self.IsValidNode(node): raise ValueError("Invalid node [%s] in CheckNode" % node)
class CtsLab: '''This class defines the Lab Environment for the Cluster Test System. It defines those things which are expected to change from test environment to test environment for the same cluster manager. It is where you define the set of nodes that are in your test lab what kind of reset mechanism you use, etc. This class is derived from a UserDict because we hold many different parameters of different kinds, and this provides provide a uniform and extensible interface useful for any kind of communication between the user/administrator/tester and CTS. At this point in time, it is the intent of this class to model static configuration and/or environmental data about the environment which doesn't change as the tests proceed. Well-known names (keys) are an important concept in this class. The HasMinimalKeys member function knows the minimal set of well-known names for the class. The following names are standard (well-known) at this time: nodes An array of the nodes in the cluster reset A ResetMechanism object logger An array of objects that log strings... CMclass The type of ClusterManager we are running (This is a class object, not a class instance) RandSeed Random seed. It is a triple of bytes. (optional) The CTS code ignores names it doesn't know about/need. The individual tests have access to this information, and it is perfectly acceptable to provide hints, tweaks, fine-tuning directions or other information to the tests through this mechanism. ''' def __init__(self, args=None): self.Env = EnvFactory().getInstance(args) self.Scenario = None self.logger = LogFactory() self.rsh = RemoteFactory().getInstance() def dump(self): self.Env.dump() def has_key(self, key): return self.Env.has_key(key) def __getitem__(self, key): return self.Env[key] def __setitem__(self, key, value): self.Env[key] = value def HasMinimalKeys(self): 'Return TRUE if our object has the minimal set of keys/values in it' result = 1 for key in self.MinimalKeys: if not self.has_key(key): result = None return result def run(self, Scenario, Iterations): if not Scenario: self.logger.log("No scenario was defined") return 1 self.logger.log("Cluster nodes: ") for node in self.Env["nodes"]: self.logger.log(" * %s" % (node)) if not Scenario.SetUp(): return 1 try: Scenario.run(Iterations) except: self.logger.log("Exception by %s" % sys.exc_info()[0]) self.logger.traceback(traceback) Scenario.summarize() Scenario.TearDown() return 1 #ClusterManager.oprofileSave(Iterations) Scenario.TearDown() Scenario.summarize() if Scenario.Stats["failure"] > 0: return Scenario.Stats["failure"] elif Scenario.Stats["success"] != Iterations: self.logger.log( "No failure count but success != requested iterations") return 1 return 0 def IsValidNode(self, node): 'Return TRUE if the given node is valid' return self.Nodes.has_key(node) def __CheckNode(self, node): "Raise a ValueError if the given node isn't valid" if not self.IsValidNode(node): raise ValueError("Invalid node [%s] in CheckNode" % node)