Fixing issues with serialization

[nepi.git] / src / nepi / execution / ec.py

diff --git a/src/nepi/execution/ec.py b/src/nepi/execution/ec.py
index 1357e4f..5664d2f 100644 (file)
--- a/src/nepi/execution/ec.py
+++ b/src/nepi/execution/ec.py
@@ -26,6 +26,7 @@ from nepi.execution.scheduler import HeapScheduler, Task, TaskStatus
 from nepi.execution.trace import TraceAttr
 from nepi.util.serializer import ECSerializer, SFormats
 from nepi.util.plotter import ECPlotter, PFormats
 from nepi.execution.trace import TraceAttr
 from nepi.util.serializer import ECSerializer, SFormats
 from nepi.util.plotter import ECPlotter, PFormats

+from nepi.util.netgraph import NetGraph, TopologyType 

 
 # TODO: use multiprocessing instead of threading
 # TODO: Allow to reconnect to a running experiment instance! (reconnect mode vs deploy mode)
 
 # TODO: use multiprocessing instead of threading
 # TODO: Allow to reconnect to a running experiment instance! (reconnect mode vs deploy mode)


@@ -101,7 +102,7 @@ class ExperimentController(object):
     .. note::
 
     An experiment, or scenario, is defined by a concrete set of resources,
     .. note::
 
     An experiment, or scenario, is defined by a concrete set of resources,

-    behavior, configuration and interconnection of those resources. 
+    and the behavior, configuration and interconnection of those resources. 

     The Experiment Description (ED) is a detailed representation of a
     single experiment. It contains all the necessary information to 
     allow repeating the experiment. NEPI allows to describe
     The Experiment Description (ED) is a detailed representation of a
     single experiment. It contains all the necessary information to 
     allow repeating the experiment. NEPI allows to describe


@@ -116,7 +117,7 @@ class ExperimentController(object):
     recreated (and re-run) by instantiating an EC and recreating 
     the same experiment description. 
 
     recreated (and re-run) by instantiating an EC and recreating 
     the same experiment description. 
 

-    In NEPI, an experiment is represented as a graph of interconnected
+    An experiment is represented as a graph of interconnected

     resources. A resource is a generic concept in the sense that any
     component taking part of an experiment, whether physical of
     virtual, is considered a resource. A resources could be a host, 
     resources. A resource is a generic concept in the sense that any
     component taking part of an experiment, whether physical of
     virtual, is considered a resource. A resources could be a host, 


@@ -126,10 +127,9 @@ class ExperimentController(object):
     single resource. ResourceManagers are specific to a resource
     type (i.e. An RM to control a Linux application will not be
     the same as the RM used to control a ns-3 simulation).
     single resource. ResourceManagers are specific to a resource
     type (i.e. An RM to control a Linux application will not be
     the same as the RM used to control a ns-3 simulation).

-    To support a new type of resource in NEPI, a new RM must be 
-    implemented. NEPI already provides a variety of
-    RMs to control basic resources, and new can be extended from
-    the existing ones.
+    To support a new type of resource, a new RM must be implemented. 
+    NEPI already provides a variety of RMs to control basic resources, 
+    and new can be extended from the existing ones.

 
     Through the EC interface the user can create ResourceManagers (RMs),
     configure them and interconnect them, to describe an experiment.
 
     Through the EC interface the user can create ResourceManagers (RMs),
     configure them and interconnect them, to describe an experiment.


@@ -160,22 +160,31 @@ class ExperimentController(object):
         ec = serializer.load(filepath)
         return ec
 
         ec = serializer.load(filepath)
         return ec
 

-    def __init__(self, exp_id = None, local_dir = None, persist = False):
-        """ ExperimentController entity to model an execute a network experiment.
+    def __init__(self, exp_id = None, local_dir = None, persist = False,
+            add_node_callback = None, add_edge_callback = None, **kwargs):
+        """ ExperimentController entity to model an execute a network 
+        experiment.

         
         :param exp_id: Human readable name to identify the experiment
         
         :param exp_id: Human readable name to identify the experiment

-        :type name: str
+        :type exp_id: str

 
         :param local_dir: Path to local directory where to store experiment
             related files
 
         :param local_dir: Path to local directory where to store experiment
             related files

-        :type name: str
+        :type local_dir: str

 
         :param persist: Save an XML description of the experiment after 
         completion at local_dir
 
         :param persist: Save an XML description of the experiment after 
         completion at local_dir

-        :type name: bool
+        :type persist: bool

 
 

-        """
+        :param add_node_callback: Callback to invoke for node instantiation
+        when automatic topology creation mode is used 
+        :type add_node_callback: function
+
+        :param add_edge_callback: Callback to invoke for edge instantiation 
+        when automatic topology creation mode is used 
+        :type add_edge_callback: function

 
 

+        """

         super(ExperimentController, self).__init__()
 
         # Logging
         super(ExperimentController, self).__init__()
 
         # Logging


@@ -233,6 +242,12 @@ class ExperimentController(object):
         # EC state
         self._state = ECState.RUNNING
 
         # EC state
         self._state = ECState.RUNNING
 

+        # Automatically construct experiment description 
+        self._netgraph = None
+        if add_node_callback and add_edge_callback:
+            self._build_from_netgraph(add_node_callback, add_edge_callback, 
+                    **kwargs)
+

         # The runner is a pool of threads used to parallelize 
         # execution of tasks
         self._nthreads = 20
         # The runner is a pool of threads used to parallelize 
         # execution of tasks
         self._nthreads = 20


@@ -313,11 +328,20 @@ class ExperimentController(object):
 
     @property
     def persist(self):
 
     @property
     def persist(self):

-        """ If Trie persist the ExperimentController to XML format upon completion
+        """ If True, persists the ExperimentController to XML format upon 
+        experiment completion

 
         """
         return self._persist
 
 
         """
         return self._persist
 

+    @property
+    def netgraph(self):
+        """ Return NetGraph instance if experiment description was automatically 
+        generated
+
+        """
+        return self._netgraph
+

     @property
     def abort(self):
         """ Returns True if the experiment has failed and should be interrupted,
     @property
     def abort(self):
         """ Returns True if the experiment has failed and should be interrupted,


@@ -478,7 +502,7 @@ class ExperimentController(object):
         return rm
 
     def get_resources_by_type(self, rtype):
         return rm
 
     def get_resources_by_type(self, rtype):

-        """ Returns a registered ResourceManager by its guid
+        """ Returns the ResourceManager objects of type rtype

 
             :param rtype: Resource type
             :type rtype: string
 
             :param rtype: Resource type
             :type rtype: string


@@ -488,7 +512,7 @@ class ExperimentController(object):
         """
         rms = []
         for guid, rm in self._resources.iteritems():
         """
         rms = []
         for guid, rm in self._resources.iteritems():

-            if rm.get_rtype() == type: 
+            if rm.get_rtype() == rtype: 

                 rms.append(rm)
         return rms
 
                 rms.append(rm)
         return rms
 


@@ -497,16 +521,31 @@ class ExperimentController(object):
 
     @property
     def resources(self):
 
     @property
     def resources(self):

-        """ Returns the set() of guids of all the ResourceManager
+        """ Returns the guids of all ResourceManagers 

 
             :return: Set of all RM guids
 
             :return: Set of all RM guids

-            :rtype: set
+            :rtype: list

 
         """
         keys = self._resources.keys()
 
         return keys
 
 
         """
         keys = self._resources.keys()
 
         return keys
 

+    def filter_resources(self, rtype):
+        """ Returns the guids of all ResourceManagers of type rtype
+
+            :param rtype: Resource type
+            :type rtype: string
+            
+            :rtype: list of guids
+            
+        """
+        rms = []
+        for guid, rm in self._resources.iteritems():
+            if rm.get_rtype() == rtype: 
+                rms.append(rm.guid)
+        return rms
+

     def register_resource(self, rtype, guid = None):
         """ Registers a new ResourceManager of type 'rtype' in the experiment
         
     def register_resource(self, rtype, guid = None):
         """ Registers a new ResourceManager of type 'rtype' in the experiment
         


@@ -1184,3 +1223,18 @@ class ExperimentController(object):
         self._cond.notify()
         self._cond.release()
 
         self._cond.notify()
         self._cond.release()
 

+    def _build_from_netgraph(self, add_node_callback, add_edge_callback, 
+            **kwargs):
+        """ Automates experiment description using a NetGraph instance.
+        """
+        self._netgraph = NetGraph(**kwargs)
+
+        ### Add resources to the EC
+        for nid in self.netgraph.graph.nodes():
+            add_node_callback(self, nid)
+
+        #### Add connections between resources
+        for nid1, nid2 in self.netgraph.graph.edges():
+            add_edge_callback(self, nid1, nid2)
+
+