Add in dogstatsd hooks for machine learning

create.py

@@ -10,6 +10,9 @@ sys.path.append(one_up_path)
 import model_creator
 import util_functions
 
+from statsd import statsd
+
+@statsd.timed('open_ended_assessment.machine_learning.creator.time')
 def create(text,score,prompt_string,model_path):
 
     results = {'errors': [],'success' : False, 'cv_kappa' : 0, 'cv_mean_absolute_error': 0}
@@ -29,5 +32,9 @@ def create(text,score,prompt_string,model_path):
     except:
         results['errors'].append("could not write model to: {0}".format(model_path))
 
+    #Count number of successful/unsuccessful creations
+    statsd.increment("open_ended_assessment.machine_learning.creator_count",
+        tags=["success:{0}".format(results['success'])])
+
     return results
 

grade.py

@@ -10,6 +10,7 @@ import pickle
 import os
 import numpy
 import logging
+from statsd import statsd
 
 base_path = os.path.dirname(__file__)
 sys.path.append(base_path)
@@ -25,7 +26,7 @@ log = logging.getLogger(__name__)
 
 TEMPORARY_WANTS_CONFIG=True
 
-
+@statsd.timed('open_ended_assessment.machine_learning.grader.time')
 def grade(grader_path,grader_config,submission,sandbox=None):
 
     results = {'errors': [],'tests': [],'score': 0, 'feedback' : "", 'success' : False}
@@ -87,6 +88,10 @@ def grade(grader_path,grader_config,submission,sandbox=None):
         #If error, success is False.
         results['success']=False
 
+    #Count number of successful/unsuccessful gradings
+    statsd.increment("open_ended_assessment.machine_learning.grader_count",
+        tags=["success:{0}".format(results['success'])])
+
     return results