Finalized consistent Error Checking, and added myself to the AUTHORS document

AUTHORS

@@ -4,3 +4,4 @@ John Jarvis <jarv@edx.org>
 James Tauber <jtauber@jtauber.com>
 Nate Aune <naune@edx.org>
 John Kern <kern3020@gmail.com>
+Grady Ward <gward@brandeis.edu>
\ No newline at end of file

ease/create.py

@@ -69,7 +69,7 @@ def create(examples, scores, prompt_string, dump_data=False):
     # Create an essay set object that encapsulates all the essays and alternate representations (tokens, etc)
     try:
         essay_set = _create_essay_set(examples, scores, prompt_string)
-    except (EssaySetRequestError, ExampleCreationInternalError) as ex:
+    except EssaySetRequestError as ex:
         msg = "Essay Set Creation failed (likely due to an error in essay cleaning/parsing) {}".format(ex)
         results['errors'].append(msg)
         log.exception(msg)

ease/errors.py

@@ -2,20 +2,52 @@
 Errors for the EASE repository
 """
 
-class EssaySetRequestError(Exception):
+class EaseError(Exception):
     pass
 
-class ExampleCreationInternalError(Exception):
+
+class EssaySetRequestError(EaseError):
+    """
+    There was a problem with a request sent to the Essay Set module.
+    """
     pass
 
-class EaseError(Exception):
+
+class GradingRequestError(EaseError):
+    """
+    There was a problem with a request sent to the Grading module.
+    """
     pass
 
-class GradingRequestError(Exception):
+
+class ClassifierTrainingInternalError(EaseError):
+    """
+    An unexpected error occurred when training a classifier.
+    """
     pass
 
-class ClassifierTrainingInternalError(Exception):
+
+class CreateRequestError(EaseError):
+    """
+    There was a problem with a request sent to the Create Module.
+    """
     pass
 
-class CreateRequestError(Exception):
+
+class FeatureExtractionInternalError(EaseError):
+    """
+    An unexpected error occurred while extracting features from an essay.
+    """
     pass
+
+
+class InputError(EaseError):
+    """
+    The user supplied an argument which was incorrect.
+    """
+    def __init__(self, expr, msg):
+        self.expr = expr
+        self.msg = msg
+
+    def __str__(self):
+        "An input error occurred at '{0}': {1}".format(self.expr, self.msg)
\ No newline at end of file

ease/essay_set.py

@@ -8,6 +8,7 @@ import sys
 import random
 import os
 import logging
+from ease.errors import InputError
 from errors import *
 
 base_path = os.path.dirname(__file__)
@@ -171,7 +172,7 @@ class EssaySet(object):
         if isinstance(prompt_text, basestring):
             self._prompt = util_functions.sub_chars(prompt_text)
         else:
-            raise util_functions.InputError(prompt_text, "Invalid prompt. Need to enter a string value.")
+            raise InputError('prompt_text', "Invalid prompt. Need to enter a string value.")
         return self._prompt
 
     def generate_additional_essays(self, original_essay, original_score, to_generate=3):

ease/feature_extractor.py

@@ -11,6 +11,7 @@ import os
 from itertools import chain
 import operator
 import logging
+from errors import *
 
 base_path = os.path.dirname(__file__)
 sys.path.append(base_path)
@@ -100,9 +101,9 @@ class FeatureExtractor(object):
                 # Average index of how "topical" essays are
                 self._mean_topical_index = feature_row_sum / float(sum([len(t) for t in essay_set._cleaned_essays]))
             else:
-                raise util_functions.InputError(essay_set, "needs to be an essay set of the train type.")
+                raise InputError('essay_set', "The EssaySet provided needs to be an EssaySet of the 'train' type.")
         else:
-            raise util_functions.InputError(essay_set, "wrong input. need an essay set object.")
+            raise InputError('essay_set', "Wrong input provided, it must provide an EssaySet object.")
 
     def generate_features(self, essay_set):
         """
@@ -117,9 +118,14 @@ class FeatureExtractor(object):
                 - Vocabulary Features (both Normal and Stemmed Vocabulary)
                 - Prompt Features
         """
+        try:
             vocabulary_features = self._generate_vocabulary_features(essay_set)
             length_features = self._generate_length_features(essay_set)
             prompt_features = self._generate_prompt_features(essay_set)
+        except Exception as ex:
+            msg = "An unexpected error occurred during feature extraction: {}".format(ex)
+            log.exception(msg)
+            raise FeatureExtractionInternalError(msg)
 
         # Lumps them all together, copies to solidify, and returns
         overall_features = numpy.concatenate((length_features, prompt_features, vocabulary_features), axis=1)

ease/grade.py

@@ -2,10 +2,12 @@
 Functions to score specified data using specified ML models
 """
 
-import sys
 import os
 import logging
 
+import sys
+
+
 # Append sys to base path to import the following modules
 base_path = os.path.dirname(__file__)
 sys.path.append(base_path)
@@ -52,18 +54,17 @@ def grade(grader_data, submission):
     try:
         grader_set.add_essay(str(submission), 0)
         grader_set.update_prompt(str(grader_data['prompt']))
-    except:
+    except (EssaySetRequestError, InputError):
         error_message = "Essay could not be added to essay set:{0}".format(submission)
         log.exception(error_message)
         results['errors'].append(error_message)
 
     # Tries to extract features from submission and assign score via the model
-    grader_features = None
     try:
         grader_features = extractor.generate_features(grader_set)
         results['score'] = int(model.predict(grader_features)[0])
-    except:
-        error_message = "Could not extract features and score essay."
+    except FeatureExtractionInternalError as ex:
+        error_message = "Could not extract features and score essay: {ex}".format(ex=ex)
         log.exception(error_message)
         results['errors'].append(error_message)
 

ease/util_functions.py

@@ -200,15 +200,6 @@ def get_vocab(essays, scores, max_features_pass_1=750, max_features_pass_2=200):
     return vocab
 
 
-class InputError(Exception):
-    """
-    A class to report to the user that one of their inputs was incorrect.
-    """
-    def __init__(self, expr, msg):
-        self.expr = expr
-        self.msg = msg
-
-
 def gen_cv_preds(clf, arr, sel_score, num_chunks=3):
     """
     Generates cross validated predictions using an input classifier and data.