Set base logging level as info, remove unused debug strings.

naive-nlu/knowledge_base.py

@@ -23,18 +23,18 @@ class KnowledgeBase(object):
         # Parse everything
         parsed_examples = []
         for example in examples:
-            logging.debug("\x1b[7;32m> {} \x1b[0m".format(example))
+            logging.info("\x1b[7;32m> {} \x1b[0m".format(example))
             tokens, decomposition, inferred_tree = parsing.integrate_language(self, example)
-            logging.debug(tokens)
+            logging.info(tokens)
             result = knowledge_evaluation.integrate_information(self.knowledge, {
                 "elements": tokens,
                 "decomposition": decomposition,
                 "parsed": inferred_tree,
             })
 
-            logging.debug("\x1b[7;33m< {} \x1b[0m".format(self.get_value(result)))
+            logging.info("\x1b[7;33m< {} \x1b[0m".format(self.get_value(result)))
             self.act_upon(result)
-            logging.debug("\x1b[7;34m> set: {} \x1b[0m".format(self.get_value(result)))
+            logging.info("\x1b[7;34m> set: {} \x1b[0m".format(self.get_value(result)))
             self.examples.append((decomposition, inferred_tree))
 
             # Reduce values
@@ -49,7 +49,7 @@ class KnowledgeBase(object):
 
     def process(self, row):
         knowledge_before = copy.deepcopy(self.knowledge)
-        logging.debug("\x1b[7;32m> {} \x1b[0m".format(row))
+        logging.info("\x1b[7;32m> {} \x1b[0m".format(row))
         tokens = parsing.to_tokens(row)
         tokens, inferred_tree = parsing.get_fit(self, tokens)
         result = knowledge_evaluation.integrate_information(self.knowledge,
@@ -75,4 +75,4 @@ class KnowledgeBase(object):
         if is_modifiable_property(result):
             result.setter()
         else:
-            logging.debug(result)
+            logging.warning("Cannot act upon: {}".format(result))

naive-nlu/knowledge_evaluation.py

@@ -41,8 +41,6 @@ def get_subquery_type(knowledge_base, atom):
 
 
 def property_for_value(knowledge_base, value):
-    # logging.debug(value)
-    # logging.debug(knowledge_base[value])
     return knowledge_base[value]['as_property']
 
 

naive-nlu/parsing.py

@@ -133,26 +133,11 @@ def apply_remix(tokens, remix):
 
 
 def build_remix_matrix(knowledge_base, tokens, atom, similar):
-    # logging.debug("+" * 20)
-
     tokens = list(tokens)
     tokens, matcher, result = make_template(knowledge_base, tokens, atom)
     similar_matcher, similar_result, similar_result_resolved, _ = similar
 
-    # logging.debug("NEW:")
-    # logging.debug("Tokens:", tokens)
-    # logging.debug("Matcher:", matcher)
-    # logging.debug("Result:", result)
-    # logging.debug("---")
-    # logging.debug("Similar:")
-    # logging.debug("Matcher:", similar_matcher)
-    # logging.debug("Result:", similar_result)
-
     start_bounds, end_bounds = find_bounds(matcher, similar_matcher)
-    # logging.debug("---")
-    # logging.debug("Bounds:")
-    # logging.debug("Start:", start_bounds)
-    # logging.debug("End:  ", end_bounds)
 
     for i, element in (end_bounds + start_bounds[::-1]):
         matcher.pop(i)
@@ -161,15 +146,10 @@ def build_remix_matrix(knowledge_base, tokens, atom, similar):
     possible_remixes = get_possible_remixes(knowledge_base, matcher, similar_matcher)
     chosen_remix = possible_remixes[0]
 
-    # logging.debug("New tokens:", tokens)
-    # logging.debug("-" * 20)
     return chosen_remix, (start_bounds, end_bounds)
 
 
 def get_possible_remixes(knowledge_base, matcher, similar_matcher):
-    # logging.debug("*" * 20)
-    # logging.debug(matcher)
-    # logging.debug(similar_matcher)
 
     matrix = []
     for element in matcher:
@@ -183,8 +163,6 @@ def get_possible_remixes(knowledge_base, matcher, similar_matcher):
             indexes = all_indexes(similar_matcher, element)
         matrix.append(indexes)
 
-    # logging.debug(matrix)
-    # logging.debug([list(x) for x in list(zip(*matrix))])
     # TODO: do some scoring to find the most "interesting combination"
     return [list(x) for x in list(zip(*matrix))]
 
@@ -304,19 +282,14 @@ def get_matching(sample, other):
 def reprocess_language_knowledge(knowledge_base, examples):
     examples = knowledge_base.examples + examples
 
-    logging.debug('\n'.join(map(str, knowledge_base.examples)))
-    logging.debug("--")
-
     pattern_examples = []
     for i, sample in enumerate(examples):
         other = examples[:i] + examples[i + 1:]
         match = get_matching(sample, other)
-        logging.debug("->", match)
         if len(match) > 0:
             sample = (match, sample[1],)
         pattern_examples.append(sample)
-        logging.debug("---")
+
-    logging.debug("\x1b[7m--\x1b[0m")
     return pattern_examples
 
 

naive-nlu/test.py

@@ -1,6 +1,8 @@
 import json
 import logging
 
+logging.getLogger().setLevel(logging.INFO)
+
 from knowledge_base import KnowledgeBase
 from modifiable_property import is_modifiable_property