Change Box plugin to mimic a sklearn classifier

example-plugins/basic_box_plugin.py

@@ -18,7 +18,7 @@ class BasicBox(SentimentBox):
         'default': 'marl:Neutral'
     }
 
-    def box(self, input, **kwargs):
+    def predict(self, input):
         output = basic.get_polarity(input)
         return self.mappings.get(output, self.mappings['default'])
 

example-plugins/basic_plugin.py

@@ -18,7 +18,7 @@ class Basic(MappingMixin, SentimentBox):
         'default': 'marl:Neutral'
     }
 
-    def box(self, input, **kwargs):
+    def predict(self, input):
         return basic.get_polarity(input)
 
     test_cases = [{

example-plugins/sklearn/pipeline_plugin.py

@@ -18,7 +18,7 @@ class PipelineSentiment(MappingMixin, SentimentBox):
         -1: 'marl:Negative'
     }
 
-    def box(self, input, *args, **kwargs):
+    def predict(self, input):
         return pipeline.predict([input, ])[0]
 
     test_cases = [

senpy/plugins/__init__.py

@@ -251,7 +251,7 @@ class Box(AnalysisPlugin):
 
     .. code-block::
 
-                   entry --> input() --> box() --> output() --> entry'
+                   entry --> input() --> predict() --> output() --> entry'
 
 
     In other words: their ``input`` method convers a query (entry and a set of parameters) into
@@ -267,13 +267,13 @@ class Box(AnalysisPlugin):
         '''Transforms the results of the black box into an entry'''
         return output
 
-    def box(self):
+    def predict(self, input):
         raise NotImplementedError('You should define the behavior of this plugin')
 
     def analyse_entries(self, entries, params):
         for entry in entries:
             input = self.input(entry=entry, params=params)
-            results = self.box(input=input, params=params)
+            results = self.predict(input=input)
             yield self.output(output=results, entry=entry, params=params)
 
 
@@ -453,7 +453,8 @@ def install_deps(*plugins):
     return installed
 
 
-is_plugin_file = re.compile(r'.*\.senpy$|senpy_[a-zA-Z0-9_]+\.py$|[a-zA-Z0-9_]+_plugin.py$')
+is_plugin_file = re.compile(r'.*\.senpy$|senpy_[a-zA-Z0-9_]+\.py$|'
+                            '^(?!test_)[a-zA-Z0-9_]+_plugin.py$')
 
 
 def find_plugins(folders):

tests/test_plugins.py

@@ -212,7 +212,7 @@ class PluginsTest(TestCase):
             def input(self, entry, **kwargs):
                 return entry.text
 
-            def box(self, input, **kwargs):
+            def predict(self, input):
                 return 'SIGN' in input
 
             def output(self, output, entry, **kwargs):
@@ -242,7 +242,7 @@ class PluginsTest(TestCase):
 
             mappings = {'happy': 'marl:Positive', 'sad': 'marl:Negative'}
 
-            def box(self, input, **kwargs):
+            def predict(self, input, **kwargs):
                 return 'happy' if ':)' in input else 'sad'
 
             test_cases = [

[J. Fernando Sánchez]

@icorcuera You can now adapt your example and add the evaluation part to the Box plugin :)