Dev016 (#117)

* check that input to step.fit_transform and step.transform is dict. Same for step outputs

* prepare for 0.1.16

* Update base.py

docs/conf.py

@@ -26,7 +26,7 @@
 # The short X.Y version
 version = '0.1'
 # The full version, including alpha/beta/rc tags
-release = '0.1.15'
+release = '0.1.16'
 
 
 # -- General configuration ---------------------------------------------------

setup.py

@@ -13,11 +13,11 @@
 
 setup(name='steppy',
       packages=['steppy'],
-      version='0.1.15',
+      version='0.1.16',
       description='A lightweight, open-source, Python library for fast and reproducible experimentation',
       long_description=long_description,
       url='https://github.com/minerva-ml/steppy',
-      download_url='https://github.com/minerva-ml/steppy/archive/0.1.15.tar.gz',
+      download_url='https://github.com/minerva-ml/steppy/archive/0.1.16.tar.gz',
       author='Kamil A. Kaczmarek, Jakub Czakon',
       author_email='[email protected], [email protected]',
       keywords=['machine-learning', 'reproducibility', 'pipeline', 'data-science'],

steppy/base.py

@@ -329,7 +329,11 @@ def fit_transform(self, data):
         Returns:
             dict: Step output from the ``self.transformer.fit_transform`` method
         """
+        if data:
+            assert isinstance(data, dict), 'Step {}, "data" argument in the "fit_transform()" method must be dict, ' \
+                                           'got {} instead.'.format(self.name, type(data))
         logger.info('Step {}, working in "{}" mode'.format(self.name, self._mode))
+
         if self._mode == 'inference':
             ValueError('Step {}, you are in "{}" mode, where you cannot run "fit".'
                        'Please change mode to "train" to enable fitting.'
@@ -384,7 +388,11 @@ def transform(self, data):
         Returns:
             dict: step output from the transformer.transform method
         """
+        if data:
+            assert isinstance(data, dict), 'Step {}, "data" argument in the "transform()" method must be dict, ' \
+                                           'got {} instead.'.format(self.name, type(data))
         logger.info('Step {}, working in "{}" mode'.format(self.name, self._mode))
+
         if self.output_is_cached:
             logger.info('Step {} using cached output'.format(self.name))
             step_output_data = self.output
@@ -556,6 +564,12 @@ def _fit_transform_operation(self, step_inputs):
                 raise StepError(msg) from e
 
             logger.info('Step {}, transforming completed'.format(self.name))
+
+        assert isinstance(step_output_data, dict), 'Step {}, Transformer "{}", error. ' \
+            'Output from transformer must be dict, got {} instead'.format(self.name,
+                                                                          self.transformer.__class__.__name__,
+                                                                          type(step_output_data))
+
         if self.cache_output:
             logger.info('Step {}, caching output'.format(self.name))
             self.output = step_output_data
@@ -596,6 +610,12 @@ def _transform_operation(self, step_inputs):
                 raise StepError(msg) from e
 
             logger.info('Step {}, transforming completed'.format(self.name))
+
+        assert isinstance(step_output_data, dict), 'Step {}, Transformer "{}", error. ' \
+            'Output from transformer must be dict, got {} instead'.format(self.name,
+                                                                          self.transformer.__class__.__name__,
+                                                                          type(step_output_data))
+
         if self.cache_output:
             logger.info('Step {}, caching output'.format(self.name))
             self.output = step_output_data