updated pytype & coveralls

Makefile

@@ -47,7 +47,7 @@ lint:
 	black --check rasa tests
 
 types:
-	pytype --keep-going rasa
+	pytype --keep-going rasa -j 16
 
 prepare-tests-macos: prepare-wget-macos prepare-tests-files
 	brew install graphviz || true

rasa/core/featurizers.py

@@ -54,7 +54,7 @@ def action_as_one_hot(action: Text, domain: Domain) -> np.ndarray:
     def create_encoded_all_actions(self, domain: Domain) -> np.ndarray:
         """Create matrix with all actions from domain encoded in rows."""
 
-        pass
+        raise NotImplementedError("Featurizer must implement encoding actions.")
 
 
 class BinarySingleStateFeaturizer(SingleStateFeaturizer):

rasa/core/policies/embedding_policy.py

@@ -268,8 +268,8 @@ def _create_session_data(
             label_ids = np.expand_dims(label_ids, -1)
         else:
             # prediction time
-            label_ids = None
-            Y = None
+            label_ids = np.asarray([])
+            Y = np.asarray([])
 
         return {
             "dialogue_features": [data_X],

rasa/core/training/data.py

@@ -15,7 +15,9 @@ def __init__(
     def limit_training_data_to(self, max_samples: int) -> None:
         self.X = self.X[:max_samples]
         self.y = self.y[:max_samples]
-        self.true_length = self.true_length[:max_samples]
+        self.true_length = (
+            self.true_length[:max_samples] if self.true_length is not None else None
+        )
 
     def is_empty(self) -> bool:
         """Check if the training matrix does contain training samples."""

rasa/core/utils.py

@@ -88,7 +88,7 @@ def is_int(value: Any) -> bool:
         return False
 
 
-def one_hot(hot_idx: int, length: int, dtype: Optional[Text] = None) -> np.array:
+def one_hot(hot_idx: int, length: int, dtype: Optional[Text] = None) -> np.ndarray:
     if hot_idx >= length:
         raise ValueError(
             "Can't create one hot. Index '{}' is out "
@@ -176,7 +176,7 @@ def __eq__(self, other) -> bool:
     def __hash__(self) -> int:
         return self.__hash
 
-    def unwrap(self) -> np.array:
+    def unwrap(self) -> np.ndarray:
         """Returns the encapsulated ndarray.
 
         If the wrapper is "tight", a copy of the encapsulated ndarray is

rasa/nlu/test.py

@@ -64,8 +64,8 @@
 
 
 def plot_confusion_matrix(
-    cm: np.array,
-    classes: np.array,
+    cm: np.ndarray,
+    classes: np.ndarray,
     normalize: bool = False,
     title: Text = "Confusion matrix",
     cmap=None,
@@ -535,7 +535,7 @@ def evaluate_intents(
 def _plot_confusion_matrix(
     output_directory: Optional[Text],
     confmat_filename: Optional[Text],
-    cnf_matrix: np.array,
+    cnf_matrix: np.ndarray,
     labels: Collection[Text],
 ) -> None:
     if output_directory:
@@ -563,7 +563,7 @@ def _plot_histogram(
 
 def merge_labels(
     aligned_predictions: List[Dict], extractor: Optional[Text] = None
-) -> np.array:
+) -> np.ndarray:
     """Concatenates all labels of the aligned predictions.
     Takes the aligned prediction labels which are grouped for each message
     and concatenates them."""

requirements-dev.txt

@@ -22,12 +22,12 @@ mongomock==3.18.0
 # lint/format/types
 black==19.10b0
 flake8==3.7.8
-pytype==2019.7.11
+pytype==2020.2.6
 
 # other
 google-cloud-storage==1.7.0
 azure-storage-blob==1.0.0
-coveralls==1.7.0
+coveralls==1.11.0
 
 # release tools
 semantic_version==2.8.3

tests/core/test_processor.py

@@ -47,10 +47,10 @@ async def test_message_processor(
     await default_processor.handle_message(
         UserMessage('/greet{"name":"Core"}', default_channel)
     )
-    assert {
+    assert default_channel.latest_output() == {
         "recipient_id": "default",
         "text": "hey there Core!",
-    } == default_channel.latest_output()
+    }
 
 
 async def test_message_id_logging(default_processor: MessageProcessor):
@@ -565,10 +565,10 @@ async def test_handle_message_with_session_start(
         UserMessage(f"/greet{json.dumps(slot_1)}", default_channel, sender_id)
     )
 
-    assert {
+    assert default_channel.latest_output() == {
         "recipient_id": sender_id,
         "text": "hey there Core!",
-    } == default_channel.latest_output()
+    }
 
     # patch processor so a session start is triggered
     monkeypatch.setattr(default_processor, "_has_session_expired", lambda _: True)