fix: updated wrong type hint

src/augmenty/span/entities.py

@@ -239,7 +239,7 @@ def create_ent_augmenter_v1(
             i.e. ["Kenneth", "Enevoldsen"], 2) a string of the desired entity i.e. "Kenneth Enevoldsen", this
             will be split using the tokenizer of the nlp pipeline, or 3) Span object with the desired entity, here all information will be passed
             on except for the dependency tree.
-        replace_consistency: Should an entity always be replaced with the same entity? 
+        replace_consistency: Should an entity always be replaced with the same entity?
         resolve_dependencies: Attempts to resolve the dependency tree
             by setting head of the original entitity aa the head of the
             first token in the new entity. The remainder is the passed as

src/augmenty/token/insert.py

@@ -269,7 +269,8 @@ def __insert(
         if context_window:
             span = doc[
                 max(0, t.i - context_window) : min(  # type: ignore
-                    len(doc), t.i + context_window  # type: ignore
+                    len(doc),
+                    t.i + context_window,  # type: ignore
                 )
             ]
         elif doc.has_annotation("SENT_START"):

src/augmenty/token/replace.py

@@ -58,9 +58,9 @@ def create_token__dict_replace_augmenter_v1(
     Args:
         level: Probability to replace token given that it is in synonym dictionary.
         replace: A dictionary of words and a list of their replacement (e.g. synonyms) or a dictionary denoting replacement based on pos tag.
-        ignore_casing: When doing the lookup should the model ignore casing? 
+        ignore_casing: When doing the lookup should the model ignore casing?
         getter: A getter function to extract the POS-tag.
-        keep_titlecase: Should the model keep the titlecase of the replaced word. 
+        keep_titlecase: Should the model keep the titlecase of the replaced word.
 
     Returns:
         The augmenter.

tests/test_all_augmenters.py

@@ -100,10 +100,10 @@ def is_pronoun(token: Token) -> bool:
         ),
     ],
 )
-def test_augmenters(aug: Callable, args: dict, examples, nlp: Language, level: float):  # noqa  # type: ignore
+def test_augmenters(aug: str, args: dict, examples, nlp: Language, level: float):  # noqa  # type: ignore
     args["level"] = level
-    aug = augmenty.load(aug, **args)
-    augmented_examples = [e for ex in examples for e in aug(nlp=nlp, example=ex)]
+    augmenter = augmenty.load(aug, **args)
+    augmented_examples = [e for ex in examples for e in augmenter(nlp=nlp, example=ex)]
 
 
 def test_check_untested():