Make Lemmagen lemmatizer picklable

orangecontrib/text/preprocess/normalize.py

@@ -222,9 +222,18 @@ class LemmagenLemmatizer(BaseNormalizer):
 
     def __init__(self, language='English'):
         super().__init__()
-        self.lemmatizer = Lemmatizer(self.lemmagen_languages[language])
+        self.language = language
+        self.lemmatizer = None
+
+    def __call__(self, corpus: Corpus, callback: Callable = None) -> Corpus:
+        # lemmagen3 lemmatizer is not picklable, define it on call and discard it afterward
+        self.lemmatizer = Lemmatizer(self.lemmagen_languages[self.language])
+        output_corpus = super().__call__(corpus, callback)
+        self.lemmatizer = None
+        return output_corpus
 
     def normalizer(self, token):
+        assert self.lemmatizer is not None
         t = self.lemmatizer.lemmatize(token)
         # sometimes Lemmagen returns an empty string, return original tokens
         # in this case

orangecontrib/text/tests/test_preprocess.py

@@ -302,12 +302,21 @@ def test_udpipe_deepcopy(self):
 
     def test_lemmagen(self):
         normalizer = preprocess.LemmagenLemmatizer('Slovenian')
-        token = 'veselja'
+        sentence = 'Gori na gori hiša gori'
+        self.corpus.metas[0, 0] = sentence
         self.assertEqual(
-            normalizer._preprocess(token),
-            Lemmatizer("sl").lemmatize(token)
+            [Lemmatizer("sl").lemmatize(t) for t in sentence.split()],
+            normalizer(self.corpus).tokens[0],
         )
 
+    def test_normalizers_picklable(self):
+        """ Normalizers must be picklable, tests if it is true"""
+        for nm in set(preprocess.normalize.__all__) - {"BaseNormalizer"}:
+            normalizer = getattr(preprocess.normalize, nm)()
+            normalizer(self.corpus)
+            loaded = pickle.loads(pickle.dumps(normalizer))
+            loaded(self.corpus)
+
     def test_cache(self):
         normalizer = preprocess.UDPipeLemmatizer('Slovenian')
         self.corpus.metas[0, 0] = 'sem'