Normalize - Use language from Corpus

orangecontrib/text/language.py

@@ -41,7 +41,7 @@
     "ga": "Irish",
     "gl": "Galician",
     "got": "Gothic",
-    "grc": "Ancient greek",
+    "grc": "Ancient Greek",
     "gu": "Gujarati",
     "he": "Hebrew",
     "hi": "Hindi",

orangecontrib/text/preprocess/normalize.py

@@ -84,46 +84,43 @@ def __init__(self, language='en'):
         self.normalizer = stem.SnowballStemmer(ISO2LANG[language].lower()).stem
 
 
-def language_to_name(language):
-    return language.lower().replace(' ', '') + 'ud'
-
-
-def file_to_name(file):
-    return file.replace('-', '').replace('_', '')
-
-
-def file_to_language(file):
-    return file[:file.find('ud') - 1] \
-        .replace('-', ' ').replace('_', ' ').capitalize()
-
-
 class UDPipeModels:
     server_url = "https://file.biolab.si/files/udpipe/"
 
+    # some languages differ between udpipe and iso standard
+    UDPIPE2LANG = {"Norwegian Bokmaal": "Norwegian Bokmål"}
+
     def __init__(self):
         self.local_data = os.path.join(data_dir(versioned=False), 'udpipe/')
         self.serverfiles = serverfiles.ServerFiles(self.server_url)
         self.localfiles = serverfiles.LocalFiles(self.local_data,
                                                  serverfiles=self.serverfiles)
 
     def __getitem__(self, language):
-        file_name = self._find_file(language_to_name(language))
+        file_name = self._find_file(language)
         return self.localfiles.localpath_download(file_name)
 
     @property
     def model_files(self):
         try:
-            return self.serverfiles.listfiles()
+            files = self.serverfiles.listfiles()
         except ConnectionError:
-            return self.localfiles.listfiles()
+            files = self.localfiles.listfiles()
+        return self.__files_to_dict(files)
 
     def _find_file(self, language):
-        return next(filter(lambda f: file_to_name(f).startswith(language),
-                           map(lambda f: f[0], self.model_files)))
+        return self.model_files[language][1]
+
+    def __files_to_dict(self, files):
+        iso2lang = {}
+        for f in files:
+            langauge, iso = self.__file_to_language(f[0])
+            iso2lang[iso] = (langauge, f[0])
+        return iso2lang
 
     @property
     def supported_languages(self):
-        return list(map(lambda f: file_to_language(f[0]), self.model_files))
+        return [(name, iso) for iso, (name, _) in self.model_files.items()]
 
     @property
     def online(self):
@@ -133,6 +130,32 @@ def online(self):
         except ConnectionError:
             return False
 
+    def __file_to_language(self, file):
+        """
+        Transform filenames to langauge strings and iso codes.
+        Language name has format "Language (Model)"
+        ISO code consist of real iso code which we add the model variation to for
+        example "en_lines" for lines english model.
+        """
+        # language and potential model variation are delimited with -
+        name_split = file[: file.find("ud") - 1].split("-")
+        # capitalize multi-word languages separated by _
+        lg = name_split[0].replace("_", " ").title()
+        # fix wrong spelling for Norwegian Bokmål
+        lg = self.UDPIPE2LANG.get(lg, lg)
+
+        if len(name_split) > 1:
+            # languages with multiple models have model name as second item in split
+            return f"{lg} ({name_split[1]})", self.__lang2iso(lg, name_split[1])
+        return lg, self.__lang2iso(lg, None)
+
+    @staticmethod
+    def __lang2iso(language, model):
+        language = [LANG2ISO[language]]
+        if model:
+            language.append(model)
+        return "_".join(language)
+
 
 class UDPipeStopIteration(StopIteration):
     pass
@@ -141,7 +164,7 @@ class UDPipeStopIteration(StopIteration):
 class UDPipeLemmatizer(BaseNormalizer):
     name = 'UDPipe Lemmatizer'
 
-    def __init__(self, language='English', use_tokenizer=False):
+    def __init__(self, language="en", use_tokenizer=False):
         super().__init__()
         self.__language = language
         self.__use_tokenizer = use_tokenizer

orangecontrib/text/tests/test_preprocess.py

@@ -20,12 +20,7 @@
     PreprocessorList,
     StopwordsFilter,
 )
-from orangecontrib.text.preprocess.normalize import (
-    file_to_language,
-    file_to_name,
-    language_to_name,
-    UDPipeModels,
-)
+from orangecontrib.text.preprocess.normalize import UDPipeModels
 
 
 SF_LIST = "orangecontrib.text.preprocess.normalize.serverfiles.ServerFiles.listfiles"
@@ -270,7 +265,7 @@ def test_call_word_net(self):
         self.assertEqual(len(corpus.used_preprocessor.preprocessors), 2)
 
     def test_call_UDPipe(self):
-        pp = preprocess.UDPipeLemmatizer(language="Lithuanian")
+        pp = preprocess.UDPipeLemmatizer(language="lt")
         self.assertFalse(self.corpus.has_tokens())
         corpus = pp(self.corpus)
         self.assertTrue(corpus.has_tokens())
@@ -304,7 +299,7 @@ def test_snowball_all_langs(self):
 
     def test_udpipe(self):
         """Test udpipe token lemmatization"""
-        normalizer = preprocess.UDPipeLemmatizer("Lithuanian")
+        normalizer = preprocess.UDPipeLemmatizer("lt")
         with self.corpus.unlocked():
             self.corpus.metas[0, 0] = "esu"
         corpus = normalizer(self.corpus)
@@ -313,15 +308,15 @@ def test_udpipe(self):
 
     def test_udpipe_doc(self):
         """Test udpipe lemmatization with its own tokenization"""
-        normalizer = preprocess.UDPipeLemmatizer("Lithuanian", True)
+        normalizer = preprocess.UDPipeLemmatizer("lt", True)
         with self.corpus.unlocked():
             self.corpus.metas[0, 0] = "Ant kalno dega namas"
         corpus = normalizer(self.corpus)
         self.assertListEqual(list(corpus.tokens[0]), ["ant", "kalno", "degas", "namas"])
         self.assertEqual(len(corpus.used_preprocessor.preprocessors), 1)
 
     def test_udpipe_pickle(self):
-        normalizer = preprocess.UDPipeLemmatizer("Lithuanian", True)
+        normalizer = preprocess.UDPipeLemmatizer("lt", True)
         # udpipe store model after first call - model is not picklable
         normalizer(self.corpus)
         loaded = pickle.loads(pickle.dumps(normalizer))
@@ -336,7 +331,7 @@ def test_udpipe_pickle(self):
         )
 
     def test_udpipe_deepcopy(self):
-        normalizer = preprocess.UDPipeLemmatizer("Lithuanian", True)
+        normalizer = preprocess.UDPipeLemmatizer("lt", True)
         copied = copy.deepcopy(normalizer)
         self.assertEqual(normalizer._UDPipeLemmatizer__language,
                          copied._UDPipeLemmatizer__language)
@@ -370,7 +365,7 @@ def test_normalizers_picklable(self):
         for nm in set(preprocess.normalize.__all__) - {"BaseNormalizer"}:
             normalizer = getattr(preprocess.normalize, nm)
             normalizer = (
-                normalizer(language="Lithuanian")
+                normalizer(language="lt")
                 if normalizer is preprocess.UDPipeLemmatizer
                 else normalizer()
             )
@@ -379,7 +374,7 @@ def test_normalizers_picklable(self):
             loaded(self.corpus)
 
     def test_cache(self):
-        normalizer = preprocess.UDPipeLemmatizer("Lithuanian")
+        normalizer = preprocess.UDPipeLemmatizer("lt")
         with self.corpus.unlocked():
             self.corpus.metas[0, 0] = "esu"
         normalizer(self.corpus)
@@ -395,21 +390,21 @@ def test_cache(self):
 class UDPipeModelsTests(unittest.TestCase):
     def test_label_transform(self, _):
         """Test helper functions for label transformation"""
-        self.assertEqual(file_to_language('slovenian-sst-ud-2.0-170801.udpipe'),
-                         'Slovenian sst')
-        self.assertEqual(file_to_name('slovenian-sst-ud-2.0-170801.udpipe'),
-                         'sloveniansstud2.0170801.udpipe')
-        self.assertEqual(language_to_name('Slovenian sst'), 'sloveniansstud')
+        fun = UDPipeModels()._UDPipeModels__file_to_language
+        r = fun("slovenian-sst-ud-2.0-170801.udpipe")
+        self.assertTupleEqual(r, ("Slovenian (sst)", "sl_sst"))
+        r = fun("norwegian_bokmaal-sst-ud-2.0-170801.udpipe")
+        self.assertTupleEqual(r, ("Norwegian Bokmål (sst)", "nb_sst"))
 
     @patch(SF_DOWNLOAD, download_patch)
     def test_udpipe_model(self, _):
         """Test udpipe models loading from server"""
         models = UDPipeModels()
-        self.assertIn("Lithuanian", models.supported_languages)
+        self.assertIn(('Lithuanian', 'lt'), models.supported_languages)
         self.assertEqual(7, len(models.supported_languages))
 
         local_file = os.path.join(models.local_data, "lithuanian-ud-2.0-170801.udpipe")
-        model = models["Lithuanian"]
+        model = models["lt"]
         self.assertEqual(model, local_file)
         self.assertTrue(os.path.isfile(local_file))
 
@@ -419,10 +414,11 @@ def test_udpipe_local_models(self, sf_mock):
         models = UDPipeModels()
         [models.localfiles.remove(f[0]) for f in models.localfiles.listfiles()]
         # use Uyghur, it is the smallest model, we can have it in the repository
-        _ = models["Lithuanian"]
+        _ = models["lt"]
         sf_mock.side_effect = ConnectionError()
-        self.assertIn("Lithuanian", UDPipeModels().supported_languages)
-        self.assertEqual(1, len(UDPipeModels().supported_languages))
+        exp = {"lt": ('Lithuanian', 'lithuanian-ud-2.0-170801.udpipe')}
+        self.assertDictEqual(exp, models.model_files)
+        self.assertListEqual([('Lithuanian', 'lt')], models.supported_languages)
 
     def test_udpipe_offline(self, sf_mock):
         """Test if UDPipe works offline"""