Making lang/th/test_tokenizer.py pass by creating ThaiTokenizer (#3078)

spacy/lang/ja/__init__.py

@@ -1,20 +1,22 @@
 # encoding: utf8
 from __future__ import unicode_literals, print_function
 
-from ...language import Language
-from ...attrs import LANG
-from ...tokens import Doc, Token
-from ...tokenizer import Tokenizer
-from .tag_map import TAG_MAP
-
 import re
 from collections import namedtuple
 
+from .tag_map import TAG_MAP
+
+from ...attrs import LANG
+from ...language import Language
+from ...tokens import Doc, Token
+from ...util import DummyTokenizer
+
 ShortUnitWord = namedtuple('ShortUnitWord', ['surface', 'lemma', 'pos'])
 
 # XXX Is this the right place for this?
 Token.set_extension('mecab_tag', default=None)
 
+
 def try_mecab_import():
     """Mecab is required for Japanese support, so check for it.
 
@@ -26,6 +28,7 @@ def try_mecab_import():
         raise ImportError("Japanese support requires MeCab: "
                           "https://github.com/SamuraiT/mecab-python3")
 
+
 def resolve_pos(token):
     """If necessary, add a field to the POS tag for UD mapping.
 
@@ -40,81 +43,76 @@ def resolve_pos(token):
     # PoS mappings.
 
     if token.pos == '連体詞,*,*,*':
-        if re.match('^[こそあど此其彼]の', token.surface):
+        if re.match(r'[こそあど此其彼]の', token.surface):
             return token.pos + ',DET'
-        if re.match('^[こそあど此其彼]', token.surface):
+        if re.match(r'[こそあど此其彼]', token.surface):
             return token.pos + ',PRON'
-        else:
+        return token.pos + ',ADJ'
-            return token.pos + ',ADJ'
+
     return token.pos
 
+
 def detailed_tokens(tokenizer, text):
     """Format Mecab output into a nice data structure, based on Janome."""
 
     node = tokenizer.parseToNode(text)
-    node = node.next # first node is beginning of sentence and empty, skip it
+    node = node.next  # first node is beginning of sentence and empty, skip it
     words = []
     while node.posid != 0:
         surface = node.surface
-        base = surface # a default value. Updated if available later.
+        base = surface  # a default value. Updated if available later.
         parts = node.feature.split(',')
         pos = ','.join(parts[0:4])
 
         if len(parts) > 7:
-            # this information is only available for words in the tokenizer dictionary
+            # this information is only available for words in the tokenizer
+            # dictionary
             base = parts[7]
 
-        words.append( ShortUnitWord(surface, base, pos) )
+        words.append(ShortUnitWord(surface, base, pos))
         node = node.next
     return words
 
-class JapaneseTokenizer(object):
+
+class JapaneseTokenizer(DummyTokenizer):
     def __init__(self, cls, nlp=None):
         self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
 
-        MeCab = try_mecab_import()
+        self.tokenizer = try_mecab_import().Tagger()
-        self.tokenizer = MeCab.Tagger()
         self.tokenizer.parseToNode('')  # see #2901
 
     def __call__(self, text):
         dtokens = detailed_tokens(self.tokenizer, text)
+
         words = [x.surface for x in dtokens]
-        doc = Doc(self.vocab, words=words, spaces=[False]*len(words))
+        spaces = [False] * len(words)
+        doc = Doc(self.vocab, words=words, spaces=spaces)
+
         for token, dtoken in zip(doc, dtokens):
             token._.mecab_tag = dtoken.pos
             token.tag_ = resolve_pos(dtoken)
             token.lemma_ = dtoken.lemma
+
         return doc
 
-    # add dummy methods for to_bytes, from_bytes, to_disk and from_disk to
-    # allow serialization (see #1557)
-    def to_bytes(self, **exclude):
-        return b''
-
-    def from_bytes(self, bytes_data, **exclude):
-        return self
-
-    def to_disk(self, path, **exclude):
-        return None
-
-    def from_disk(self, path, **exclude):
-        return self
 
 class JapaneseDefaults(Language.Defaults):
     lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
-    lex_attr_getters[LANG] = lambda text: 'ja'
+    lex_attr_getters[LANG] = lambda _text: 'ja'
+
     tag_map = TAG_MAP
 
     @classmethod
     def create_tokenizer(cls, nlp=None):
         return JapaneseTokenizer(cls, nlp)
 
+
 class Japanese(Language):
     lang = 'ja'
     Defaults = JapaneseDefaults
-    Tokenizer = JapaneseTokenizer
 
     def make_doc(self, text):
         return self.tokenizer(text)
 
+
 __all__ = ['Japanese']

spacy/lang/th/__init__.py

@@ -5,34 +5,49 @@ from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
 from .tag_map import TAG_MAP
 from .stop_words import STOP_WORDS
 
-from ..tokenizer_exceptions import BASE_EXCEPTIONS
+from ...attrs import LANG
-from ...tokens import Doc
-from ..norm_exceptions import BASE_NORMS
 from ...language import Language
-from ...attrs import LANG, NORM
+from ...tokens import Doc
-from ...util import update_exc, add_lookups
+from ...util import DummyTokenizer
+
+
+class ThaiTokenizer(DummyTokenizer):
+    def __init__(self, cls, nlp=None):
+        try:
+            from pythainlp.tokenize import word_tokenize
+        except ImportError:
+            raise ImportError(
+                "The Thai tokenizer requires the PyThaiNLP library: "
+                "https://github.com/PyThaiNLP/pythainlp")
+
+        self.word_tokenize = word_tokenize
+        self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
+
+    def __call__(self, text):
+        words = list(self.word_tokenize(text, "newmm"))
+        spaces = [False] * len(words)
+        return Doc(self.vocab, words=words, spaces=spaces)
 
 
 class ThaiDefaults(Language.Defaults):
     lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
-    lex_attr_getters[LANG] = lambda text: 'th'
+    lex_attr_getters[LANG] = lambda _text: 'th'
+
     tokenizer_exceptions = dict(TOKENIZER_EXCEPTIONS)
     tag_map = TAG_MAP
     stop_words = STOP_WORDS
 
+    @classmethod
+    def create_tokenizer(cls, nlp=None):
+        return ThaiTokenizer(cls, nlp)
+
 
 class Thai(Language):
     lang = 'th'
     Defaults = ThaiDefaults
 
     def make_doc(self, text):
-        try:
+        return self.tokenizer(text)
-            from pythainlp.tokenize import word_tokenize
-        except ImportError:
-            raise ImportError("The Thai tokenizer requires the PyThaiNLP library: "
-                              "https://github.com/PyThaiNLP/pythainlp")
-        words = [x for x in list(word_tokenize(text,"newmm"))]
-        return Doc(self.vocab, words=words, spaces=[False]*len(words))
 
 
 __all__ = ['Thai']

spacy/util.py

@@ -635,3 +635,19 @@ class SimpleFrozenDict(dict):
 
     def update(self, other):
         raise NotImplementedError(Errors.E095)
+
+
+class DummyTokenizer(object):
+    # add dummy methods for to_bytes, from_bytes, to_disk and from_disk to
+    # allow serialization (see #1557)
+    def to_bytes(self, **exclude):
+        return b''
+
+    def from_bytes(self, _bytes_data, **exclude):
+        return self
+
+    def to_disk(self, _path, **exclude):
+        return None
+
+    def from_disk(self, _path, **exclude):
+        return self