fix PEP8 issues

Author: Chakri Lowphansirikul

pythainlp/tag/named_entity.py

@@ -90,7 +90,7 @@ def __init__(self):
         )
 
     def get_ner(
-        self, text: str, pos: bool = True, tag:bool = False
+        self, text: str, pos: bool = True, tag: bool = False
     ) -> Union[List[Tuple[str, str]], List[Tuple[str, str, str]]]:
         """
         This function tags named-entitiy from text in IOB format.
@@ -99,9 +99,9 @@ def get_ner(
         :param boolean pos: To include POS tags in the results (`True`) or
                             exclude (`False`). The defualt value is `True`
         :param boolean tag: output like html tag.
-        :return: a list of tuple associated with tokenized word, NER tag, 
+        :return: a list of tuple associated with tokenized word, NER tag,
                  POS tag (if the parameter `pos` is specified as `True`),
-                 and output like html tag (if the parameter `tag` is 
+                 and output like html tag (if the parameter `tag` is
                  specified as `True`).
                  Otherwise, return a list of tuple associated with tokenized
                  word and NER tag
@@ -128,8 +128,8 @@ def get_ner(
             ('49', 'NUM', 'I-TIME'), (' ', 'PUNCT', 'I-TIME'),
             ('น.', 'NOUN', 'I-TIME')]
             >>>
-            >>> ner.get_ner("วันที่ 15 ก.ย. 61 ทดสอบระบบเวลา 14:49 น.", \\
-                pos=False)
+            >>> ner.get_ner("วันที่ 15 ก.ย. 61 ทดสอบระบบเวลา 14:49 น.",
+                            pos=False)
             [('วันที่', 'O'), (' ', 'O'),
             ('15', 'B-DATE'), (' ', 'I-DATE'),
             ('ก.ย.', 'I-DATE'), (' ', 'I-DATE'),
@@ -139,7 +139,8 @@ def get_ner(
             ('14', 'B-TIME'), (':', 'I-TIME'),
             ('49', 'I-TIME'), (' ', 'I-TIME'),
             ('น.', 'I-TIME')]
-            >>> ner.get_ner("วันที่ 15 ก.ย. 61 ทดสอบระบบเวลา 14:49 น.",tag=True)
+            >>> ner.get_ner("วันที่ 15 ก.ย. 61 ทดสอบระบบเวลา 14:49 น.",
+                            tag=True)
             'วันที่ <DATE>15 ก.ย. 61</DATE> ทดสอบระบบเวลา <TIME>14:49 น.</TIME>'
         """
         self.__tokens = word_tokenize(text, engine=_WORD_TOKENIZER)
@@ -149,19 +150,20 @@ def get_ner(
         self.__x_test = self.__extract_features(self.__pos_tags)
         self.__y = self.crf.predict_single(self.__x_test)
 
-        self.sent_ner = [(self.__pos_tags[i][0], data) for i, data in enumerate(self.__y)]
+        self.sent_ner = [(self.__pos_tags[i][0], data)
+                         for i, data in enumerate(self.__y)]
         if tag:
-            self.temp=""
-            self.sent=""
-            for idx,(word,ner) in enumerate(self.sent_ner):
+            self.temp = ""
+            self.sent = ""
+            for idx, (word, ner) in enumerate(self.sent_ner):
                 if "B-" in ner:
-                    self.temp = ner.replace("B-","")
+                    self.temp = ner.replace("B-", "")
                     self.sent += "<"+self.temp+">"
-                elif "O"== ner and self.temp!="":
-                    self.sent+="</"+self.temp+">"
-                    self.temp=""
+                elif "O" == ner and self.temp != "":
+                    self.sent += "</"+self.temp+">"
+                    self.temp = ""
                 self.sent += word
-                if idx == len(self.sent_ner)-1 and self.temp!="":
+                if idx == len(self.sent_ner)-1 and self.temp != "":
                     self.sent += "</"+self.temp+">"
             return self.sent
         elif pos:
@@ -172,7 +174,6 @@ def get_ner(
         else:
             return self.sent_ner
 
-
     @staticmethod
     def __extract_features(doc):
         return [_doc2features(doc, i) for i in range(len(doc))]