Update file handling. Now md5 is correct

spacy-nlp

@@ -16,29 +16,32 @@ spacy_models = {spacy.info(pipeline)['lang']: pipeline
 
 # Parse the given arguments
 parser = ArgumentParser(description='Create annotations for a given txt file')
-parser.add_argument('input', metavar='Path to txt input file')
-parser.add_argument('output', metavar='Path to JSON output file')
+parser.add_argument('input', help='Path to txt input file')
+parser.add_argument('output', help='Path to JSON output file')
 parser.add_argument('-l', '--language',
                     choices=spacy_models.keys(),
+                    help='Language of the input (2-character ISO 639-1 language codes)',  # noqa
                     required=True)
-parser.add_argument('-c', '--check-encoding', action='store_true')
+parser.add_argument('-c', '--check-encoding',
+                    action='store_true',
+                    help='Check encoding of the input file, UTF-8 is used instead')  # noqa
 args = parser.parse_args()
 
+if args.check_encoding:
+    with open(args.input, "rb") as text_file:
+        if args.check_encoding:
+            encoding = chardet.detect(text_file.read())['encoding']
+        else:
+            encoding = 'utf-8'
 
-# If requested: Check the encoding of the text contents from the input file
-# Else: Use utf-8
 with open(args.input, "rb") as text_file:
-    if args.check_encoding:
-        encoding = chardet.detect(text_file.read())['encoding']
-    else:
-        encoding = 'utf-8'
     text_md5 = hashlib.md5()
     for chunk in iter(lambda: text_file.read(128 * text_md5.block_size), b''):
         text_md5.update(chunk)
 
 # Load the text contents from the input file
 with open(args.input, encoding=encoding) as text_file:
-    # spaCy NLP is limited to strings with maximum 1 million characters at
+    # spaCy NLP is limited to strings with a maximum of 1 million characters at
     # once. So we split it into suitable chunks.
     text_chunks = textwrap.wrap(
         text_file.read(),