Add stand off varaiant and metadata

spacy-nlp

@@ -6,6 +6,7 @@ from xml.sax.saxutils import escape
 import chardet
 import spacy
 import textwrap
+import hashlib
 
 
 SPACY_MODELS = {'de': 'de_core_news_sm',
@@ -39,12 +40,19 @@ else:
     encoding = 'utf-8'
 
 
+# hashing in chunks to avoid full RAM with huge files.
+with open(args.i, 'rb') as input_file:
+    md5_hash = hashlib.md5()
+    for chunk in iter(lambda: input_file.read(128 * md5_hash.block_size), b''):
+        md5_hash.update(chunk)
+    md5_hash = md5_hash.hexdigest()
+
 # Load the text contents from the input file
 with open(args.i, encoding=encoding) as input_file:
     text = input_file.read()
     # spaCys NLP is limited to strings with maximum 1 million characters at
     # once. So we split it into suitable chunks.
-    text_chunks = textwrap.wrap(text, 1000000, break_long_words=False)
+    text_chunks = textwrap.wrap(text, 1000, break_long_words=False)
     # the text variable potentially occupies a lot of system memory and is no
     # longer needed...
     del text
@@ -56,21 +64,56 @@ nlp = spacy.load(SPACY_MODELS[args.language])
 
 # Create the output file in verticalized text format
 # See: http://cwb.sourceforge.net/files/CWB_Encoding_Tutorial/node3.html
-output_file = open(args.o, 'w+')
-output_file.write('<?xml version="1.0" encoding="UTF-8"?>\n<corpus>\n<text>\n')
-for text_chunk in text_chunks:
-    doc = nlp(text_chunk)
-    for sent in doc.sents:
-        output_file.write('<s>\n')
-        for token in sent:
+output_file_original_filename = args.o
+output_file_stand_off_filename = args.o.replace('.vrt', '.stand-off.vrt')
+output_file_tokens_filename = args.o.replace('.vrt', '.tokens.txt')
+xml_head = '''<?xml version="1.0" encoding="UTF-8"?>\n\
+<corpus>\n\
+<text>\n\
+<metadata\n\
+    spacyVersion="{spacy_version}"
+    spacyModel="{spacy_model}"
+    md5HashOfInput="{md5_hash}">\n'''.format(md5_hash=md5_hash,
+                                             spacy_version=spacy.__version__,
+                                             spacy_model=SPACY_MODELS[args.language])
+
+with open(output_file_original_filename, 'w+') as output_file_original, \
+     open(output_file_stand_off_filename, 'w+') as output_file_stand_off, \
+     open(output_file_tokens_filename, 'w+') as output_file_tokens:
+
+    output_file_original.write(xml_head)
+    output_file_stand_off.write(xml_head)
+    output_file_tokens.write(xml_head)
+    text_offset = 0
+    for text_chunk in text_chunks:
+        doc = nlp(text_chunk)
+        for sent in doc.sents:
+            output_file_original.write('<s>\n')
+            output_file_stand_off.write('<s>\n')
+            space_flag = False
             # Skip whitespace tokens
-            if token.text.isspace():
-                continue
-            output_file.write('{}'.format(escape(token.text))
-                              + '\t{}'.format(escape(token.lemma_))
-                              + '\t{}'.format(token.pos_)
-                              + '\t{}'.format(token.tag_)
-                              + '\t{}\n'.format(token.ent_type_ or 'NULL'))
-        output_file.write('</s>\n')
-output_file.write('</text>\n</corpus>')
-output_file.close()
+            sent_no_space = [token for token in sent if not token.text.isspace()]
+            # No space variant for cwb original .vrt file input.
+            for token in sent_no_space:
+                output_file_original.write('{}'.format(escape(token.text))
+                                           + '\t{}'.format(escape(token.lemma_))
+                                           + '\t{}'.format(token.pos_)
+                                           + '\t{}'.format(token.tag_)
+                                           + '\t{}\n'.format(token.ent_type_ or 'NULL'))
+            # Stand off variant with spaces.
+            for token in sent:
+                token_start = token.idx + text_offset
+                token_end = token.idx + len(token.text) + text_offset
+                output_file_stand_off.write('{}:{}'.format(token_start,
+                                                           token_end)
+                                            + '\t{}'.format(escape(token.lemma_))
+                                            + '\t{}'.format(token.pos_)
+                                            + '\t{}'.format(token.tag_)
+                                            + '\t{}\n'.format(token.ent_type_ or 'NULL'))
+                output_file_tokens.write('{}\n'.format(escape(token.text)))
+            output_file_original.write('</s>\n')
+            output_file_stand_off.write('</s>\n')
+        text_offset = token_end + 1
+    output_file_original.write('</metadata>\n</text>\n</corpus>')
+    output_file_stand_off.write('</metadata>\n</text>\n</corpus>')
+    output_file_tokens.write('</metadata>\n</text>\n</corpus>')