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wordless/wl_nlp/wl_token_processing.py

Summary

Maintainability
C
1 day
Test Coverage

Avoid deeply nested control flow statements.
Open

                    for token in sentence_seg:
                        if token.tag is not None:
                            token.tag = token.tag.lower()

                        if token.lemma is not None:
Severity: Major
Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

    Avoid deeply nested control flow statements.
    Open

                        for sentence_seg in sentence:
                        for i, token in enumerate(sentence_seg):
                            if token.isupper():
                                sentence_seg[i] = wl_texts.Wl_Token('')
        # Title Case
    Severity: Major
    Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

      Avoid deeply nested control flow statements.
      Open

                          for sentence_seg in sentence:
                        for i, token in enumerate(sentence_seg):
                            if token.istitle():
                                sentence_seg[i] = wl_texts.Wl_Token('')
    else:
      Severity: Major
      Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

        Avoid deeply nested control flow statements.
        Open

                            for sentence_seg in sentence:
                        for i, token in enumerate(sentence_seg):
                            # Convert to strings to ignore tags and punctuation marks, if any, when checking for stop words
                            if token.lower() in stop_words:
                                sentence_seg[i] = wl_texts.Wl_Token('')
        Severity: Major
        Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

          Avoid deeply nested control flow statements.
          Open

                              for sentence_seg in sentence:
                        for i, token in enumerate(sentence_seg):
                            if token.islower():
                                sentence_seg[i] = wl_texts.Wl_Token('')
        # Uppercase
          Severity: Major
          Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

            Avoid deeply nested control flow statements.
            Open

                                for i, token in enumerate(sentence_seg):
                        if wl_checks_tokens.is_num(token):
                            sentence_seg[i] = wl_texts.Wl_Token('')

    # Replace token texts with lemmas
            Severity: Major
            Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

              Avoid deeply nested control flow statements.
              Open

                                  if i == 0 and j == 0 and k == 0:
                        tokens = []

                        for l, token in enumerate(sentence_seg):
                            # Do not remove the first token and set it to an empty token instead if it is a punctuation mark
              Severity: Major
              Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

                Avoid deeply nested control flow statements.
                Open

                                    for sentence_seg in sentence:
                        for i, token in enumerate(sentence_seg):
                            # Convert to strings to ignore tags and punctuation marks, if any, when checking for stop words
                            if str(token) in stop_words:
                                sentence_seg[i] = wl_texts.Wl_Token('')
                Severity: Major
                Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

                  Avoid deeply nested control flow statements.
                  Open

                                      for i, token in enumerate(sentence_seg):
                        if wl_checks_tokens.is_word_alphabetic(token):
                            sentence_seg[i] = wl_texts.Wl_Token('')

    # Numerals
                  Severity: Major
                  Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

                    Avoid deeply nested control flow statements.
                    Open

                                        for token in sentence_seg:
                        if wl_checks_tokens.is_punc(token.head):
                            token.head = None
                    Severity: Major
                    Found in wordless/wl_nlp/wl_token_processing.py - About 45 mins to fix

                      Consider simplifying this complex logical expression.
                      Open

                          if (
        token_settings.get('apply_lemmatization', False)
        or search_settings['match_inflected_forms']
        or (
            search_settings['context_settings']['incl']['incl']
                      Severity: Major
                      Found in wordless/wl_nlp/wl_token_processing.py - About 40 mins to fix

                        Function wl_process_tokens_concordancer has 5 arguments (exceeds 4 allowed). Consider refactoring.
                        Open

                        def wl_process_tokens_concordancer(main, text, token_settings, search_settings, preserve_blank_lines = False):
                        Severity: Minor
                        Found in wordless/wl_nlp/wl_token_processing.py - About 35 mins to fix

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