Merge pull request #117 from DHANUSHRAJA22/feature/html-file-support

feat: Add comprehensive HTML file support with intelligent parsing and minimal dependenciesfeat: Add HTML file support for instrument loadingfeat: Add HTML file support for instrument loadingFeature/html file support

Author: woodthom2

src/harmony/parsing/html_parser.py

@@ -0,0 +1,257 @@
+'''
+MIT License
+Copyright (c) 2023 Ulster University (https://www.ulster.ac.uk).
+Project: Harmony (https://harmonydata.ac.uk)
+Maintainer: Thomas Wood (https://fastdatascience.com)
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+'''
+
+from typing import List
+from harmony.schemas.requests.text import RawFile, Instrument, Question
+from harmony.parsing.util import normalise_text
+
+# Try to import BeautifulSoup, fall back to basic text extraction if not available
+try:
+    from bs4 import BeautifulSoup
+    BEAUTIFULSOUP_AVAILABLE = True
+except ImportError:
+    BEAUTIFULSOUP_AVAILABLE = False
+    
+# Try to import lxml for better performance, fall back to html.parser
+try:
+    import lxml
+    DEFAULT_PARSER = 'lxml'
+except ImportError:
+    DEFAULT_PARSER = 'html.parser'
+
+
+def convert_html_to_instruments(file: RawFile) -> List[Instrument]:
+    """
+    Convert HTML file to Harmony instruments by extracting text content.
+    
+    This function parses HTML files and extracts meaningful text content,
+    attempting to preserve semantic structure while removing HTML tags.
+    Uses BeautifulSoup if available for better parsing, otherwise falls
+    back to basic text extraction.
+    
+    Args:
+        file (RawFile): The raw HTML file to parse
+        
+    Returns:
+        List[Instrument]: List of instruments extracted from the HTML
+    """
+    
+    if not file.content:
+        return []
+    
+    # Extract text content from HTML
+    if BEAUTIFULSOUP_AVAILABLE:
+        text_content = _extract_text_with_beautifulsoup(file.content)
+    else:
+        text_content = _extract_text_basic(file.content)
+    
+    if not text_content.strip():
+        return []
+    
+    # Create questions from extracted text
+    questions = _extract_questions_from_text(text_content)
+    
+    if not questions:
+        return []
+    
+    # Create instrument
+    instrument = Instrument(
+        file_id=file.file_id,
+        instrument_name=file.file_name or "HTML Document",
+        questions=questions,
+        language="en"  # Default to English, could be enhanced with language detection
+    )
+    
+    return [instrument]
+
+
+def _extract_text_with_beautifulsoup(html_content: str) -> str:
+    """
+    Extract text content from HTML using BeautifulSoup.
+    
+    This provides better text extraction by:
+    - Removing script and style tags
+    - Preserving semantic structure
+    - Handling HTML entities properly
+    
+    Args:
+        html_content (str): Raw HTML content
+        
+    Returns:
+        str: Extracted text content
+    """
+    try:
+        soup = BeautifulSoup(html_content, DEFAULT_PARSER)
+        
+        # Remove script and style elements
+        for element in soup(["script", "style"]):
+            element.decompose()
+        
+        # Get text content
+        text = soup.get_text()
+        
+        # Clean up whitespace
+        lines = (line.strip() for line in text.splitlines())
+        chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
+        text = ' '.join(chunk for chunk in chunks if chunk)
+        
+        return text
+        
+    except Exception as e:
+        # Fall back to basic extraction if BeautifulSoup fails
+        return _extract_text_basic(html_content)
+
+
+def _extract_text_basic(html_content: str) -> str:
+    """
+    Basic text extraction from HTML without external dependencies.
+    
+    This is a fallback method that uses simple string operations
+    to remove HTML tags when BeautifulSoup is not available.
+    
+    Args:
+        html_content (str): Raw HTML content
+        
+    Returns:
+        str: Extracted text content
+    """
+    import re
+    
+    # Remove HTML tags
+    text = re.sub(r'<[^>]+>', ' ', html_content)
+    
+    # Handle common HTML entities
+    html_entities = {
+        '&amp;': '&',
+        '&lt;': '<',
+        '&gt;': '>',
+        '&quot;': '"',
+        '&apos;': "'",
+        '&nbsp;': ' '
+    }
+    
+    for entity, replacement in html_entities.items():
+        text = text.replace(entity, replacement)
+    
+    # Clean up whitespace
+    text = re.sub(r'\s+', ' ', text).strip()
+    
+    return text
+
+
+def _extract_questions_from_text(text: str) -> List[Question]:
+    """
+    Extract potential questions from text content.
+    
+    This function looks for question-like patterns in the text and
+    creates Question objects from them. It uses heuristics to identify
+    sentences that might be questionnaire items.
+    
+    Args:
+        text (str): Extracted text content
+        
+    Returns:
+        List[Question]: List of identified questions
+    """
+    questions = []
+    
+    # Normalize the text
+    normalized_text = normalise_text(text)
+    
+    # Split into sentences/lines for potential questions
+    # Use multiple delimiters to split the text
+    import re
+    sentences = re.split(r'[.!?\n\r]+', normalized_text)
+    
+    for i, sentence in enumerate(sentences):
+        sentence = sentence.strip()
+        
+        # Skip very short or empty sentences
+        if len(sentence) < 10:
+            continue
+            
+        # Skip sentences that are likely not questions
+        if _is_likely_question(sentence):
+            question = Question(
+                question_no=str(i + 1),
+                question_intro="",
+                question_text=sentence,
+                options=None,
+                source_page=1
+            )
+            questions.append(question)
+    
+    return questions
+
+
+def _is_likely_question(text: str) -> bool:
+    """
+    Determine if a text segment is likely to be a questionnaire item.
+    
+    Uses heuristics to identify potential questionnaire items:
+    - Contains question words or patterns
+    - Has appropriate length
+    - Doesn't look like navigation or metadata
+    
+    Args:
+        text (str): Text segment to evaluate
+        
+    Returns:
+        bool: True if the text is likely a question
+    """
+    text_lower = text.lower()
+    
+    # Skip navigation and common non-question patterns
+    skip_patterns = [
+        'click here', 'read more', 'continue', 'next', 'previous',
+        'home', 'about', 'contact', 'privacy', 'terms',
+        'copyright', 'all rights reserved', 'menu', 'navigation'
+    ]
+    
+    for pattern in skip_patterns:
+        if pattern in text_lower:
+            return False
+    
+    # Look for question indicators
+    question_indicators = [
+        'how', 'what', 'when', 'where', 'why', 'who', 'which',
+        'do you', 'are you', 'have you', 'would you', 'could you',
+        'please', 'rate', 'scale', 'agree', 'disagree', 'often',
+        'never', 'sometimes', 'always', 'feel', 'think', 'believe'
+    ]
+    
+    # Check for question indicators
+    for indicator in question_indicators:
+        if indicator in text_lower:
+            return True
+    
+    # Check if it ends with a question mark
+    if text.strip().endswith('?'):
+        return True
+    
+    # Check length - typical questionnaire items are of reasonable length
+    if 20 <= len(text) <= 200:
+        # Additional heuristics for questionnaire-like content
+        if any(word in text_lower for word in ['you', 'your', 'i', 'my']):
+            return True
+    
+    return False

src/harmony/parsing/wrapper_all_parsers.py

@@ -1,58 +1,61 @@
 '''
 MIT License
-
 Copyright (c) 2023 Ulster University (https://www.ulster.ac.uk).
 Project: Harmony (https://harmonydata.ac.uk)
 Maintainer: Thomas Wood (https://fastdatascience.com)
-
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
 to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 copies of the Software, and to permit persons to whom the Software is
 furnished to do so, subject to the following conditions:
-
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.
-
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
-
 '''
 
 from typing import List
-
 from harmony.parsing.excel_parser import convert_excel_to_instruments
 from harmony.parsing.pdf_parser import convert_pdf_to_instruments
 from harmony.parsing.text_parser import convert_text_to_instruments
+from harmony.parsing.html_parser import convert_html_to_instruments
 from harmony.schemas.enums.file_types import FileType
 from harmony.schemas.requests.text import RawFile, Instrument
 
 
 def _get_instruments_from_file(file):
+    """
+    Route files to appropriate parsers based on file type.
+    
+    Args:
+        file: RawFile object containing file content and metadata
+        
+    Returns:
+        List[Instrument]: Parsed instruments from the file
+    """
     if file.file_type == FileType.pdf or file.file_type == FileType.docx:
         instruments_from_this_file = convert_pdf_to_instruments(file)
     elif file.file_type == FileType.txt or file.file_type == FileType.csv:
         instruments_from_this_file = convert_text_to_instruments(file)
     elif file.file_type == FileType.xlsx:
         instruments_from_this_file = convert_excel_to_instruments(file)
+    elif file.file_type == FileType.html or file.file_type == FileType.htm:
+        instruments_from_this_file = convert_html_to_instruments(file)
     else:
         instruments_from_this_file = []
     return instruments_from_this_file
 
 
 def convert_files_to_instruments(files: List[RawFile]) -> List[Instrument]:
     """Convert files to instruments"""
-
     instruments = []
-
     for file in files:
         instruments_from_this_file = _get_instruments_from_file(file)
         instruments.extend(instruments_from_this_file)
-
     return instruments

src/harmony/schemas/enums/file_types.py

@@ -1,36 +1,34 @@
 '''
 MIT License
-
 Copyright (c) 2023 Ulster University (https://www.ulster.ac.uk).
 Project: Harmony (https://harmonydata.ac.uk)
 Maintainer: Thomas Wood (https://fastdatascience.com)
-
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
 to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 copies of the Software, and to permit persons to whom the Software is
 furnished to do so, subject to the following conditions:
-
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.
-
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
-
 '''
 
 from enum import Enum
 
 
 class FileType(str, Enum):
+    """Enumeration of supported file types for Harmony parsing."""
     pdf: str = 'pdf'
     xlsx: str = 'xlsx'
     txt: str = 'txt'
     csv: str = 'csv'
     docx: str = 'docx'
+    html: str = 'html'
+    htm: str = 'htm'