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c0f31c1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 | import logging
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
import re
class TextPreprocessor:
def __init__(self):
try:
self.stopwords = set(stopwords.words('english'))
self.lemmatizer = WordNetLemmatizer()
self.logger = logging.getLogger(__name__)
except Exception as e:
self.logger.error(f"Failed to initialize NLTK resources: {e}")
raise
def standardize_case(self, text):
return text.lower()
def remove_punctuation(self, text):
return re.sub(r'[^\w\s]', '', text)
def normalize_whitespace(self, text):
return re.sub(r'\s+', ' ', text).strip()
def remove_stopwords(self, words):
return [word for word in words if word not in self.stopwords]
def lemmatize_words(self, words):
return [self.lemmatizer.lemmatize(word) for word in words]
def remove_headers_and_footers(self, text, aggressive=False, pattern=None):
try:
if not text or not text.strip():
return text
lines = text.splitlines()
if len(lines) <= 4: # For very short text, don't remove anything
return text
# Store original lines for fallback
original_lines = lines.copy()
# Use different strategies based on document characteristics
if self._appears_to_be_slide(lines):
# Slide-friendly approach - only remove obvious headers/footers
cleaned_lines = self._clean_slide_headers_footers(lines, pattern)
elif aggressive:
# Traditional document approach - remove first/last few lines
num_lines = 2
cleaned_lines = lines[num_lines:-num_lines]
else:
# Conservative approach - only remove based on patterns
cleaned_lines = self._pattern_based_removal(lines, pattern)
# If we removed too much (over 30% of content), revert to original
if len(cleaned_lines) < len(lines) * 0.7:
self.logger.warning("Header/footer removal eliminated too much content, reverting")
cleaned_lines = original_lines
# Additional heuristic: Remove single-word lines that might be page numbers
cleaned_lines = [line for line in cleaned_lines
if not (len(line.strip().split()) == 1 and
line.strip().isdigit())]
# Join lines back into text
return '\n'.join(cleaned_lines)
except Exception as e:
self.logger.error(f"Error removing headers/footers: {e}")
return text # Return original text on error
def _appears_to_be_slide(self, lines):
"""Detect if the content appears to be from a slide/presentation."""
# Characteristics of slides:
# - Shorter overall text
# - Fewer lines
# - More bullet points
# - Title followed by bullet points
if len(lines) < 15: # Short content
return True
# Check for bullet point patterns
bullet_pattern = r'^\s*[•\-\*\>\◦\○\◆\◇\▪\▫\⚫\⚪\✓\✔\✕\✖\✗\✘]'
bullet_lines = sum(1 for line in lines if re.match(bullet_pattern, line))
# If more than 20% of lines are bullets, likely a slide
if bullet_lines > len(lines) * 0.2:
return True
# If first non-empty line is short (likely a title) and followed by bullet points
non_empty_lines = [line for line in lines if line.strip()]
if non_empty_lines and len(non_empty_lines[0].strip()) < 60:
# Check for bullet points in the following lines
for line in non_empty_lines[1:4]: # Check next few lines
if re.match(bullet_pattern, line):
return True
return False
def _clean_slide_headers_footers(self, lines, pattern=None):
"""Clean headers/footers from slide-based content."""
cleaned_lines = lines.copy()
# For slides, we primarily rely on pattern matching rather than line position
if pattern:
cleaned_lines = [line for line in cleaned_lines
if not re.search(pattern, line)]
# Common slide footer patterns to remove
footer_patterns = [
r'^\s*\d+\s*$', # Standalone page number
r'confidential', # Confidentiality notices
r'all rights reserved',
r'proprietary',
r'^\s*www\.', # Website in footer
r'^\s*https?://', # URL in footer
r'\bpage\s+\d+\b', # "Page X" footer
r'^\s*[©Ⓒ]\s*\d{4}' # Copyright notice
]
# Combine all patterns
combined_pattern = '|'.join(f'({p})' for p in footer_patterns)
# Filter out footer lines
if combined_pattern:
cleaned_lines = [line for line in cleaned_lines
if not re.search(combined_pattern, line, re.IGNORECASE)]
return cleaned_lines
def _pattern_based_removal(self, lines, pattern=None):
"""Remove headers/footers based only on patterns, not position."""
if not pattern:
# Default patterns for headers/footers
patterns = [
r'^\s*\d+\s*$', # Standalone page numbers
r'^\s*page\s+\d+\s+of\s+\d+\s*$', # Page X of Y
r'^\s*[©Ⓒ]\s*\d{4}.*$', # Copyright lines
r'^\s*confidential\s*$', # Confidentiality markers
r'^\s*https?://.*$', # URLs alone on a line
r'^\s*www\..*$', # Website alone on a line
r'^\s*[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}\s*$' # Email addresses
]
combined_pattern = '|'.join(f'({p})' for p in patterns)
else:
combined_pattern = pattern
return [line for line in lines
if not re.search(combined_pattern, line, re.IGNORECASE)]
def remove_common_pdf_artifacts(self, text):
try:
# Remove form field indicators
text = re.sub(r'\[\s*\]\s*|\[\s*X\s*\]|\(\s*\)\s*|\(\s*X\s*\)', '', text)
# Remove common PDF annotations
text = re.sub(r'<<[^>]*>>', '', text)
# Remove artifact markers often found in PDFs
text = re.sub(r'obj\s*\d+\s*\d+\s*R', '', text)
return text
except Exception as e:
self.logger.error(f"Error removing PDF artifacts: {e}")
return text
def preprocess(self, text, remove_headers_footers=True, aggressive_removal=False):
try:
if remove_headers_footers:
text = self.remove_headers_and_footers(text, aggressive=aggressive_removal)
text = self.remove_common_pdf_artifacts(text)
text = self.standardize_case(text)
text = self.remove_punctuation(text)
text = self.normalize_whitespace(text)
words = text.split()
words = self.remove_stopwords(words)
words = self.lemmatize_words(words)
return ' '.join(words)
except Exception as e:
self.logger.error(f"Error preprocessing text: {e}")
raise |