heatmap / backend /data_sources /base /data_validator.py
Ndg07's picture
Feat: 24-hour cleanup for local SQLite
c293f7c
#!/usr/bin/env python3
"""
Data validation utilities for ensuring quality of ingested events.
Implements multi-layer filtering and validation logic.
"""
import logging
import re
from typing import Dict, List, Optional, Set
from datetime import datetime, timedelta
from .base_connector import RawEvent
logger = logging.getLogger(__name__)
class DataValidator:
"""Multi-layer data validation for raw events."""
def __init__(self, config: Dict = None):
"""Initialize validator with configuration.
Args:
config: Validation configuration dictionary
"""
self.config = config or {}
# Content quality thresholds
self.min_content_length = self.config.get('min_content_length', 10)
self.max_content_length = self.config.get('max_content_length', 50000)
self.min_word_count = self.config.get('min_word_count', 3)
# Language settings
self.allowed_languages = set(self.config.get('allowed_languages', [
'en', 'hi', 'bn', 'te', 'ta', 'mr', 'gu', 'kn', 'ml', 'or', 'pa', 'as'
]))
# Geographic relevance
self.require_india_relevance = self.config.get('require_india_relevance', True)
# Spam and quality filters
self.spam_keywords = set(self.config.get('spam_keywords', [
'buy now', 'click here', 'limited offer', 'act now', 'free money',
'earn money', 'work from home', 'get rich quick', 'miracle cure',
'lose weight fast', 'enlargement', 'viagra', 'casino', 'lottery'
]))
# Indian context keywords for relevance checking
self.india_keywords = set([
'india', 'indian', 'bharat', 'bharatiya', 'delhi', 'mumbai', 'bangalore',
'chennai', 'kolkata', 'hyderabad', 'pune', 'ahmedabad', 'surat', 'jaipur',
'lucknow', 'kanpur', 'nagpur', 'indore', 'bhopal', 'visakhapatnam', 'patna',
'vadodara', 'ludhiana', 'agra', 'nashik', 'faridabad', 'meerut', 'rajkot',
'kalyan', 'vasai', 'varanasi', 'srinagar', 'aurangabad', 'dhanbad', 'amritsar',
'navi mumbai', 'allahabad', 'ranchi', 'howrah', 'coimbatore', 'jabalpur',
'gwalior', 'vijayawada', 'jodhpur', 'madurai', 'raipur', 'kota', 'guwahati',
'chandigarh', 'solapur', 'hubli', 'tiruchirappalli', 'bareilly', 'mysore',
'tiruppur', 'gurgaon', 'aligarh', 'jalandhar', 'bhubaneswar', 'salem',
'warangal', 'mira', 'bhiwandi', 'thiruvananthapuram', 'bhavnagar', 'dehradun',
'durgapur', 'asansol', 'nanded', 'kolhapur', 'ajmer', 'gulbarga', 'jamnagar',
'ujjain', 'loni', 'siliguri', 'jhansi', 'ulhasnagar', 'nellore', 'jammu',
'sangli', 'belgaum', 'mangalore', 'ambattur', 'tirunelveli', 'malegaon',
'gaya', 'jalgaon', 'udaipur', 'maheshtala'
])
# Indian states and union territories
self.indian_states = set([
'andhra pradesh', 'arunachal pradesh', 'assam', 'bihar', 'chhattisgarh',
'goa', 'gujarat', 'haryana', 'himachal pradesh', 'jharkhand', 'karnataka',
'kerala', 'madhya pradesh', 'maharashtra', 'manipur', 'meghalaya', 'mizoram',
'nagaland', 'odisha', 'punjab', 'rajasthan', 'sikkim', 'tamil nadu',
'telangana', 'tripura', 'uttar pradesh', 'uttarakhand', 'west bengal',
'andaman and nicobar islands', 'chandigarh', 'dadra and nagar haveli',
'daman and diu', 'delhi', 'lakshadweep', 'puducherry', 'jammu and kashmir',
'ladakh'
])
# Statistics
self.stats = {
'total_validated': 0,
'passed': 0,
'failed': 0,
'failure_reasons': {}
}
def validate_event(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Validate a raw event through multiple layers.
Args:
event: RawEvent to validate
Returns:
Tuple of (is_valid, failure_reason)
"""
self.stats['total_validated'] += 1
try:
# Layer 1: Basic validation
is_valid, reason = self._validate_basic(event)
if not is_valid:
self._record_failure(reason)
return False, reason
# Layer 2: Content quality
is_valid, reason = self._validate_content_quality(event)
if not is_valid:
self._record_failure(reason)
return False, reason
# Layer 3: Language validation
is_valid, reason = self._validate_language(event)
if not is_valid:
self._record_failure(reason)
return False, reason
# Layer 4: Geographic relevance
if self.require_india_relevance:
is_valid, reason = self._validate_india_relevance(event)
if not is_valid:
self._record_failure(reason)
return False, reason
# Layer 5: Spam and quality filtering
is_valid, reason = self._validate_not_spam(event)
if not is_valid:
self._record_failure(reason)
return False, reason
# All validations passed
self.stats['passed'] += 1
return True, None
except Exception as e:
logger.error(f"Validation error for event {event.event_id}: {e}")
self._record_failure(f"validation_error: {str(e)}")
return False, f"validation_error: {str(e)}"
def _validate_basic(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Basic validation checks."""
# Check required fields
if not event.content:
return False, "empty_content"
if not event.source_id:
return False, "missing_source_id"
if not event.timestamp:
return False, "missing_timestamp"
# Check content length
content_length = len(event.content)
if content_length < self.min_content_length:
return False, f"content_too_short: {content_length} < {self.min_content_length}"
if content_length > self.max_content_length:
return False, f"content_too_long: {content_length} > {self.max_content_length}"
# Check word count
word_count = len(event.content.split())
if word_count < self.min_word_count:
return False, f"insufficient_words: {word_count} < {self.min_word_count}"
# Check timestamp is reasonable (not too old or in future)
now = datetime.now(event.timestamp.tzinfo or None)
age = now - event.timestamp
if age.days > 30: # Older than 30 days
return False, f"content_too_old: {age.days} days"
if age.total_seconds() < -3600: # More than 1 hour in future
return False, "content_from_future"
return True, None
def _validate_content_quality(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Validate content quality and structure."""
content = event.content.lower()
# Check for excessive repetition
words = content.split()
if len(words) > 10:
unique_words = set(words)
repetition_ratio = len(unique_words) / len(words)
if repetition_ratio < 0.3: # Less than 30% unique words
return False, f"excessive_repetition: {repetition_ratio:.2f}"
# Check for excessive capitalization
if len(event.content) > 50:
caps_ratio = sum(1 for c in event.content if c.isupper()) / len(event.content)
if caps_ratio > 0.5: # More than 50% uppercase
return False, f"excessive_caps: {caps_ratio:.2f}"
# Check for excessive punctuation
punct_count = sum(1 for c in event.content if c in '!?.,;:')
if len(words) > 0:
punct_ratio = punct_count / len(words)
if punct_ratio > 0.3: # More than 30% punctuation to words ratio
return False, f"excessive_punctuation: {punct_ratio:.2f}"
# Check for minimum sentence structure
sentences = re.split(r'[.!?]+', event.content)
valid_sentences = [s.strip() for s in sentences if len(s.strip()) > 5]
if len(valid_sentences) == 0 and len(words) > 20:
return False, "no_sentence_structure"
return True, None
def _validate_language(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Validate language is in allowed set."""
if not self.allowed_languages:
return True, None # No language restrictions
# Use detected language or try to detect
language = event.language
if not language:
language = self._detect_language_simple(event.content)
if language and language not in self.allowed_languages:
return False, f"unsupported_language: {language}"
return True, None
def _validate_india_relevance(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Validate content is relevant to India."""
content_lower = event.content.lower()
title_lower = (event.title or "").lower()
# Check for India-related keywords
text_to_check = f"{content_lower} {title_lower}"
# Direct keyword matching
for keyword in self.india_keywords:
if keyword in text_to_check:
return True, None
# Check for Indian states
for state in self.indian_states:
if state in text_to_check:
return True, None
# Check location hint
if event.location_hint:
location_lower = event.location_hint.lower()
if any(keyword in location_lower for keyword in self.india_keywords):
return True, None
if any(state in location_lower for state in self.indian_states):
return True, None
# Check metadata for India relevance
if event.metadata:
metadata_str = str(event.metadata).lower()
if any(keyword in metadata_str for keyword in self.india_keywords):
return True, None
return False, "not_india_relevant"
def _validate_not_spam(self, event: RawEvent) -> tuple[bool, Optional[str]]:
"""Validate content is not spam or low quality."""
content_lower = event.content.lower()
# Check for spam keywords
for spam_keyword in self.spam_keywords:
if spam_keyword in content_lower:
return False, f"spam_keyword: {spam_keyword}"
# Check for excessive URLs
url_count = len(re.findall(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', event.content))
word_count = len(event.content.split())
if word_count > 0 and url_count / word_count > 0.2: # More than 20% URLs
return False, f"excessive_urls: {url_count}/{word_count}"
# Check for excessive numbers (might indicate spam/ads)
number_count = len(re.findall(r'\b\d+\b', event.content))
if word_count > 0 and number_count / word_count > 0.3: # More than 30% numbers
return False, f"excessive_numbers: {number_count}/{word_count}"
# Check for promotional language patterns
promo_patterns = [
r'\b(call|contact|visit)\s+(?:us\s+)?(?:at\s+)?\+?\d{10,}', # Phone numbers
r'\b(?:only|just)\s+(?:rs\.?|₹)\s*\d+', # Price mentions
r'\b(?:free|discount|offer|sale)\b.*\b(?:today|now|limited)\b', # Promotional offers
]
for pattern in promo_patterns:
if re.search(pattern, content_lower):
return False, f"promotional_content: {pattern}"
return True, None
def _detect_language_simple(self, content: str) -> Optional[str]:
"""Simple language detection based on script."""
if not content:
return None
# Count characters by script
latin_count = sum(1 for c in content if ord(c) < 256 and c.isalpha())
devanagari_count = sum(1 for c in content if 0x0900 <= ord(c) <= 0x097F)
bengali_count = sum(1 for c in content if 0x0980 <= ord(c) <= 0x09FF)
tamil_count = sum(1 for c in content if 0x0B80 <= ord(c) <= 0x0BFF)
telugu_count = sum(1 for c in content if 0x0C00 <= ord(c) <= 0x0C7F)
gujarati_count = sum(1 for c in content if 0x0A80 <= ord(c) <= 0x0AFF)
total_alpha = sum([latin_count, devanagari_count, bengali_count, tamil_count, telugu_count, gujarati_count])
if total_alpha == 0:
return None
# Determine dominant script
if latin_count / total_alpha > 0.7:
return 'en'
elif devanagari_count / total_alpha > 0.5:
return 'hi' # Could also be Marathi, but Hindi is more common
elif bengali_count / total_alpha > 0.5:
return 'bn'
elif tamil_count / total_alpha > 0.5:
return 'ta'
elif telugu_count / total_alpha > 0.5:
return 'te'
elif gujarati_count / total_alpha > 0.5:
return 'gu'
return 'en' # Default to English
def _record_failure(self, reason: str):
"""Record validation failure statistics."""
self.stats['failed'] += 1
if reason not in self.stats['failure_reasons']:
self.stats['failure_reasons'][reason] = 0
self.stats['failure_reasons'][reason] += 1
def get_stats(self) -> Dict:
"""Get validation statistics."""
stats = self.stats.copy()
if stats['total_validated'] > 0:
stats['pass_rate'] = stats['passed'] / stats['total_validated']
stats['fail_rate'] = stats['failed'] / stats['total_validated']
else:
stats['pass_rate'] = 0.0
stats['fail_rate'] = 0.0
return stats
def reset_stats(self):
"""Reset validation statistics."""
self.stats = {
'total_validated': 0,
'passed': 0,
'failed': 0,
'failure_reasons': {}
}