f65b35f881
- Job history tracking with SQLite table - Dry-run mode (--dry-run) to test scrape rules - Plugin system with 3 built-in plugins (sentiment, dedupe, keywords) - REST API server (--api) for Metabase/Grafana integration - Parquet export (--export-parquet) for DuckDB/warehouses - SQLite maintenance (--backup, --vacuum) - Dashboard Integrations tab with external tools guides - Updated Dockerfile and docker-compose.yml for cloud deployment - Comprehensive README documentation
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
"""
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Sentiment Tagger Plugin
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Adds sentiment scores and labels to posts and comments.
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"""
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import sys
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from pathlib import Path
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# Add parent to path for imports
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from plugins import Plugin
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from analytics.sentiment import analyze_sentiment
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class SentimentTagger(Plugin):
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"""Add sentiment analysis to scraped content."""
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name = "sentiment_tagger"
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description = "Adds sentiment scores and labels to posts"
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enabled = True
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def process_posts(self, posts):
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"""Add sentiment to posts."""
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for post in posts:
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text = f"{post.get('title', '')} {post.get('selftext', '')}"
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score, label = analyze_sentiment(text)
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post['sentiment_score'] = score
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post['sentiment_label'] = label
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# Count sentiments
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pos = sum(1 for p in posts if p.get('sentiment_label') == 'positive')
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neg = sum(1 for p in posts if p.get('sentiment_label') == 'negative')
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neu = len(posts) - pos - neg
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print(f" 📊 Sentiment: {pos} positive, {neu} neutral, {neg} negative")
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return posts
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def process_comments(self, comments):
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"""Add sentiment to comments."""
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for comment in comments:
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score, label = analyze_sentiment(comment.get('body', ''))
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comment['sentiment_score'] = score
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comment['sentiment_label'] = label
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return comments
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