Consultoría AS
ecc2ca73ea
Phase 1 - Analytics y Reportes: - PostMetrics and AnalyticsReport models for tracking engagement - Analytics service with dashboard stats, top posts, optimal times - 8 API endpoints at /api/analytics/* - Interactive dashboard with Chart.js charts - Celery tasks for metrics fetch (15min) and weekly reports Phase 2 - Integración Odoo: - Lead and OdooSyncLog models for CRM integration - Odoo fields added to Product and Service models - XML-RPC service for bidirectional sync - Lead management API at /api/leads/* - Leads dashboard template - Celery tasks for product/service sync and lead export Phase 3 - A/B Testing y Recycling: - ABTest, ABTestVariant, RecycledPost models - Statistical winner analysis using chi-square test - Content recycling with engagement-based scoring - APIs at /api/ab-tests/* and /api/recycling/* - Automated test evaluation and content recycling tasks Phase 4 - Thread Series y Templates: - ThreadSeries and ThreadPost models for multi-post threads - AI-powered thread generation - Enhanced ImageTemplate with HTML template support - APIs at /api/threads/* and /api/templates/* - Thread scheduling with reply chain support Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
"""
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Post Metrics Model - Tracking engagement metrics per post.
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"""
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from datetime import datetime
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from sqlalchemy import Column, Integer, Float, String, DateTime, ForeignKey, Index
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from sqlalchemy.orm import relationship
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from app.core.database import Base
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class PostMetrics(Base):
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"""
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Stores engagement metrics for posts.
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Multiple records per post to track metrics over time.
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"""
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__tablename__ = "post_metrics"
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id = Column(Integer, primary_key=True, index=True)
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post_id = Column(Integer, ForeignKey("posts.id", ondelete="CASCADE"), nullable=False)
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platform = Column(String(50), nullable=False)
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# Core engagement metrics
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likes = Column(Integer, default=0)
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comments = Column(Integer, default=0)
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shares = Column(Integer, default=0) # retweets, reposts
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impressions = Column(Integer, default=0)
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reach = Column(Integer, default=0)
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saves = Column(Integer, default=0) # bookmarks
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clicks = Column(Integer, default=0) # link clicks
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replies = Column(Integer, default=0)
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quotes = Column(Integer, default=0) # quote tweets
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# Calculated metrics
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engagement_rate = Column(Float, default=0.0)
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engagement_total = Column(Integer, default=0)
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# Timestamps
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recorded_at = Column(DateTime, default=datetime.utcnow, index=True)
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created_at = Column(DateTime, default=datetime.utcnow)
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# Relationships
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post = relationship("Post", back_populates="metrics_history")
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# Indexes for efficient queries
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__table_args__ = (
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Index("ix_post_metrics_post_platform", "post_id", "platform"),
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Index("ix_post_metrics_recorded", "recorded_at"),
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)
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def calculate_engagement_rate(self):
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"""Calculate engagement rate based on impressions."""
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self.engagement_total = (
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self.likes + self.comments + self.shares +
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self.saves + self.replies + self.quotes
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)
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if self.impressions > 0:
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self.engagement_rate = (self.engagement_total / self.impressions) * 100
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else:
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self.engagement_rate = 0.0
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def to_dict(self):
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return {
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"id": self.id,
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"post_id": self.post_id,
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"platform": self.platform,
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"likes": self.likes,
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"comments": self.comments,
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"shares": self.shares,
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"impressions": self.impressions,
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"reach": self.reach,
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"saves": self.saves,
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"clicks": self.clicks,
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"replies": self.replies,
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"quotes": self.quotes,
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"engagement_rate": round(self.engagement_rate, 2),
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"engagement_total": self.engagement_total,
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"recorded_at": self.recorded_at.isoformat() if self.recorded_at else None
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}
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