Samir Boulahtit
6d6eba75bf
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Migrates scanning pipeline from marketing-.lu-domains app into Orion module. Supports digital (domain scan) and offline (manual capture) lead channels with enrichment, scoring, campaign management, and interaction tracking. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
100 lines
3.4 KiB
Python
100 lines
3.4 KiB
Python
# app/modules/prospecting/services/stats_service.py
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"""
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Statistics service for the prospecting dashboard.
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"""
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import logging
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from sqlalchemy import func
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from sqlalchemy.orm import Session
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from app.modules.prospecting.models import (
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Prospect,
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ProspectChannel,
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ProspectScanJob,
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ProspectScore,
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)
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logger = logging.getLogger(__name__)
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class StatsService:
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"""Service for dashboard statistics and reporting."""
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def get_overview(self, db: Session) -> dict:
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"""Get overview statistics for the dashboard."""
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total = db.query(func.count(Prospect.id)).scalar() or 0
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digital = db.query(func.count(Prospect.id)).filter(Prospect.channel == ProspectChannel.DIGITAL).scalar() or 0
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offline = db.query(func.count(Prospect.id)).filter(Prospect.channel == ProspectChannel.OFFLINE).scalar() or 0
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with_website = db.query(func.count(Prospect.id)).filter(Prospect.has_website.is_(True)).scalar() or 0
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with_https = db.query(func.count(Prospect.id)).filter(Prospect.uses_https.is_(True)).scalar() or 0
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scored = db.query(func.count(ProspectScore.id)).scalar() or 0
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avg_score = db.query(func.avg(ProspectScore.score)).scalar()
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# Leads by tier
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tier_results = (
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db.query(ProspectScore.lead_tier, func.count(ProspectScore.id))
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.group_by(ProspectScore.lead_tier)
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.all()
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)
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leads_by_tier = {tier: count for tier, count in tier_results if tier}
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# Common issues (from reason_flags JSON)
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# Simplified: count scored prospects per tier
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top_priority = leads_by_tier.get("top_priority", 0)
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return {
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"total_prospects": total,
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"digital_count": digital,
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"offline_count": offline,
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"with_website": with_website,
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"with_https": with_https,
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"scored": scored,
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"avg_score": round(avg_score, 1) if avg_score else None,
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"top_priority": top_priority,
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"leads_by_tier": leads_by_tier,
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"common_issues": self._get_common_issues(db),
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}
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def get_scan_jobs(
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self,
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db: Session,
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*,
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page: int = 1,
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per_page: int = 20,
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status: str | None = None,
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) -> tuple[list[ProspectScanJob], int]:
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"""Get paginated scan jobs."""
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query = db.query(ProspectScanJob)
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if status:
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query = query.filter(ProspectScanJob.status == status)
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total = query.count()
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jobs = (
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query.order_by(ProspectScanJob.created_at.desc())
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.offset((page - 1) * per_page)
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.limit(per_page)
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.all()
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)
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return jobs, total
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def _get_common_issues(self, db: Session) -> list[dict]:
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"""Extract common issue flags from scored prospects."""
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scores = db.query(ProspectScore.reason_flags).filter(ProspectScore.reason_flags.isnot(None)).all()
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import json
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flag_counts: dict[str, int] = {}
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for (flags_json,) in scores:
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try:
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flags = json.loads(flags_json)
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for flag in flags:
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flag_counts[flag] = flag_counts.get(flag, 0) + 1
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except (json.JSONDecodeError, TypeError):
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continue
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sorted_flags = sorted(flag_counts.items(), key=lambda x: x[1], reverse=True)
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return [{"flag": flag, "count": count} for flag, count in sorted_flags[:10]]
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stats_service = StatsService()
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