Add complete automation, reporting, and CI/CD system
Features Added: ============== 📧 EMAIL REPORTING SYSTEM: - EmailReporter: Send reports via SMTP (Gmail, SendGrid, custom) - ReportGenerator: Generate daily/weekly summaries with HTML/text formatting - Configurable via .env (SMTP_HOST, SMTP_PORT, etc.) - Scripts: send_daily_report.py, send_weekly_report.py 🤖 AUTOMATED RUNS: - automated_daily_run.sh: Full daily ETL pipeline + reporting - automated_weekly_run.sh: Weekly pattern analysis + reports - setup_cron.sh: Interactive cron job setup (5-minute setup) - Logs saved to ~/logs/ with automatic cleanup 🔍 HEALTH CHECKS: - health_check.py: System health monitoring - Checks: DB connection, data freshness, counts, recent alerts - JSON output for programmatic use - Exit codes for monitoring integration 🚀 CI/CD PIPELINE: - .github/workflows/ci.yml: Full CI/CD pipeline - GitHub Actions / Gitea Actions compatible - Jobs: lint & test, security scan, dependency scan, Docker build - PostgreSQL service for integration tests - 93 tests passing in CI 📚 COMPREHENSIVE DOCUMENTATION: - AUTOMATION_QUICKSTART.md: 5-minute email setup guide - docs/12_automation_and_reporting.md: Full automation guide - Updated README.md with automation links - Deployment → Production workflow guide 🛠️ IMPROVEMENTS: - All shell scripts made executable - Environment variable examples in .env.example - Report logs saved with timestamps - 30-day log retention with auto-cleanup - Health checks can be scheduled via cron WHAT THIS ENABLES: ================== After deployment, users can: 1. Set up automated daily/weekly email reports (5 min) 2. Receive HTML+text emails with: - New trades, market alerts, suspicious timing - Weekly patterns, rankings, repeat offenders 3. Monitor system health automatically 4. Run full CI/CD pipeline on every commit 5. Deploy with confidence (tests + security scans) USAGE: ====== # One-time setup (on deployed server) ./scripts/setup_cron.sh # Or manually send reports python scripts/send_daily_report.py --to user@example.com python scripts/send_weekly_report.py --to user@example.com # Check system health python scripts/health_check.py See AUTOMATION_QUICKSTART.md for full instructions. 93 tests passing | Full CI/CD | Email reports ready
This commit is contained in:
ilia
@@ -12,3 +12,4 @@ __all__ = [
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"PerformanceMetrics",
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]
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@@ -220,3 +220,4 @@ class BenchmarkComparison:
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"window_days": window_days,
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}
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@@ -289,3 +289,4 @@ class PerformanceMetrics:
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**aggregate,
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}
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@@ -242,3 +242,4 @@ class AlertManager:
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html_parts.append("</body></html>")
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return "\n".join(html_parts)
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@@ -356,3 +356,4 @@ class DisclosureCorrelator:
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"analyses": sorted(analyses, key=lambda x: x["timing_score"], reverse=True),
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}
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@@ -279,3 +279,4 @@ class MarketMonitor:
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return summary
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@@ -357,3 +357,4 @@ class PatternDetector:
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"party_comparison": party_comparison,
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}
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@@ -0,0 +1,12 @@
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"""
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POTE Reporting Module
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Generates and sends formatted reports via email, files, or other channels.
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"""
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from .email_reporter import EmailReporter
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from .report_generator import ReportGenerator
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__all__ = ["EmailReporter", "ReportGenerator"]
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@@ -0,0 +1,116 @@
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"""
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Email Reporter for POTE
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Sends formatted reports via SMTP email.
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"""
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import logging
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import smtplib
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from email.mime.multipart import MIMEMultipart
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from email.mime.text import MIMEText
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from typing import List, Optional
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from pote.config import settings
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logger = logging.getLogger(__name__)
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class EmailReporter:
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"""Sends email reports via SMTP."""
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def __init__(
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self,
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smtp_host: Optional[str] = None,
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smtp_port: Optional[int] = None,
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smtp_user: Optional[str] = None,
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smtp_password: Optional[str] = None,
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from_email: Optional[str] = None,
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):
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"""
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Initialize email reporter.
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If parameters are not provided, will attempt to use settings from config.
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"""
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self.smtp_host = smtp_host or getattr(settings, "smtp_host", "localhost")
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self.smtp_port = smtp_port or getattr(settings, "smtp_port", 587)
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self.smtp_user = smtp_user or getattr(settings, "smtp_user", None)
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self.smtp_password = smtp_password or getattr(settings, "smtp_password", None)
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self.from_email = from_email or getattr(
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settings, "from_email", "pote@localhost"
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)
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def send_report(
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self,
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to_emails: List[str],
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subject: str,
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body_text: str,
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body_html: Optional[str] = None,
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) -> bool:
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"""
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Send an email report.
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Args:
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to_emails: List of recipient email addresses
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subject: Email subject line
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body_text: Plain text email body
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body_html: Optional HTML email body
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Returns:
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True if email sent successfully, False otherwise
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"""
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try:
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msg = MIMEMultipart("alternative")
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msg["Subject"] = subject
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msg["From"] = self.from_email
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msg["To"] = ", ".join(to_emails)
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# Attach plain text part
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msg.attach(MIMEText(body_text, "plain"))
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# Attach HTML part if provided
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if body_html:
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msg.attach(MIMEText(body_html, "html"))
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# Connect to SMTP server and send
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with smtplib.SMTP(self.smtp_host, self.smtp_port) as server:
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server.ehlo()
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if self.smtp_port == 587: # TLS
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server.starttls()
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server.ehlo()
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if self.smtp_user and self.smtp_password:
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server.login(self.smtp_user, self.smtp_password)
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server.send_message(msg)
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logger.info(f"Email sent successfully to {', '.join(to_emails)}")
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return True
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except Exception as e:
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logger.error(f"Failed to send email: {e}")
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return False
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def test_connection(self) -> bool:
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"""
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Test SMTP connection.
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Returns:
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True if connection successful, False otherwise
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"""
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try:
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with smtplib.SMTP(self.smtp_host, self.smtp_port, timeout=10) as server:
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server.ehlo()
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if self.smtp_port == 587:
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server.starttls()
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server.ehlo()
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if self.smtp_user and self.smtp_password:
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server.login(self.smtp_user, self.smtp_password)
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logger.info("SMTP connection test successful")
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return True
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except Exception as e:
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logger.error(f"SMTP connection test failed: {e}")
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return False
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@@ -0,0 +1,423 @@
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"""
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Report Generator for POTE
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Generates formatted reports from database data.
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"""
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import logging
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from datetime import date, datetime, timedelta
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from typing import Any, Dict, List, Optional
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from sqlalchemy import func
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from sqlalchemy.orm import Session
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from pote.db.models import MarketAlert, Official, Security, Trade
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from pote.monitoring.disclosure_correlator import DisclosureCorrelator
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from pote.monitoring.pattern_detector import PatternDetector
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logger = logging.getLogger(__name__)
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class ReportGenerator:
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"""Generates various types of reports from database data."""
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def __init__(self, session: Session):
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self.session = session
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self.correlator = DisclosureCorrelator(session)
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self.detector = PatternDetector(session)
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def generate_daily_summary(
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self, report_date: Optional[date] = None
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) -> Dict[str, Any]:
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"""
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Generate a daily summary report.
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Args:
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report_date: Date to generate report for (defaults to today)
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Returns:
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Dictionary containing report data
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"""
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if report_date is None:
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report_date = date.today()
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start_of_day = datetime.combine(report_date, datetime.min.time())
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end_of_day = datetime.combine(report_date, datetime.max.time())
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# Count new trades filed today
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new_trades = (
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self.session.query(Trade).filter(Trade.filing_date == report_date).all()
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)
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# Count market alerts today
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new_alerts = (
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self.session.query(MarketAlert)
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.filter(
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MarketAlert.timestamp >= start_of_day,
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MarketAlert.timestamp <= end_of_day,
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)
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.all()
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)
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# Get high-severity alerts
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critical_alerts = [a for a in new_alerts if a.severity >= 7]
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# Get suspicious timing matches
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suspicious_trades = []
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for trade in new_trades:
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analysis = self.correlator.analyze_trade(trade)
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if analysis["timing_score"] >= 50:
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suspicious_trades.append(analysis)
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return {
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"date": report_date,
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"new_trades_count": len(new_trades),
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"new_trades": [
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{
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"official": t.official.name if t.official else "Unknown",
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"ticker": t.security.ticker if t.security else "Unknown",
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"side": t.side,
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"transaction_date": t.transaction_date,
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"value_min": t.value_min,
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"value_max": t.value_max,
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}
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for t in new_trades
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],
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"market_alerts_count": len(new_alerts),
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"critical_alerts_count": len(critical_alerts),
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"critical_alerts": [
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{
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"ticker": a.ticker,
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"type": a.alert_type,
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"severity": a.severity,
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"timestamp": a.timestamp,
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"details": a.details,
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}
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for a in critical_alerts
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],
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"suspicious_trades_count": len(suspicious_trades),
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"suspicious_trades": suspicious_trades,
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}
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def generate_weekly_summary(self) -> Dict[str, Any]:
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"""
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Generate a weekly summary report.
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Returns:
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Dictionary containing report data
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"""
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week_ago = date.today() - timedelta(days=7)
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# Most active officials
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active_officials = (
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self.session.query(
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Official.name, func.count(Trade.id).label("trade_count")
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)
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.join(Trade)
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.filter(Trade.filing_date >= week_ago)
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.group_by(Official.id, Official.name)
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.order_by(func.count(Trade.id).desc())
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.limit(10)
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.all()
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)
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# Most traded securities
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active_securities = (
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self.session.query(
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Security.ticker, func.count(Trade.id).label("trade_count")
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)
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.join(Trade)
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.filter(Trade.filing_date >= week_ago)
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.group_by(Security.id, Security.ticker)
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.order_by(func.count(Trade.id).desc())
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.limit(10)
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.all()
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)
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# Get top suspicious patterns
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repeat_offenders = self.detector.identify_repeat_offenders(
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days_lookback=7, min_suspicious_trades=2, min_timing_score=40
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)
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return {
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"period_start": week_ago,
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"period_end": date.today(),
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"most_active_officials": [
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{"name": name, "trade_count": count} for name, count in active_officials
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],
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"most_traded_securities": [
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{"ticker": ticker, "trade_count": count}
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for ticker, count in active_securities
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],
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"repeat_offenders_count": len(repeat_offenders),
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"repeat_offenders": repeat_offenders[:5], # Top 5
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}
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def format_as_text(self, report_data: Dict[str, Any], report_type: str) -> str:
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"""
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Format report data as plain text.
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Args:
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report_data: Report data dictionary
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report_type: Type of report ('daily' or 'weekly')
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Returns:
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Formatted plain text report
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"""
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if report_type == "daily":
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return self._format_daily_text(report_data)
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elif report_type == "weekly":
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return self._format_weekly_text(report_data)
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else:
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return str(report_data)
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def _format_daily_text(self, data: Dict[str, Any]) -> str:
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"""Format daily report as plain text."""
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lines = [
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"=" * 70,
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f"POTE DAILY REPORT - {data['date']}",
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"=" * 70,
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"",
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"📊 SUMMARY",
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f" • New Trades Filed: {data['new_trades_count']}",
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f" • Market Alerts: {data['market_alerts_count']}",
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f" • Critical Alerts (≥7 severity): {data['critical_alerts_count']}",
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f" • Suspicious Timing Trades: {data['suspicious_trades_count']}",
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"",
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]
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if data["new_trades"]:
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lines.append("📝 NEW TRADES")
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for t in data["new_trades"][:10]: # Limit to 10
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lines.append(
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f" • {t['official']}: {t['side']} {t['ticker']} "
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f"(${t['value_min']:,.0f} - ${t['value_max']:,.0f}) "
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f"on {t['transaction_date']}"
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)
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if len(data["new_trades"]) > 10:
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lines.append(f" ... and {len(data['new_trades']) - 10} more")
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lines.append("")
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if data["critical_alerts"]:
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lines.append("🚨 CRITICAL MARKET ALERTS")
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for a in data["critical_alerts"][:5]:
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lines.append(
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f" • {a['ticker']}: {a['type']} (severity {a['severity']}) "
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f"at {a['timestamp'].strftime('%H:%M:%S')}"
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)
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lines.append("")
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if data["suspicious_trades"]:
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lines.append("⚠️ SUSPICIOUS TIMING DETECTED")
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for st in data["suspicious_trades"][:5]:
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lines.append(
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f" • {st['official_name']}: {st['side']} {st['ticker']} "
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f"(Timing Score: {st['timing_score']}/100, "
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f"{st['prior_alerts_count']} prior alerts)"
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)
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lines.append("")
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lines.extend(
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[
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"=" * 70,
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"DISCLAIMER: This is for research purposes only. Not investment advice.",
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"=" * 70,
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]
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)
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return "\n".join(lines)
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def _format_weekly_text(self, data: Dict[str, Any]) -> str:
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"""Format weekly report as plain text."""
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lines = [
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"=" * 70,
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f"POTE WEEKLY REPORT - {data['period_start']} to {data['period_end']}",
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"=" * 70,
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"",
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"👥 MOST ACTIVE OFFICIALS",
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]
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for official in data["most_active_officials"]:
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lines.append(f" • {official['name']}: {official['trade_count']} trades")
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lines.extend(["", "📈 MOST TRADED SECURITIES"])
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for security in data["most_traded_securities"]:
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lines.append(f" • {security['ticker']}: {security['trade_count']} trades")
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if data["repeat_offenders"]:
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lines.extend(
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["", f"⚠️ REPEAT OFFENDERS ({data['repeat_offenders_count']} total)"]
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)
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for offender in data["repeat_offenders"]:
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lines.append(
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f" • {offender['official_name']}: "
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f"{offender['trades_with_timing_advantage']}/{offender['total_trades']} "
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f"suspicious trades (avg score: {offender['average_timing_score']:.1f})"
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)
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lines.extend(
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[
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"",
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"=" * 70,
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"DISCLAIMER: This is for research purposes only. Not investment advice.",
|
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"=" * 70,
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||||
]
|
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)
|
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return "\n".join(lines)
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|
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def format_as_html(self, report_data: Dict[str, Any], report_type: str) -> str:
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"""
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Format report data as HTML.
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Args:
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report_data: Report data dictionary
|
||||
report_type: Type of report ('daily' or 'weekly')
|
||||
|
||||
Returns:
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Formatted HTML report
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||||
"""
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if report_type == "daily":
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return self._format_daily_html(report_data)
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elif report_type == "weekly":
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return self._format_weekly_html(report_data)
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else:
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return f"<pre>{report_data}</pre>"
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def _format_daily_html(self, data: Dict[str, Any]) -> str:
|
||||
"""Format daily report as HTML."""
|
||||
html = f"""
|
||||
<html>
|
||||
<head>
|
||||
<style>
|
||||
body {{ font-family: Arial, sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; }}
|
||||
h1 {{ color: #2c3e50; border-bottom: 3px solid #3498db; padding-bottom: 10px; }}
|
||||
h2 {{ color: #34495e; margin-top: 30px; }}
|
||||
.summary {{ background: #ecf0f1; padding: 15px; border-radius: 5px; margin: 20px 0; }}
|
||||
.stat {{ display: inline-block; margin-right: 20px; }}
|
||||
.alert {{ background: #fff3cd; padding: 10px; margin: 5px 0; border-left: 4px solid #ffc107; }}
|
||||
.critical {{ background: #f8d7da; border-left: 4px solid #dc3545; }}
|
||||
.trade {{ background: #d1ecf1; padding: 10px; margin: 5px 0; border-left: 4px solid #17a2b8; }}
|
||||
.disclaimer {{ background: #e9ecef; padding: 10px; margin-top: 30px; font-size: 0.9em; border-left: 4px solid #6c757d; }}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>POTE Daily Report - {data['date']}</h1>
|
||||
|
||||
<div class="summary">
|
||||
<h2>📊 Summary</h2>
|
||||
<div class="stat"><strong>New Trades:</strong> {data['new_trades_count']}</div>
|
||||
<div class="stat"><strong>Market Alerts:</strong> {data['market_alerts_count']}</div>
|
||||
<div class="stat"><strong>Critical Alerts:</strong> {data['critical_alerts_count']}</div>
|
||||
<div class="stat"><strong>Suspicious Trades:</strong> {data['suspicious_trades_count']}</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
if data["new_trades"]:
|
||||
html += "<h2>📝 New Trades</h2>"
|
||||
for t in data["new_trades"][:10]:
|
||||
html += f"""
|
||||
<div class="trade">
|
||||
<strong>{t['official']}</strong>: {t['side']} {t['ticker']}
|
||||
(${t['value_min']:,.0f} - ${t['value_max']:,.0f}) on {t['transaction_date']}
|
||||
</div>
|
||||
"""
|
||||
|
||||
if data["critical_alerts"]:
|
||||
html += "<h2>🚨 Critical Market Alerts</h2>"
|
||||
for a in data["critical_alerts"][:5]:
|
||||
html += f"""
|
||||
<div class="alert critical">
|
||||
<strong>{a['ticker']}</strong>: {a['type']} (severity {a['severity']})
|
||||
at {a['timestamp'].strftime('%H:%M:%S')}
|
||||
</div>
|
||||
"""
|
||||
|
||||
if data["suspicious_trades"]:
|
||||
html += "<h2>⚠️ Suspicious Timing Detected</h2>"
|
||||
for st in data["suspicious_trades"][:5]:
|
||||
html += f"""
|
||||
<div class="alert">
|
||||
<strong>{st['official_name']}</strong>: {st['side']} {st['ticker']}<br>
|
||||
Timing Score: {st['timing_score']}/100 ({st['prior_alerts_count']} prior alerts)
|
||||
</div>
|
||||
"""
|
||||
|
||||
html += """
|
||||
<div class="disclaimer">
|
||||
<strong>DISCLAIMER:</strong> This is for research purposes only. Not investment advice.
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
return html
|
||||
|
||||
def _format_weekly_html(self, data: Dict[str, Any]) -> str:
|
||||
"""Format weekly report as HTML."""
|
||||
html = f"""
|
||||
<html>
|
||||
<head>
|
||||
<style>
|
||||
body {{ font-family: Arial, sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; }}
|
||||
h1 {{ color: #2c3e50; border-bottom: 3px solid #3498db; padding-bottom: 10px; }}
|
||||
h2 {{ color: #34495e; margin-top: 30px; }}
|
||||
table {{ width: 100%; border-collapse: collapse; margin: 20px 0; }}
|
||||
th, td {{ padding: 10px; text-align: left; border-bottom: 1px solid #ddd; }}
|
||||
th {{ background: #3498db; color: white; }}
|
||||
.disclaimer {{ background: #e9ecef; padding: 10px; margin-top: 30px; font-size: 0.9em; border-left: 4px solid #6c757d; }}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>POTE Weekly Report</h1>
|
||||
<p><strong>Period:</strong> {data['period_start']} to {data['period_end']}</p>
|
||||
|
||||
<h2>👥 Most Active Officials</h2>
|
||||
<table>
|
||||
<tr><th>Official</th><th>Trade Count</th></tr>
|
||||
"""
|
||||
|
||||
for official in data["most_active_officials"]:
|
||||
html += f"<tr><td>{official['name']}</td><td>{official['trade_count']}</td></tr>"
|
||||
|
||||
html += """
|
||||
</table>
|
||||
|
||||
<h2>📈 Most Traded Securities</h2>
|
||||
<table>
|
||||
<tr><th>Ticker</th><th>Trade Count</th></tr>
|
||||
"""
|
||||
|
||||
for security in data["most_traded_securities"]:
|
||||
html += f"<tr><td>{security['ticker']}</td><td>{security['trade_count']}</td></tr>"
|
||||
|
||||
html += "</table>"
|
||||
|
||||
if data["repeat_offenders"]:
|
||||
html += f"""
|
||||
<h2>⚠️ Repeat Offenders ({data['repeat_offenders_count']} total)</h2>
|
||||
<table>
|
||||
<tr><th>Official</th><th>Suspicious Trades</th><th>Total Trades</th><th>Avg Score</th></tr>
|
||||
"""
|
||||
for offender in data["repeat_offenders"]:
|
||||
html += f"""
|
||||
<tr>
|
||||
<td>{offender['official_name']}</td>
|
||||
<td>{offender['trades_with_timing_advantage']}</td>
|
||||
<td>{offender['total_trades']}</td>
|
||||
<td>{offender['average_timing_score']:.1f}</td>
|
||||
</tr>
|
||||
"""
|
||||
html += "</table>"
|
||||
|
||||
html += """
|
||||
<div class="disclaimer">
|
||||
<strong>DISCLAIMER:</strong> This is for research purposes only. Not investment advice.
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
return html
|
||||
|
||||
Reference in New Issue
Block a user