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
301 lines
6.4 KiB
Markdown
301 lines
6.4 KiB
Markdown
# Local Testing Guide for POTE
|
|
|
|
## ✅ Testing Locally Before Deployment
|
|
|
|
### Quick Test - Run Full Suite
|
|
|
|
```bash
|
|
cd /home/user/Documents/code/pote
|
|
source venv/bin/activate
|
|
pytest -v
|
|
```
|
|
|
|
**Expected Result:** All 55 tests should pass ✅
|
|
|
|
---
|
|
|
|
## 📊 Current Data Status
|
|
|
|
### Live Data Status: ❌ **NOT LIVE YET**
|
|
|
|
**Why?**
|
|
- 🔴 **House Stock Watcher API is DOWN** (domain issues, unreachable)
|
|
- 🟢 **yfinance works** (for price data)
|
|
- 🟡 **Sample data available** (5 trades from fixtures)
|
|
|
|
### What Data Do You Have?
|
|
|
|
**On Your Deployed System (Proxmox):**
|
|
```bash
|
|
ssh poteapp@10.0.10.95
|
|
cd ~/pote
|
|
source venv/bin/activate
|
|
python ~/status.sh
|
|
```
|
|
|
|
This will show:
|
|
- 5 sample trades (from fixtures)
|
|
- 5 securities (NVDA, MSFT, AAPL, TSLA, GOOGL)
|
|
- 0 price data (needs manual fetch)
|
|
|
|
---
|
|
|
|
## 🧪 Testing Analytics Locally
|
|
|
|
### 1. Unit Tests (Fast, No External Dependencies)
|
|
|
|
```bash
|
|
# Test analytics calculations with mock data
|
|
pytest tests/test_analytics.py -v
|
|
|
|
# Test integration with realistic data
|
|
pytest tests/test_analytics_integration.py -v
|
|
```
|
|
|
|
These tests:
|
|
- ✅ Create synthetic price data
|
|
- ✅ Simulate trades with known returns
|
|
- ✅ Verify calculations are correct
|
|
- ✅ Test edge cases (missing data, sell trades, etc.)
|
|
|
|
### 2. Manual Test with Local Database
|
|
|
|
```bash
|
|
# Create a fresh local database
|
|
export DATABASE_URL="sqlite:///./test_pote.db"
|
|
|
|
# Run migrations
|
|
alembic upgrade head
|
|
|
|
# Ingest sample data
|
|
python scripts/ingest_from_fixtures.py
|
|
|
|
# Fetch some real price data (requires internet)
|
|
python scripts/fetch_sample_prices.py
|
|
|
|
# Now test analytics
|
|
python scripts/analyze_official.py "Nancy Pelosi"
|
|
```
|
|
|
|
### 3. Test Individual Components
|
|
|
|
```python
|
|
# Test return calculator
|
|
from pote.analytics.returns import ReturnCalculator
|
|
from pote.db import get_session
|
|
|
|
session = next(get_session())
|
|
calc = ReturnCalculator(session)
|
|
|
|
# Test with your data...
|
|
```
|
|
|
|
---
|
|
|
|
## 📦 What Gets Tested?
|
|
|
|
### Core Functionality (All Working ✅)
|
|
1. **Database Models** - Officials, Securities, Trades, Prices
|
|
2. **Data Ingestion** - Trade loading, security enrichment
|
|
3. **Analytics Engine** - Returns, benchmarks, metrics
|
|
4. **Edge Cases** - Missing data, sell trades, disclosure lags
|
|
|
|
### Integration Tests Cover:
|
|
- ✅ Return calculations over multiple time windows (30/60/90/180 days)
|
|
- ✅ Benchmark comparisons (stock vs SPY/QQQ)
|
|
- ✅ Abnormal return (alpha) calculations
|
|
- ✅ Official performance summaries
|
|
- ✅ Sector analysis
|
|
- ✅ Disclosure timing analysis
|
|
- ✅ Top performer rankings
|
|
- ✅ System-wide statistics
|
|
|
|
---
|
|
|
|
## 🔄 Getting Live Data
|
|
|
|
### Option 1: Wait for House Stock Watcher API
|
|
The API is currently down. Once it's back up:
|
|
|
|
```bash
|
|
python scripts/fetch_congressional_trades.py --days 30
|
|
```
|
|
|
|
### Option 2: Use Manual CSV Import (NOW)
|
|
|
|
**Step 1: Find a source**
|
|
- Go to https://housestockwatcher.com/ (manual download)
|
|
- Or use https://www.capitoltrades.com/ (has CSV export)
|
|
- Or https://senatestockwatcher.com/
|
|
|
|
**Step 2: Format as CSV**
|
|
```bash
|
|
python scripts/scrape_alternative_sources.py template
|
|
# Edit trades_template.csv with real data
|
|
|
|
python scripts/scrape_alternative_sources.py import-csv trades_template.csv
|
|
```
|
|
|
|
### Option 3: Add Individual Trades Manually
|
|
|
|
```bash
|
|
python scripts/add_custom_trades.py \
|
|
--official-name "Nancy Pelosi" \
|
|
--party "Democrat" \
|
|
--chamber "House" \
|
|
--state "CA" \
|
|
--ticker "NVDA" \
|
|
--company-name "NVIDIA Corporation" \
|
|
--side "buy" \
|
|
--value-min 15001 \
|
|
--value-max 50000 \
|
|
--transaction-date "2024-01-15" \
|
|
--disclosure-date "2024-02-01"
|
|
```
|
|
|
|
### Option 4: Use the Free Alternative API (QuiverQuant - Requires API Key)
|
|
|
|
Sign up at https://www.quiverquant.com/ (free tier available)
|
|
|
|
```bash
|
|
export QUIVER_API_KEY="your_key_here"
|
|
# Then implement client (we can add this)
|
|
```
|
|
|
|
---
|
|
|
|
## 📈 After Adding Data, Fetch Prices
|
|
|
|
```bash
|
|
# This will fetch prices for all securities in your database
|
|
python scripts/fetch_sample_prices.py
|
|
|
|
# Then enrich security info (name, sector, industry)
|
|
python scripts/enrich_securities.py
|
|
```
|
|
|
|
---
|
|
|
|
## 🎯 Complete Local Test Workflow
|
|
|
|
```bash
|
|
# 1. Run all tests
|
|
pytest -v
|
|
# ✅ All 55 tests should pass
|
|
|
|
# 2. Check local database
|
|
python -c "
|
|
from pote.db import get_session
|
|
from pote.db.models import Official, Trade, Security, Price
|
|
|
|
with next(get_session()) as session:
|
|
print(f'Officials: {session.query(Official).count()}')
|
|
print(f'Trades: {session.query(Trade).count()}')
|
|
print(f'Securities: {session.query(Security).count()}')
|
|
print(f'Prices: {session.query(Price).count()}')
|
|
"
|
|
|
|
# 3. Add some test data
|
|
python scripts/ingest_from_fixtures.py
|
|
|
|
# 4. Fetch price data
|
|
python scripts/fetch_sample_prices.py
|
|
|
|
# 5. Run analytics
|
|
python scripts/analyze_official.py "Nancy Pelosi"
|
|
|
|
# 6. Calculate all returns
|
|
python scripts/calculate_all_returns.py --window 90
|
|
```
|
|
|
|
---
|
|
|
|
## 🚀 Deploy to Proxmox
|
|
|
|
Once local tests pass:
|
|
|
|
```bash
|
|
# Push code
|
|
git add -A
|
|
git commit -m "Your changes"
|
|
git push
|
|
|
|
# SSH to Proxmox container
|
|
ssh root@10.0.10.95
|
|
|
|
# Pull updates
|
|
su - poteapp
|
|
cd ~/pote
|
|
git pull
|
|
source venv/bin/activate
|
|
|
|
# Run tests on server
|
|
pytest -v
|
|
|
|
# Update database
|
|
alembic upgrade head
|
|
|
|
# Restart services if using systemd
|
|
```
|
|
|
|
---
|
|
|
|
## 🐛 Common Issues
|
|
|
|
### "No price data found"
|
|
**Fix:** Run `python scripts/fetch_sample_prices.py`
|
|
|
|
### "No trades in database"
|
|
**Fix:**
|
|
- Option 1: `python scripts/ingest_from_fixtures.py` (sample data)
|
|
- Option 2: Manually add trades (see Option 3 above)
|
|
- Option 3: Wait for House Stock Watcher API to come back online
|
|
|
|
### "Connection refused" (on Proxmox)
|
|
**Fix:** Check PostgreSQL is running and configured correctly
|
|
```bash
|
|
sudo systemctl status postgresql
|
|
sudo -u postgres psql -c "\l"
|
|
```
|
|
|
|
---
|
|
|
|
## 📊 Test Coverage
|
|
|
|
Run tests with coverage report:
|
|
|
|
```bash
|
|
pytest --cov=src/pote --cov-report=html
|
|
firefox htmlcov/index.html # View coverage report
|
|
```
|
|
|
|
**Current Coverage:**
|
|
- Models: ~90%
|
|
- Ingestion: ~85%
|
|
- Analytics: ~80%
|
|
- Overall: ~85%
|
|
|
|
---
|
|
|
|
## ✨ Summary
|
|
|
|
**Before Deploying:**
|
|
1. ✅ Run `pytest -v` - all tests pass
|
|
2. ✅ Run `make lint` - no errors
|
|
3. ✅ Test locally with sample data
|
|
4. ✅ Verify analytics work with synthetic prices
|
|
|
|
**Getting Live Data:**
|
|
- 🔴 House Stock Watcher API is down (external issue)
|
|
- 🟢 Manual CSV import works NOW
|
|
- 🟢 yfinance for prices works NOW
|
|
- 🟡 QuiverQuant available (requires free API key)
|
|
|
|
**You can deploy and use the system NOW with:**
|
|
- Manual data entry
|
|
- CSV imports
|
|
- Fixture data for testing
|
|
- Full analytics on whatever data you add
|
|
|
|
|