Files
myTradeTracker/PROJECT_SUMMARY.md
Chris eea4469095 Initial release v1.1.0
- Complete MVP for tracking Fidelity brokerage account performance
- Transaction import from CSV with deduplication
- Automatic FIFO position tracking with options support
- Real-time P&L calculations with market data caching
- Dashboard with timeframe filtering (30/90/180 days, 1 year, YTD, all time)
- Docker-based deployment with PostgreSQL backend
- React/TypeScript frontend with TailwindCSS
- FastAPI backend with SQLAlchemy ORM

Features:
- Multi-account support
- Import via CSV upload or filesystem
- Open and closed position tracking
- Balance history charting
- Performance analytics and metrics
- Top trades analysis
- Responsive UI design

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-22 14:27:43 -05:00

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# myFidelityTracker - Project Summary
## Overview
Complete MVP for tracking Fidelity brokerage account performance with transaction import, position tracking, and real-time P&L calculations.
## What's Been Built
### ✅ Backend (Python/FastAPI)
- **Database Models**: Account, Transaction, Position (with junction tables)
- **CSV Parser**: Fidelity-specific parser with deduplication
- **Services**:
- Import Service (file upload + filesystem import)
- Position Tracker (FIFO matching, options support)
- Performance Calculator (with Yahoo Finance integration)
- **API Endpoints**:
- Accounts (CRUD)
- Transactions (list, filter, pagination)
- Positions (open/closed, stats)
- Analytics (overview, balance history, top trades)
- Import (upload + filesystem)
- **Database**: PostgreSQL with Alembic migrations
- **Features**: Deduplication, real-time P&L, market data caching
### ✅ Frontend (React/TypeScript)
- **Components**:
- Dashboard (metrics cards + charts)
- Account Manager (create/list/delete accounts)
- Import Dropzone (drag-drop + filesystem import)
- Transaction Table (filterable, sortable)
- Position Cards (open/closed with P&L)
- Performance Chart (balance over time)
- Metrics Cards (KPIs)
- **Styling**: TailwindCSS with Robinhood-inspired design
- **State Management**: React Query for data fetching
- **Routing**: Tab-based navigation
### ✅ Infrastructure
- **Docker Compose**: Multi-container setup (postgres, backend, frontend)
- **Nginx**: Reverse proxy for SPA routing + API proxying
- **Multi-arch**: Supports amd64 and arm64
- **Volumes**: Persistent database + import directory
- **Health Checks**: Service readiness monitoring
### ✅ Developer Experience
- **Documentation**:
- README.md (comprehensive guide)
- QUICKSTART.md (2-minute setup)
- API docs (auto-generated at /docs)
- **Scripts**:
- start.sh (automated startup with health checks)
- stop.sh (graceful shutdown)
- seed_demo_data.py (demo data loader)
- **Environment**: .env.example template
- **Git**: .gitignore configured
## Key Features
### Transaction Management
- Import via CSV upload or filesystem
- Automatic deduplication using SHA-256 hashing
- Support for stocks, calls, puts
- Handle assignments, expirations, rolls
### Position Tracking
- Automatic FIFO matching
- Multi-leg position support
- Open vs. closed positions
- Partial position closes
- Average entry/exit prices
### Performance Analytics
- Realized P&L (closed positions)
- Unrealized P&L (open positions with live prices)
- Win rate calculation
- Average win/loss metrics
- Top trades analysis
- Balance history charting
### User Experience
- Clean, modern UI (Robinhood-inspired)
- Mobile-responsive design
- Real-time data updates
- Intuitive navigation
- Error handling with user feedback
## Architecture
### Data Flow
```
CSV File → Parser → Deduplication → Database (Transactions)
Position Tracker (FIFO)
Positions DB
Performance Calculator + Yahoo Finance
Analytics API
React Frontend
```
### Tech Stack
- **Backend**: Python 3.11, FastAPI, SQLAlchemy, PostgreSQL, Pandas, yfinance
- **Frontend**: React 18, TypeScript, Vite, TailwindCSS, React Query, Recharts
- **Infrastructure**: Docker, Docker Compose, Nginx
## File Structure
```
fidelity/
├── backend/
│ ├── app/
│ │ ├── api/endpoints/ # API routes
│ │ ├── models/ # Database models
│ │ ├── schemas/ # Pydantic schemas
│ │ ├── services/ # Business logic
│ │ ├── parsers/ # CSV parsers
│ │ └── utils/ # Helper functions
│ ├── alembic/ # DB migrations
│ ├── Dockerfile
│ ├── requirements.txt
│ └── seed_demo_data.py
├── frontend/
│ ├── src/
│ │ ├── components/ # React components
│ │ ├── api/ # API client
│ │ ├── types/ # TypeScript types
│ │ └── styles/ # CSS
│ ├── Dockerfile
│ ├── nginx.conf
│ └── package.json
├── imports/ # CSV import directory
├── docker-compose.yml
├── start.sh
├── stop.sh
├── README.md
├── QUICKSTART.md
└── .env.example
```
## Getting Started
### Quick Start
```bash
cd /Users/chris/Desktop/fidelity
./start.sh
```
### Access
- Frontend: http://localhost:3000
- Backend: http://localhost:8000
- API Docs: http://localhost:8000/docs
### Demo Data
```bash
cp History_for_Account_X38661988.csv imports/
docker-compose exec backend python seed_demo_data.py
```
## Testing Checklist
### ✅ To Test
1. Start application (`./start.sh`)
2. Create account via UI
3. Import sample CSV
4. Verify transactions imported
5. Check positions calculated
6. View dashboard metrics
7. Test filters and sorting
8. Verify P&L calculations
9. Check responsive design
10. Test re-import (deduplication)
## Future Enhancements
- [ ] Additional brokerages (Schwab, E*TRADE, Robinhood)
- [ ] Authentication/multi-user
- [ ] Tax reporting (wash sales, capital gains)
- [ ] Email notifications
- [ ] Dark mode
- [ ] PDF export
- [ ] AI trade recommendations
- [ ] Backtesting
## Notes
- Uses FIFO for position matching
- Market data cached for 60 seconds
- Options pricing uses Yahoo Finance (may not be perfect)
- Designed for personal use (single-user)
---
**Status**: ✅ MVP Complete and Ready for Testing
**Last Updated**: January 2026