📊 OpenFP&A — Open-Source Financial Planning & Analysis Platform

OpenFP&A is an open-source platform designed to automate Financial Planning & Analysis (FP&A) workflows for SMEs, consultants, and finance professionals.

No expensive software. No SaaS lock-ins. Just transparent, modular tools you control — built for real-world business needs.

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✨ Key Features

Phase 1 MVP (Current)

• Multiple Data Source Connections (PostgreSQL, MySQL, SQL Server, Oracle, SQLite)
• Flexible Reporting & Data Model with REST API
• Advanced Analytics Engine powered by Pandas
  • Pivot tables and cross-tabulation
  • Slice & dice operations
  • Statistical analysis and aggregations
• Excel Export/Import for end-users who prefer spreadsheets
• Docker-based deployment for easy setup
• Modern Tech Stack: FastAPI backend with comprehensive API documentation

Phase 2 & Beyond (Roadmap)

• Budgeting & Forecasting modules
• Workflow support for closing/budgeting cycles
• Manual journal entries and adjustments
• Advanced Excel integration (MDX connectors)
• ClickHouse/OLAP engine integration for performance
• Real-time dashboards and visualizations

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🏗️ Architecture

• Backend: FastAPI (Python 3.11+)
• Database: PostgreSQL (primary), Redis (caching)
• Data Processing: Pandas, NumPy
• Containerization: Docker & Docker Compose
• API Documentation: Auto-generated Swagger/OpenAPI

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📂 Project Structure

fpa-platform/
├── docker-compose.yml          # Docker orchestration
├── .env.example               # Environment variables template
├── README.md                  # This file
├── backend/                   # FastAPI backend application
│   ├── Dockerfile            # Backend container definition
│   ├── requirements.txt      # Python dependencies
│   ├── app/
│   │   ├── main.py          # FastAPI application entry point
│   │   ├── core/            # Core functionality
│   │   │   ├── config.py    # Application configuration
│   │   │   ├── database.py  # Database connection management
│   │   │   └── security.py  # Authentication & authorization
│   │   ├── api/
│   │   │   └── v1/
│   │   │       └── endpoints/   # API endpoints
│   │   │           ├── health.py        # Health checks
│   │   ├── models/          # SQLAlchemy ORM models - TODO
│   │   ├── schemas/         # Pydantic validation schemas - TODO
│   │   ├── services/        # Business logic layer - TODO
│   │   └── utils/           # Utility functions
│   └── tests/               # Test suite
└── migrations/              # Database migrations (Alembic)

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🚀 Quick Start

Prerequisites

• Docker & Docker Compose
• Git
• Python 3.11+ (for local development)

Installation

1. Clone the repository:

   git clone https://github.com/Finasis/OpenFPA.git
   cd OpenFPA

2. Create environment file:

   cp .env.example .env
   # Edit .env with your configuration

3. Start the platform:

   docker-compose up -d

4. Check service health:

   # API Health check
   curl http://localhost:8000/api/v1/health/
   
   # Readiness check (database & redis)
   curl http://localhost:8000/api/v1/health/ready

5. Access the platform:

   • API Documentation: http://localhost:8000/docs
   • API Base URL: http://localhost:8000/api/v1

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📋 API Endpoints

ALL ENDPOINTS ARE TODO

Data Sources

• GET /api/v1/data-sources - List all data sources
• POST /api/v1/data-sources - Create new data source
• GET /api/v1/data-sources/{id} - Get specific data source
• PUT /api/v1/data-sources/{id} - Update data source
• DELETE /api/v1/data-sources/{id} - Delete data source
• POST /api/v1/data-sources/{id}/test - Test connection
• POST /api/v1/data-sources/{id}/query - Execute query
• GET /api/v1/data-sources/{id}/tables - List tables

Analytics

• POST /api/v1/analytics/pivot - Create pivot table
• POST /api/v1/analytics/analyze - Perform data analysis
• POST /api/v1/analytics/slice-dice - Slice and dice operations
• POST /api/v1/analytics/export/excel - Export to Excel
• POST /api/v1/analytics/upload/csv - Analyze CSV upload
• GET /api/v1/analytics/functions - List available functions

Reports

• GET /api/v1/reports - List all reports
• POST /api/v1/reports - Create new report
• GET /api/v1/reports/{id} - Get specific report
• POST /api/v1/reports/{id}/execute - Execute report
• POST /api/v1/reports/{id}/schedule - Schedule report

Health & Monitoring

• GET /api/v1/health - Basic health check
• GET /api/v1/health/ready - Readiness probe
• GET /api/v1/health/live - Liveness probe

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🔧 Development

Local Development Setup

1. Create Python virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

   cd backend
   pip install -r requirements.txt
   pip install -r requirements-dev.txt  # For development tools

3. Run locally (requires PostgreSQL and Redis running):

   uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Running Tests

cd backend
pytest tests/ -v --cov=app

Database Migrations

# Create a new migration
alembic revision --autogenerate -m "Description of changes"

# Apply migrations
alembic upgrade head

# Rollback one version
alembic downgrade -1

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🐳 Docker Commands

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f backend

# Stop services
docker-compose down

# Stop and remove volumes (data)
docker-compose down -v

# Rebuild containers
docker-compose build --no-cache

# Access backend container
docker exec -it fpa_backend bash

# Access database
docker exec -it fpa_postgres psql -U fpa_user -d fpa_db

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🔒 Security Considerations

• Change default passwords in production
• Use environment variables for sensitive data
• Enable HTTPS in production
• Implement proper authentication (JWT tokens ready)
• Encrypt database passwords
• Regular security updates

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🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• Built for the FP&A community
• Inspired by the need for accessible financial tools
• Powered by open-source technologies

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📧 Contact

• Project Link: https://github.com/Finasis/OpenFPA
• Issues: https://github.com/Finasis/OpenFPA/issues

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