Skip to content

development.md

Latest commit

 

History

History
120 lines (86 loc) · 2.98 KB

development.md

File metadata and controls

120 lines (86 loc) · 2.98 KB

development.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Repository Overview

This repository contains the design and implementation for a cloud-based SaaS platform for surrogate modeling in engineering. The platform is designed to help engineering companies reduce computational costs and accelerate design cycles by replacing expensive FEA/CFD simulations with fast, accurate surrogate models.

Project Architecture

Platform Type: Cloud-native SaaS application for engineering surrogate modeling

Key Documentation:

  • PLATFORM_DESIGN.md - Comprehensive platform design including architecture, features, and business model
  • README.md - Project overview

Technology Stack (Planned)

Backend:

  • FastAPI (Python) for API services
  • PyTorch/TensorFlow for ML models
  • PostgreSQL + Redis for data management
  • Celery for task processing

Frontend:

  • React with TypeScript
  • Plotly.js for data visualization

Infrastructure:

  • Kubernetes on AWS/GCP/Azure
  • Docker containerization
  • S3-compatible storage for simulation data

Development Workflow

When implementing features:

  1. Follow the architecture outlined in PLATFORM_DESIGN.md
  2. Multi-tenant design - ensure all code supports tenant isolation
  3. Security-first - implement proper authentication, authorization, and data encryption
  4. ML best practices - use proper validation, model versioning, and monitoring
  5. API-first development - ensure all features are accessible via REST API

Key Development Considerations

  • Data Privacy: Handle sensitive engineering IP with appropriate security measures
  • Scalability: Design for horizontal scaling and high-throughput predictions
  • ML Operations: Implement proper model lifecycle management
  • Performance: Optimize for sub-second prediction response times
  • Compliance: Consider ITAR/EAR regulations for engineering data

Common Commands

Backend Development:

cd backend

# Install dependencies
pip install -r requirements.txt

# Run development server
uvicorn app.main:app --reload

# Run tests
make test

# Run tests with coverage
make test-cov

# Lint and format code
make lint
make format

# Database migrations
make migrate                    # Apply migrations
make migrate-create name="..."  # Create new migration

Frontend Development:

cd frontend

# Install dependencies
npm install

# Start development server
npm start

# Run tests
npm test

# Build for production
npm run build

Docker Commands:

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

# Rebuild containers
docker-compose build

Project Structure

When code is added, organize as:

/backend          # FastAPI services
/frontend         # React application
/ml-models        # Surrogate model implementations
/infrastructure   # Kubernetes manifests, Dockerfiles
/docs            # Additional documentation