# AtomizerField Requirements
# Python 3.8+ required

# ============================================================================
# Phase 1: Data Parser
# ============================================================================

# Core FEA parsing
pyNastran>=1.4.0

# Numerical computing
numpy>=1.20.0

# HDF5 file format for efficient field data storage
h5py>=3.0.0

# ============================================================================
# Phase 2: Neural Network Training
# ============================================================================

# Deep learning framework
torch>=2.0.0

# Graph neural networks
torch-geometric>=2.3.0

# TensorBoard for training visualization
tensorboard>=2.13.0

# ============================================================================
# Optional: Development and Testing
# ============================================================================

# Testing
# pytest>=7.0.0
# pytest-cov>=4.0.0

# Visualization
# matplotlib>=3.5.0
# plotly>=5.0.0

# Progress bars
# tqdm>=4.65.0