| # Neuro-Symbolic AI Forecasting - Requirements | |
| # ============================================ | |
| # Python Version | |
| # ============================================ | |
| # Python 3.9+ required | |
| # Tested on: Python 3.10, 3.11 | |
| # ============================================ | |
| # Core Dependencies | |
| # ============================================ | |
| # Deep Learning Framework | |
| torch>=2.0.0 # PyTorch for neural network and GPU support | |
| torchvision>=0.15.0 # For data loading utilities | |
| # Data Processing & Analysis | |
| numpy>=1.21.0 # Numerical computing | |
| pandas>=1.3.0 # Data manipulation and time series handling | |
| scikit-learn>=1.0.0 # Machine learning utilities (MinMaxScaler) | |
| # Financial Data | |
| yfinance>=0.2.28 # Download stock data from Yahoo Finance | |
| # Optimization (Symbolic Layer) | |
| cvxpy>=1.3.0 # Convex optimization for symbolic seam projection | |
| osqp>=0.6.2 # OSQP solver (backend for cvxpy) | |
| # Visualization | |
| matplotlib>=3.5.0 # Plotting and visualization | |
| # ============================================ | |
| # Optional Dependencies | |
| # ============================================ | |
| # Jupyter Notebooks | |
| jupyter>=1.0.0 # Jupyter notebook support | |
| ipython>=8.0.0 # Enhanced interactive Python | |
| # Development & Testing | |
| pytest>=7.0.0 # Unit testing framework | |
| black>=22.0.0 # Code formatting | |
| pylint>=2.12.0 # Code linting | |
| # ============================================ | |
| # GPU/CPU Requirements | |
| # ============================================ | |
| # GPU Support (Optional but Recommended) | |
| # For NVIDIA GPU: Install CUDA 11.8 or 12.1 | |
| # Command: pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 | |
| # For CPU-only (slower training, 10-20x slower on large datasets): | |
| # Already included in default torch installation | |
| # ============================================ | |
| # Hardware Specifications | |
| # ============================================ | |
| # Minimum (CPU-only): | |
| # - Processor: 4 cores | |
| # - RAM: 8 GB | |
| # - Storage: 2 GB | |
| # - Time to train: ~30 minutes per epoch | |
| # Recommended (GPU): | |
| # - GPU: NVIDIA with 4GB+ VRAM (tested on T4, V100) | |
| # - Processor: 8 cores | |
| # - RAM: 16 GB | |
| # - Storage: 5 GB | |
| # - Time to train: ~1-2 minutes per epoch | |
| # ============================================ | |
| # Installation Instructions | |
| # ============================================ | |
| # 1. Create virtual environment | |
| # python -m venv neuro-symbolic-env | |
| # .\neuro-symbolic-env\Scripts\activate # Windows | |
| # source neuro-symbolic-env/bin/activate # Linux/Mac | |
| # 2. Install basic requirements | |
| # pip install -r requirements.txt | |
| # 3. For GPU support (NVIDIA only) | |
| # pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 | |
| # 4. Verify installation | |
| # python -c "import torch; print(torch.__version__); print(torch.cuda.is_available())" | |
| # ============================================ | |
| # Version Pinning (Exact Versions Used) | |
| # ============================================ | |
| # Uncomment below to use exact versions that were tested: | |
| # torch==2.1.0 | |
| # torchvision==0.16.0 | |
| # numpy==1.24.3 | |
| # pandas==2.0.3 | |
| # scikit-learn==1.3.0 | |
| # yfinance==0.2.32 | |
| # cvxpy==1.3.2 | |
| # matplotlib==3.7.2 | |
| # jupyter==1.0.0 | |