PySMILESUtils is a framework for working with SMILES based deep learning architectures in PyTorch. It has classes for efficient vocabulary and tokenization, data augmentation, as well as optimized data loading for pre-augmented datasets, out-of-memory datasets. Significant speedups can be achieved by smart sampling of mini-batches based on SMILES length. The framework should provide a good and extensible starting point for building SMILES based deep learning models. By releasing it as opensource we hope to lower the barrier in for using SMILES based methods in deep learning for the molecular data science community and allow for greater collaboration and consistency across projects