tsflex provides a toolkit for time series processing and feature extraction that is efficient and makes few assumptions about sequence data. It focuses on windowing and stride-based operations for extracting features from multivariate and multimodal time series data, commonly used as a preprocessing step in machine learning pipelines for time-series classification, regression, or anomaly detection tasks.