Python Library
Python libraries are increasingly crucial for accelerating scientific computing and facilitating reproducible research across diverse fields. Current research emphasizes developing specialized libraries for tasks like machine learning prototyping, data assimilation with deep learning, efficient algorithm implementations (e.g., BM25, CMA-ES), and handling specific data types (e.g., audio, MIDI, molecular fingerprints, EEG). These tools enhance research productivity by streamlining workflows, improving performance, and promoting standardization, ultimately impacting various scientific domains and practical applications.
Papers
TextDescriptives: A Python package for calculating a large variety of metrics from text
Lasse Hansen, Ludvig Renbo Olsen, Kenneth Enevoldsen
Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning
Wenting Zhao, Ibrahim Abdelaziz, Julian Dolby, Kavitha Srinivas, Mossad Helali, Essam Mansour