SciPy 1.0: fundamental algorithms for scientific computing in Python

Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson et al.

Nature Methods, 2020

39,949 citations

Abstract

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Read the paper

• DOI
• PubMed
• Publisher page

Related studies

• A Survey on Knowledge Graphs: Representation, Acquisition, and Applications IEEE Transactions on Neural Networks and Learning Systems, 2021
• Toxicity of nanomaterials Chemical Society Reviews, 2011
• The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies Human Genetics, 2017
• Halogen bonding (X‐bonding): A biological perspective Protein Science, 2012
• Biofilm formation at the air–liquid interface by the Pseudomonas fluorescens SBW25 wrinkly spreader requires an acetylated form of cellulose Molecular Microbiology, 2003
• Opioid Activation of Toll-Like Receptor 4 Contributes to Drug Reinforcement Journal of Neuroscience, 2012

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free