  We describe how Python can be leveraged to streamline the curation, modelling
and dissemination of drug discovery data as well as the development of
innovative, freely available tools for the related scientific community. We
look at various examples, such as chemistry toolkits, machine-learning
applications and web frameworks and show how Python can glue it all together to
create efficient data science pipelines.
