Description
What is the best way to develop analysis code in the Jupyter notebook, while managing complex dependencies between analyses? In this talk, I will introduce nbflow, which is a project that integrates a Python-based build system (SCons) with the Jupyter notebook, enabling researchers to easily build sophisticated, complex analysis pipelines entirely within notebooks while still maintaining a "one-button workflow" in which all analyses can be executed, in the correct order, from a single command. I will show how nbflow can be applied to existing analyses and how it can be used to construct an analysis pipeline stretching the entire way from data cleaning, to computing statistics, to generating figures, and even to automatically generating LaTeX commands that can be used in publications to format results without the risk of copy-and-paste error.