Data scientists often use notebooks at the early stages of a project to explore solutions and validate technical feasibility. However, coding in notebooks can prevent the implementation of good software development practices and often requires recoding when going into production. Using an IDE and writing scripts instead can increase efficiency and shorten development time. This article discusses the drawbacks of using notebooks, such as lack of traceability and reproducibility, and provides solutions for maintaining the benefits of notebooks when using an IDE. If youre a data scientist using notebooks, this article will make you reconsider your workflow.
