In recent years, model deployment in machine learning is observed to be an interesting area
of study. It can be seen as a process similar to the one established for traditional software …

Jupyter notebooks---documents that contain live code, equations, visualizations, and
narrative text---now are among the most popular means to compute, present, discuss and …

Computational notebooks have become the tool of choice for many data scientists and
practitioners for performing analyses and disseminating results. Despite their increasing …

In this paper, we present the first exploratory study of deprecated Python library APIs to
understand the status quo of API deprecation in the realm of Python libraries. Specifically …

Jupyter Notebooks have been widely adopted by many different communities, both in
science and industry. They support the creation of literate programming documents that …

Background Jupyter notebooks facilitate the bundling of executable code with its
documentation and output in one interactive environment, and they represent a popular …

In recent years, Jupyter notebooks have grown in popularity in several domains of software
engineering, such as data science, machine learning, and computer science education …

More than ninety percent of published Jupyternotebooks do not state dependencies on
external packages. This makes them non-executable and thus hinders reproducibility of …

Python is a widely used programming language that powers important application domains
such as machine learning, data analysis, and web applications. For many programs in these …

Despite the widespread adoption of computational notebooks, little is known about best
practices for their usage in collaborative contexts. In this paper, we fill this gap by eliciting a …