  By bringing together code, text, and examples, Jupyter notebooks have become
one of the most popular means to produce scientific results in a productive and
reproducible way. As many of the notebook authors are experts in their
scientific fields, but laymen with respect to software engineering, one may ask
questions on the quality of notebooks and their code. In a preliminary study,
we experimentally demonstrate that Jupyter notebooks are inundated with poor
quality code, e.g., not respecting recommended coding practices, or containing
unused variables and deprecated functions. Considering the education nature of
Jupyter notebooks, these poor coding practices as well as the lacks of quality
control might be propagated into the next generation of developers. Hence, we
argue that there is a strong need to programmatically analyze Jupyter
notebooks, calling on our community to pay more attention to the reliability of
Jupyter notebooks.
