Papermill is a powerful tool for parameterizing, executing, and analyzing Jupyter Notebooks. It allows users to easily parameterize and execute notebooks, opening up new possibilities for their utilization. This can be particularly useful for tasks like running financial reports with different values based on specific dates or conditions. Papermill simplifies the process of programmatically executing workflows without manual copying and pasting between notebooks. With an opinionated approach to parameterization and execution, Papermill leverages experiences in using notebooks at scale in data pipelines. Supported by Python 3.8+, Papermill offers various ways to parameterize and execute notebooks, whether through the Python API or the command line interface. The tool supports different methods for setting parameters, including using YAML files or base64-encoded strings. Papermill also provides support for various name handlers for input and output paths during execution, including local file systems, HTTP/HTTPS protocols, AWS S3, Azure, and Google Cloud. Developers can refer to the documentation on ReadTheDocs and contributing guidelines in the project repository for more information on setting up a development environment and making code changes.
https://github.com/nteract/papermill