An algorithm that re-splits Jupyter notebooks by merging and splitting their cells.

The repository has the following structure:

/resplitter/ — the implementation of ReSplit.

/data/— the storage for the datasets.

/analysis/ — the notebooks for running ReSplit and analysing the results.

/experiment/ — the code for generating the sample for the user study that we used to evaluate the algorithm.

/jupyter_experiment/ — the generated data and the code for hosting the Jupyter server for the experiment. Additionally, in survey.pdf you can find the form with the questions from the survey.

1. Install the requirements by running

   pip install -r requirements.txt

2. Download the data from Zenodo, unzip it, and place it in the data folder in the repository.

3. Currently, one can run ReSplit on the entire dataset of notebooks. To start, you need to create the NotebokProcessor object and specify whеther to preform splitting, merging, or both.

   nbp = NotebookProcessor({'merge': True, 'split': True})

4. Then, you can process a dataset using the process_notebook_dataset method or process a single notebook with the process_notebook method. For the first method, you need to provide a path for the dataset. For the second method, you need to provide the notebook as DataFrame. For both formats, please look into the provided data files.

ReSplit uses the definition-usage chain analysis of the code to find candidates to merge or split, as well as a number of heuristics to select the best among them. To see find out more about how the algorithm works, please refer to our SANER'22 paper.

TBD: we will add a number of examples here to highlight the operation of ReSplit.

If you have any questions or suggestions about the work, feel free to create an issue or contacnt Sergey Titov at [email protected].