Connect to a notebook and corresponding kernel. It is the FIRST STEP before ANY subsequent operations.

List all currently connected Notebooks. It will return unique name, Jupyter URL and Path of all connected Notebooks

Restart the kernel of a specified Notebook, clear all imported packages and variables

Read the source content (without output) of a connected Notebook. It will return the formatted content of the Notebook (including Index, Cell Type, Execution Count and Full Source Content). ONLY used when the user explicitly instructs to read the full content of the Notebook.

List the basic information of cells. It will return Index, Type, Execution Count and First Line of the Cell. It will be used to quickly overview the structure and current status of the Notebook or locate the index of specific cells for following operations(e.g. delete, insert).

Read the detailed content of a specific cell. It will return the source code, execution count and output of the cell.

Delete a specific cell. When deleting many cells, MUST delete them in descending order of their index.

Insert a cell at the specified index. When inserting many cells, MUST insert them in ascending order of their index.

Execute a specific cell with a timeout. It will return the output of the cell.

Overwrite the content of a specific cell It will return a comparison (diff style, + for new lines, - for deleted lines) of the cell's content.

Add a new code cell to the end of a Notebook and immediately execute it. It is highly recommended for replacing the combination of insert_cell and execute_cell for a code cell at the end of the Notebook. It will return the output of the cell.

Execute a temporary code block (not saved to the Notebook) and will return the output.

It will recommend to use in following cases:

1. Execute Jupyter magic commands(e.g., %timeit, %pip install xxx)

2. Debug code

3. View intermediate variable values(e.g., print(xxx), df.head())

4. Perform temporary statistical calculations(e.g., np.mean(df['xxx']))

DO NOT USE IN THE FOLLOWING CASES:

1. Import new modules and perform variable assignments that affect subsequent Notebook execution

2. Run code that requires a long time to run