AgentSkillsCN

jupyter-notebook

Jupyter Notebook专家技能——笔记本执行和Databricks内核集成的指南 适用情况： - 通过CLI执行Jupyter笔记本（jupyter execute） - 使用Databricks内核运行笔记本 - 配置笔记本执行选项（超时、inplace）

SKILL.md
--- frontmatter
name: jupyter-notebook
description: |
  Jupyter Notebook Expert Skill - Guide for notebook execution and Databricks kernel integration
  Use when:
  - Executing Jupyter notebooks via CLI (jupyter execute)
  - Running notebooks with Databricks kernel
  - Configuring notebook execution options (timeout, inplace)

Jupyter Notebook Expert Skill

This skill provides a guide for Jupyter Notebook execution.

1. Databricks Jupyter Kernel

https://github.com/i9wa4/jupyter-databricks-kernel

bash
uv pip install jupyter-databricks-kernel
uv run python -m jupyter_databricks_kernel.install

2. Default Execution Method

When instructed to execute an entire notebook, use this command:

sh
uv run jupyter execute <notebook_path> --inplace --timeout=300

3. Execute with Databricks Kernel

When running notebook on Databricks cluster:

sh
uv run jupyter execute <notebook_path> --inplace --kernel_name=databricks --timeout=300

Required environment variables:

  • •DATABRICKS_HOST: Databricks workspace URL
  • •DATABRICKS_TOKEN: Personal Access Token
  • •DATABRICKS_CLUSTER_ID: Cluster ID

4. Usage Examples

bash
# Execute with local Python kernel
uv run jupyter execute /workspace/notebooks/sample.ipynb --inplace --timeout=300

# Execute with Databricks kernel
uv run jupyter execute /workspace/notebooks/databricks-sample.ipynb --inplace --kernel_name=databricks --timeout=300

5. Option Descriptions

  • •--inplace: Overwrite original file with execution results
  • •--kernel_name=<name>: Specify kernel to use (databricks, python3, etc.)
  • •--timeout=<seconds>: Set timeout in seconds (-1 for unlimited)
  • •--startup_timeout=<seconds>: Kernel startup timeout (default 60 seconds)
  • •--allow-errors: Continue execution to end even with errors

6. Notes

  • •Verify required environment variables are properly set before execution
  • •Adjust --timeout value for long-running cells
  • •If open in VS Code, verify file updates after execution
  • •For Databricks kernel, cluster startup takes 5-6 minutes if stopped

7. Reference Links