JupyterLab vs Jupyter Notebook: Which One Should You Choose?

As a Google SEO expert, the choice between JupyterLab and Jupyter Notebook is one that developers often grapple with. The Jupyter team has clearly decided that JupyterLab is the future, positioning it as the primary interface for the Jupyter project, while Jupyter Notebook remains a 'legacy' version.

Overview and Usability

From a functional standpoint, both JupyterLab and Jupyter Notebook offer similar capabilities, though the development process might differ slightly based on personal preference. JupyterLab operates in a single tab with sub-tabs, whereas Jupyter Notebook opens new notebooks in separate tabs. This might limit Jupyter Notebook to appear more standalone or independent, which could be advantageous depending on your project needs.

Modularity and Independence

One significant advantage of JupyterLab is its modularity. Unlike Jupyter Notebook, JupyterLab allows you to run notebook or terminal tabs independently of the kernels (e.g., Python, R) executing each cell. This feature enables you to perform multiple experiments quickly without cluttering your main notebook cells. For instance, you can run multiple notebook tabs or terminal windows all connected to the same kernel. This setup is particularly useful for conducting rapid experiments based on the current notebook state.

Extension Compatibility and Development

The choice of which interface to use heavily depends on the availability of Jupyter extensions. Active development is required to port an extension between JupyterLab and Jupyter Notebook. As a result, some functionalities might not work as seamlessly as expected. For example, the extension framework in JupyterLab can sometimes be overly complex, making it difficult to manage and understand the setup, especially when compiling and minifying JavaScript.

Perspectives and Future Developments

From a personal perspective, I find Jupyter Notebook to be more straightforward and less overwhelming, allowing me to focus on my work without being distracted by additional complexities. However, if you prefer to adapt to new environments quickly and master productivity shortcuts, JupyterLab might be more efficient for you. The IDE-like nature of JupyterLab can lead to faster work in the long run, especially as more extensions and features are developed.

Ultimately, both JupyterLab and Jupyter Notebook are part of a great free and open-source ecosystem. The broader Jupyter project ecosystem is invaluable, and the developments happening with JupyterLab are promising. The team behind Jupyter is constantly working to improve and simplify their tools, ensuring that developers can work more efficiently and effectively.

Thank you to all the developers who contribute to making these tools available and continue to enhance them. I hope the thoughts shared here can help you make the most of the Jupyter project, whether you opt for JupyterLab or Jupyter Notebook.