Marimo Vs. Jupyter: Solving Slow Page Loads With Notebooks

Are you experiencing slow page load times due to dynamic Marimo notebooks? Many users find themselves in this situation when using Marimo for documentation purposes. This article explores the challenges of using Marimo for fast documentation and proposes a strategic shift to Jupyter notebooks to leverage existing tools and improve performance. We will delve into the benefits of separating notebooks from documentation, exporting static HTML, and utilizing dynamic Pyodide exports for enhanced browsing experiences. Ultimately, we aim to create a more efficient and user-friendly documentation system.

The Performance Bottleneck: Dynamic Marimo Notebooks

Dynamic Marimo notebooks, while offering interactive features, can sometimes become a bottleneck when it comes to page load times. This is particularly noticeable when using them for documentation, where quick access and seamless browsing are crucial. The dynamic nature of Marimo, which involves real-time execution and rendering, can introduce delays that impact the overall user experience. When a user navigates to a page containing a Marimo notebook, the browser needs to process and execute the code, which can take time, especially for complex notebooks with extensive computations or large datasets. This delay can be frustrating for users seeking quick information, leading to a less-than-ideal documentation experience. In essence, while Marimo's dynamic capabilities are powerful for certain applications, they might not be the most efficient solution for delivering fast and responsive documentation.

Moreover, the architecture of Marimo notebooks, designed for interactivity and real-time updates, often requires more resources compared to static content. This can strain server resources, especially during peak usage times, further contributing to slow page load times. Therefore, it's essential to consider alternative approaches that can strike a better balance between interactivity and performance. Switching to a system that allows for both static and dynamic content delivery can be a significant step towards resolving these performance issues. By separating the interactive notebook functionality from the static documentation, we can optimize the browsing experience for all users, ensuring that information is readily accessible without unnecessary delays.

Another factor contributing to the performance challenge is the reliance on server-side execution for dynamic content in Marimo notebooks. Each request to view or interact with a Marimo notebook often triggers server-side computations, which can quickly become a bottleneck as the number of users and complexity of notebooks grow. This highlights the need for solutions that can offload some of the processing to the client-side, reducing the load on the server and improving response times. By adopting a hybrid approach, where static content is served directly and dynamic content is rendered on the client's browser, we can achieve a more scalable and efficient documentation system. This approach not only enhances the user experience but also reduces the overall cost of maintaining the documentation infrastructure.

The Proposed Solution: Switching to Jupyter Notebooks

To address the performance issues associated with dynamic Marimo notebooks, a strategic shift to Jupyter notebooks is proposed. Jupyter notebooks offer a robust and versatile platform for creating and sharing documents that contain live code, equations, visualizations, and narrative text. One of the key advantages of Jupyter notebooks is their flexibility in terms of exporting content. Unlike Marimo, which primarily focuses on dynamic rendering, Jupyter notebooks can be exported in various formats, including static HTML, which is ideal for fast-loading documentation. This allows us to decouple the interactive notebook functionality from the documentation, ensuring that users can quickly access information without the overhead of real-time execution.

By switching to Jupyter notebooks, we can leverage existing tools and workflows that are well-established within the data science and scientific computing communities. Jupyter has a vast ecosystem of extensions, libraries, and resources, making it easier to integrate with other systems and customize the documentation experience. Furthermore, Jupyter notebooks are widely supported across different platforms and environments, ensuring compatibility and accessibility for all users. This transition not only addresses the performance issues but also opens up opportunities for enhancing the documentation with richer content and interactive elements. For instance, we can incorporate interactive widgets, visualizations, and simulations directly into the notebooks, providing users with a more engaging and informative learning experience.

Another significant benefit of using Jupyter notebooks is the ability to create both static and dynamic versions of the same document. This can be achieved by utilizing tools like mkdocs-jupyter and mkdocs-jupyterlite, which enable the export of Jupyter notebooks as static HTML pages and dynamic Pyodide exports, respectively. The static HTML pages provide a fast and efficient way to browse the documentation, while the dynamic Pyodide exports allow users to interact with the notebooks directly in their browser without the need for a server-side kernel. This hybrid approach offers the best of both worlds, combining the speed of static content delivery with the interactivity of dynamic notebooks. By providing a toggle to switch between the static and dynamic versions, we can cater to different user preferences and use cases, ensuring a seamless and flexible documentation experience.

Exporting Jupyter Notebooks: Static HTML and Dynamic Pyodide

A crucial aspect of transitioning to Jupyter notebooks is the ability to export them in different formats to optimize for various use cases. The primary goal is to provide fast-loading documentation while retaining the interactive capabilities of the notebooks. To achieve this, we will leverage two powerful tools: a static MKDocs notebook exporter and a dynamic MKDocs notebook exporter. The static exporter, such as the one provided by mkdocs-jupyter, allows us to convert Jupyter notebooks into static HTML pages. These pages are lightweight and can be served quickly, making them ideal for browsing documentation. The dynamic exporter, such as mkdocs-jupyterlite, enables the creation of dynamic Pyodide exports, which allow users to run the notebooks directly in their browser.

The use of static HTML pages ensures that the documentation is accessible and responsive, regardless of the user's network connection or device capabilities. Static pages load quickly because they do not require server-side processing, which significantly reduces latency and improves the overall user experience. This is particularly important for users who are accessing the documentation from locations with limited bandwidth or on mobile devices. By providing static HTML versions of the notebooks, we can ensure that all users have a smooth and efficient browsing experience. The static pages also serve as a reliable fallback option in case the dynamic content is temporarily unavailable or encounters issues.

The dynamic Pyodide exports, on the other hand, provide an interactive environment where users can experiment with the code and data within the notebooks. Pyodide is a Python distribution that runs entirely in the browser using WebAssembly, allowing for client-side execution of Python code. This eliminates the need for a server-side kernel, reducing the load on the server and enabling users to interact with the notebooks without any delays. By integrating dynamic Pyodide exports into the documentation, we can offer a more engaging and hands-on learning experience. Users can modify the code, run experiments, and see the results in real-time, fostering a deeper understanding of the concepts being presented. The combination of static HTML pages and dynamic Pyodide exports provides a versatile solution that caters to different user needs and preferences.

Linking Static and Dynamic Pages: A Seamless User Experience

To fully leverage the benefits of both static and dynamic notebook exports, it's essential to seamlessly link them within the documentation. This can be achieved by providing clear and intuitive navigation between the static HTML pages and the dynamic Pyodide versions of the notebooks. One effective approach is to include a link on each static page that directs users to the corresponding dynamic version. This allows users to easily switch between the two formats, depending on their needs and preferences. The link can be prominently displayed, such as a button or a banner at the top of the page, ensuring that users are aware of the option to interact with the notebook dynamically.

Conversely, the dynamic Pyodide pages should also include a link back to the static HTML version. This is particularly important for users who might encounter performance issues or browser compatibility problems with the dynamic content. By providing a link to the static version, we ensure that users always have a fallback option and can access the information without any disruptions. This bidirectional linking creates a cohesive and user-friendly experience, allowing users to seamlessly navigate between the static and dynamic content. The links should be clearly labeled and easy to find, minimizing any confusion and maximizing the usability of the documentation.

In addition to direct links between corresponding static and dynamic pages, it's also beneficial to provide a site-wide toggle that allows users to switch between static and dynamic rendering modes. This toggle can be implemented as a simple switch in the navigation bar or a settings panel, allowing users to set their preferred rendering mode for the entire site. When the toggle is set to static mode, all notebook pages will be rendered as static HTML, while dynamic mode will load the Pyodide versions. This feature provides users with a consistent and personalized experience, allowing them to choose the rendering mode that best suits their needs and device capabilities. The toggle should persist across sessions, so users only need to set their preference once. By implementing these linking strategies, we can create a documentation system that is both performant and interactive, providing a seamless experience for all users.

Creating a Toggle for the Entire Site: User-Centric Design

A user-centric design approach is crucial for creating a documentation system that meets the needs of a diverse audience. One of the key aspects of this approach is to provide users with control over their browsing experience. Implementing a toggle for the entire site that allows users to switch between static and dynamic rendering modes is a significant step in this direction. This toggle empowers users to choose the rendering mode that best suits their device, network conditions, and personal preferences. For example, users with limited bandwidth or older devices might prefer the static mode for faster loading times, while those with modern hardware and reliable internet connections might opt for the dynamic mode to take advantage of the interactive features.

The toggle can be implemented as a simple switch or button in the site's navigation bar or settings panel. It should be clearly labeled, such as "Static/Dynamic Mode" or "Interactive Notebooks On/Off," to ensure that users understand its purpose. When a user changes the toggle setting, the site should immediately update to reflect the new preference. This can be achieved using client-side JavaScript to dynamically load the appropriate version of the notebook pages. To provide a seamless experience, the toggle setting should persist across sessions, so users don't have to re-select their preferred mode each time they visit the site. This can be accomplished by storing the user's preference in a cookie or local storage.

In addition to the global toggle, it's also beneficial to provide individual links to the static and dynamic versions of each notebook, as discussed earlier. This gives users even more flexibility and control over their browsing experience. For instance, a user might prefer to browse the site in static mode for most pages but occasionally switch to the dynamic version for a particular notebook that they want to interact with. By offering both a global toggle and individual links, we can cater to a wide range of user needs and preferences. This user-centric design approach ensures that the documentation system is accessible, efficient, and enjoyable to use, ultimately enhancing the learning experience for all users. By prioritizing user control and flexibility, we can create a documentation system that truly meets the needs of its audience.

Implementation Checklist

To ensure a smooth transition from Marimo to Jupyter notebooks and to effectively address the slow page load issues, the following checklist outlines the key steps to be taken:

• [ ] Setup basic MKDocs pages export: Configure MKDocs to generate static HTML pages from the documentation source files. This involves setting up the MKDocs project structure, defining the navigation, and creating the initial pages.
• [ ] Swap Marimo notebooks to Jupyter: Convert existing Marimo notebooks to Jupyter notebooks. This may involve some manual adjustments to ensure compatibility and proper rendering in the Jupyter environment.
• [ ] Export Jupyter notebooks as static pages: Utilize a tool like mkdocs-jupyter to export the Jupyter notebooks as static HTML pages. This step is crucial for ensuring fast page load times and a smooth browsing experience.
• [ ] Export Jupyter notebooks as dynamic pages: Employ a tool like mkdocs-jupyterlite to export the Jupyter notebooks as dynamic Pyodide exports. This will enable users to interact with the notebooks directly in their browser without the need for a server-side kernel.
• [ ] Link static and dynamic pages: Implement a clear and intuitive linking mechanism between the static HTML pages and the dynamic Pyodide versions of the notebooks. This allows users to seamlessly switch between the two formats based on their needs and preferences.
• [ ] Create toggle for entire site: Develop a site-wide toggle that allows users to switch between static and dynamic rendering modes. This toggle should persist across sessions and provide users with control over their browsing experience.

By following this checklist, we can ensure a systematic and effective transition to a more performant and user-friendly documentation system. Each step is crucial for achieving the desired outcome of fast-loading, interactive documentation that meets the needs of a diverse user base.

Conclusion

In conclusion, addressing the slow page load times caused by dynamic Marimo notebooks requires a strategic shift towards a more versatile and efficient solution. By transitioning to Jupyter notebooks, we can leverage the power of static HTML exports and dynamic Pyodide integration to create a seamless and user-friendly documentation experience. The combination of fast-loading static pages and interactive dynamic notebooks provides the best of both worlds, catering to the diverse needs of our users. Implementing a site-wide toggle and clear linking mechanisms ensures that users have control over their browsing experience and can easily access the content in their preferred format. This approach not only improves performance but also enhances the overall usability and accessibility of the documentation system.

Remember to explore additional resources and tools to further optimize your documentation workflow. For more information on web development best practices and performance optimization, visit Mozilla Developer Network (MDN). This will help you stay informed and continue to improve your documentation and website performance.