DEVELOPER TIPS AND TRICKS: HARNESSING THE POWER OF CODE NOTEBOOKS

Code notebooks have become a vital tool for software development, especially within the realm of data science.

Unlike traditional development environments where code runs as a complete program, notebooks organize code and commentary into distinct cells.

Each cell can be executed independently, displaying its output directly below, which provides an interactive, iterative, and exploratory coding experience.

This format originally catered to data scientists who needed to experiment with data manipulations and visualizations directly and immediately see the effects of incremental changes.

However, the flexibility and utility of code notebooks have prompted their adoption across various programming disciplines.

Visual Studio Code Notebooks

Visual Studio Code (VS Code) supports notebook-style programming through extensions like Jupyter and the core Notebook APIs.

This integration offers developers the familiar robust environment of VS Code but with the interactivity of a notebook.

This setup is particularly beneficial for projects that require frequent tweaking and immediate feedback.

VS Code notebooks support multiple languages and can be customized with various kernels, allowing a seamless transition between different programming tasks.

The direct integration with Git also offers version control, making it easier to track and revert changes across notebook iterations.

Notebook Kernels for Compiled Languages

Contrary to common belief, notebooks are not limited to interpreted languages like Python and R.

Many programming languages have processes called kernels that can receive cell code, execute it, and return the results back to a notebook environment.

Thanks to advancements in kernel technology, such as the Xeus project, notebooks can now run compiled languages like C++ and Rust.

This capability leverages Just-In-Time (JIT) compilation techniques to compile code on-the-fly, allowing notebooks to support languages that traditionally required separate compilation steps.

This development opens up notebook functionalities to a broader range of programming languages and applications, enhancing the flexibility and reach of notebook technology in software development.

IntelliJ IDEA Kotlin Notebooks

Kotlin, a full-stack language and the primary language for native Android development, now has notebook support in Intellij IDEA, which allows developers to import Kotlin modules and interact with them on-the-fly.

This capability is particularly useful for testing new libraries or modules before integrating them into larger projects, especially since testing mobile app code can be quite tricky to set up.

The direct integration of notebooks within IntelliJ provides a consistent and powerful environment for both traditional and notebook-style coding, ensuring that many tools and plugins available for Kotlin development (that don’t require a target device to be running) are accessible within the notebooks as well.

Notebooks in DevOps for QA

Beyond their use in data science and software development, notebooks are finding a place in DevOps and quality assurance (QA).

Developers can use notebooks to script and execute web requests and other diagnostic code with custom logic across multiple cells.

This method is distinct from standalone tools like Postman because it allows for the use of actual project code within the notebook. By embedding the same code snippets used in the application into the notebook, developers can more accurately test and monitor live endpoints.

Additionally, using custom cell logic and outputs, developers can aggregate, filter, and graph data from multiple endpoints, providing a more cohesive, controlled, and rich testing environment that mirrors real-world usage more closely than traditional tools.

Conclusion

Whether through enhancing traditional IDEs like VS Code and IntelliJ IDEA, integrating with DevOps practices for better QA, or expanding the scope of supported programming languages through advanced kernels, notebooks continue to evolve.

This evolution underscores their growing role in various facets of programming, providing developers with an effective platform for coding, testing, and deployment in an increasingly interactive and integrated manner.