Intro to containers updated #237
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…e explaining the distinction between research code and production code, emphasizing its exploratory and analysis-driven nature. It outlines the common challenges researchers face, such as reusability, documentation, code quality, and computational scalability. The guide also provides best practices for improving research code quality, including version control, dependency management, and workflow automation. Additionally, we integrate a section on the advent of AI in research coding, illustrating how AI can function as a pair programming partner. This highlights the shift in roles, where researchers become navigators, focusing on software architecture and computational principles while AI handles implementation. The guide stresses the importance of **responsible AI use**, ensuring conceptual understanding rather than blind copy-pasting, ultimately enhancing scientific computing skills. Overall, this guide serves as a structured introduction to research code development, helping researchers at TU Delft and beyond improve their coding practices for better scientific reproducibility and collaboration. I would still like to maybe at somepoint make some example or something that illustrates with code something, but for now this is a good enough getting started guide.
…, and audience relevance. Enhanced section organization to align with researchers' needs, emphasizing use cases for short-term reproducibility, long-term preservation, and CI/CD. Simplified cloud computing discussion by focusing on virtualization as the core principle. Expanded explanations for HPC clusters and containerized Jupyter environments. Improved conclusion to highlight when to adopt containers based on complexity and necessity.
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Hi guys here is a PR for containers #212.
I believe I saw intro to containers needed some improvements. I checked the content and in any case I thought it could definetely be improved.