A.1 Cuadernos computacionales

“A notebook interface (also called a computational notebook) is a virtual notebook environment used for literate programming, a method of writing computer programs. Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections.
Modular notebooks may connect to a variety of computational back ends, called”kernels”. Notebook interfaces are widely used for statistics, data science, machine learning, and computer algebra.
At the notebook core is the idea of literate programming tools which can be described as “tools let you arrange the parts of a program in any order and extract documentation and code from the same source file.”, the notebook takes this approach to a new level extending it with some graphic functionality and a focus on interactivity. According to Stephen Wolfram: “The idea of a notebook is to have an interactive document that freely mixes code, results, graphics, text and everything else.”, and according to the Jupyter Project Documentation: “The notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based application suitable for capturing the whole computation process: developing, documenting, and executing code, as well as communicating the results. The Jupyter notebook combines two components”.”

A.1.1 Jupyter Notebooks

“Jupyter Notebook (formerly IPython Notebooks) is a web-based interactive computational environment for creating notebook documents.
A Jupyter Notebook document is a browser-based REPL containing an ordered list of input/output cells which can contain code, text (using Markdown), mathematics, plots and rich media. Underneath the interface, a notebook is a JSON document, following a versioned schema, usually ending with the”.ipynb” extension.”

“Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.”

“Colaboratory, or”Colab” for short, allows you to write and execute Python in your browser, with - Zero configuration required - Free access to GPUs - Easy sharing

Whether you’re a student, a data scientist or an AI researcher, Colab can make your work easier.”

A.1.2 R Markdown

“Analyze. Share. Reproduce.
Your data tells a story. Tell it with R Markdown. Turn your analyses into high quality documents, reports, presentations and dashboards.
R Markdown documents are fully reproducible. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output. Use multiple languages including R, Python, and SQL.”