23 Matching Annotations
  1. Mar 2020
    1. Jupytext can be configured to automatically pair a git-friendly file for input data while preserving the output data in the .ipynb file

      git-friendly Jupytext options include

      • Julia: .jl
      • Python: .py
      • R: .R
      • Markdown: .md
      • RMarkdown: .Rmd
      • and more!
    1. They switch to get features like good doc lookup, good syntax highlighting, integration with unit tests, and (critically!) the ability to produce final, distributable source code files, as opposed to notebooks or REPL histories

      Things missed in Jupyter Notebooks:

      • good doc lookup
      • good syntax highlighting
      • integration with unit tests
      • ability to produce final, distributable source code files
    2. Development Pros Cons

      Table comparing pros and cons of:

      • IDE/Editor
      • REPL/shell
      • Traditional notebooks (like Jupyter)
    3. Exploratory programming is based on the observation that most of us spend most of our time as coders exploring and experimenting

      In exploratory programming, we:

      • experiment with a new API to understand how it works
      • explore the behavior of an algorithm that we're developing
      • debug our code through combination of inputs
    4. The point of nbdev is to bring the key benefits of IDE/editor development into the notebook system, so you can work in notebooks without compromise for the entire lifecycle
    5. This kind of “exploring” is easiest when you develop on the prompt (or REPL), or using a notebook-oriented development system like Jupyter Notebooks

      It's easier to explore the code:

      • when you develop on the prompt (or REPL)
      • in notebook-oriented system like Jupyter

      but, it's not efficient to develop in them

    6. notebook contains an actual running Python interpreter instance that you’re fully in control of. So Jupyter can provide auto-completions, parameter lists, and context-sensitive documentation based on the actual state of your code

      Notebook makes it easier to handle dynamic Python features

  2. Jan 2020
  3. Sep 2019
  4. Jul 2019
  5. May 2019
  6. Jul 2018
    1. We want to even go even further and add reproducible elements to JATS documents. We are working together with Stencila on extending Texture to allow both textual narrative and executable code to coexist in one document.
  7. Apr 2018
    1. JupyterHub, a multi-user Hub, spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server.
    1. At one point, Pérez told me the name Jupyter honored Galileo, perhaps the first modern scientist. The Jupyter logo is an abstracted version of Galileo’s original drawings of the moons of Jupiter. “Galileo couldn’t go anywhere to buy a telescope,” Pérez said. “He had to build his own.”

      Cool name/logo story!

    2. At every turn, IPython chose the way that was more inclusive, to the point where it’s no longer called “IPython”: The project rebranded itself as “Jupyter” in 2014 to recognize the fact that it was no longer just for Python.

      Such an interesting progression!

    3. At every turn, IPython chose the way that was more inclusive

      Nice to see that decision pay off!

  8. Jan 2018
  9. Aug 2017
    1. markdown_display_priority

      I don't know why or when my annotations will be properly applied.

      This is quite confusing. The interface remembers my tag, but not the content of my annotation.

      It does not seem to allow the application of an annotation to text inside of an iframe. This prevents proper testing of hypothes.is as a jupyter notebook annotation tool.

      In some ways it's great, but the interface and user model could use a lot of work. If it allowed annotations inside iframes I'd gladly navigate those rough edges. But without that feature it's hard to justify trying to use this for the purpose of annotating notebooks.

      Hopefully, this can be fixed, in which case I'll edit this annotation to acknowledge that annotation inside iframes works. That would mean the annotation of Jupyter notebooks would be be a process capable of supporting code review on a notebook via GitHub.

    1. markdown_display_priority

      Unfortunately this is probably the easiest place to apply a hypothes.is annotation. They don't look inside iframes. So the rendered version of the notebook will not work.

  10. Mar 2017
    1. Seco, si bien es una implementación del 2004, tiene varias ideas que son similares a las de Grafoscopio de hoy, incluyendo la persistencia de una imagen (ellos usan HyperGraphDB, pero incluso mencionan Smalltalk), el hecho de ser una aplicación de escritorio y la idea de una computación p2p, o la opción de embeber el motor de rendering de un browser o el browser mismo en un ambiente más rico, incluso la inspiración de los notebooks de mathematica.

  11. Jan 2017