3 ms·

why pick just one language? with the polyglot Beaker Notebook, you can work with many languages, even in the same notebook, and your data is automatically trans

by spot 11y ago

why pick just one language? with the polyglot Beaker Notebook, you can work with many languages, even in the same notebook, and your data is automatically translated between them. each of these languages has its strong point. there is always some library you want to use in some other language. or you want to collaborate with someone. or next year you change your mind and Julia is finally good enough. http://BeakerNotebook.com http://BeakerNotebook.com

stuartaxelowen 11y ago
Knowing other languages is great, but there is very real overhead in learning them. Python is mature enough that you have mature libraries available for pretty much everything.
- spot 11y ago
  believe it or not, there are some people who know R and face overhead to learn Python. and they love ggplot2. and frankly, Python has no libraries for interactive visualization in your browser because only JavaScript runs there. etc.
  - evanpw 11y ago
    http://bokeh.pydata.org/en/latest/ http://bokeh.pydata.org/en/latest/ "Bokeh is a Python interactive visualization library that targets modern web browsers for presentation." (Of course, it works by generating JavaScript)
    - spot 11y ago
      right, and in order to really customize what bokeh does you need to write JS in strings in your python code, so this just proves my point. http://bokeh.pydata.org/en/latest/docs/user_guide/interaction.html#userguide-interaction http://bokeh.pydata.org/en/latest/docs/user_guide/interactio... see the CustomJS function.
      - tanlermin 11y ago
        No you don't. It now does python to JS compilation. And that's if you want client side callbacks.
  - ced 11y ago
    Python has no libraries for interactive visualization in your browser because only JavaScript runs there Isn't that like saying that C has no visualization libraries on Intel processors because only assembly runs there?
    - deleted 11y ago
      [deleted]
zmmmmm 11y ago
I really like Beaker. However Jupyter also caters to a wide range of languages, albeit one language per notebook. So the main differentiator for Beaker is that it can auto translate data between languages. However there is a giant catch to that: it is done by serialising the data which intrinsically means it is extremely expensive for any significant sized data set. As a result, in most cases I end up writing my data out to a file in one language, then reading it in again in another, even when I'm using Beaker, because the auto-translation is just too inefficient to do through Beaker's process. However both Beaker and Jupyter lag behind RStudio in raw usability and convenience, especially for plotting. There doesn't seem to be any tool in this vein that "has it all" right now.
- spot 11y ago
  thanks. indeed autotranslation currently only works for small data. fixing it with shared memory and hdf5 is on the agenda for later this year: https://github.com/twosigma/beaker-notebook/wiki/Roadmap https://github.com/twosigma/beaker-notebook/wiki/Roadmap I would really like to hear what usability and convenience advantages RStudio has for you...
  - zmmmmm 11y ago
    Reflecting on it, what I think I find most attractive about RStudio is two things: 1) the IDE like environment. Although I do a lot of work "literate document" style, there's a very fluid relationship between the one-off / throw away code that ends up in those documents and the code that ends up becoming reusable. RStudio puts the interactive environment into my hands but gives me tabs with full documents to work with so that I can take those ad hoc bits of code and seamlessly move them into reusable scripts, or even fully structured libraries and program code. Conversely, any piece of code in those scripts or libraries is trivial to throw back into my interactive console to use ad hoc as well. This fluid workflow perfectly matches my development style: starts with experiments to figure out how to do things which is very ad hoc, gradually matures and eventually ends up being a static solid thing that I want to capture as a reusable component. With Beaker and Jupyter I feel like I am always stuck in "throw away code" mode, and there's a high friction to move code between the two paradigms. 2) The plot display seems to work a lot better. With both Beaker and jupyter I find the inline plots are too static - always the wrong size or the wrong shape, etc. In RStudio I can drag and resize that window independently. I feel bad because I'm not telling you solutions and I don't really have any - but these are the things I love about RStudio. Of course, the downside of RStudio is ... R.

by spot 11y ago

stuartaxelowen 11y ago

Knowing other languages is great, but there is very real overhead in learning them. Python is mature enough that you have mature libraries available for pretty much everything.

spot 11y ago
believe it or not, there are some people who know R and face overhead to learn Python. and they love ggplot2. and frankly, Python has no libraries for interactive visualization in your browser because only JavaScript runs there. etc.
- evanpw 11y ago
  http://bokeh.pydata.org/en/latest/ http://bokeh.pydata.org/en/latest/ "Bokeh is a Python interactive visualization library that targets modern web browsers for presentation." (Of course, it works by generating JavaScript)
  - spot 11y ago
    right, and in order to really customize what bokeh does you need to write JS in strings in your python code, so this just proves my point. http://bokeh.pydata.org/en/latest/docs/user_guide/interaction.html#userguide-interaction http://bokeh.pydata.org/en/latest/docs/user_guide/interactio... see the CustomJS function.
    - tanlermin 11y ago
      No you don't. It now does python to JS compilation. And that's if you want client side callbacks.
- ced 11y ago
  Python has no libraries for interactive visualization in your browser because only JavaScript runs there Isn't that like saying that C has no visualization libraries on Intel processors because only assembly runs there?
  - deleted 11y ago
    [deleted]

zmmmmm 11y ago

I really like Beaker. However Jupyter also caters to a wide range of languages, albeit one language per notebook. So the main differentiator for Beaker is that it can auto translate data between languages. However there is a giant catch to that: it is done by serialising the data which intrinsically means it is extremely expensive for any significant sized data set. As a result, in most cases I end up writing my data out to a file in one language, then reading it in again in another, even when I'm using Beaker, because the auto-translation is just too inefficient to do through Beaker's process. However both Beaker and Jupyter lag behind RStudio in raw usability and convenience, especially for plotting. There doesn't seem to be any tool in this vein that "has it all" right now.

spot 11y ago
thanks. indeed autotranslation currently only works for small data. fixing it with shared memory and hdf5 is on the agenda for later this year: https://github.com/twosigma/beaker-notebook/wiki/Roadmap https://github.com/twosigma/beaker-notebook/wiki/Roadmap I would really like to hear what usability and convenience advantages RStudio has for you...
- zmmmmm 11y ago
  Reflecting on it, what I think I find most attractive about RStudio is two things: 1) the IDE like environment. Although I do a lot of work "literate document" style, there's a very fluid relationship between the one-off / throw away code that ends up in those documents and the code that ends up becoming reusable. RStudio puts the interactive environment into my hands but gives me tabs with full documents to work with so that I can take those ad hoc bits of code and seamlessly move them into reusable scripts, or even fully structured libraries and program code. Conversely, any piece of code in those scripts or libraries is trivial to throw back into my interactive console to use ad hoc as well. This fluid workflow perfectly matches my development style: starts with experiments to figure out how to do things which is very ad hoc, gradually matures and eventually ends up being a static solid thing that I want to capture as a reusable component. With Beaker and Jupyter I feel like I am always stuck in "throw away code" mode, and there's a high friction to move code between the two paradigms. 2) The plot display seems to work a lot better. With both Beaker and jupyter I find the inline plots are too static - always the wrong size or the wrong shape, etc. In RStudio I can drag and resize that window independently. I feel bad because I'm not telling you solutions and I don't really have any - but these are the things I love about RStudio. Of course, the downside of RStudio is ... R.