5 HN users recommended this talk6 months2014–2018score 6.5
Years with an HN recommendation, 2007–2026
Repeatedly recommended as the canonical demo of org-mode for literate programming and reproducible research.
John Kitchin shows how Emacs org-mode with Python lets researchers combine narrative, math, figures and executable code in one document. It exports to LaTeX, HTML and PDF, and he used it for papers and e-books.
“on Emacs + org-mode + python in reproducible research is worth a watch” (HN, 2015)
A lot of people are starting to use org-mode for that kind of thing. Fully reproducible research in a single file. To check the work, just export the file to pdf/html/etc., or "C-c C-c" the code blocks as you read through in org-mode. It's fantastic. For python specifically, this video is a must watch: [this video]
Must-watch on reproducible research with org-mode and Python.
The Orgmode extension to Emacs has quite an elegant, flexible, and powerful way of doing what you want. Can be hard to wrap your mind around at the beginning but has good payoff once you're up to speed. Here's a video showing how one guy uses it with Python (though it integrates with multitude of languages, including R): [this video] Here's paper (itself from LaTeX generated by Orgmode) describing use of Orgmode for this kind of "reproducible research": [link]
Demonstrates using org-mode with Python for reproducible research.
I know it gets said a lot, but have you considered emacs and org-mode. Because, it goes a very long way for this. See this great talk showing its use with python. [this video]
Do check out org-mode, then. It is surprising how far that tool has been extended. Many of these features are actually under the label "reproducible research" nowdays. There was a really good talk given on this at a pypy convention a couple of years ago.[1] [1] [this video]
Talk on org-mode for reproducible research and literate programming.
Seriously, try emacs. You want to see what color you have put in a css field?[1] Want to see the image you are referencing in a repl?[2] More amazingly, want to combine TeX, lisp, a markdown like language, and python/whatever in a single document? Try org-mode.[3][4] [1] [link] [2] [link] [3] [link] [4] [this video]
Shows combining TeX, lisp, markdown and python in one document.
This SciPy presentation (Kitchin, John Carnegie Mellon University) on Emacs + org-mode + python in reproducible research is worth a watch: [this video]
Kitchin's SciPy presentation on emacs, org-mode and python research.
I Agree with all those points. I've used org mode for a few things, but not for python notebooks. I remember seeing a great video a few years back on using python in org mode to make a research notebook. It really made me want to try org mode for literate / notebook style programming. I think it was this one: [this video] It sounds like org mode does not store images inline, since you don't like the b64 images in Jupyter? I imagine that could go both ways depending on what you want. Even for diffing, you might like to see that the image changed (though I generally agree that diffing images is not ideal). If you have to package images separately when sharing, then wouldn't inline images score a point for easier sharing? > use other languages that python Agreed, and that is powerful, but this also goes to my point. Jupyter is made for python and org mode isn't. Jupyter comes with python and libraries, where with Emacs you're on your own to figure out how to install and use different languages, and setup your environment so Emacs can see them. You're on your own to bring in images and plots, where Jupyter already understands commands that output images. > Plus, you get to use a proper text editor instead of editing on a browser textarea. Yes, but the editor is Emacs. :) For a lot of people the browser textarea is a bonus because it's the same thing you use everywhere. It's uncomplicated and non-technical and utterly consistent, even if lacking any power.
Great video on using python in org-mode as a research notebook.
If you use emacs org-mode, check out org-drill [link] . It uses the same algorithms, allows you to tweak everything, and you can keep your flashcards alongside the relevant notes/code/files/issues/ToDos/bookmarks/contacts/feeds/calendar-entry/emails/thesis/spreadsheets/journals/diagrams/pictures/evernotes/etc. [this video] , rather than in a totally separate program.
Org-mode workflow keeping notes and flashcards together.
I hate to be one of those that harps on "why the downvotes," but I really would appreciate tips on how folks would plan on testing these claims. Just imagining that we could do better than some good pieces of software doesn't really do much to say that we can. For example, people have been imagining faster than light travel for a long time. I realize these don't compare directly, as we have reasons to believe upper bounds on speed. So, I am curious if we have reasons to believe that the upper bounds on editors and such is really that much higher. For inspiration, consider [1]. Same for typesetting. Take a look at most of the papers at [2] and tell me whether translating these to new languages is really necessary. (Though, note that I am not arguing against this. Just asking how we plan to know that "things are better now.") [1] [this video] [2] [link]
Cited as inspiration for how powerful existing editors already are.
The workflow proposed in the first link looks quite interesting: Emacs + org-mode + python in reproducible research; SciPy 2013 [this video] And here are some more reviews, opinions, advices and experiences I just stumbled upon: [link] [link]
Interesting emacs, org-mode and python research workflow.
I like to use org mode for cleaning up my hard drives... a little script to pipe du into something that sums the files in a directory and adds asterisks, and viola, you have a UI for finding all the large and delete-able files & directories. I haven't used org mode for all the other cool things it can do, but I remember watching a great video about someone who uses it a lot like a Jupyter notebook. [this video]
Video list and Hacker News comment labels from HackerTube (prompted by @karpathy), released under ODC-By 1.0, built on the open-index/hacker-news archive. Hacker News data is provided by Y Combinator; comments remain the work of their authors. Video titles, channel names and thumbnails belong to their creators and are shown via YouTube. HackerTube Watch is an unofficial edition. Data export of 2026-10-31.
11 Hacker News comments
From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.
Read more
Citations, criticism and jokes
Read more