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The majority of the complaints I hear about notebooks I think come from a misunderstanding of what they're supposed to be. It's a mashup between a scientific pa

The majority of the complaints I hear about notebooks I think come from a misunderstanding of what they're supposed to be. It's a mashup between a scientific paper and a repl. So it's useful for a bit of both: a) Just like with a paper, you can present scientific or mathematical ideas with accompanying visualizations or simulations. From the REPL side, as a bonus, you get interactivity, and the reader can pause and experiment with the examples you're giving to improve their understanding or test their hypotheses. If I change this variable, how will the system react? You can just try it! b) Just like with a REPL, you can type in and execute commands step by step, viewing the output of the previous command instead of running the whole thing at once. From the document side, as a bonus, you get nicer presentation (charts, interactivity, nice and wide sortable tables, etc) than you would in a shell, which comes in handy when doing things like data exploration or mathematical simulation. It's decidedly NOT there for you to type all your code in like an editor and make a huge mess. It's apples and oranges w.r.t and a poor substitute for something like PyCharm or VS Code or vim. It is there for you to a) try things out yourself, and whatever you discover hopefully eventually make it into proper python modules b) make interesting ideas presentable and explorable for others. That's all! When I see stuff like "out of order execution is confusing", I don't disagree, but it does make me wonder how long and convoluted the notebooks these people work with are - probably a ripe candidate to refactor stuff out into python modules as functions. When I see stuff around notebooks for "reproducibility", I'm a bit confused in that notebooks often don't specify any guidance on installation and dependencies, let alone things like arguments and options that a regular old script would. In that regard I think it's barely an improvement over .py files lying around. When I hear "how do I import a notebook like a python module", I'm very very scared. Granted, I've seen huge notebooks that are a mess, so I understand the frustration, but it's not like we all haven't seen the single file of code with 5000 lines and 10 nested layers of conditionals at some point in our lives.

taeric 8y ago
You parting "Granted..." is precisely what fills me with dread when I see notebooks. Yes, I have seen poorly done source files. I made more than a few myself. However, many of the practices we have grown into as sound programming advice seem to be largely thrown out the window for these notebooks. The irony, to me, is that I actually typically argue for the mixing of presentation and content. But to me, notebooks look like an attempt by people to make a WYSIWYG out of JUnit/TestNG/whatever style reports. Only, without the repeatability. There is also the entire bend where these are taking off in a way that doesn't make sense. Do they do the things you are saying? Well, yeah. But no better than plenty of tools before them. Mathematica and Matlab both had "notebook" like features for a long long time. Complete with optimized libraries. And this is ignoring the interactivity of the old LISP machines. (You can see from my history I have a soft spot for emacs org-mode.) Jupyter is a lot of things. Bad isn't necessarily one of them, but exceptional isn't, either. Heavily marketed is.
- jacquesm 8y ago
  > However, many of the practices we have grown into as sound programming advice seem to be largely thrown out the window for these notebooks. The exact same thing happened with the arrival of the www.
- renjimen 8y ago
  > Mathematica and Matlab both had "notebook" like features for a long long time. They probably didn't take off to the same extent as Jupyter because they're not free. IIRC MATLAB was quite expensive, particularly if you wanted to do anything specialised.
  - 3rdAccount 8y ago
    Yes, both are expensive outside the student licenses, but Mathematica is significantly cheaper and has a lot more built into the language, so you don't have to turn around and buy expensive "toolboxes" for all the functionality missing in Matlab. Notebooks have been in Mathematica for ages and are really powerful and difficult to describe to those who haven't used them. To give an example, I was building a tool and embedded images as variables in a way reminiscent of being an engineer on the USS Enterprise. You can point to a file in Python as a variable, but you can't just copy-paste an image in as a variable last I checked (don't think Jupyter is there yet).
- ubernostrum 8y ago
  There is also the entire bend where these are taking off in a way that doesn't make sense. It makes perfect sense. Just not to a lot of HN readers. The average HN reader is approaching this from a perspective of "I am a professional programmer who might occasionally dabble in scientific computing, and therefore I hate this thing because it's not a professional programmer's tool designed by and for professional programmers according to the best practices of professional programmers". The people who are actually using notebooks, meanwhile, are not professional programmers. They're scientists who increasingly have to do programming as part of their science. And notebooks are a godsend for them. We don't need to drag them all the way into our world; we need to pay attention to what they actually want, need, and find useful, and accept that it's going to differ from what we want, need, and find useful.
klmr 8y ago
I fundamentally agree with you but I have the feeling that some some of the major proponents of notebooks belong to the category of people who misunderstand them, and simply use them for everything, and write long and convoluted notebooks; I’ve definitely seen my share of those in my domain (bioinformatics, AI) and elsewhere. By contrast, Joel Grus for instance perfectly understands their strengths and weaknesses. As for being a a good REPL, I feel that an actual REPL (+ editor integration) works better than notebooks: You can combine a literate document with a REPL but still get the benefits of a proper editor/IDE and a proper execution environment, rather than a half-hearted mix of both that’s hosted inside a HTML contenteditable (= Jupyter), and you also get “charts, interactivity, nice and wide sortable tables, etc” if you want). RMarkdown inside RStudio or Nvim-R does this well. — I just don’t want to give up the advantages of a proper editor for the very slight increase in integration that Jupyter gives me.
jrumbut 8y ago
I think it speaks to people's desire for a quick and easy to set up basic GUI creator with an editor that allows inline code editing, and no need to deal explicitly with the client server interaction. I myself, as someone who likes to create really solid and maintainable tools, have fallen into the notebook trap and written things like "change the month in cell 22 then execute cells 1 through 3 and 20 through 27 to update the report". The notebook format was great for prototyping what was really a small app. You don't really have those problems when you're just generating a document.
- Immortalin 8y ago
  Yes. It's called Microsoft Excel. Software engineers don't like VB for the same reason they don't like Python-in-a-notebook but you cannot deny its effectiveness.
  - jrumbut 8y ago
    You're right about what excel is (and the whole VB ecosystem for that matter), but I think the critical difference is that the language and environment are very different. If I know the smallest amount of python (or R) I can leverage Jupyter notebooks and it is intuitive. To really get something great out of excel you have to learn excel. I think that difference is almost as important as the excel stigma.
    - taeric 8y ago
      Interestingly, excel has the advantage that the data has to always be visible. This is also a disadvantage, because it can't work with too much data. My gut is that the amount of data it can work with more than compensates for the disadvantage.
jonnycomputer 8y ago
If you ever have used an R Notebook written in R-Markdown, then its pretty easy to see why Jupyter Notebooks putting everything in JSON is just... infuriatingly wrong-headed. In an R Notebook, I can see my code, I can see my text, everything is exceedingly simple to understand, and I can edit it in any of the fantastic text editors out there (Jupyter's editor is not among them)
- optimuspaul 8y ago
  YES! R Notebook is so much better in my opinion than Jupyter. I definitely prefer to work with a simple format verses JSON for this kind of work.
  - narwally 8y ago
    Agreed, but I'm coming from the org-mode side of things. Have you ever tried git diff on a JSON file? It's not always pretty.
- celrod 8y ago
  RStudio is also my favorite editor. All my work is data science / stats related, where I like the workflow of writing/modifying code in a .R (or .py) file, and being able to quickly experiment by running chunks in a REPL with Ctrl + Enter. R and Python are supported. No Julia, unfortunately. VS Code and Atom support similar workflows with Julia. However, the Julia Language server in VS Code is extremely unstable and I regularly lose LaTeX completions. The REPL in Atom is mind boggling laggy and slow to the point that it is much less frustrating to copy and paste code into a REPL running in your favorite terminal emulator.
  - mlevental 8y ago
    r studio supports python? does it completion and stuff like that?
    - celrod 8y ago
      It uses reticulate for REPL support, and has basic Python completions and snippets. However, it doesn't seem to complete variable names. Eg, if I defined "foobar", it won't let me tab-complete that later when I start typing "foo".
achompas 8y ago
I agree completely on your first point - notebooks are a poor substitute for proper software tooling. I wrote this recently [1] > In the case of an analyst, the domain of "software engineering" lies close to their own domain. Projects in both areas require code which (ideally) exhibits clarity and reproducibility. Obfuscated software is bad [...] and idempotency is good. > The problem, then, is when the analyst takes a core tool from their domain and applies it to a slightly different domain like software engineering. Things go south fast: your notebook has not-quite-imperative code that is untested and unmonitored. It is, in other words, bad software. As for the point about "refactoring stuff out into python modules as functions," the problem is that the new crop of data scientists aren't learning how to do this. The role of "machine learning engineer" is emerging to address this shortcoming in SWE skill throughout the data science community. It honestly cannot happen quickly enough. [1] https://buttondown.email/oneshotlearning/archive/c06a0ded-746d-4783-a5e9-db68003eab0c https://buttondown.email/oneshotlearning/archive/c06a0ded-74...
neuromantik8086 8y ago
> When I see stuff around notebooks for "reproducibility", I'm a bit confused in that notebooks often don't specify any guidance on installation and dependencies, let alone things like arguments and options that a regular old script would. At the core of this, as some others may have already alluded to already, is that many academic scientists have not been socialized to make a distinction between development and production environments. Jupyter notebooks are clearly beneficial for sandboxing and trying out analyses creatively (with many wrong turns) before running "production" analyses, which ideally should be the ones that are reproducible. For many scientific papers, the analysis stops at "I was messing around in SPSS and MATLAB at 3 AM and got this result" without much consideration for reformulating what the researcher did and rewriting code/scripts so that they can be re-run consistently.
- cbkeller 8y ago
  > many academic scientists have not been socialized to make a distinction between development and production environments Geologist here - definitely true in my field. Nonetheless, while I don't develop in notebooks at all, I do use them for "reproducibility" in a sense -- by putting a bit of dependency info in a github repo along with a .ipynb file, I can do things like this: https://mybinder.org/v2/gh/brenhinkeller/Chron.jl/master?filepath=examples%2Fdemo.ipynb https://mybinder.org/v2/gh/brenhinkeller/Chron.jl/master?fil... Which ends up being useful when a lot of folks in my field don't do any computational work at all, so being able to just click on a link and have something work in browser is a big help.
  - Insanity 8y ago
    Don't know if it is something you actively need, but the image did not load for me. (Even after re-evaluating the cell). The image after: "For example (KJ04-70)" (I also re-ran the preceding cells).
    - cbkeller 8y ago
      Thanks for the tip! Interestingly enough, this appears to be browser-dependent. Apparently including a pdf in notebook markdown using an img tag like <img src="DenverUPbExampleData/KJ04-70_distribution.pdf" align="left"/> works in Safari but not Chrome or Firefox. Switched to SVGs for now. So much for reproducibility :/
analog31 8y ago
I work in development of scientific equipment. Jupyter is my lab notebook. I think that to make good use of Jupyter for this purpose, you have to be a good programmer and a good scientist. No tool will turn us into these things against our will. With that said, Jupyter has greatly improved my ability to find my own mistakes, and to reproduce my own results later on.
j2kun 8y ago
My complaint is that people use notebooks as production systems.
- brootstrap 8y ago
  I think we can all agree some notebooks are shit storms and should not be relied upon at ALL for production. AT my job we started using notebooks as an 'in-repo', 'interactive' documentation of sorts. Showcase various modules and give simple usage examples of them. It was pretty awesome. I love using notebooks as a more advanced scratch pad. For the times when ipython shell isnt enough, and you want something extra. Also i had to install the vim bindings ASAP, gotta have that vim
narwally 8y ago
I'd say it's more of a shell than a REPL. For most languages that provide a shell, there isn't a real separation between the reader, evaluator, and the printer. Being able to interact with those components separately is the real advantage of a REPL over a shell.
qwerty456127 8y ago
Is it actually a common skill to write meaningful non-helloworldish Python code that yields expected results without a number of iterations of debugging and correcting and without PyCharm intelligent completion, hinting and correcting features? I understand the value of Jupyter notebooks for publishing your work results but find it almost impossible to use it to actually do the work - it feels million times more convenient to code in PyCharm then copy-paste the code to Jupyter once it's ready.
gaius 8y ago
The majority of the complaints I hear about notebooks I think come from a misunderstanding of what they're supposed to be No, the majority of complaints are that notebooks are great, but Jupyter is a bad notebook. I mean maybe it’s impressive to someone who’s never seen a notebook before but to someone used to Mathematica, MathCAD, RMarkdown, org-mode, whatever, it just seems clunky as hell. I wonder how many “data scientists” claiming it as their top choice have ever tried anything else?

taeric 8y ago

You parting "Granted..." is precisely what fills me with dread when I see notebooks. Yes, I have seen poorly done source files. I made more than a few myself. However, many of the practices we have grown into as sound programming advice seem to be largely thrown out the window for these notebooks. The irony, to me, is that I actually typically argue for the mixing of presentation and content. But to me, notebooks look like an attempt by people to make a WYSIWYG out of JUnit/TestNG/whatever style reports. Only, without the repeatability. There is also the entire bend where these are taking off in a way that doesn't make sense. Do they do the things you are saying? Well, yeah. But no better than plenty of tools before them. Mathematica and Matlab both had "notebook" like features for a long long time. Complete with optimized libraries. And this is ignoring the interactivity of the old LISP machines. (You can see from my history I have a soft spot for emacs org-mode.) Jupyter is a lot of things. Bad isn't necessarily one of them, but exceptional isn't, either. Heavily marketed is.

jacquesm 8y ago
> However, many of the practices we have grown into as sound programming advice seem to be largely thrown out the window for these notebooks. The exact same thing happened with the arrival of the www.
renjimen 8y ago
> Mathematica and Matlab both had "notebook" like features for a long long time. They probably didn't take off to the same extent as Jupyter because they're not free. IIRC MATLAB was quite expensive, particularly if you wanted to do anything specialised.
- 3rdAccount 8y ago
  Yes, both are expensive outside the student licenses, but Mathematica is significantly cheaper and has a lot more built into the language, so you don't have to turn around and buy expensive "toolboxes" for all the functionality missing in Matlab. Notebooks have been in Mathematica for ages and are really powerful and difficult to describe to those who haven't used them. To give an example, I was building a tool and embedded images as variables in a way reminiscent of being an engineer on the USS Enterprise. You can point to a file in Python as a variable, but you can't just copy-paste an image in as a variable last I checked (don't think Jupyter is there yet).
ubernostrum 8y ago
There is also the entire bend where these are taking off in a way that doesn't make sense. It makes perfect sense. Just not to a lot of HN readers. The average HN reader is approaching this from a perspective of "I am a professional programmer who might occasionally dabble in scientific computing, and therefore I hate this thing because it's not a professional programmer's tool designed by and for professional programmers according to the best practices of professional programmers". The people who are actually using notebooks, meanwhile, are not professional programmers. They're scientists who increasingly have to do programming as part of their science. And notebooks are a godsend for them. We don't need to drag them all the way into our world; we need to pay attention to what they actually want, need, and find useful, and accept that it's going to differ from what we want, need, and find useful.

klmr 8y ago

I fundamentally agree with you but I have the feeling that some some of the major proponents of notebooks belong to the category of people who misunderstand them, and simply use them for everything, and write long and convoluted notebooks; I’ve definitely seen my share of those in my domain (bioinformatics, AI) and elsewhere. By contrast, Joel Grus for instance perfectly understands their strengths and weaknesses. As for being a a good REPL, I feel that an actual REPL (+ editor integration) works better than notebooks: You can combine a literate document with a REPL but still get the benefits of a proper editor/IDE and a proper execution environment, rather than a half-hearted mix of both that’s hosted inside a HTML contenteditable (= Jupyter), and you also get “charts, interactivity, nice and wide sortable tables, etc” if you want). RMarkdown inside RStudio or Nvim-R does this well. — I just don’t want to give up the advantages of a proper editor for the very slight increase in integration that Jupyter gives me.

jrumbut 8y ago

I think it speaks to people's desire for a quick and easy to set up basic GUI creator with an editor that allows inline code editing, and no need to deal explicitly with the client server interaction. I myself, as someone who likes to create really solid and maintainable tools, have fallen into the notebook trap and written things like "change the month in cell 22 then execute cells 1 through 3 and 20 through 27 to update the report". The notebook format was great for prototyping what was really a small app. You don't really have those problems when you're just generating a document.

Immortalin 8y ago
Yes. It's called Microsoft Excel. Software engineers don't like VB for the same reason they don't like Python-in-a-notebook but you cannot deny its effectiveness.
- jrumbut 8y ago
  You're right about what excel is (and the whole VB ecosystem for that matter), but I think the critical difference is that the language and environment are very different. If I know the smallest amount of python (or R) I can leverage Jupyter notebooks and it is intuitive. To really get something great out of excel you have to learn excel. I think that difference is almost as important as the excel stigma.
  - taeric 8y ago
    Interestingly, excel has the advantage that the data has to always be visible. This is also a disadvantage, because it can't work with too much data. My gut is that the amount of data it can work with more than compensates for the disadvantage.

jonnycomputer 8y ago

If you ever have used an R Notebook written in R-Markdown, then its pretty easy to see why Jupyter Notebooks putting everything in JSON is just... infuriatingly wrong-headed. In an R Notebook, I can see my code, I can see my text, everything is exceedingly simple to understand, and I can edit it in any of the fantastic text editors out there (Jupyter's editor is not among them)

optimuspaul 8y ago
YES! R Notebook is so much better in my opinion than Jupyter. I definitely prefer to work with a simple format verses JSON for this kind of work.
- narwally 8y ago
  Agreed, but I'm coming from the org-mode side of things. Have you ever tried git diff on a JSON file? It's not always pretty.
celrod 8y ago
RStudio is also my favorite editor. All my work is data science / stats related, where I like the workflow of writing/modifying code in a .R (or .py) file, and being able to quickly experiment by running chunks in a REPL with Ctrl + Enter. R and Python are supported. No Julia, unfortunately. VS Code and Atom support similar workflows with Julia. However, the Julia Language server in VS Code is extremely unstable and I regularly lose LaTeX completions. The REPL in Atom is mind boggling laggy and slow to the point that it is much less frustrating to copy and paste code into a REPL running in your favorite terminal emulator.
- mlevental 8y ago
  r studio supports python? does it completion and stuff like that?
  - celrod 8y ago
    It uses reticulate for REPL support, and has basic Python completions and snippets. However, it doesn't seem to complete variable names. Eg, if I defined "foobar", it won't let me tab-complete that later when I start typing "foo".

achompas 8y ago

I agree completely on your first point - notebooks are a poor substitute for proper software tooling. I wrote this recently [1] > In the case of an analyst, the domain of "software engineering" lies close to their own domain. Projects in both areas require code which (ideally) exhibits clarity and reproducibility. Obfuscated software is bad [...] and idempotency is good. > The problem, then, is when the analyst takes a core tool from their domain and applies it to a slightly different domain like software engineering. Things go south fast: your notebook has not-quite-imperative code that is untested and unmonitored. It is, in other words, bad software. As for the point about "refactoring stuff out into python modules as functions," the problem is that the new crop of data scientists aren't learning how to do this. The role of "machine learning engineer" is emerging to address this shortcoming in SWE skill throughout the data science community. It honestly cannot happen quickly enough. [1] https://buttondown.email/oneshotlearning/archive/c06a0ded-746d-4783-a5e9-db68003eab0c https://buttondown.email/oneshotlearning/archive/c06a0ded-74...

neuromantik8086 8y ago

> When I see stuff around notebooks for "reproducibility", I'm a bit confused in that notebooks often don't specify any guidance on installation and dependencies, let alone things like arguments and options that a regular old script would. At the core of this, as some others may have already alluded to already, is that many academic scientists have not been socialized to make a distinction between development and production environments. Jupyter notebooks are clearly beneficial for sandboxing and trying out analyses creatively (with many wrong turns) before running "production" analyses, which ideally should be the ones that are reproducible. For many scientific papers, the analysis stops at "I was messing around in SPSS and MATLAB at 3 AM and got this result" without much consideration for reformulating what the researcher did and rewriting code/scripts so that they can be re-run consistently.

cbkeller 8y ago
> many academic scientists have not been socialized to make a distinction between development and production environments Geologist here - definitely true in my field. Nonetheless, while I don't develop in notebooks at all, I do use them for "reproducibility" in a sense -- by putting a bit of dependency info in a github repo along with a .ipynb file, I can do things like this: https://mybinder.org/v2/gh/brenhinkeller/Chron.jl/master?filepath=examples%2Fdemo.ipynb https://mybinder.org/v2/gh/brenhinkeller/Chron.jl/master?fil... Which ends up being useful when a lot of folks in my field don't do any computational work at all, so being able to just click on a link and have something work in browser is a big help.
- Insanity 8y ago
  Don't know if it is something you actively need, but the image did not load for me. (Even after re-evaluating the cell). The image after: "For example (KJ04-70)" (I also re-ran the preceding cells).
  - cbkeller 8y ago
    Thanks for the tip! Interestingly enough, this appears to be browser-dependent. Apparently including a pdf in notebook markdown using an img tag like <img src="DenverUPbExampleData/KJ04-70_distribution.pdf" align="left"/> works in Safari but not Chrome or Firefox. Switched to SVGs for now. So much for reproducibility :/

analog31 8y ago

I work in development of scientific equipment. Jupyter is my lab notebook. I think that to make good use of Jupyter for this purpose, you have to be a good programmer and a good scientist. No tool will turn us into these things against our will. With that said, Jupyter has greatly improved my ability to find my own mistakes, and to reproduce my own results later on.

j2kun 8y ago

My complaint is that people use notebooks as production systems.

brootstrap 8y ago
I think we can all agree some notebooks are shit storms and should not be relied upon at ALL for production. AT my job we started using notebooks as an 'in-repo', 'interactive' documentation of sorts. Showcase various modules and give simple usage examples of them. It was pretty awesome. I love using notebooks as a more advanced scratch pad. For the times when ipython shell isnt enough, and you want something extra. Also i had to install the vim bindings ASAP, gotta have that vim

narwally 8y ago

I'd say it's more of a shell than a REPL. For most languages that provide a shell, there isn't a real separation between the reader, evaluator, and the printer. Being able to interact with those components separately is the real advantage of a REPL over a shell.

qwerty456127 8y ago

Is it actually a common skill to write meaningful non-helloworldish Python code that yields expected results without a number of iterations of debugging and correcting and without PyCharm intelligent completion, hinting and correcting features? I understand the value of Jupyter notebooks for publishing your work results but find it almost impossible to use it to actually do the work - it feels million times more convenient to code in PyCharm then copy-paste the code to Jupyter once it's ready.

gaius 8y ago

The majority of the complaints I hear about notebooks I think come from a misunderstanding of what they're supposed to be No, the majority of complaints are that notebooks are great, but Jupyter is a bad notebook. I mean maybe it’s impressive to someone who’s never seen a notebook before but to someone used to Mathematica, MathCAD, RMarkdown, org-mode, whatever, it just seems clunky as hell. I wonder how many “data scientists” claiming it as their top choice have ever tried anything else?