5 ms·

When would someone use jupyterhub? I've been running my own notebook server for years, but it's single-user, single machine. Is hub for like providing separate

When would someone use jupyterhub? I've been running my own notebook server for years, but it's single-user, single machine. Is hub for like providing separate jupyterlab instances for a bunch of different users/different machines?

deleted 7y ago
[deleted]
rhizome31 7y ago
Yes exactly. At my work when a new scientist joins us we just create an account and she can get started on her research within minutes. Each user gets a contained environment in which we mount a disk of shared data.
- erikgaas 7y ago
  I just did this in my University lab as well. Most people aren't savvy with Linux, so having normal accounts with Jupyter port forwarding is out of the question. JupyterHub is just about the lowest friction I can possibly make it for introducing the Python data science stack to non data scientists.
  - rhizome31 7y ago
    And just to be explicit for readers, Jupyter and JupyterHub also allow to work with other data science stacks, R in particular.
  - amrrs 7y ago
    IMO, Jupyter Notebook is the closest equivalent to Python as what Rstudio is for R. While Pycharm and VSCode are also preferred by some Py-based Data scientists, Jupyterhub offers almost everything that a typical IDE would do along with the traditional Notebook environment which a lot of beginners these days start with. Thus much less friction while getting started.
    - prakhar987 7y ago
      I would be really hesitant to comapre Jupyter Notebook to an IDE.....an example is a debugger...the only visual debugger that i have come across for jupyter is pixie debugger, which is miles behind the debugger of an IDE like Pycharm.... there is a huge list of features that jupyter needs before you can compare it to an IDE
      - d0mine 7y ago
        It is an interactive environment (not much use for a debugger).
        erikgaas 7y ago
        FWIW I use the %debug magic command in Jupyter and it has been a great experience. I'm pretty ignorant of the enterprise debugging tools so take that with a grain of salt.
        y4mi 7y ago
        Debuggers are only really useful if you're trying to figure out why some object in your server doesn't do what you want it to. I'd wager that almost no data scientists write object oriented code.. it's probably mostly done one calculation at a time. executed in the notebooks repl. So the value you get from ide debuggers is tiny, as you're already doing everything one step at a time.
        bonoboTP 7y ago
        You still write functions and may want to inspect variable state in the middle of function execution.
        applecrazy 7y ago
        Correct. RStudio has this feature, where variable values can be inspected in a sidebar. This would be a really useful feature for Jupyter, especially when running a Python kernel.
- deleted 7y ago
  [deleted]
- Fomite 7y ago
  This was my use case for it. I ended up getting really frustrated with setting it up. Followed several different tutorials, had it blow up in a different way each time. Going to have to revisit this to see if the documentation has gotten better.
jabl 7y ago
We have it setup at work, as an alternative way to use our HPC resource compared to the traditional Linux shell + slurm usage. User goes with the web browser to our jupyterhub URL, logs in with our usual credentials, selects a job type (amount of memory and max duration), and jupyterhub takes care of launching a jupyter kernel as a slurm batch job on a compute node in the cluster, and proxies http I/O via the jupyterhub node to the user web browser. In the jupyter notebook, users have access to the same cluster filesystems as if she would login traditionally via ssh.
- sliken 7y ago
  I'd like to setup exactly this, any more details on your setup available?
  - jabl 7y ago
    None publicly available AFAIK. There were some fixes required to the slurmspawner, but those should all be upstream now. Then there's the PITA of integration with the site auth system, but that tends to be site specific..
jjtheblunt 7y ago
it's to share work with others, i believe. nothing more really.
beojan 7y ago
I use JupyterHub on my laptop because it makes the process of starting a server automatically a lot easier.
bhl 7y ago
My school uses this for its data science classes so let me provide an example. Say that you have a lab or homework assignment done in Python. It may require a lot of storage (a large dataset), compute (maybe you have a large model), or dependencies. JupyterHub is one way to setup once and then deploy to multiple users regardless of their computer.
TallGuyShort 7y ago
I give talks in math classes about how math is used in the real world, and I've been looking at JupyterHub as a way to give everyone in the class a way to work through an activity with instructions & equations, diagrams, places to enter their own data, and run a little mathematical program, etc.

deleted 7y ago

[deleted]

rhizome31 7y ago

Yes exactly. At my work when a new scientist joins us we just create an account and she can get started on her research within minutes. Each user gets a contained environment in which we mount a disk of shared data.

erikgaas 7y ago
I just did this in my University lab as well. Most people aren't savvy with Linux, so having normal accounts with Jupyter port forwarding is out of the question. JupyterHub is just about the lowest friction I can possibly make it for introducing the Python data science stack to non data scientists.
- rhizome31 7y ago
  And just to be explicit for readers, Jupyter and JupyterHub also allow to work with other data science stacks, R in particular.
- amrrs 7y ago
  IMO, Jupyter Notebook is the closest equivalent to Python as what Rstudio is for R. While Pycharm and VSCode are also preferred by some Py-based Data scientists, Jupyterhub offers almost everything that a typical IDE would do along with the traditional Notebook environment which a lot of beginners these days start with. Thus much less friction while getting started.
  - prakhar987 7y ago
    I would be really hesitant to comapre Jupyter Notebook to an IDE.....an example is a debugger...the only visual debugger that i have come across for jupyter is pixie debugger, which is miles behind the debugger of an IDE like Pycharm.... there is a huge list of features that jupyter needs before you can compare it to an IDE
    - d0mine 7y ago
      It is an interactive environment (not much use for a debugger).
      - erikgaas 7y ago
        FWIW I use the %debug magic command in Jupyter and it has been a great experience. I'm pretty ignorant of the enterprise debugging tools so take that with a grain of salt.
        y4mi 7y ago
        Debuggers are only really useful if you're trying to figure out why some object in your server doesn't do what you want it to. I'd wager that almost no data scientists write object oriented code.. it's probably mostly done one calculation at a time. executed in the notebooks repl. So the value you get from ide debuggers is tiny, as you're already doing everything one step at a time.
        bonoboTP 7y ago
        You still write functions and may want to inspect variable state in the middle of function execution.
        applecrazy 7y ago
        Correct. RStudio has this feature, where variable values can be inspected in a sidebar. This would be a really useful feature for Jupyter, especially when running a Python kernel.
deleted 7y ago
[deleted]
Fomite 7y ago
This was my use case for it. I ended up getting really frustrated with setting it up. Followed several different tutorials, had it blow up in a different way each time. Going to have to revisit this to see if the documentation has gotten better.

jabl 7y ago

We have it setup at work, as an alternative way to use our HPC resource compared to the traditional Linux shell + slurm usage. User goes with the web browser to our jupyterhub URL, logs in with our usual credentials, selects a job type (amount of memory and max duration), and jupyterhub takes care of launching a jupyter kernel as a slurm batch job on a compute node in the cluster, and proxies http I/O via the jupyterhub node to the user web browser. In the jupyter notebook, users have access to the same cluster filesystems as if she would login traditionally via ssh.

sliken 7y ago
I'd like to setup exactly this, any more details on your setup available?
- jabl 7y ago
  None publicly available AFAIK. There were some fixes required to the slurmspawner, but those should all be upstream now. Then there's the PITA of integration with the site auth system, but that tends to be site specific..

jjtheblunt 7y ago

it's to share work with others, i believe. nothing more really.

beojan 7y ago

I use JupyterHub on my laptop because it makes the process of starting a server automatically a lot easier.

bhl 7y ago

My school uses this for its data science classes so let me provide an example. Say that you have a lab or homework assignment done in Python. It may require a lot of storage (a large dataset), compute (maybe you have a large model), or dependencies. JupyterHub is one way to setup once and then deploy to multiple users regardless of their computer.

TallGuyShort 7y ago

I give talks in math classes about how math is used in the real world, and I've been looking at JupyterHub as a way to give everyone in the class a way to work through an activity with instructions & equations, diagrams, places to enter their own data, and run a little mathematical program, etc.