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Advanced computing with IPython

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Re: Advanced computing with IPython

#11

Post by chrxr »

chrxr wrote: post #10

At Harvard we've built out an infrastructure to allow us to deploy JupyterHub to courses with authentication managed by Canvas. It has allowed us to easily deploy complex set-ups to students so they can do really cool stuff without having to spend hours walking them through setup. Instructors are writing their lectures as IPython notebooks, and distributing them to students, who then work through them in their Jupyte…

It is worth noting that there is an argument that it is a worthwhile task for students to learn how to setup complex computing environments, as it better prepares them for the real world. However, in reality, there just isn't time within a single semester to do this for a class of 100+ students. So implementations such as this one trade-off that learning for a greater focus on computational theory and its implementations.

Re: Advanced computing with IPython

#12

Post by Asooka »

Waterluvian wrote: post #7
leephillips wrote: post #5

Earlier quoted context omitted.

Yup, whenever I write one of these I need to spend some time on terminology. It's even more confusing now with Jupyter, as there is still much overlap between that and IPython.

Yep. I honestly thought Jupyter is just a rename of IPython until you said that. Now I have to go learn the difference.

Summary: Jupyter is the evolution of IPython. IPython is deprecated.

Re: Advanced computing with IPython

#13

Post by da_chicken »

chrxr wrote: post #10

At Harvard we've built out an infrastructure to allow us to deploy JupyterHub to courses with authentication managed by Canvas. It has allowed us to easily deploy complex set-ups to students so they can do really cool stuff without having to spend hours walking them through setup. Instructors are writing their lectures as IPython notebooks, and distributing them to students, who then work through them in their Jupyte…

I'm torn. On the one hand that's really cool to get everything configured and up and running so students can get to the interesting parts. On the other hand, learning how to configure your own environment is kind of an essential part of working with any tool that forces you to understand at least some of the structure involved.

Re: Advanced computing with IPython

#14

Post by chrxr »

da_chicken wrote: post #13
chrxr wrote: post #10

At Harvard we've built out an infrastructure to allow us to deploy JupyterHub to courses with authentication managed by Canvas. It has allowed us to easily deploy complex set-ups to students so they can do really cool stuff without having to spend hours walking them through setup. Instructors are writing their lectures as IPython notebooks, and distributing them to students, who then work through them in their Jupyte…

I'm torn. On the one hand that's really cool to get everything configured and up and running so students can get to the interesting parts. On the other hand, learning how to configure your own environment is kind of an essential part of working with any tool that forces you to understand at least some of the structure involved.

That is a fair point. Please see my reply to my post.

Re: Advanced computing with IPython

#15

Post by uasnew »

chrxr wrote: post #10

At Harvard we've built out an infrastructure to allow us to deploy JupyterHub to courses with authentication managed by Canvas. It has allowed us to easily deploy complex set-ups to students so they can do really cool stuff without having to spend hours walking them through setup. Instructors are writing their lectures as IPython notebooks, and distributing them to students, who then work through them in their Jupyte…

Is this something that is open source so that other schools could use it?

Re: Advanced computing with IPython

#16

Post by chrxr »

uasnew wrote: post #15
chrxr wrote: post #10

At Harvard we've built out an infrastructure to allow us to deploy JupyterHub to courses with authentication managed by Canvas. It has allowed us to easily deploy complex set-ups to students so they can do really cool stuff without having to spend hours walking them through setup. Instructors are writing their lectures as IPython notebooks, and distributing them to students, who then work through them in their Jupyte…

Is this something that is open source so that other schools could use it?

Most of the implementation is open source. Authentication module is separate as it's part of our Canvas app work, but it will likely be open sourced soon. We've also done implementations which authenticate via GitHub...

https://github.com/harvard/cloudJHub

Re: Advanced computing with IPython

#17

Post by bunderbunder »

mlthoughts2018 wrote: post #6

If interested, I spent some time on a comment thread a few days ago describing how my experience leads me to believe the Notebook environment (not all of Jupyter / IPython, just the Notebook part) is actually only appropriate for a tiny subset of pedagogical or throw-away situations, and should be avoided most of the time and avoided in most of the cases it’s marketed for (especially anything having to do with ‘repro…

You're not wrong, though I think the value of pedagogical and throw-away situations in your work may not be a universal experience.

For me, at least, pedagogic and throw-away situations aren't a tiny subset. They're most of what I do. It's exploratory work, figuring out how the data behaves, if the data behaves, where it needs to be cleaned, churning through great heaps of experiments and iterations before hitting on the ultimate plan, and putting together a presentation to help explain what I finally settled on to colleagues and stakeholders.

Only after sinking a whole lot of sweat into that process do I go on to start building anything that we intend to keep. At which point, forget Jupyter notebooks, I'm typically not even working in Python anymore for that part of the job.

Re: Advanced computing with IPython

#18

Post by wenc »

Waterluvian wrote: post #7
leephillips wrote: post #5

Earlier quoted context omitted.

Yup, whenever I write one of these I need to spend some time on terminology. It's even more confusing now with Jupyter, as there is still much overlap between that and IPython.

Yep. I honestly thought Jupyter is just a rename of IPython until you said that. Now I have to go learn the difference.

Also Jupyter Notebook (pure notebook interface) is evolving into Jupyter Lab (a notebook-oriented IDE). The latter is much more IDE-like than the former, though the former is still really good.

Technology evolves...

Re: Advanced computing with IPython

#19

Post by detaro »

Asooka wrote: post #12
Waterluvian wrote: post #7

Earlier quoted context omitted.

Yep. I honestly thought Jupyter is just a rename of IPython until you said that. Now I have to go learn the difference.

Summary: Jupyter is the evolution of IPython. IPython is deprecated.

Jupyter is the language-agnostic parts of IPython (UI, notebook format, protocols to talk to notebooks, ...) extracted out to be used with many languages.

IPython remains as the project maintaining the Python-specific parts of that stack. It's not deprecated, but has been limited in scope.

Re: Advanced computing with IPython

#20

Post by giu »

The linked slides "Python in HPC" [0] are quite awesome, from which I learned about mpi4py's [1] existance. Definitely going to give it a try in the future; using the MPI API with an "easy-to-follow" syntax should be fun.

[0] https://hpc.nih.gov/training/handouts/171121_python_in_hpc.p...

[1] http://mpi4py.scipy.org/docs/

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