Earlier quoted context omitted.
That seems great, but for the comparison between DN viewer and the other, is there any benchmark tests specifically or it just a general feeling of speed when someone is using them. Because for each Jupyter notebook viewer it will depend on the setup, machine and the load itself.
Hi there! Simon (Engineer at Deepnote) here. We didn't benchmark the load speed but for some reason, Github's ipynb viewer has always felt to me quite slow and unreliable. All viewers are publicly accessible so I'd love it someone did an independent benchmark. I'd prefer to avoid doing one ourselves because of the obvious conflict of interest
Show HN: Render Jupyter notebooks as interactive articles
31–34 of 34 posts
Re: Show HN: Render Jupyter notebooks as interactive articles
#32Earlier quoted context omitted.
Hi there! Simon (Engineer at Deepnote) here. We didn't benchmark the load speed but for some reason, Github's ipynb viewer has always felt to me quite slow and unreliable. All viewers are publicly accessible so I'd love it someone did an independent benchmark. I'd prefer to avoid doing one ourselves because of the obvious conflict of interest
I thought that it is more than this. I think you should support any claim about that by creating a reproducible open benchmark test so at least people can understand what criteria you selected.
Re: Show HN: Render Jupyter notebooks as interactive articles
#33That's pretty neat and looks nice. I wonder how it compares to fastai's nbdev/nb2md? https://www.fast.ai/2020/01/20/nb2md/
FYI, the blog post you linked to is a bit out of date - we have something much better for blogging with jupyter notebooks nowadays, which is fastpages: https://fastpages.fast.ai/ . It's compatible with the same annotations used in nbdev.