Oh this would be such a good fit for my dream of serving federated backend code from web readable hosting https://webcode.run/. - Source: Hacker News / 10 months ago

This would be so amazing. In order to access most vanilla services like redis, postgres etc. You need to deploy a bridge https://github.com/zquestz/ws-tcp-proxy -- somewhat abandoned at this point but it is still running), and a big problem with the approach was the web's inability to make TCP connections. - Source: Hacker News / over 1 year ago

Yeah, you are right. I made https://webcode.run also for this reason (also hot code reload and debugging but for JavaScript computational notebooks). - Source: Hacker News / almost 2 years ago

This was why I created https://webcode.run the elimination of all tooling and a fast development loop even for backend. - Source: Hacker News / almost 2 years ago

I am building a compute layer for Observablehq which enables services to brought up using nothing other than a web browser. It's a bit too soon to call it a K8s replacement but the motivation was the complexity and laggyness of bringing up services on cloud or k8s. The WEB + on demand infrastructure is the distributed replacement of K8S https://webcode.run/ WEBCode is about eliminating environments and the... - Source: Hacker News / over 2 years ago

Example notebooks are included in the repo and can be previewed using nbviewer:. Source: over 1 year ago

Nbviewer (https://nbviewer.org/): very easy to use for smaller jupyter notebook that does not require heavy rendering. Source: over 1 year ago

Nbconvert renders everything exactly as it looks in your notebook app into a read-only HTML version and is what GitHub uses for notebooks. Interactive plots from Bokeh, Holoviews, etc can still work if you trust the JS, and since editing notebooks while showing them during a meeting usually doesn't go well, read-only is probably good enough (eager to hear feedback on this point though). The nice thing is that... Source: over 1 year ago

Just as a heads up, I used plotly to generate a lot of the charts, so you'll need to view it from an nbviewer like nbviewer.org. Source: about 2 years ago

I used a lot of plotly not knowing that Github wouldn't show it, so you'll need notebook viewer like nbviewer.org to see some of the charts. Source: about 2 years ago