ricochet 🐇 (@ricochet.rs)

ricochet 🐇

@ricochet.rs

Putting R, Julia, and Python in production with 🤍🐇 ricochet.rs #rstats #julialang #python

Is there something you'd like to see supported in @ricochet.rs? Contribute to our roadmap roadmap.ricochet.rs/p/ricochet #databs #rstats #python #julialang

roadmap.ricochet.rsricochetRoadmap for ricochet.rs

ricochet 🐇

@ricochet.rs

"deploy this shiny app" 🐇 is all it took to deploy an app to @ricochet.rs Our new Claude Code and Codex plugins makes pushing to prod a whole lot simpler for data scientists. 👇 An actual recording of deploying an app. #rstats #databs #julialang #python #claude

ricochet 🐇

@ricochet.rs

• "deploy this FastAPI" • "setup a persistent DuckDB" • "schedule my Quarto doc" • "Configure OpenTelemetry collection" We've made Claude Code and Codex plugins to simplify putting #rstats, #julialang, and #python into production. github.com/ricochet-rs/...

ricochet 🐇

@ricochet.rs

📣 Jupyter notebooks 📓, CPU monitoring ⚙️, and UI improvements and more just shipped in v0.24 of ricochet! 🧵 Take a look below! 👇🏼 Full release notes: docs.ricochet.rs/releases/v0.... #rstats #julialang #python #databs

docs.ricochet.rsv0.24.0

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ricochet 🐇

@ricochet.rs

Or view all tasks and app workers server wide to keep track of memory hogs 🐷 and long running processes.

ricochet 🐇

@ricochet.rs

We now support @jupyter.org notebooks! Deploy as a static site, run on a schedule, or invoke via REST API.

ricochet 🐇

@ricochet.rs

docs.ricochet.rsv0.24.0

ricochet 🐇

@ricochet.rs

Monitor your Shiny app or FastAPI usage with live worker monitoring. RAM, CPU, and connections in the UI. All of which are exposed to an internal @prometheus.io 🔥 server.

ricochet 🐇 reposted

Josiah

@josiah.rs

reeeee feeling giddy about the next release of @ricochet.rs live monitoring of app (shiny in this case) processes—max ram, CPU, and connections.

ricochet 🐇

@ricochet.rs

App deployment in R got a whole lot simpler thanks to {plumber2}🪠 and the _server.yml standard! 🧵1/4 👀 📜 ricochet.rs/blog/server-... #rstats #databs

ricochet.rsSimplifying app deployment in R | ricochetUnderstanding the _server.yml standard.

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ricochet 🐇

@ricochet.rs

v0.20 of ricochet supports the _server.yml standard which means you can now deploy {plumber2}, {mcptools}, {nanonext}, and {fiery}! This app is built with {plumber2}: gallery.ricochet.rs/app/penguins...

gallery.ricochet.rsHello from ricochet

ricochet 🐇

@ricochet.rs

The source code for the example app 👇 github.com/ricochet-rs/...

ricochet 🐇

@ricochet.rs

App deployment in R got a whole lot simpler thanks to {plumber2}🪠 and the _server.yml standard! 🧵1/4 👀 📜 ricochet.rs/blog/server-... #rstats #databs

ricochet.rsSimplifying app deployment in R | ricochetUnderstanding the _server.yml standard.

ricochet 🐇

@ricochet.rs

Every package has its own bespoke way to start an app: - plumber::pr_run() - plumber2::api_run() - shiny::runApp() The _server.yml standard defines a launch_server() function that is in each “engine” (a package 📦) with the same arguments: config, host, port. Keep the messy config to the yaml

ricochet 🐇 reposted

Josiah

@josiah.rs

31 Aug

🌍 Scalable spatial viz📍 Or, why Lonboard from @developmentseed.org is so fast! 💨 And how R-spatial is embracing the pattern 🐇 TL;DR - Forsake GeoJSON - Embrace GeoArrow ✨The inaugural @ricochet.rs blog post! #rspatial #gischat #databs #rstats ricochet.rs/blog/high-pe...

ricochet.rsScalable Spatial Viz: Lonboard and Shiny for Python | ricochetHow GeoArrow, GeoParquet, and GPU rendering are reshaping geospatial visualization.

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