Marimo notebooks are now supported natively inside VSCode
with an extension.
To work on them agentically with the GitHub Copilot Chat Agent, add marimo.agent.md as an
agent definition,
and select the Marimo agent in the chat.
The agent understands the structure and common patterns of Marimo notebooks. It operates on the Python code directly and you can see the changes reflected instantly.
| # remotes::install_github("juba/robservable") | |
| library(robservable) | |
| # see entire notebook | |
| robservable("@timelyportfolio/a-github-inspired-calendar") | |
| # only see the chart | |
| robservable( | |
| "@timelyportfolio/a-github-inspired-calendar", |
| # packages | |
| library("dplyr") | |
| library("reshape") | |
| library("microbenchmark") | |
| set.seed(1) | |
| # prep data | |
| m <- mtcars | |
| n <- 50L # number of data.frames |
Cheatsheet for LaTex, using Markdown for markup. I use this with atom.io
and 📦markdown-preview-plus to write math stuff. 📦keyboard-localization
is necessary when using an international layout (like [swiss] german).
Further Reference and source: ftp://ftp.ams.org/pub/tex/doc/amsmath/short-math-guide.pdf
| library(shiny) | |
| library(dplyr) | |
| library(lubridate) | |
| # Load libraries and functions needed to create SQLite databases. | |
| library(RSQLite) | |
| library(RSQLite.extfuns) | |
| saveSQLite <- function(data, name){ | |
| path <- dplyr:::db_location(filename=paste0(name, ".sqlite")) |
| #!/bin/bash | |
| # Shell script to get disk usage, cpu usage, RAM usage,system load,etc. | |
| # from multiple Linux servers and output the information on a single | |
| # server in html format. Read below for usage/installation info | |
| # *--------------------------------------------------------------------* | |
| # * ORIGINAL WORK BY: | |
| # * dig_remote_linux_server_information.bash,v0.1 | |
| # * Last updated on 25-Jul-2005* | |
| # * Copyright (c) 2005 nixCraft project * | |
| # * Comment/bugs: http://cyberciti.biz/fb/ * |