This document shows how to mount an AWS S3 bucket on Mac OS X using goofyfs.
The first three steps illustrate how to use goofys
- Install goofyfs via brew
brew cask install osxfuse
brew install goofys
library(glue) | |
library(RSQLite) | |
con <- dbConnect(RSQLite::SQLite(), ":memory:") | |
var = "test" | |
glue_sql("{var}", .con = con) # <SQL> 'test' | |
glue_sql("{`var`}", .con = con) # <SQL> `test` | |
glue_sql("{DBI::SQL(var)}", .con = con) # <SQL> test (unquoted) | |
glue_sql("`{var}`", .con = con) # <SQL> `'test'` NOT USEFUL |
# The following code is based on the shiny::conditionalPanel() help page. The `ui` and `server` | |
# components have been compartmentalized into the `mod_histogram` module. The `histogramApp` | |
# function shows an example of using this module. | |
# Note that the `ns = ns` argument needs to be passed ot the conditionalPanel() call. | |
library(shiny) | |
mod_histogram_ui <- function(id){ | |
ns <- NS(id) | |
fluidPage( |
This document shows how to mount an AWS S3 bucket on Mac OS X using goofyfs.
The first three steps illustrate how to use goofys
brew cask install osxfuse
brew install goofys
library(glue) | |
library(httr) | |
library(jsonlite) | |
library(xml2) | |
#' Query ENA's REST API for information about records | |
#' | |
#' @param accessions Character vector of one or more ENA record identifiers | |
#' @return An `xml_document` object | |
get_records <- function(accessions) { |
library(palmerpenguins) | |
library(shiny) | |
library(shinyjqui) | |
categories <- colnames(penguins)[vapply(penguins, is.factor, logical(1))] | |
server <- function(input, output) { | |
lapply(categories, \(category) { | |
output[[category]] <- renderPrint({ print(input[[category]]) }) | |
}) |
#' Create an image tag with an example image | |
#' | |
#' @param width Scalar integer, the width of the image | |
#' @param height Scalar integer, the height of the image | |
#' @param title Scalar character, the title of the image | |
#' @return A `shiny.tag` with the URL to a random image from | |
#' [Lorem Picsum](https://picsum.photos/) | |
#' @export | |
#' @importFrom htmltool tags | |
#' @importFrom checkmate assert_count assert_character |
There is a lot of confusing information about virtual environments in python out there, in part because the tool chain has evolved over many years.
I decided to follow the advice of Real python and The hitchhiker's guide to python and manage both multiple python versions and multiple virtual environments with pyenv
--- | |
title: "Embedding R into Quarto documents with quarto-webr" | |
subtitle: "Example: intersecting differential expression results" | |
author: "Thomas Sandmann" | |
date: '2023/11/18' | |
format: html | |
engine: knitr | |
webr: | |
show-startup-message: true | |
packages: ['ggvenn', 'huxtable'] |
As an introduction into Luigi, I am following this tutorial with some modifications, e.g. installation using conda.
The problems and solutions described in the examples below have led to the development of sciluigi,