How can I conveniently move objects between sessions - r

It's obviously not something to advise in an ideal workflow but sometimes it can be useful.
Can it be done easily ?


I made the following functions, it will put a temp file in your home folder and delete it when it's fetched by default :
shoot <- function(..., list = character(), rm = FALSE){
path <- file.path(path.expand("~"),"temp_object.RData")
save(..., list = list, file = path)
if(rm) rm(list = c(list,as.character(substitute(alist(...))[-1])),
envir = parent.frame())
invisible(NULL)
}
loot <- function(rm = TRUE){
path <- file.path(path.expand("~"),"temp_object.RData")
if(file.exists(path)){
load(path,envir = parent.frame())
if(rm) file.remove(path)
} else {
stop("nothing to loot!")
}
invisible(NULL)
}
test <- "abcd"
shoot(test)
rm(test)
loot() # in practice from another session
test
# [1] "abcd"
Useful in my case if one RStudio session has a bug and I can't plot, so I can send it to another.
With a simple change in the default path can be used in a network to easily pass data between colleagues for example.
Thanks to #MrFlick for suggestions

Related

Removing Files from Global Environment with a Certain Pattern

I have these files in my global environment:
x <- sapply(sapply(ls(), get), is.data.frame)
n = names(x)[(x==TRUE)]
n
[1] "sample_1" "sample_10" "sample_2" "sample_3" "sample_4" "sample_5" "sample_6" "sample_7" "sample_8" "sample_9" "table_i"
I want to remove all files that start with "samp". I found the this code that can do this (How do I clear only a few specific objects from the workspace?):
rm(list = apropos("samp_"))
Now, I want to learn how to do the same thing using a different way. I found another way to find out all files in the global environment that start with "samp":
nn = grep("samp", n, value = TRUE)
[1] "sample_1" "sample_10" "sample_2" "sample_3" "sample_4" "sample_5" "sample_6" "sample_7" "sample_8" "sample_9"
Then, I tried to delete these files:
for (file in nn){
nn[i] <- NULL
}
do.call(file.remove, list(nn))
I think I am missing something here - can someone please show me how to correct this?
Thank you!

You can make use of pattern inside of the remove function:
rm(list = ls(pattern = "^samp"))
Or using grep:
rm(list = grep("^samp", ls(), value = TRUE))

function to clean current workspace apart from some variables

How can I write a generic R function that cleans the current workspace apart from some self-defined variables? For sure, I can achieve this in a single script with the following code:
prj = '/path/to/project'
src = 'string'
data_to_clean = head(iris)
rm(list = ls()[ !ls() %in% c('prj', 'src') ] )
# only prj and src remain
However I want this to be a function, so that it's applicable for multiple scripts and I can change the variables which should not be cleaned, in one place. Is this possible?

In case you wrap this in a function, you have to keep in mind, that a function will create its own environment, when executed. Therefore, you need to specify the environment every time (in each ls as well as rm). You probably want to remove them from the .GlobalEnv.
clean_workspace <- function(not_to_be_removed) {
rm(list =
setdiff(ls(envir = .GlobalEnv), c("clean_workspace", not_to_be_removed)),
envir = .GlobalEnv)
}
prj = '/path/to/project'
src = 'string'
data_to_clean = head(iris)
clean_workspace(c('prj', 'src'))
In order not to remove the function itself, it should be added to the values not to be removed.
If you want to read more about environments, have a look a this overview.

I think you want to remove the function itself. The important bit is to tell rm the environment where to remove these objects from:
clean_workspace <- function(not_to_be_removed, envir = globalenv()) {
objs <- ls(envir = envir)
rm(list = objs[ !objs %in% not_to_be_removed], envir = envir)
}
prj = '/path/to/project'
src = 'string'
data_to_clean = head(iris)
clean_workspace(c('prj', 'src'))
ls()
#> [1] "prj" "src"

add a data frame to an existing rdata file

I am fairly new to R
and will try my best to make myself understood.
Suppose if I have an existing rdata file with multiple objects.
Now I want to add a data frame to it how do i do that?
I tried the following:
write.data.loc <- 'users/Jim/Objects'
rdataPath <- 'users/Jim/Objects.Rda'
myFile<- read.csv("myFile.csv")
loadObjects <- load(rdataPath)
save(loadObjects,myFile,file=paste(write.data.loc,".Rda",sep=""))
But this does not seem to work?

I'm not certain of your actual use-case, but if you must "append" a new object to an rda file, here is one method. This tries to be clever by loading all of the objects from the rda file into a new environment (there are many tutorials and guides that discuss the use and relevance of environments, Hadley's "Advanced R" is one that does a good job, I think).
This first step loads all of the objects into a new (empty) environment. It's useful to use an otherwise-empty environment so that we can get all of the objects from it rather easily using ls.
e <- new.env(parent = emptyenv())
load("path/to/.rda", envir = e)
The object you want to add should be loaded into a variable within the environment. Note that the dollar-sign access looks the same as lists, which makes it both (1) easy to confuse the two, and (2) easy to understand the named indexing that $ provides.
e$myFile <- read.csv("yourFile.csv")
This last piece, re-saving the rda file, is an indirect method. The ls(envir = e) returns the variable names of all objects within the environment. This is good, because save can deal with objects or with their names.
do.call("save", c(ls(envir = e), list(envir = e, file = "newsave.rda")))
Realize that this is not technically appending the data.frame to the rda file, it's over-writing the rda file with a new one that happens to contain all the previous objects and the new one data.frame.

I wrote this solution that can add dataframes, list, matrices or lists. By default it will overwrite an existing object but can be reversed with overwrite=TRUE.
add_object_to_rda <- function(obj, rda_file, overwrite = FALSE) {
.dummy <- NULL
if (!file.exists(rda_file)) save(.dummy, file = rda_file)
old_e <- new.env()
new_e <- new.env()
load(file = rda_file, envir = old_e)
name_obj <- deparse(substitute(obj)) # get the name of the object
# new_e[[name_obj]] <- get(name_obj) # use this only outside a function
new_e[[name_obj]] <- obj
# merge object from old environment with the new environment
# ls(old_e) is a character vector of the object names
if (overwrite) {
# the old variables take precedence over the new ones
invisible(sapply(ls(new_e), function(x)
assign(x, get(x, envir = new_e), envir = old_e)))
# And finally we save the variables in the environment
save(list = ls(old_e), file = rda_file, envir = old_e)
}
else {
invisible(sapply(ls(old_e), function(x)
assign(x, get(x, envir = old_e), envir = new_e)))
# And finally we save the variables in the environment
save(list = ls(new_e), file = rda_file, envir = new_e)
}
}

Unexpected behavior with on.exit(..., add = TRUE)

First, please note that the following code creates and removes a folder in the current directory. If it conflicts with any of your file names, don't run this code. I'm not sure how to explain this question without it.
In fun1 I use on.exit(..., add = TRUE) on one line, and on the next I try to remove the directory I created with another on.exit call. It doesn't work.
fun1 <- function(){
if(!file.exists("Rsaber")) dir.create("Rsaber")
on.exit(file.remove(paste0("Rsaber/", list.files("Rsaber"))), add = TRUE)
on.exit(file.remove("Rsaber"))
write.csv("1,2,3,4", file = "Rsaber/new.csv")
}
> fun1()
# Warning message:
# In file.remove("Rsaber") :
# cannot remove file 'Rsaber', reason 'Directory not empty'
> file.exists("Rsaber")
# [1] TRUE
> list.files("Rsaber")
# [1] "new.csv"
However, this method works.
fun2 <- function(){
if(!file.exists("Rsaber")) dir.create("Rsaber")
on.exit(file.remove(c(paste0("Rsaber/", list.files("Rsaber"))), "Rsaber"))
write.csv("1,2,3,4", file = "Rsaber/new.csv")
}
> fun2()
> file.exists("Rsaber")
# [1] FALSE
This second method is also much cleaner and probably the way to go, but
Why doesn't on.exit(..., add = TRUE) behave as expected in fun1 ?
Note that I'm not using a temporary directory here because this is part of a larger function that has a logical argument for determining whether or not to keep a downloaded data file.
System info:
> version[[1]]
# [1] "x86_64-pc-linux-gnu"

I think you need add=TRUE on the second file.remove otherwise the second statement replaces the first:
fun1 <- function(){
if(!file.exists("Rsaber")) dir.create("Rsaber")
on.exit(file.remove(paste0("Rsaber/", list.files("Rsaber"))))
on.exit(file.remove("Rsaber"), add = TRUE)
write.csv("1,2,3,4", file = "Rsaber/new.csv")
}
Also as noted this wont work on windows as the directory will not be considered as a file.
For cross-platform support maybe consider unlink
fun1 <- function(){
if(!file.exists("Rsaber")) dir.create("Rsaber")
on.exit(unlink("Rsaber", recursive = TRUE))
write.csv("1,2,3,4", file = "Rsaber/new.csv")
print(system('ls'))
}

Customizing R profile [duplicate]

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Closed 10 years ago.
I have always found startup profile files of other people both useful and instructive about the language. Moreover, while I have some customization for Bash and Vim, I have nothing for R.
For example, one thing I always wanted is different colors for input and output text in a window terminal, and maybe even syntax highlighting.

Here is mine. It won't help you with the coloring but I get that from ESS and Emacs...
options("width"=160) # wide display with multiple monitors
options("digits.secs"=3) # show sub-second time stamps
r <- getOption("repos") # hard code the US repo for CRAN
r["CRAN"] <- "http://cran.us.r-project.org"
options(repos = r)
rm(r)
## put something this is your .Rprofile to customize the defaults
setHook(packageEvent("grDevices", "onLoad"),
function(...) grDevices::X11.options(width=8, height=8,
xpos=0, pointsize=10,
#type="nbcairo")) # Cairo device
#type="cairo")) # other Cairo dev
type="xlib")) # old default
## from the AER book by Zeileis and Kleiber
options(prompt="R> ", digits=4, show.signif.stars=FALSE)
options("pdfviewer"="okular") # on Linux, use okular as the pdf viewer

I hate to type the full words 'head', 'summary', 'names' every time, so I use aliases.
You can put aliases into your .Rprofile file, but you have to use the full path to the function (e.g. utils::head) otherwise it won't work.
# aliases
s <- base::summary
h <- utils::head
n <- base::names
EDIT: to answer your question, you can use the colorout package to have different colors in the terminal. Cool! :-)

options(stringsAsFactors=FALSE)
Although I don't actually have that in my .Rprofile, because it might breaks my coauthors' code, I wish it was the default. Why?
1) Character vectors use less memory (but only barely);
2) More importantly, we would avoid problems such as:
> x <- factor(c("a","b","c"))
> x
[1] a b c
Levels: a b c
> x <- c(x, "d")
> x
[1] "1" "2" "3" "d"
and
> x <- factor(c("a","b","c"))
> x[1:2] <- c("c", "d")
Warning message:
In `[<-.factor`(`*tmp*`, 1:2, value = c("c", "d")) :
invalid factor level, NAs generated
Factors are great when you need them (e.g. implementing ordering in graphs) but a nuisance most of the time.

I like saving my R command history and having it available each time I run R:
In the shell or .bashrc:
export R_HISTFILE=~/.Rhistory
in .Rprofile:
.Last <- function() {
if (!any(commandArgs()=='--no-readline') && interactive()){
require(utils)
try(savehistory(Sys.getenv("R_HISTFILE")))
}
}

Here are two functions I find handy for working with windows.
The first converts the \s to /.
.repath <- function() {
cat('Paste windows file path and hit RETURN twice')
x <- scan(what = "")
xa <- gsub('\\\\', '/', x)
writeClipboard(paste(xa, collapse=" "))
cat('Here\'s your de-windowsified path. (It\'s also on the clipboard.)\n', xa, '\n')
}
The second opens the working directory in a new explorer window.
getw <- function() {
suppressWarnings(shell(paste("explorer", gsub('/', '\\\\', getwd()))))
}

Here's mine. I always use the main cran repository, and have code to make it easy to source in-development package code.
.First <- function() {
library(graphics)
options("repos" = c(CRAN = "http://cran.r-project.org/"))
options("device" = "quartz")
}
packages <- list(
"describedisplay" = "~/ggobi/describedisplay",
"linval" = "~/ggobi/linval",
"ggplot2" = "~/documents/ggplot/ggplot",
"qtpaint" = "~/documents/cranvas/qtpaint",
"tourr" = "~/documents/tour/tourr",
"tourrgui" = "~/documents/tour/tourr-gui",
"prodplot" = "~/documents/categorical-grammar"
)
l <- function(pkg) {
pkg <- tolower(deparse(substitute(pkg)))
if (is.null(packages[[pkg]])) {
path <- file.path("~/documents", pkg, pkg)
} else {
path <- packages[pkg]
}
source(file.path(path, "load.r"))
}
test <- function(path) {
path <- deparse(substitute(path))
source(file.path("~/documents", path, path, "test.r"))
}

I've got this, more dynamic trick to use full terminal width, which tries to read from the COLUMNS environment variable (on Linux):
tryCatch(
{options(
width = as.integer(Sys.getenv("COLUMNS")))},
error = function(err) {
write("Can't get your terminal width. Put ``export COLUMNS'' in your \
.bashrc. Or something. Setting width to 120 chars",
stderr());
options(width=120)}
)
This way R will use the full width even as you resize your terminal window.

Most of my personal functions and loaded libraries are in the Rfunctions.r script
source("c:\\data\\rprojects\\functions\\Rfunctions.r")
.First <- function(){
cat("\n Rrrr! The statistics program for Pirates !\n\n")
}
.Last <- function(){
cat("\n Rrrr! Avast Ye, YO HO!\n\n")
}
#===============================================================
# Tinn-R: necessary packages
#===============================================================
library(utils)
necessary = c('svIDE', 'svIO', 'svSocket', 'R2HTML')
if(!all(necessary %in% installed.packages()[, 'Package']))
install.packages(c('SciViews', 'R2HTML'), dep = T)
options(IDE = 'C:/Tinn-R/bin/Tinn-R.exe')
options(use.DDE = T)
library(svIDE)
library(svIO)
library(svSocket)
library(R2HTML)
guiDDEInstall()
shell(paste("mkdir C:\\data\\rplots\\plottemp", gsub('-','',Sys.Date()), sep=""))
pldir <- paste("C:\\data\\rplots\\plottemp", gsub('-','',Sys.Date()), sep="")
plot.str <-c('savePlot(paste(pldir,script,"\\BeachSurveyFreq.pdf",sep=""),type="pdf")')

Here's from my ~/.Rprofile, designed for Mac and Linux.
These make errors easier to see.
options(showWarnCalls=T, showErrorCalls=T)
I hate the CRAN menu choice, so set to a good one.
options(repos=c("http://cran.cnr.Berkeley.edu","http://cran.stat.ucla.edu"))
More history!
Sys.setenv(R_HISTSIZE='100000')
The following is for running on Mac OSX from the terminal (which I greatly prefer to R.app because it's more stable, and you can organize your work by directory; also make sure to get a good ~/.inputrc). By default, you get an X11 display, which doesn't look as nice; this instead gives a quartz display same as the GUI. The if statement is supposed to catch the case when you're running R from the terminal on Mac.
f = pipe("uname")
if (.Platform$GUI == "X11" && readLines(f)=="Darwin") {
# http://www.rforge.net/CarbonEL/
library("grDevices")
library("CarbonEL")
options(device='quartz')
Sys.unsetenv("DISPLAY")
}
close(f); rm(f)
And preload a few libraries,
library(plyr)
library(stringr)
library(RColorBrewer)
if (file.exists("~/util.r")) {
source("~/util.r")
}
where util.r is a random bag of stuff I use, under flux.
Also, since other people were mentioning console width, here's how I do it.
if ( (numcol <-Sys.getenv("COLUMNS")) != "") {
numcol = as.integer(numcol)
options(width= numcol - 1)
} else if (system("stty -a &>/dev/null") == 0) {
# mac specific? probably bad in the R GUI too.
numcol = as.integer(sub(".* ([0-9]+) column.*", "\\1", system("stty -a", intern=T)[1]))
if (numcol > 0)
options(width= numcol - 1 )
}
rm(numcol)
This actually isn't in .Rprofile because you have to re-run it every time you resize the terminal window. I have it in util.r then I just source it as necessary.

Here are mine:
.First <- function () {
options(device="quartz")
}
.Last <- function () {
if (!any(commandArgs() == '--no-readline') && interactive()) {
require(utils)
try(savehistory(Sys.getenv("R_HISTFILE")))
}
}
# Slightly more flexible than as.Date
# my.as.Date("2009-01-01") == my.as.Date(2009, 1, 1) == as.Date("2009-01-01")
my.as.Date <- function (a, b=NULL, c=NULL, ...) {
if (class(a) != "character")
return (as.Date(sprintf("%d-%02d-%02d", a, b, c)))
else
return (as.Date(a))
}
# Some useful aliases
cd <- setwd
pwd <- getwd
lss <- dir
asd <- my.as.Date # examples: asd("2009-01-01") == asd(2009, 1, 1) == as.Date("2009-01-01")
last <- function (x, n=1, ...) tail(x, n=n, ...)
# Set proxy for all web requests
Sys.setenv(http_proxy="http://192.168.0.200:80/")
# Search RPATH for file <fn>. If found, return full path to it
search.path <- function(fn,
paths = strsplit(chartr("\\", "/", Sys.getenv("RPATH")), split =
switch(.Platform$OS.type, windows = ";", ":"))[[1]]) {
for(d in paths)
if (file.exists(f <- file.path(d, fn)))
return(f)
return(NULL)
}
# If loading in an environment that doesn't respect my RPATH environment
# variable, set it here
if (Sys.getenv("RPATH") == "") {
Sys.setenv(RPATH=file.path(path.expand("~"), "Library", "R", "source"))
}
# Load commonly used functions
if (interactive())
source(search.path("afazio.r"))
# If no R_HISTFILE environment variable, set default
if (Sys.getenv("R_HISTFILE") == "") {
Sys.setenv(R_HISTFILE=file.path("~", ".Rhistory"))
}
# Override q() to not save by default.
# Same as saying q("no")
q <- function (save="no", ...) {
quit(save=save, ...)
}
# ---------- My Environments ----------
#
# Rather than starting R from within different directories, I prefer to
# switch my "environment" easily with these functions. An "environment" is
# simply a directory that contains analysis of a particular topic.
# Example usage:
# > load.env("markets") # Load US equity markets analysis environment
# > # ... edit some .r files in my environment
# > reload() # Re-source .r/.R files in my environment
#
# On next startup of R, I will automatically be placed into the last
# environment I entered
# My current environment
.curr.env = NULL
# File contains name of the last environment I entered
.last.env.file = file.path(path.expand("~"), ".Rlastenv")
# Parent directory where all of my "environment"s are contained
.parent.env.dir = file.path(path.expand("~"), "Analysis")
# Create parent directory if it doesn't already exist
if (!file.exists(.parent.env.dir))
dir.create(.parent.env.dir)
load.env <- function (string, save=TRUE) {
# Load all .r/.R files in <.parent.env.dir>/<string>/
cd(file.path(.parent.env.dir, string))
for (file in lss()) {
if (substr(file, nchar(file)-1, nchar(file)+1) %in% c(".r", ".R"))
source(file)
}
.curr.env <<- string
# Save current environment name to file
if (save == TRUE) writeLines(.curr.env, .last.env.file)
# Let user know environment switch was successful
print (paste(" -- in ", string, " environment -- "))
}
# "reload" current environment.
reload <- resource <- function () {
if (!is.null(.curr.env))
load.env(.curr.env, save=FALSE)
else
print (" -- not in environment -- ")
}
# On startup, go straight to the environment I was last working in
if (interactive() && file.exists(.last.env.file)) {
load.env(readLines(.last.env.file))
}

sink(file = 'R.log', split=T)
options(scipen=5)
.ls.objects <- function (pos = 1, pattern, order.by = "Size", decreasing=TRUE, head = TRUE, n = 10) {
# based on postings by Petr Pikal and David Hinds to the r-help list in 2004
# modified by: Dirk Eddelbuettel (http://stackoverflow.com/questions/1358003/tricks-to- manage-the-available-memory-in-an-r-session)
# I then gave it a few tweaks (show size as megabytes and use defaults that I like)
# a data frame of the objects and their associated storage needs.
napply <- function(names, fn) sapply(names, function(x)
fn(get(x, pos = pos)))
names <- ls(pos = pos, pattern = pattern)
obj.class <- napply(names, function(x) as.character(class(x))[1])
obj.mode <- napply(names, mode)
obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
obj.size <- napply(names, object.size) / 10^6 # megabytes
obj.dim <- t(napply(names, function(x)
as.numeric(dim(x))[1:2]))
vec <- is.na(obj.dim)[, 1] & (obj.type != "function")
obj.dim[vec, 1] <- napply(names, length)[vec]
out <- data.frame(obj.type, obj.size, obj.dim)
names(out) <- c("Type", "Size", "Rows", "Columns")
out <- out[order(out[[order.by]], decreasing=decreasing), ]
if (head)
out <- head(out, n)
out
}

Make data.frames display somewhat like 'head', only without having to type 'head'
print.data.frame <- function(df) {
if (nrow(df) > 10) {
base::print.data.frame(head(df, 5))
cat("----\n")
base::print.data.frame(tail(df, 5))
} else {
base::print.data.frame(df)
}
}
(From How to make 'head' be applied automatically to output? )

I often have a chain of debug calls I need to call and uncommenting them can be very tedious. With the help of the SO community, I went for the following solution and inserted this into my .Rprofile.site. # BROWSER is there for my Eclipse Tasks so that I have an overview of browser calls in the Task View window.
# turn debugging on or off
# place "browser(expr = isTRUE(getOption("debug"))) # BROWSER" in your function
# and turn debugging on or off by bugon() or bugoff()
bugon <- function() options("debug" = TRUE)
bugoff <- function() options("debug" = FALSE) #pun intended

Mine is not too fancy:
# So the mac gui can find latex
Sys.setenv("PATH" = paste(Sys.getenv("PATH"),"/usr/texbin",sep=":"))
#Use last(x) instead of x[length(x)], works on matrices too
last <- function(x) { tail(x, n = 1) }
#For tikzDevice caching
options( tikzMetricsDictionary='/Users/cameron/.tikzMetricsDictionary' )

setwd("C://path//to//my//prefered//working//directory")
library("ggplot2")
library("RMySQL")
library("foreign")
answer <- readline("What database would you like to connect to? ")
con <- dbConnect(MySQL(),user="root",password="mypass", dbname=answer)
I do a lot of work from mysql databases, so connecting right away is a godsend. I only wish there was a way of listing the avaialble databases so I wouldn't have to remember all the different names.

Stephen Turner's post on .Rprofiles has several useful aliases and starter functions.
I find myself using his ht and hh often.
#ht==headtail, i.e., show the first and last 10 items of an object
ht <- function(d) rbind(head(d,10),tail(d,10))
# Show the first 5 rows and first 5 columns of a data frame or matrix
hh <- function(d) d[1:5,1:5]

Here's mine, including some of the mentioned ideas.
Two things you might want to look at:
.set.width() / w() update your print width to the one of the terminal. Unfortunately I did not find a way to do this automatically on terminal resize - R documentation mentions this is done by some R interpreters.
history is saved every time together with a timestamp and the working directory
.
.set.width <- function() {
cols <- as.integer(Sys.getenv("COLUMNS"))
if (is.na(cols) || cols > 10000 || cols < 10)
options(width=100)
options(width=cols)
}
.First <- function() {
options(digits.secs=3) # show sub-second time stamps
options(max.print=1000) # do not print more than 1000 lines
options("report" = c(CRAN="http://cran.at.r-project.org"))
options(prompt="R> ", digits=4, show.signif.stars=FALSE)
}
# aliases
w <- .set.width
.Last <- function() {
if (!any(commandArgs()=='--no-readline') && interactive()){
timestamp(,prefix=paste("##------ [",getwd(),"] ",sep=""))
try(savehistory("~/.Rhistory"))
}
}

I use the following to get cacheSweave (or pgfSweave) to work with the "Compile PDF" button in RStudio:
library(cacheSweave)
assignInNamespace("RweaveLatex", cacheSweave::cacheSweaveDriver, "utils")

Mine includes options(menu.graphics=FALSE) because I like to Disable/suppress tcltk popup for CRAN mirror selection in R.

Here's mine. Nothing too innovative. Thoughts on why particular choices:
I went with setting a default for stringsAsFactors because I find
it extremely draining to pass it as an argument each time I read a CSV in. That said, it has already caused me some minor vexation when using code written on my usual computer on a computer which did not have my .Rprofile. I'm keeping it, though, as the troubles it has caused pale in comparison to the troubles not having it set everyday used to cause.
If you don't load the utils package before options(error=recover), it cannot find recover when placed inside an interactive() block.
I used .db for my dropbox setting rather than options(dropbox=...) because I use it all the time inside file.path and it saves much typing. The leading . keeps it from appearing with ls().
Without further ado:
if(interactive()) {
options(stringsAsFactors=FALSE)
options(max.print=50)
options(repos="http://cran.mirrors.hoobly.com")
}
.db <- "~/Dropbox"
# `=` <- function(...) stop("Assignment by = disabled, use <- instead")
options(BingMapsKey="blahblahblah") # Used by taRifx.geo::geocode()
.First <- function() {
if(interactive()) {
require(functional)
require(taRifx)
require(taRifx.geo)
require(ggplot2)
require(foreign)
require(R.utils)
require(stringr)
require(reshape2)
require(devtools)
require(codetools)
require(testthat)
require(utils)
options(error=recover)
}
}

Here's a little snippet for use exporting tables to LaTeX. It changes all the column names to math mode for the many reports I write. The rest of my .Rprofile is pretty standard and mostly covered above.
# Puts $dollar signs in front and behind all column names col_{sub} -> $col_{sub}$
amscols<-function(x){
colnames(x) <- paste("$", colnames(x), "$", sep = "")
x
}

I set my lattice color theme in my profile. Here are two other tweaks I use:
# Display working directory in the titlebar
# Note: This causes demo(graphics) to fail
utils::setWindowTitle(base::getwd())
utils::assignInNamespace("setwd",function(dir) {.Internal(setwd(dir));setWindowTitle(base::getwd())},"base")
# Don't print more than 1000 lines
options(max.print=2000)

I have an environment variable R_USER_WORKSPACE which points to the top directory of my packages. In .Rprofile I define a function devlib which sets the working directory (so that data() works) and sources all .R files in the R subdirectory. It is quite similar to Hadley's l() function above.
devlib <- function(pkg) {
setwd(file.path(Sys.getenv("R_USER_WORKSPACE", "."), deparse(substitute(pkg)), "dev"))
sapply(list.files("R", pattern=".r$", ignore.case=TRUE, full.names=TRUE), source)
invisible(NULL)
}
.First <- function() {
setwd(Sys.getenv("R_USER_WORKSPACE", "."))
options("repos" = c(CRAN = "http://mirrors.softliste.de/cran/", CRANextra="http://www.stats.ox.ac.uk/pub/RWin"))
}
.Last <- function() update.packages(ask="graphics")

I found two functions really necessary: First when I have set debug() on several functions and I have resolved the bug, so I want to undebug() all functions - not one by one. The undebug_all() function added as the accepted answer here is the best.
Second, when I have defined many functions and I am looking for a specific variable name, it's hard to find it within all results of the the ls(), including the function names. The lsnofun() function posted here is really good.

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