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library(digest)

test <- c("hobe", "jmjj", 1)

digest(test, algo = "md5")
digest(test, algo = "sha1")
digest(test, algo = "crc32") # not collision proof
digest(test, algo = "sha256")
digest(test, algo = "sha512")

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# install.packages("rjson")
library("rjson")
json_file <- "json_file.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# additional if needed
library(plyr)
json_data <- lapply(json_data, as.data.frame)
json_data <- do.call(rbind.fill, json_data)

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### string matching


### metric to find the similarity between two strings
### some context in:
### http://en.wikipedia.org/wiki/String_metric


### testing levenshtein metric
library(RecordLinkage)

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#' best package to read excel files is gdata
#' which works with both .xls and .xlsx

#' windows: follow instructions here: 
#' http://cran.r-project.org/web/packages/gdata/INSTALL
library(gdata)
xlsx_file <- "myfile.xls"
sheet1 <- read.xls(xlsx_file,
                   sheet = "Sheet1", 
                   stringsAsFactors = FALSE, 

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# remove non-ascii characters
df$text <- gsub("[^\x20-\x7E]", "", df$text)

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(source: http://nvie.com/posts/a-successful-git-branching-model/)

create new branch:

git checkout -b develop

you can already use it this way

git remote add origin git push origin develop git pull origin develop

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# tricks with regular expressions ####

# insert character after a given pattern: use \\1

sub("([[:digit:]]{4})", "\\15", "12346789") 

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df$g <- factor(df$g, levels = letters[4:1])

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library(R2HTML)

# setup a temporaty file to store the code
fileName <- 'temp.html'
.HTML.file = file.path(getwd(), fileName)

# make a title
HTML(as.title("Title of my report"), append = FALSE)
# add space
HTMLhr()

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# looping through vector ####
library(inline)

sign <- signature(x="numeric", n="integer", d="numeric")
code <- "
      for (int i=1; i < *n; i++) {
        x[i] = x[i-1]*d[0] + x[i];
      }"

c_fn <- cfunction(sign,