https://github.com/jooyoungseo/mboxr

Reading, Extracting, and Converting an Mbox File into a Tibble in R
https://github.com/jooyoungseo/mboxr

anaconda cran email mbox r tibble

Last synced: about 6 hours ago
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Reading, Extracting, and Converting an Mbox File into a Tibble in R

• Host: GitHub
• URL: https://github.com/jooyoungseo/mboxr
• Owner: jooyoungseo
• Created: 2018-11-05T03:22:25.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-12-27T18:35:19.000Z (almost 4 years ago)
• Last Synced: 2023-07-27T18:57:47.489Z (over 1 year ago)
• Topics: anaconda, cran, email, mbox, r, tibble
• Language: R
• Homepage: https://jooyoungseo.github.io/mboxr
• Size: 167 KB
• Stars: 12
• Watchers: 4
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd

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README

        
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# mboxr

[![CRAN status](https://www.r-pkg.org/badges/version/mboxr)](https://cran.r-project.org/package=mboxr)

[![Total Downloads](https://cranlogs.r-pkg.org/badges/grand-total/mboxr?color=orange)](https://cranlogs.r-pkg.org/badges/grand-total/mboxr)

[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)

[![Travis build status](https://travis-ci.org/jooyoungseo/mboxr.svg?branch=master)](https://travis-ci.org/jooyoungseo/mboxr)

[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/jooyoungseo/mboxr?branch=master&svg=true)](https://ci.appveyor.com/project/jooyoungseo/mboxr)

[![Codecov test coverage](https://codecov.io/gh/jooyoungseo/mboxr/branch/master/graph/badge.svg)](https://codecov.io/gh/jooyoungseo/mboxr?branch=master)

The goal of mboxr is to allow R users to conveniently import an [**mbox file**](https://en.wikipedia.org/wiki/Mbox) into [**R tibble**](https://tibble.tidyverse.org/) for hands-on analyses in R environment.

# Installation

## Python Dependencies

`mboxr` requires Anaconda Python environment on your system Path.

If you have not installed Conda environment on your system, please [download and install Anaconda](https://www.anaconda.com/download/) (Python 3.6 or later is recommended).

For this package, I have implemented [**mailbox.mbox**](https://docs.python.org/3/library/mailbox.html), [**email.header.decode_header**](https://docs.python.org/3/library/email.header.html), [**email.utils**](https://docs.python.org/3/library/email.utils.html) and [**pandas.DataFrame**](https://pandas.pydata.org/) Python modules into R using [**reticulate**](https://rstudio.github.io/reticulate/).

## R Package Installation

### Development Version

You can install the latest development version as follows:

```{r, eval=FALSE}

if(!require(remotes)) {

install.packages("remotes")

}

remotes::install_github("jooyoungseo/mboxr")

```

### Stable Version

You can install the released version of mboxr from [CRAN](https://CRAN.R-project.org) with:

```{r, eval=FALSE}

install.packages('mboxr')

```

## Usage

Please use `read_mbox()` function after loading `mboxr` library like below:

```{r test, eval=FALSE}

library(mboxr)

# Importing your mbox file into an R:

test <- system.file("extdata", "test1.mbox", package = "mboxr")

data <- read_mbox(test)

data

#> # A tibble: 2 x 6

#>   date                from      to         cc    subject  content          

#>                                             

#> 1 2011-07-08 12:08:34 Author <~ Recipient~   Sample ~ "This is the bod~

#> 2 2011-07-08 12:08:34 Author <~ Recipient~   Sample ~ "This is the sec~

# Or, you can save your mbox file as an RDS file while assigning a tibble variable at the same time like below:

data <- read_mbox(mbox = test, file = "output.rds")

data

#> # A tibble: 2 x 6

#>   date                from      to         cc    subject  content          

#>                                             

#> 1 2011-07-08 12:08:34 Author <~ Recipient~   Sample ~ "This is the bod~

#> 2 2011-07-08 12:08:34 Author <~ Recipient~   Sample ~ "This is the sec~

# You can merge all mbox files in your current directory or in any specified path into one tibble and save as an RDS file for the integrated one:

test_path <- system.file("extdata", package = "mboxr")

all_data <- merge_mbox_all(path = test_path, file = "all_merged_mbox.rds")

## Find your "output.rds" file saved in your working directory while freely using the imported tibble in your R session!

all_data

#> # A tibble: 4 x 6

#>   date                from      to         cc    subject   content         

#>                                             

#> 1 2011-07-08 12:08:34 Author <~ Recipient~   Sample m~ "This is the bo~

#> 2 2011-07-08 12:08:34 Author <~ Recipient~   Sample m~ "This is the se~

#> 3 2011-07-09 12:09:35 Author <~ Recipient~   Another ~ "R is the best!~

#> 4 2011-07-10 10:03:32 Author <~ Recipient~   The last~ "This is the la~

```