Example dashboard now live at here.
Parses the XML output from Android SMS Backup and Restore and writes metadata to CSV and a SQLite database (with one table called texts). This data can be used by a Shiny app to construct a dashboard of your text message based friendships.
Either use the functions in sms.py for your own purposes or run the import.py script at the
command line. For import.py, run
python import.py basePath encrypt
where basePath is the path to the folder with the sms xml files to be imported. The files should be named
sms1.xml, sms2.xml and so on. encrypt should be True or False and determines whether the contact
names and phone numbers should be hashed with sha224.
Example usage would be
python import.py /home/iacobus42/sms/ True
The script will produce output of sms1.csv and so forth for each .xml file. If fewer than 1 files are
found in the basepath, an warning will print saying 0 files were imported and to check the path. The
trailing parens is required (/home/iacobus42/sms will not work while /home/iacobus42/sms/ will).
The script will produce a SQLite database sms.db in the folder given by basePath. If you don't have
SQLite installed, it may crash after writing out the .csv files.
To connect to the database after writing it out, from the command line run
sqlite3 path/to/data/base/sms.db
and you'll enter a SQLite session with the sms.db database.
In the file app.R, change the path to the database in line 7 (under the comment) from mine to
the path for your database.
Load an R session and running the script with that change will generate the dashboard. RStudio will automatically start a brower session, otherwise you will need to connect to the port directed in the console.
Note that the dashboard requires the packages shiny, shinydashboard, dplyr and ggplot2
in addition to survival (survival should already be installed, the rest can be installed
using install.packages() except for shinydashboard which is installed using the devtools
package with the command devtools::install_github("rstudio/shinydashboard") or by using
R CMD build with the source from the shinydashboard repo.