R/Clean_Email_Input.R

In matthewjdenny/REmail: A package for reading in email data wraping the python email libraries.

Clean_Email_Input <- function(email_object){
  #Taken from http://www.webmonkey.com/2008/08/four_regular_expressions_to_check_email_addresses/
  email_re <- "([a-z0-9][-a-z0-9_\\+\\.]*[a-z0-9])@([a-z0-9][-a-z0-9\\.]*[a-z0-9]\\.(arpa|root|aero|biz|cat|com|coop|edu|gov|info|int|jobs|mil|mobi|museum|name|net|org|pro|tel|travel|ac|ad|ae|af|ag|ai|al|am|an|ao|aq|ar|as|at|au|aw|ax|az|ba|bb|bd|be|bf|bg|bh|bi|bj|bm|bn|bo|br|bs|bt|bv|bw|by|bz|ca|cc|cd|cf|cg|ch|ci|ck|cl|cm|cn|co|cr|cu|cv|cx|cy|cz|de|dj|dk|dm|do|dz|ec|ee|eg|er|es|et|eu|fi|fj|fk|fm|fo|fr|ga|gb|gd|ge|gf|gg|gh|gi|gl|gm|gn|gp|gq|gr|gs|gt|gu|gw|gy|hk|hm|hn|hr|ht|hu|id|ie|il|im|in|io|iq|ir|is|it|je|jm|jo|jp|ke|kg|kh|ki|km|kn|kr|kw|ky|kz|la|lb|lc|li|lk|lr|ls|lt|lu|lv|ly|ma|mc|md|mg|mh|mk|ml|mm|mn|mo|mp|mq|mr|ms|mt|mu|mv|mw|mx|my|mz|na|nc|ne|nf|ng|ni|nl|no|np|nr|nu|nz|om|pa|pe|pf|pg|ph|pk|pl|pm|pn|pr|ps|pt|pw|py|qa|re|ro|ru|rw|sa|sb|sc|sd|se|sg|sh|si|sj|sk|sl|sm|sn|so|sr|st|su|sv|sy|sz|tc|td|tf|tg|th|tj|tk|tl|tm|tn|to|tp|tr|tt|tv|tw|tz|ua|ug|uk|um|us|uy|uz|va|vc|ve|vg|vi|vn|vu|wf|ws|ye|yt|yu|za|zm|zw)|([0-9]{1,3}\\.{3}[0-9]{1,3}))"
  
  #get jsut email address if it is available, otherwise preserve what was there
  temp <- stringr::str_extract(email_object@from,email_re)
  if(length(temp) > 0){
    email_object@from <- temp
  }
  
  #same thing for to field
  num_recipients <- length(email_object@to)
  for(i in 1:length(email_object@to)){
    temp <- stringr::str_extract(email_object@to[i],email_re)
    if(length(temp) > 0){
      email_object@to[i] <- temp
    }
  }
  
  #same thing for cc field
  for(i in 1:length(email_object@CC)){
    temp <- stringr::str_extract(email_object@CC[i],email_re)
    if(length(temp) > 0){
      email_object@CC[i] <- temp
      num_recipients <- num_recipients + 1
    }
  }
  
  #store number of recipeints 
  email_object@num_recipients <- num_recipients 
  
  Clean_String <- function(string){
    # string <- "inspections..#$^relocation..???!!!}{[]()"
    temp <- tolower(string)
    #remove everything that is not a number letter ? or !
    temp <- stringr::str_replace_all(temp,"[^a-zA-Z\\d\\s:\\?\\!]", " ")
    # shrink down to just one white space
    temp <- stringr::str_replace_all(temp,"[\\d\\s]+", " ")
    #split it
    temp <- stringr::str_split(temp, " ")[[1]]
    #get rid of trailing "" if necessary
    indexes <- which(temp == "")
    if(length(indexes) > 0){
      temp <- temp[-indexes]
    }
    return(temp)
  }
  
  all_tokens <- 0 
  num_tokens <- 0
  
  #now deal with subject
  email_object@subject_tokenized <- Clean_String(email_object@subject)
  
  num_tokens <- num_tokens + length(email_object@subject_tokenized)
  all_tokens <- email_object@subject_tokenized
  
  #now deal with message 
  if(length(email_object@message) == 1){
    if(email_object@message == ""){
      email_object@message_tokenized <- ""
    }else{
      email_object@message_tokenized <- Clean_String(email_object@message)
      num_tokens <- num_tokens + length(email_object@message_tokenized)
      all_tokens <- append(all_tokens,email_object@message_tokenized)
    }  
  }else if(length(email_object@message) > 1){
    indexes <- which(email_object@message == "")
    if (length(indexes) > 0){
      email_object@message <- email_object@message[-indexes]
    }
    tokenized <- Clean_String(email_object@message[1])
    one_string <- email_object@message[1]
    for(i in 2:length(email_object@message)){
      tokenized <- append(tokenized, Clean_String(email_object@message[i]))
      one_string <- paste(one_string,email_object@message[i], sep = " ")
    }
    
    email_object@message <- one_string
    email_object@message_tokenized <- tokenized
    
    num_tokens <- num_tokens + length(email_object@message_tokenized)
    all_tokens <- append(all_tokens,email_object@message_tokenized)
  }
  
  email_object@num_tokens <- num_tokens 
  email_object@all_tokens <- all_tokens
  
  return(email_object)
}