%
% stack: cust-text
%
% analyze customer text message
% first adjust common usage of name and email indicators
%

 "," " " replall
 ":" " " replall
 Str.NormSpc
 trim
 onlylf
 " email " lf &"email " replall
 " name " lf &"name " replall
 catlf &"|" catlf
 0 -1 1 splitsln
%
% stack: [ [|]token . . . ] count
%

 empty !Cust.First
 empty !Cust.Middle
 empty !Cust.Last
 empty !Cust.Pronoun
 empty !Cust.Gender
 empty !Cust.Email
 empty !Cust.Addr
 empty !Cust.Guid

dup "@" found?
{
%
% this is an email
%
 trim dup !Cust.Email !Cust.Xemail
}
{
%
% this is a name
%
 trim
 " " slice
 trim any?
 {
%
% has first and last at least
%
  " " slice
  trim any?
  {
%
% has third name, this is last
%
   !Cust.Last
   ^" " & dup !Cust.First !Cust.Xfirst
  }
  {
%
% has only two names, first and last
%
   !Cust.Last
   dup !Cust.First !Cust.Xfirst
  } ifelse
 }
 {
%
% no last name, check first
%
  trim isnull
  {
%
% no info of any kind
%
   pop
  }
  {
%
% has first name
%
   dup !Cust.First !Cust.Xfirst
  } ifelse
 } ifelse

} ifelse

/*
%
% first, determine if any of the words is a keyword
% at the beginning of the line
%
% stack: [ [|]token . . . ] count
%
{
 pos(
 {
  dup index -1 left lower
"anly" log)(
  <
  |name
%
% a gender prefix may still be part of name token series
%
   dup + -1 roll pop -
   pos(
   {

    *splitnam
   } if
  |email
%
% parse the next word as the email address
%
   dup + -1 roll pop -
   pos(
   {
    *spliteml
   } if
  >
  {
   false
  }
  {
%
% not in the list of labels
% this is a message for shooter
%
% stack: [ [|]token . . . ] count
%
   true
  } ifelse
 }
 {
%
% no significant message
%
% stack: 
%
  true
 } ifelse
 ?
} loop
popoff
*/