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gawk: Multiple Line

 
 4.9 Multiple-Line Records
 =========================
 
 In some databases, a single line cannot conveniently hold all the
 information in one entry.  In such cases, you can use multiline records.
 The first step in doing this is to choose your data format.
 
    One technique is to use an unusual character or string to separate
 records.  For example, you could use the formfeed character (written
 '\f' in 'awk', as in C) to separate them, making each record a page of
 the file.  To do this, just set the variable 'RS' to '"\f"' (a string
 containing the formfeed character).  Any other character could equally
 well be used, as long as it won't be part of the data in a record.
 
    Another technique is to have blank lines separate records.  By a
 special dispensation, an empty string as the value of 'RS' indicates
 that records are separated by one or more blank lines.  When 'RS' is set
 to the empty string, each record always ends at the first blank line
 encountered.  The next record doesn't start until the first nonblank
 line that follows.  No matter how many blank lines appear in a row, they
 all act as one record separator.  (Blank lines must be completely empty;
 lines that contain only whitespace do not count.)
 
    You can achieve the same effect as 'RS = ""' by assigning the string
 '"\n\n+"' to 'RS'.  This regexp matches the newline at the end of the
 record and one or more blank lines after the record.  In addition, a
 regular expression always matches the longest possible sequence when
 there is a choice (⇒Leftmost Longest).  So, the next record
 doesn't start until the first nonblank line that follows--no matter how
 many blank lines appear in a row, they are considered one record
 separator.
 
    However, there is an important difference between 'RS = ""' and 'RS =
 "\n\n+"'.  In the first case, leading newlines in the input data file
 are ignored, and if a file ends without extra blank lines after the last
 record, the final newline is removed from the record.  In the second
 case, this special processing is not done.  (d.c.)
 
    Now that the input is separated into records, the second step is to
 separate the fields in the records.  One way to do this is to divide
 each of the lines into fields in the normal manner.  This happens by
 default as the result of a special feature.  When 'RS' is set to the
 empty string _and_ 'FS' is set to a single character, the newline
 character _always_ acts as a field separator.  This is in addition to
 whatever field separations result from 'FS'.(1)
 
    The original motivation for this special exception was probably to
 provide useful behavior in the default case (i.e., 'FS' is equal to
 '" "').  This feature can be a problem if you really don't want the
 newline character to separate fields, because there is no way to prevent
 it.  However, you can work around this by using the 'split()' function
 to break up the record manually (⇒String Functions).  If you have
 a single-character field separator, you can work around the special
 feature in a different way, by making 'FS' into a regexp for that single
 character.  For example, if the field separator is a percent character,
 instead of 'FS = "%"', use 'FS = "[%]"'.
 
    Another way to separate fields is to put each field on a separate
 line: to do this, just set the variable 'FS' to the string '"\n"'.
 (This single-character separator matches a single newline.)  A practical
 example of a data file organized this way might be a mailing list, where
 blank lines separate the entries.  Consider a mailing list in a file
 named 'addresses', which looks like this:
 
      Jane Doe
      123 Main Street
      Anywhere, SE 12345-6789
 
      John Smith
      456 Tree-lined Avenue
      Smallville, MW 98765-4321
      ...
 
 A simple program to process this file is as follows:
 
      # addrs.awk --- simple mailing list program
 
      # Records are separated by blank lines.
      # Each line is one field.
      BEGIN { RS = "" ; FS = "\n" }
 
      {
            print "Name is:", $1
            print "Address is:", $2
            print "City and State are:", $3
            print ""
      }
 
    Running the program produces the following output:
 
      $ awk -f addrs.awk addresses
      -| Name is: Jane Doe
      -| Address is: 123 Main Street
      -| City and State are: Anywhere, SE 12345-6789
      -|
      -| Name is: John Smith
      -| Address is: 456 Tree-lined Avenue
      -| City and State are: Smallville, MW 98765-4321
      -|
      ...
 
    ⇒Labels Program for a more realistic program dealing with
 address lists.  The following list summarizes how records are split,
 based on the value of 'RS'.  ('==' means "is equal to.")
 
 'RS == "\n"'
      Records are separated by the newline character ('\n').  In effect,
      every line in the data file is a separate record, including blank
      lines.  This is the default.
 
 'RS == ANY SINGLE CHARACTER'
      Records are separated by each occurrence of the character.
      Multiple successive occurrences delimit empty records.
 
 'RS == ""'
      Records are separated by runs of blank lines.  When 'FS' is a
      single character, then the newline character always serves as a
      field separator, in addition to whatever value 'FS' may have.
      Leading and trailing newlines in a file are ignored.
 
 'RS == REGEXP'
      Records are separated by occurrences of characters that match
      REGEXP.  Leading and trailing matches of REGEXP delimit empty
      records.  (This is a 'gawk' extension; it is not specified by the
      POSIX standard.)
 
    If not in compatibility mode (⇒Options), 'gawk' sets 'RT' to
 the input text that matched the value specified by 'RS'.  But if the
 input file ended without any text that matches 'RS', then 'gawk' sets
 'RT' to the null string.
 
    ---------- Footnotes ----------
 
    (1) When 'FS' is the null string ('""') or a regexp, this special
 feature of 'RS' does not apply.  It does apply to the default field
 separator of a single space: 'FS = " "'.
 
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