NAME

tablify - turn a delimited text file into a text table

SYNOPSIS

  tablify [options] file

Options:

  -h|--help           Show help
  --no-headers        Assume first line is data, not headers
  -l|--list           List the fields in the file (for use with -f)
  -f|--fields=f1[,f2] Show only fields in comma-separated list;
                      when used in conjunction with "no-headers"
                      the list should be field numbers (starting at 1);
                      otherwise, should be field names
  -w|where=f<cmp>v    Apply the "cmp" Perl operator to restrict output 
                      where field "f" matches the value "v";  acceptable
                      operators include ==, eq, >, >=, <=, and =~
  --limit=n           Limit to first "n" records
  --fs=x              Use "x" as the field separator 
                      (default is tab "\t")
  --rs=x              Use "x" as the record separator 
                      (default is newline "\n")

DESCRIPTION

This script is essentially a quick way to parse a delimited text file and view it as a nice ASCII table. By selecting only certain fields, employing a where clause to only select records where a field matches some value, and using the limit to only see some of the output, you almost have a mini-database front-end for a simple text file.

EXAMPLES

Given a data file like this:

  name,rank,serial_no,is_living,age
  George,General,190293,0,64
  Dwight,General,908348,0,75
  Attila,Hun,,0,56
  Tojo,Emporor,,0,87
  Tommy,General,998110,1,54

To find the fields you can reference, use the list option:

  $ tablify --fs ',' -l people.dat 
  +-----------+-----------+
  | Field No. | Field     |
  +-----------+-----------+
  | 1         | name      |
  | 2         | rank      |
  | 3         | serial_no |
  | 4         | is_living |
  | 5         | age       |
  +-----------+-----------+

To extract just the name and serial numbers, use the fields option:

  $ tablify --fs ',' -f name,serial_no people.dat 
  +--------+-----------+
  | name   | serial_no |
  +--------+-----------+
  | George | 190293    |
  | Dwight | 908348    |
  | Attila |           |
  | Tojo   |           |
  | Tommy  | 998110    |
  +--------+-----------+
  5 records returned

To extract the first through third fields and the fifth field (where field numbers start at "1" -- tip: use the list option to quickly determine field numbers), use this syntax for fields:

  $ tablify --fs ',' -f 1-3,5 people.dat 
  +--------+---------+-----------+------+
  | name   | rank    | serial_no | age  |
  +--------+---------+-----------+------+
  | George | General | 190293    | 64   |
  | Dwight | General | 908348    | 75   |
  | Attila | Hun     |           | 56   |
  | Tojo   | Emporor |           | 87   |
  | Tommy  | General | 998110    | 54   |
  +--------+---------+-----------+------+
  5 records returned

To select only the ones with six serial numbers, use a where clause:

  $ tablify --fs ',' -w 'serial_no=~/^\d{6}$/' people.dat
  +--------+---------+-----------+-----------+------+
  | name   | rank    | serial_no | is_living | age  |
  +--------+---------+-----------+-----------+------+
  | George | General | 190293    | 0         | 64   |
  | Dwight | General | 908348    | 0         | 75   |
  | Tommy  | General | 998110    | 1         | 54   |
  +--------+---------+-----------+-----------+------+
  3 records returned

To find Dwight's record, you would do this:

  $ tablify --fs ',' -w 'name eq "Dwight"' people.dat
  +--------+---------+-----------+-----------+------+
  | name   | rank    | serial_no | is_living | age  |
  +--------+---------+-----------+-----------+------+
  | Dwight | General | 908348    | 0         | 75   |
  +--------+---------+-----------+-----------+------+
  1 record returned

To find the name of all the people with a serial number who are living:

  $ tablify --fs ',' -f name -w 'is_living==1' -w 'serial_no>0' people.dat 
  +-------+
  | name  |
  +-------+
  | Tommy |
  +-------+
  1 record returned

To filter outside of program and simply format the results, use "-" as the last argument to force reading of STDIN (and probably assume no headers):

  $ grep General people.dat | tablify --fs ',' -f 1-3 --no-headers -
  +---------+--------+--------+
  | Field1  | Field2 | Field3 |
  +---------+--------+--------+
  | General | 190293 | 0      |
  | General | 908348 | 0      |
  | General | 998110 | 1      |
  +---------+--------+--------+
  3 records returned

When dealing with data lacking field names, you can specify "no-headers" and then refer to fields by number (starting at one), e.g.:

  $ tail -5 people.dat | tablify --fs ',' --no-headers -w '3 eq "General"' -
  +--------+--------+---------+--------+--------+
  | Field1 | Field2 | Field3  | Field4 | Field5 |
  +--------+--------+---------+--------+--------+
  | 64     | George | General | 190293 | 0      |
  | 75     | Dwight | General | 908348 | 0      |
  | 54     | Tommy  | General | 998110 | 1      |
  +--------+--------+---------+--------+--------+
  3 records returned

SEE ALSO

  • Text::RecordParser

  • Text::TabularDisplay

  • DBD::CSV

    Although I don't use this module, the idea was much the inspiration for this. I just didn't want to have to install DBI and DBD::CSV to get this kind of functionality. I think my interface is simpler.

COPYRIGHT

Copyright (C) 2004 Ken Y. Clark

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; version 2.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

AUTHOR

Ken Y. Clark <kclark@cshl.org>.