tablify - Man Page
turn a delimited text file into a text table
Synopsis
tablify [options] file
Options:
-h|--help Show help -c|--comment Define the beginning of a (single-line) comment -n|--no-headers Assume first line is data, not headers --no-pager Do not use $ENV{'PAGER'} even if defined --strip-quotes Strip " or ' around fields -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 =~ -v|--vertical Show records vertically -i|--limit=n Limit to given number of 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") --as-html Create an HTML table instead of plain text --headers Comma-separated list of names matching the number of columns
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 | +--------+---------+--------+--------+--------+ | George | General | 190293 | 0 | 64 | | Dwight | General | 908348 | 0 | 75 | | Tommy | General | 998110 | 1 | 54 | +--------+---------+--------+--------+--------+ 3 records returned
If your file has many fields which are hard to see across the screen, consider using the vertical display with "-v" or "--vertical", e.g.:
$ tablify --fs ',' -v --limit 1 people.dat ************ Record 1 ************ name: George rank: General serial_no: 190293 is_living: 0 age : 64 1 record returned
See Also
- Text::RecordParser
- Text::TabularDisplay
DBD::CSV
Although I don't DBD::CSV 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.
Author
Ken Youens-Clark <kclark@cpan.org>.
License and Copyright
Copyright (C) 2006-10 Ken Youens-Clark. All rights reserved.
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.