tablifyp - Online in the Cloud

PROGRAM:

NAME

tablify - 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

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