cut Command Linux: Extract and Process Columns from Text Files Efficiently

The cut command is one of the most powerful and versatile text processing utilities in Linux and Unix systems. It allows you to extract specific portions of text from files or input streams by selecting columns, fields, or character ranges. Whether you’re processing CSV files, log files, or any structured text data, the cut command provides an efficient way to slice and dice your data exactly how you need it.

What is the cut Command?

The cut command is a command-line utility that extracts sections from each line of input. It can cut text based on:

• Character positions – Extract specific characters from each line
• Fields/columns – Extract fields separated by delimiters
• Byte positions – Extract specific bytes (useful for binary data)

Basic Syntax

cut [OPTIONS] [FILE...]

If no file is specified, cut reads from standard input, making it perfect for use in pipelines.

Essential Options and Parameters

Character-based Extraction

Use the -c option to extract specific character positions:

cut -c [RANGE] [FILE]

Example: Extracting Characters

Let’s create a sample file to demonstrate:

echo -e "Hello World\nLinux Commands\nText Processing" > sample.txt

Extract the first 5 characters from each line:

cut -c 1-5 sample.txt

Output:

Hello
Linux
Text

Extract specific character positions (1st, 3rd, and 5th characters):

cut -c 1,3,5 sample.txt

Output:

Hlo
Lnx
Tt

Field-based Extraction

Use the -f option to extract fields separated by delimiters:

cut -f [FIELD_LIST] -d [DELIMITER] [FILE]

Example: Working with CSV Data

Create a CSV file for demonstration:

echo -e "Name,Age,City,Country\nJohn,25,New York,USA\nAlice,30,London,UK\nBob,22,Tokyo,Japan" > employees.csv

Extract the first column (names):

cut -f 1 -d ',' employees.csv

Output:

Name
John
Alice
Bob

Extract multiple fields (Name and City):

cut -f 1,3 -d ',' employees.csv

Output:

Name,City
John,New York
Alice,London
Bob,Tokyo

Advanced Usage Examples

Working with Tab-delimited Files

The default delimiter for cut is the tab character. Create a tab-separated file:

echo -e "Product\tPrice\tQuantity\nLaptop\t1200\t5\nMouse\t25\t50\nKeyboard\t75\t20" > inventory.txt

Extract product names and quantities:

cut -f 1,3 inventory.txt

Output:

Product	Quantity
Laptop	5
Mouse	50
Keyboard	20

Using Ranges

You can specify ranges using the hyphen (-) operator:

• 1-5 – Characters/fields 1 through 5
• 1- – From character/field 1 to the end
• -5 – From the beginning to character/field 5

Example: Character Ranges

echo "Linux System Administration" | cut -c 7-12

Output:

System

Extract from the 7th character to the end:

echo "Linux System Administration" | cut -c 7-

Output:

System Administration

Processing System Files

The cut command is excellent for extracting information from system files like /etc/passwd:

# Extract usernames (1st field)
cut -f 1 -d ':' /etc/passwd | head -5

Extract usernames and home directories:

cut -f 1,6 -d ':' /etc/passwd | head -5

Combining with Other Commands

The real power of cut shines when combined with other commands in pipelines:

Extract Running Process Names

ps aux | cut -c 61- | head -10

This extracts the command column from the ps output.

Process Log Files

# Extract timestamps from log files (assuming space-delimited)
cat /var/log/syslog | cut -d ' ' -f 1-3 | head -5

Practical Use Cases

1. Extract Email Addresses from a List

If you have a file with “Name <[email protected]>” format:

echo -e "John Doe <[email protected]>\nJane Smith <[email protected]>" > contacts.txt
cut -d '<' -f 2 contacts.txt | cut -d '>' -f 1

Output:

[email protected]
[email protected]

2. Extract IP Addresses from Access Logs

# Assuming Apache/Nginx log format
echo '192.168.1.100 - - [25/Aug/2025:12:18:00 +0000] "GET /index.html"' | cut -d ' ' -f 1

Output:

192.168.1.100

3. Process Configuration Files

Extract values from configuration files:

echo -e "server_name=web01\nport=8080\ndatabase=mydb" > config.conf
cut -d '=' -f 2 config.conf

Output:

web01
8080
mydb

Important Options and Flags

Advanced Examples

Using Complement Option

The --complement option selects everything except the specified fields:

echo "one,two,three,four,five" | cut -d ',' --complement -f 2,4

Output:

one,three,five

Custom Output Delimiter

Change the output delimiter when extracting fields:

echo "apple,banana,cherry" | cut -d ',' -f 1,3 --output-delimiter=" | "

Output:

apple | cherry

Processing Only Lines with Delimiter

Use -s to suppress lines that don’t contain the delimiter:

echo -e "name:john\nage\nemail:[email protected]" | cut -s -d ':' -f 2

Output:

john
[email protected]

Common Pitfalls and Solutions

1. Handling Spaces in Delimited Data

When working with space-delimited data that might have extra spaces:

# Wrong approach - might not work with extra spaces
echo "john  doe  30" | cut -d ' ' -f 2

# Better approach - use tr to squeeze spaces first
echo "john  doe  30" | tr -s ' ' | cut -d ' ' -f 2

2. Empty Fields

Cut preserves empty fields, which might cause issues:

echo "a,,c,d" | cut -d ',' -f 2

This returns an empty line. Be aware of this behavior when processing data with missing values.

3. Multi-character Delimiters

Cut only supports single-character delimiters. For multi-character delimiters, use awk instead:

# This won't work as expected
echo "data::separated::by::double::colons" | cut -d '::' -f 2

# Use awk instead
echo "data::separated::by::double::colons" | awk -F '::' '{print $2}'

Performance Tips

1. Use character positions when possible – Character-based cutting is generally faster than field-based cutting
2. Specify exact ranges – Avoid open-ended ranges like 1- when you know the exact positions
3. Combine with head/tail – When processing large files, combine with head or tail to limit processing

Integration with Shell Scripts

Here’s a practical shell script example that processes a CSV file:

#!/bin/bash
# Script to extract and format employee data

CSV_FILE="employees.csv"

echo "Employee Names:"
cut -f 1 -d ',' "$CSV_FILE" | tail -n +2

echo -e "\nAges and Cities:"
cut -f 2,3 -d ',' "$CSV_FILE" | tail -n +2 | while IFS=',' read -r age city; do
    echo "Age: $age, City: $city"
done

Conclusion

The cut command is an indispensable tool for text processing in Linux environments. Its ability to extract specific portions of text makes it perfect for data analysis, log processing, and system administration tasks. While it has limitations like single-character delimiters, its simplicity and efficiency make it the go-to choice for straightforward text extraction operations.

Master the cut command by practicing with different file formats and combining it with other Unix utilities. Remember that cut works best with structured, consistently formatted data, and when you need more complex text processing, consider combining it with tools like awk, sed, or grep for more powerful text manipulation capabilities.

Whether you’re extracting columns from CSV files, processing log entries, or manipulating configuration files, the cut command provides a clean, efficient solution that integrates seamlessly into shell scripts and command pipelines.