cut

Overview

The cut command extracts specific columns or fields from lines of text. It’s useful for processing structured data like CSV files, logs, and delimited text.

Syntax

cut [options] [file...]

Common Options

Option	Description
-f list	Select fields
-d char	Field delimiter
-c list	Select characters
-b list	Select bytes
-s	Suppress lines without delimiters
--complement	Invert selection
--output-delimiter=string	Output delimiter

Field/Character Lists

Format	Description
1	Field/character 1
1,3,5	Fields 1, 3, and 5
1-5	Fields 1 through 5
1-	Field 1 to end
-5	First 5 fields
1,3-5,7	Mixed selection

Key Use Cases

1. Extract CSV columns
2. Process log files
3. Parse structured text
4. Data extraction
5. Text manipulation

Examples with Explanations

Example 1: Extract Fields

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

Extracts fields 1 and 3 from CSV file

Example 2: Extract Characters

cut -c 1-10 file.txt

Extracts first 10 characters from each line

Example 3: Custom Delimiter

cut -f 2 -d ':' /etc/passwd

Extracts usernames from passwd file

Working with Different Delimiters

Common delimiters: - , - Comma (CSV) - : - Colon (passwd, PATH) - \t - Tab (TSV) - - Space - | - Pipe

Common Usage Patterns

1. Extract usernames:

   cut -f 1 -d ':' /etc/passwd

2. Get file extensions:

   ls | cut -d '.' -f 2-

3. Process CSV data:

   cut -f 2,4,6 -d ',' data.csv

Advanced Operations

1. Suppress delimiter-less lines:

   cut -f 1 -d ',' -s file.csv

2. Change output delimiter:

   cut -f 1,2 -d ',' --output-delimiter='|' data.csv

3. Complement selection:

   cut -f 1,3 --complement -d ',' data.csv

Character vs Field Extraction

Character extraction (-c): - Fixed position extraction - Useful for fixed-width data - Byte-based positioning

Field extraction (-f): - Delimiter-based extraction - Variable width fields - More flexible for structured data

Performance Analysis

• Very fast operation
• Minimal memory usage
• Streaming operation
• Efficient for large files
• Good pipeline performance

Related Commands

• awk - More powerful field processing
• grep - Pattern matching
• sed - Stream editing
• sort - Sort lines
• uniq - Remove duplicates

Additional Resources

• GNU cut manual
• Cut Command Examples

Best Practices

1. Specify delimiters explicitly
2. Test field numbers with sample data
3. Use character extraction for fixed-width data
4. Consider using awk for complex operations
5. Handle missing delimiters appropriately

Common Patterns

1. Extract IP addresses:

   cut -f 1 -d ' ' access.log

2. Get file sizes:

   ls -l | cut -c 30-40

3. Process PATH variable:

   echo $PATH | cut -f 1 -d ':'

Integration Examples

1. With sort and uniq:

   cut -f 1 -d ',' data.csv | sort | uniq -c

2. With grep:

   grep "error" log.txt | cut -f 1 -d ' '

3. Pipeline processing:

   cat data.txt | cut -f 2,4 -d '|' | sort

Troubleshooting

1. Wrong field numbers
2. Delimiter not found
3. Character encoding issues
4. Empty fields handling
5. Multi-character delimiters (use awk instead)