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Text Duplicate Remover Examples
The Text Duplicate Remover eliminates duplicate lines from text, keeping only the first occurrence of each unique line. Below are practical examples for cleaning lists, log files, URL sets, and data exports.
Basic Duplicate Removal
// Input
apple
banana
apple
cherry
banana
date
cherry
// Output (duplicates removed, order preserved)
apple
banana
cherry
date
The first occurrence of each line is kept. Subsequent duplicates are removed. The original order is preserved.
URL List Deduplication
// Input (URLs from multiple crawls)
https://example.com/page-1
https://example.com/page-2
https://example.com/page-1
https://example.com/page-3
https://example.com/page-2
https://example.com/page-4
https://example.com/page-1
// Output (unique URLs only)
https://example.com/page-1
https://example.com/page-2
https://example.com/page-3
https://example.com/page-4
// Stats: 7 lines → 4 unique (3 duplicates removed)
Case-Insensitive Deduplication
// Input
Hello World
hello world
HELLO WORLD
Hello World
Goodbye
// Case-sensitive output (all kept — different cases)
Hello World
hello world
HELLO WORLD
Goodbye
// Case-insensitive output (first occurrence kept)
Hello World
Goodbye
Log File Deduplication
// Input (repeated log entries)
[ERROR] Connection timeout to database
[INFO] Request received: GET /api/users
[ERROR] Connection timeout to database
[ERROR] Connection timeout to database
[INFO] Request received: GET /api/users
[WARN] Cache miss for key: user_42
[ERROR] Connection timeout to database
// Output (unique log lines)
[ERROR] Connection timeout to database
[INFO] Request received: GET /api/users
[WARN] Cache miss for key: user_42
// Stats: 7 lines → 3 unique (4 duplicates removed)
Whitespace-Normalized Deduplication
// Input (same content, different whitespace)
apple
apple
apple
apple
// With trim whitespace enabled — all treated as duplicates:
apple
// Without trim — all kept (different leading/trailing spaces):
apple
apple
apple
apple
Email List Cleanup
// Input (compiled from multiple sources)
alice@example.com
bob@example.com
alice@example.com
carol@example.com
BOB@EXAMPLE.COM
dave@example.com
alice@example.com
// Case-insensitive output
alice@example.com
bob@example.com
carol@example.com
dave@example.com
// Stats: 7 lines → 4 unique (3 duplicates removed)
Deduplicate and Sort
// Input
cherry
apple
banana
apple
date
cherry
// Output (deduplicated + sorted alphabetically)
apple
banana
cherry
date
CSV Data Deduplication
// Input
id,name,email
1,Alice,alice@example.com
2,Bob,bob@example.com
1,Alice,alice@example.com
3,Carol,carol@example.com
2,Bob,bob@example.com
// Output (duplicate rows removed)
id,name,email
1,Alice,alice@example.com
2,Bob,bob@example.com
3,Carol,carol@example.com
Empty Line Handling
// Input
Section One
Content here
Section Two
Content here
// Remove all empty lines:
Section One
Content here
Section Two
Content here
// Keep one empty line between sections:
Section One
Content here
Section Two
Content here
// Treat empty lines as duplicates (keep first):
Section One
Content here
Section Two
Content here
Programming: Deduplicate in Code
// JavaScript
const lines = text.split('\n');
const unique = [...new Set(lines)];
const result = unique.join('\n');
// Python
lines = text.splitlines()
seen = set()
unique = []
for line in lines:
if line not in seen:
seen.add(line)
unique.append(line)
result = '\n'.join(unique)
// Case-insensitive Python
seen = set()
unique = []
for line in lines:
key = line.strip().lower()
if key not in seen:
seen.add(key)
unique.append(line)
Deduplication Statistics
- Original line count: total lines in input
- Unique lines: lines kept in output
- Duplicates removed: original count minus unique count
- Duplicate rate: (duplicates / original) × 100%
A high duplicate rate (over 20%) often signals a data quality issue worth investigating at the source.
Common Use Cases
- Clean URL lists from web crawlers
- Deduplicate email or subscriber lists
- Remove repeated log entries
- Clean data exports before analysis
- Merge lists from multiple sources and remove overlaps
- Prepare unique keyword lists for SEO or search
- Remove duplicate lines from configuration files
Paste your text into the Text Duplicate Remover, choose your options, and get a clean unique list instantly.