Ethereum Vanity Address Filter

This Python script filters Ethereum addresses based on specific patterns often sought in vanity address generation. It supports multiprocessing for performance and writes matches to categorized .txt files.

🔍 What It Does

The script reads a list of Ethereum addresses (in the format: address privatekey on each line), then applies multiple pattern-matching filters to classify vanity-style addresses.

✅ Filters Included

Each matching address is saved into a separate file under the filtered_results/ directory.

Filter File	Description	Example Match
5same.txt	Address starts and ends with the same character repeated 5+ times	0xaaaaaa...aaaaa
mirror.txt	Starts and ends with the same exact byte pattern	0xabc123...abc123
reverse.txt	Ends with the reversed beginning	0x123abc...cba321
leading_repeat.txt	Starts with the same character repeated 9+ times	0xaaaaaaaaa...
any_repeat.txt	Contains 10+ consecutive repeated characters anywhere	0x1234bbbbbbbbbb5678
numeric_mirror.txt	Fully numeric and mirrored (start == end)	0x123456...123456
sequence.txt	Sequential patterns like 123456789 or 0123456789	0x123456789abcd...
startX_endY.txt	Starts and ends with 5+ same digits, but different (e.g. 00000...99999)	0x00000...99999
xyxyxy.txt	Repeating two-digit pattern	0x121212...121212
xxyxxy.txt	Custom pattern like 112233112233	0x112233...112233
3x4.txt	At least four blocks of the same digit repeated 3+ times	0x444...555...444...555
3x5.txt	Exactly five such 3-digit repetition blocks	Same as above, with exact count

📁 Input File Format

The input file should be located at:

data/addresses.txt

Each line must contain:

<ethereum_address> <private_key>

⚙️ Usage

Just run the script:

python3 filter_script.py

Output will be saved in:

filtered_results/

🚀 Performance

• Utilizes Python’s multiprocessing with 10 processes for fast filtering.
• Efficient for large address lists (e.g., 1M+ entries).

With the power of the Mac Mini M4 (10 CPU cores and 10 GPUs), the filter script can process and filter 6 million Ethereum addresses in just 12 seconds, making it a highly optimized solution for large-scale address filtering.