pyagg

Python Algorand GPU vanity address generator

Installation

Install from the repository

pip install git+https://github.com/dragmz/pyagg

Usage

Optimize batch size

pyagg-optimize

(hit ctrl+c to stop)

Optimizing batch size for device: NVIDIA GeForce GTX 950
Batch size range: 32 - 524224
Prefixes: AAAAAAAA
Max performance: 448615 keys/s, batch size: 157408
Max performance: 463908 keys/s, batch size: 38112
Max performance: 466800 keys/s, batch size: 351328
Save configuration (y/N):
Saving configuration to C:\Users\dragmz\.pyagg\config.json
Configuration saved

Run the generator

pyagg --prefix TEST --count 3 --benchmark

(Address 1),(Mnemonic 1)
(Address 2),(Mnemonic 2)
(Address 3),(Mnemonic 3)
Total: 2097152, matching: 3, time: 7.384147644042969, avg: 284007 keys/s

Lookup multiple prefixes at once

pyagg --prefix TEST,TEST2,TEST3 --count 10

Lookup prefixes from a file

pyagg --file prefixes.txt --count 10

Credits

This work has been performed with support from the Algorand Foundation xGov Grants Program.