I'm a pentester and need help optimizing my Python script for cracking passwords. I've got a large wordlist, but it's cluttered with duplicates and nonsensical lines. I want a script that not only cleans this up but is also efficient enough to handle new wordlists in the future. I initially thought about using SQLite because I'm familiar with it, but I recently heard about LMDB. My script works fine with smaller files, but performance drops noticeably with files over 500MB. I'm looking for tips on how to enhance the script's speed and efficiency. Full code is available for reference!
5 Answers
If speed is a priority, remember that Python isn't the fastest language. Have you thought about switching to a compiled language like Go? It could offer much better performance for your needs.
You might want to try running Postgres in Docker to manage your wordlist. It's great at handling duplicates and scales well. If you need quick cleanup, that could simplify your process a lot!
Thanks for the suggestion! I'm leaning towards Postgres—it seems like a solid choice for this.
Consider using a profiler like pyinstrument to identify what's slowing down your script. It’s likely the database operations that are taking up most of your processing time. Also, instead of reading files line by line, try processing them in chunks. That can significantly speed things up!
Absolutely! Using a profiler is critical—it tells you exactly where the bottlenecks are. And yes, chunking the reads will definitely improve speed!
Instead of relying solely on Python’s capabilities, consider using tools like DuckDB for processing. They can handle larger datasets efficiently and come with Python bindings, so you can integrate it easily. Also, Linux tools for sorting files can be a game changer too.
I appreciate the tip! Thinking outside the Python box might just lead me to the solution I need.
If you want to stick with Python but need better performance, have you tried using PyPy? It can greatly speed up execution. Also, make sure you're on Python 3.13 or later for performance improvements, as newer versions include JIT compilation features.
Yes, I've heard good things about PyPy! I'll definitely give that a shot.
True, but let's remember that Python can still be optimized. You've already got a starting point, so consider enhancing the existing code before a full rewrite.