RandPyPwMan
Random Python password generator and manager.
Runssource: GitHubhomepagePythonMITcommit 4bb971918130
Python, MIT licensed. The project labels itself: gui, open source, password manager, passwords and python.
RandPyPwMan runs. An Argusic agent installed it in 8 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Python 3.12 venv with pyperclip, cryptography, and bcrypt installed; tkinter works via extracted .deb libraries; the password manager GUI launches on the virtual display and creates its SQLite databases on first run.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 60 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- python3-tk not installed (no tkinter module)5 minutes
- pip install tk (PyPI stub) did not actually provide tkinter1 minute
- source command not available in /bin/sh
- Install time
- 8 minutes
- Cold machine to finish
- 6 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- How the result was proved
- timeout 8 python main.py ran on Xvfb display :99, exited 0 with no stderr; 10 standalone tests covering bcrypt auth, Fernet encryption/decryption, CRUD operations, settings, password generation, and master password change all passed
- Model tokens used
- 217,187
- Exact commit tested
- 4bb971918130
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
ps -p $PID -o pid,state,etime,cmd --no-headers 2>/dev/null || echo "process not running" kill $PID 2>/dev/null wait $PID 2>/dev/null echo "--- App was running during the 4-second window ---"' in /work/repo succeeded in 3955ms: --- ps --- 5445 S 00:04 /usr/bin/bash -c cd /work/repo && . .venv/bin/activate && LD_LIBRARY_PATH=".v… --- App was running during the 4-second window --- Now I have everything I need to produce the final report. Let me compile it. tokens used 217,187 Now I have everything I need to produce the final report. Let me compile it.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Installed in 8 minutes.
- Recovered from all 3 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
- Measured 2 times, so the result is not a one-off.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- A quick evaluation: it was running 8 minutes after the clone.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Runs | 100.00 | 0.04 | |
| Argusic Runner | 1/3 | Did not run | 20.00 | 0.05 |
Topics (from GitHub)
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/randpypwman)Questions
- Does RandPyPwMan run?
- Yes. RandPyPwMan runs. Argusic installed and launched it on a clean machine in 8 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test RandPyPwMan?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4bb971918130. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test RandPyPwMan?
- The run that produced this verdict cost $0.04: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does RandPyPwMan take to install?
- 8 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does RandPyPwMan need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing RandPyPwMan?
- 3 things broke in the recorded run, and 3 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for RandPyPwMan?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.