unqlite-python
Python bindings for the UnQLite embedded NoSQL database
Runssource: GitHubhomepageCMITcommit b42c6aa4e53a
C, MIT licensed. The project labels itself: embedded database, nosql, python and unqlite.
unqlite-python runs. An Argusic agent installed it in 2.5 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
unqlite 1.2.0 builds and installs in a venv; all 53 unit tests pass; key/value store, transactions, cursors, Jx9 VM, and JSON document collections all work with real UnQLite databases (both in-memory and file-backed).
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 100 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.
- build fails: Python.h: No such file or directory (missing python3-dev headers, no root)0.8 minutes
- build fails: nested pyconfig.h include for x86_64-linux-gnu/python3.12/pyconfig.h not found0.3 minutes
- pip install fails with externally-managed-environment (PEP 668)0.2 minutes
- Install time
- 3 minutes
- Cold machine to finish
- 7 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- How the result was proved
- python -m unittest tests.py exited 0, 53 passed; key/value, transactions, cursors, VM/Jx9 document store, and collection APIs all exercised end-to-end against real in-memory and file-backed databases
- Model tokens used
- 48,523
- Exact commit tested
- b42c6aa4e53a
- 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
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 1, run . The verdict above comes from a different attempt, so read this as one session and not as the current result. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
print('Total test cases:', suite.countTestCases())
\" 2>&1 | tail -3" in /work/repo
succeeded in 403ms:
Ran 53 tests in 0.476s
OK
exec
/bin/sh -lc '/work/repo/venv/bin/python -m pytest tests.py -q 2>&1 || /work/repo/venv/bin/python -m…
succeeded in 410ms:
Ran 53 tests in 0.464s
OK
tokens used
48,523Replay 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.
- 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 did not, or is not known
- Took 2.5 minutes to install, slower than the median of the 3 comparable projects Argusic has measured.
Of the 4 embedded-database projects Argusic has installed and timed, unqlite-python was the 3rd fastest to reach a running state, and 4 of 4 reached one at all.
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 2.5 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
Topics (from GitHub)
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/unqlite-python)Questions
- Does unqlite-python run?
- Yes. unqlite-python runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test unqlite-python?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit b42c6aa4e53a. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test unqlite-python?
- The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does unqlite-python take to install?
- 2.5 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 unqlite-python need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing unqlite-python?
- 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.
- How does unqlite-python compare with the alternatives?
- Of the 4 embedded-database projects Argusic has installed and timed, unqlite-python was the 3rd fastest to reach a running state, and 4 of 4 reached one at all.
- Where is the evidence for unqlite-python?
- 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.