jc

CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts.

Runssource: GitHubPythonMITcommit 8290734a87a3

Python, MIT licensed. The project labels itself: bash, bash scripting, cli, command line, command line interface, command line tool, convert and json.

jc runs. An Argusic agent installed it in 0 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

The jc package v1.25.7 is installed in a Python 3.12.3 venv, the CLI produces JSON from command output, the Python library API works, and all 1557 unit tests pass.

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

verdict
Runs
Argusic Score
100 / 100
cost of the verifying run
$0.01 (measured)
recorded runs
2
last tested
stars
8,682
forks
256
open issues
28
watchers
29
size
17 MB
created
last push

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.

Install time
under a minute
Cold machine to finish
2 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
TZ=PST8PDT venv/bin/python -m unittest returned OK, 1557 passed, 7 skipped; venv/bin/jc ls returned valid JSON for 31 files; jc.parse() library call returned correct dict
Model tokens used
20,037
Exact commit tested
8290734a87a3
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 2, run , the attempt that decided the verdict above. 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.

**Tests** – `python -m unittest` ran 1557 tests in 10.3s, all passed (7 skipped for expected reason…
**CLI** – `venv/bin/jc --help` prints usage, `venv/bin/jc ls` returns valid JSON output listing dir…
**Library** – `jc.parse('ls', ...)` returns correct Python dicts, `jc.__version__` is `1.25.7`.
No errors occurred at any step. No third-party keys are needed; jc works entirely offline parsing c…
tokens used
20,037
Everything installed and verified cleanly. Here's the summary:
**Install** – Created a venv, `pip install -e .` succeeded with all three dependencies (ruamel.yaml…
**Tests** – `python -m unittest` ran 1557 tests in 10.3s, all passed (7 skipped for expected reason…
**CLI** – `venv/bin/jc --help` prints usage, `venv/bin/jc ls` returns valid JSON output listing dir…
**Library** – `jc.parse('ls', ...)` returns correct Python dicts, `jc.__version__` is `1.25.7`.
No errors occurred at any step. No third-party keys are needed; jc works entirely offline parsing c…

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 0 minutes, faster than the median of the 4 comparable projects Argusic has measured.
  • Nothing broke on the way: zero errors between clone and running.
  • 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.

Of the 5 bash projects Argusic has installed and timed, jc was the 1st fastest to reach a running state, and 4 of 5 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 0 minutes after the clone.
  • Following its own README: the documented path worked with nothing to fix.

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 byattemptoutcomescorecost USDwhen
Argusic Runner2/3Runs100.000.01
Argusic Runner1/3Runs100.000.02

Topics (from GitHub)

bashbash-scriptingclicommand-linecommand-line-interfacecommand-line-toolconvertjsonlinuxparserspythonpython-libraryscriptingserializeshell-scriptingyaml

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/jc.svg)](https://argusic.com/subject/jc)

Questions

Does jc run?
Yes. jc runs. Argusic installed and launched it on a clean machine in 0 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test jc?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit 8290734a87a3. 2 attempts are recorded, and the full method is on the methodology page.
What did it cost to test jc?
The run that produced this verdict cost $0.01: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does jc take to install?
0 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 jc need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing jc?
Nothing did, in the recorded run: zero errors between clone and running.
How does jc compare with the alternatives?
Of the 5 bash projects Argusic has installed and timed, jc was the 1st fastest to reach a running state, and 4 of 5 reached one at all.
Where is the evidence for jc?
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.

Discussion