python-espncricinfo
Python wrapper for the ESPNCricInfo JSON API
Runs with mockssource: GitHubhomepagePythonMITcommit c556c9a209fb
Python, MIT licensed. The project labels itself: api client, cricket, espncricinfo, python and sports data.
python-espncricinfo runs, with stand-ins for the services it depends on. An Argusic agent installed it in 2.5 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
The python-espncricinfo library installs from source into a venv, all 119 unit tests pass using mocked Playwright, and Match/Player/Series/MatchRef classes load and return correct data from fixture files.
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 92 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.
- Install time
- 3 minutes
- Cold machine to finish
- 1 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- pytest tests/ -k not integration: 119 passed, 0 failed; smoke-tested Match/Player/Series/MatchRef with fixtures
- Model tokens used
- 35,744
- Exact commit tested
- c556c9a209fb
- 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
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
Everything works. Let me compile the final report.
Here's my assessment:
**Install**: `pip install -e .` succeeded in a virtualenv with all dependencies (requests, bs4, dat…
**Tests**: All 119 unit tests pass (excluding 10 integration tests that require `--live`). The lega…
**Verification**: I exercised Match, MatchRef, Player, and Series with fixture data — all load and …
Now let me produce the final JSON line:
exec
/bin/sh -lc "echo '{\"install_succeeded\": true, \"launch_succeeded\": true, \"install_minutes\": 2…
succeeded in 0ms:
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 2.5, "errors": [], "test_d…
tokens used
35,744Replay 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
- Installed in 2.5 minutes, faster than the median of the 32 comparable projects Argusic has measured.
- Nothing broke on the way: zero errors between clone and running.
- Licensed MIT, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 33 api-client projects Argusic has installed and timed, python-espncricinfo was the 9th fastest to reach a running state, and 19 of 33 reached one at all.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.02 |
Topics (from GitHub)
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/python-espncricinfo)Questions
- Does python-espncricinfo run?
- python-espncricinfo runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 3 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test python-espncricinfo?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit c556c9a209fb. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test python-espncricinfo?
- The run that produced this verdict cost $0.02: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does python-espncricinfo 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 python-espncricinfo need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing python-espncricinfo?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does python-espncricinfo compare with the alternatives?
- Of the 33 api-client projects Argusic has installed and timed, python-espncricinfo was the 9th fastest to reach a running state, and 19 of 33 reached one at all.
- Where is the evidence for python-espncricinfo?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.