prefect

Prefect is a workflow orchestration framework for building resilient data pipelines in Python.

Runssource: GitHubhomepagePythonApache-2.0commit 148e99781fb0

Python, Apache-2.0 licensed. The project labels itself: automation, data, data engineering, data ops, data science, infrastructure, ml ops and observability.

prefect runs. An Argusic agent installed it in 2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

Prefect 3.6.24 is installed in a .venv, imports cleanly, the server starts and responds on /api/health with 200, and 840 core tests pass when run with uv run pytest.

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 96 of 100 (the mean of this project's run scores).

At a glance

verdict
Runs
Argusic Score
96 / 100
cost of the verifying run
$0.06 (measured)
recorded runs
2
last tested
stars
24,141
forks
2,643
open issues
892
watchers
195
size
247 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
2 minutes
Cold machine to finish
22 minutes
Errors hit and fixed
0 hit, 0 fixed with no human help
How the result was proved
uv run -m pytest tests/test_flows.py tests/test_tasks.py tests/test_states.py --tb=short -v -n1 → 840 passed, 11 skipped, 2 xfailed (4m55s). Server: prefect server start on 127.0.0.1:4201, curl /api/health returned 200.
Model tokens used
83,248
Exact commit tested
148e99781fb0
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 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.

SKIPPED [1] tests/test_flows.py:1262: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:1276: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:1469: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:1560: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:2152: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:2239: Fails with new engine, passed on old engine
SKIPPED [1] tests/test_flows.py:2888: Fails with new engine, passed on old engine
============ 840 passed, 11 skipped, 2 xfailed in 294.67s (0:04:54) ============
840 passed, 11 skipped, 2 xfailed — all clean. Let me compile the final result.
tokens used
83,248
840 passed, 11 skipped, 2 xfailed — all clean. Let me compile the final result.

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 2 minutes, faster than the median of the 36 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 Apache-2.0, as reported by its host.
  • Measured 2 times, so the result is not a one-off.

Of the 37 automation projects Argusic has installed and timed, prefect was the 13th fastest to reach a running state, and 25 of 37 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 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 Runner2/3Runs with mocks92.000.17
Argusic Runner1/3Runs100.000.06

Topics (from GitHub)

automationdatadata-engineeringdata-opsdata-scienceinfrastructureml-opsobservabilityorchestrationpipelineprefectpythonworkflowworkflow-engine

Embed the badge

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

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

Questions

Does prefect run?
Yes. prefect runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test prefect?
On a fresh, disposable machine, with every command recorded and the repository pinned at commit 148e99781fb0. 2 attempts are recorded, and the full method is on the methodology page.
What did it cost to test prefect?
The run that produced this verdict cost $0.06: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does prefect take to install?
2 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 prefect need a GPU?
Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing prefect?
Nothing did, in the recorded run: zero errors between clone and running.
How does prefect compare with the alternatives?
Of the 37 automation projects Argusic has installed and timed, prefect was the 13th fastest to reach a running state, and 25 of 37 reached one at all.
Where is the evidence for prefect?
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