Flowfile
Flowfile is a visual ETL tool and Python library combining drag-and-drop workflows with Polars dataframes. Build data pipelines visually, define flows programmatically with a Polars-like API, and export to standalone Python code. Perfect for fast, intuitive data processing from development to production.
Runssource: GitHubPythonMITcommit ec12885c61af
Python, MIT licensed. The project labels itself: drag and drop, etl, etl pipeline, low code, no code, polars, python and tauri.
Flowfile runs. An Argusic agent installed it in 30 minutes and hit 1 error and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Flowfile 0.24.0-rc.1 installed with poetry; all 15206 non-Docker tests pass; core and worker servers start successfully on ports 63578 and 63579
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. 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.
- find_parent_directory('Flowfile') fails when repo root directory is not named 'Flowfile'5 minutes
- Install time
- 30 minutes
- Cold machine to finish
- 31 minutes
- Errors hit and fixed
- 1 hit, 1 fixed with no human help
- How the result was proved
- poetry run pytest flowfile_frame/tests: 1906 passed; flowfile_core/tests: 12505 passed; flowfile_worker/tests: 700 passed; flowfile_scheduler/tests: 39 passed; flowfile/tests: 56 passed; total 15206 tests passed, 334 skipped; curl http://localhost:63578/docs returned HTTP 200
- Model tokens used
- 612,472
- Exact commit tested
- ec12885c61af
- 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.
flowfile_core: 12505 passed flowfile_worker: 700 passed flowfile_scheduler: 39 passed flowfile: 56 passed Total: 15206 passed exec /bin/sh -lc '# Calculate time spent echo "Started around 14:03 UTC, completed around 14:33 UTC = ~30 minutes"' in /work/repo succeeded in 0ms: Started around 14:03 UTC, completed around 14:33 UTC = ~30 minutes tokens used 612,472
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 30 minutes.
- Recovered from all 1 error 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.
What did not, or is not known
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
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)
drag-and-dropetletl-pipelinelow-codeno-codepolarspythontaurivisual-etlvisual-programmingvue
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/flowfile)Questions
- Does Flowfile run?
- Yes. Flowfile runs. Argusic installed and launched it on a clean machine in 30 minutes, hitting 1 error on the way, and recorded the session.
- How did Argusic test Flowfile?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit ec12885c61af. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test Flowfile?
- The run that produced this verdict cost $0.14: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does Flowfile take to install?
- 30 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 Flowfile need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing Flowfile?
- 1 thing broke in the recorded run, and 1 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for Flowfile?
- 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.