textual
The lean application framework for Python. Build sophisticated user interfaces with a simple Python API. Run your apps in the terminal and a web browser.
Runssource: GitHubhomepagePythonMITcommit 06dbeef4bb70
Python, MIT licensed. The project labels itself: cli, framework, python, rich, terminal and tui.
textual runs. An Argusic agent installed it in 2 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Textual 8.2.8 with syntax extras is installed; the full test suite (3459 tests) passes; the demo app and a minimal app both run and render correctly.
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 73.3 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.
- NO_COLOR=1 env var set in container suppresses Rich ANSI escape codes, causing ~408 test failures3 minutes
- tree-sitter syntax extras not installed, 3 syntax-marked tests fail2 minutes
- Install time
- 2 minutes
- Cold machine to finish
- 14 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- pytest tests/ -n 16 returned 3459 passed, 3 skipped, 4 xfailed, 1 xpassed
- Model tokens used
- 49,435
- Exact commit tested
- 06dbeef4bb70
- 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.
All 3459 tests pass (3 skipped, 4 xfailed, 1 xpassed). Let me now produce the final report.
The project is **Textual** by Textualize — a Python TUI framework. Here's what happened:
## Errors Found and Fixed
**Error 1**: `NO_COLOR=1` was set in the container environment. Rich (the rendering library) respec…
- **Fix**: Unset `NO_COLOR` before running tests: `env -u NO_COLOR poetry run pytest ...`
**Error 2**: Tree-sitter syntax packages (for syntax highlighting) are optional extras not installe…
- **Fix**: `poetry install --extras syntax`
## Verification
- **Install**: `poetry install` and `poetry install --extras syntax` both succeeded (textual 8.2.8 …
- **Full test suite**: `pytest tests/ -n 16` — **3459 passed, 3 skipped, 4 xfailed, 1 xpassed** in …
- **App launched**: `poetry run python -m textual` rendered its interactive TUI successfully on the…
- **App rendered correctly**: A minimal `TestApp(Label('Hello World'))` produced output containing …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 24 comparable projects Argusic has measured.
- Recovered from all 2 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 3 times, so the result is not a one-off.
Of the 25 cli projects Argusic has installed and timed, textual was the 6th fastest to reach a running state, and 23 of 25 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.
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/textual)Questions
- Does textual run?
- Yes. textual runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test textual?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 06dbeef4bb70. 3 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test textual?
- The run that produced this verdict cost $0.05: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does textual 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 textual need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing textual?
- 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does textual compare with the alternatives?
- Of the 25 cli projects Argusic has installed and timed, textual was the 6th fastest to reach a running state, and 23 of 25 reached one at all.
- Where is the evidence for textual?
- All 3 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.