chart/AGENTS.md

Working on this repo

Tests earn their place by catching a real bug

When a bug is found, ask whether a unit test could reasonably have caught it. If yes, write that test with the fix. If no — a rendering artefact, a browser quirk, a data-source oddity — say so and don't add one.

The bar is "would this have failed before the fix, and would it fail again if someone reintroduced it". Tests that restate the implementation, assert constructor defaults, or exercise paths nothing depends on are noise; they make the suite slow to run and expensive to change, which is how a suite stops being trusted.

What has actually paid off here: bar aggregation and bucket boundaries, the store's replace-vs-append rules, level and alert arithmetic, parsing real market-data payloads (fixtures are trimmed real responses, not invented), and the invariants that would otherwise be silent — a comment must never become a level, a tick must never overwrite a settled bar, volume must be counted once.

Name the test after the failure, not the function: test_a_tick_cannot_overwrite _a_settled_bar beats test_put.

Where things run

The agent works on a remote machine over SSH. The user's browser runs on a different machine. Consequences, all learned the hard way:

• You cannot see the user's screen, console, or cursor. Screenshots and pasted console output are the only window into it. Browser extensions that drive "your" Chrome do not help — they attach to the machine the browser is on.
• Headless Chromium here renders on server hardware: different screen, window size and device pixel ratio from the user's. "Works in my headless run" is not evidence that it works for them. When a UI bug will not reproduce, match their viewport and deviceScaleFactor explicitly before concluding anything.
• The dev stack is served to them over the network (e.g. hera.local:8010), which is the same app the headless browser reaches as http://api:8000.

When a visual bug resists reproduction, prefer putting the numbers on screen in the app over asking for another console paste — one screenshot then carries the whole diagnosis.

Verify UI in a real browser

Chart bugs are invisible from the outside — the API, the socket and the frontend source can each be correct while the screen is wrong. Drive the Playwright container against the dev stack:

docker exec -i chart-playwright-1 node - <<'EOF'
const { chromium } = require('/usr/lib/node_modules/playwright');
// launch with args:['--lang=en-US'] — see below
EOF

Always launch Chromium with args: ['--lang=en-US']. The container has no usable locale, so Chromium reports en-US@posix, Intl throws, and the chart renders as a blank canvas that looks exactly like a broken app.

window.__chart is a deliberate debug handle. Querying it separates "the data is missing" from "the data is off-screen" — which is how a viewport bug that three passing API checks had missed was finally found.

Diagnostic mode

Chart geometry bugs live in the browser, which is usually on a different machine from whoever is debugging them. Rather than asking for console pastes:

open the chart with ?diag=1          # remembered until ?diag=0
docker compose logs api | grep SNAPDBG

With it on, every snap the trendline tool computes is posted to /api/debug/snap and logged server-side — the cursor's time, price and x, the snapped time and price, how many bars were held, the first and last bar, and the chart's width. Throttled to about one a second. It reads the client's own numbers, which is exactly what "works in my headless run" cannot tell you.

Extend it when the next geometry puzzle appears; the endpoint takes whatever fields SnapReport declares.

Running tests

docker exec chart-api-1 sh -c "cd /app && python -m pytest -q"

pytest + pytest-asyncio, declared in requirements-dev.txt. Tests live in tests/, import from app.*, and use tmp_path for anything that persists. Async paths are driven with asyncio.run(...) directly rather than async test markers.

Things that will cost you an hour

• Never write scratch .py files into the repo root. It is bind-mounted, so --reload restarts the app, and startup takes ~82 seconds. Pipe throwaway scripts over stdin instead: docker exec -i chart-api-1 python - <<'EOF'. Screenshots into artifacts/ are safe; only .py triggers the reloader.
• Dev and production keep separate drawing stores. Dev writes data/manual_lines.json; production has its own Coolify volume. A fix that "didn't land" is often the other store.
• Rebuild the image after touching requirements.txt. The bind mount makes source edits look live while an added dependency is simply absent.
• A deploy resets alert cooldowns, so production may re-alert on whatever price is sitting on. There is no durable state yet.
• Times are epoch seconds, UTC, everywhere. Only the display is localised — never shift the stored values.