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Fourteen test files, each its own __main__, and no way to run them but from
memory -- so in practice you ran the one you were working on and hoped. Worse,
nothing said which files need a licensed IDA and a real worker (minutes) and
which are pure stdlib (milliseconds), so the cheap ones nobody ran either.
tests/run.py runs the lot and prints one table. --fast selects only the suites
that need nothing, which is 257 checks in half a second under any python3 --
that's the one you run between edits.
The classification lives in the test files, not in a table here that would rot
the first time someone adds a test: each declares NEEDS_IDA at module scope and
run.py reads it with ast (it can't import them -- they run their suite at
import). A file without the marker is a hard error rather than a silent guess.
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Textbook Sugiyama, the same shape IDA's own graph uses: break cycles,
longest-path layering, dummy nodes, median/transposition ordering,
priority x-coords, then port-and-channel edge routing. Pure python -- no
IDA, no Textual, no I/O -- so it is tested offline in milliseconds with no
worker, which is the whole reason the hard part is kept out of the UI.
Dummy nodes are what make routing tractable: a long edge occupies real
horizontal space, so no edge ever has to cross a box. The tests assert
exactly that over a 128-function corpus, and it holds at 0.
Two things cost real time to find. A self-loop never drains its own
in-degree, so it deadlocks the ranking and collapses the graph into three
layers, 280 columns wide -- they are dropped from the layout and drawn as
a marker. And crossing minimisation is the entire runtime: recounting
globally per candidate swap is O(n^3) and took 20.4s on a 424-block
function, against 152ms for Fenwick inversion counting plus a local
O(deg*deg) swap delta.
The result is not a painted canvas -- that function is ~13M cells. It is
an index: per-row runs, bucketed vertical intervals, and point marks,
queried one row at a time.
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