perf: avoid redundant work in Graph.transitive_closure - #1015
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The adjacency map is built over every edge before the traversal starts, which an empty node set never needs. Return early instead: on a 20k-node, 2M-edge graph an empty closure drops from ~1.3s to microseconds. Resolve `reverse` to a pair of tuple indices once rather than branching on it per edge in both loops, worth 1.1-1.4x on sparse graphs. Accept a frozenset in the input assert, since Graph.nodes is itself a frozenset and g.transitive_closure(g.nodes) previously tripped it. The four worked examples in the docstring had forward and reverse swapped. They have been wrong since 2eec861 imported the module in 2019, were never covered by a test, and contradict the prose above them, which was correct. Add coverage for the diamond, frozenset and unknown-node paths.
Merging this PR will improve performance by 36.14%
Performance Changes
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #1015 +/- ##
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+ Coverage 77.47% 77.50% +0.03%
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Files 132 132
Lines 12552 12561 +9
Branches 1506 1507 +1
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+ Hits 9725 9736 +11
+ Misses 2439 2438 -1
+ Partials 388 387 -1 ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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The adjacency map is built over every edge before the traversal starts, which an empty node set never needs. Return early instead: on a 20k-node, 2M-edge graph an empty closure drops from ~1.3s to microseconds.
Resolve
reverseto a pair of tuple indices once rather than branching on it per edge in both loops, worth 1.1-1.4x on sparse graphs. Accept a frozenset in the input assert, since Graph.nodes is itself a frozenset and g.transitive_closure(g.nodes) previously tripped it.The four worked examples in the docstring had forward and reverse swapped. They have been wrong since 2eec861 imported the module in 2019, were never covered by a test, and contradict the prose above them, which was correct.
Add coverage for the diamond, frozenset and unknown-node paths.