WIP: dense CallSpec, lazy NodeKeywords, deferred TopRequest

[RonnyPfannschmidt]

Summary

• WIP / experimental exploration of collection memory for large parametrized suites (related to Very large test suites take *far* too much RAM #619).
• Store CallSpec2 densely as parallel tuples (_argnames / _values / _indices / _scopes) with tuple marks, exposing dict-like views via _CallSpecMap.
• Make NodeKeywords lazy: derive node.name, markers, function attributes, and callspec.id on read instead of eagerly copying into a per-item dict.
• Defer TopRequest until first access (None → construct; False still means cleared after a run).
• Add bench/collection_memory.py to measure RSS delta per collected item.

Local numbers (parametrized ints, --collect-only)

build	items	B/item
main	50k	~2860
this branch	50k	~2120 (−26%)
this branch	100k	~1910

python bench/collection_memory.py
python bench/collection_memory.py --counts 50000,100000 --json

Test plan

• python bench/collection_memory.py --counts 1000,10000,50000,100000
• pytest testing/test_mark.py testing/python/metafunc.py testing/python/fixtures.py::TestRequestBasic -q
• Smoke: collect + run multi-arg parametrize and -k selection
• Broader CI once ready to leave draft

Notes

• No changelog yet (experiment).
• Nodeid interning intentionally out of scope (follow-up after new nodeid classes).
• Further density likely still needs compact single-arg CallSpec / lazy items.

Made with Cursor

[RonnyPfannschmidt]

this one doesn't bring in enough win yet