v2 Stage 1: schema foundation + L1#77
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Adds assert_conformant() check verifying schema_version, relative symbol_table keys, module sources, callable span validity, and absent null values. Fixes core.py to emit relative paths for symbol_table keys per v2 schema spec.
…bling imports
- core.py: key Ray module_map by path relative to project_dir (was absolute),
matching serial/single-file paths so can:// ids and cache lookups are portable
- delete test/__init__.py so pytest re-adds test/ to sys.path for bare
sibling imports (from sample_graph_app import ...)
- test_v2_conformance.py: import conftest_v2 bare, matching repo convention
- conftest_v2.py: guard node kind access with .get("kind")
Key PyModule/PyClass/PyCallable Neo4j nodes on their canonical can:// id (stamped by assign_ids) instead of the file_key / dotted signature, so the JSON and Neo4j projections agree on node identity. Call-graph endpoints for declared symbols resolve through the signature->id map; externals keep their signature-keyed PyExternal identity. Update the declarative schema catalog's merge keys to id (signature/file_key kept as regular props) and thread the id map through emit_neo4j.
The analysis cache now persists the full v2 Analysis envelope (with schema_version) instead of a bare PyApplication. On load, a payload that fails Analysis validation or lacks schema_version 2.0.0 (e.g. an old v1 cache) is detected and treated as a cache miss so the analysis rebuilds cleanly instead of silently reusing incompatible data.
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Part of #69. Stacked on
feat/v2-stage0-scalpel-spike— review that PR first.Stage 1 — canonical schema v2 foundation + L1:
Analysisenvelope (schema_version: "2.0.0",language,max_level,k_limit,application).PyApplication/PyModule/PyClass/PyCallable(+id/kind/span/body; modulesource; dropped per-nodecodeand the separateprogram_graphssection);Spanwith byte offsets.can://durable ids (schema/ids.py,schema/assign_ids.py); L1bodycallnodes; relativesymbol_tablekeys.can://ids (two-projection agreement); cache stores the envelope + rebuilds stale v1 caches.v2 suite 15/15. Legacy dataflow/neo4j suites are module-skipped pending their Stage 3/4/5 migration; remaining full-suite failures are pre-existing/environmental (PyCG & Ray on Python 3.14 — see #61).
Closes #71.