fix: bolt optimization to avoid object materialization for graph exports

[n24q02m]

What: Introduced iter_all_nodes_raw and iter_all_edges_raw methods in GraphStore that yield sqlite3.Cursor and replaced uses of get_all_nodes and get_all_edges inside exporter.py format functions to iterate over raw rows as dictionaries instead of fully materializing Python wrapper objects (like GraphNode or GraphEdge) into lists.

Why: Using .fetchall() or list materialization on large database result sets forces SQLite to allocate heavy lists of mapped Python objects into memory. This is especially problematic for large text-columns (like in export_crg) or large repositories in typical export_* endpoints. Iterating directly on the cursor using standard row dictionary lookup bypasses memory bloat entirely.

Impact: Substantially lowers the peak memory footprint during any full graph export (GraphML, JSON-LD, Dot, Cypher, and CRG exports). Avoids O(N) list-appends of Python ORM objects where N = total graph nodes/edges. Memory scales constantly (only tracking generator state) instead of linearly.

Measurement: Run export_graph() on a large repository and measure memory using tracemalloc. Comparing memory footprint against the previous implementation yields significantly lower allocations since nodes/edges are garbage collected dynamically rather than hoarded in a list before serialization.

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PR created automatically by Jules for task 12815269464629342211 started by @n24q02m

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[github-actions]

Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

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[n24q02m]

Closing: competing variant (iter_all_nodes_raw) of the design landed by #1015.

[google-labs-jules]

Closing: competing variant (iter_all_nodes_raw) of the design landed by #1015.

Understood. Acknowledging that this work is obsolete and a competing variant landed. Stopping work on this task.