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**Target:** engine/interpreters/inline_executor.py - execute_workflow_graph() and related methods **Expected Gain:** 20-30% **Bottleneck Analysis:** - Core execution loop with repeated set/dict lookups - _add_newly_ready_tasks(): nested loops over task graph - _check_trigger_rule(): set membership + enum comparisons - List operations (pop, append) in tight loops **Cython Strategy:** - Use typed collections (set[str], dict[str, Any]) - Inline _check_trigger_rule with cdef - C-level set operations - Struct-based task representation for dependency checking **Related methods to optimize:** - _add_newly_ready_tasks() - 15-20% gain - _check_trigger_rule() - 12-18% gain - _build_initial_ready_tasks_* - 10-15% gain Tags: cython, performance
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