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The optimized code achieves a **17% speedup** through several targeted micro-optimizations that reduce attribute lookups and method resolution overhead in the AST traversal hot path:
**Key Optimizations:**
1. **Cached attribute lookups in `__init__`**: The construction loop now caches method references (`add_dot_methods = self._dot_methods.setdefault`) to avoid repeated attribute resolution during the preprocessing phase.
2. **Single `getattr` call with None fallback**: Replaced repeated `isinstance(node_value, ast.Name)` checks and `node_value.id` accesses with a single `val_id = getattr(node_value, "id", None)` call. This eliminates redundant type checking and attribute lookups.
3. **Direct base class method calls**: Changed `self.generic_visit(node)` to `ast.NodeVisitor.generic_visit(self, node)` to bypass Python's method resolution and attribute lookup on `self`, providing faster direct method invocation.
4. **Restructured control flow**: Combined the imported modules check with the function name lookup in a single conditional branch, reducing the number of separate `isinstance` calls from the original nested structure.
**Performance Impact:**
- The line profiler shows the most expensive line (`self.generic_visit(node)`) dropped from 9.86ms to 8.80ms (10.8% improvement)
- The `generic_visit` method itself became 40% faster (5.04ms → 2.99ms) due to direct base class calls
- Test results show consistent 8-17% improvements across various scenarios, with the largest gains (up to 23.6%) in complex cases involving multiple lookups
**Best Use Cases:**
The optimization is most effective for:
- Large ASTs with many attribute nodes (as shown in the large-scale tests)
- Codebases with extensive import analysis where `visit_Attribute` is called frequently
- Scenarios with many non-matching attributes, where the fast-path optimizations provide the most benefit
The changes preserve all original functionality while eliminating Python overhead in this performance-critical AST traversal code.
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