⚡️ Speed up method AuthSettings.validate_superuser by 41% in PR #9674 (auto-login-removals)#9814
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The optimized code achieves a 40% speedup by **caching attribute lookups** that would otherwise be performed multiple times within the validation method.
**Key optimizations:**
1. **Cached `info.data` lookup**: The original code calls `info.data.get()` up to 3 times per invocation. The optimized version stores `info.data` in a local variable `data` and reuses it, eliminating repeated attribute access overhead.
2. **Cached `info.field_name` lookup**: Similarly, `info.field_name` is accessed multiple times in the original code. The optimized version caches it as `field_name`, reducing attribute lookup overhead.
3. **Cached `auto_login` value**: The `data.get("AUTO_LOGIN")` result is stored in `auto_login` variable, avoiding the dictionary lookup and method call overhead when the condition is checked.
**Why this works:**
In Python, attribute access (like `info.data`) and method calls (like `.get()`) have non-trivial overhead. When these operations are performed repeatedly within a tight loop or frequently-called validation method, caching them in local variables provides measurable performance benefits. Local variable access is significantly faster than attribute lookups in Python's execution model.
**Test case performance:**
The optimization is particularly effective for the large-scale test cases (`test_large_scale_*` functions) that call the validator 500+ times in loops, where the cumulative effect of eliminating repeated attribute lookups becomes substantial. The basic test cases also benefit, but the gains are more pronounced in high-frequency validation scenarios.
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⚡️ This pull request contains optimizations for PR #9674
If you approve this dependent PR, these changes will be merged into the original PR branch
auto-login-removals.📄 41% (0.41x) speedup for
AuthSettings.validate_superuserinlangflow/services/settings/auth.py⏱️ Runtime :
4.80 milliseconds→3.41 milliseconds(best of14runs)📝 Explanation and details
The optimized code achieves a 40% speedup by caching attribute lookups that would otherwise be performed multiple times within the validation method.
Key optimizations:
Cached
info.datalookup: The original code callsinfo.data.get()up to 3 times per invocation. The optimized version storesinfo.datain a local variabledataand reuses it, eliminating repeated attribute access overhead.Cached
info.field_namelookup: Similarly,info.field_nameis accessed multiple times in the original code. The optimized version caches it asfield_name, reducing attribute lookup overhead.Cached
auto_loginvalue: Thedata.get("AUTO_LOGIN")result is stored inauto_loginvariable, avoiding the dictionary lookup and method call overhead when the condition is checked.Why this works:
In Python, attribute access (like
info.data) and method calls (like.get()) have non-trivial overhead. When these operations are performed repeatedly within a tight loop or frequently-called validation method, caching them in local variables provides measurable performance benefits. Local variable access is significantly faster than attribute lookups in Python's execution model.Test case performance:
The optimization is particularly effective for the large-scale test cases (
test_large_scale_*functions) that call the validator 500+ times in loops, where the cumulative effect of eliminating repeated attribute lookups becomes substantial. The basic test cases also benefit, but the gains are more pronounced in high-frequency validation scenarios.✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-pr9674-2025-09-11T02.05.39and push.