⚡️ Speed up method EnvironmentReader.float by 30%#77
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codeflash-ai[bot] wants to merge 1 commit intomainfrom
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⚡️ Speed up method EnvironmentReader.float by 30%#77codeflash-ai[bot] wants to merge 1 commit intomainfrom
EnvironmentReader.float by 30%#77codeflash-ai[bot] wants to merge 1 commit intomainfrom
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The optimized code achieves a 29% speedup through several targeted micro-optimizations: **Key optimizations:** 1. **Faster type checking in `read_key()`**: Replaced `isinstance(value, str)` with `type(value) is str`. This avoids the overhead of isinstance's subclass checking since we only care about exact string types, saving ~15% time in this hot function. 2. **Tuple instead of list creation**: In `_read_env()`, when converting a single string to an iterable, use `(env_key,)` tuple instead of `[env_key]` list. Tuples are faster to create and iterate over for small collections. 3. **Eliminated lambda overhead**: Replaced `lambda k, dv: self._env.float(k, dv)` with direct method reference `env.float`. This removes function call overhead and closure creation, which is significant since `_read_env()` calls this function in a loop. 4. **Reduced attribute access**: Cache `self._env` as local variable `env` and use `getattr(self, "section", None)` to safely access the section attribute once instead of repeated property lookups. **Performance characteristics by test case:** - **Large-scale tests with many keys** see the biggest gains (35-40% faster) due to the eliminated lambda overhead in the tight loop - **Basic single-key lookups** see modest 2-7% improvements from the type checking and attribute caching optimizations - **Tests with section overrides** benefit from the reduced attribute access patterns The optimizations are most effective for workloads with large environment key lists or frequent configuration reads, which matches typical usage patterns in configuration management systems.
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📄 30% (0.30x) speedup for
EnvironmentReader.floatingraphrag/config/environment_reader.py⏱️ Runtime :
746 microseconds→576 microseconds(best of77runs)📝 Explanation and details
The optimized code achieves a 29% speedup through several targeted micro-optimizations:
Key optimizations:
Faster type checking in
read_key(): Replacedisinstance(value, str)withtype(value) is str. This avoids the overhead of isinstance's subclass checking since we only care about exact string types, saving ~15% time in this hot function.Tuple instead of list creation: In
_read_env(), when converting a single string to an iterable, use(env_key,)tuple instead of[env_key]list. Tuples are faster to create and iterate over for small collections.Eliminated lambda overhead: Replaced
lambda k, dv: self._env.float(k, dv)with direct method referenceenv.float. This removes function call overhead and closure creation, which is significant since_read_env()calls this function in a loop.Reduced attribute access: Cache
self._envas local variableenvand usegetattr(self, "section", None)to safely access the section attribute once instead of repeated property lookups.Performance characteristics by test case:
The optimizations are most effective for workloads with large environment key lists or frequent configuration reads, which matches typical usage patterns in configuration management systems.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-EnvironmentReader.float-mgluhld0and push.