⚡️ Speed up PandasSeries._from_sample()
by 5% in src/bentoml/_internal/io_descriptors/pandas.py
#7
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📄
PandasSeries._from_sample()
insrc/bentoml/_internal/io_descriptors/pandas.py
📈 Performance improved by
5%
(0.05x
faster)⏱️ Runtime went down from
780 microseconds
to742 microseconds
Explanation and details
To optimize this Python program for better performance, I'll focus on reducing any unnecessary overhead and ensuring that key operations are efficient. Given that the
PandasSeries
class involves handlingpd.Series
objects, I'll make sure that any checks and transformations are minimal and performed efficiently.Here’s the optimized version of the given code.
Changes Made.
dtype
andshape
to ensure they are only set when necessary, avoiding redundant operations.I also corrected a potential mistake in the example where
pd.DataFrame
was wrongly used instead ofpd.Series
, which matches the context.By focusing on these areas, the code can achieve improved runtime efficiency while maintaining the same functionality.
Correctness verification
The new optimized code was tested for correctness. The results are listed below.
🔘 (none found) − ⚙️ Existing Unit Tests
✅ 13 Passed − 🌀 Generated Regression Tests
(click to show generated tests)
🔘 (none found) − ⏪ Replay Tests