⚡️ Speed up function ioff by 67%
#249
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📄 67% (0.67x) speedup for
ioffinlib/matplotlib/pyplot.py⏱️ Runtime :
580 microseconds→347 microseconds(best of107runs)📝 Explanation and details
The optimized code achieves a 66% speedup by implementing conditional execution guards in the
ion()andioff()functions.Key optimizations applied:
State-aware conditional execution: The optimized version caches the current interactive mode state (
current_mode = isinteractive()) and only performs expensive operations when the state actually needs to change:ioff(): Only callsmatplotlib.interactive(False)anduninstall_repl_displayhook()when currently interactive (if current_mode)ion(): Only callsmatplotlib.interactive(True)andinstall_repl_displayhook()when currently non-interactive (if not current_mode)Reduced function call overhead: When interactive mode is already in the desired state, the optimization avoids:
matplotlib.interactive()(which involves dictionary lookups inrcParams)install_repl_displayhook()oruninstall_repl_displayhook()(which involve module imports and event registration)Why this provides significant speedup:
Impact on workloads:
This optimization particularly benefits scenarios where
ion()/ioff()are called repeatedly in loops, initialization sequences, or defensive programming patterns where the current state is unknown. The preserved context manager behavior ensures backward compatibility while dramatically reducing overhead for common usage patterns.✅ Correctness verification report:
⚙️ Existing Unit Tests and Runtime
test_pyplot.py::test_iofftest_pyplot.py::test_iontest_pyplot.py::test_nested_ion_ioff🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-ioff-mjaa2dkhand push.