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@codeflash-ai codeflash-ai bot commented Oct 29, 2025

📄 10% (0.10x) speedup for _quarterly_finder in pandas/plotting/_matplotlib/converter.py

⏱️ Runtime : 970 microseconds 885 microseconds (best of 9 runs)

📝 Explanation and details

The optimization achieves a 9% speedup through several key improvements:

1. Direct Return Statements

  • Replaced tuple assignments with direct returns in _get_default_annual_spacing() (e.g., return (1, 2) instead of (min_spacing, maj_spacing) = (1, 2); return (min_spacing, maj_spacing))
  • This eliminates unnecessary variable creation and assignment overhead

2. Streamlined Conditional Logic

  • In has_level_label(), extracted size = label_flags.size to avoid repeated attribute access
  • Simplified the return logic by removing the redundant else branch

3. Optimized Array Operations in _quarterly_finder()

  • Used bytes literals (b"Q%q") instead of strings for numpy structured array assignments, avoiding string-to-bytes conversion overhead for the "|S8" dtype
  • Removed unnecessary info["fmt"] = "" assignment since zero-initialized structured arrays already have empty string fields
  • Used more descriptive variable names (vmin_i, vmax_i) and intermediate variables for better code clarity

4. Reduced Redundant ppd Initialization

  • Moved ppd = -1 assignments closer to where they're needed instead of initializing once at the top, though this has minimal performance impact

These optimizations are particularly effective for:

  • Frequent function calls where tuple creation overhead adds up
  • Large arrays where byte string operations and avoiding redundant assignments matter
  • Plotting operations that repeatedly call these functions during tick formatting

The improvements focus on micro-optimizations that reduce Python object creation and unnecessary operations while maintaining identical functionality.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 139 Passed
🌀 Generated Regression Tests 🔘 None Found
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 87.9%
⚙️ Existing Unit Tests and Runtime
Test File::Test Function Original ⏱️ Optimized ⏱️ Speedup
plotting/test_converter.py::test_quarterly_finder 970μs 885μs 9.64%✅

To edit these changes git checkout codeflash/optimize-_quarterly_finder-mhbq5qtu and push.

Codeflash

The optimization achieves a 9% speedup through several key improvements:

**1. Direct Return Statements**
- Replaced tuple assignments with direct returns in `_get_default_annual_spacing()` (e.g., `return (1, 2)` instead of `(min_spacing, maj_spacing) = (1, 2); return (min_spacing, maj_spacing)`)
- This eliminates unnecessary variable creation and assignment overhead

**2. Streamlined Conditional Logic**
- In `has_level_label()`, extracted `size = label_flags.size` to avoid repeated attribute access
- Simplified the return logic by removing the redundant `else` branch

**3. Optimized Array Operations in `_quarterly_finder()`**
- Used bytes literals (`b"Q%q"`) instead of strings for numpy structured array assignments, avoiding string-to-bytes conversion overhead for the `"|S8"` dtype
- Removed unnecessary `info["fmt"] = ""` assignment since zero-initialized structured arrays already have empty string fields
- Used more descriptive variable names (`vmin_i`, `vmax_i`) and intermediate variables for better code clarity

**4. Reduced Redundant ppd Initialization**
- Moved `ppd = -1` assignments closer to where they're needed instead of initializing once at the top, though this has minimal performance impact

These optimizations are particularly effective for:
- **Frequent function calls** where tuple creation overhead adds up
- **Large arrays** where byte string operations and avoiding redundant assignments matter
- **Plotting operations** that repeatedly call these functions during tick formatting

The improvements focus on micro-optimizations that reduce Python object creation and unnecessary operations while maintaining identical functionality.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 29, 2025 08:19
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash labels Oct 29, 2025
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⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash

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