⚡️ Speed up method PdfPages.infodict by 62%

[codeflash-ai]

📄 62% (0.62x) speedup for PdfPages.infodict in lib/matplotlib/backends/backend_pdf.py

⏱️ Runtime : 1.23 microseconds → 759 nanoseconds (best of 5 runs)

📝 Explanation and details

The optimization eliminates unnecessary method calls and attribute lookups by inlining the _ensure_file() logic directly into infodict().

Key Changes:

• Inlined lazy initialization: The infodict() method now directly checks if self._file is not None and handles file creation inline, eliminating the overhead of calling _ensure_file()
• Reduced call stack depth: Removes one function call from the hot path when accessing infoDict

Why it's faster:

1. Method call elimination: Python function calls have overhead for stack frame creation, argument passing, and return value handling. By inlining the logic, we avoid this completely.
2. Fewer attribute lookups: The original code accessed self._file twice (once in _ensure_file(), once for the return), while the optimized version accesses it only once per execution path.
3. Better branch prediction: The direct conditional check allows the CPU to better predict the most common execution path.

Performance characteristics:

• Shows 62% speedup (1.23μs → 759ns) for the test case where _file already exists
• Most beneficial when infodict() is called repeatedly after the first file initialization
• The optimization is particularly effective in scenarios where PDF metadata is accessed multiple times during document creation workflows

This micro-optimization targets a common access pattern in PDF generation where metadata dictionaries are frequently queried, making the cumulative performance gain significant over many operations.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 26 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from matplotlib.backends.backend_pdf import PdfPages

# ------------------ UNIT TESTS ------------------

# 1. BASIC TEST CASES


def test_infodict_mutation_does_not_affect_other_instances():
    """Test that mutating one infodict does not affect another PdfPages instance."""
    pdf1 = PdfPages("f1.pdf")
    pdf2 = PdfPages("f2.pdf")
    pdf1.infodict()["X"] = 1
    codeflash_output = pdf2.infodict()

# imports
from matplotlib.backends.backend_pdf import PdfPages


# --- Minimal stub for PdfFile to allow PdfPages to work for unit tests ---
class PdfFile:
    def __init__(self, filename, metadata=None):
        # Simulate infoDict as a dict, initialized with metadata if provided
        self.infoDict = dict(metadata) if metadata else {}


# --- Unit tests for PdfPages.infodict ---

# 1. Basic Test Cases


def test_infodict_after_manual_file_initialization():
    """Test infodict after _file is manually set (simulating internal state changes)."""
    pdf = PdfPages("test.pdf")
    # Simulate file initialization
    pdf._file = PdfFile("test.pdf", metadata={"X": 1})
    codeflash_output = pdf.infodict()
    info = codeflash_output  # 1.23μs -> 759ns (62.3% faster)


# 3. Large Scale Test Cases

To edit these changes git checkout codeflash/optimize-PdfPages.infodict-miypfu2q and push.