⚡️ Speed up method Figure.add_scattercarpet by 17%

[codeflash-ai]

📄 17% (0.17x) speedup for Figure.add_scattercarpet in plotly/graph_objs/_figure.py

⏱️ Runtime : 11.8 milliseconds → 10.1 milliseconds (best of 23 runs)

📝 Explanation and details

The optimized code achieves a 16% speedup through two key optimizations:

1. Import Caching Optimization: The most significant improvement comes from caching the Scattercarpet import as a class attribute. In the original code, from plotly.graph_objs import Scattercarpet is executed on every call to add_scattercarpet, which the line profiler shows takes 6.8ms (7.8% of total time). The optimized version uses a try/except pattern to cache this import as self.__class__._Scattercarpet after the first call, reducing subsequent import overhead to just attribute lookups (~57μs vs 6.8ms).

2. Constructor Micro-optimization: The __init__ method caches super().__init__ as a local variable _super_init, avoiding repeated attribute resolution on the super() object. While this provides a smaller benefit, it's a safe micro-optimization that reduces lookup overhead.

Performance Profile: The line profiler shows the import line dropping from 6.8ms to 379μs (99.4% reduction) after the first call. The trace construction time also improves from 33.2ms to 32.5ms, likely due to the cached reference reducing object lookup overhead.

Best Use Cases: This optimization particularly benefits scenarios with:

• Repeated trace creation (like the 100-trace test showing 16.7% improvement)
• Interactive applications where users frequently add traces
• Programmatic figure generation with multiple scattercarpet traces

The optimization maintains identical behavior and API while eliminating redundant import costs in hot code paths.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 106 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest
from plotly.graph_objs._figure import Figure


# Minimal implementation of add_scattercarpet for testing
def add_scattercarpet(
    a=None,
    b=None,
    carpet=None,
    connectgaps=None,
    customdata=None,
    fill=None,
    fillcolor=None,
    hoverinfo=None,
    hoveron=None,
    hovertemplate=None,
    hovertext=None,
    ids=None,
    legend=None,
    legendgroup=None,
    legendrank=None,
    legendwidth=None,
    line=None,
    marker=None,
    meta=None,
    mode=None,
    name=None,
    opacity=None,
    selected=None,
    selectedpoints=None,
    showlegend=None,
    stream=None,
    text=None,
    textfont=None,
    textposition=None,
    uid=None,
    uirevision=None,
    unselected=None,
    visible=None,
    xaxis=None,
    yaxis=None,
    zorder=None,
    row=None,
    col=None,
    secondary_y=None,
    **kwargs,
):
    # Create a dict representing the scattercarpet trace
    trace = {
        "type": "scattercarpet",
        "a": a,
        "b": b,
        "carpet": carpet,
        "connectgaps": connectgaps,
        "customdata": customdata,
        "fill": fill,
        "fillcolor": fillcolor,
        "hoverinfo": hoverinfo,
        "hoveron": hoveron,
        "hovertemplate": hovertemplate,
        "hovertext": hovertext,
        "ids": ids,
        "legend": legend,
        "legendgroup": legendgroup,
        "legendrank": legendrank,
        "legendwidth": legendwidth,
        "line": line,
        "marker": marker,
        "meta": meta,
        "mode": mode,
        "name": name,
        "opacity": opacity,
        "selected": selected,
        "selectedpoints": selectedpoints,
        "showlegend": showlegend,
        "stream": stream,
        "text": text,
        "textfont": textfont,
        "textposition": textposition,
        "uid": uid,
        "uirevision": uirevision,
        "unselected": unselected,
        "visible": visible,
        "xaxis": xaxis,
        "yaxis": yaxis,
        "zorder": zorder,
        "row": row,
        "col": col,
        "secondary_y": secondary_y,
    }
    trace.update(kwargs)
    # Simulate adding to a figure by returning the trace
    return trace

# ========================
# Basic Test Cases
# ========================

































#------------------------------------------------
import pytest
from plotly.graph_objs._figure import Figure


# Minimal stub for Scattercarpet trace (since we can't import plotly in this environment)
class Scattercarpet:
    def __init__(self, **kwargs):
        self._props = dict(kwargs)
        # Required for BaseFigure logic
        self._parent = None
        self._orphan_props = {}
        self._trace_ind = None

# Minimal stub for BaseFigure and Figure
class BaseFigure:
    def __init__(self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs):
        self.data = []
        self.traces = []
        if data:
            self.data = list(data)
            self.traces = list(data)
    def add_trace(self, trace, row=None, col=None, secondary_y=None, exclude_empty_subplots=False):
        self.traces.append(trace)
        return self
from plotly.graph_objs._figure import Figure

# ----------- UNIT TESTS FOR add_scattercarpet ------------

# 1. Basic Test Cases

def test_add_scattercarpet_minimal():
    # Test adding a minimal scattercarpet trace
    fig = Figure()
    fig.add_scattercarpet(a=[1,2], b=[3,4]) # 139μs -> 122μs (14.4% faster)












def test_add_scattercarpet_many_traces():
    # Add many scattercarpet traces to the same figure
    fig = Figure()
    for i in range(100):
        fig.add_scattercarpet(a=[i, i+1], b=[i+2, i+3], name=f"trace{i}") # 11.6ms -> 9.95ms (16.7% faster)
    for i in range(100):
        pass

To edit these changes git checkout codeflash/optimize-Figure.add_scattercarpet-mhfvwzbd and push.