gix-blame performance improved by a change in gix-diff

Note

This post is a modernized version of an earlier post of mine in my main blog.

This post’s “published” date reflects the date the original post was published.

In February 2026, we got a PR in gitoxide that substantially improved gix-diff’s tree diff performance. Since gix-blame’s algorithm uses a lot of tree diffs under the hood, I wanted to know what the impact on gix-blame’s performance was.

I set up a benchmark using hyperfine, and the results are quite impressive: speedups of more than 20 % in some scenarios, with no noticeable performance degradation in any of the scenarios I included. From what I can tell, the speedup depends on the directory depth at which the blamed file lives. This is plausible because nested tree diffs are more expensive than flat ones.

Running the benchmark

The comparison was run between this commit that contained the optimization and its parent. After compiling both executables with cargo build --release --locked, I ran the following script to collect some data using hyperfine.

env GIT_DIR="$HOME/github/Byron/gitoxide/.git" BASELINE_EXECUTABLE="$HOME/bin/gix-blame-2026-03-08-29040a827" COMPARISON_EXECUTABLE="$HOME/bin/gix-blame-2026-03-08-e63d487fb" ./run_benchmark.py

#!/usr/bin/env python
# /// script
# requires-python = ">=3.13"
# ///

import os

def run(path, i):
    os.system(
        f'hyperfine --parameter-list command "$BASELINE_EXECUTABLE","$COMPARISON_EXECUTABLE" --parameter-list path {path} "{{command}} blame {{path}}" --command-name baseline --command-name comparison --export-json benchmark-{i}.json'
    )

for i, path in enumerate(
    [
        "CHANGELOG.md",
        "STABILITY.md",
        "README.md",
        "Cargo.toml",
        "gix-blame/src/file/function.rs",
        "gix-path/src/env/mod.rs",
        "gix-index/tests/index/file/write.rs",
        "gix-object/src/lib.rs",
        "gix-odb/src/store_impls/loose/write.rs",
    ]
):
    run(path, i + 1)

This will create a couple of Markdown files, benchmark-1.json through benchmark-9.json.

Loading the data

Then, in order to work with these files, we’re going to use numpy and pandas to load them into data.

import numpy as np
import pandas as pd

import matplotlib as mpl

import seaborn as sns

import json

def load_results(filename):
    with open(filename) as f:
        return json.load(f)["results"]

def extract_data_points(result):
    command = result["command"]
    path = result["parameters"]["path"]

    return {"command": command, "path": path, "time": result["times"]}

filenames = [f"benchmark-{i}.json" for i in range(1, 10)]
results = [load_results(filename) for filename in filenames]
results = [extract_data_points(result) for result in np.concatenate(results)]

data = pd.concat(
    [pd.DataFrame(result) for result in results],
    ignore_index=True,
)

And finally, we’re going to create 2 plots that will give us an idea of how both versions of gix blame compare with respect to performance. In both plots, there’s a clearly visible speedup associated with the change. It’s also clearly visible that the speedup is much more pronounced for files nested a few directories deep.

Creating a boxplot

FIGURE_WIDTH = 8
FIGURE_ASPECT = 1.6

sns.set_theme(
    palette="Paired",
    rc={"figure.figsize": (FIGURE_WIDTH, FIGURE_WIDTH / FIGURE_ASPECT)},
)

boxplot = sns.boxplot(x="time", y="path", hue="command", data=data)
sns.despine(offset=10, trim=True)
mpl.pyplot.tight_layout()
mpl.pyplot.show()

Creating a stripplot

mpl.pyplot.figure(figsize=(FIGURE_WIDTH * 0.75, FIGURE_WIDTH / FIGURE_ASPECT))

stripplot = sns.stripplot(
    x="time",
    y="path",
    hue="command",
    dodge=True,
    size=2.5,
    jitter=0.2,
    legend=False,
    data=data,
)

mpl.pyplot.show()

Conclusion

The aggregated data confirm the visual impression: for files in the repository’s root directory, there’s only a small performance improvement, but for deeper hierarchies, there’s large improvements of more than 20 % in some cases.

summary = (
    data
    .groupby(["path", "command"])
    .agg(
        mean=("time", "mean"),
        stddev=("time", "std"),
    )
    .reset_index()
)

summary["mean_ms"] = summary["mean"] * 1000
summary["stddev_ms"] = summary["stddev"] * 1000

wide = summary.pivot(
    index="path",
    columns="command",
    values=["mean_ms", "stddev_ms"],
)

table = pd.DataFrame({
    "baseline_mean_ms": wide["mean_ms"]["baseline"],
    "baseline_stddev_ms": wide["stddev_ms"]["baseline"],
    "comparison_mean_ms": wide["mean_ms"]["comparison"],
    "comparison_stddev_ms": wide["stddev_ms"]["comparison"],
})

table["Δ ms"] = table["comparison_mean_ms"] - table["baseline_mean_ms"]
table["Δ %"] = table["Δ ms"] / table["baseline_mean_ms"] * 100
table["ratio"] = table["comparison_mean_ms"] / table["baseline_mean_ms"]

table = table.sort_values("Δ %", ascending=False)

display_table = pd.DataFrame({
    "path": table.index.to_list(),
    "baseline mean ± sd": [
        f"{mean:.2f} ± {sd:.2f}"
        for mean, sd in zip(table["baseline_mean_ms"], table["baseline_stddev_ms"])
    ],
    "comparison mean ± sd": [
        f"{mean:.2f} ± {sd:.2f}"
        for mean, sd in zip(table["comparison_mean_ms"], table["comparison_stddev_ms"])
    ],
    "Δ ms": table["Δ ms"].to_list(),
    "Δ %": table["Δ %"].to_list(),
    "ratio": table["ratio"].to_list(),
})

display_table.style.format({
    "Δ ms": "{:+.2f}",
    "Δ %": "{:+.2f}%",
    "ratio": "{:.3f}×",
}).background_gradient(
    subset=["Δ %"],
    cmap="Greens_r",
).hide(axis="index")

path	baseline mean ± sd	comparison mean ± sd	Δ ms	Δ %	ratio
README.md	103.66 ± 2.47	103.09 ± 2.01	-0.57	-0.55%	0.995×
CHANGELOG.md	142.11 ± 2.74	140.84 ± 2.17	-1.28	-0.90%	0.991×
STABILITY.md	51.22 ± 1.57	50.72 ± 1.92	-0.51	-0.99%	0.990×
Cargo.toml	93.16 ± 3.40	91.91 ± 2.18	-1.26	-1.35%	0.987×
gix-object/src/lib.rs	84.23 ± 2.18	76.44 ± 1.89	-7.79	-9.25%	0.907×
gix-odb/src/store_impls/loose/write.rs	84.01 ± 2.44	74.44 ± 2.08	-9.57	-11.40%	0.886×
gix-path/src/env/mod.rs	44.55 ± 1.31	36.21 ± 1.50	-8.34	-18.72%	0.813×
gix-index/tests/index/file/write.rs	62.93 ± 1.53	49.32 ± 1.42	-13.61	-21.62%	0.784×
gix-blame/src/file/function.rs	44.43 ± 1.53	34.69 ± 1.58	-9.74	-21.93%	0.781×