patched function.py

from types import CodeType, FunctionType
from dis import dis

def patch(fn, name, codestring):
    code = fn.__code__
    code = CodeType(
        code.co_argcount, code.co_posonlyargcount, code.co_kwonlyargcount,
        code.co_nlocals, code.co_stacksize, code.co_flags, codestring,
        code.co_consts, code.co_names, code.co_varnames,
        code.co_filename, name, code.co_firstlineno, code.co_lnotab,
        code.co_freevars,  code.co_cellvars,
    )
    return FunctionType(
        code, fn.__globals__, name, fn.__defaults__, fn.__closure__
    )

def only_dict(d, i):
    d[i] = 0
    return d[i]

def without_walrus(d, i):
    r = 0
    d[i] = r
    return r

def with_walrus(d, i):
    d[i] = (r := 0)
    return r

patched_walrus = patch(with_walrus, 'patched_walrus', bytes([100, 1, 4, 0, 124, 0, 124, 1, 60, 0, 83, 0]))

dis(patched_walrus)

plot.py

import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns

sns.set(style='ticks')

df = pd.read_csv('idx_vs_walrus.csv')

fig, (ax1, ax2) = plt.subplots(
    ncols=2, sharey=True, figsize=(9, 4),
    gridspec_kw=dict(width_ratios=[10, 1]),
)

mn, mx = np.quantile(df.values, [0, 0.99])
d = mx - mn
ax1.set_ylim(mn-0.06*d, mx+0.15*d)
ax1.set_xmargin(0)

for name, series in df.items():
    sd = series.values.copy()
    s2 = series.sort_values()[95:]
    s1 = sd; s1[s2.index] = np.nan
    
    al, = ax1.plot(s1, label=name)
    ax1.plot(s2, '.', color=al.get_color())

    s1 = s1[~np.isnan(s1)]
    mu = np.mean(s1)
    sd = np.std(s1)
    std = sd / np.sqrt(sum(s1))

    print(*np.array([
        mu-2*std, mu, mu+2*std,
    ]).round(4))

    ax1.axhline(mu, ls='--', color='black', lw=1, alpha=0.5)
    kde = stats.gaussian_kde(s1)
    x = np.linspace(mu-6*sd, mu+6*sd, 201)

    ax2.plot(kde.evaluate(x), x, color=al.get_color())

ax1.set_xlabel('Timer run')
ax1.set_ylabel('time (seconds)')

ax1.legend()
ax2.get_xaxis().set_visible(False)

sns.despine(ax=ax1)
sns.despine(ax=ax2, bottom=True)

fig.tight_layout()

fig.savefig('idx_vs_walrus.png', dpi=160)

Thank you :)