benchmark_a_range.py

import timeit
import pandas as pd
import matplotlib.pyplot as plt

# measuring

numpy_results = {}
python_results = {}

config = {'number': 100, 'repeat': 100}
sizes = [2**exp for exp in range(12)] # or np.arange(12) ;-)
for size in sizes:
    numpy_results[size] = min(timeit.repeat(f'np.arange({size})', setup='import numpy as np', **config))
    python_results[size] = min(timeit.repeat(f'range({size})', **config))

df = pd.concat((pd.Series(numpy_results, name='np.arange'), pd.Series(python_results, name='range')), axis=1)

# plotting

fig, ax = plt.subplots()
df.plot(ax=ax)
ax.set_xscale('log', base=2)
ax.set_xticks(sizes)
ax.set_xticklabels(sizes)
ax.set_xlabel('Size')
ax.set_ylabel('Best runtime for 10 runs out of 10 repetition')