This library is based around generating nice graphs for timings. It's highly modular and provides an interface to quickly and cleanly use modules.

$ python -m pip install graphtimer

The high-level interface is the Plotter class which takes a timer class as its only argument. The builtin timer is MultiTimer, where TimerNamespace builds it without you having to.

From here you have three steps:

1. Time the code by using the timer provided. Usual usage is repeat, as timeit only times the functions once and skips step 2.
2. Perform the statistical analysis on the timings. Most of the time you'll want to use min, which gets the lowest value that isn't an outlier. And shows the error bars from the lowest outlier to Q₃.
3. Plot the data on the graph. This by default uses matplotlib via the MatPlotLib class.

import matplotlib.pyplot as plt
from graphtimer import Plotter, TimerNamespace


class ManualListCreation(TimerNamespace):
    def test_comprehension(iterable):
        return [i for i in iterable]

    def test_append(iterable):
        a = []
        append = a.append
        for i in iterable:
            append(i)
        return a


fig, axs = plt.subplots()
(
    Plotter(ManualListCreation)
        .repeat(100, 5, list(range(0, 10001, 1000)), args_conv=range)
        .min()
        .plot(axs)
)
fig.show()

Documentation is available via GitHub.

To run all tests run nox. No venv is needed; nox makes all of them for us.

$ python -m pip install --user nox
$ git clone https://peilonrayz.github.io/graphtimer/
$ cd graphtimer
graphtimer $ nox

GraphTimer is available under the MIT license.