timple

What it is and what it does

Timple patches Matplotlib to handle timedelta plotting natively. Matplotlib can plot timedelta values as raw numbers but lacks the locators and formatters needed to create readable axis ticks in time intervals (minutes, hours, etc.) or to format durations into human-readable strings like '3:05' for 185 seconds. Timple fills that gap by registering automatic converters and providing customizable tick placement and formatting.

The package supports numpy.timedelta64, datetime.timedelta, and pandas.Timedelta objects, and can also handle pandas.NaT (missing time values). Once enabled, Timple's patches apply globally to Matplotlib, so you use plt.plot() and related functions exactly as usual—the enhanced timedelta handling happens transparently.

Use it for:

• Plot lap times or race durations on a y-axis with readable minute:second formatting
• Visualize event durations or time intervals in scientific data with automatic tick spacing
• Display performance metrics measured in seconds or milliseconds with human-readable axis labels
• Create time-series plots where the x or y axis represents elapsed time rather than wall-clock time

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Timple extends Matplotlib with locators and formatters for plotting timedelta values, enabling readable time-interval axis ticks and automatic formatting of duration data.

Yes, if you regularly plot timedelta data in Matplotlib and want readable time-formatted axes without manual tick configuration. The low install friction and permissive license make it a safe addition. However, dormant maintenance (last update 2023-12-27) means you should verify compatibility with your current Matplotlib and pandas versions before relying on it in production; no active support is available.

Install

timple on PyPI

pip install timple

uv add timple

poetry add timple

Installing timple

Before you install

Low install friction; pure Python wheel with only numpy and matplotlib as runtime dependencies. Maintenance is dormant—last release was 2023-12-27 and no commits since then—so expect no active bug fixes or feature updates.

License in practice

MIT license is permissive; you can use, modify, and distribute this package with minimal legal restriction.

Quickstart

import matplotlib.pyplot as plt
import timple

tmpl = timple.Timple()
tmpl.enable()

plt.plot([...timedelta data...])
plt.show()

Requires numpy and matplotlib to be installed; Python >= 3.7

Verify before relying

• Whether pandas.Timedelta and pandas.NaT support work correctly in current pandas versions
• Compatibility with recent Matplotlib versions beyond what 'supports_current' Python implies

Package facts

Evidence: timple-0.1.8-py3-none-any.whl

Tags

More Scientific/Engineering packages