timple
Extended functionality for plotting timedelta-like values with Matplotlib
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires numpy and matplotlib to be installed; Python >= 3.7
- 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 · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package with minimal legal restriction.
last release 2023-12-27 (961 days) · last repo commit 2023-12-27 · 9 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 106,232 downloads/mo, #12,662 on PyPI
Alternatives
Verify before relying
import matplotlib.pyplot as plt
import timple
tmpl = timple.Timple()
tmpl.enable()
plt.plot([...timedelta data...])
plt.show()- Whether pandas.Timedelta and pandas.NaT support work correctly in current pandas versions
- Compatibility with recent Matplotlib versions beyond what 'supports_current' Python implies
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 on it.
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
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.
Requires numpy and matplotlib to be installed; Python >= 3.7
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()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
| License | MIT permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnumpymatplotlib |
| Maintenance | Dormant 961 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 106,232 / month, #12,662 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: timple-0.1.8-py3-none-any.whl
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