timple

library0.1.8pypypi✓ verified 84d ago

A Python library that extends Matplotlib's plotting capabilities for timedelta-like values, providing custom tick locators and formatters for intuitive axis formatting. Version 0.1.8 supports Python >=3.7 and is actively maintained.

data ai-ml

pip install timple

github ↗package ↗

INSTALL

IMPORT

SIG · TIMPLE

timple

datapythonv0.1.8

Install

7.6s avg

Import

—

Disk

181MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.8 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 177.7MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 7.6s · import 0.000s · 170MB

181MB installed

● package 181MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Timple

✓ from timple import Timple

✗ from timple import TimedeltaConverter

timedelta

✓ from timple import timedelta

core

✓ from timple import core

Plot timedelta data with automatic axis formatting.

import matplotlib.pyplot as plt import pandas as pd from timple import TimedeltaConverter # Create a simple timedelta series times = pd.to_timedelta(['00:00:00', '00:01:30', '00:03:00', '00:04:30']) values = [1, 2, 3, 4] fig, ax = plt.subplots() ax.plot(times, values) # Apply Timple converter TimedeltaConverter(times).apply(ax.xaxis) ax.set_xlabel('Time') ax.set_ylabel('Value') plt.show()

Debug

Known issues

gotchaTimple converters only work with ax.xaxis or ax.yaxis, not directly with plt.xticks(). Apply the converter to the desired axis instance.

fix

Use TimedeltaConverter(timedelta_data).apply(axis_object) where axis_object is an Axes.xaxis or Axes.yaxis.

affects: all

gotchaPassing a list or tuple of Pandas Timedelta objects can cause crashes in versions prior to 0.1.6. Ensure you use NumPy array or Pandas Series.

fix

Upgrade to timple>=0.1.6 or convert to numpy array with np.array(your_list).

affects: <0.1.6

deprecatedThe argument 'concise' was deprecated in v0.1.1 in favor of separate locators/formatters. Avoid passing concise=True to the converter.

fix

Use ticker_concise or formatter_concise directly instead.

affects: >=0.1.1

gotchaWhen using Pandas NaT values, converters may fail on older versions (before 0.1.2). Upgrade or drop NaT values before plotting.

fix

Upgrade to timple>=0.1.2 or drop NaT with times.dropna() if using Pandas Series.

affects: <0.1.2

gotchaMasked arrays introduced in Matplotlib 3.7.0 are only supported from timple 0.1.6 onwards. Plotting masked timedelta data with earlier versions will crash.

fix

Upgrade to timple>=0.1.6 or avoid using masked arrays.

affects: <0.1.6

Upgrade

Version history

0.1.8latest on PyPI · released Dec 27, 2023

Audit

Dependencies

matplotlibrequiredCore integration with Matplotlib's axis formatter and locator API

pandasrequiredRequired for converting Pandas Timedelta and NaT objects

numpyrequiredUsed for array operations and compatibility

Agent activity

28 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/theOehrly/Timple ↗

packagehttps://pypi.org/project/timple/ ↗