lovelyplots

library1.0.2pypypiunverified

LovelyPlots is a Python library that provides a collection of Matplotlib styles specifically designed to format plots for scientific papers, theses, and reports. It aims to make plots professional, consistent, and aesthetically pleasing with minimal effort. The current version is 1.0.2, and releases are generally driven by bug fixes or the addition of new styles.

data

pip install lovelyplots

github ↗package ↗

INSTALL

IMPORT

SIG · LOVELYPLOTS

lovelyplots

datapythonv1.0.2

Install

7.9s avg

Import

2456ms

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 v1.0.2 · 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 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 2.521s · 177.7MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 7.9s · import 2.390s · 170MB

181MB installed

● package 181MB

Code

Verified usage

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

lovelyplots

✓ import lovelyplots

✗ import lovelyplots

This quickstart demonstrates how to apply a LovelyPlots style to a Matplotlib figure. It highlights the crucial `import lovelyplots` step and then proceeds with a basic sine wave plot using the default 'lovelyplots' style.

import lovelyplots # Required since v1.0.1 import matplotlib.pyplot as plt import numpy as np # Apply one of the lovelyplots styles (e.g., 'lovelyplots', 'paper', 'notebook', 'presentation') plt.style.use('lovelyplots') # Example plot x = np.linspace(0, 2 * np.pi, 400) y = np.sin(x) + np.cos(x**2) fig, ax = plt.subplots(figsize=(8, 4.5)) ax.plot(x, y, label='A Lovely Plot Example') ax.set_title('My Scientific Plot') ax.set_xlabel('Time (s)') ax.set_ylabel('Amplitude (a.u.)') ax.legend() fig.tight_layout() # plt.show() # Uncomment to display the plot # fig.savefig('my_lovely_plot.png', dpi=300) # Uncomment to save the plot

Debug

Known issues

breakingStarting from version 1.0.1, it is mandatory to explicitly `import lovelyplots` at the beginning of your script. Failing to do so will result in Matplotlib not finding the 'lovelyplots' styles.

fix

Ensure `import lovelyplots` is present before any `plt.style.use('lovelyplots')` call.

affects: >=1.0.1

gotchaLovelyPlots requires Matplotlib to be installed. Ensure your Matplotlib version is compatible with LovelyPlots (currently `matplotlib>=3.3`).

fix

Run `pip install matplotlib --upgrade` to ensure you have a recent version of Matplotlib.

affects: All versions

Upgrade

Version history

1.0.2latest on PyPI · released Mar 6, 2024

Audit

Dependencies

matplotlibrequiredCore functionality; LovelyPlots provides styles for Matplotlib.

Agent activity

14 hits · last 30 days

node

Resources

githubhttps://github.com/killiansheriff/LovelyPlots ↗

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