aquarel

library0.0.7pypypi✓ verified 23d ago

Aquarel is a lightweight templating engine and wrapper around Matplotlib's rcparams designed to simplify plot styling. It enables programmatic definition and JSON serialization of themes, facilitating sharing and consistent visualization across projects. Beyond standard Matplotlib stylesheets, Aquarel introduces 'transforms' for aesthetics not achievable via rcparams alone, such as trimmed axes. The library is actively maintained with frequent minor updates.

data

pip install aquarel

github ↗package ↗

INSTALL

IMPORT

SIG · AQUAREL

aquarel

datapythonv0.0.7

Install

11.8s avg

Import

3670ms

Disk

258MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.0.7 · 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 3.794s · 254.8MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 11.8s · import 3.546s · 243MB

258MB installed

● package 258MB

Code

Verified usage

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

load_theme

✓ from aquarel import load_theme

This quickstart demonstrates how to apply an Aquarel theme using a context manager. The `load_theme()` function fetches a predefined theme, which is then applied within the `with` block. All plotting commands inside this block will adopt the specified theme. Remember that `plt.savefig()` or `plt.show()` should be called *outside* the context manager if transforms are used, to ensure they are correctly applied.

import matplotlib.pyplot as plt import numpy as np from aquarel import load_theme # Define a sample plotting function def create_plot(): fig, ax = plt.subplots(figsize=(8, 6)) x = np.linspace(0, 10, 100) y = np.sin(x) ax.plot(x, y, label='Sine Wave') ax.set_title('Sample Plot') ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.legend() return fig # Apply a theme using a context manager with load_theme('arctic_light'): fig = create_plot() plt.savefig('arctic_light_plot.png') # In a non-script environment (e.g., Jupyter), you might call plt.show() here if needed print('Plot with arctic_light theme saved to arctic_light_plot.png')

Debug

Known issues

gotchaAquarel 'transforms' (e.g., for trimming axes) must be applied after the plot objects (figure/axes) are created. While the context manager (`with load_theme(...)`) handles this automatically on exit, if applying a theme globally (`theme.apply()`), you must manually call `theme.apply_transforms()` after all plotting commands for the effects to take place.

fix

Use the context manager (`with load_theme(...):`) for automatic transform application, or ensure `theme.apply_transforms()` is explicitly called after plot creation when applying themes globally.

affects: All versions

gotchaWhen using a theme with transforms via the context manager, ensure `plt.show()` or `fig.savefig()` is called *outside* the `with` block. This guarantees that transforms, which modify the finished figure, are correctly applied before rendering or saving.

fix

Place `plt.show()` or `fig.savefig()` after the `with load_theme(...):` block.

affects: All versions

breakingVersion 0.0.6 addressed an incompatibility with `MatplotlibDeprecationWarning`. Users on older `aquarel` versions might encounter issues or warnings with newer Matplotlib releases, or conversely, `aquarel` updates might require a specific Matplotlib version to resolve internal warnings.

fix

Upgrade to `aquarel` version 0.0.6 or newer to ensure compatibility with recent Matplotlib changes and avoid deprecation warnings.

affects: <0.0.6

gotchaUnlike standard Matplotlib stylesheets that are applied once globally for the current plotting context, Aquarel aims to provide per-plot styling with temporary changes. The style applied within an Aquarel context manager is only active inside that block and reverts outside of it, which differs from how global `plt.style.use()` typically functions.

fix

Understand that Aquarel's context manager provides scoped styling. For persistent global styling, `theme.apply()` can be used, but remember the implications for transforms.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'aquarel'

This error occurs when the 'aquarel' library is not installed in your Python environment.

fix

Install the 'aquarel' package using pip: 'pip install aquarel'.

ImportError: cannot import name 'load_theme' from 'aquarel'

This error occurs when attempting to import a function or class that does not exist in the 'aquarel' module.

fix

Ensure that 'load_theme' is a valid function in 'aquarel' and that you are using the correct import statement: 'from aquarel import load_theme'.

AttributeError: module 'aquarel' has no attribute 'Theme'

This error occurs when trying to access an attribute or class that does not exist in the 'aquarel' module.

fix

Verify that 'Theme' is a valid class in 'aquarel' and that you are using the correct import statement: 'from aquarel import Theme'.

TypeError: 'NoneType' object is not callable

This error occurs when attempting to call a function that is actually a 'None' object, possibly due to incorrect assignment or import.

fix

Check the assignment and import statements to ensure that the function or object is correctly defined and imported.

ValueError: Invalid theme name 'arctic_light'

This error occurs when specifying a theme name that does not exist in the 'aquarel' library.

fix

Ensure that the theme name is spelled correctly and exists in 'aquarel'. You can list available themes using 'aquarel.list_themes()'.

Upgrade

Version history

0.0.7latest on PyPI · released Jan 23, 2025

Audit

Dependencies

matplotlibrequiredCore dependency as Aquarel acts as a styling wrapper for Matplotlib plots.

seabornoptionalAquarel builds on top of Matplotlib and Seaborn for enhanced data visualization capabilities.

Agent activity

31 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/lgienapp/aquarel ↗

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