Metadata-Version: 2.4
Name: glowplot
Version: 0.1.0
Summary: Luminous, dark-canvas charts with a single aurora-borealis aesthetic, built on matplotlib.
Author: Gaziz Makhanov
License: MIT
Project-URL: Homepage, https://github.com/gazizmakhanov/claud_visualization
Project-URL: Repository, https://github.com/gazizmakhanov/claud_visualization
Keywords: visualization,matplotlib,charts,dataviz,plotting
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Intended Audience :: Developers
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib>=3.5
Requires-Dist: numpy>=1.20
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Dynamic: license-file

# glowplot

**Luminous, dark-canvas charts with a single aurora-borealis aesthetic — built on matplotlib.**

`glowplot` is a tiny Python visualization library with one job: make
good-looking charts that all share one visual identity, with almost no
styling code on your side. Every chart is drawn on a deep night-sky canvas
with data rendered in glowing teal-to-violet aurora colors.

<p align="center">
  <img src="examples/glowline.png" width="48%" alt="glowline example" />
  <img src="examples/radial.png" width="42%" alt="radial_bars example" />
</p>

## Install

```bash
pip install glowplot
```

Or straight from this repo:

```bash
pip install git+https://github.com/gazizmakhanov/claud_visualization.git
```

It pulls in `matplotlib` and `numpy` and nothing else.

## Quick start

```python
import glowplot as ap

# A glowing line chart
ap.glowline([6, 8, 7, 11, 9, 12], title="Weekly signups", label="new users").save("glow.png")

# A circular bar chart
days   = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]
visits = [820, 932, 901, 934, 1290, 1330, 1120]
ap.radial_bars(days, visits, title="Visits by day").save("radial.png")
```

Every plotting function returns a `Chart` — a thin handle around the
matplotlib figure — so you can `.save(path)`, `.show()`, or keep tweaking
via `chart.fig` / `chart.ax`.

## The two signature visualizations

### `glowline(x, y=None, *, color, title, label, glow)`

A line chart where the line is stroked several times — each pass wider and
fainter — so it reads as **light bleeding into the dark canvas** rather than
a flat pen stroke. A vertical gradient under the curve fades the aurora
color to transparent, giving the line mass without a heavy fill. A single
bright dot marks the latest point.

*Aesthetic intent:* make a single trend feel alive and focal on a dark
dashboard. Pass one sequence to plot it against its index, or `x, y`.

### `radial_bars(categories, values, *, title, start, gap)`

A bar chart wrapped around a ring. It trades a little precise
comparability for a lot of visual rhythm — the eye follows the sweep of the
circle — which suits **ranked or cyclical data** (top-N lists, hours of a
day, days of a week). Each bar is colored by its position along the aurora
ramp, so the whole ring reads as one continuous gradient.

## Theming

The look lives in one place — `glowplot.AURORA` (the `Palette`) and
`glowplot.AURORA_CMAP` (the teal→violet→pink colormap). `apply_theme(fig, ax)`
paints any matplotlib axes with the aurora identity, so you can style your
own charts to match.

## Development

```bash
pip install -e ".[dev]"
pytest                    # 7 tests, headless (Agg backend)
python examples/gallery.py   # regenerate the README images
```

## License

MIT
