quicklooks
quicklooks is a Python package for creating presentation-ready data visualizations quickly. It wraps matplotlib with a simple, consistent API designed for data scientists, product managers, and researchers working in Jupyter notebooks.
v2.0 — designed for AI agents
quicklooks v2 is built for the AI-agent workflow. Every chart the agent writes follows the same template, making it easy to scan, understand, and modify. A companion Cursor skill guides agents to produce consistent, well-structured code every time.
Install
pip install quicklooks
Then in your notebook:
import quicklooks as ql
AI agent skill
quicklooks includes a companion skill that teaches AI agents how to use the package consistently. Install it once after pip install quicklooks:
import quicklooks as ql
ql.install_skill()
This auto-detects which agents are installed on your machine:
- Cursor — copies skill files to
~/.cursor/skills/ql-viz/. Restart Cursor to activate. - Claude Code — copies skill files to
~/.claude/quicklooks/and adds an import line to~/.claude/CLAUDE.md.
If both are installed, both are set up in one call. Safe to re-run — it updates the skill files and won't duplicate the Claude Code import.
Quick start
import numpy as np
import quicklooks as ql
x = np.linspace(0, 10, 50)
y = np.sin(x) * 40 + 50
# https://github.com/alexdsbreslav/quicklooks/blob/main/quicklooks/skill/reference.md
cs = ql.chart(
title="Sine Wave",
xlabel="X",
ylabel="Y",
x_min_max=(0, 10),
y_min_max=(0, 100),
xtick_interval=2,
ytick_interval=20,
size="notebook",
colors="bloom",
font="rubik",
xtick_labels="default",
ytick_labels="default",
horizontal_gridlines=False,
vertical_gridlines=False,
);
ql.line(cs,
x=x,
y=y,
color="default",
yerror=None,
linewidth=3,
linestyle="solid",
marker=None,
opacity=1,
label="sin(x)",
end_label=True,
layer_order=1,
);
API overview
| Function | Purpose |
|---|---|
ql.chart() |
Create the chart skeleton (axes, title, styling) |
ql.line() |
Add a line plot |
ql.area() |
Add a stacked area band |
ql.bar() |
Add a bar chart |
ql.stacked_bar() |
Add a segment to a stacked bar chart |
ql.scatter() |
Add a scatter plot |
ql.dist() |
Add a distribution (histogram / density) plot |
ql.refline() |
Add a reference line (horizontal, vertical, diagonal) |
ql.legend() |
Add a legend |
ql.text() |
Add a text annotation |
ql.save() |
Save the chart to disk |
Color libraries
quicklooks ships with five color libraries: extended, neon, sorbet, bloom, and hockney. Pass the library name to ql.chart() and color names as strings to each plot function:
cs = ql.chart(..., colors="bloom")
ql.line(cs, x=x, y=y, color="cornflower")
ql.line(cs, x=x, y=y2, color="purple")
Acknowledgments
quicklooks is built on matplotlib, NumPy, pandas, seaborn, Open Color, and Figma's brand colors.
Metadata
Release files for quicklooks 2.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| quicklooks-2.0.4.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quicklooks-2.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.4 MB
Release files / quicklooks-2.0.4.tar.gz
| Download URL | quicklooks-2.0.4.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4dbfd23edd052936c09ec46f0627bab0cc3327138be926c06611afafa8c6d4f5
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Transparency logRelease files / quicklooks-2.0.4-py3-none-any.whl
| Download URL | quicklooks-2.0.4-py3-none-any.whl |
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| Size | 1.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
946eb968086673a80deed3e87f1e4b2c2605dc14ed4e8acc8ca12db70ffffd0b
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Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
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PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 29, 2026.
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