quicklooks 2.0.4

Create presentation-ready data visualizations quickly.

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.