Overview

vl-convert-python is a dependency-free Python package for converting Vega-Lite chart specifications into static images (SVG or PNG) or Vega chart specifications.

Since an Altair chart can generate Vega-Lite, this package can be used to easily create static images from Altair charts.

Try it out on Binder!

Installation

vl-convert-python can be installed using pip with

$ pip install vl-convert-python

Usage

The vl-convert-python package provides a series of conversion functions under the vl_convert module.

Convert Vega-Lite to SVG, PNG, and Vega

The vegalite_to_svg and vegalite_to_png functions can be used to convert Vega-Lite specifications to static SVG and PNG images respectively. The vegalite_to_vega function can be used to convert a Vega-Lite specification to a Vega specification.

import vl_convert as vlc
import json

vl_spec = r"""
{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "data": {"url": "https://raw.githubusercontent.com/vega/vega-datasets/next/data/movies.json"},
  "mark": "circle",
  "encoding": {
    "x": {
      "bin": {"maxbins": 10},
      "field": "IMDB Rating"
    },
    "y": {
      "bin": {"maxbins": 10},
      "field": "Rotten Tomatoes Rating"
    },
    "size": {"aggregate": "count"}
  }
}
"""

# Create SVG image string and then write to a file
svg_str = vlc.vegalite_to_svg(vl_spec=vl_spec)
with open("chart.svg", "wt") as f:
    f.write(svg_str)

# Create PNG image data and then write to a file
png_data = vlc.vegalite_to_png(vl_spec=vl_spec, scale=2)
with open("chart.png", "wb") as f:
    f.write(png_data)

# Create low-level Vega representation of chart and write to file
vg_spec = vlc.vegalite_to_vega(vl_spec)
with open("chart.vg.json", "wt") as f:
    json.dump(vg_spec, f)

Convert Altair Chart to SVG, PNG, and Vega

The Altair visualization library provides a Pythonic API for generating Vega-Lite visualizations. As such, vl-convert-python can be used to convert Altair charts to PNG, SVG, or Vega. The vegalite_* functions support an optional vl_version argument that can be used to specify the particular version of the Vega-Lite JavaScript library to use. Version 4.2 of the Altair package uses Vega-Lite version 4.17, so this is the version that should be specified when converting Altair charts.

import altair as alt
from vega_datasets import data
import vl_convert as vlc
import json

source = data.barley()

chart = alt.Chart(source).mark_bar().encode(
    x='sum(yield)',
    y='variety',
    color='site'
)

# Create SVG image string and then write to a file
svg_str = vlc.vegalite_to_svg(chart.to_json(), vl_version="4.17")
with open("altair_chart.svg", "wt") as f:
    f.write(svg_str)

# Create PNG image data and then write to a file
png_data = vlc.vegalite_to_png(chart.to_json(), vl_version="4.17", scale=2)
with open("altair_chart.png", "wb") as f:
    f.write(png_data)

# Create low-level Vega representation of chart and write to file
vg_spec = vlc.vegalite_to_vega(chart.to_json(), vl_version="4.17")
with open("altair_chart.vg.json", "wt") as f:
    json.dump(vg_spec, f)

How it works

This crate uses PyO3 to wrap the vl-convert-rs Rust crate as a Python library. The vl-convert-rs crate is a self-contained Rust library for converting Vega-Lite visualization specifications into various formats. The conversions are performed using the Vega-Lite and Vega JavaScript libraries running in a v8 JavaScript runtime provided by the deno_runtime crate. Font metrics and SVG-to-PNG conversions are provided by the resvg crate.

Of note, vl-convert-python is fully self-contained and has no dependency on an external web browser or Node.js runtime.

Development setup

Create development conda environment

$ conda create -n vl-convert-dev -c conda-forge python=3.10 deno maturin altair pytest black black-jupyter scikit-image

Activate environment and pip install remaining dependencies

$ conda activate vl-convert-dev
$ pip install pypdfium2

Change to Python package directory

$ cd vl-convert-python

Build Rust python package with maturin in develop mode

$ maturin develop --release

Run tests

$ pytest tests