vl-convert-python

import vl_convert as vlc import json # A simple Vega-Lite chart specification as a Python dictionary vl_spec = { "$schema": "https://vega.github.io/schema/vega-lite/v5.json", "description": "A simple bar chart with embedded data.", "data": {"values": [{"a": "A", "b": 28}, {"a": "B", "b": 55}, {"a": "C", "b": 43}]}, "mark": "bar", "encoding": { "x": {"field": "a", "type": "nominal", "axis": {"labelAngle": 0}}, "y": {"field": "b", "type": "quantitative"} } } # Convert to SVG string # It's crucial to pass the spec as a JSON string and specify vl_version svg_str = vlc.vegalite_to_svg(vl_spec=json.dumps(vl_spec), vl_version="5.json") # Convert to PNG bytes with a scale factor png_data = vlc.vegalite_to_png(vl_spec=json.dumps(vl_spec), scale=2, vl_version="5.json") print(f"Generated SVG (first 100 chars): {svg_str[:100]}...") print(f"Generated PNG data (first 10 bytes): {png_data[:10]}...") # To save to files (uncomment to enable): # with open("output_chart.svg", "wt") as f: # f.write(svg_str) # with open("output_chart.png", "wb") as f: # f.write(png_data) # Example for Altair charts (requires altair installed): # import altair as alt # from vega_datasets import data # chart = alt.Chart(data.cars.url).mark_point().encode( # x='Horsepower:Q', # y='Miles_per_Gallon:Q' # ) # # Use the vl_version compatible with your Altair version (e.g., Altair 4.2 uses VL 4.17) # altair_svg_str = vlc.vegalite_to_svg(chart.to_json(), vl_version="4.17") # print(f"Generated Altair SVG length: {len(altair_svg_str)} bytes")