bharat-choropleth

bharat-choropleth creates dependency-free, accessible static SVG choropleths from TopoJSON. It is a Python sibling to the repository’s React, plain-JavaScript, and Flutter renderers, intended for reports, generated web pages, and notebooks that should not need a browser or JavaScript runtime.

It includes no boundaries. Pass a mapping or path to your own TopoJSON and retain the source attribution and licence for any boundary bundle you use. The repository’s prepared bundles are under data/generated and their notices are documented in data/ATTRIBUTION.md.

Install

pip install bharat-choropleth

# Only when you need a Matplotlib axes rather than SVG:
pip install 'bharat-choropleth[matplotlib]'

# Only when you need interactive state-to-district controls in Jupyter:
pip install 'bharat-choropleth[notebook]'

Generate an SVG

from bharat_choropleth import render_svg

values = {
    "in-cs-30-goa": 6,
    "in-cs-24-gujarat": 7,
    "in-cs-27-maharashtra": 41,
}

svg = render_svg(
    "data/generated/current-2019-states/states.topo.json",
    values,
    object_name="states",
    title="Example state metric",
    description="A static map. Regions without a supplied value are marked as no data.",
)
open("states.svg", "w", encoding="utf-8").write(svg)

render_svg returns a complete <svg> element with a title, optional description, per-region accessible labels, an even-odd fill rule, and a lower-to-higher legend. Features with missing, invalid, or non-finite values receive the distinct no-data colour; they are never treated as low values.

Decode once, render repeatedly

from bharat_choropleth import decode_topology, render_svg

states = decode_topology("states.topo.json", object_name="states")
svg = render_svg(states, {"in-cs-30-goa": 6})

The decoder understands TopoJSON’s quantized delta arcs, reversed arc indexes, holes, polygons, and multi-polygons. Every part is retained—an archipelago is rendered as separate islands, never as a fabricated enclosing polygon.

Optional Matplotlib

from bharat_choropleth.matplotlib import render_matplotlib

ax = render_matplotlib("states.topo.json", values, object_name="states")
ax.figure.savefig("states.png", dpi=180, bbox_inches="tight")

The Matplotlib adapter is an extra, so importing bharat_choropleth does not pull in Matplotlib or any other rendering dependency.

Jupyter drill-down

Install the notebook extra for an ipywidgets state selector and lazy district loader. The control updates its inline SVG when a state is selected; it has no browser-map or JavaScript runtime dependency.

from pathlib import Path
from bharat_choropleth.notebook import notebook_drilldown

root = Path.cwd()
states = root / "data/generated/current-2019-states/states.topo.json"
district_dir = root / "data/generated/current-2019-districts/districts"

map_control = notebook_drilldown(
    states,
    {"in-cs-30-goa": 6, "in-cs-31-lakshadweep": 43},
    district_loader=lambda state_id: district_dir / f"{state_id}.topo.json",
    states_object_name="states",
)
map_control.widget  # Display this as the last Jupyter cell expression.

Pass district_values as either a {state_id: {district_id: value}} mapping or a state_id -> {district_id: value} callable to colour the district view.

API

Develop and package

python -m unittest discover -s tests -v
python -m build
twine check dist/*

Publishing to PyPI is intentionally a separate, identity-bound action:

python -m twine upload --repository testpypi dist/*  # optional first check
python -m twine upload dist/*

Never commit a PyPI token or generated third-party boundary data without first checking its redistribution conditions.