---
id: altex
version: "0.2.0"
license: Apache-2.0
license_treatment: permissive
maintenance: aging
---

# altex — A simple wrapper on top of Altair to make charts with an express API

License: permissive · Maintenance: aging · Downloads: 180.3K/mo

## What it is and what it does

Altex is a thin wrapper around Altair that reduces boilerplate when building charts for Streamlit dashboards. Instead of writing full Altair specifications, you call simple functions like `line_chart()`, `bar_chart()`, or `scatter_chart()` with your data and column names, and Altex handles the chart construction and Streamlit integration. It is designed for developers who want the expressiveness of Altair but prefer a more concise, plotly-express-like interface.

The package depends on altair, pandas, and streamlit as runtime dependencies. It supports modern Python versions and installs as a pure Python wheel with low friction. The codebase is permissively licensed under Apache-2.0, making it suitable for both open and commercial projects. However, the package is aging—it has not been updated since its initial release, and adoption remains modest.

Use it for:

- Build interactive Streamlit dashboards with minimal chart configuration code.
- Quickly prototype data visualizations without writing full Altair specifications.
- Add sparklines and spark bar charts to dashboard summaries for compact trend display.
- Create multi-chart layouts in Streamlit apps using a consistent, simple API.
- Visualize pandas DataFrames in Streamlit with one-line chart calls.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Altex wraps Altair to provide a simple, express-style API for creating charts directly in Streamlit applications with minimal boilerplate.

Yes, if you are building a Streamlit dashboard and want a faster, simpler charting API than raw Altair. Install friction is minimal and the license is permissive. However, be aware that the package is aging with no updates since its initial release, so consider it suitable for straightforward charting tasks rather than as a long-term dependency for complex visualization needs. Check the demo app to confirm it covers your chart types before committing.

## Install

pip install altex
uv add altex
poetry add altex

## Installing altex

Before you install: Low friction: pure Python wheel with three straightforward dependencies (altair, pandas, streamlit). Package is aging—last release was 2025-06-30 with no commits since, and adoption remains modest.

License in practice: Apache-2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects, provided you include a copy of the license and state significant changes.

Quickstart:

pip install altex

import streamlit as st
import altex
import pandas as pd

data = pd.DataFrame({'x': range(10), 'y': [i**2 for i in range(10)]})
altex.line_chart(data=data, x='x', y='y', title='My Chart')

Requires Streamlit to be installed and running; intended for use within a Streamlit application context.

Verify before relying:

- Whether the package is actively maintained beyond its initial release or if development has stalled.
- Performance characteristics when handling large datasets or many concurrent charts.
- Completeness of the API surface relative to Altair's full capabilities.
- Python version support upper bound and compatibility with current Streamlit versions.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 180.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

streamlit chart wrapper, altair express api, quick streamlit visualization, simple altair charts, streamlit plotting library, altair simplified, dashboard charting tool, streamlit-integration, data-visualization, charting

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