altex
A simple wrapper on top of Altair to make charts with an express API
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Streamlit to be installed and running; intended for use within a Streamlit application context.
- 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 · maintenance · safety
Apache-2.0 (permissive) — 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.
last release 2025-06-30 (410 days) · last repo commit 2025-06-30
0 known vulnerabilities (OSV.dev, 2026-08-14) · 180,324 downloads/mo, #10,147 on PyPI
Alternatives
Verify before relying
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')- 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.
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 on this page. Verify before relying on it.
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
altex on PyPI
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.
Requires Streamlit to be installed and running; intended for use within a Streamlit application context.
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')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 the current Python release <3.14,>=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesaltairpandasstreamlit |
| Maintenance | Aging 410 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 180,324 / month, #10,147 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: altex-0.2.0-py3-none-any.whl
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See also streamlit-echarts · streamlit-plotly-events · plotly-express · leather · streamlit · vl-convert-python · streamlit-extras · streamlit-code-editor · sparklines