---
id: streamlit-autorefresh
version: "1.0.1"
license: unclear
license_treatment: unclear
maintenance: abandoned
---

# streamlit-autorefresh — Simple way to autorefresh your Streamlit apps

License: unclear · Maintenance: abandoned · Downloads: 764.4K/mo

## What it is and what it does

Streamlit Autorefresh is a custom Streamlit component that places a timer in the browser frontend to periodically trigger app reruns on a fixed interval. Instead of using an infinite loop in your script (which blocks the server and complicates shutdown), you call st_autorefresh() once with an interval in milliseconds and an optional refresh limit, and the browser handles the timing. The function returns a counter tracking how many times the refresh has fired, letting you conditionally execute different logic at different refresh counts.

The component is designed for dashboards and real-time stats applications where you want regular updates without tying up server resources. You can optionally debounce refreshes when users interact with the app, and you should use a unique key to maintain state across reruns. The trade-off is that it shifts timing work to the browser and relies on frontend timers, which are not perfectly precise.

Use it for:

- Building a live dashboard that updates metrics or stats at regular intervals without blocking the Streamlit server.
- Displaying real-time data feeds or sensor readings at regular intervals in a web app.
- Creating a monitoring application that polls for status changes without an infinite loop in the script.
- Refreshing a Streamlit app at a fixed cadence while allowing users to interact with controls between refreshes.
- Limiting the total number of refreshes to prevent unbounded resource consumption in long-running apps.

## Worth the install?

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

Adds a frontend timer to Streamlit apps that triggers periodic script reruns without blocking the server or requiring an infinite loop.

No—the package is abandoned (last release 2023-06-25, no commits since). While it has low install friction and no known vulnerabilities, the lack of maintenance means it may break with future Streamlit versions, and the unclear license creates legal ambiguity. For new projects, consider native Streamlit refresh patterns or actively maintained alternatives.

## Install

pip install streamlit-autorefresh
uv add streamlit-autorefresh
poetry add streamlit-autorefresh

## Installing streamlit-autorefresh

Before you install: Low friction install with a single runtime dependency on streamlit. However, the package is abandoned—last release was 2023-06-25 with no commits since. No active maintenance or updates.

License in practice: License status is unclear; the package declares no SPDX license identifier. Before relying on this package in production or proprietary work, verify the actual license terms in the repository.

Quickstart:

pip install streamlit-autorefresh

import streamlit as st
from streamlit_autorefresh import st_autorefresh

count = st_autorefresh(interval=2000, limit=100, key="mykey")
st.write(f"Refresh count: {count}")

Requires streamlit to be installed and running; the component runs on the frontend and relies on browser timers, which are not perfectly precise.

Verify before relying:

- Whether the package works reliably with current Streamlit versions post-2023-06-25.
- Actual license terms, since the package declares no SPDX identifier.
- Whether the frontend timer remains accurate under heavy server load or network latency.

## Package facts

- License: not declared (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: abandoned
- Downloads: 764.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

streamlit auto refresh component, periodic streamlit app rerun, streamlit dashboard refresh timer, streamlit realtime stats update, streamlit interval-based refresh, streamlit frontend timer, streamlit refresh without loop, streamlit-component, dashboard, abandoned

[View on SkillFed](https://skillfed.io/packages/streamlit-autorefresh) · [View on PyPI](https://pypi.org/project/streamlit-autorefresh/)