datasette-ports 0.1

2026-04-06 · Source: Simon Willison's Weblog · Field: Technology & Digital — Software Development & Engineering, Data Science & Analytics · Depth: Intermediate, quick

Summary

The `datasette-ports` 0.1 plugin, released on April 6, 2026, addresses the challenge of managing multiple concurrent Datasette instances. This tool allows users to quickly identify and list all currently running Datasette instances, along with their respective ports, versions, loaded databases, and active plugins. The plugin is installed via `datasette install datasette-ports` and executed with `datasette ports`, providing an overview of each instance, such as `http://127.0.0.1:8333/ - v1.0a26` with associated databases like "data" and plugins like "datasette-enrichments" and "datasette-llm". It helps users track instances spread across various terminal windows.

Key takeaway

For Data Scientists or Developers frequently running multiple Datasette instances for different projects or plugin development, integrating `datasette-ports` into your workflow is highly recommended. This tool simplifies the process of locating and understanding your active Datasette environments, preventing lost instances and improving development efficiency. You can quickly see which databases and plugins are loaded on each running server.

Key insights

The `datasette-ports` plugin helps users track and manage multiple running Datasette instances.

Method

Install `datasette-ports` using `datasette install datasette-ports`, then execute `datasette ports` to list all active Datasette instances, their ports, versions, databases, and plugins.

In practice

• Install `datasette-ports` for instance discovery.
• Use `datasette ports` to monitor active Datasette deployments.

Topics

• datasette-ports
• Datasette instances
• Port discovery
• Developer tools
• Datasette plugins

Best for: Software Engineer, Data Scientist

Related on AIssential

• datasette-ports 0.3 — Datasette-ports 0.3 enhances local Datasette instance monitoring by detailing directories, database paths, and plugins.
• datasette-fixtures 0.1a0 — Datasette-fixtures simplifies plugin testing by providing a standardized, pre-populated database environment.
• How Docker Can Help You Become A More Effective Data Scientist — Docker containers enhance data science reproducibility, portability, and deployment capabilities by encapsulating compute environments.
• Building Your First Streamlit App: Uploads, Charts, and Filters (Part 2) — Streamlit enables rapid development of interactive data apps with uploads, visualizations, filtering, and export.
• How to Orchestrate Across Multiple Databricks Workspaces Without Losing Your Mind — Managing cross-workspace dependencies is critical for scalable Databricks orchestration, which native tools lack.
• Top 10 Python Libraries for Data Engineering in 2026 — The Python data engineering ecosystem offers specialized libraries for every pipeline stage, from orchestration to high-performance data transformation.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Simon Willison's Weblog.