astral-sh/python-build-standalone

Produce redistributable builds of Python

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Summary Information

Updated 39 minutes ago
Added to GitGenius on September 15th, 2026
Created on December 18th, 2018
Open Issues & Pull Requests: 199 (+0)
GitHub issues: Enabled
Number of forks: 315
Total Stargazers: 4,432 (+0)
Total Subscribers: 27 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 14.1 hours
Mean response time: 30.2 days
90th percentile: 60.0 days
Tracked items: 300

Most active contributors

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How this project is maintained

About 9% of issues opened in the past year have never received a reply. 58% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Work labelled "bug" is answered fastest, typically in about an hour, while "platform:linux" waits about 4 weeks. 60% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. 60% of issues opened in the past year have been closed, leaving a working backlog.

Charts & Analytics

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Issue Activity (beta)

Open issues: 144
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 611 days
Stale 30+ days: 133
Stale 90+ days: 113

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 1

Top labels

  • bug (27)
  • platforms (15)
  • enhancement (14)
  • internal (11)
  • platform:windows (11)
  • compatibility (10)
  • platform:linux (10)
  • performance (8)

Detailed Description

Python Build Standalone is a tool that produces redistributable builds of Python optimized for embedding and distribution.

The project addresses the challenge of creating Python binaries that can be reliably deployed across different systems without requiring users to install Python separately or manage complex dependencies. It generates self-contained Python builds that include the interpreter, standard library, and necessary runtime components, packaged in a format suitable for redistribution. This approach eliminates version conflicts and platform-specific installation issues by bundling everything needed to run Python applications into a single, portable artifact.

Organizations building applications that depend on Python should consider this tool when they need to ship Python as part of their product rather than requiring end users to install it independently. It suits projects that prioritize ease of deployment, consistent runtime environments across machines, and simplified installation workflows. The tool is particularly valuable for creating installers, containerized applications, or embedded Python environments where controlling the exact Python version and configuration is critical.

The project maintains active development with regular updates to support new Python versions and improve build reliability. Work focuses on expanding platform coverage and refining the build process to ensure binaries remain compatible across diverse deployment environments. The maintainers actively address issues and incorporate feedback from users deploying these builds in production systems.