docker/docker-py

A Python library for the Docker Engine API

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Summary Information

Updated 50 minutes ago
Added to GitGenius on September 9th, 2026
Created on May 23rd, 2013
Open Issues & Pull Requests: 569 (+0)
GitHub issues: Enabled
Number of forks: 1,728
Total Stargazers: 7,211 (+0)
Total Subscribers: 190 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 8.3 days
Mean response time: 203.3 days
90th percentile: 710.9 days
Tracked items: 75

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 2% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 77
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,080 days
Stale 30+ days: 74
Stale 90+ days: 74

Recent activity

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

Top labels

  • kind/feature-request (4)
  • kind/question (4)
  • group/api-upgrade (2)
  • kind/bug (2)
  • level/apiclient (1)
  • needs-buildkit (1)

Detailed Description

Docker SDK for Python is a Python library that provides programmatic access to the Docker Engine API.

The library solves the problem of controlling Docker from within Python applications without shelling out to the command-line interface. It wraps the Docker Engine API, allowing developers to perform any operation available through the docker command—such as running and managing containers, handling images, and managing Swarms—directly from Python code. The approach is straightforward: it connects to Docker via the default socket or environment configuration and exposes the full API surface through Python methods and objects.

Developers should choose this library when building Python applications that need to automate Docker operations programmatically. It suits projects ranging from simple container orchestration scripts to complex applications that need deep integration with Docker. The library handles connection setup automatically through environment configuration, reducing boilerplate. It supports streaming operations like log retrieval, which is essential for monitoring running containers. The installation is minimal and dependency-light, with TLS support included by default.

The project maintains active engagement with its codebase, regularly addressing issues and accepting contributions. Development follows a structured approach to API coverage, ensuring that new Docker Engine features are incorporated into the library. The maintainers prioritize backwards compatibility while modernizing the codebase, as evidenced by the removal of optional TLS dependencies while preserving support for legacy installation patterns.