docker-image-py
Parse docker image as distribution does.
Decision gist · record as of 2026-08-14
Yes. The package solves a specific, well-defined problem (Docker image reference parsing) with low install friction, active maintenance, permissive licensing, and no known vulnerabilities. It's appropriate for any tool that needs to handle Docker image strings programmatically.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction install with a single runtime dependency (regex).
- Active maintenance with recent release 46 days ago and current Python version support (3.10–3.14).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
last release 2026-06-29 (46 days) · last repo commit 2026-06-29 · 23 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,169,705 downloads/mo, #2,715 on PyPI
Alternatives
Verify before relying
pip install docker-image-py
from docker_image import reference
ref = reference.Reference.parse_normalized_named('ubuntu')
print(ref.familiar_name())- Whether parse_normalized_named() and parse() handle all edge cases in real-world container registries beyond the examples shown.
- Performance characteristics when parsing large batches of image references.
- Compatibility with container orchestration platforms and CI/CD systems that may have specific reference format requirements.
What it is and what it does
docker-image-py is a Python library for parsing Docker image reference strings into structured components. It implements the Docker distribution reference grammar, allowing you to extract and normalize registry hostnames, repository names, tags, and content digests from image strings.
The package provides two main parsing modes: parse_normalized_named() applies Docker CLI conventions (filling in docker.io for unqualified names, adding library/ for official images), while parse() performs raw grammar-level parsing without inference. It's useful in tools that need to validate, normalize, or decompose image references programmatically.
Use it for
- Normalize user-provided image names to ensure consistent registry and namespace handling.
- Extract registry hostname and repository path from image strings for routing to custom registries.
- Parse image digests and tags for validation or logging in deployment workflows.
- Validate Docker image reference syntax before passing to container runtime APIs.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package solves a specific, well-defined problem (Docker image reference parsing) with low install friction, active maintenance, permissive licensing, and no known vulnerabilities. It's appropriate for any tool that needs to handle Docker image strings programmatically.
Install
docker-image-py on PyPI
Before you install
Low friction install with a single runtime dependency (regex). Active maintenance with recent release 46 days ago and current Python version support (3.10–3.14).
Requires Python 3.10 or later.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install docker-image-py
from docker_image import reference
ref = reference.Reference.parse_normalized_named('ubuntu')
print(ref.familiar_name())
Verify before relying
- Whether parse_normalized_named() and parse() handle all edge cases in real-world container registries beyond the examples shown.
- Performance characteristics when parsing large batches of image references.
- Compatibility with container orchestration platforms and CI/CD systems that may have specific reference format requirements.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageregex |
| Maintenance | Actively maintained 46 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,169,705 / month, #2,715 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development :: Libraries :: Python Modules |
Evidence: docker_image_py-0.2.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “parse docker image names”
- docker-image-pyParses Docker image reference strings into their component parts…
- container-inspectorAnalyzes Docker images, containers, and virtual machine images to…
- opentelemetry-resource-detector-containeridDetects and registers container runtime metadata (container ID, image…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also azure-containerregistry · pem · cdk-ecr-deployment · python-on-whales · dparse · dparse2 · pypiserver · checksumdir · pyunormalize · dockerfile