dockerlens-py 0.1.1

Programmatic Docker image layer analysis, auditing, and diffing for Python

dockerlens

Programmatic Docker image layer analysis, auditing, and diffing for Python.

dockerlens is a typed Python library that lets you inspect Docker images from your own code — no CLI scraping, no shell-outs. Think of it as a Pythonic alternative to tools like dive or container-diff, designed to be imported into your scripts, CI pipelines, and dashboards.

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Installation

pip install dockerlens

Requires Python 3.9+ and a running Docker daemon (for image inspection, not for tests).

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Quick Start

from dockerlens import ImageAnalyzer

# Analyze an image
analyzer = ImageAnalyzer("nginx:latest")

# Inspect layers
for layer in analyzer.layers():
    print(f"Layer {layer.index}: {layer.size_human:>10}  {layer.command}")

# Run security & best-practice audit
for issue in analyzer.audit():
    print(f"[{issue.severity}] {issue.rule_id}: {issue.message}")

# Compare two images
for change in analyzer.diff("nginx:1.24"):
    print(f"  {change.change_type:>8}  {change.path}")

# Generate a full report as JSON
report = analyzer.report()
print(report.to_json())

# Pretty-print to the terminal with rich
analyzer.print_layers()
analyzer.print_audit()
analyzer.print_diff("nginx:1.24")

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API Reference

ImageAnalyzer(image, docker_client=None)

Main entry point. Pass an image name/tag (e.g. "nginx:latest") and optionally a pre-configured docker.DockerClient.

Method	Returns	Description
layers()	list[Layer]	Ordered list of image layers (base → top)
audit()	list[AuditResult]	Best-practice audit findings
diff(other)	list[DiffEntry]	Filesystem differences vs. another image
report()	ImageReport	Combined layers + audit, serializable to JSON
print_layers()	None	Pretty-print layer table to terminal
print_audit()	None	Pretty-print audit results to terminal
print_diff(other)	None	Pretty-print filesystem diff to terminal

Data Classes

• Layer — index, digest, size_bytes, command, created_at, size_human (property)
• AuditResult — rule_id, severity, message, layer_index
• DiffEntry — path, change_type, size_before, size_after
• ImageReport — image_name, image_id, total_size_bytes, layers, audit_results, to_dict(), to_json()

Exceptions

• DockerLensError — base exception
• DockerNotAvailable — Docker daemon unreachable
• ImageNotFound — image not present locally

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Audit Rules

Rule ID	Severity	Description
NO_USER	WARNING	Container runs as root — no USER instruction found
APT_CACHE_NOT_CLEARED	WARNING	apt-get install without cache cleanup in the same layer
LATEST_TAG	INFO	Image uses the :latest tag (non-reproducible builds)
LARGE_LAYER	INFO	A single layer exceeds 200 MB
ADD_INSTEAD_OF_COPY	INFO	ADD used instead of COPY (implicit tar extraction / URL fetch)
SECRET_PATTERN	ERROR	Environment variable name matches PASSWORD, SECRET, API_KEY, or TOKEN
MANY_LAYERS	INFO	Image has more than 20 layers

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JSON Output

report = ImageAnalyzer("nginx:latest").report()
print(report.to_json())

{
  "image_name": "nginx:latest",
  "image_id": "sha256:abc123...",
  "total_size_bytes": 142000000,
  "layers": [
    {
      "index": 0,
      "digest": "sha256:a3ed...",
      "size_bytes": 80000000,
      "command": "ADD file:abc in /",
      "created_at": "2024-11-14T22:13:20+00:00"
    }
  ],
  "audit_results": [
    {
      "rule_id": "NO_USER",
      "severity": "WARNING",
      "message": "Container runs as root (no USER instruction found)",
      "layer_index": null
    }
  ]
}

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Contributing

See CONTRIBUTING.md for development setup, testing, and code style guidelines.

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License

MIT — see LICENSE for details.