MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Azure Containerregistry Py

Azure Containerregistry Py is an data AI skill with a core value of |. It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

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Last verified on: 2026-07-08

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-08
Risk Level Low
mkdir -p ./skills/azure-containerregistry-py && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-containerregistry-py/SKILL.md -o ./skills/azure-containerregistry-py/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Azure Container Registry SDK for Python


Manage container images, artifacts, and repositories in Azure Container Registry.


Installation


bash 
pip install azure-containerregistry

Environment Variables


bash 
AZURE_CONTAINERREGISTRY_ENDPOINT=https://<registry-name>.azurecr.io

Authentication


Entra ID (Recommended)


python 
from azure.containerregistry import ContainerRegistryClient
from azure.identity import DefaultAzureCredential

client = ContainerRegistryClient(
    endpoint=os.environ["AZURE_CONTAINERREGISTRY_ENDPOINT"],
    credential=DefaultAzureCredential()
)

Anonymous Access (Public Registry)


python 
from azure.containerregistry import ContainerRegistryClient

client = ContainerRegistryClient(
    endpoint="https://mcr.microsoft.com",
    credential=None,
    audience="https://mcr.microsoft.com"
)

List Repositories


python 
client = ContainerRegistryClient(endpoint, DefaultAzureCredential())

for repository in client.list_repository_names():
    print(repository)

Repository Operations


Get Repository Properties


python 
properties = client.get_repository_properties("my-image")
print(f"Created: {properties.created_on}")
print(f"Modified: {properties.last_updated_on}")
print(f"Manifests: {properties.manifest_count}")
print(f"Tags: {properties.tag_count}")

Update Repository Properties


python 
from azure.containerregistry import RepositoryProperties

client.update_repository_properties(
    "my-image",
    properties=RepositoryProperties(
        can_delete=False,
        can_write=False
    )
)

Delete Repository


python 
client.delete_repository("my-image")

List Tags


python 
for tag in client.list_tag_properties("my-image"):
    print(f"{tag.name}: {tag.created_on}")

Filter by Order


python 
from azure.containerregistry import ArtifactTagOrder

# Most recent first
for tag in client.list_tag_properties(
    "my-image",
    order_by=ArtifactTagOrder.LAST_UPDATED_ON_DESCENDING
):
    print(f"{tag.name}: {tag.last_updated_on}")

Manifest Operations


List Manifests


python 
from azure.containerregistry import ArtifactManifestOrder

for manifest in client.list_manifest_properties(
    "my-image",
    order_by=ArtifactManifestOrder.LAST_UPDATED_ON_DESCENDING
):
    print(f"Digest: {manifest.digest}")
    print(f"Tags: {manifest.tags}")
    print(f"Size: {manifest.size_in_bytes}")

Get Manifest Properties


python 
manifest = client.get_manifest_properties("my-image", "latest")
print(f"Digest: {manifest.digest}")
print(f"Architecture: {manifest.architecture}")
print(f"OS: {manifest.operating_system}")

Update Manifest Properties


python 
from azure.containerregistry import ArtifactManifestProperties

client.update_manifest_properties(
    "my-image",
    "latest",
    properties=ArtifactManifestProperties(
        can_delete=False,
        can_write=False
    )
)

Delete Manifest


python 
# Delete by digest
client.delete_manifest("my-image", "sha256:abc123...")

# Delete by tag
manifest = client.get_manifest_properties("my-image", "old-tag")
client.delete_manifest("my-image", manifest.digest)

Tag Operations


Get Tag Properties


python 
tag = client.get_tag_properties("my-image", "latest")
print(f"Digest: {tag.digest}")
print(f"Created: {tag.created_on}")

Delete Tag


python 
client.delete_tag("my-image", "old-tag")

Upload and Download Artifacts


python 
from azure.containerregistry import ContainerRegistryClient

client = ContainerRegistryClient(endpoint, DefaultAzureCredential())

# Download manifest
manifest = client.download_manifest("my-image", "latest")
print(f"Media type: {manifest.media_type}")
print(f"Digest: {manifest.digest}")

# Download blob
blob = client.download_blob("my-image", "sha256:abc123...")
with open("layer.tar.gz", "wb") as f:
    for chunk in blob:
        f.write(chunk)

Async Client


python 
from azure.containe

🎯 Best For

  • Claude users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Azure Containerregistry Py to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Azure Containerregistry Py?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-containerregistry-py/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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