跳到正文
cccskills
Microsoft 官方免费在 GitHub 公开

azure-containerregistry-py

Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories. Triggers: "azure-containerregistry", "ContainerRegistryClient", "container images", "docker registry", "ACR".

中文简介正在准备中。当前显示原文说明。

集成工具Azure
查看安装方法

包含的文件(3)

  • SKILL.md8.5 KB
  • references/capabilities.md1.7 KB
  • references/non-hero-scenarios.md2.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Azure Container Registry SDK for Python

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

Installation

pip install azure-containerregistry

Environment Variables

AZURE_CONTAINERREGISTRY_ENDPOINT=https://<registry-name>.azurecr.io  # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication & Lifecycle

🔑 Two rules apply to every code sample below:

  1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
    • Local dev: DefaultAzureCredential works as-is.
    • Production: set AZURE_TOKEN_CREDENTIALS=prod (or AZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
  2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
    • Sync: with <Client>(...) as client:
    • Async: async with <Client>(...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio)

Snippets may abbreviate this setup, but production code should always follow both rules.

Entra ID (Recommended)

import os
from azure.containerregistry import ContainerRegistryClient
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()

with ContainerRegistryClient(
    endpoint=os.environ["AZURE_CONTAINERREGISTRY_ENDPOINT"],
    credential=credential
) as client:
    # Use client here (see following sections for operations)
    ...

Anonymous Access (Public Registry)

from azure.containerregistry import ContainerRegistryClient

with ContainerRegistryClient(
    endpoint="https://mcr.microsoft.com",
    credential=None,
    audience="https://mcr.microsoft.com"
) as client:
    # Use client here (see following sections for operations)
    ...

List Repositories

with ContainerRegistryClient(endpoint, DefaultAzureCredential()) as client:
    for repository in client.list_repository_names():
        print(repository)

Repository Operations

Get Repository Properties

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

from azure.containerregistry import RepositoryProperties

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

Delete Repository

client.delete_repository("my-image")

List Tags

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

Filter by Order

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

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

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

from azure.containerregistry import ArtifactManifestProperties

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

Delete Manifest

# 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

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

Delete Tag

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

Upload and Download Artifacts

from azure.containerregistry import ContainerRegistryClient

with ContainerRegistryClient(endpoint, DefaultAzureCredential()) as client:
    # 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

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

async def list_repos():
    async with DefaultAzureCredential() as credential:
        async with ContainerRegistryClient(endpoint, credential) as client:
            async for repo in client.list_repository_names():
                print(repo)

Clean Up Old Images

from datetime import datetime, timedelta, timezone

cutoff = datetime.now(timezone.utc) - timedelta(days=30)

for manifest in client.list_manifest_properties("my-image"):
    if manifest.last_updated_on < cutoff and not manifest.tags:
        print(f"Deleting {manifest.digest}")
        client.delete_manifest("my-image", manifest.digest)

Client Operations

OperationDescription
list_repository_namesList all repositories
get_repository_propertiesGet repository metadata
delete_repositoryDelete repository and all images
list_tag_propertiesList tags in repository
get_tag_propertiesGet tag metadata
delete_tagDelete specific tag
list_manifest_propertiesList manifests in repository
get_manifest_propertiesGet manifest metadata
delete_manifestDelete manifest by digest
download_manifestDownload manifest content
download_blobDownload layer blob

Best Practices

  1. Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
  2. Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
  3. Use Microsoft Entra ID for authentication in production
  4. Delete by digest not tag to avoid orphaned images
  5. Lock production images with can_delete=False
  6. Clean up untagged manifests regularly
  7. Use async client for high-throughput operations
  8. Order by last_updated to find recent/old images
  9. Check manifest.tags before deleting to avoid removing tagged images

Reference Files

FileContents
references/capabilities.mdAdditional non-hero capabilities, operation-group coverage, and production checklists.
references/non-hero-scenarios.mdDedicated non-hero examples for secondary/advanced scenarios.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

agent-framework-azure-ai-py

Microsoft 官方免费

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

airunway-aks-setup

Microsoft 官方免费

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

aks-gpu-inference

Microsoft 官方免费

Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

aks-known-issues

Microsoft 官方免费

Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

aks-network-capture

Microsoft 官方免费

Collects bounded packet captures from AKS nodes and Azure network configuration for wire-level evidence. WHEN: "capture packets on an AKS node", "take a pcap", "run tcpdump on AKS", "prove where packets drop". Use for explicit packet-capture intent after read-only diagnostics, not general AKS connectivity or ingress troubleshooting.

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

aks-troubleshooting

Microsoft 官方免费

Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.

中文简介正在准备中。当前显示原文说明。

microsoft/skills31372026年10月21日 更新

查看 microsoft 的全部技能

报告此技能的问题