Azure Mgmt Apicenter Py
Azure Mgmt Apicenter Py is an code AI skill with a core value of |. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
|
Quick Facts
mkdir -p ./skills/azure-mgmt-apicenter-py && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-mgmt-apicenter-py/SKILL.md -o ./skills/azure-mgmt-apicenter-py/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Azure API Center Management SDK for Python
Manage API inventory, metadata, and governance in Azure API Center.
Installation
pip install azure-mgmt-apicenter
pip install azure-identityEnvironment Variables
AZURE_SUBSCRIPTION_ID=your-subscription-idAuthentication
from azure.identity import DefaultAzureCredential
from azure.mgmt.apicenter import ApiCenterMgmtClient
import os
client = ApiCenterMgmtClient(
credential=DefaultAzureCredential(),
subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
)Create API Center
from azure.mgmt.apicenter.models import Service
api_center = client.services.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
resource=Service(
location="eastus",
tags={"environment": "production"}
)
)
print(f"Created API Center: {api_center.name}")List API Centers
api_centers = client.services.list_by_subscription()
for api_center in api_centers:
print(f"{api_center.name} - {api_center.location}")Register an API
from azure.mgmt.apicenter.models import Api, ApiKind, LifecycleStage
api = client.apis.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
resource=Api(
title="My API",
description="A sample API for demonstration",
kind=ApiKind.REST,
lifecycle_stage=LifecycleStage.PRODUCTION,
terms_of_service={"url": "https://example.com/terms"},
contacts=[{"name": "API Team", "email": "api-team@example.com"}]
)
)
print(f"Registered API: {api.title}")Create API Version
from azure.mgmt.apicenter.models import ApiVersion, LifecycleStage
version = client.api_versions.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
version_name="v1",
resource=ApiVersion(
title="Version 1.0",
lifecycle_stage=LifecycleStage.PRODUCTION
)
)
print(f"Created version: {version.title}")Add API Definition
from azure.mgmt.apicenter.models import ApiDefinition
definition = client.api_definitions.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
version_name="v1",
definition_name="openapi",
resource=ApiDefinition(
title="OpenAPI Definition",
description="OpenAPI 3.0 specification"
)
)Import API Specification
from azure.mgmt.apicenter.models import ApiSpecImportRequest, ApiSpecImportSourceFormat
# Import from inline content
client.api_definitions.import_specification(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
version_name="v1",
definition_name="openapi",
body=ApiSpecImportRequest(
format=ApiSpecImportSourceFormat.INLINE,
value='{"openapi": "3.0.0", "info": {"title": "My API", "version": "1.0"}, "paths": {}}'
)
)List APIs
apis = client.apis.list(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default"
)
for api in apis:
print(f"{api.name}: {api.title} ({api.kind})")Create Environment
from azure.mgmt.apicenter.models import Environment, EnvironmentKind
environment = client.environments.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
environment_name="production",
resource=Environment(
title="Production",
description="Production environment",
kind=EnvironmentKind.PRODUCTION,
server={"type": "Azure API Management", "management_portal_uri": ["https://portal.azure.com🎯 Best For
- Claude users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 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
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Mgmt Apicenter Py to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is Azure Mgmt Apicenter Py compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Azure Mgmt Apicenter Py?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Azure Mgmt Apicenter Py?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-mgmt-apicenter-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
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.