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✳Claude Code
By Dave AIDave AI original
MIT · FreeView skill
Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization.
---
name: azure-mgmt-apicenter-py
description: Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization.
risk: critical
source: community
date_added: '2026-02-27'
---
# Azure API Center Management SDK for Python
Manage API inventory, metadata, and governance in Azure API Center.
## Installation
```bash
pip install azure-mgmt-apicenter
pip install azure-identity
```
## Environment Variables
```bash
AZURE_SUBSCRIPTION_ID=your-subscription-id
```
## Authentication
```python
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
```python
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
```python
api_centers = client.services.list_by_subscription()
for api_center in api_centers:
print(f"{api_center.name} - {api_center.location}")
```
## Register an API
```python
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
```python
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
```python
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
```python
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
```python
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
```python
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"]}
)
)
```
## Create Deployment
```python
from azure.mgmt.apicenter.models import Deployment, DeploymentState
deployment = client.deployments.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
deployment_name="prod-deployment",
resource=Deployment(
title="Production Deployment",
description="Deployed to production APIM",
environment_id="/workspaces/default/environments/production",
definition_id="/workspaces/default/apis/my-api/versions/v1/definitions/openapi",
state=DeploymentState.ACTIVE,
server={"runtime_uri": ["https://api.example.com"]}
)
)
```
## Define Custom Metadata
```python
from azure.mgmt.apicenter.models import MetadataSchema
metadata = client.metadata_schemas.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
metadata_schema_name="data-classification",
resource=MetadataSchema(
schema='{"type": "string", "title": "Data Classification", "enum": ["public", "internal", "confidential"]}'
)
)
```
## Client Types
| Client | Purpose |
|--------|---------|
| `ApiCenterMgmtClient` | Main client for all operations |
## Operations
| Operation Group | Purpose |
|----------------|---------|
| `services` | API Center service management |
| `workspaces` | Workspace management |
| `apis` | API registration and management |
| `api_versions` | API version management |
| `api_definitions` | API definition management |
| `deployments` | Deployment tracking |
| `environments` | Environment management |
| `metadata_schemas` | Custom metadata definitions |
## Best Practices
1. **Use workspaces** to organize APIs by team or domain
2. **Define metadata schemas** for consistent governance
3. **Track deployments** to understand where APIs are running
4. **Import specifications** to enable API analysis and linting
5. **Use lifecycle stages** to track API maturity
6. **Add contacts** for API ownership and support
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
---
name: azure-mgmt-apicenter-py
description: Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization.
risk: critical
source: community
date_added: '2026-02-27'
---
# Azure API Center Management SDK for Python
Manage API inventory, metadata, and governance in Azure API Center.
## Installation
```bash
pip install azure-mgmt-apicenter
pip install azure-identity
```
## Environment Variables
```bash
AZURE_SUBSCRIPTION_ID=your-subscription-id
```
## Authentication
```python
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
```python
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
```python
api_centers = client.services.list_by_subscription()
for api_center in api_centers:
print(f"{api_center.name} - {api_center.location}")
```
## Register an API
```python
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
```python
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
```python
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
```python
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
```python
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
```python
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"]}
)
)
```
## Create Deployment
```python
from azure.mgmt.apicenter.models import Deployment, DeploymentState
deployment = client.deployments.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
workspace_name="default",
api_name="my-api",
deployment_name="prod-deployment",
resource=Deployment(
title="Production Deployment",
description="Deployed to production APIM",
environment_id="/workspaces/default/environments/production",
definition_id="/workspaces/default/apis/my-api/versions/v1/definitions/openapi",
state=DeploymentState.ACTIVE,
server={"runtime_uri": ["https://api.example.com"]}
)
)
```
## Define Custom Metadata
```python
from azure.mgmt.apicenter.models import MetadataSchema
metadata = client.metadata_schemas.create_or_update(
resource_group_name="my-resource-group",
service_name="my-api-center",
metadata_schema_name="data-classification",
resource=MetadataSchema(
schema='{"type": "string", "title": "Data Classification", "enum": ["public", "internal", "confidential"]}'
)
)
```
## Client Types
| Client | Purpose |
|--------|---------|
| `ApiCenterMgmtClient` | Main client for all operations |
## Operations
| Operation Group | Purpose |
|----------------|---------|
| `services` | API Center service management |
| `workspaces` | Workspace management |
| `apis` | API registration and management |
| `api_versions` | API version management |
| `api_definitions` | API definition management |
| `deployments` | Deployment tracking |
| `environments` | Environment management |
| `metadata_schemas` | Custom metadata definitions |
## Best Practices
1. **Use workspaces** to organize APIs by team or domain
2. **Define metadata schemas** for consistent governance
3. **Track deployments** to understand where APIs are running
4. **Import specifications** to enable API analysis and linting
5. **Use lifecycle stages** to track API maturity
6. **Add contacts** for API ownership and support
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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