azure-mgmt-apimanagement-py
Azure API Management SDK for Python. Use for managing APIM services, APIs, products, subscriptions, and policies. Triggers: "azure-mgmt-apimanagement", "ApiManagementClient", "APIM", "API gateway", "API Management".
- License 许可
- MIT
- 所属仓库
- microsoft/skills
- 最近更新
- 2026-11-14
- Stars
- ★ 3.2k
- Forks
- 368
01 前言 Front Matter
- name
- azure-mgmt-apimanagement-py
- license
- MIT
- metadata
- { "author": "Microsoft", "package": "azure-mgmt-apimanagement", "version": "1.0.0" }
- description
- Azure API Management SDK for Python. Use for managing APIM services, APIs, products, subscriptions, and policies. Triggers: "azure-mgmt-apimanagement", "ApiManagementClient", "APIM", "API gateway", "API Management".
02 资源文件 2
- 参考文档references/capabilities.md2.2 KB
- 参考文档references/non-hero-scenarios.md3.7 KB
03 SKILL.md 正文
Azure API Management SDK for Python
Manage Azure API Management services, APIs, products, and policies.
Installation
pip install azure-mgmt-apimanagement
pip install azure-identity
Environment Variables
AZURE_SUBSCRIPTION_ID=your-subscription-id # 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:
- 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:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.- 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:andasync with DefaultAzureCredential() as credential:(fromazure.identity.aio)Snippets may abbreviate this setup, but production code should always follow both rules.
from azure.identity import DefaultAzureCredential
from azure.mgmt.apimanagement import ApiManagementClient
import os
with ApiManagementClient(
credential=DefaultAzureCredential(),
subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
# Use `client` for all subsequent operations (see examples below)
...
Create APIM Service
from azure.mgmt.apimanagement.models import (
ApiManagementServiceResource,
ApiManagementServiceSkuProperties,
SkuType
)
service = client.api_management_service.begin_create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
parameters=ApiManagementServiceResource(
location="eastus",
publisher_email="admin@example.com",
publisher_name="My Organization",
sku=ApiManagementServiceSkuProperties(
name=SkuType.DEVELOPER,
capacity=1
)
)
).result()
print(f"Created APIM: {service.name}")
Import API from OpenAPI
from azure.mgmt.apimanagement.models import (
ApiCreateOrUpdateParameter,
ContentFormat,
Protocol
)
api = client.api.begin_create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
api_id="my-api",
parameters=ApiCreateOrUpdateParameter(
display_name="My API",
path="myapi",
protocols=[Protocol.HTTPS],
format=ContentFormat.OPENAPI_JSON,
value='{"openapi": "3.0.0", "info": {"title": "My API", "version": "1.0"}, "paths": {"/health": {"get": {"responses": {"200": {"description": "OK"}}}}}}'
)
).result()
print(f"Imported API: {api.display_name}")
Import API from URL
api = client.api.begin_create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
api_id="petstore",
parameters=ApiCreateOrUpdateParameter(
display_name="Petstore API",
path="petstore",
protocols=[Protocol.HTTPS],
format=ContentFormat.OPENAPI_LINK,
value="https://petstore.swagger.io/v2/swagger.json"
)
).result()
List APIs
apis = client.api.list_by_service(
resource_group_name="my-resource-group",
service_name="my-apim"
)
for api in apis:
print(f"{api.name}: {api.display_name} - {api.path}")
Create Product
from azure.mgmt.apimanagement.models import ProductContract
product = client.product.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
product_id="premium",
parameters=ProductContract(
display_name="Premium",
description="Premium tier with unlimited access",
subscription_required=True,
approval_required=False,
state="published"
)
)
print(f"Created product: {product.display_name}")
Add API to Product
client.product_api.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
product_id="premium",
api_id="my-api"
)
Create Subscription
from azure.mgmt.apimanagement.models import SubscriptionCreateParameters
subscription = client.subscription.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
sid="my-subscription",
parameters=SubscriptionCreateParameters(
display_name="My Subscription",
scope=f"/products/premium",
state="active"
)
)
print(f"Subscription key: {subscription.primary_key}")
Set API Policy
from azure.mgmt.apimanagement.models import PolicyContract
policy_xml = """
<policies>
<inbound>
<rate-limit calls="100" renewal-period="60" />
<set-header name="X-Custom-Header" exists-action="override">
<value>CustomValue</value>
</set-header>
</inbound>
<backend>
<forward-request />
</backend>
<outbound />
<on-error />
</policies>
"""
client.api_policy.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
api_id="my-api",
policy_id="policy",
parameters=PolicyContract(
value=policy_xml,
format="xml"
)
)
Create Named Value (Secret)
from azure.mgmt.apimanagement.models import NamedValueCreateContract
named_value = client.named_value.begin_create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
named_value_id="backend-api-key",
parameters=NamedValueCreateContract(
display_name="Backend API Key",
value="secret-key-value",
secret=True
)
).result()
Create Backend
from azure.mgmt.apimanagement.models import BackendContract
backend = client.backend.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
backend_id="my-backend",
parameters=BackendContract(
url="https://api.backend.example.com",
protocol="http",
description="My backend service"
)
)
Create User
from azure.mgmt.apimanagement.models import UserCreateParameters
user = client.user.create_or_update(
resource_group_name="my-resource-group",
service_name="my-apim",
user_id="newuser",
parameters=UserCreateParameters(
email="user@example.com",
first_name="John",
last_name="Doe"
)
)
Operation Groups
| Group | Purpose |
|---|---|
api_management_service |
APIM instance management |
api |
API operations |
api_operation |
API operation details |
api_policy |
API-level policies |
product |
Product management |
product_api |
Product-API associations |
subscription |
Subscription management |
user |
User management |
named_value |
Named values/secrets |
backend |
Backend services |
certificate |
Certificates |
gateway |
Self-hosted gateways |
Best Practices
- Pick sync OR async and stay consistent. Do not mix
azure.xxxsync clients withazure.xxx.aioasync clients in the same call path. Choose one mode per module. - Always use context managers for clients and async credentials. Wrap every client in
with Client(...) as client:(sync) orasync with Client(...) as client:(async). For asyncDefaultAzureCredentialfromazure.identity.aio, also useasync with credential:so tokens and transports are cleaned up. - Use named values for secrets and configuration
- Apply policies at appropriate scopes (global, product, API, operation)
- Use products to bundle APIs and manage access
- Enable Application Insights for monitoring
- Use backends to abstract backend services
- Version your APIs using APIM's versioning features
Reference Files
| File | Contents |
|---|---|
| references/capabilities.md | Additional non-hero capabilities, operation-group coverage, and production checklists. |
| references/non-hero-scenarios.md | Dedicated non-hero examples for secondary/advanced scenarios. |
04 同仓库更多 Skills
skill-creator
Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.
podcast-generation
Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.
microsoft-docs
Understand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention "docs." If the question is about understanding a concept rather than writing code, this is the right skill.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP), Node/TypeScript (MCP SDK), or C#/.NET (Microsoft MCP SDK).
kql
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
github-issue-creator
Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.