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azure-cosmos-db-pyAzure cosmos DB PY 数据库

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用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

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来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:azure-cosmos-db-py(Azure cosmos DB PY 数据库)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/azure-cosmos-db-py
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill azure-cosmos-db-py
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill azure-cosmos-db-py

简介

基于 Python 构建生产级 Cosmos DB NoSQL 服务的工具包。

  • 适用于文档型数据存储、跨分区查询与批量操作开发。
  • 支持 DefaultAzureCredential 认证与模拟器本地调试。
  • 需配置 COSMOS_ENDPOINT 和数据库名称等环境变量。
  • 遵循 Clean Code 与测试驱动原则保障服务稳定性。

SKILL.md

Cosmos DB Service Implementation

Build production-grade Azure Cosmos DB NoSQL services following clean code, security best practices, and TDD principles.

Installation

pip install azure-cosmos azure-identity

Environment Variables

COSMOS_ENDPOINT=https://<account>.documents.azure.com:443/
COSMOS_DATABASE_NAME=<database-name>
COSMOS_CONTAINER_ID=<container-id>
# For emulator only (not production)
COSMOS_KEY=<emulator-key>

Authentication

DefaultAzureCredential (preferred):

from azure.cosmos import CosmosClient
from azure.identity import DefaultAzureCredential

client = CosmosClient(
    url=os.environ["COSMOS_ENDPOINT"],
    credential=DefaultAzureCredential()
)

Emulator (local development):

from azure.cosmos import CosmosClient

client = CosmosClient(
    url="https://localhost:8081",
    credential=os.environ["COSMOS_KEY"],
    connection_verify=False
)

Architecture Overview

┌─────────────────────────────────────────────────────────────────┐
│                         FastAPI Router                          │
│  - Auth dependencies (get_current_user, get_current_user_required)
│  - HTTP error responses (HTTPException)                         │
└──────────────────────────────┬──────────────────────────────────┘
                               │
┌──────────────────────────────▼──────────────────────────────────┐
│                        Service Layer                            │
│  - Business logic and validation                                │
│  - Document ↔ Model conversion                                  │
│  - Graceful degradation when Cosmos unavailable                 │
└──────────────────────────────┬──────────────────────────────────┘
                               │
┌──────────────────────────────▼──────────────────────────────────┐
│                     Cosmos DB Client Module                     │
│  - Singleton container initialization                           │
│  - Dual auth: DefaultAzureCredential (Azure) / Key (emulator)   │
│  - Async wrapper via run_in_threadpool                          │
└─────────────────────────────────────────────────────────────────┘

Quick Start

1. Client Module Setup

Create a singleton Cosmos client with dual authentication:

# db/cosmos.py
from azure.cosmos import CosmosClient
from azure.identity import DefaultAzureCredential
from starlette.concurrency import run_in_threadpool

_cosmos_container = None

def _is_emulator_endpoint(endpoint: str) -> bool:
    return "localhost" in endpoint or "127.0.0.1" in endpoint

async def get_container():
    global _cosmos_container
    if _cosmos_container is None:
        if _is_emulator_endpoint(settings.cosmos_endpoint):
            client = CosmosClient(
                url=settings.cosmos_endpoint,
                credential=settings.cosmos_key,
                connection_verify=False
            )
        else:
            client = CosmosClient(
                url=settings.cosmos_endpoint,
                credential=DefaultAzureCredential()
            )
        db = client.get_database_client(settings.cosmos_database_name)
        _cosmos_container = db.get_container_client(settings.cosmos_container_id)
    return _cosmos_container

Full implementation: See references/client-setup.md

2. Pydantic Model Hierarchy

Use five-tier model pattern for clean separation:

class ProjectBase(BaseModel):           # Shared fields
    name: str = Field(..., min_length=1, max_length=200)

class ProjectCreate(ProjectBase):       # Creation request
    workspace_id: str = Field(..., alias="workspaceId")

class ProjectUpdate(BaseModel):         # Partial updates (all optional)
    name: Optional[str] = Field(None, min_length=1)

class Project(ProjectBase):             # API response
    id: str
    created_at: datetime = Field(..., alias="createdAt")

class ProjectInDB(Project):             # Internal with docType
    doc_type: str = "project"

3. Service Layer Pattern

class ProjectService:
    def _use_cosmos(self) -> bool:
        return get_container() is not None

    async def get_by_id(self, project_id: str, workspace_id: str) -> Project | None:
        if not self._use_cosmos():
            return None
        doc = await get_document(project_id, partition_key=workspace_id)
        if doc is None:
            return None
        return self._doc_to_model(doc)

Full patterns: See references/service-layer.md

Core Principles

Security Requirements

  1. RBAC Authentication: Use DefaultAzureCredential in Azure — never store keys in code
  2. Emulator-Only Keys: Hardcode the well-known emulator key only for local development
  3. Parameterized Queries: Always use @parameter syntax — never string concatenation
  4. Partition Key Validation: Validate partition key access matches user authorization

Clean Code Conventions

  1. Single Responsibility: Client module handles connection; services handle business logic
  2. Graceful Degradation: Services return None/[] when Cosmos unavailable
  3. Consistent Naming: _doc_to_model(), _model_to_doc(), _use_cosmos()
  4. Type Hints: Full typing on all public methods
  5. CamelCase Aliases: Use Field(alias="camelCase") for JSON serialization

TDD Requirements

Write tests BEFORE implementation using these patterns:

@pytest.fixture
def mock_cosmos_container(mocker):
    container = mocker.MagicMock()
    mocker.patch("app.db.cosmos.get_container", return_value=container)
    return container

@pytest.mark.asyncio
async def test_get_project_by_id_returns_project(mock_cosmos_container):
    # Arrange
    mock_cosmos_container.read_item.return_value = {"id": "123", "name": "Test"}

    # Act
    result = await project_service.get_by_id("123", "workspace-1")

    # Assert
    assert result.id == "123"
    assert result.name == "Test"

Full testing guide: See references/testing.md

Reference Files

FileWhen to Read
references/client-setup.mdSetting up Cosmos client with dual auth, SSL config, singleton pattern
references/service-layer.mdImplementing full service class with CRUD, conversions, graceful degradation
references/testing.mdWriting pytest tests, mocking Cosmos, integration test setup
references/partitioning.mdChoosing partition keys, cross-partition queries, move operations
references/error-handling.mdHandling CosmosResourceNotFoundError, logging, HTTP error mapping

Template Files

FilePurpose
assets/cosmos_client_template.pyReady-to-use client module
assets/service_template.pyService class skeleton
assets/conftest_template.pypytest fixtures for Cosmos mocking

Quality Attributes (NFRs)

Reliability

  • Graceful degradation when Cosmos unavailable
  • Retry logic with exponential backoff for transient failures
  • Connection pooling via singleton pattern

Security

  • Zero secrets in code (RBAC via DefaultAzureCredential)
  • Parameterized queries prevent injection
  • Partition key isolation enforces data boundaries

Maintainability

  • Five-tier model pattern enables schema evolution
  • Service layer decouples business logic from storage
  • Consistent patterns across all entity services

Testability

  • Dependency injection via get_container()
  • Easy mocking with module-level globals
  • Clear separation enables unit testing without Cosmos

Performance

  • Partition key queries avoid cross-partition scans
  • Async wrapping prevents blocking FastAPI event loop
  • Minimal document conversion overhead

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.

适合场景

01

Azure 资源规划

02

云服务升级

03

基础设施检查

04

企业云环境自动化

能力概览

能力 1

整理 Azure 服务操作流程

能力 2

提示 CLI/MCP 前置条件

能力 3

辅助云资源检查和规划

能力 4

保留官方服务来源线索

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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