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Azure Cosmos DB Py

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From the author

Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides patterns and templates for integrating Azure Cosmos DB into Python and FastAPI applications. It focuses on secure authentication using DefaultAzureCredential, singleton client management, and service layer patterns for CRUD operations. The guidance includes strategies for partition key management, parameterized queries, and TDD-based testing using pytest.

What it does

  • Provides a singleton pattern for Cosmos DB client initialization.
  • Implements dual authentication for local emulator and Azure production environments.
  • Wraps synchronous SDK calls for asynchronous execution in FastAPI.
  • Defines a service layer pattern for document-to-model conversion.
  • Offers templates for pytest fixtures to facilitate unit testing.
  • Outlines error handling patterns for common Cosmos DB exceptions.

When to use it

  • When building a FastAPI backend that requires NoSQL persistence with Azure Cosmos DB.
  • When you need to implement secure, RBAC-based authentication for database access.
  • When you want to structure your database interaction layer using service classes.
  • When you need to write unit tests for code that interacts with the Cosmos DB SDK.

Advantages

  • Promotes secure coding by using identity-based authentication instead of hardcoded keys.
  • Ensures consistent connection management through singleton patterns.
  • Facilitates testability by providing patterns for mocking database containers.
  • Encourages clean code through separation of concerns between business logic and storage.

Usage examples

“How do I set up a singleton Cosmos DB client in my FastAPI app?”
The skill provides a module-level initialization pattern that uses DefaultAzureCredential for production and key-based auth for the local emulator.
“Show me how to test a service layer method that reads from Cosmos DB.”
The skill provides a pytest fixture template that uses mocking to simulate the Cosmos container, allowing you to test service logic without a live database.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/azure-cosmos-db-py/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-cosmos-db-py.zip -d .agents/skills

Documentation by Microsoft

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/  # Required for all auth methods
COSMOS_DATABASE_NAME=<database-name>  # Required for all auth methods
COSMOS_CONTAINER_ID=<container-id>  # Required for all auth methods
# For emulator only (not production)
COSMOS_KEY=<emulator-key>  # Only required for key-based auth or emulator
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.

DefaultAzureCredential (preferred):

import os
from azure.cosmos import CosmosClient
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 CosmosClient(
    url=os.environ["COSMOS_ENDPOINT"],
    credential=credential
) as client:
    # Use client here (see following sections for operations)
    ...

Emulator (local development):

from azure.cosmos import CosmosClient

with CosmosClient(
    url="https://localhost:8081",
    credential=os.environ["COSMOS_KEY"],
    connection_verify=False
) as client:
    # Use client here (see following sections for operations)
    ...

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:
        # Singleton: client lives for the FastAPI app lifetime; close in a lifespan shutdown handler.
        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

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 the client in async with CosmosClient(...) as client: (or manage its lifetime via FastAPI lifespan and close it explicitly). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.

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

Files

references/client-setup.md

Cosmos DB Client Setup

Table of Contents

  1. Dual Authentication Strategy

  2. Singleton Pattern

  3. Async Wrapping

  4. Configuration Management

  5. Connection Reset

  6. Complete Implementation


Dual Authentication Strategy

Use DefaultAzureCredential for Azure deployments and key-based auth only for the local emulator:

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

def _is_emulator_endpoint(endpoint: str) -> bool:
    """Detect Cosmos emulator by endpoint URL."""
    return "localhost" in endpoint.lower() or "127.0.0.1" in endpoint

def _create_client(settings) -> CosmosClient:
    if _is_emulator_endpoint(settings.cosmos_endpoint):
        # Emulator: use well-known key, disable SSL verification
        return CosmosClient(
            url=settings.cosmos_endpoint,
            credential=settings.cosmos_key,
            connection_verify=False  # Emulator uses self-signed cert
        )
    else:
        # Azure: use RBAC via DefaultAzureCredential
        credential = DefaultAzureCredential()
        return CosmosClient(
            url=settings.cosmos_endpoint,
            credential=credential
        )
Security Notes
  • Never store production keys in code or config files

  • The emulator key (C2y6yDjf5/R+ob0N8A7Cgv...) is publicly documented and safe to hardcode

  • Requires "Cosmos DB Built-in Data Contributor" role for RBAC auth

  • Run az login before local development against Azure Cosmos


Singleton Pattern

Initialize container once at module level to reuse connections:

import logging
from typing import Optional
from azure.cosmos import ContainerProxy

logger = logging.getLogger(__name__)

_cosmos_container: Optional[ContainerProxy] = None
_init_attempted: bool = False

def get_container() -> Optional[ContainerProxy]:
    """Get Cosmos container, initializing on first call."""
    global _cosmos_container, _init_attempted
    
    if _init_attempted:
        return _cosmos_container
    
    _init_attempted = True
    
    try:
        client = _create_client(settings)
        database = client.get_database_client(settings.cosmos_database_name)
        _cosmos_container = database.get_container_client(settings.cosmos_container_id)
        
        # Verify connection with a lightweight operation
        _cosmos_container.read()
        logger.info(f"✅ Connected to Cosmos DB: {settings.cosmos_database_name}/{settings.cosmos_container_id}")
        
    except Exception as e:
        logger.error(f"❌ Failed to initialize Cosmos DB: {type(e).__name__}: {e}")
        import traceback
        logger.error(traceback.format_exc())
        _cosmos_container = None
    
    return _cosmos_container
Why Singleton?
  1. Connection Reuse: Cosmos SDK manages connection pooling internally

  2. Startup Validation: Fail fast if Cosmos is misconfigured

  3. Graceful Degradation: Services check get_container() is not None


Async Wrapping

The Cosmos Python SDK is synchronous. Wrap calls with run_in_threadpool to avoid blocking FastAPI:

from starlette.concurrency import run_in_threadpool

async def upsert_document(doc: dict, partition_key: str) -> dict:
    """Insert or update a document."""
    container = get_container()
    if container is None:
        raise RuntimeError("Cosmos DB not initialized")
    
    result = await run_in_threadpool(
        container.upsert_item,
        doc
    )
    return result

async def get_document(doc_id: str, partition_key: str) -> Optional[dict]:
    """Read a document by ID."""
    container = get_container()
    if container is None:
        return None
    
    try:
        result = await run_in_threadpool(
            container.read_item,
            item=doc_id,
            partition_key=partition_key
        )
        return result
    except CosmosResourceNotFoundError:
        return None

async def delete_document(doc_id: str, partition_key: str) -> bool:
    """Delete a document. Returns True if deleted."""
    container = get_container()
    if container is None:
        return False
    
    try:
        await run_in_threadpool(
            container.delete_item,
            item=doc_id,
            partition_key=partition_key
        )
        return True
    except CosmosResourceNotFoundError:
        return False

Configuration Management

Use Pydantic Settings with environment-aware defaults:

from pydantic_settings import BaseSettings
from pydantic import model_validator

class Settings(BaseSettings):
    environment: str = "local"
    
    cosmos_endpoint: str = ""
    cosmos_key: str = ""  # Only for emulator
    cosmos_database_name: str = "my-database"
    cosmos_container_id: str = "my-container"
    
    class Config:
        env_file = ".env"
        extra = "ignore"
    
    @model_validator(mode="after")
    def configure_for_environment(self) -> "Settings":
        """Set defaults based on environment."""
        if self.environment == "local" and not self.cosmos_endpoint:
            # Default to emulator
            self.cosmos_endpoint = "https://localhost:8081"
            self.cosmos_key = "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4GUg9jsLAi7dnvNdc0SKFO+GRNpsq24UdBkbFCL/6C+iW9zQ=="
        return self

settings = Settings()
Environment Variables
VariableDescriptionRequired
COSMOS_ENDPOINTCosmos account URLYes
COSMOS_KEYAccount key (emulator only)No
COSMOS_DATABASE_NAMEDatabase nameYes
COSMOS_CONTAINER_IDContainer nameYes

Connection Reset

For testing or environment switching:

def reset_connection() -> None:
    """Reset Cosmos connection. Call between tests or after config changes."""
    global _cosmos_container, _init_attempted
    _cosmos_container = None
    _init_attempted = False

Complete Implementation

See assets/cosmos_client_template.py for a production-ready implementation.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python

Security

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Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-sdk-python/skills/azure-cosmos-db-py · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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