Generated banner for Azure Cosmos DB Py
Generated logo for Azure Cosmos DB Py

Azure Cosmos DB Py

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Tool integration
  • Software development
  • MIT
  • Low risk
  • Has scripts

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://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/service-layer.md

Service Layer Pattern

Table of Contents

  1. Service Class Structure

  2. Document Conversion Methods

  3. CRUD Operations

  4. Query Patterns

  5. Graceful Degradation

  6. Complete Example


Service Class Structure

Every service follows this pattern:

from typing import Optional
from app.db.cosmos import get_container, upsert_document, get_document, delete_document, query_documents
from app.models.project import Project, ProjectCreate, ProjectUpdate, ProjectInDB

class ProjectService:
    """Service for project CRUD operations."""
    
    def _use_cosmos(self) -> bool:
        """Check if Cosmos is available."""
        return get_container() is not None
    
    # Document conversion methods
    def _doc_to_model_in_db(self, doc: dict) -> ProjectInDB:
        """Convert Cosmos document to internal model."""
        ...
    
    def _model_in_db_to_doc(self, model: ProjectInDB) -> dict:
        """Convert internal model to Cosmos document."""
        ...
    
    def _model_in_db_to_model(self, model_in_db: ProjectInDB) -> Project:
        """Convert internal model to API response model."""
        ...
    
    # CRUD operations
    async def create(self, data: ProjectCreate, author_id: str) -> Project:
        ...
    
    async def get_by_id(self, project_id: str, workspace_id: str) -> Optional[Project]:
        ...
    
    async def update(self, project_id: str, workspace_id: str, data: ProjectUpdate) -> Optional[Project]:
        ...
    
    async def delete(self, project_id: str, workspace_id: str) -> bool:
        ...
    
    async def list_by_workspace(self, workspace_id: str) -> list[Project]:
        ...

# Singleton instance
project_service = ProjectService()

Document Conversion Methods

Document → Model (from Cosmos)
def _doc_to_model_in_db(self, doc: dict) -> ProjectInDB:
    """Convert Cosmos document to ProjectInDB."""
    return ProjectInDB(
        id=doc["id"],
        name=doc["name"],
        description=doc.get("description"),
        slug=doc["slug"],
        workspace_id=doc["workspaceId"],
        author_id=doc["authorId"],
        visibility=doc.get("visibility", "public"),
        tags=doc.get("tags", []),
        created_at=datetime.fromisoformat(doc["createdAt"]),
        updated_at=datetime.fromisoformat(doc["updatedAt"]) if doc.get("updatedAt") else None,
        doc_type=doc.get("docType", "project"),
    )
Model → Document (to Cosmos)
def _model_in_db_to_doc(self, model: ProjectInDB) -> dict:
    """Convert ProjectInDB to Cosmos document."""
    return {
        "id": model.id,
        "name": model.name,
        "description": model.description,
        "slug": model.slug,
        "workspaceId": model.workspace_id,  # Partition key
        "authorId": model.author_id,
        "visibility": model.visibility,
        "tags": model.tags,
        "createdAt": model.created_at.isoformat(),
        "updatedAt": model.updated_at.isoformat() if model.updated_at else None,
        "docType": model.doc_type,
    }
InDB → Response (strip internal fields)
def _model_in_db_to_model(self, model_in_db: ProjectInDB) -> Project:
    """Convert ProjectInDB to API response model."""
    return Project(
        id=model_in_db.id,
        name=model_in_db.name,
        description=model_in_db.description,
        slug=model_in_db.slug,
        workspace_id=model_in_db.workspace_id,
        author_id=model_in_db.author_id,
        visibility=model_in_db.visibility,
        tags=model_in_db.tags,
        created_at=model_in_db.created_at,
        updated_at=model_in_db.updated_at,
    )

CRUD Operations

Create
async def create(self, data: ProjectCreate, author_id: str) -> Project:
    """Create a new project."""
    if not self._use_cosmos():
        raise RuntimeError("Database unavailable")
    
    now = datetime.now(timezone.utc)
    slug = await self._generate_unique_slug(data.name, data.workspace_id)
    
    project_in_db = ProjectInDB(
        id=str(uuid.uuid4()),
        name=data.name,
        description=data.description,
        slug=slug,
        workspace_id=data.workspace_id,
        author_id=author_id,
        visibility=data.visibility,
        tags=data.tags,
        created_at=now,
        updated_at=None,
        doc_type="project",
    )
    
    doc = self._model_in_db_to_doc(project_in_db)
    await upsert_document(doc, partition_key=data.workspace_id)
    
    return self._model_in_db_to_model(project_in_db)
Read (Get by ID)
async def get_by_id(self, project_id: str, workspace_id: str) -> Optional[Project]:
    """Get project by ID. Returns None if not found."""
    if not self._use_cosmos():
        return None
    
    doc = await get_document(project_id, partition_key=workspace_id)
    if doc is None:
        return None
    
    model_in_db = self._doc_to_model_in_db(doc)
    return self._model_in_db_to_model(model_in_db)
Update
async def update(
    self, project_id: str, workspace_id: str, data: ProjectUpdate
) -> Optional[Project]:
    """Update project. Returns None if not found."""
    if not self._use_cosmos():
        return None
    
    doc = await get_document(project_id, partition_key=workspace_id)
    if doc is None:
        return None
    
    model_in_db = self._doc_to_model_in_db(doc)
    
    # Apply updates (only non-None fields)
    update_data = data.model_dump(exclude_unset=True)
    for field, value in update_data.items():
        if hasattr(model_in_db, field):
            setattr(model_in_db, field, value)
    
    model_in_db.updated_at = datetime.now(timezone.utc)
    
    updated_doc = self._model_in_db_to_doc(model_in_db)
    await upsert_document(updated_doc, partition_key=workspace_id)
    
    return self._model_in_db_to_model(model_in_db)
Delete
async def delete(self, project_id: str, workspace_id: str) -> bool:
    """Delete project. Returns True if deleted."""
    if not self._use_cosmos():
        return False
    
    return await delete_document(project_id, partition_key=workspace_id)
List
async def list_by_workspace(self, workspace_id: str) -> list[Project]:
    """List all projects in a workspace."""
    if not self._use_cosmos():
        return []
    
    docs = await query_documents(
        doc_type="project",
        partition_key=workspace_id,
    )
    
    return [
        self._model_in_db_to_model(self._doc_to_model_in_db(doc))
        for doc in docs
    ]

Query Patterns

Basic Query with Filter
async def get_by_slug(self, slug: str, workspace_id: str) -> Optional[Project]:
    """Get project by slug within a workspace."""
    docs = await query_documents(
        doc_type="project",
        partition_key=workspace_id,
        extra_filter="AND c.slug = @slug",
        parameters=[{"name": "@slug", "value": slug}],
    )
    
    if not docs:
        return None
    
    return self._model_in_db_to_model(self._doc_to_model_in_db(docs[0]))
Unique Slug Generation
async def _generate_unique_slug(self, name: str, workspace_id: str) -> str:
    """Generate unique slug from name."""
    base_slug = slugify(name)
    slug = base_slug
    counter = 1
    
    while True:
        existing = await query_documents(
            doc_type="project",
            partition_key=workspace_id,
            extra_filter="AND c.slug = @slug",
            parameters=[{"name": "@slug", "value": slug}],
        )
        if not existing:
            return slug
        slug = f"{base_slug}-{counter}"
        counter += 1

Graceful Degradation

Every public method checks _use_cosmos() and returns safe defaults:

Return TypeDefault
Optional[Model]None
list[Model][]
boolFalse
Required createraise RuntimeError
async def get_by_id(self, project_id: str, workspace_id: str) -> Optional[Project]:
    if not self._use_cosmos():
        return None  # Graceful None instead of exception
    ...

Complete Example

See assets/service_template.py for a production-ready service 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

What our scanner noticed· Low risk

  • Instructions that use the network
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

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)
Synced

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-cosmos-db-py.zip