Azure Cosmos DB SDK for Python

Client library for Azure Cosmos DB NoSQL API — globally distributed, multi-model database.

Installation

bash
pip install azure-cosmos azure-identity

Environment Variables

bash
COSMOS_ENDPOINT=https://<account>.documents.azure.com:443/  # Required for all auth methods
COSMOS_DATABASE=mydb  # Required for all auth methods
COSMOS_CONTAINER=mycontainer  # 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: > > 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.

python
import os
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.cosmos import CosmosClient

# 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()

endpoint = "https://<account>.documents.azure.com:443/"

with CosmosClient(url=endpoint, credential=credential) as client:
    # Use client here (see following sections for operations)
    ...

Client Hierarchy

| Client | Purpose | Get From | |--------|---------|----------| | CosmosClient | Account-level operations | Direct instantiation | | DatabaseProxy | Database operations | client.get_database_client() | | ContainerProxy | Container/item operations | database.get_container_client() |

Core Workflow

Setup Database and Container

python
# Get or create database
database = client.create_database_if_not_exists(id="mydb")

# Get or create container with partition key
container = database.create_container_if_not_exists(
    id="mycontainer",
    partition_key=PartitionKey(path="/category")
)

# Get existing
database = client.get_database_client("mydb")
container = database.get_container_client("mycontainer")

Create Item

python
item = {
    "id": "item-001",           # Required: unique within partition
    "category": "electronics",   # Partition key value
    "name": "Laptop",
    "price": 999.99,
    "tags": ["computer", "portable"]
}

created = container.create_item(body=item)
print(f"Created: {created['id']}")

Read Item

python
# Read requires id AND partition key
item = container.read_item(
    item="item-001",
    partition_key="electronics"
)
print(f"Name: {item['name']}")

Update Item (Replace)

python
item = container.read_item(item="item-001", partition_key="electronics")
item["price"] = 899.99
item["on_sale"] = True

updated = container.replace_item(item=item["id"], body=item)

Upsert Item

python
# Create if not exists, replace if exists
item = {
    "id": "item-002",
    "category": "electronics",
    "name": "Tablet",
    "price": 499.99
}

result = container.upsert_item(body=item)

Delete Item

python
container.delete_item(
    item="item-001",
    partition_key="electronics"
)

Queries

Basic Query

python
# Query within a partition (efficient)
query = "SELECT * FROM c WHERE c.price < @max_price"
items = container.query_items(
    query=query,
    parameters=[{"name": "@max_price", "value": 500}],
    partition_key="electronics"
)

for item in items:
    print(f"{item['name']}: ${item['price']}")

Cross-Partition Query

python
# Cross-partition (more expensive, use sparingly)
query = "SELECT * FROM c WHERE c.price < @max_price"
items = container.query_items(
    query=query,
    parameters=[{"name": "@max_price", "value": 500}],
    enable_cross_partition_query=True
)

for item in items:
    print(item)

Query with Projection

python
query = "SELECT c.id, c.name, c.price FROM c WHERE c.category = @category"
items = container.query_items(
    query=query,
    parameters=[{"name": "@category", "value": "electronics"}],
    partition_key="electronics"
)

Read All Items

python
# Read all in a partition
items = container.read_all_items()  # Cross-partition
# Or with partition key
items = container.query_items(
    query="SELECT * FROM c",
    partition_key="electronics"
)

Partition Keys

Critical: Always include partition key for efficient operations.

python
from azure.cosmos import PartitionKey

# Single partition key
container = database.create_container_if_not_exists(
    id="orders",
    partition_key=PartitionKey(path="/customer_id")
)

# Hierarchical partition key (preview)
container = database.create_container_if_not_exists(
    id="events",
    partition_key=PartitionKey(path=["/tenant_id", "/user_id"])
)

Throughput

python
# Create container with provisioned throughput
container = database.create_container_if_not_exists(
    id="mycontainer",
    partition_key=PartitionKey(path="/pk"),
    offer_throughput=400  # RU/s
)

# Read current throughput
offer = container.read_offer()
print(f"Throughput: {offer.offer_throughput} RU/s")

# Update throughput
container.replace_throughput(throughput=1000)

Async Client

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

async def cosmos_operations():
    async with DefaultAzureCredential() as credential:
        async with CosmosClient(endpoint, credential=credential) as client:
            database = client.get_database_client("mydb")
            container = database.get_container_client("mycontainer")
            
            # Create
            await container.create_item(body={"id": "1", "pk": "test"})
            
            # Read
            item = await container.read_item(item="1", partition_key="test")
            
            # Query
            async for item in container.query_items(
                query="SELECT * FROM c",
                partition_key="test"
            ):
                print(item)

import asyncio
asyncio.run(cosmos_operations())

Error Handling

python
from azure.cosmos.exceptions import CosmosHttpResponseError

try:
    item = container.read_item(item="nonexistent", partition_key="pk")
except CosmosHttpResponseError as e:
    if e.status_code == 404:
        print("Item not found")
    elif e.status_code == 429:
        print(f"Rate limited. Retry after: {e.headers.get('x-ms-retry-after-ms')}ms")
    else:
        raise

Best Practices

1. Pick sync OR async and stay consistent. Do not mix azure.cosmos sync clients with azure.cosmos.aio async clients in the same call path. Choose one mode per module.
2. Always use context managers for clients and async credentials. Wrap every client in with CosmosClient(...) as client: (sync) or async with CosmosClient(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
3. Use DefaultAzureCredential for portable auth across local dev and Azure (avoid connection strings / API keys when possible).
4. Always specify partition key for point reads and queries
5. Use parameterized queries to prevent injection and improve caching
6. Avoid cross-partition queries when possible
7. Use upsert_item for idempotent writes
8. Use async client for high-throughput scenarios
9. Design partition key for even data distribution
10. Use read_item instead of query for single document retrieval

Reference Files

| File | Contents | |------|----------| | references/partitioning.md | Partition key strategies, hierarchical keys, hot partition detection and mitigation | | references/query-patterns.md | Query optimization, aggregations, pagination, transactions, change feed | | scripts/setup_cosmos_container.py | CLI tool for creating containers with partitioning, throughput, and indexing |