/install azure-cosmos-py
Azure Cosmos DB SDK for Python
Client library for Azure Cosmos DB NoSQL API — globally distributed, multi-model database.
Installation
pip install azure-cosmos azure-identity
Environment Variables
COSMOS_ENDPOINT=https://\x3Caccount>.documents.azure.com:443/
COSMOS_DATABASE=mydb
COSMOS_CONTAINER=mycontainer
Authentication
from azure.identity import DefaultAzureCredential
from azure.cosmos import CosmosClient
credential = DefaultAzureCredential()
endpoint = "https://\x3Caccount>.documents.azure.com:443/"
client = CosmosClient(url=endpoint, credential=credential)
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
# 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
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
# Read requires id AND partition key
item = container.read_item(
item="item-001",
partition_key="electronics"
)
print(f"Name: {item['name']}")
Update Item (Replace)
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
# 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
container.delete_item(
item="item-001",
partition_key="electronics"
)
Queries
Basic Query
# Query within a partition (efficient)
query = "SELECT * FROM c WHERE c.price \x3C @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
# Cross-partition (more expensive, use sparingly)
query = "SELECT * FROM c WHERE c.price \x3C @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
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
# 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.
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
# 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
from azure.cosmos.aio import CosmosClient
from azure.identity.aio import DefaultAzureCredential
async def cosmos_operations():
credential = DefaultAzureCredential()
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
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
- Always specify partition key for point reads and queries
- Use parameterized queries to prevent injection and improve caching
- Avoid cross-partition queries when possible
- Use
upsert_itemfor idempotent writes - Use async client for high-throughput scenarios
- Design partition key for even data distribution
- Use
read_iteminstead 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 |
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install azure-cosmos-py - After installation, invoke the skill by name or use
/azure-cosmos-py - Provide required inputs per the skill's parameter spec and get structured output
What is Azure Cosmos DB Python?
Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data. Triggers: "cosmos db", "CosmosClient", "container", "document", "NoSQL", "partition key". It is an AI Agent Skill for Claude Code / OpenClaw, with 1451 downloads so far.
How do I install Azure Cosmos DB Python?
Run "/install azure-cosmos-py" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Azure Cosmos DB Python free?
Yes, Azure Cosmos DB Python is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Azure Cosmos DB Python support?
Azure Cosmos DB Python is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Azure Cosmos DB Python?
It is built and maintained by thegovind (@thegovind); the current version is v0.1.0.