Azure Cosmos Py

---
name: azure-cosmos-py
description: Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
risk: critical
source: community
date_added: '2026-02-27'
---
## Bundled upstream support

Supporting files are included at skill-relative paths. See [UPSTREAM-NOTICE.md](UPSTREAM-NOTICE.md) for their pinned sources, licenses, hashes, and import changes.

## Supporting material availability

These paths remain unavailable in this catalog copy:

- `<support-root>/scripts/setup_cosmos_container.py`

Do not invoke a step that requires one of these files. Obtain the original material and review its dependencies, license, and effects before use. Independent inline steps and the bundled helpers can proceed within the user’s authorized scope.

# 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/
COSMOS_DATABASE=mydb
COSMOS_CONTAINER=mycontainer
```

## Authentication

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

credential = DefaultAzureCredential()
endpoint = "https://<account>.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

Confirm account/database/container, partition-key definition and authorized budget before provisioning or changing throughput. `create_*_if_not_exists` does not reconcile an existing container configuration. Examples use different key paths; do not combine them against one container. Tenant partitioning is not authorization isolation. Use ETag conditions for read-modify-write operations and explicit logical-operation deduplication for retries. Change feed is not a globally ordered, exactly-once ledger; checkpoint only after successful idempotent processing and verify the pinned SDK checkpoint API.

### Setup Database and Container

```python
from azure.cosmos import PartitionKey

# 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.get_throughput()
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, 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. **Always specify partition key** for point reads and queries
2. **Use parameterized queries** to prevent injection and improve caching
3. **Avoid cross-partition queries** when possible
4. **Use stable IDs carefully**; upsert replaces existing contents and is not a concurrency or logical-operation deduplication guarantee
5. **Use async client** for high-throughput scenarios
6. **Design partition key** for even data distribution
7. **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 |

## 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.