azure-data-tables-py
用 Python 操作 Azure Table Storage 的 entity CRUD 和批次
中文翻譯
---
name: azure-data-tables-py
description: |
Python 版 Azure Tables SDK(Storage 和 Cosmos DB)。用於 NoSQL key-value 儲存、entity CRUD 和批次操作。
Triggers: "table storage", "TableServiceClient", "TableClient", "entities", "PartitionKey", "RowKey".
license: MIT
metadata:
author: Microsoft
version: "1.0.0"
package: azure-data-tables
---
# Python 版 Azure Tables SDK
用來存結構化資料的 NoSQL key-value store(Azure Storage Tables 或 Cosmos DB Table API)。
## 安裝
```bash
pip install azure-data-tables azure-identity
```
## 環境變數
```bash
# Azure Storage Tables
AZURE_STORAGE_ACCOUNT_URL=https://<account>.table.core.windows.net # Azure Storage Tables 必須設定
# Cosmos DB Table API
COSMOS_TABLE_ENDPOINT=https://<account>.table.cosmos.azure.com # Cosmos DB Table API 必須設定
AZURE_TOKEN_CREDENTIALS=prod # 只有在正式環境使用 DefaultAzureCredential 時才需要
```
## 驗證與生命週期
> **🔑 下面每個範例都適用兩條規則:**
>
> 1. **優先用 `DefaultAzureCredential`。** 它在本機(Azure CLI / VS Code / Developer CLI)和 Azure 上(managed identity、workload identity)都能跑,程式碼不用改。避免用 connection string、帳號金鑰或 API key,因為它們會繞過 Entra 的稽核和輪替。
> - 本機開發:`DefaultAzureCredential` 直接可用。
> - 正式環境:設定 `AZURE_TOKEN_CREDENTIALS=prod`(或 `AZURE_TOKEN_CREDENTIALS=<specific_credential>`),把 credential chain 限制在正式環境安全的 credential。
> 2. **每個 client 都用 context manager 包起來**,這樣 HTTP transport、socket 和 token 快取才會確定被釋放:
> - 同步:`with <Client>(...) as client:`
> - 非同步:`async with <Client>(...) as client:` **而且** `async with DefaultAzureCredential() as credential:`(來自 `azure.identity.aio`)
>
> 範例片段可能會簡化這段設定,但正式環境的程式碼一定要遵守這兩條規則。
```python
import os
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.data.tables import TableServiceClient, TableClient
# 本機開發:DefaultAzureCredential。正式環境:設定 AZURE_TOKEN_CREDENTIALS=prod 或 AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# 或是在正式環境直接用特定的 credential:
# 參考 https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
endpoint = "https://<account>.table.core.windows.net"
# Service client(管理 table)
with TableServiceClient(endpoint=endpoint, credential=credential) as service_client:
# 在這裡使用 service_client(操作請看後面的段落)
...
# Table client(處理 entity)
with TableClient(endpoint=endpoint, table_name="mytable", credential=credential) as table_client:
# 在這裡使用 table_client(操作請看後面的段落)
...
```
## Client 類型
| Client | 用途 |
|--------|---------|
| `TableServiceClient` | 建立/刪除 table、列出 table |
| `TableClient` | Entity CRUD、查詢 |
## Table 操作
```python
# 建立 table
service_client.create_table("mytable")
# 不存在才建立
service_client.create_table_if_not_exists("mytable")
# 刪除 table
service_client.delete_table("mytable")
# 列出 table
for table in service_client.list_tables():
print(table.name)
# 取得 table client
table_client = service_client.get_table_client("mytable")
```
## Entity 操作
**重要**:每個 entity 都需要 `PartitionKey` 和 `RowKey`(兩者合起來是唯一 ID)。
### 建立 Entity
```python
entity = {
"PartitionKey": "sales",
"RowKey": "order-001",
"product": "Widget",
"quantity": 5,
"price": 9.99,
"shipped": False
}
# Create(已存在會失敗)
table_client.create_entity(entity=entity)
# Upsert(建立或取代)
table_client.upsert_entity(entity=entity)
```
### 取得 Entity
```python
# 用 key 取得(最快)
entity = table_client.get_entity(
partition_key="sales",
row_key="order-001"
)
print(f"Product: {entity['product']}")
```
### 更新 Entity
```python
# 整個 entity 取代
entity["quantity"] = 10
table_client.update_entity(entity=entity, mode="replace")
# Merge(只更新特定欄位)
update = {
"PartitionKey": "sales",
"RowKey": "order-001",
"shipped": True
}
table_client.update_entity(entity=update, mode="merge")
```
### 刪除 Entity
```python
table_client.delete_entity(
partition_key="sales",
row_key="order-001"
)
```
## 查詢 Entity
### 在 Partition 內查詢
```python
# 依 partition 查詢(有效率)
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'"
)
for entity in entities:
print(entity)
```
### 帶篩選條件的查詢
```python
# 依屬性篩選
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales' and quantity gt 3"
)
# 帶參數(比較安全)
entities = table_client.query_entities(
query_filter="PartitionKey eq @pk and price lt @max_price",
parameters={"pk": "sales", "max_price": 50.0}
)
```
### 選取特定屬性
```python
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'",
select=["RowKey", "product", "price"]
)
```
### 列出所有 Entity
```python
# 列出全部(跨 partition,少用)
for entity in table_client.list_entities():
print(entity)
```
## 批次操作
```python
from azure.data.tables import TableTransactionError
# 批次操作(只限同一個 partition!)
operations = [
("create", {"PartitionKey": "batch", "RowKey": "1", "data": "first"}),
("create", {"PartitionKey": "batch", "RowKey": "2", "data": "second"}),
("upsert", {"PartitionKey": "batch", "RowKey": "3", "data": "third"}),
]
try:
table_client.submit_transaction(operations)
except TableTransactionError as e:
print(f"Transaction failed: {e}")
```
## 非同步 Client
```python
from azure.data.tables.aio import TableServiceClient, TableClient
from azure.identity.aio import DefaultAzureCredential
async def table_operations():
async with DefaultAzureCredential() as credential:
async with TableClient(
endpoint="https://<account>.table.core.windows.net",
table_name="mytable",
credential=credential
) as client:
# 建立
await client.create_entity(entity={
"PartitionKey": "async",
"RowKey": "1",
"data": "test"
})
# 查詢
async for entity in client.query_entities("PartitionKey eq 'async'"):
print(entity)
import asyncio
asyncio.run(table_operations())
```
## 資料型別
| Python 型別 | Table Storage 型別 |
|-------------|-------------------|
| `str` | String |
| `int` | Int64 |
| `float` | Double |
| `bool` | Boolean |
| `datetime` | DateTime |
| `bytes` | Binary |
| `UUID` | Guid |
## 最佳實務
1. **同步或非同步選一種,並保持一致。** 同一條呼叫路徑裡不要混用 `azure.data.tables` 的同步 client 和 `azure.data.tables.aio` 的非同步 client。每個 module 選一種模式。
2. **client 和非同步 credential 一律用 context manager。** 每個 client 都用 `with TableClient(...) as client:`(同步)或 `async with TableClient(...) as client:`(非同步)包起來。非同步的 `DefaultAzureCredential`(來自 `azure.identity.aio`)也要用 `async with credential:`,這樣 token 和 transport 才會被清掉。
3. **用 `DefaultAzureCredential`**,在本機開發和 Azure 之間驗證方式可以通用(盡量避免 connection string/API key)。
4. **依查詢模式設計 partition key**,並讓資料分布平均
5. **盡量在 partition 內查詢**(跨 partition 很貴)
6. **同一個 partition 的多個 entity 用批次操作**
7. **用 `upsert_entity`** 讓寫入具冪等性
8. **用參數化查詢**防止 injection
9. **entity 保持小**,每個 entity 最大 1MB
10. **高吞吐量情境用非同步 client**
## 參考檔案
| 檔案 | 內容 |
|------|----------|
| [references/capabilities.md](references/capabilities.md) | 其他非主打的功能、各 operation group 的涵蓋範圍,以及正式環境檢查清單。 |
| [references/non-hero-scenarios.md](references/non-hero-scenarios.md) | 次要/進階情境的專屬非主打範例。 |英文原文
---
name: azure-data-tables-py
description: |
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
Triggers: "table storage", "TableServiceClient", "TableClient", "entities", "PartitionKey", "RowKey".
license: MIT
metadata:
author: Microsoft
version: "1.0.0"
package: azure-data-tables
---
# Azure Tables SDK for Python
NoSQL key-value store for structured data (Azure Storage Tables or Cosmos DB Table API).
## Installation
```bash
pip install azure-data-tables azure-identity
```
## Environment Variables
```bash
# Azure Storage Tables
AZURE_STORAGE_ACCOUNT_URL=https://<account>.table.core.windows.net # Required for Azure Storage Tables
# Cosmos DB Table API
COSMOS_TABLE_ENDPOINT=https://<account>.table.cosmos.azure.com # Required for Cosmos DB Table API
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.data.tables import TableServiceClient, TableClient
# 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>.table.core.windows.net"
# Service client (manage tables)
with TableServiceClient(endpoint=endpoint, credential=credential) as service_client:
# Use service_client here (see following sections for operations)
...
# Table client (work with entities)
with TableClient(endpoint=endpoint, table_name="mytable", credential=credential) as table_client:
# Use table_client here (see following sections for operations)
...
```
## Client Types
| Client | Purpose |
|--------|---------|
| `TableServiceClient` | Create/delete tables, list tables |
| `TableClient` | Entity CRUD, queries |
## Table Operations
```python
# Create table
service_client.create_table("mytable")
# Create if not exists
service_client.create_table_if_not_exists("mytable")
# Delete table
service_client.delete_table("mytable")
# List tables
for table in service_client.list_tables():
print(table.name)
# Get table client
table_client = service_client.get_table_client("mytable")
```
## Entity Operations
**Important**: Every entity requires `PartitionKey` and `RowKey` (together form unique ID).
### Create Entity
```python
entity = {
"PartitionKey": "sales",
"RowKey": "order-001",
"product": "Widget",
"quantity": 5,
"price": 9.99,
"shipped": False
}
# Create (fails if exists)
table_client.create_entity(entity=entity)
# Upsert (create or replace)
table_client.upsert_entity(entity=entity)
```
### Get Entity
```python
# Get by key (fastest)
entity = table_client.get_entity(
partition_key="sales",
row_key="order-001"
)
print(f"Product: {entity['product']}")
```
### Update Entity
```python
# Replace entire entity
entity["quantity"] = 10
table_client.update_entity(entity=entity, mode="replace")
# Merge (update specific fields only)
update = {
"PartitionKey": "sales",
"RowKey": "order-001",
"shipped": True
}
table_client.update_entity(entity=update, mode="merge")
```
### Delete Entity
```python
table_client.delete_entity(
partition_key="sales",
row_key="order-001"
)
```
## Query Entities
### Query Within Partition
```python
# Query by partition (efficient)
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'"
)
for entity in entities:
print(entity)
```
### Query with Filters
```python
# Filter by properties
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales' and quantity gt 3"
)
# With parameters (safer)
entities = table_client.query_entities(
query_filter="PartitionKey eq @pk and price lt @max_price",
parameters={"pk": "sales", "max_price": 50.0}
)
```
### Select Specific Properties
```python
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'",
select=["RowKey", "product", "price"]
)
```
### List All Entities
```python
# List all (cross-partition - use sparingly)
for entity in table_client.list_entities():
print(entity)
```
## Batch Operations
```python
from azure.data.tables import TableTransactionError
# Batch operations (same partition only!)
operations = [
("create", {"PartitionKey": "batch", "RowKey": "1", "data": "first"}),
("create", {"PartitionKey": "batch", "RowKey": "2", "data": "second"}),
("upsert", {"PartitionKey": "batch", "RowKey": "3", "data": "third"}),
]
try:
table_client.submit_transaction(operations)
except TableTransactionError as e:
print(f"Transaction failed: {e}")
```
## Async Client
```python
from azure.data.tables.aio import TableServiceClient, TableClient
from azure.identity.aio import DefaultAzureCredential
async def table_operations():
async with DefaultAzureCredential() as credential:
async with TableClient(
endpoint="https://<account>.table.core.windows.net",
table_name="mytable",
credential=credential
) as client:
# Create
await client.create_entity(entity={
"PartitionKey": "async",
"RowKey": "1",
"data": "test"
})
# Query
async for entity in client.query_entities("PartitionKey eq 'async'"):
print(entity)
import asyncio
asyncio.run(table_operations())
```
## Data Types
| Python Type | Table Storage Type |
|-------------|-------------------|
| `str` | String |
| `int` | Int64 |
| `float` | Double |
| `bool` | Boolean |
| `datetime` | DateTime |
| `bytes` | Binary |
| `UUID` | Guid |
## Best Practices
1. **Pick sync OR async and stay consistent.** Do not mix `azure.data.tables` sync clients with `azure.data.tables.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 TableClient(...) as client:` (sync) or `async with TableClient(...) 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. **Design partition keys** for query patterns and even distribution
5. **Query within partitions** whenever possible (cross-partition is expensive)
6. **Use batch operations** for multiple entities in same partition
7. **Use `upsert_entity`** for idempotent writes
8. **Use parameterized queries** to prevent injection
9. **Keep entities small** — max 1MB per entity
10. **Use async client** for high-throughput scenarios
## Reference Files
| File | Contents |
|------|----------|
| [references/capabilities.md](references/capabilities.md) | Additional non-hero capabilities, operation-group coverage, and production checklists. |
| [references/non-hero-scenarios.md](references/non-hero-scenarios.md) | Dedicated non-hero examples for secondary/advanced scenarios. |