用于 Python 的 Azure 数据工厂库Azure Data Factory libraries for Python

使用 Azure 数据工厂将数据存储、移动和处理服务组成自动的数据管道Compose data storage, movement, and processing services into automated data pipelines with Azure Data Factory

详细了解数据工厂，并通过使用 Python 创建数据工厂和管道快速入门来入门。Learn more about Data Factory and get started with the Create a data factory and pipeline using Python quickstart.

管理模块Management module

使用管理模块在订阅中创建和管理数据工厂实例。Create and manage Data Factory instances in your subscription with the management module.

安装Installation

使用 pip 来安装包：Install the package with pip:

pip install azure-mgmt-datafactory 

示例Example

在“美国东部”区域的订阅中创建数据工厂。Create a Data Factory in your subscription on the East US region.

from azure.common.credentials import ServicePrincipalCredentials
from azure.mgmt.resource import ResourceManagementClient
from azure.mgmt.datafactory import DataFactoryManagementClient
from azure.mgmt.datafactory.models import *
import time

#Create a data factory
subscription_id = '<Specify your Azure Subscription ID>'
credentials = ServicePrincipalCredentials(client_id='<Active Directory application/client ID>', secret='<client secret>', tenant='<Active Directory tenant ID>')
adf_client = DataFactoryManagementClient(credentials, subscription_id)

rg_params = {'location':'eastus'}
df_params = {'location':'eastus'}  

df_resource = Factory(location='eastus')
df = adf_client.factories.create_or_update(rg_name, df_name, df_resource)
print_item(df)
while df.provisioning_state != 'Succeeded':
    df = adf_client.factories.get(rg_name, df_name)
    time.sleep(1)