编辑

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

  • 项目

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)

了解管理 APIExplore the Management APIs