Snowflake Python APIs 教程的常用设置¶

简介

This topic provides instructions for the common setup required for all Snowflake Python APIs tutorials available in this documentation.

Overview of the Snowflake Python APIs¶

Before starting your setup, take a look at the Snowflake Python APIs structure. The following table lists some common modules in the API:

For a complete list of the APIs currently available, see the API reference documentation.

The snowflake.core module represents the entry point to the core Snowflake Python APIs that manage Snowflake objects. To use the API, you follow a common pattern:

1. 使用 Snowpark 或 Python Connector 连接建立会话，表示您与 Snowflake 的连接。

2. Import and instantiate the Root class from snowflake.core, and pass the Snowpark session object as an argument.

   You use the resulting Root object to access the rest of the methods and types in the API.

For more information about the programming model of the API, see Snowflake Python APIs: General concepts.

下面的代码提供了此模式的典型示例：

from snowflake.snowpark import Session
from snowflake.core import Root

session = Session.builder.config("connection_name", "default").create()
root = Root(session)

For more information about various connection options and attributes, see Connect to Snowflake with the Snowflake Python APIs.

继续执行下一步，开始设置 API 及您的开发环境！

Install the Snowflake Python APIs¶

在安装 API 之前，您需要激活 Python 环境。

在本教程中，您可以使用 conda 或虚拟环境 (venv)。

1. To create and activate a conda or virtual environment, open a command-line terminal and run the following commands:

   condavenv

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   conda create -n <env_name> python==3.10
   conda activate <env_name>

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2. The Snowflake Python APIs package is available in PyPI.

若要在新的 conda 或虚拟环境中安装 API 包，运行以下命令：

pip install snowflake -U

3. To install the snowflake-snowpark-python package, run the following command:

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   pip install 'snowflake-snowpark-python>=1.5.0,<2.0.0'

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   In these tutorials, you use the snowflake.snowpark.Session object from the Snowpark API for Python to create a connection to Snowflake.

设置开发环境

This tutorial walks through code examples that you can run in a Jupyter notebook. Each step in the tutorial incrementally showcases the capabilities of the Snowflake Python APIs.

首先设置您的开发环境，以便在笔记本中运行代码示例。

1. Create a file named $HOME/.snowflake/connections.toml with the following connection parameters, and update it with your real credentials:

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   [default]
   account = "<YOUR ACCOUNT NAME>"
   user = "<YOUR ACCOUNT USER>"
   password = "<YOUR ACCOUNT USER PASSWORD>"
   # optional
   # warehouse = "<YOUR COMPUTE WH>"
   # optional
   # database = "<YOUR DATABASE>"
   # optional
   # schema = "<YOUR SCHEMA>"

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   Note

   The account parameter does not support account identifiers with underscores. You must specify an account identifier with dashes in place of any underscores. For more information, see Account name in your organization.

   This example specifies these parameters as the default connection to Snowflake in your environment by creating a connection definition named default.

2. 使用如下方法之一打开笔记本：

   • 在支持 Jupyter 笔记本的代码编辑器（例如 Visual Studio Code）中打开一个新笔记本。

   • To open a notebook in your browser, start a notebook server with the command jupyter notebook.

     To ensure that your environment can run a notebook, run conda install notebook in your terminal before starting the notebook server.

3. 在笔记本的第一个单元格中，运行以下导入语句：

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   from datetime import timedelta
   
   from snowflake.snowpark import Session
   from snowflake.snowpark.functions import col
   from snowflake.core import Root, CreateMode
   from snowflake.core.database import Database
   from snowflake.core.schema import Schema
   from snowflake.core.stage import Stage
   from snowflake.core.table import Table, TableColumn, PrimaryKey
   from snowflake.core.task import StoredProcedureCall, Task
   from snowflake.core.task.dagv1 import DAGOperation, DAG, DAGTask
   from snowflake.core.warehouse import Warehouse

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   Note

   After running this cell, you might be prompted to set your Python kernel. If you activated a conda environment, select conda as the Python kernel (for example, something similar to: ~/miniconda3/envs/<your conda env>/bin/python).

在此单元格中，导入 Snowpark 和管理 Snowflake 对象的核心 APIs。

4. 要与 Snowflake 建立连接，请在下一个单元格中，运行以下代码：

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   session = Session.builder.config("connection_name", "default").create()

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   In this cell, you create a Snowpark session and set the connection parameters for your session by specifying the connection_name as the default connection definition that you previously configured.

5. To create a Root object, pass your session object to the Root constructor:

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   root = Root(session)

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And that’s it! By running the code in these three cells, you’re now ready to use the Snowflake Python APIs.

下一步是什么？

You can now explore Tutorial 1: Create a database, schema, table, and warehouse.