Question

I m trying to set up a SQL server with Google, that I m able to connect to with Microsoft SQL server, but when I try to connect with python, I m not able to import google.cloud.sql.connector to my code. I installed the Google libraries with PIP and can import google.cloud.sql, but when I try to add or import the connector it gives me "The requests library is not installed from please install the requests package to use the requests transport." Any advice?

我曾尝试安装谷歌图书馆,配备几个PIP指挥部,所有这些指挥部都安装了没有问题的设备,但I m仍然无法在我的代码中进口连接器。 I ve安装了图书馆,安装了云-sql-python-linkor,还单独安装了方言。 [pymysql], [pg8000], [asyncpg], and [pytds]

Answer 1

您是否尝试了<代码>pip安装申请? Seems such as that's里, 你的失踪

Answer 2

就像你在试图利用谷歌云库连接器时,用沙尔环境再次面对依赖问题一样。为您的项目创造一个专门的虚拟环境,有助于更有效地管理依赖性,并使你的项目与全球沙尔一揽子计划设施分离。在这里,你可以如何建立灰色虚拟环境,安装必要的图书馆,并开始使用谷歌云云层连接器:

Step 1: Install Python and PIP

确保在你的系统中安装“灰色”和“皮带”。你可以从官方网站下载“灰色”节目,通常包括PIP。

Step 2: Create a Virtual Environment

1. 开放您的终端或指挥,并迅速与您的项目目录挂钩。随后,执行以下指令,以建立一个名为<代码>venv的虚拟环境:

# On Windows
python -m venv venv

# On macOS or Linux
python3 -m venv venv

Step 3: Activate the Virtual Environment

在安装任何包裹之前,你需要启动虚拟环境:

# On Windows
.venvScriptsactivate

# On macOS or Linux
source venv/bin/activate

Step 4: Install Google Cloud SQL Connector and Requests

• 安装谷歌云库连接器和请求图书馆,使用PIP:

pip install google-cloud-sql-connector requests

Step 5: Write Python Code to Use the Connector

Now you can write your Python code to connect to your SQL Server instance on Google Cloud using the connector. Here’s a basic example of how to do this:

import google.cloud.sql.connector
import sqlalchemy

# Function to create SQL connection
def getconn() -> sqlalchemy.engine.base.Connection:
    conn = google.cloud.sql.connector.connect(
        "project-id:region:instance-id",  # Use your Cloud SQL instance connection name
        "pymysql",
        user="your-user",  # Replace with your database user
        password="your-password",  # Replace with your database password
        db="your-database-name"  # Replace with your database name
    )
    return conn

# Create a SQLAlchemy engine
engine = sqlalchemy.create_engine(
    "mysql+pymysql://",
    creator=getconn,
)

# Use the engine to execute SQL queries
with engine.connect() as conn:
    result = conn.execute("SELECT * FROM your_table")  # Replace  your_table  with your actual table name
    for row in result:
        print(row)

# Close the engine
engine.dispose()

Step 6: Run Your Python Script

Execute your Python script within the activated virtual environment. This ensures that it uses the correct dependencies.

Additional Tips

Always activate your virtual environment when working on your project.
If you encounter other dependency-related issues, make sure to check that your dependencies are correctly listed and compatible.

这一设置应有助于你更好地管理你们的依赖,并解决你与谷歌云层联谊会所经历的进口问题。