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There are several ways to manage Python dependencies with AWS Lambda:

1. Using a virtual environment: You can create a virtual environment to manage your dependencies and upload it as a ZIP file along with your Lambda function code.

2. Using Lambda layers: You can use Lambda layers to include your dependencies and share them across multiple Lambda functions. You can create a layer by including your dependencies in a ZIP file and uploading it to AWS Lambda.

3. Using a package manager: You can use a package manager like pip to install your dependencies and then package your Lambda function along with the dependencies.

4. Using AWS Serverless Application Model (SAM): You can use SAM to define your Lambda function along with its dependencies in a YAML or JSON file. SAM will automatically package your function and its dependencies and deploy it to AWS Lambda.

Regardless of the method you choose, it is important to ensure that your dependencies are up to date and that you have a reliable way to manage them as your code evolves.