python-digitalocean is a community-maintained Python library for interacting with the DigitalOcean API, allowing management of resources like Droplets, Images, and more. It is currently at version 1.17.0 and receives releases for new API features and bug fixes. While widely used, DigitalOcean also provides an official client, `pydo`.
pip install python-digitaloceanVerified import paths — ran on the pinned version, not inferred.
Initializes the DigitalOcean Manager with an API token from an environment variable and lists all active Droplets in your account. Requires a DigitalOcean API token with read access configured as DIGITALOCEAN_ACCESS_TOKEN.
Review the GitHub repositories (koalalorenzo/python-digitalocean vs. digitalocean/pydo) and documentation to choose the appropriate client. If switching to `pydo`, consult its separate documentation and import paths.
Always use environment variables (e.g., `DIGITALOCEAN_ACCESS_TOKEN`) or a secure configuration management system to store and retrieve API tokens. Ensure your tokens have the minimum necessary scopes/permissions.
Implement proper error handling for rate limit responses, introduce delays between API calls, or utilize caching mechanisms where appropriate.
Always test new versions thoroughly in development environments before deploying to production. Check the project's GitHub issues for reported bugs related to your version and environment.
Ensure the `DIGITALOCEAN_ACCESS_TOKEN` environment variable is correctly set with a valid, active API token. Verify the token's scopes in your DigitalOcean account settings. Generate a new token if necessary.
Use `from digitalocean import Manager` or ensure `import digitalocean` is used, and then access it as `digitalocean.Manager(...)`. Check for typos in the class name.
Consult the DigitalOcean API documentation or the library's methods (e.g., `manager.get_all_images()`, `manager.get_all_regions()`, `manager.get_all_sizes()`) to retrieve valid and compatible parameters before attempting resource creation.
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