Integrate the DigitalOcean Spaces API with the Python API

Setup the DigitalOcean Spaces API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate DigitalOcean Spaces and Python remarkably fast. Free for developers.

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Popular Ways to Connect DigitalOcean Spaces with Python#

Run Python Code with Python API on File Deleted from DigitalOcean Spaces API

DigitalOcean Spaces + Python

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Run Python Code with Python API on New File Uploaded from DigitalOcean Spaces API

DigitalOcean Spaces + Python

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Popular DigitalOcean Spaces and Python Triggers#

File Deleted from the DigitalOcean Spaces API

Emit new event when a file is deleted from a DigitalOcean Spaces bucket

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New File Uploaded from the DigitalOcean Spaces API

Emit new event when a file is uploaded to a DigitalOcean Spaces bucket

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Popular DigitalOcean Spaces and Python Actions#

Delete Files with the DigitalOcean Spaces API

Delete files in a bucket. See the docs.

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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List Files with the DigitalOcean Spaces API

List files in a bucket. See the docs.

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Upload File /tmp with the DigitalOcean Spaces API

Accepts a file path starting from /tmp, then uploads as a file to DigitalOcean Spaces. See the docs.

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Upload File Base64 with the DigitalOcean Spaces API

Accepts a base64-encoded string and a filename, then uploads as a file to DigitalOcean Spaces. See the docs.

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Overview of DigitalOcean Spaces#

DigitalOcean Spaces API permits you to manage object storage, allowing for the storage and serving of massive amounts of data. This API is great for backing up, archiving, and providing public access to data or assets. On Pipedream, you can use this API to automate file operations like uploads, downloads, and deletions, as well as manage permissions and metadata. You can integrate it with other services for end-to-end workflow automation.

Connect DigitalOcean Spaces#

import { S3 } from "@aws-sdk/client-s3";
import { ListBucketsCommand  } from "@aws-sdk/client-s3";

export default defineComponent({
  props: {
    digitalocean_spaces: {
      type: "app",
      app: "digitalocean_spaces"
    }
  },
  async run({ steps, $ }) {
    console.log(this.digitalocean_spaces.$auth)
    const s3Client = new S3({
        forcePathStyle: false, // Configures to use subdomain/virtual calling format.
        endpoint: `https://${this.digitalocean_spaces.$auth.region}.digitaloceanspaces.com`,
        region: "us-east-1",
        credentials: {
          accessKeyId: this.digitalocean_spaces.$auth.key,
          secretAccessKey: this.digitalocean_spaces.$auth.secret
        }
    });

    const data = await s3Client.send(new ListBucketsCommand({}));
    return data.Buckets;
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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