Integrate the CloudTables API with the Python API

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

Popular CloudTables and Python Actions#

Add Single Row with the CloudTables API

Add a single row of data into CloudTable data set

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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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Delete Row with the CloudTables API

Delete a row in a CloudTable data set

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Update Row with the CloudTables API

Update a row in a CloudTable data set

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Overview of CloudTables#

CloudTables API allows the creation and manipulation of sophisticated and dynamic data tables in the cloud. With this API, you can manage table schemas, insert, update, and fetch data in real time, and control access with fine-grained permissions. Leveraging CloudTables on Pipedream, you can automate data flows, sync with other services, and respond to events—think of it as supercharging your data tables with the power of integration and automation.

Connect CloudTables#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cloudtables: {
      type: "app",
      app: "cloudtables",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.cloudtables.$auth.subdomain}.cloudtables.io/api/1/datasets`,
      params: {
        key: `${this.cloudtables.$auth.api_key}`,
      },
    })
  },
})

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}}