Integrate the Gigasheet API with the Python API

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

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Popular Gigasheet and Python Actions#

Create Export with the Gigasheet API

Creates an export for a gigasheet dataset. See the documentation

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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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Download Export with the Gigasheet API

Downloads an export from Gigasheet. See the documentation

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Upload Data From URL with the Gigasheet API

Uploads data from a URL to Gigasheet. See the documentation

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Overview of Gigasheet#

The Gigasheet API enables users to manipulate large-scale data sheets within the cloud effortlessly. Through Pipedream, you can leverage this functionality to automate data analysis, manipulation, and enrichment workflows. By connecting Gigasheet with other apps, you can streamline processes like data import, transformation, and sharing, making Pipedream an ideal platform to enhance productivity and data handling efficiency.

Connect Gigasheet#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    gigasheet: {
      type: "app",
      app: "gigasheet",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.gigasheet.com/user/whoami`,
      headers: {
        "X-GIGASHEET-TOKEN": `${this.gigasheet.$auth.api_key}`,
        "accept": `application/json`,
      },
    })
  },
})

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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