Integrate the Grafbase API with the Python API

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

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Popular Grafbase and Python Actions#

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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Overview of Grafbase#

The Grafbase API allows you to interact with your Grafbase backend, enabling CRUD operations on your data models, managing authentication, and triggering custom business logic. Grafbase provides real-time updates and serverless deployment which makes it a perfect partner for Pipedream's serverless platform. You can build workflows to automate tasks, integrate with various services, and respond to events without managing infrastructure.

Connect Grafbase#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    grafbase: {
      type: "app",
      app: "grafbase",
    }
  },
  async run({steps, $}) {
    const data = {
      "query": `{
          __schema {
            types {
              name
            }
          }
        }`,
    }
    return await axios($, {
      method: "post",
      url: `${this.grafbase.$auth.url}`,
      headers: {
        "Content-Type": `application/json`,
        "x-api-key": `${this.grafbase.$auth.api_key}`,
      },
      data,
    })
  },
})

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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