Integrate the Contentful (GraphQL Content) API with the Python API

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

Overview of Contentful (GraphQL Content)#

The Contentful GraphQL Content API opens up a world of possibilities for creating, managing, and delivering content across multiple platforms. With this API, you can query your Contentful content model using GraphQL, allowing for more efficient data retrieval with fewer requests. Integrate this with Pipedream's serverless capabilities, and you've got a powerful tool to automate content workflows, sync content across applications, trigger notifications based on content changes, and more.

Connect Contentful (GraphQL Content)#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    contentful_graphql: {
      type: "app",
      app: "contentful_graphql",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://graphql.contentful.com/content/v1/spaces/[SPACE]/environments/[ENVIRONMENT]`,
      headers: {
        Authorization: `Bearer ${this.contentful_graphql.$auth.access_token}`,
      },
      params: {
        query: `query($preview: Boolean){
      assetCollection(preview: $preview){
        items{
          title
        }
      }
    }`,
      },
    })
  },
})

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}}