Contentful (GraphQL Content)

The GraphQL Content API provides a GraphQL interface to the content from Contentful

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.

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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.

 
Try it

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)

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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

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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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Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo
Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo