Integrate the LinkedIn API with the Python API

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

Popular LinkedIn and Python Actions#

Create a Simple Post (Organization) with the LinkedIn API

Create post on LinkedIn using text, URL or article. See the docs for more information

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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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Create a Simple Post (User) with the LinkedIn API

Create post on LinkedIn using text, URL or article. See the docs for more information

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Create Comment with the LinkedIn API

Create a comment on a share or user generated content post. See the docs here

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Create Image Post (Organization) with the LinkedIn API

Create an image post on LinkedIn. See the docs here

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Overview of LinkedIn#

The LinkedIn API on Pipedream allows you to automate interactions with your LinkedIn account, such as posting updates, managing your profile, and engaging with your network. With Pipedream's serverless platform, you can create workflows that trigger on various events, process data, and connect with countless other apps to extend your LinkedIn presence, analyze your network's demographics, automate content sharing, and more.

Connect LinkedIn#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    linkedin: {
      type: "app",
      app: "linkedin",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.linkedin.com/v2/me`,
      headers: {
        Authorization: `Bearer ${this.linkedin.$auth.oauth_access_token}`,
      },
    })
  },
})

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}}