Integrate the Proxycurl API with the Python API

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

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Popular Proxycurl and Python Actions#

Find Social Media Profiles from Email with the Proxycurl API

Find Social Media Profiles from Email. Cost: 3 credit/successful request 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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Look Up Email from LinkedIn Profile with the Proxycurl API

Lookup work email address of a LinkedIn Person Profile. If you provided a webhook in your request parameter, our application will call your webhook with the result once. Cost: 3 credit/successful request See the documentation.

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Retrieve Company Metadata from LinkedIn with the Proxycurl API

Retrieve Company Metadata from LinkedIn URL. Cost: 1 credit/successful request See the documentation.

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Overview of Proxycurl#

The Proxycurl API is a tool for scraping LinkedIn data, enabling users to extract professional information from LinkedIn profiles and company pages. When integrated with Pipedream's serverless platform, Proxycurl can automate the collection of LinkedIn data, which can be used for lead generation, market research, or recruitment. Pipedream's capabilities allow users to create workflows that respond to various triggers, process the data with Proxycurl, and then output it to desired destinations or further manipulate it with other apps and services.

Connect Proxycurl#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    proxycurl: {
      type: "app",
      app: "proxycurl",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://nubela.co/proxycurl/api/credit-balance`,
      headers: {
        Authorization: `Bearer ${this.proxycurl.$auth.api_key}`,
      },
    })
  },
})

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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