Integrate the LeadIQ API with the Python API

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

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Popular LeadIQ and Python Actions#

Find Contact with the LeadIQ API

Searches for contact information based on user-defined props which may include identifiers such as name, email, or company. Returns the contact data if a match is found within the LeadIQ database. 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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Overview of LeadIQ#

The LeadIQ API enables seamless integration of LeadIQ’s capabilities into various marketing and sales workflows, automating the lead capture and enrichment processes. By harnessing this API on Pipedream, you can automate the extraction of lead data, sync it with CRM systems, and trigger personalized outreach campaigns, all within a serverless environment. This reduces manual tasks, enhances lead quality, and accelerates the sales pipeline.

Connect LeadIQ#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    leadiq: {
      type: "app",
      app: "leadiq",
    }
  },
  async run({steps, $}) {
    const data = {
      "query": `query Usage {
      usage {
        planUsage {
          name
          usageType
          creditType
          units
          cap
          billingType
        }
      }
    }`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.leadiq.com/graphql`,
      auth: {
        username: `${this.leadiq.$auth.api_key}`,
        password: ``,
      },
      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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