Zenserp

Zenserp enables you to scrape search engine result pages in a fast and scalable way. Getting SERPs has never been easier.

Integrate the Zenserp API with the Python API

Setup the Zenserp API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Zenserp 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 Zenserp

The Zenserp API enables you to automate search engine queries, parsing SERPs (Search Engine Results Pages) to extract valuable data such as search results, location-based results, and even Google image searches. Within Pipedream's platform, you can harness this API to create workflows that react to various triggers, like webhooks or schedules, to perform automated searches and process the resulting data. This can be powerful for SEO analysis, market research, and content monitoring. Pipedream's serverless architecture makes it seamless to integrate Zenserp with other apps to augment your workflows.

Connect Zenserp

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    zenserp: {
      type: "app",
      app: "zenserp",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.zenserp.com/api/v2/search`,
      headers: {
        "apikey": `${this.zenserp.$auth.api_key}`,
      },
      params: {
        "q": `Pipedream`,
      },
    })
  },
})

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}}

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

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
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