Integrate the ScrapeNinja API with the Python API

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

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Popular ScrapeNinja and Python Actions#

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 ScrapeNinja#

ScrapeNinja API on Pipedream allows you to craft powerful serverless workflows for web scraping without the hassle of managing proxies or browsers. It's a tool that can extract data from websites, handling JavaScript rendering and anti-bot measures with ease. By integrating ScrapeNinja with Pipedream, you can automate data collection, collate and process the scraped data, and connect it to numerous other services for further analysis, alerting, or storage.

Connect ScrapeNinja#

import { axios } from '@pipedream/platform';

export default defineComponent({
  props: {
    scrapeninja: {
      type: "app",
      app: "scrapeninja",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: 'POST',
      url: 'https://scrapeninja.p.rapidapi.com/scrape',
      headers: {
        'content-type': 'application/json',
        'X-RapidAPI-Key': this.scrapeninja.$auth.rapid_api_key,
        'X-RapidAPI-Host': 'scrapeninja.p.rapidapi.com'
      },
      data: {
        url:"https://news.ycombinator.com/"
      }
    })
  },
})

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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