Integrate the Automatic Data Extraction API with the Python API

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

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Popular Automatic Data Extraction and Python Actions#

Extract Data From URL with the Automatic Data Extraction API

Extract data from a specified URL See the docs here

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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 Automatic Data Extraction#

The Automatic Data Extraction API by Zyte specializes in extracting structured data from web pages. When incorporated into Pipedream workflows, this API allows you to automate the process of gathering web data, which can feed into various tasks such as market research, price monitoring, or even lead generation. By triggering workflows with new data inputs, processing and storing the extracted data, and connecting to other apps, Pipedream amplifies the API's utility.

Connect Automatic Data Extraction#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    automatic_data_extraction: {
      type: "app",
      app: "automatic_data_extraction",
    }
  },
  async run({steps, $}) {
    const data = JSON.stringify([{
      'url': 'http://books.toscrape.com/catalogue/a-light-in-the-attic_1000/index.html',
      'pageType': 'product',
    }]);
    return await axios($, {
      method: "post",
      url: `https://autoextract.scrapinghub.com/v1/extract`,
      headers: {
        "Content-Type": `application/json`,
      },
      auth: {
        username: `${this.automatic_data_extraction.$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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