Integrate the Wappalyzer API with the Python API

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

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Popular Wappalyzer and Python Actions#

Get Technologies with the Wappalyzer API

Returns the details of technologies used on a specific URL. 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 Wappalyzer#

The Wappalyzer API lets you uncover the technology stack of any website. On Pipedream, you can integrate this capability into workflows to automate tech stack detection. Here's what you can do: identify the software used by your competitors, track technology adoption, and get insights into your target market's tech preferences. By leveraging Pipedream's robust platform, you can connect Wappalyzer with other services to create custom workflows that trigger actions based on the tech stack data you collect.

Connect Wappalyzer#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    wappalyzer: {
      type: "app",
      app: "wappalyzer",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.wappalyzer.com/v2/credits/balance/`,
      headers: {
        "x-api-key": `${this.wappalyzer.$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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