Neutrino

The Neutrino API platform provides a highly available, performant global network that lets developers focus on their product and not on building and maintaining complex in-house tools not relevant to their core business.

Integrate the Neutrino API with the Python API

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

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 Neutrino

The Neutrino API provides a set of tools for performing various utility functions over the web. Leveraging this API within Pipedream workflows enables you to automate tasks like email validation, bad word filtering, IP blocklisting, and data conversion. It's a Swiss Army knife for developers needing to ensure data integrity, security, and streamlined data processing within their applications.

Connect Neutrino

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    neutrino: {
      type: "app",
      app: "neutrino",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://neutrinoapi.net/email-validate`,
      params: {
        email: `YOUR_EMAIL_ADDRESS`,
        "api-key": `${this.neutrino.$auth.api_key}`,
        "user-id": `${this.neutrino.$auth.user_id}`,
      },
    })
  },
})

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}}