Integrate the ncScale API with the Python API

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

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Popular ncScale and Python Actions#

Push Log with the ncScale API

Pushes a new log entry to the ncscale app. 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 ncScale#

The ncScale API offers scalable solutions for handling complex data transformations, computations, and integrations. By leveraging this API on Pipedream, you can automate and streamline processes like real-time data analysis, dynamic resource allocation, and system monitoring. Pipedream's serverless platform allows you to trigger workflows with HTTP requests, emails, and over 800+ integrations, making it highly versatile for incorporating ncScale's capabilities into a variety of systems.

Connect ncScale#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    ncscale: {
      type: "app",
      app: "ncscale",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.ncscale.$auth.subdomain}.ncscale.io/v1/tools`,
      headers: {
        Authorization: `Bearer ${this.ncscale.$auth.api_token}`,
        "Accept": `application/json`,
      },
    })
  },
})

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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