Integrate the Cisco Meraki API with the Python API

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

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Popular Cisco Meraki and Python Actions#

Create Organization with the Cisco Meraki API

Creates a new organization. See the docs.

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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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Get Network with the Cisco Meraki API

Gets a network. See the docs.

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Update Network with the Cisco Meraki API

Updates a network. See the docs.

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Overview of Cisco Meraki#

The Cisco Meraki API on Pipedream allows developers to interact with Meraki's cloud-managed network infrastructure. Through the API, you can automate tasks, gather network insights, and control various aspects of your Meraki environment like network settings, clients, devices, and more. This seamless integration can elevate your network management to be more efficient and responsive to real-time data and events.

Connect Cisco Meraki#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cisco_meraki: {
      type: "app",
      app: "cisco_meraki",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.meraki.com/api/v1/organizations`,
      headers: {
        "X-Cisco-Meraki-API-Key": `${this.cisco_meraki.$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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