Integrate the Melo API with the Python API

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

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Popular Ways to Connect Melo with Python#

Run Python Code with Python API on New Property Created (Instant) from Melo API

Melo + Python

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Popular Melo and Python Triggers#

New Property Created (Instant) from the Melo API

Emit new event when a new property ad is created in Melo. Requires a Production Environment.

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Popular Melo and Python Actions#

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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Search Properties with the Melo API

Searches properties in Melo. See the documentation

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Overview of Melo#

Melo API enables you to manage and automate tasks related to project management and team collaboration. Utilize Melo's endpoints to create tasks, update project details, manage team assignments, and retrieve project metrics. Integrating Melo API with Pipedream allows you to connect your project management workflows with other apps and services, streamlining productivity and providing real-time updates across your tech stack.

Connect Melo#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    melo: {
      type: "app",
      app: "melo",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.melo.$auth.environment}.notif.immo/documents/properties`,
      headers: {
        "Content-Type": `application/json`,
        "X-API-KEY": `${this.melo.$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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