HUB Planner

A Modern and Smart Resource Management, Planning & Scheduling tool with Time Sheets and Powerful Reporting. Ideal for Managing Global Teams of Resources.

Integrate the HUB Planner API with the Python API

Setup the HUB Planner API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate HUB Planner 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 HUB Planner

The HUB Planner API is a toolset for managing resources, projects, and bookings in a visual and interactive way. By using the API with Pipedream, you can automate complex workflows, sync data across multiple platforms, and create custom integrations to streamline operations. From scheduling resources to analyzing project data, the opportunities are vast for enhancing project management efficiency.

Connect HUB Planner

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    hub_planner: {
      type: "app",
      app: "hub_planner",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.hubplanner.com/v1/project`,
      headers: {
        "Authorization": `${this.hub_planner.$auth.api_key}`,
        "Accept": `application/json`,
        "Content-Type": `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

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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}}