Everhour

Everhour is one of the best time tracking tools for teams. See who’s tracking time, who’s overworked and who can handle more. Keep track of all your project budgets, schedule threshold alerts, use forward resource planning. Build any kind of reports and send professional-looking invoices.

Integrate the Everhour API with the Python API

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

Everhour is a time tracking API that allows you to monitor project hours and manage tasks effectively. With Pipedream, you can automate workflows by integrating Everhour with various apps, streamlining time entry, syncing with project management tools, and generating custom reports. Whether you're consolidating time tracking data for invoicing or keeping project budgets in check, Everhour and Pipedream make a powerful duo for automating your time tracking and project management processes.

Connect Everhour

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    everhour: {
      type: "app",
      app: "everhour",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.everhour.com/users/me`,
      headers: {
        "Content-Type": `application/json`,
        "X-Api-Key": `${this.everhour.$auth.api_token}`,
      },
    })
  },
})

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}}