Integrate the Timely Time Tracking API with the Python API

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

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Popular Timely Time Tracking 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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Overview of Timely Time Tracking#

The Timely Time Tracking API lets you automate your time tracking, reporting, and project management tasks. With Pipedream, you can connect the API to create custom workflows that fit your needs without managing infrastructure. You can streamline time entries, sync project data, and trigger actions based on time tracked. Using Pipedream's serverless platform, you can execute code that interacts with Timely's data on a schedule, or in response to HTTP requests or events from other apps.

Connect Timely Time Tracking#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    timely_time_tracking: {
      type: "app",
      app: "timely_time_tracking",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.timelyapp.com/1.1/accounts`,
      headers: {
        Authorization: `Bearer ${this.timely_time_tracking.$auth.oauth_access_token}`,
        "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#

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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