Integrate the timeBuzzer API with the Python API

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

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Popular Ways to Connect timeBuzzer with Python#

Run Python Code with Python API on New Activity (Instant) from timeBuzzer API

timeBuzzer + Python

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Popular timeBuzzer and Python Triggers#

New Activity (Instant) from the timeBuzzer API

Emit new event whenever a new activity is logged in Timebuzzer. See the documentation

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Popular timeBuzzer and Python Actions#

Create Activity with the timeBuzzer API

Generates a new activity in Timebuzzer. See the documentation

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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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List Activities with the timeBuzzer API

Retrieves a list of all activities in Timebuzzer. See the documentation

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Update Activity with the timeBuzzer API

Modifies an existing activity in Timebuzzer. See the documentation

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Overview of timeBuzzer#

The timeBuzzer API enables you to track, manage, and analyze time spent across various projects and tasks, directly from the Pipedream platform. With this API, you can create, update, and retrieve time entries, as well as manage projects and activities. This provides a powerful way to automate your workflow, integrate with other apps, and streamline your time tracking processes.

Connect timeBuzzer#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    timebuzzer: {
      type: "app",
      app: "timebuzzer",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://my.timebuzzer.com/open-api/account/me`,
      headers: {
        "Authorization": `APIKey ${this.timebuzzer.$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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