Integrate the TimeCamp API with the Python API

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

Popular Ways to Connect TimeCamp with Python#

Run Python Code with Python API on New Task from TimeCamp API

TimeCamp + Python

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Run Python Code with Python API on New Time Entry from TimeCamp API

TimeCamp + Python

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Popular TimeCamp and Python Triggers#

New Task from the TimeCamp API

Emit new event on each created task.

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New Time Entry from the TimeCamp API

Emit new event on each created time entry.

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Popular TimeCamp and Python Actions#

Create Task with the TimeCamp API

Creates a task. See docs here

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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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Create Time Entry with the TimeCamp API

Creates a time entry. See docs here

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Overview of TimeCamp#

TimeCamp's API unlocks the potential to automate and integrate time tracking data with a myriad of services and platforms. By leveraging Pipedream's capabilities, you can create custom workflows that respond to events in TimeCamp, such as new time entries, projects, or tasks. These workflows can then trigger actions in other apps, or even process and analyze time tracking data to provide insights and streamline operations.

Connect TimeCamp#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    timecamp: {
      type: "app",
      app: "timecamp",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.timecamp.com/third_party/api/me`,
      headers: {
        "Authorization": `${this.timecamp.$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#

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}}