Integrate the Google Fit API with the Python API

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

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Popular Google Fit 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 Google Fit#

Google Fit (Developer App) provides a robust API for accessing and storing a user's health and wellness data collected from various devices and apps. With it, you can read and write different types of fitness data, such as steps, calories burned, and heart rate, enabling the development of personalized health dashboards, proactive fitness reminders, and integrative health reports. Using Pipedream, this data can be ingested and combined with other services to automate health tracking, set goals, and even inform healthcare providers or coaching systems of a user's progress.

Connect Google Fit#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    google_fit_developer_app: {
      type: "app",
      app: "google_fit_developer_app",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.googleapis.com/oauth2/v1/userinfo`,
      headers: {
        Authorization: `Bearer ${this.google_fit_developer_app.$auth.oauth_access_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}}

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