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Python

Integrate the API Sports API with the Python API

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

Popular API Sports 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.

Try it

Overview of API Sports#

The API Sports API is a robust data source offering detailed information on numerous sports, leagues, teams, and players. It provides real-time scores, stats, standings, and historical data, making it a treasure trove for sports enthusiasts, fantasy league managers, and sports analysts. On Pipedream, you can leverage this API to create serverless workflows that respond to various sports events and data updates. Combine it with other apps to craft automated processes, notifications, and data analysis pipelines that enrich your application or feed your sports data obsession.

Connect API Sports#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    api_sports: {
      type: "app",
      app: "api_sports",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.api_sports.$auth.api_name}.api-sports.io/countries`,
      headers: {
        "x-apisports-key": `${this.api_sports.$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}}